**2. The Landscape Evolution Observatory large-scale controllable infrastructure to study coupled Earth-surface processes**

#### **2.1. The model landscapes, their atmosphere, and associated infrastructure**

communities that inhabit them, and their water, biogeochemical, and energy cycles, (ii) determining whether simple or complex biological communities, weathering patterns, and flow networks arise as a consequence of differing climate regimes, (iii) understanding how point- to plot-scale processes impact integrated fluxes of mass and energy at the whole-landscape level, (iv) assessing whether knowledge of how and why multiscale heterogeneity in landscape structure forms can enable improved prediction of landscape function under change, and whether existing or new predictive tools are required, and (v) determining whether our present knowledge and observational capacity allow closing the balances of mass and energy at the landscape scale.

28 Hydrology of Artificial and Controlled Experiments

The controlled experimentation and dense observations at LEO are combined with mathematical modeling to effectively advance our understanding of landscape evolution and its effects on mass and energy cycling between the landscapes and their overlying atmospheres. Modeling is used to help formalize newly gained process knowledge, infer aspects of the system that are difficult to measure, refine the experimental and instrumental design, and generate cross-disciplinary hypotheses that can be tested in the experiments. Specifically, we are using a "learning cycle" approach in which models are used to predict system response before an experiment is performed, and subsequent targeted experiments are used to improve the models' accuracy. Modeling efforts at LEO focus specifically on (i) integrating existing community model representations of hydro-biogeochemical and ecological processes into a coupled modeling framework and (ii) representing landscape behavior over a wide spectrum of elementary scales, ranging from highly resolved small-scale parameterizations to whole-hillslope integrations. Ultimately, model development provides us with the opportunity to transpose the knowledge gained through the LEO experiment into natural environments and therefore forms a critical

basis to improving the accuracy of forecasts of landscape change in the real world.

LEO was fundamentally designed as a community resource to effectively meet targets of scientific merit and broader impact. Acknowledging the complexity of the project and maximizing its use for the Earth sciences and general public, the LEO project seeks to (i) facilitate open and real-time availability of sensor network data, (ii) provide a framework for community collaboration and facility access that includes integration of new or comparative measurement capabilities into existing facility cyber-infrastructure, (iii) foster a community-guided approach to science planning, and (iv) develop novel education and outreach programs. This strategy has already proven successful in informing the landscapes' design and first climate experiments, as well as in informing the public through numerous general media publications, the more than 1000 site visitors per year and hundreds of students trained in Earth sciences.

This book chapter provides a detailed overview of the Landscape Evolution Observatory project. We first present the LEO large-scale controllable research infrastructure, its instrumentation and support facilities, and the integrated modeling framework being developed in feedback with experiments. We then describe LEO's combined capabilities to track important mass and energy balances as well as changes in physicochemical landscape structure and biological communities. This is followed by a discussion of LEO's potential to serve as an experimental platform to study interactions between hydrological, biogeochemical, microbiological, plant-ecological, and geomorphological processes associated with incipient hillslope coevolution. Characterizing those interactions is critical for the advancement of hydrologic and coupled-process models at LEO, which are also discussed. We conclude by summarizing The Landscape Evolution Observatory (LEO) is comprised of three model landscapes that were designed and constructed to be exact replicas of each other and to contain landscape features emblematic of upland zero-order basins (hereafter ZOBs). The model ZOBs are contained within steel structures oriented parallel to one another within three adjacent, enclosed bays along the western extent of the University of Arizona—Biosphere 2 facility (**Figure 1**). Individually, the bays include more than 596 m2 of floor space. The total volume of air that interacts with the landscapes is 12,956 m3 , including 10,712 m<sup>3</sup> within the bays where the model ZOBs are located and 2244 m3 within the underlying basement where air passes before recirculating to the bay above. The steel structures are generally shaped like rectangular trays, with an average slope of 10° and a southerly aspect. Their interior length and width are 30 m and 11 m, respectively (**Figure 2**). The base of the interior volume of the trays is formed by concrete board, secured to steel slats, and mounted atop structural steel beams. That base is not planar but contains an 18-m long depression that is deepest at the downslope extent of the steel trays and diminishes in depth as it expands upslope. The sidewalls of the trays are all built vertically. The whole interior surface area of the trays was coated with an epoxy primer, which was covered with an elastomeric membrane, then an aggregate-filled urethane coating. At 144 locations along the base of the tray, holes were drilled to allow passage of sensor cables. A length of acrylic tubing

**Figure 1.** The Landscape Evolution Observatory is housed in adjacent bays within the Biosphere 2 facility (a) and comprises three replicate model landscapes (b) embedded into elaborate steel structures (c).

was fitted inside a bulkhead fitting that was sealed into the hole. After final passage of sensor cables through these tubing lengths, they were sealed at their bottom end using expanding foam insulation and epoxy. The base and three of the interior walls of the steel trays are thus impermeable to water. The wall at the downslope extent of the trays was designed to allow water seepage out of the model landscapes. Steel supports and a lattice of steel slats form the primary retention structure of the downslope wall. Porous plastic sheeting was secured to that lattice, which allows water to readily seep out of the landscapes and into six partitioned

Controlled Experiments of Hillslope Coevolution at the Biosphere 2 Landscape Evolution…

http://dx.doi.org/10.5772/intechopen.72325

The interior volume of the steel structures was filled with crushed basaltic tephra, which comprises the original "parent material" of the model ZOBs. The material was mined from a subterranean deposit of basaltic tephra associated with Merriam Crater in northern Arizona. The mining company was contracted to crush the original rock material down to a loamysand texture. The average particle size distribution and elemental composition of the material were reported in [10]. The average sand (50–2000 μm), silt (2–50 μm), and clay (<2 μm) particle-size fractions are 84.6, 12.2, and 3.2%, respectively. The material contains exceptionally low amounts of organic carbon and nitrogen, which was desirable because the target initial condition was a landscape that was effectively abiotic and as spatially homogenous as could be achieved. The loamy sand was hauled from the mining site to LEO and eventually installed within the steel trays by conveyor belt and through manual dispersal and packing by workers. The packing procedure involved incremental installation of four discrete soil layers, each 0.32-m thick when filled into the tray and subsequently compacted to a thickness of 0.25 m. The final bulk density of the packed soil is 1.59 g cm−3, and the porosity is 39% on average. Groundbased laser scans were performed after the installation of each layer, to ensure the greatest possible homogeneity of packing density among individual layers, and across the three rep

licate model landscapes. The final soil depth on each landscape is, on average, approximately 1 m throughout, though with spatial variability (see Figure 3 in [10]). Because of the designed shape of the underlying steel structure, the ZOBs' surfaces have convergent topography. A primary zone of convergence, or trough, lies near the center of the ZOBs and extends upslope approximately 18 m (**Figure 2**). At that point, the primary zone of convergence terminates at the base of a planar hillslope section that spans to the upslope extend of the ZOBs. Two smaller troughs emanate from this termination point and span toward the upslope corners of the model landscapes. This topographic signature is similar to that observed across many ZOBs in nature [11]. Though the model ZOBs have an average slope of 10°, maximum slopes of approximately 17° exist at that transition from hillslope segments to the primary zone of convergence. The soil should not ever be disturbed by foot traffic or any other source other than natural erosive pro

cesses. To accomplish that goal, a personnel transport system was designed and constructed on each landscape (**Figure 3a**). The system allows workers to travel within a railed cart to any point on the soil surface without ever stepping on the surface. This capability is imperative for pointscale measurements of soil and vegetation properties integral to the long-term research agenda.

Irrigation rates of less than 3 mm h−1 to approximately 40 mm h−1 may be applied individually to each landscape via the engineered irrigation system. In the basement below the landscapes, there are seven storage tanks, each with 8037-liter storage capacity (**Figure 3e**). The tanks are filled with water that is pumped from a local well and passes through a reverse-osmosis


31


drainage basins immediately bordering the downslope extent of the landscapes.

was fitted inside a bulkhead fitting that was sealed into the hole. After final passage of sensor cables through these tubing lengths, they were sealed at their bottom end using expanding foam insulation and epoxy. The base and three of the interior walls of the steel trays are thus impermeable to water. The wall at the downslope extent of the trays was designed to allow water seepage out of the model landscapes. Steel supports and a lattice of steel slats form the primary retention structure of the downslope wall. Porous plastic sheeting was secured to that lattice, which allows water to readily seep out of the landscapes and into six partitioned drainage basins immediately bordering the downslope extent of the landscapes.

The interior volume of the steel structures was filled with crushed basaltic tephra, which comprises the original "parent material" of the model ZOBs. The material was mined from a subterranean deposit of basaltic tephra associated with Merriam Crater in northern Arizona. The mining company was contracted to crush the original rock material down to a loamysand texture. The average particle size distribution and elemental composition of the material were reported in [10]. The average sand (50–2000 μm), silt (2–50 μm), and clay (<2 μm) particle-size fractions are 84.6, 12.2, and 3.2%, respectively. The material contains exceptionally low amounts of organic carbon and nitrogen, which was desirable because the target initial condition was a landscape that was effectively abiotic and as spatially homogenous as could be achieved. The loamy sand was hauled from the mining site to LEO and eventually installed within the steel trays by conveyor belt and through manual dispersal and packing by workers. The packing procedure involved incremental installation of four discrete soil layers, each 0.32-m thick when filled into the tray and subsequently compacted to a thickness of 0.25 m. The final bulk density of the packed soil is 1.59 g cm−3, and the porosity is 39% on average. Groundbased laser scans were performed after the installation of each layer, to ensure the greatest possible homogeneity of packing density among individual layers, and across the three replicate model landscapes. The final soil depth on each landscape is, on average, approximately 1 m throughout, though with spatial variability (see Figure 3 in [10]). Because of the designed shape of the underlying steel structure, the ZOBs' surfaces have convergent topography. A primary zone of convergence, or trough, lies near the center of the ZOBs and extends upslope approximately 18 m (**Figure 2**). At that point, the primary zone of convergence terminates at the base of a planar hillslope section that spans to the upslope extend of the ZOBs. Two smaller troughs emanate from this termination point and span toward the upslope corners of the model landscapes. This topographic signature is similar to that observed across many ZOBs in nature [11]. Though the model ZOBs have an average slope of 10°, maximum slopes of approximately 17° exist at that transition from hillslope segments to the primary zone of convergence. The soil should not ever be disturbed by foot traffic or any other source other than natural erosive processes. To accomplish that goal, a personnel transport system was designed and constructed on each landscape (**Figure 3a**). The system allows workers to travel within a railed cart to any point on the soil surface without ever stepping on the surface. This capability is imperative for pointscale measurements of soil and vegetation properties integral to the long-term research agenda.

Irrigation rates of less than 3 mm h−1 to approximately 40 mm h−1 may be applied individually to each landscape via the engineered irrigation system. In the basement below the landscapes, there are seven storage tanks, each with 8037-liter storage capacity (**Figure 3e**). The tanks are filled with water that is pumped from a local well and passes through a reverse-osmosis

**Figure 2.**

Diagram showing the orientation of the sensor and sampler network in and above the LEO landscapes. The left-most panel shows the approximate lateral (*xy*coordinate plane) locations of instrumentation aboveground, where sensors are installed at one specific (CSAT-3, CNR4) or five different (all other sensors) heights along

30 Hydrology of Artificial and Controlled Experiments

vertical aluminum masts. Each of the five remaining panels shows the lateral locations of belowground instrumentation at one specific depth (*z*-coordinate) below the soil

surface. Note that CS-451 pressure transducers are actually installed within the structural base of the landscapes at 1-m soil depth, and ERT electrode stacks extend over

multiple depths. Dashed gray lines indicate the axes of slope convergence zones.

(**Figures 2** and **3a**) to an approximate distance of 0.15 m from the soil surface. The masts serve as attachment structures for meteorological instruments that monitor the LEO atmosphere (described in Section 2.1.1). The bottom segment of each mast is telescopic and may be raised to variable heights above the soil surface to accommodate future vegetation growth. A hinged mount connects the masts to the space frame, allowing the masts to be rotated upward to the point of being nearly parallel with the space frame. That action is controlled by motorized winches and braided metal cable that passes through a series of pulleys mounted to the space frame and attaches to the masts at two locations along their length. In this way, the masts can be raised high enough to allow passage of the personnel transport system and to avoid any accumulation and dripping of water during irrigation events, without ever having to remove or rewire any of the meteorological instruments. Air circulation over the landscapes is driven by three air-handler units located in the basement of each bay. These units pull air from a vertical duct that connects the basement and landscape level along the southern extent of the bay. The units push air from south to north through the basement, then vertically through a similar duct on the northern extent of the bay. The air then circulates predominantly from upslope to downslope over the surface of the landscapes. These air handlers are capable of producing maximum air velocities exceeding 1 m s−1 over the landscape surfaces—with air velocity being greater near the soil surface and lesser toward the space frame. Additional portable fans can be installed at any time, and at varying locations within the bay, to create greater velocities or turbulence as needed. Coiled radiators within the air-handling units allow circulation of heated or cooled water for temperature and humidity control. These systems are operated through proportional-integral-derivative (PID) controllers, enabling real-time manipulation of air velocities, temperature, and humidity, within some operational constraints. The air space immediately surrounding each landscape is isolated from that in adjacent bays by air partitioning structures consisting of aluminum-pipe framing and twin-wall polycarbonate plastic sheeting mounted to the frame. The air space of each bay is also isolated within the underlying basement by wood-framed walls composed of either plastic sheeting or regular sheetrock. In addition to the three full-scale model landscapes, a much smaller version of a LEO landscape was built within the central bay of LEO. This scaled-down model, referred to as the miniLEO, was designed as a rectangular cuboid with length of 2 m, width of 0.5 m, uniform soil depth of 1 m, and a 10° slope [14, 15]. Its construction otherwise resembles that of the fullscale models, and it is filled with the same basaltic tephra and equipped with equivalent basic instrumentation, including an irrigation system. The miniLEO is typically used for shorter term experimentation, and destructive soil sampling and complete soil excavations are possible. The primary purpose of the miniLEO is to evaluate measurement and interpretation techniques, optimize experiments (e.g., irrigation sequences), and test specific hypotheses with comparatively low cost and risk before extensive large-scale experiments are launched.

Controlled Experiments of Hillslope Coevolution at the Biosphere 2 Landscape Evolution…

http://dx.doi.org/10.5772/intechopen.72325

33

*2.1.1. The network of automated, electronic sensors operating at LEO*

Here, we outline the array of automated, electronic sensors that are installed in, on, or around the model ZOBs and the measurement capabilities they provide (**Figures 2** and **3**). Other manual sensing and sampling devices utilized within LEO are described in subsequent sections (e.g., an electrical-resistivity tomography system, soil solution, and soil gas sampling). All instruments

**Figure 3.** Selected elements of the extensive instrumentation array at LEO: Atmospheric sensors along vertical masts, and personnel transport system in the background (a); high-resolution imaging system mounted to track system (b); multivalves for subsurface gas sampling (c); vacuum box with 55 sample vials for automated collection of soil solution from pore water samplers (d); reverse osmosis system and tanks storing irrigation water (e); sprinkler system for applying irrigation water (f); tipping buckets and flow meters for measuring discharge from six discrete lateral sections of the seepage face (g); 1 of 10 load cells per LEO hillslope measuring changes in total landscape mass.

purification system before storage. The tanks are plumbed such that water can be drawn from any individual tank, or from any combination of tanks, controlled through simple valve selections. Three water pumps deliver water to the landscape level. Here again, the plumbing was installed so that any pump may deliver water to any particular landscape at any time, which provides maximum operational flexibility. At the landscape level, there are five independent plumbing circuits that the water may be delivered to. Each circuit is opened and closed by a programmable valve. Each plumbing circuit dispenses through a unique combination of sprinkler heads (MP Rotator, Hunter Industries, San Marcos, CA, USA) that are located on risers resting approximately 3.3 m above the soil surface (**Figures 1b** and **3f**). There are seven such risers mounted on both the west and east edges of the steel structures containing the model ZOBs. Irrigation water may be dispensed onto the landscapes through any circuit individually or through any combination of the circuits. The spatial homogeneity of applied irrigation varies among the circuits. In general, spatial variability is greatest at low irrigation rates (coefficient of variation, CV > 0.5) and becomes more homogenous at high irrigation rates (CV ≈ 0.2). Disdrometer measurements show that the distribution of water-drop velocities created by the irrigation system approach realistic values of terminal velocity for naturally occurring precipitation. The drop sizes are somewhat smaller than real precipitation [10].

Each bay is enclosed by space frame construction. The exterior of the space frame is covered with 0.011-m thick duo-laminated glass with an interior Mylar sheet. Total solar radiation transmission through the glass is 50–60%, with less than 1% of ultra-violet radiation transmission. The glass is cleaned intermittently. Information about specific transmissions of different wavelengths of radiation was published previously [12, 13]. The space frame directly above the model ZOBs is arranged in three tiers. At the downslope extent, the space frame is approximately 9 m above the soil surface. Across the upper portions of the landscape, the distance to the overlying space frame is greater than 10 m above the surface. At five locations over the landscapes, aluminum masts hang vertically from attachment points on the space frame (**Figures 2** and **3a**) to an approximate distance of 0.15 m from the soil surface. The masts serve as attachment structures for meteorological instruments that monitor the LEO atmosphere (described in Section 2.1.1). The bottom segment of each mast is telescopic and may be raised to variable heights above the soil surface to accommodate future vegetation growth. A hinged mount connects the masts to the space frame, allowing the masts to be rotated upward to the point of being nearly parallel with the space frame. That action is controlled by motorized winches and braided metal cable that passes through a series of pulleys mounted to the space frame and attaches to the masts at two locations along their length. In this way, the masts can be raised high enough to allow passage of the personnel transport system and to avoid any accumulation and dripping of water during irrigation events, without ever having to remove or rewire any of the meteorological instruments. Air circulation over the landscapes is driven by three air-handler units located in the basement of each bay. These units pull air from a vertical duct that connects the basement and landscape level along the southern extent of the bay. The units push air from south to north through the basement, then vertically through a similar duct on the northern extent of the bay. The air then circulates predominantly from upslope to downslope over the surface of the landscapes. These air handlers are capable of producing maximum air velocities exceeding 1 m s−1 over the landscape surfaces—with air velocity being greater near the soil surface and lesser toward the space frame. Additional portable fans can be installed at any time, and at varying locations within the bay, to create greater velocities or turbulence as needed. Coiled radiators within the air-handling units allow circulation of heated or cooled water for temperature and humidity control. These systems are operated through proportional-integral-derivative (PID) controllers, enabling real-time manipulation of air velocities, temperature, and humidity, within some operational constraints. The air space immediately surrounding each landscape is isolated from that in adjacent bays by air partitioning structures consisting of aluminum-pipe framing and twin-wall polycarbonate plastic sheeting mounted to the frame. The air space of each bay is also isolated within the underlying basement by wood-framed walls composed of either plastic sheeting or regular sheetrock.

In addition to the three full-scale model landscapes, a much smaller version of a LEO landscape was built within the central bay of LEO. This scaled-down model, referred to as the miniLEO, was designed as a rectangular cuboid with length of 2 m, width of 0.5 m, uniform soil depth of 1 m, and a 10° slope [14, 15]. Its construction otherwise resembles that of the fullscale models, and it is filled with the same basaltic tephra and equipped with equivalent basic instrumentation, including an irrigation system. The miniLEO is typically used for shorter term experimentation, and destructive soil sampling and complete soil excavations are possible. The primary purpose of the miniLEO is to evaluate measurement and interpretation techniques, optimize experiments (e.g., irrigation sequences), and test specific hypotheses with comparatively low cost and risk before extensive large-scale experiments are launched.

#### *2.1.1. The network of automated, electronic sensors operating at LEO*

purification system before storage. The tanks are plumbed such that water can be drawn from any individual tank, or from any combination of tanks, controlled through simple valve selections. Three water pumps deliver water to the landscape level. Here again, the plumbing was installed so that any pump may deliver water to any particular landscape at any time, which provides maximum operational flexibility. At the landscape level, there are five independent plumbing circuits that the water may be delivered to. Each circuit is opened and closed by a programmable valve. Each plumbing circuit dispenses through a unique combination of sprinkler heads (MP Rotator, Hunter Industries, San Marcos, CA, USA) that are located on risers resting approximately 3.3 m above the soil surface (**Figures 1b** and **3f**). There are seven such risers mounted on both the west and east edges of the steel structures containing the model ZOBs. Irrigation water may be dispensed onto the landscapes through any circuit individually or through any combination of the circuits. The spatial homogeneity of applied irrigation varies among the circuits. In general, spatial variability is greatest at low irrigation rates (coefficient of variation, CV > 0.5) and becomes more homogenous at high irrigation rates (CV ≈ 0.2). Disdrometer measurements show that the distribution of water-drop velocities created by the irrigation system approach realistic values of terminal velocity for naturally occurring precipitation. The drop sizes are somewhat smaller than real precipitation [10].

of the seepage face (g); 1 of 10 load cells per LEO hillslope measuring changes in total landscape mass.

32 Hydrology of Artificial and Controlled Experiments

**Figure 3.** Selected elements of the extensive instrumentation array at LEO: Atmospheric sensors along vertical masts, and personnel transport system in the background (a); high-resolution imaging system mounted to track system (b); multivalves for subsurface gas sampling (c); vacuum box with 55 sample vials for automated collection of soil solution from pore water samplers (d); reverse osmosis system and tanks storing irrigation water (e); sprinkler system for applying irrigation water (f); tipping buckets and flow meters for measuring discharge from six discrete lateral sections

Each bay is enclosed by space frame construction. The exterior of the space frame is covered with 0.011-m thick duo-laminated glass with an interior Mylar sheet. Total solar radiation transmission through the glass is 50–60%, with less than 1% of ultra-violet radiation transmission. The glass is cleaned intermittently. Information about specific transmissions of different wavelengths of radiation was published previously [12, 13]. The space frame directly above the model ZOBs is arranged in three tiers. At the downslope extent, the space frame is approximately 9 m above the soil surface. Across the upper portions of the landscape, the distance to the overlying space frame is greater than 10 m above the surface. At five locations over the landscapes, aluminum masts hang vertically from attachment points on the space frame

Here, we outline the array of automated, electronic sensors that are installed in, on, or around the model ZOBs and the measurement capabilities they provide (**Figures 2** and **3**). Other manual sensing and sampling devices utilized within LEO are described in subsequent sections (e.g., an electrical-resistivity tomography system, soil solution, and soil gas sampling). All instruments described here are connected to a network of Compact Reconfigurable Input-Output devices (CRIOs; National Instruments Corp, Austin, TX, USA), ultimately with data transmission and storage to two onsite servers. Unless otherwise stated, data from each instrument are recorded at 15-min intervals, although this recording interval can be readily adjusted as needed. The instruments and quantities listed below are replicated on each of the three model ZOBs.

calibration of the sensors was performed by the manufacturer, using the LEO soil, which

*] Sensors*—Based on Vaisala's CARBOCAP technology, these sen-

Controlled Experiments of Hillslope Coevolution at the Biosphere 2 Landscape Evolution…

http://dx.doi.org/10.5772/intechopen.72325

35

] within air in the soil pore space. They are buried at 48 loca-

• *496 Decagon MPS-2 Soil Water Potential Sensors*—These sensors also measure dielectric permittivity of an attached, wetted ceramic disc that is in equilibrium with soil water. Based on a calibrated relationship between permittivity and water content of the disc, they report soil water pressure across a range from −6 to −500 kPa. The manufacturer-stated accuracy

• *15 Campbell Scientific CS-451 Vented Pressure Transducers*—These vented pressure transducers record gauge pressure. They are installed within sealed bulkhead fittings with compression caps at 15 locations along the base of the steel structure. The portion of the bulkhead fitting exposed to soil on the interior of the steel structure is screened to allow water intrusion, but not soil. These transducers measure pressure heads of 0 to 2 m and allow monitor-

• *10 Honeywell Model 3130 Load Cells*—These loads cells were installed at a nexus point between the primary vertical supports and the lateral beams forming the perimeter of the steel trays. Collectively, the 10 load cells enable accurate and precise measurements of changes in total-landscape mass (due to additions or losses of water). The manufacturer-

• *6 SeaMetrics PE102 Flow Meters*—Groundwater seepage from the landscapes flows into one of six partitioned troughs at the downslope extent and then through tubing that leads to these meters. The manufacturer-reported accuracy is 1% relative error across flow rates of

• *6 NovaLynx 26-2501-A Tipping Bucket Gauges*—After passing through the flow meters, the seepage water then flows into one of these tipping bucket gauges. They are calibrated onsite multiple times per year. These provide superior accuracy at very low flow rates com-

Sampling of soil solution is facilitated through 496 suction cup pore water samplers (Super Quartz, Prenart Equipment, Frederiksberg, Denmark; pore size <2 μm) that are embedded in each of the LEO hillslopes. The pore water samplers are co-located with the moisture and matric potential sensors (**Figure 2**). Each sampler is connected via a PTFE sampling line to one of 11 custom vacuum sampling modules distributed across the base structure of each hillslope (**Figure 3d**). Each sampling line is equipped with an individual shut-off valve. The modules consist of a Plexiglas vacuum box equipped with a manual pressure regulator, a vacuum gauge,

*2.1.2. Collection and analysis of soil solution, rainfall, and discharge samples*

enables estimates of volumetric water content with accuracy of ±0.025 or better.

is ±25% of reading.

• *48 Vaisala GMM222 [CO2*

sors are able to measure [CO<sup>2</sup>

tions within each model ZOB.

Other instruments installed external to the landscapes include:

ing of the spatial dynamics of water table height.

reported repeatability is 0.05% of full scale.

0.11–11.4 liters per minute.

pared to the flow meters.

Aboveground instrumentation includes:


Instruments installed within the subsurface of the model ZOBs include:


calibration of the sensors was performed by the manufacturer, using the LEO soil, which enables estimates of volumetric water content with accuracy of ±0.025 or better.


Other instruments installed external to the landscapes include:

described here are connected to a network of Compact Reconfigurable Input-Output devices (CRIOs; National Instruments Corp, Austin, TX, USA), ultimately with data transmission and storage to two onsite servers. Unless otherwise stated, data from each instrument are recorded at 15-min intervals, although this recording interval can be readily adjusted as needed. The instruments and quantities listed below are replicated on each of the three model ZOBs.

• *2 Kipp and Zonen CNR4 4-Way Radiometers*—These instruments are mounted at 2-m height above the soil surface on the masts overlying the east- and west-facing hillslope facets adjacent to the central convergence area. Separate radiometers record incoming and outgoing short- and long-wave radiation. The spectral range of measurements provided by the set of radiometers is 300–2800 μm and 4500–42,000 μm. The paired instruments allow comparison of all radiation components on portions of the model ZOBs with different slope aspect.

• *1 Campbell Scientific CSAT-3 Sonic Anemometer*—The instrument is mounted at 2-m height on the mast overhanging the centermost location of the ZOB and oriented upslope. The instrument measures the three-dimensional air-velocity field in high temporal resolution. The instrument is co-located with gas-intake tubing that is routed to an infra-red gas analyzer housed underneath the centermost model ZOB. The sonic anemometer records data

• *24 Davis Cup Anemometers*—These instruments are located at up to 5 heights along each mast: 0.25, 1, 3, 6, and 10 m above soil surface. No instruments are available at the maximum height at the most downslope mast position, due to the closer proximity of the space frame. They measure wind speed and direction, with an initiation speed of approximately 1.3 m s−1.

• *24 Vaisala HMP60 Temperature and Humidity Sensors*—These instruments are located at the same heights on all masts and measure air temperature and relative humidity within the

• *24 Apogee Instruments Quantum Sensors*—These sensors are also co-located with others on the masts. They measure photon-flux density within wavelengths spanning 410–655 nm.

• *24 Huskeflux HPF-1 and HPF-1SC Soil-Heat-Flux Plates*—These instruments are located as 12 pairs, individual sensors within pairs spaced at 1 m, and broader spacing between pairs. They are thermopiles that measure conductive heat transport into the soil profile. They are buried at 0.05-m depth, with an accompanying thermocouple buried at 0.025-m depth, and co-located with soil water content sensors. Actual conductive heat transport into the soil is estimated based on an algorithm provided by the sensor manufacturer, which considers

• *496 Decagon 5TM Soil Water Content and Temperature Sensors*—These sensors measure the dielectric permittivity of wetted soil and convert to volumetric water content using a calibration equation. They also measure temperature with an installed thermistor. A soil-specific

Aboveground instrumentation includes:

34 Hydrology of Artificial and Controlled Experiments

at a frequency of 60 Hz.

ranges −40 to 60°C and 0 to 100%, respectively.

Instruments installed within the subsurface of the model ZOBs include:

the water content-dependent heat capacity of the soil-water-air mixture.


#### *2.1.2. Collection and analysis of soil solution, rainfall, and discharge samples*

Sampling of soil solution is facilitated through 496 suction cup pore water samplers (Super Quartz, Prenart Equipment, Frederiksberg, Denmark; pore size <2 μm) that are embedded in each of the LEO hillslopes. The pore water samplers are co-located with the moisture and matric potential sensors (**Figure 2**). Each sampler is connected via a PTFE sampling line to one of 11 custom vacuum sampling modules distributed across the base structure of each hillslope (**Figure 3d**). Each sampling line is equipped with an individual shut-off valve. The modules consist of a Plexiglas vacuum box equipped with a manual pressure regulator, a vacuum gauge, and a tray capable of holding 55 centrifuge tubes of 50 mL volume for sample collection. Each module is connected to a vacuum manifold. Vacuum is supplied by a total of two single-stage rotary vane vacuum pumps (Model RC0100, Busch LLC, Virginia Beach, VA, USA) located outside of the LEO domain. The vacuum system allows simultaneous sample collection from all 496 samplers on each slope. However, when needed, vacuum application and sampling can be limited to any subset of modules or even any subset of individual samplers. This allows adapting the timing of sampling to in-slope processes, e.g., to the progression of a wetting front. Furthermore, the suction to be used in each module can be adjusted to matric potential recorded by the sensors co-located with solution samplers to ensure that adequate suction is applied to obtain a sufficient sample volume while avoiding excessive draw beyond the immediate vicinity of the samplers. In addition to soil solution sampling, water samples from the seven common irrigation tanks and from two to four custom precipitation collectors per hillslope are collected manually during irrigation events. Finally, custom-built, Arduino-based autosamplers for discrete sample collection at set intervals are in place to collect water samples from the outflow at the base of each hillslope (seepage flow and potentially overland flow) when it is generated.

and oxygen (δ<sup>18</sup>O–H<sup>2</sup>

CO<sup>2</sup>

ously and simultaneously the δ<sup>2</sup>

isotope composition of CO<sup>2</sup>

water vapor as well as the carbon (δ<sup>13</sup>C–CO<sup>2</sup>

O; 1*σ* < 0.05%) isotope composition of water vapor [16]. The second

Controlled Experiments of Hillslope Coevolution at the Biosphere 2 Landscape Evolution…

; 1*σ* < 0.03%) and oxygen (δ<sup>18</sup>O–CO<sup>2</sup>

[17]. The third instrument is a carbonyl sulfide (COS) monitor

O (1*σ* < 0.03%) composition of

http://dx.doi.org/10.5772/intechopen.72325

; 1*σ* < 0.03%)

37

instrument is a dual quantum cascade laser absorption spectrometer (QCLAS; TILDAS-D, Aerodyne Research Inc., Billerica, MA, USA) with two tunable lasers to measure continu-

(mini QCLAS, Aerodyne Research Inc.) for continuous high-sensitivity (1*σ* < 2 pptv) trace gas analysis. Finally, a bench-top differential infrared gas analyzer (LI-7000; LI-COR Biosciences, Lincoln, NE, USA) is available for simultaneous high-speed measurements of water vapor and

A multisource liquid sampling system was devised for high-frequency sampling and realtime analysis of seepage water outflow from the three LEO ZOBs utilizing the OA-ICOS instrument. The sampling system uses a four-channel peristaltic pump (Minipuls 3, Gilson Inc., Middleton, WI, USA) to continuously deliver liquid water from a given source to one of four ports of a stainless-steel sampling manifold that is mounted on the tray-holder of an autosampler (LC PAL, CTC Analytics AG, Zwingen, Switzerland) for liquid injection into a vaporization unit and subsequent vapor delivery into the isotope analyzer. This setup delivers robust performance [22] and facilitates water isotopologue analysis of outflow from each LEO landscape at approximately 30-min intervals. To obtain an even higher temporal resolution of discharge isotope composition, as well as for complementary analysis of irrigation, discharge, and soil solution samples, the OA-ICOS instrument and autosampler setup can be

Gas sampling is performed in the atmospheres and subsurface soil of each LEO landscape utilizing extensive valving and probing arrays that can be simultaneously linked to the dual-QCLAS, COS, and benchtop gas analyzers. Twenty-four air intake lines, with sheltered inlets at four to five different heights along each of the five masts distributed over each slope surface (Section 2.1; **Figures 2** and **3a**), are available for atmospheric gas sampling. Subsequent sample intake from each of the lines is facilitated by three stream selector valves (VICI Valco Instruments Inc., Houston, TX, USA) situated at the central onsite laboratory, with flow driven by a downstream vacuum pump. To eliminate temporal delay associated with sample gas transport from air inlet to analyzer, the intake line sections upstream of the valves can be constantly purged with fresh atmospheric air using branch-off lines connected to a purge pump via custom vacuum manifolds. To extract air samples from the subsurface, 141 custom soil gas samplers installed in a uniform grid at multiple soil depths are available within each of the model landscapes (**Figure 2**). The samplers were constructed from microporous, hydrophobic PTFE tubing sealed at both ends to gas transport lines with epoxy and heat shrink tubing. A multilevel conveyance system, comprising 27 sub-level stream selector valves mounted at varied locations across the landscapes' structural bases (**Figure 3c**), three main-level selector valves (VICI Valco Instruments Inc.), and several digital mass flow and pressure controllers (Alicat Scientific, Tucson, AZ, USA), allows for automated sampling from the dense probe network according to programmed sequences. The best achievable sample

 concentrations. Details on the respective technologies can be found elsewhere [18–21]. The gas analyzers are interfaced with sophisticated sample conveyance and control systems utilizing custom LabView (National Instruments Corp.) software for automated in-situ moni-

O (1*σ* < 0.1%) and δ<sup>18</sup>O–H<sup>2</sup>

H–H2

toring of liquid and gas compositions across the LEO domains.

used to analyze collected water samples (Section 2.1.2) offline.

All collected water samples are archived in freezers at a temperature of −9°C. Biogeochemical sample analysis is performed in an onsite analytical laboratory and can be complemented by isotopic analysis in the isotope and trace gas facility (Section 2.1.3). Prior to analysis samples are centrifuged at 4816 relative centrifugal force for 20 min to remove particulates (Sorvall Legend XTR, Thermo Fisher Scientific Inc., Waltham, MA, USA). The analytical lab is equipped with a Dionex ICS 5000 ion chromatography system (Thermo Fisher Scientific Inc.) with two conductivity detectors for high throughput and concurrent sample analysis for major anions and cations. Further capabilities include solution analysis for dissolved organic and inorganic carbon and total dissolved nitrogen (TOC-L Series total organic carbon and nitrogen analyzer, equipped with TOC-LCSH autosampler; all Shimadzu, Kyoto, Japan), as well as for pH and electrical conductivity (sympHony multimeter, VWR International, Radnor, PA, USA). In addition, selected samples are analyzed offsite for major, trace, and rare earth elements using inductively coupled plasma mass spectrometry (Elan DRC-II, Perkin Elmer, Waltham, MA, USA). Characterization of organic compounds in collected solutions is performed at the Environmental Molecular Sciences Laboratory (Richland, WA, USA) using Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS).

#### *2.1.3. Stable isotope and trace gas monitoring*

Analysis of the concentration and/or stable isotope composition of key molecular species across the hydrologically and biogeochemically relevant landscape compartments (soil, atmosphere, and outflow) of LEO is facilitated by extensive onsite equipment arrays, encompassing state-of-the-art probing interfaces and analyzing instruments. All central equipment is housed in a custom laboratory facility constructed below the central LEO landscape structure. To facilitate stable and gap-free operation of sensitive instrumentation onsite, the laboratory was equipped with uninterrupted power supply, air-conditioning, and zero air (i.e., air that is free of water, CO<sup>2</sup> , and contaminants) supply from a lab generator (Aadco Instruments Inc., Cleves, OH, USA), utilizing compressed facility air via a 60-gal in-line back-up reservoir. The facility currently houses four laser-based gas analyzers. The first instrument is an offaxis integrated cavity output spectrometer (OA-ICOS; IWA-35EP, Los Gatos Research Inc., Mountain View, CA. USA) for continuous measurement of the hydrogen (δ<sup>2</sup> H–H2 O; 1*σ* < 0.2%) and oxygen (δ<sup>18</sup>O–H<sup>2</sup> O; 1*σ* < 0.05%) isotope composition of water vapor [16]. The second instrument is a dual quantum cascade laser absorption spectrometer (QCLAS; TILDAS-D, Aerodyne Research Inc., Billerica, MA, USA) with two tunable lasers to measure continuously and simultaneously the δ<sup>2</sup> H–H2 O (1*σ* < 0.1%) and δ<sup>18</sup>O–H<sup>2</sup> O (1*σ* < 0.03%) composition of water vapor as well as the carbon (δ<sup>13</sup>C–CO<sup>2</sup> ; 1*σ* < 0.03%) and oxygen (δ<sup>18</sup>O–CO<sup>2</sup> ; 1*σ* < 0.03%) isotope composition of CO<sup>2</sup> [17]. The third instrument is a carbonyl sulfide (COS) monitor (mini QCLAS, Aerodyne Research Inc.) for continuous high-sensitivity (1*σ* < 2 pptv) trace gas analysis. Finally, a bench-top differential infrared gas analyzer (LI-7000; LI-COR Biosciences, Lincoln, NE, USA) is available for simultaneous high-speed measurements of water vapor and CO<sup>2</sup> concentrations. Details on the respective technologies can be found elsewhere [18–21]. The gas analyzers are interfaced with sophisticated sample conveyance and control systems utilizing custom LabView (National Instruments Corp.) software for automated in-situ monitoring of liquid and gas compositions across the LEO domains.

and a tray capable of holding 55 centrifuge tubes of 50 mL volume for sample collection. Each module is connected to a vacuum manifold. Vacuum is supplied by a total of two single-stage rotary vane vacuum pumps (Model RC0100, Busch LLC, Virginia Beach, VA, USA) located outside of the LEO domain. The vacuum system allows simultaneous sample collection from all 496 samplers on each slope. However, when needed, vacuum application and sampling can be limited to any subset of modules or even any subset of individual samplers. This allows adapting the timing of sampling to in-slope processes, e.g., to the progression of a wetting front. Furthermore, the suction to be used in each module can be adjusted to matric potential recorded by the sensors co-located with solution samplers to ensure that adequate suction is applied to obtain a sufficient sample volume while avoiding excessive draw beyond the immediate vicinity of the samplers. In addition to soil solution sampling, water samples from the seven common irrigation tanks and from two to four custom precipitation collectors per hillslope are collected manually during irrigation events. Finally, custom-built, Arduino-based autosamplers for discrete sample collection at set intervals are in place to collect water samples from the outflow at the base of each hillslope (seepage flow and potentially overland flow) when it is generated.

All collected water samples are archived in freezers at a temperature of −9°C. Biogeochemical sample analysis is performed in an onsite analytical laboratory and can be complemented by isotopic analysis in the isotope and trace gas facility (Section 2.1.3). Prior to analysis samples are centrifuged at 4816 relative centrifugal force for 20 min to remove particulates (Sorvall Legend XTR, Thermo Fisher Scientific Inc., Waltham, MA, USA). The analytical lab is equipped with a Dionex ICS 5000 ion chromatography system (Thermo Fisher Scientific Inc.) with two conductivity detectors for high throughput and concurrent sample analysis for major anions and cations. Further capabilities include solution analysis for dissolved organic and inorganic carbon and total dissolved nitrogen (TOC-L Series total organic carbon and nitrogen analyzer, equipped with TOC-LCSH autosampler; all Shimadzu, Kyoto, Japan), as well as for pH and electrical conductivity (sympHony multimeter, VWR International, Radnor, PA, USA). In addition, selected samples are analyzed offsite for major, trace, and rare earth elements using inductively coupled plasma mass spectrometry (Elan DRC-II, Perkin Elmer, Waltham, MA, USA). Characterization of organic compounds in collected solutions is performed at the Environmental Molecular Sciences Laboratory (Richland, WA,

USA) using Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS).

Analysis of the concentration and/or stable isotope composition of key molecular species across the hydrologically and biogeochemically relevant landscape compartments (soil, atmosphere, and outflow) of LEO is facilitated by extensive onsite equipment arrays, encompassing state-of-the-art probing interfaces and analyzing instruments. All central equipment is housed in a custom laboratory facility constructed below the central LEO landscape structure. To facilitate stable and gap-free operation of sensitive instrumentation onsite, the laboratory was equipped with uninterrupted power supply, air-conditioning, and zero air (i.e., air that

Inc., Cleves, OH, USA), utilizing compressed facility air via a 60-gal in-line back-up reservoir. The facility currently houses four laser-based gas analyzers. The first instrument is an offaxis integrated cavity output spectrometer (OA-ICOS; IWA-35EP, Los Gatos Research Inc.,

Mountain View, CA. USA) for continuous measurement of the hydrogen (δ<sup>2</sup>

, and contaminants) supply from a lab generator (Aadco Instruments

H–H2

O; 1*σ* < 0.2%)

*2.1.3. Stable isotope and trace gas monitoring*

36 Hydrology of Artificial and Controlled Experiments

is free of water, CO<sup>2</sup>

A multisource liquid sampling system was devised for high-frequency sampling and realtime analysis of seepage water outflow from the three LEO ZOBs utilizing the OA-ICOS instrument. The sampling system uses a four-channel peristaltic pump (Minipuls 3, Gilson Inc., Middleton, WI, USA) to continuously deliver liquid water from a given source to one of four ports of a stainless-steel sampling manifold that is mounted on the tray-holder of an autosampler (LC PAL, CTC Analytics AG, Zwingen, Switzerland) for liquid injection into a vaporization unit and subsequent vapor delivery into the isotope analyzer. This setup delivers robust performance [22] and facilitates water isotopologue analysis of outflow from each LEO landscape at approximately 30-min intervals. To obtain an even higher temporal resolution of discharge isotope composition, as well as for complementary analysis of irrigation, discharge, and soil solution samples, the OA-ICOS instrument and autosampler setup can be used to analyze collected water samples (Section 2.1.2) offline.

Gas sampling is performed in the atmospheres and subsurface soil of each LEO landscape utilizing extensive valving and probing arrays that can be simultaneously linked to the dual-QCLAS, COS, and benchtop gas analyzers. Twenty-four air intake lines, with sheltered inlets at four to five different heights along each of the five masts distributed over each slope surface (Section 2.1; **Figures 2** and **3a**), are available for atmospheric gas sampling. Subsequent sample intake from each of the lines is facilitated by three stream selector valves (VICI Valco Instruments Inc., Houston, TX, USA) situated at the central onsite laboratory, with flow driven by a downstream vacuum pump. To eliminate temporal delay associated with sample gas transport from air inlet to analyzer, the intake line sections upstream of the valves can be constantly purged with fresh atmospheric air using branch-off lines connected to a purge pump via custom vacuum manifolds. To extract air samples from the subsurface, 141 custom soil gas samplers installed in a uniform grid at multiple soil depths are available within each of the model landscapes (**Figure 2**). The samplers were constructed from microporous, hydrophobic PTFE tubing sealed at both ends to gas transport lines with epoxy and heat shrink tubing. A multilevel conveyance system, comprising 27 sub-level stream selector valves mounted at varied locations across the landscapes' structural bases (**Figure 3c**), three main-level selector valves (VICI Valco Instruments Inc.), and several digital mass flow and pressure controllers (Alicat Scientific, Tucson, AZ, USA), allows for automated sampling from the dense probe network according to programmed sequences. The best achievable sample interval is approximately 1 h for sampling all atmospheric inlets and 36 h for sampling all subsurface probes. Actual sampling frequencies for atmospheric and soil gases vary depending on experimental priorities. All measured trace gas concentrations and isotope abundances in water vapor and CO<sup>2</sup> are calibrated to reference scales using self-built delivery systems for calibration standards (e.g., NOAA and IAEA standards). In addition, and because the isotopic liquid-vapor equilibrium in soils is mainly temperature dependent [23], the measured vaporphase isotope composition in soil air can be utilized along with measured soil temperatures to infer the liquid soil water isotope composition [24–26] throughout the LEO subsurface.

injections are performed at various locations in order to create a set of redundant potential measurements, which are used to derive a set of apparent electrical resistivity values. The apparent electrical resistivity values are then converted to a "true" electrical resistivity set through an inversion procedure [28], which can ultimately be related to soil physical proper-

Controlled Experiments of Hillslope Coevolution at the Biosphere 2 Landscape Evolution…

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39

Each LEO landscape is equipped with two current-injecting electrodes and 24 custom potential-measuring electrode stacks (**Figure 4a**). Each electrode stack is installed vertically into the LEO soil and comprises five stainless steel electrodes, separated by insulating acrylic cylinders, for potential measurements at varied soil depths (**Figure 4b**). Each of the 120 total electrodes can be connected to a Supersting R8 (Advanced Geosciences Inc., Austin, TX, USA) electrical resistivity meter and induced polarization and self-potential system. The fully automated eight-channel system allows rapid three-dimensional surveying and sequential imaging of dynamic processes with high accuracy and low noise levels. Specialized software (RES3DINVx64, Geotomo Software, Kardinya, Australia) is used for data processing. The system can provide a spatial resolution of a few centimeters in proximity to the electrodes

The Supersting electrical resistivity meter is also used to perform geophysical surveys of the miniLEO small-scale replicate system, where intensive soil sampling is possible to validate ERT measurement and interpretation methods for use on the full-scale LEO landscapes. Specifically, we seek to establish relationships between measured resistivity fields and features of subsurface heterogeneity associated with, e.g., changes in porosity, clay formation, moving wetting fronts,

**Figure 4.** Overview of electrical resistivity tomography (ERT) instrumentation at LEO. (a) Horizontal (*xy*-plane) arrangement of the 2 current-injecting electrodes (gray dots) and the 24 potential-measuring electrode stacks (black x's) across a LEO hillslope. (b) Schematic of an electrode stack, where dark gray sections indicate stainless steel electrodes and light gray sections indicate insulating acrylic rods. (c) The miniLEO small-scale replicate of the LEO hillslopes, equipped with 228 electrodes installed through its walls along 12 vertical transects. This miniLEO setup is used to test and develop ERT surveying and interpretation methods that can ultimately be applied to nondestructively monitor

ties (e.g., porosity), water content, and solute concentration [29].

and is coarser at increased distance from the electrodes.

incipient subsurface heterogeneity on the large-scale LEO landscapes.

#### *2.1.4. Remote sensing instrumentation*

Each hillslope is equipped with a custom-designed camera imaging system consisting of a hyperspectral imager and a thermal infrared camera. The hyperspectral imager (SOC710VP, Surface Optics Corp, San Diego, CA, USA) produces images within the wavelength range of 400–1000 nm with 4.7-nm bands (128 total bands). The thermal infrared camera (ICI 9640 P-Series, Infrared Cameras Inc., Beaumont, TX, USA) produces images with a 7–14 μm spectral response with a ±1°C accuracy. The images will be used to estimate spatiotemporal patterns of bare soil evaporation, plant transpiration, and photosynthesis (see, e.g., [27]).

In order to image the entire surface of the LEO hillslopes in a precise and repeatable way, the cameras are installed on a 35-m long belt drive linear actuator (MSA-14S, Misumi, Schaumburg, IL, USA), which is suspended from the space frame of Biosphere 2 and hangs 7 m above the surface of the LEO hillslopes at a 10° pitch (**Figure 3b**). This linear actuator allows movement of the camera boxes in the *x*-direction of the hillslopes and provides submillimeter linear resolution. A custom robotic stage allows the cameras to pan right and left and provides a 0.2° angular resolution or 1.5 cm at the soil surface. The hyperspectral camera uses a f = 8 mm lens producing an image area of 4.6 × 4.6 m with 0.9-cm resolution at the slope surface, while the infrared camera uses a f = 16 mm lens producing an image of 4.6 × 3.4 m with 0.7-cm resolution. The cameras are housed in an environmentally controlled enclosure to minimize temperature fluctuations using chilled compressed air. The linear actuator and robotic stage allow recording the 27 images required (9 along the *x*-axis and 3 along the *y*-axis) to cover the entire LEO soil surface. The camera system and data offload are controlled using custom LabView software, and software is being developed to stitch the images together to create complete images of the LEO surfaces.

In addition to imaging of the LEO surfaces, a LiDAR scanner (ScanStation C10, Leica Geosystems, Heerbrugg, Switzerland) is used to map surface topography changes in the LEO hillslopes and will be used in the future to measure vegetation growth as plants are introduced. The scanner provides a 6-mm spatial accuracy and 2-mm modeled surface precision. A 6-month scan interval of all hillslopes will provide us with a time series of geomorphologic change.

#### *2.1.5. Electrical resistivity tomography system*

Electrical resistivity tomography (ERT) is used for minimal-invasive monitoring of the subsurface at LEO. An ERT survey is performed by injecting an electrical current through a pair of electrodes and measuring the potential at several other electrode pairs. Several current injections are performed at various locations in order to create a set of redundant potential measurements, which are used to derive a set of apparent electrical resistivity values. The apparent electrical resistivity values are then converted to a "true" electrical resistivity set through an inversion procedure [28], which can ultimately be related to soil physical properties (e.g., porosity), water content, and solute concentration [29].

interval is approximately 1 h for sampling all atmospheric inlets and 36 h for sampling all subsurface probes. Actual sampling frequencies for atmospheric and soil gases vary depending on experimental priorities. All measured trace gas concentrations and isotope abundances

calibration standards (e.g., NOAA and IAEA standards). In addition, and because the isotopic liquid-vapor equilibrium in soils is mainly temperature dependent [23], the measured vaporphase isotope composition in soil air can be utilized along with measured soil temperatures to infer the liquid soil water isotope composition [24–26] throughout the LEO subsurface.

Each hillslope is equipped with a custom-designed camera imaging system consisting of a hyperspectral imager and a thermal infrared camera. The hyperspectral imager (SOC710VP, Surface Optics Corp, San Diego, CA, USA) produces images within the wavelength range of 400–1000 nm with 4.7-nm bands (128 total bands). The thermal infrared camera (ICI 9640 P-Series, Infrared Cameras Inc., Beaumont, TX, USA) produces images with a 7–14 μm spectral response with a ±1°C accuracy. The images will be used to estimate spatiotemporal pat-

In order to image the entire surface of the LEO hillslopes in a precise and repeatable way, the cameras are installed on a 35-m long belt drive linear actuator (MSA-14S, Misumi, Schaumburg, IL, USA), which is suspended from the space frame of Biosphere 2 and hangs 7 m above the surface of the LEO hillslopes at a 10° pitch (**Figure 3b**). This linear actuator allows movement of the camera boxes in the *x*-direction of the hillslopes and provides submillimeter linear resolution. A custom robotic stage allows the cameras to pan right and left and provides a 0.2° angular resolution or 1.5 cm at the soil surface. The hyperspectral camera uses a f = 8 mm lens producing an image area of 4.6 × 4.6 m with 0.9-cm resolution at the slope surface, while the infrared camera uses a f = 16 mm lens producing an image of 4.6 × 3.4 m with 0.7-cm resolution. The cameras are housed in an environmentally controlled enclosure to minimize temperature fluctuations using chilled compressed air. The linear actuator and robotic stage allow recording the 27 images required (9 along the *x*-axis and 3 along the *y*-axis) to cover the entire LEO soil surface. The camera system and data offload are controlled using custom LabView software, and software is being developed to stitch the images together to

In addition to imaging of the LEO surfaces, a LiDAR scanner (ScanStation C10, Leica Geosystems, Heerbrugg, Switzerland) is used to map surface topography changes in the LEO hillslopes and will be used in the future to measure vegetation growth as plants are introduced. The scanner provides a 6-mm spatial accuracy and 2-mm modeled surface precision. A 6-month scan inter-

Electrical resistivity tomography (ERT) is used for minimal-invasive monitoring of the subsurface at LEO. An ERT survey is performed by injecting an electrical current through a pair of electrodes and measuring the potential at several other electrode pairs. Several current

val of all hillslopes will provide us with a time series of geomorphologic change.

terns of bare soil evaporation, plant transpiration, and photosynthesis (see, e.g., [27]).

are calibrated to reference scales using self-built delivery systems for

in water vapor and CO<sup>2</sup>

*2.1.4. Remote sensing instrumentation*

38 Hydrology of Artificial and Controlled Experiments

create complete images of the LEO surfaces.

*2.1.5. Electrical resistivity tomography system*

Each LEO landscape is equipped with two current-injecting electrodes and 24 custom potential-measuring electrode stacks (**Figure 4a**). Each electrode stack is installed vertically into the LEO soil and comprises five stainless steel electrodes, separated by insulating acrylic cylinders, for potential measurements at varied soil depths (**Figure 4b**). Each of the 120 total electrodes can be connected to a Supersting R8 (Advanced Geosciences Inc., Austin, TX, USA) electrical resistivity meter and induced polarization and self-potential system. The fully automated eight-channel system allows rapid three-dimensional surveying and sequential imaging of dynamic processes with high accuracy and low noise levels. Specialized software (RES3DINVx64, Geotomo Software, Kardinya, Australia) is used for data processing. The system can provide a spatial resolution of a few centimeters in proximity to the electrodes and is coarser at increased distance from the electrodes.

The Supersting electrical resistivity meter is also used to perform geophysical surveys of the miniLEO small-scale replicate system, where intensive soil sampling is possible to validate ERT measurement and interpretation methods for use on the full-scale LEO landscapes. Specifically, we seek to establish relationships between measured resistivity fields and features of subsurface heterogeneity associated with, e.g., changes in porosity, clay formation, moving wetting fronts,

**Figure 4.** Overview of electrical resistivity tomography (ERT) instrumentation at LEO. (a) Horizontal (*xy*-plane) arrangement of the 2 current-injecting electrodes (gray dots) and the 24 potential-measuring electrode stacks (black x's) across a LEO hillslope. (b) Schematic of an electrode stack, where dark gray sections indicate stainless steel electrodes and light gray sections indicate insulating acrylic rods. (c) The miniLEO small-scale replicate of the LEO hillslopes, equipped with 228 electrodes installed through its walls along 12 vertical transects. This miniLEO setup is used to test and develop ERT surveying and interpretation methods that can ultimately be applied to nondestructively monitor incipient subsurface heterogeneity on the large-scale LEO landscapes.

and plant root distributions. The miniLEO was therefore equipped with 228 electrodes distributed along its walls (**Figure 4c**), allowing for subsurface mapping with particularly high resolution.

Sciences Laboratory, a national scientific user facility at the Pacific Northwest National Laboratory (PNNL). Selected soil samples from various depths and along specific flow paths

together with co-located solution samples by FTICR-MS. Air-dried samples are also used for sequential extraction followed by inductively coupled plasma mass spectrometry (ICP-MS) and X-ray diffraction analysis (following size fractionation to concentrate newly formed minerals) to quantify changes in mineralogical composition of the hillslopes. Mossbauer spectroscopy is employed to characterize the oxidation state and bonding environment of iron in weathering basalt in order to trace weathering of Fe-containing phases and precipitation of new minerals.

Experiments at LEO are iterated with coupled Earth system modeling. The Terrestrial Integrated Modeling System (TIMS) takes advantage of existing state-of-the-art community models to study interactions and feedbacks between various physical, geochemical, and biological processes by communicating fluxes and states of energy, water, and mass between various component models (**Figure 5**). A model developed in a specific discipline is typically limited by the scope of the developers' expertise and limited knowledge of other disciplines. To compensate

**Figure 5.** Schematic diagram of the Terrestrial Integrated Modeling System (TIMS) used to inform experiments and formalize observed interactions and feedbacks between physical, geochemical, and biological processes at LEO. TIMS couples existing state-of-the-art community models and aims to simulate the dynamics of (1) surface water in rivers, lakes, and wetlands, subsurface water in the vadose zone and aquifers, (2) organic and inorganic solute transport driven by surface and subsurface flow, volumes of various minerals, and porosity, (3) plant species and biomass distribution over a landscape, and (4) land surface energy, water, and carbon exchanges with the overlying air through atmospheric

O, MeOH, and CHCl<sup>3</sup>

Controlled Experiments of Hillslope Coevolution at the Biosphere 2 Landscape Evolution…

), and soil extracts are analyzed

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41

are subjected to solvent exactions (H<sup>2</sup>

*2.1.7. Integrated mathematical modeling framework*

turbulent transfer and radiation transfer.

#### *2.1.6. Sampling of soil material for physicochemical and biological analysis*

Regular soil sampling is required to assess the spatiotemporal microbiological variations and geochemical transformations occurring in the hillslopes. However, soil coring in the landscapes has to be performed conservatively to preserve the topography of the slopes and avoid preferential flow paths following soil removal. Therefore, coring has thus far been limited temporally to a twice-yearly basis (including times before and after irrigation events) and spatially to 4–6 locations corresponding to the zones that are expected to experience divergent evolution (including head slope, convergence zone, toe slope, and side slopes). We use the personnel transport system to access coring locations without disturbing the soil surface. A 1-m long steel corer with 1-inch internal diameter powered by drill and fitted with 1 × 37 3/4-inch plastic liner (AMS Inc., American Falls, ID, USA) is used to collect the samples. For each location, a new clean liner is fitted into the corer to prevent cross-contamination between samples. The plastic sleeve is extracted post-coring and sealed at both ends to prevent soil loss. After core extraction, the resulting hole in the soil is backfilled with the same amount of original tephra material, which is stored in barrels. To ensure that the backfill material is as similar in composition and extent of weathering to the extracted slope material as possible, the barrels receive irrigation water at similar rates as the ZOB soil.

The cores are brought to the lab where their lengths are measured, and they are sub-sectioned according to the depth profile recovered. Each subsection is partitioned into two halves to obtain samples for microbiological and geochemical analyses. Soil sampling areas are co-located with solution samplers and sensors to obtain complementary physicochemical measurements, and modeled variables needed to perform coupled hydro-geochemical and mineralogical analyses.

After extraction, samples for microbiological analyses are either stored on ice or flash-frozen for DNA and RNA extractions, respectively. High-throughput analyses of DNA provide total community composition (amplicon sequencing) and predictions of functional potential (metagenome sequencing), while RNA sequencing (metatranscriptomics) provides expressed function of the community. Soil samples are also used to analyze copy numbers of important functional genes using quantitative real-time polymerase chain reactions (qPCRs).

Samples for geochemical and mineralogical analyses are air-dried, with weight recorded before and after drying to determine moisture content of the sample. Air-dried samples are analyzed to quantify and characterize accumulation of organic compounds and to quantify inorganic carbon accumulation through weathering processes. Content of total nitrogen and total and organic carbon (following treatment with phosphoric acid to remove inorganic carbon) is determined using a total carbon and nitrogen analyzer (TOC-L Series, Shimadzu; see also Section 2.1.2) coupled with a solid sample combustion unit (SSM-5000A, Shimadzu). Molecular characterization of soil organic matter (SOM) to observe carbon stabilization and fractionation during weathering processes is performed using Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) at the William R. Wiley Environmental Molecular Sciences Laboratory, a national scientific user facility at the Pacific Northwest National Laboratory (PNNL). Selected soil samples from various depths and along specific flow paths are subjected to solvent exactions (H<sup>2</sup> O, MeOH, and CHCl<sup>3</sup> ), and soil extracts are analyzed together with co-located solution samples by FTICR-MS. Air-dried samples are also used for sequential extraction followed by inductively coupled plasma mass spectrometry (ICP-MS) and X-ray diffraction analysis (following size fractionation to concentrate newly formed minerals) to quantify changes in mineralogical composition of the hillslopes. Mossbauer spectroscopy is employed to characterize the oxidation state and bonding environment of iron in weathering basalt in order to trace weathering of Fe-containing phases and precipitation of new minerals.

#### *2.1.7. Integrated mathematical modeling framework*

and plant root distributions. The miniLEO was therefore equipped with 228 electrodes distributed along its walls (**Figure 4c**), allowing for subsurface mapping with particularly high resolution.

Regular soil sampling is required to assess the spatiotemporal microbiological variations and geochemical transformations occurring in the hillslopes. However, soil coring in the landscapes has to be performed conservatively to preserve the topography of the slopes and avoid preferential flow paths following soil removal. Therefore, coring has thus far been limited temporally to a twice-yearly basis (including times before and after irrigation events) and spatially to 4–6 locations corresponding to the zones that are expected to experience divergent evolution (including head slope, convergence zone, toe slope, and side slopes). We use the personnel transport system to access coring locations without disturbing the soil surface. A 1-m long steel corer with 1-inch internal diameter powered by drill and fitted with 1 × 37 3/4-inch plastic liner (AMS Inc., American Falls, ID, USA) is used to collect the samples. For each location, a new clean liner is fitted into the corer to prevent cross-contamination between samples. The plastic sleeve is extracted post-coring and sealed at both ends to prevent soil loss. After core extraction, the resulting hole in the soil is backfilled with the same amount of original tephra material, which is stored in barrels. To ensure that the backfill material is as similar in composition and extent of weathering to the extracted slope material as possible,

The cores are brought to the lab where their lengths are measured, and they are sub-sectioned according to the depth profile recovered. Each subsection is partitioned into two halves to obtain samples for microbiological and geochemical analyses. Soil sampling areas are co-located with solution samplers and sensors to obtain complementary physicochemical measurements, and modeled variables needed to perform coupled hydro-geochemical and

After extraction, samples for microbiological analyses are either stored on ice or flash-frozen for DNA and RNA extractions, respectively. High-throughput analyses of DNA provide total community composition (amplicon sequencing) and predictions of functional potential (metagenome sequencing), while RNA sequencing (metatranscriptomics) provides expressed function of the community. Soil samples are also used to analyze copy numbers of important

Samples for geochemical and mineralogical analyses are air-dried, with weight recorded before and after drying to determine moisture content of the sample. Air-dried samples are analyzed to quantify and characterize accumulation of organic compounds and to quantify inorganic carbon accumulation through weathering processes. Content of total nitrogen and total and organic carbon (following treatment with phosphoric acid to remove inorganic carbon) is determined using a total carbon and nitrogen analyzer (TOC-L Series, Shimadzu; see also Section 2.1.2) coupled with a solid sample combustion unit (SSM-5000A, Shimadzu). Molecular characterization of soil organic matter (SOM) to observe carbon stabilization and fractionation during weathering processes is performed using Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) at the William R. Wiley Environmental Molecular

functional genes using quantitative real-time polymerase chain reactions (qPCRs).

*2.1.6. Sampling of soil material for physicochemical and biological analysis*

40 Hydrology of Artificial and Controlled Experiments

the barrels receive irrigation water at similar rates as the ZOB soil.

mineralogical analyses.

Experiments at LEO are iterated with coupled Earth system modeling. The Terrestrial Integrated Modeling System (TIMS) takes advantage of existing state-of-the-art community models to study interactions and feedbacks between various physical, geochemical, and biological processes by communicating fluxes and states of energy, water, and mass between various component models (**Figure 5**). A model developed in a specific discipline is typically limited by the scope of the developers' expertise and limited knowledge of other disciplines. To compensate

**Figure 5.** Schematic diagram of the Terrestrial Integrated Modeling System (TIMS) used to inform experiments and formalize observed interactions and feedbacks between physical, geochemical, and biological processes at LEO. TIMS couples existing state-of-the-art community models and aims to simulate the dynamics of (1) surface water in rivers, lakes, and wetlands, subsurface water in the vadose zone and aquifers, (2) organic and inorganic solute transport driven by surface and subsurface flow, volumes of various minerals, and porosity, (3) plant species and biomass distribution over a landscape, and (4) land surface energy, water, and carbon exchanges with the overlying air through atmospheric turbulent transfer and radiation transfer.

for these limitations in the models of individual disciplines, TIMS integrates advanced knowledge and expertise from various disciplines and may thereby exceed the sum of its parts. TIMS has integrated a physically based hydrological model (CATchment Hydrology model, CATHY) and a land-atmosphere energy, water, and carbon exchange scheme (NoahMP) [30, 31]. In addition, it has integrated newly developed modules such as a radiation correction model, which accounts for the effects of topographic shading and scattering [32], and a six-carbon pool microbial enzyme model, which provides the capability to model the responses of soil microbial respiration to soil moisture dynamics [33]. TIMS aims to further integrate an individualbased ecological model (e.g., ECOTONE) and a geochemical model (e.g., CrunchFlow).

\_\_\_ <sup>∂</sup>*<sup>S</sup>*

injected deuterium abundance in irrigation water).

where *S* represents the volume of water stored within the landscape (L<sup>3</sup>

tion inflow (L<sup>3</sup> T−1), *Q* represents the discharge outflow at the downslope end of the landscape (L<sup>3</sup> T−1), and *ET* represents the combined vapor-phase flux associated with bare soil evaporation and plant transpiration from land to atmosphere (L<sup>3</sup> T−1). All variables are functions of time *t*. All water balance terms in Eq. 1 can be measured as integrated, landscape-scale states and fluxes at LEO—a capability critical for characterizing hydrologic partitioning under variable environmental conditions yet not achieved in any other experiment at the hillslope scale (**Figure 6a**–**c**). Temporal changes in water storage within the entire landscape are monitored via 10 load cells installed under the only load-bearing points connecting the main hillslope with the supporting structure. This makes the LEO landscapes the world's largest weighing lysimeters. Volumetric irrigation flow rates are monitored with electromagnetic flow meters. The total specific flux and the spatial distribution associated with each of the five irrigation circuits were characterized through a series of manual calibration trials. The discharge term can comprise both subsurface and overland outflows of water from the landscape, depending on intensity and duration of irrigation forcing. Subsurface flow can exit through one of six lateral subsections of the seepage face at the downslope extent of each landscape and is then routed through

**Figure 6.** Measured hydrological and tracer dynamics for the three LEO landscapes (East, Center, and West) over the course of a two-month long experiment with periodic forcing and deuterium tracer application during two subsequent irrigation pulses (indicated by black arrows; preliminary data). Data shown are whole-landscape means of irrigation influx (*I*), water storage (*S*), discharge (*Q*), and deuterium tracer abundance in discharge (*D*; values are relative to the

<sup>∂</sup>*<sup>t</sup>* <sup>=</sup> *<sup>I</sup>*(*t*) <sup>−</sup> *<sup>Q</sup>*(*t*) <sup>−</sup> *ET*(*t*) (1)

Controlled Experiments of Hillslope Coevolution at the Biosphere 2 Landscape Evolution…

), *I* represents the irriga-

43

http://dx.doi.org/10.5772/intechopen.72325

CATHY [34] is a 3D, physically based, surface-subsurface coupled flow model. The subsurface flow module in CATHY solves the pressure-based 3D Richards equation describing flow in variably saturated porous media [35], while the quasi-2D surface flow module solves the diffusive wave equation describing surface flow propagation over hillslopes and in stream channels and lakes identified using terrain topography and the hydraulic geometry concept [36]. This model has undergone long-term development and represents one of the most thoroughly developed, physically based flow models. NoahMP [37] represents the land surface energy (e.g., radiation, sensible, and latent heat fluxes), water (e.g., transpiration and evaporation), and carbon fluxes exchanging with the atmosphere and provides multiple physical options for hypothesis testing. It is a community land surface model developed through collaborations among scientists in national centers (e.g., NCAR, NCEP, and NASA) and universities for use in water, weather, and short-term climate predictions (e.g., the National Water Model and the Weather Research and Forecasting Model). It also represents assimilation of carbon through photosynthesis, carbon allocation to various parts of the plant, autotrophic and heterotrophic respiration, leaf litter, root exudates, and dead roots, as well as leaf and root dynamics. ECOTONE [38] is an individual-based ecological model simulating changes in species and associated biomass of individual plants within a patch of land (1–10 m<sup>2</sup> area). Seed germination, establishment of seedlings, and mortality are described by stochastic elements (e.g., seed dispersal, local disturbance), but growth is deterministic based on root distribution and access to water and nitrogen within a competitive context. Resources are distributed to each plant based on the proportion of active roots at each depth relative to total root biomass of all plants. The yearly time step computation is changed to a daily time step to update the biomass in response to daily soil moisture dynamics that are aggregated from CATHY operating at sub-hourly time step. CrunchFlow [39] is a multicomponent reactive transport model describing advective, dispersive, and diffusive transport of solutes, resulting from various chemical reactions such as aqueous complexation, mineral precipitation and dissolution, ion exchange, surface complexation, radioactive decay, and biologically mediated reactions. It also deals with burial, erosion, and compaction of porous media, with an explicit treatment of spatially variable advection of solids as well as reactioninduced porosity and permeability feedbacks to both diffusion and flow.

#### **2.2. Monitoring of hydrologic cycling and flow pathways**

Each landscape and its surrounding atmosphere are extensively equipped to close the terrestrial water balance, written as follows:

Controlled Experiments of Hillslope Coevolution at the Biosphere 2 Landscape Evolution… http://dx.doi.org/10.5772/intechopen.72325 43

$$\frac{\partial S}{\partial t} = \left[I(t) - Q(t) - ET(t)\right] \tag{1}$$

where *S* represents the volume of water stored within the landscape (L<sup>3</sup> ), *I* represents the irrigation inflow (L<sup>3</sup> T−1), *Q* represents the discharge outflow at the downslope end of the landscape (L<sup>3</sup> T−1), and *ET* represents the combined vapor-phase flux associated with bare soil evaporation and plant transpiration from land to atmosphere (L<sup>3</sup> T−1). All variables are functions of time *t*.

for these limitations in the models of individual disciplines, TIMS integrates advanced knowledge and expertise from various disciplines and may thereby exceed the sum of its parts. TIMS has integrated a physically based hydrological model (CATchment Hydrology model, CATHY) and a land-atmosphere energy, water, and carbon exchange scheme (NoahMP) [30, 31]. In addition, it has integrated newly developed modules such as a radiation correction model, which accounts for the effects of topographic shading and scattering [32], and a six-carbon pool microbial enzyme model, which provides the capability to model the responses of soil microbial respiration to soil moisture dynamics [33]. TIMS aims to further integrate an individualbased ecological model (e.g., ECOTONE) and a geochemical model (e.g., CrunchFlow).

CATHY [34] is a 3D, physically based, surface-subsurface coupled flow model. The subsurface flow module in CATHY solves the pressure-based 3D Richards equation describing flow in variably saturated porous media [35], while the quasi-2D surface flow module solves the diffusive wave equation describing surface flow propagation over hillslopes and in stream channels and lakes identified using terrain topography and the hydraulic geometry concept [36]. This model has undergone long-term development and represents one of the most thoroughly developed, physically based flow models. NoahMP [37] represents the land surface energy (e.g., radiation, sensible, and latent heat fluxes), water (e.g., transpiration and evaporation), and carbon fluxes exchanging with the atmosphere and provides multiple physical options for hypothesis testing. It is a community land surface model developed through collaborations among scientists in national centers (e.g., NCAR, NCEP, and NASA) and universities for use in water, weather, and short-term climate predictions (e.g., the National Water Model and the Weather Research and Forecasting Model). It also represents assimilation of carbon through photosynthesis, carbon allocation to various parts of the plant, autotrophic and heterotrophic respiration, leaf litter, root exudates, and dead roots, as well as leaf and root dynamics. ECOTONE [38] is an individual-based ecological model simulating changes in species and associated biomass of individual

and mortality are described by stochastic elements (e.g., seed dispersal, local disturbance), but growth is deterministic based on root distribution and access to water and nitrogen within a competitive context. Resources are distributed to each plant based on the proportion of active roots at each depth relative to total root biomass of all plants. The yearly time step computation is changed to a daily time step to update the biomass in response to daily soil moisture dynamics that are aggregated from CATHY operating at sub-hourly time step. CrunchFlow [39] is a multicomponent reactive transport model describing advective, dispersive, and diffusive transport of solutes, resulting from various chemical reactions such as aqueous complexation, mineral precipitation and dissolution, ion exchange, surface complexation, radioactive decay, and biologically mediated reactions. It also deals with burial, erosion, and compaction of porous media, with an explicit treatment of spatially variable advection of solids as well as reaction-

Each landscape and its surrounding atmosphere are extensively equipped to close the terres-

induced porosity and permeability feedbacks to both diffusion and flow.

**2.2. Monitoring of hydrologic cycling and flow pathways**

area). Seed germination, establishment of seedlings,

plants within a patch of land (1–10 m<sup>2</sup>

42 Hydrology of Artificial and Controlled Experiments

trial water balance, written as follows:

All water balance terms in Eq. 1 can be measured as integrated, landscape-scale states and fluxes at LEO—a capability critical for characterizing hydrologic partitioning under variable environmental conditions yet not achieved in any other experiment at the hillslope scale (**Figure 6a**–**c**). Temporal changes in water storage within the entire landscape are monitored via 10 load cells installed under the only load-bearing points connecting the main hillslope with the supporting structure. This makes the LEO landscapes the world's largest weighing lysimeters. Volumetric irrigation flow rates are monitored with electromagnetic flow meters. The total specific flux and the spatial distribution associated with each of the five irrigation circuits were characterized through a series of manual calibration trials. The discharge term can comprise both subsurface and overland outflows of water from the landscape, depending on intensity and duration of irrigation forcing. Subsurface flow can exit through one of six lateral subsections of the seepage face at the downslope extent of each landscape and is then routed through

**Figure 6.** Measured hydrological and tracer dynamics for the three LEO landscapes (East, Center, and West) over the course of a two-month long experiment with periodic forcing and deuterium tracer application during two subsequent irrigation pulses (indicated by black arrows; preliminary data). Data shown are whole-landscape means of irrigation influx (*I*), water storage (*S*), discharge (*Q*), and deuterium tracer abundance in discharge (*D*; values are relative to the injected deuterium abundance in irrigation water).

a plumbing system with inline electromagnetic flow meters and tipping bucket gauges. Each subsection is measured separately to capture spatial variability of flow, particularly during high flow conditions, and two different types of instruments are used to achieve optimal precision over the full range of possible flow rates. If present, overland flow will be routed over a flume structure and through a plumbing system into an open reservoir, where a pressure transducer continuously monitors changes in water depth. The single remaining water balance component, the combined evapotranspiration flux, can be estimated as the residual term of Eq. 1 using the directly measured rates of all other terms as described above.

surface temperature at centimeter-scale resolution (Section 2.1.4). When coupled with atmospheric measurements and known soil properties, the thermal imagery facilitates calculation of surface evaporation using methods similar to those applied by [27]. Given the high density of these spatially resolved aboveground and belowground measurements, good approximations of landscape integrated hydrological states, and fluxes can be attained to corroborate the

Controlled Experiments of Hillslope Coevolution at the Biosphere 2 Landscape Evolution…

http://dx.doi.org/10.5772/intechopen.72325

45

Characterizing the origin, flow pathways, and transit times of water through landscapes is a particular challenge that none of the above instrumentation can meet. LEO was therefore additionally equipped with a state-of-the-art stable isotope facility that operates the first hillslope-scale real-time isotope monitoring network (Section 2.1.3) and performs isotope analysis of collected water samples (Section 2.1.2). Irrigation water can be analyzed and labeled to create a known and time-variable isotope tracer input to the landscapes. Using equilibrium calculations, online measurements from the dense soil gas probing system (141 samplers per hillslope; **Figure 2**) can then be used to track the labeled liquid water through the subsurface soil in continuous time [24]. Isotopic analysis of pore water samples provides additional, spatially detailed (496 samplers per hillslope) snapshots of tracer plumes. Tracer finally leaving the landscapes through evaporation and transpiration can be identified through online gas monitoring along the masts throughout the LEO atmospheres (24 gas inlets per slope), and tracer leaving the landscapes as discharge is recorded using online or offline high-frequency liquid water sampling and isotope analysis (**Figure 6d**). These landscape-integrating and spatially resolved isotope measurements can thus be integrated with mixing models [25], transfer functions [14], and coupled-process models [48, 49] to characterize the pathways and fate of water molecules entering the hillslopes at a given

The exchange of energy is a key component of the coupling between the landscape surface and the overlying atmospheric boundary layer. The surface energy balance of a LEO land-

where *R* represents radiative fluxes associated with shortwave and longwave (subscripts *s* and *l*) radiation that is incoming or outgoing (subscripts *i* and *o*) to or from the landscape (P L−2), *H* represents the sensible heat flux between land and air (P L−2), λ*ET* is the product of the latent heat of vaporization (E M−1) and the magnitude of evapotranspiration (M T−1 L−2),

The latent heat flux is the only term in Eq. 2 that is measured at the landscape scale. This is accomplished using the known value of heat of vaporization and the whole-landscape evapotranspiration flux estimates, which are based on load cell measurements and mass balance calculations (see Section 2.2). All other terms of the energy balance are measured at several discrete locations across each LEO landscape, and landscape-scale fluxes can be estimated

and *G* represents the conductive heat transport and storage into the landscape (P L−2).

(*t*) = *H*(*t*) + *ET*(*t*) + *G*(*t*) (2)

direct landscape-scale measurements outlined above.

time throughout the LEO domains.

scape can be described as follows:

*Rsi*

**2.3. Monitoring of land-surface energy exchange**

based on the point measurements (**Figure 7c**).

(*t*) + *Rli*

(*t*) + *Rso*(*t*) + *Rlo*

The landscape-scale hydrologic cycling is the product of inherently variable surface and subsurface hydrological fluxes and dominantly controlled by landscape heterogeneity [1, 40]. Even in a simplified model system such as the initial LEO landscapes, water movement is not homogeneous [41], and continued coevolution and variable forcing are anticipated to induce increasingly complex flow patterns. The landscape-scale measurements of water storage and fluxes are therefore complemented by spatially resolved measurements utilizing conventional hydrometric as well as innovative, minimal-invasive geophysical and optical techniques. A laterally (154 locations in the *xy*-plane) and vertically (five different depths) dense grid comprising 496 co-located soil water content and matric potential sensors (**Figure 2**) provide meter-scale lateral and sub-meter-scale vertical resolution of water storage, availability, and retention characteristics in continuous time. An even higher spatial resolution of subsurface water dynamics can be achieved using electrical resistivity tomography (ERT) measurements (Section 2.1.5). Three-dimensional time-lapse ERT scans from 24 potential-measuring electrode stacks installed into each hillslope can be geophysically inverted [42] and coupled with hydrological models [43] to resolve decimeter-scale variations in water content and flow processes.

Direct measurements of spatially distributed soil evaporation and plant transpiration fluxes can, in principal, be obtained based on flux-gradient and eddy covariance techniques commonly used in field studies (e.g., [44, 45]). The vapor-phase surface fluxes are mainly determined by wind speeds and a vertical gradient of atmospheric vapor pressure deficit (VPD, a function of air temperature and humidity), and the atmospheric instrumentation array at LEO delivers all required data. Profiles of air temperature, absolute and relative humidity, and wind speed are measured along five vertical masts (at heights of 0.25, 1, 3, 6, and 10 m above the land surface) distributed over each landscape's surface, and high-frequency measurements of the three-dimensional wind vector are available for a central location over each landscape (**Figure 2**). However, application of conventional flux-estimation methods is challenging under the indoor climate conditions at Biosphere 2 [46], as stable atmospheric stratification and associated turbulent intermittency, waves, and other processes make specific methodological adaptations necessary (e.g., [47]). The closed nature of the LEO atmospheres makes it possible, in turn, to use mass balance calculations to approximate whole-landscape evapotranspiration fluxes and their spatial heterogeneity from the spatially stratified measurements. An additional opportunity for measuring spatially resolved evaporation fluxes is through high-resolution thermal imaging. An infrared camera system moving precisely along a track system mounted to the space frame of each LEO bay maps whole-slope soil surface temperature at centimeter-scale resolution (Section 2.1.4). When coupled with atmospheric measurements and known soil properties, the thermal imagery facilitates calculation of surface evaporation using methods similar to those applied by [27]. Given the high density of these spatially resolved aboveground and belowground measurements, good approximations of landscape integrated hydrological states, and fluxes can be attained to corroborate the direct landscape-scale measurements outlined above.

Characterizing the origin, flow pathways, and transit times of water through landscapes is a particular challenge that none of the above instrumentation can meet. LEO was therefore additionally equipped with a state-of-the-art stable isotope facility that operates the first hillslope-scale real-time isotope monitoring network (Section 2.1.3) and performs isotope analysis of collected water samples (Section 2.1.2). Irrigation water can be analyzed and labeled to create a known and time-variable isotope tracer input to the landscapes. Using equilibrium calculations, online measurements from the dense soil gas probing system (141 samplers per hillslope; **Figure 2**) can then be used to track the labeled liquid water through the subsurface soil in continuous time [24]. Isotopic analysis of pore water samples provides additional, spatially detailed (496 samplers per hillslope) snapshots of tracer plumes. Tracer finally leaving the landscapes through evaporation and transpiration can be identified through online gas monitoring along the masts throughout the LEO atmospheres (24 gas inlets per slope), and tracer leaving the landscapes as discharge is recorded using online or offline high-frequency liquid water sampling and isotope analysis (**Figure 6d**). These landscape-integrating and spatially resolved isotope measurements can thus be integrated with mixing models [25], transfer functions [14], and coupled-process models [48, 49] to characterize the pathways and fate of water molecules entering the hillslopes at a given time throughout the LEO domains.

#### **2.3. Monitoring of land-surface energy exchange**

a plumbing system with inline electromagnetic flow meters and tipping bucket gauges. Each subsection is measured separately to capture spatial variability of flow, particularly during high flow conditions, and two different types of instruments are used to achieve optimal precision over the full range of possible flow rates. If present, overland flow will be routed over a flume structure and through a plumbing system into an open reservoir, where a pressure transducer continuously monitors changes in water depth. The single remaining water balance component, the combined evapotranspiration flux, can be estimated as the residual term of Eq. 1 using the directly measured rates of all other terms as

The landscape-scale hydrologic cycling is the product of inherently variable surface and subsurface hydrological fluxes and dominantly controlled by landscape heterogeneity [1, 40]. Even in a simplified model system such as the initial LEO landscapes, water movement is not homogeneous [41], and continued coevolution and variable forcing are anticipated to induce increasingly complex flow patterns. The landscape-scale measurements of water storage and fluxes are therefore complemented by spatially resolved measurements utilizing conventional hydrometric as well as innovative, minimal-invasive geophysical and optical techniques. A laterally (154 locations in the *xy*-plane) and vertically (five different depths) dense grid comprising 496 co-located soil water content and matric potential sensors (**Figure 2**) provide meter-scale lateral and sub-meter-scale vertical resolution of water storage, availability, and retention characteristics in continuous time. An even higher spatial resolution of subsurface water dynamics can be achieved using electrical resistivity tomography (ERT) measurements (Section 2.1.5). Three-dimensional time-lapse ERT scans from 24 potential-measuring electrode stacks installed into each hillslope can be geophysically inverted [42] and coupled with hydrological models [43] to resolve decimeter-scale variations in water content and flow

Direct measurements of spatially distributed soil evaporation and plant transpiration fluxes can, in principal, be obtained based on flux-gradient and eddy covariance techniques commonly used in field studies (e.g., [44, 45]). The vapor-phase surface fluxes are mainly determined by wind speeds and a vertical gradient of atmospheric vapor pressure deficit (VPD, a function of air temperature and humidity), and the atmospheric instrumentation array at LEO delivers all required data. Profiles of air temperature, absolute and relative humidity, and wind speed are measured along five vertical masts (at heights of 0.25, 1, 3, 6, and 10 m above the land surface) distributed over each landscape's surface, and high-frequency measurements of the three-dimensional wind vector are available for a central location over each landscape (**Figure 2**). However, application of conventional flux-estimation methods is challenging under the indoor climate conditions at Biosphere 2 [46], as stable atmospheric stratification and associated turbulent intermittency, waves, and other processes make specific methodological adaptations necessary (e.g., [47]). The closed nature of the LEO atmospheres makes it possible, in turn, to use mass balance calculations to approximate whole-landscape evapotranspiration fluxes and their spatial heterogeneity from the spatially stratified measurements. An additional opportunity for measuring spatially resolved evaporation fluxes is through high-resolution thermal imaging. An infrared camera system moving precisely along a track system mounted to the space frame of each LEO bay maps whole-slope soil

described above.

44 Hydrology of Artificial and Controlled Experiments

processes.

The exchange of energy is a key component of the coupling between the landscape surface and the overlying atmospheric boundary layer. The surface energy balance of a LEO landscape can be described as follows:

$$R\_{\rm s}(t) + R\_{\rm l}(t) + R\_{\rm so}(t) + R\_{\rm h}(t) = H(t) + \lambda ET(t) + G(t) \tag{2}$$

where *R* represents radiative fluxes associated with shortwave and longwave (subscripts *s* and *l*) radiation that is incoming or outgoing (subscripts *i* and *o*) to or from the landscape (P L−2), *H* represents the sensible heat flux between land and air (P L−2), λ*ET* is the product of the latent heat of vaporization (E M−1) and the magnitude of evapotranspiration (M T−1 L−2), and *G* represents the conductive heat transport and storage into the landscape (P L−2).

The latent heat flux is the only term in Eq. 2 that is measured at the landscape scale. This is accomplished using the known value of heat of vaporization and the whole-landscape evapotranspiration flux estimates, which are based on load cell measurements and mass balance calculations (see Section 2.2). All other terms of the energy balance are measured at several discrete locations across each LEO landscape, and landscape-scale fluxes can be estimated based on the point measurements (**Figure 7c**).

All radiative flux terms on the left-hand side of Eq. 2, and thus the net radiative flux, are measured directly by a pair of four-way net radiometers installed at 1-m height above the soil surface on the two masts located off-axis over the east- and west-facing hillslope segments adjacent to the convergence zone (**Figure 2**). Photosynthetically active radiation (i.e. visible light) is additionally measured at 4–5 heights along all five vertical atmospheric masts. Added uncertainties exist in utilizing these point measurements to represent the average landscape-scale fluxes due to the effects of the windows and structural frames of the climate-controlled bay on solar radiation and mismatched source areas. The conductive heat flux into and out of the ground is measured by 12 pairs of heat flux plates (buried at 0.08 m depth, with associated averaging soil thermocouple probes installed at 0.02 m depth). Those devices are arranged in an approximately uniform grid spanning most of the landscape surface, including monitoring locations below the atmospheric masts (**Figure 2**). Finally, the sensible heat flux from land to atmosphere can be estimated as the residual term of Eq. (2). An alternative possibility for monitoring *H*, as well as λ*ET*, is through application of modified flux-gradient or eddy covariance methods (e.g., [47]). As described in Section 2.2, those methods would utilize the array of aboveground meteorological instruments, but their application under often stable adiabatic conditions above the hillslopes' surfaces poses a challenge and requires methodological developments. Finally, the aboveground and belowground instrumentation allows tracking the spatial and temporal variations in kinetic energy (in terms of temperature, measured at 496 soil locations and 24 atmospheric location; **Figure 7a**, **b**) and latent energy (in terms of humidity, measured at 24 atmospheric location) contained across the LEO domain that result from the local balance of energy fluxes and importantly control hydro-biogeochemical flux and reaction processes.

#### **2.4. Monitoring of biogeochemical cycling**

The LEO landscapes are uniquely suited to examine biogeochemical cycling (with the potential to close elemental mass balances) due to the comprehensive array of sensors and samplers installed in and above the hillslopes. In general, a cycle of any element on the landscape can be described in the following common terms:

$$\frac{\partial E}{\partial t} = E\_p(t) + E\_a(t) - E\_r(t) - E\_q(t) \tag{3}$$

well as seepage volumes per time enables determination of *Eq*

and *Er*

set is analyzed for major and trace elements (Section 2.1.2).

Energy flux (*E*) observations include the net downward radiative flux (*Rn*

associated with spatial variability across the landscape's domain.

Exchange with the atmosphere, *Ea*

used for analysis of CO<sup>2</sup>

infrared gas analyzer to measure CO<sup>2</sup>

to capture these water samples during and following all irrigation events on the landscapes. Collected rainfall and seepage samples are analyzed for major cations and anions, as well as total, organic, and inorganic carbon, in addition to pH and electrical conductivity, and a sub-

**Figure 7.** Diel cycles of temperatures and land-surface energy fluxes measured across the domain of one LEO landscape. Air temperatures (*Tair*) are based on all available sensors installed at three selected heights along masts above the land surface, and soil temperatures (*Tsoil*) are based on all available sensors installed at three selected depths below the surface.

Controlled Experiments of Hillslope Coevolution at the Biosphere 2 Landscape Evolution…

http://dx.doi.org/10.5772/intechopen.72325

47

the downward ground heat flux into the subsurface medium (*G*). The latent heat flux was negligible due to extremely dry soil conditions. Solid lines represent whole-landscape means and shaded bounds indicate standard deviations

installed above and within the LEO slopes. Atmospheric air can be drawn into the benchtop

samples per slope; see also Section 2.1.3). The gas analysis system is flexible and can also be

bon monoxide, nitrous oxide, hydrogen, carbonyl sulfide, etc.) when connected to alternative

. Autosamplers are installed

), the upward surface sensible heat flux (*H*), and

, is measured using profiles of gas sampling ports

concentrations at approximately hourly intervals (24

isotope ratios and mole fractions of other gases (such as methane, car-

where *E* is the element storage in different forms on or within the landscape (M), *Ep* represents the transfer rate to the landscape with precipitation (M T−1), *Ea* represents the transfer from the atmosphere through different mechanisms (M T−1), *Er* represents the release back into (or new emissions to) the atmosphere (M T−1), and *Eq* represents the loss with water discharge from the landscape (M T−1). All of these fluxes can be measured, integrated at the landscape scale, and spatially resolved across the landscape using existing instrumentation for major and trace elements. A particular focus lies on carbon, elements essential for plant nutrition, and those indicative of soil formation processes, such as weathering.

Given known rainfall duration and intensity (as well as changes in the mass of the hillslopes), the *Ep* term can be quantified for the whole landscape by measuring the total element content in rainfall. Measuring element concentrations in the seepage and overland flow (if any) as

Controlled Experiments of Hillslope Coevolution at the Biosphere 2 Landscape Evolution… http://dx.doi.org/10.5772/intechopen.72325 47

All radiative flux terms on the left-hand side of Eq. 2, and thus the net radiative flux, are measured directly by a pair of four-way net radiometers installed at 1-m height above the soil surface on the two masts located off-axis over the east- and west-facing hillslope segments adjacent to the convergence zone (**Figure 2**). Photosynthetically active radiation (i.e. visible light) is additionally measured at 4–5 heights along all five vertical atmospheric masts. Added uncertainties exist in utilizing these point measurements to represent the average landscape-scale fluxes due to the effects of the windows and structural frames of the climate-controlled bay on solar radiation and mismatched source areas. The conductive heat flux into and out of the ground is measured by 12 pairs of heat flux plates (buried at 0.08 m depth, with associated averaging soil thermocouple probes installed at 0.02 m depth). Those devices are arranged in an approximately uniform grid spanning most of the landscape surface, including monitoring locations below the atmospheric masts (**Figure 2**). Finally, the sensible heat flux from land to atmosphere can be estimated as the residual term of Eq. (2). An alternative possibility for monitoring *H*, as well as λ*ET*, is through application of modified flux-gradient or eddy covariance methods (e.g., [47]). As described in Section 2.2, those methods would utilize the array of aboveground meteorological instruments, but their application under often stable adiabatic conditions above the hillslopes' surfaces poses a challenge and requires methodological developments. Finally, the aboveground and belowground instrumentation allows tracking the spatial and temporal variations in kinetic energy (in terms of temperature, measured at 496 soil locations and 24 atmospheric location; **Figure 7a**, **b**) and latent energy (in terms of humidity, measured at 24 atmospheric location) contained across the LEO domain that result from the local balance of energy fluxes and importantly control hydro-biogeochemical flux

The LEO landscapes are uniquely suited to examine biogeochemical cycling (with the potential to close elemental mass balances) due to the comprehensive array of sensors and samplers installed in and above the hillslopes. In general, a cycle of any element on the landscape can

(*t*) − *Er*

the landscape (M T−1). All of these fluxes can be measured, integrated at the landscape scale, and spatially resolved across the landscape using existing instrumentation for major and trace elements. A particular focus lies on carbon, elements essential for plant nutrition, and those

Given known rainfall duration and intensity (as well as changes in the mass of the hillslopes),

 term can be quantified for the whole landscape by measuring the total element content in rainfall. Measuring element concentrations in the seepage and overland flow (if any) as

(*t*) − *Eq*

(*t*) (3)

represents the transfer from the

represents the release back into (or new

represents the loss with water discharge from

represents

(*t*) + *Ea*

where *E* is the element storage in different forms on or within the landscape (M), *Ep*

<sup>∂</sup>*<sup>t</sup>* <sup>=</sup> *Ep*

the transfer rate to the landscape with precipitation (M T−1), *Ea*

indicative of soil formation processes, such as weathering.

atmosphere through different mechanisms (M T−1), *Er*

emissions to) the atmosphere (M T−1), and *Eq*

and reaction processes.

the *Ep*

**2.4. Monitoring of biogeochemical cycling**

46 Hydrology of Artificial and Controlled Experiments

be described in the following common terms:

\_\_\_ <sup>∂</sup>*<sup>E</sup>*

**Figure 7.** Diel cycles of temperatures and land-surface energy fluxes measured across the domain of one LEO landscape. Air temperatures (*Tair*) are based on all available sensors installed at three selected heights along masts above the land surface, and soil temperatures (*Tsoil*) are based on all available sensors installed at three selected depths below the surface. Energy flux (*E*) observations include the net downward radiative flux (*Rn* ), the upward surface sensible heat flux (*H*), and the downward ground heat flux into the subsurface medium (*G*). The latent heat flux was negligible due to extremely dry soil conditions. Solid lines represent whole-landscape means and shaded bounds indicate standard deviations associated with spatial variability across the landscape's domain.

well as seepage volumes per time enables determination of *Eq* . Autosamplers are installed to capture these water samples during and following all irrigation events on the landscapes. Collected rainfall and seepage samples are analyzed for major cations and anions, as well as total, organic, and inorganic carbon, in addition to pH and electrical conductivity, and a subset is analyzed for major and trace elements (Section 2.1.2).

Exchange with the atmosphere, *Ea* and *Er* , is measured using profiles of gas sampling ports installed above and within the LEO slopes. Atmospheric air can be drawn into the benchtop infrared gas analyzer to measure CO<sup>2</sup> concentrations at approximately hourly intervals (24 samples per slope; see also Section 2.1.3). The gas analysis system is flexible and can also be used for analysis of CO<sup>2</sup> isotope ratios and mole fractions of other gases (such as methane, carbon monoxide, nitrous oxide, hydrogen, carbonyl sulfide, etc.) when connected to alternative analytical instrumentation such as continuous and discrete gas samplers (e.g., laser spectrometers and gas chromatographs, respectively). The anticipated transfer processes from the atmosphere, *Ea* , that affect CO<sup>2</sup> dynamics at LEO include ecosystem uptake by photosynthesis, as well as via silicate weathering. Relevant emission processes to the atmosphere, *Er* , include a sum of autotrophic and heterotrophic respiration. In systems with well-developed atmospheric turbulence, *Ea* and *Er* are routinely determined from changes in atmospheric concentrations using eddy covariance [50–52] and flux-gradient [45] techniques. However, application of these flux-estimation methods is challenging given frequent temperature and wind speed inversions in the LEO atmospheres, and specific methodological adaptations are required to monitor ecosystem trace gas cycling (see Section 2.2). Currently, with limited expected contributions of biological activity, estimation of the weathering flux of CO<sup>2</sup> can be achieved through in-slope sensors and samplers, as well as through carbonate mass balance of seepage face discharge (see the following paragraph). Microbial respiration is anticipated to increase over time, and once plants are introduced on the landscapes, root respiration, and enhanced microbial activity associated with plant organic matter inputs will increase the biological influence on soil gas concentrations. However, the organic and inorganic carbon export and conserved element export can be used as an estimate of total weathering. The increased complexity of CO<sup>2</sup> net exchange between soil and atmosphere following the introduction of plants will require application and further development of sophisticated flux partitioning approaches to quantify abiotic and biotic components. Currently available approaches focus on partitioning net exchange of CO<sup>2</sup> into the biological gross primary productivity and ecosystem respiration components based on nighttime versus daytime assumptions (e.g., [51]). Nighttime approaches assume that only respiration occurs at night; however, they do not account for CO<sup>2</sup> uptake through weathering reactions. Daytime approaches, in turn, poorly represent daytime respiration and neglect carbonate precipitation. Combining these approaches with use of relationships between CO<sup>2</sup> flux and measured photosynthetically active radiation (PAR) as well as with available measurements of trace gases homologous to CO<sup>2</sup> , such as COS [53] and CO<sup>2</sup> isotopologues [50, 52], can help constrain the spatial and temporal mechanics of CO<sup>2</sup> flux processes at LEO and improve empirical and process-based models.

the solution phase was quantified as the product of TIC concentrations obtained via the pore water samplers over time and the moisture contents measured by co-located sensors. The study demonstrated that the estimated change in storage was consistent with the difference between incoming and outgoing carbon fluxes (**Figure 8**), validating the capacity of the LEO system to close the carbon mass balance. Employing various densities of pore water sampler data for these calculations further showed that a decrease in data density by one order of magnitude (from about 350 to 35 samples per hillslope) does not significantly affect solution

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For lithogenic elements, such as Si, Na, Ca, K, Al, and Fe, inputs and outputs to and from the atmosphere are negligible (dust deposition is minimized by the superstructure), but their mass balance is strongly impacted by weathering processes that release a fraction of these elements from rock into solutions that are exported as seepage water (i.e., "from land to rivers"). A fraction of the element mass released from rock by weathering is retained within the landscape in secondary mineral form, promoting the formation of reactive soil interfaces and transforming the pore size distribution with important feedbacks to hydrologic flows. Measuring concentrations of these elements in seepage waters enables a quantification of terrestrial-to-aquatic effluxes [54], while in-slope measurements from pore water samplers

fluxes (a; positive values indicate fluxes from the atmosphere into the soil), gas-

 concentrations (b), soil water content (SWC; c), and total inorganic carbon storage (TIC; d) of a LEO landscape over several rainfall events (indicated by gray vertical bars). TIC storage was predicted using incoming and outgoing fluxes (solid line) as well as integrated from measured concentrations in pore solutions (dot markers). Shaded bounds

storage estimates for carbon at LEO.

**Figure 8.** Time series of calculated CO<sup>2</sup>

and error bars indicate 95% confidence intervals associated with each variable.

phase CO<sup>2</sup>

Changes in landscape storage of the elements obtained using estimates of influxes and outfluxes of the hillslopes can be verified by direct measurements of the storage in the landscapes through time. This is made possible by analyzing element concentrations in (i) the solution phase collected from 496 suction lysimeters distributed across each hillslope, (ii) the gas phase obtained using 141 soil gas samplers and 48 Vaisala [CO<sup>2</sup> ] sensors, and (iii) the solid phase extracted by coring of the soil for subsequent analysis. Solution and gas sampling are nondestructive, and the main limitations on frequency and density of sampling are cost and time of the analyses. Soil coring, in turn, is destructive and has to be used conservatively in order to avoid impacting hillslope behavior (see Section 2.1.6). The unique ability to close elemental mass balances was demonstrated for carbon by [54]. The study was conducted early in the LEO project, when no vegetation was present and most of the carbon fluxes were assumed to be controlled by abiotic processes, driven by weathering of basalt substrate. We quantified atmospheric CO<sup>2</sup> consumption by basalt weathering using pore gas concentration data (from Vaisala sensors) and carbon input with rainfall and export with seepage by analysis of rainfall and seepage solutions for inorganic carbon. Storage of total inorganic carbon (TIC) in the solution phase was quantified as the product of TIC concentrations obtained via the pore water samplers over time and the moisture contents measured by co-located sensors. The study demonstrated that the estimated change in storage was consistent with the difference between incoming and outgoing carbon fluxes (**Figure 8**), validating the capacity of the LEO system to close the carbon mass balance. Employing various densities of pore water sampler data for these calculations further showed that a decrease in data density by one order of magnitude (from about 350 to 35 samples per hillslope) does not significantly affect solution storage estimates for carbon at LEO.

analytical instrumentation such as continuous and discrete gas samplers (e.g., laser spectrometers and gas chromatographs, respectively). The anticipated transfer processes from the

a sum of autotrophic and heterotrophic respiration. In systems with well-developed atmo-

tions using eddy covariance [50–52] and flux-gradient [45] techniques. However, application of these flux-estimation methods is challenging given frequent temperature and wind speed inversions in the LEO atmospheres, and specific methodological adaptations are required to monitor ecosystem trace gas cycling (see Section 2.2). Currently, with limited expected contri-

in-slope sensors and samplers, as well as through carbonate mass balance of seepage face discharge (see the following paragraph). Microbial respiration is anticipated to increase over time, and once plants are introduced on the landscapes, root respiration, and enhanced microbial activity associated with plant organic matter inputs will increase the biological influence on soil gas concentrations. However, the organic and inorganic carbon export and conserved element export can be used as an estimate of total weathering. The increased complexity of

 net exchange between soil and atmosphere following the introduction of plants will require application and further development of sophisticated flux partitioning approaches to quantify abiotic and biotic components. Currently available approaches focus on partition-

piration components based on nighttime versus daytime assumptions (e.g., [51]). Nighttime approaches assume that only respiration occurs at night; however, they do not account for

isotopologues [50, 52], can help constrain the spatial and temporal mechanics of CO<sup>2</sup>

Changes in landscape storage of the elements obtained using estimates of influxes and outfluxes of the hillslopes can be verified by direct measurements of the storage in the landscapes through time. This is made possible by analyzing element concentrations in (i) the solution phase collected from 496 suction lysimeters distributed across each hillslope, (ii) the

phase extracted by coring of the soil for subsequent analysis. Solution and gas sampling are nondestructive, and the main limitations on frequency and density of sampling are cost and time of the analyses. Soil coring, in turn, is destructive and has to be used conservatively in order to avoid impacting hillslope behavior (see Section 2.1.6). The unique ability to close elemental mass balances was demonstrated for carbon by [54]. The study was conducted early in the LEO project, when no vegetation was present and most of the carbon fluxes were assumed to be controlled by abiotic processes, driven by weathering of basalt substrate. We quanti-

(from Vaisala sensors) and carbon input with rainfall and export with seepage by analysis of rainfall and seepage solutions for inorganic carbon. Storage of total inorganic carbon (TIC) in

 uptake through weathering reactions. Daytime approaches, in turn, poorly represent daytime respiration and neglect carbonate precipitation. Combining these approaches with use of

as well as via silicate weathering. Relevant emission processes to the atmosphere, *Er*

butions of biological activity, estimation of the weathering flux of CO<sup>2</sup>

well as with available measurements of trace gases homologous to CO<sup>2</sup>

processes at LEO and improve empirical and process-based models.

gas phase obtained using 141 soil gas samplers and 48 Vaisala [CO<sup>2</sup>

dynamics at LEO include ecosystem uptake by photosynthesis,

are routinely determined from changes in atmospheric concentra-

into the biological gross primary productivity and ecosystem res-

flux and measured photosynthetically active radiation (PAR) as

consumption by basalt weathering using pore gas concentration data

, include

can be achieved through

, such as COS [53] and

] sensors, and (iii) the solid

flux

atmosphere, *Ea*

CO<sup>2</sup>

CO<sup>2</sup>

CO<sup>2</sup>

spheric turbulence, *Ea*

ing net exchange of CO<sup>2</sup>

relationships between CO<sup>2</sup>

fied atmospheric CO<sup>2</sup>

, that affect CO<sup>2</sup>

48 Hydrology of Artificial and Controlled Experiments

and *Er*

For lithogenic elements, such as Si, Na, Ca, K, Al, and Fe, inputs and outputs to and from the atmosphere are negligible (dust deposition is minimized by the superstructure), but their mass balance is strongly impacted by weathering processes that release a fraction of these elements from rock into solutions that are exported as seepage water (i.e., "from land to rivers"). A fraction of the element mass released from rock by weathering is retained within the landscape in secondary mineral form, promoting the formation of reactive soil interfaces and transforming the pore size distribution with important feedbacks to hydrologic flows. Measuring concentrations of these elements in seepage waters enables a quantification of terrestrial-to-aquatic effluxes [54], while in-slope measurements from pore water samplers

**Figure 8.** Time series of calculated CO<sup>2</sup> fluxes (a; positive values indicate fluxes from the atmosphere into the soil), gasphase CO<sup>2</sup> concentrations (b), soil water content (SWC; c), and total inorganic carbon storage (TIC; d) of a LEO landscape over several rainfall events (indicated by gray vertical bars). TIC storage was predicted using incoming and outgoing fluxes (solid line) as well as integrated from measured concentrations in pore solutions (dot markers). Shaded bounds and error bars indicate 95% confidence intervals associated with each variable.

enable characterization of the spatial and temporal variability in the trajectory of mineral transformations and soil formation [55].

#### **2.5. Monitoring of biological community composition and function**

Microbial community dynamics on LEO are monitored via soil core collection (Section 2.1.6) to identify pioneering microbial species and metabolisms and to describe the response of microbial communities to environmental forcing (e.g., rainfall) and their longer term successional patterns. This approach provides information on the long-term reciprocal impact of landscape evolution on microbial community composition and function. High-throughput amplicon sequencing of 16S rRNA genes to target the bacterial and archaeal communities revealed significant differences in relative abundances for samples collected from the LEO landscapes before and after rainfall (**Figure 9**) with distinct depth-dependent community distribution profiles of the soils (**Figure 10**). We expected microbes to be distributed nonrandomly along environmental gradients in accordance to their metabolic strategies as observed in the scaled-down mini-LEO model (**Figure 11**; [56]). The phylogenetic distribution observed in the cores extracted from LEO soils was significantly different from that of the parent material [56] and revealed heterogeneous microbial community establishment and development in an otherwise nearly homogeneous soil system. Furthermore, significant differences in pre- and post-rainfall community structure suggest a dynamic system that responds to rainfall events, which may have implications for accelerating bio-weathering rates. Additional genomic and transcriptomic sequencing efforts will reveal functional diversity (gene abundance) and gene-expression profiles, respectively, in the hillslopes. An integrated understanding of microbial community diversity, gene abundance, and functional potential alongside geochemical changes, CO<sup>2</sup> fluxes, and hydrological flow paths can potentially reveal predictive patterns of landscape evolution.

**Figure 9.** Relative abundance of the 14 most abundant bacterial and archaeal phyla in the three LEO landscapes (East,

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**Figure 10.** Bray-Curtis ordination of microbial community composition in the East (E), Center (C), and West (W) landscapes before (November) and after (December) a series of irrigation events (preliminary data). Soil depths are indicated by integers representing increments of 15 cm and starting at the surface (number 1). Depth-dependent clustering is observed for December samples and most November samples (solid-line ellipses), while November samples

from intermediate depths reveal a more widely distributed pattern (dashed-line ellipse).

Center, and West) before (November) and after (December) a series of irrigation events (preliminary data).

Plant community function, composition, and organization will be monitored through a blend of direct and remote-sensing approaches. Using the personnel transport system that operates over the LEO structure, we will measure leaf-level carbon and water exchange to inform our mass balance equations and to examine interspecific variation in plant function, as it is extensively done outside model systems in critical zone research [57, 58]. Coupling these point-specific measures with multispectral and thermal imaging (Section 2.1.4) will provide spatial patterns of function across the artificial landscape, and the repeated image acquisition through time will provide insights into temporal dynamics. Hyperspectral analysis of ecosystems can yield remarkable insights into vegetation function, and "signatures" of spectra specific to plant species can also be used for mapping distribution across the landscape. The use of narrow (<5 nm) band spectrometers allows for the observation of many ecological features such as pigment composition and content, canopy water content, dry plant litter and wood, and foliar chemistry (e.g., [59] and references therein). Photosynthesis, or gross primary production (GPP), is the largest global land surface carbon flux [60, 61], but the spatially explicit approaches to quantify GPP based on meteorology-driven land surface carbon cycle models, MODIS-based remote sensing, and typical eddy flux tower measurement driven models carry large uncertainties [62, 63]. GPP is directly correlated with solar-induced chlorophyll fluorescence (ChF), because both are driven by absorbed radiation [64–67]. This correlation Controlled Experiments of Hillslope Coevolution at the Biosphere 2 Landscape Evolution… http://dx.doi.org/10.5772/intechopen.72325 51

enable characterization of the spatial and temporal variability in the trajectory of mineral

Microbial community dynamics on LEO are monitored via soil core collection (Section 2.1.6) to identify pioneering microbial species and metabolisms and to describe the response of microbial communities to environmental forcing (e.g., rainfall) and their longer term successional patterns. This approach provides information on the long-term reciprocal impact of landscape evolution on microbial community composition and function. High-throughput amplicon sequencing of 16S rRNA genes to target the bacterial and archaeal communities revealed significant differences in relative abundances for samples collected from the LEO landscapes before and after rainfall (**Figure 9**) with distinct depth-dependent community distribution profiles of the soils (**Figure 10**). We expected microbes to be distributed nonrandomly along environmental gradients in accordance to their metabolic strategies as observed in the scaled-down mini-LEO model (**Figure 11**; [56]). The phylogenetic distribution observed in the cores extracted from LEO soils was significantly different from that of the parent material [56] and revealed heterogeneous microbial community establishment and development in an otherwise nearly homogeneous soil system. Furthermore, significant differences in pre- and post-rainfall community structure suggest a dynamic system that responds to rainfall events, which may have implications for accelerating bio-weathering rates. Additional genomic and transcriptomic sequencing efforts will reveal functional diversity (gene abundance) and gene-expression profiles, respectively, in the hillslopes. An integrated understanding of microbial community diversity, gene

**2.5. Monitoring of biological community composition and function**

abundance, and functional potential alongside geochemical changes, CO<sup>2</sup>

logical flow paths can potentially reveal predictive patterns of landscape evolution.

Plant community function, composition, and organization will be monitored through a blend of direct and remote-sensing approaches. Using the personnel transport system that operates over the LEO structure, we will measure leaf-level carbon and water exchange to inform our mass balance equations and to examine interspecific variation in plant function, as it is extensively done outside model systems in critical zone research [57, 58]. Coupling these point-specific measures with multispectral and thermal imaging (Section 2.1.4) will provide spatial patterns of function across the artificial landscape, and the repeated image acquisition through time will provide insights into temporal dynamics. Hyperspectral analysis of ecosystems can yield remarkable insights into vegetation function, and "signatures" of spectra specific to plant species can also be used for mapping distribution across the landscape. The use of narrow (<5 nm) band spectrometers allows for the observation of many ecological features such as pigment composition and content, canopy water content, dry plant litter and wood, and foliar chemistry (e.g., [59] and references therein). Photosynthesis, or gross primary production (GPP), is the largest global land surface carbon flux [60, 61], but the spatially explicit approaches to quantify GPP based on meteorology-driven land surface carbon cycle models, MODIS-based remote sensing, and typical eddy flux tower measurement driven models carry large uncertainties [62, 63]. GPP is directly correlated with solar-induced chlorophyll fluorescence (ChF), because both are driven by absorbed radiation [64–67]. This correlation

fluxes, and hydro-

transformations and soil formation [55].

50 Hydrology of Artificial and Controlled Experiments

**Figure 9.** Relative abundance of the 14 most abundant bacterial and archaeal phyla in the three LEO landscapes (East, Center, and West) before (November) and after (December) a series of irrigation events (preliminary data).

**Figure 10.** Bray-Curtis ordination of microbial community composition in the East (E), Center (C), and West (W) landscapes before (November) and after (December) a series of irrigation events (preliminary data). Soil depths are indicated by integers representing increments of 15 cm and starting at the surface (number 1). Depth-dependent clustering is observed for December samples and most November samples (solid-line ellipses), while November samples from intermediate depths reveal a more widely distributed pattern (dashed-line ellipse).

of electrical resistivity tomography (ERT) provides an opportunity to observe nondestructively the subsurface structure changes of the initially homogenous crushed basalt tephra in response to hydrological (e.g., surface-subsurface water interactions) and biogeochemical processes. Through geophysical inversion of the three-dimensional resistivity field recorded by the ERT system, changes in soil physicochemical properties (e.g., pore volume) can be mapped at high spatial resolution. The combined above observations, especially within the saturated zone, can resolve the spatial distribution of biogeochemical transformations due to

Controlled Experiments of Hillslope Coevolution at the Biosphere 2 Landscape Evolution…

Pore water geochemistry can be used to predict the initial stages of basalt weathering, while soil coring samples can validate predictions based on pore water geochemistry. The coupling of pore water data and soil coring data enables measurements of elemental partitioning during the basalt weathering. Therefore, the cycle of a given element on the landscape can also be

where subscript *aq* represents the aqueous phase (where concentrations *E* can be measured from pore water samplers), subscript *s* represents the solid phase (where concentrations *E* are derived from soil coring), and subscript *g* represents the gas phase (where concentrations *E* can be obtained from gas sensors and samplers). The gas-phase term only applies when quantifying the partitioning of elements that form gaseous compounds, such as most importantly

**Figure 12** demonstrates the onset of carbon and nitrogen accumulation on the LEO hillslopes as measured from soil cores. While organic carbon and total nitrogen accumulations are mostly limited to the soil surface, inorganic carbon tends to precipitate in a lens in the center of the hillslope. This supports observations of developing heterogeneity in calcite saturation indices on the slopes [55]. Collected soil samples are also analyzed by synchrotron-based (for higher sensitivity) X-ray diffraction to examine changes in mineral composition of the soil, particularly formation of secondary crystalline minerals. By further examining the change of element availability in the solid phase by sequential extraction, it is possible to characterize operationally the formation of X-ray amorphous phases and to better understand geochemical transformations in the soil. In addition to bulk measurements, stabilization of organic carbon in the soils―an integral part of soil formation and important mechanism of carbon sequestration from the atmosphere―is being examined for selected soil samples by Mossbauer spectroscopy, high-resolution transmission electron microscopy (HRTEM), scanning electron microscopy (SEM), high spatial resolution secondary ion mass spectrometry (NanoSIMS) analysis, and X-ray photoelectron spectroscopy (XPS). Release and fractionation of dissolved organic matter are also being examined using Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) analysis of pore waters and soil sample extracts. The microbiological analysis of the soil cores (Sections 2.1.6 and 2.5) can address variations in carbon cycling and nutrient availability in addition to linking biological and abiotic processes during the initial stages of basalt

<sup>∂</sup>*<sup>t</sup>* (4)

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53

<sup>∂</sup>*<sup>t</sup>* <sup>=</sup> <sup>∂</sup>*Eaq* \_\_\_\_ <sup>∂</sup>*<sup>t</sup>* <sup>+</sup> ∂*E*\_\_\_*s* <sup>∂</sup>*<sup>t</sup>* <sup>+</sup> ∂*E* \_\_\_*<sup>g</sup>*

abiotic and biotic processes in a pedogenic environment.

described by rewriting Eq. 3 as follows:

\_\_\_ <sup>∂</sup>*<sup>E</sup>*

weathering and pedogenesis.

carbon.

**Figure 11.** Relative abundance of two major phyla (*Cyanobacteria* and *Actinobacteria*) across the lateral (*x*-coordinate; long axis) and vertical (*z*-coordinate) dimensions of the miniLEO small-scale replicate model. Rectangles indicate unique voxels of volume 200 cm<sup>3</sup> (increments of 20 cm in the lateral and 10 cm in the vertical direction). Samples were collected from each voxel, followed by DNA extraction and high-throughput sequence analysis.

is the result of a reduction in ChF and photosynthesis yield following increases in heat dissipation under high light conditions. Chlorophyll fluorescence is the re-emission of absorbed photosynthetically active radiation (400–700 nm) by the plants at higher wavelengths in the visible red and near infrared (660–800 nm). We will use spectral features around the higher wavelength because the lower band is affected by the re-absorption of chlorophyll pigments, while the higher one is minimally affected by chlorophyll re-absorption effects [68].

#### **2.6. Monitoring of subsurface structural development and pedogenesis**

The dense sensor and sampler arrays at LEO offer the capabilities (i) to characterize in great detail the spatial and temporal variability of solution chemistry for a small ZOB (via solution sampling and analysis; see Sections 2.1.2 and 2.4) and (ii) to monitor in high resolution the subsurface structural development (via electrical resistivity tomography surveys and soil coring; see Sections 2.1.5 and 2.1.6) critical during incipient stages of landscape evolution. Together, these capabilities enable the establishment of cause-and-effect relations in soil formation. Known inputs of rainwater, which act as both solvent and transport vector, drive the dissolution of primary mineral surfaces and increase in pore water saturation with respect to secondary mineral phases, including carbonates. Precipitating solids can passivate the surfaces of primary minerals against further dissolution [69]. They also contribute to stabilization of organic carbon against leaching, to mineralization by interacting with newly formed minerals [70–72], and to soil retention of plant-available water and surface-exchangeable nutrients in plant-available form.

Dissolution of primary minerals and precipitation of clay-sized secondary minerals lead to shifts in particle size distribution of the soils toward finer materials. This is predicted to be correlated to flow patterns across the landscapes [8]. In addition, precipitation of poorly crystalline silicates, phyllosilicate clays, and sesquioxides as well as additions of carbon, initially from microbial activity and later from plant root exudation, promote aggregation of the primary particles resulting in changes of the hillslopes' physical structure. The application of electrical resistivity tomography (ERT) provides an opportunity to observe nondestructively the subsurface structure changes of the initially homogenous crushed basalt tephra in response to hydrological (e.g., surface-subsurface water interactions) and biogeochemical processes. Through geophysical inversion of the three-dimensional resistivity field recorded by the ERT system, changes in soil physicochemical properties (e.g., pore volume) can be mapped at high spatial resolution. The combined above observations, especially within the saturated zone, can resolve the spatial distribution of biogeochemical transformations due to abiotic and biotic processes in a pedogenic environment.

Pore water geochemistry can be used to predict the initial stages of basalt weathering, while soil coring samples can validate predictions based on pore water geochemistry. The coupling of pore water data and soil coring data enables measurements of elemental partitioning during the basalt weathering. Therefore, the cycle of a given element on the landscape can also be described by rewriting Eq. 3 as follows:

$$\frac{\partial E}{\partial t} = \frac{\partial E\_{eq}}{\partial t} + \frac{\partial E\_s}{\partial t} + \frac{\partial E\_g}{\partial t} \tag{4}$$

where subscript *aq* represents the aqueous phase (where concentrations *E* can be measured from pore water samplers), subscript *s* represents the solid phase (where concentrations *E* are derived from soil coring), and subscript *g* represents the gas phase (where concentrations *E* can be obtained from gas sensors and samplers). The gas-phase term only applies when quantifying the partitioning of elements that form gaseous compounds, such as most importantly carbon.

is the result of a reduction in ChF and photosynthesis yield following increases in heat dissipation under high light conditions. Chlorophyll fluorescence is the re-emission of absorbed photosynthetically active radiation (400–700 nm) by the plants at higher wavelengths in the visible red and near infrared (660–800 nm). We will use spectral features around the higher wavelength because the lower band is affected by the re-absorption of chlorophyll pigments,

**Figure 11.** Relative abundance of two major phyla (*Cyanobacteria* and *Actinobacteria*) across the lateral (*x*-coordinate; long axis) and vertical (*z*-coordinate) dimensions of the miniLEO small-scale replicate model. Rectangles indicate unique

(increments of 20 cm in the lateral and 10 cm in the vertical direction). Samples were collected

The dense sensor and sampler arrays at LEO offer the capabilities (i) to characterize in great detail the spatial and temporal variability of solution chemistry for a small ZOB (via solution sampling and analysis; see Sections 2.1.2 and 2.4) and (ii) to monitor in high resolution the subsurface structural development (via electrical resistivity tomography surveys and soil coring; see Sections 2.1.5 and 2.1.6) critical during incipient stages of landscape evolution. Together, these capabilities enable the establishment of cause-and-effect relations in soil formation. Known inputs of rainwater, which act as both solvent and transport vector, drive the dissolution of primary mineral surfaces and increase in pore water saturation with respect to secondary mineral phases, including carbonates. Precipitating solids can passivate the surfaces of primary minerals against further dissolution [69]. They also contribute to stabilization of organic carbon against leaching, to mineralization by interacting with newly formed minerals [70–72], and to soil retention of plant-available water and surface-exchangeable nutrients in

Dissolution of primary minerals and precipitation of clay-sized secondary minerals lead to shifts in particle size distribution of the soils toward finer materials. This is predicted to be correlated to flow patterns across the landscapes [8]. In addition, precipitation of poorly crystalline silicates, phyllosilicate clays, and sesquioxides as well as additions of carbon, initially from microbial activity and later from plant root exudation, promote aggregation of the primary particles resulting in changes of the hillslopes' physical structure. The application

while the higher one is minimally affected by chlorophyll re-absorption effects [68].

**2.6. Monitoring of subsurface structural development and pedogenesis**

from each voxel, followed by DNA extraction and high-throughput sequence analysis.

plant-available form.

voxels of volume 200 cm<sup>3</sup>

52 Hydrology of Artificial and Controlled Experiments

**Figure 12** demonstrates the onset of carbon and nitrogen accumulation on the LEO hillslopes as measured from soil cores. While organic carbon and total nitrogen accumulations are mostly limited to the soil surface, inorganic carbon tends to precipitate in a lens in the center of the hillslope. This supports observations of developing heterogeneity in calcite saturation indices on the slopes [55]. Collected soil samples are also analyzed by synchrotron-based (for higher sensitivity) X-ray diffraction to examine changes in mineral composition of the soil, particularly formation of secondary crystalline minerals. By further examining the change of element availability in the solid phase by sequential extraction, it is possible to characterize operationally the formation of X-ray amorphous phases and to better understand geochemical transformations in the soil. In addition to bulk measurements, stabilization of organic carbon in the soils―an integral part of soil formation and important mechanism of carbon sequestration from the atmosphere―is being examined for selected soil samples by Mossbauer spectroscopy, high-resolution transmission electron microscopy (HRTEM), scanning electron microscopy (SEM), high spatial resolution secondary ion mass spectrometry (NanoSIMS) analysis, and X-ray photoelectron spectroscopy (XPS). Release and fractionation of dissolved organic matter are also being examined using Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) analysis of pore waters and soil sample extracts. The microbiological analysis of the soil cores (Sections 2.1.6 and 2.5) can address variations in carbon cycling and nutrient availability in addition to linking biological and abiotic processes during the initial stages of basalt weathering and pedogenesis.

these research foci and early results from initial experiments are presented. The process research at LEO is complemented by the development of hillslope-integrated parametrizations and distributed coupled-process modeling approaches that are hoped to ultimately allow improved prediction of real-world systems' behavior in a changing environment. These modeling approaches are described first (Section 3.1) and with emphasis on hydrologic predictions.

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In recent years, there has been a paradigm shift in our understanding of flow and transport at watershed scales and in our approaches to prediction. The complexity and heterogeneity of water movement within individual landscape units have been recognized in hillslopes [73, 74], riparian areas [75, 76], and within streams and their hyporheic zone [77]. This has led to calls for new predictive approaches that go beyond the traditional continuum models (i.e., Richards and Saint-Venant equations for flow and convection-dispersion/diffusion equations for transport) [40, 78–80], as these generally rely on calibrated "effective" property values to replace the spatially distributed properties of the landscape—those are essentially unknow-

New approaches have sought ways to represent flow and transport directly at the scales of interest, with the expectation that the new equations may differ in form, not just in the parameters [79], from the continuum-scale equations. The concept of a representative elementary watershed, or REW [78, 81–83], provides a framework for representing flow through individual landscape elements and in a river network based on a rigorous time-space averaging of the conservation laws for mass, energy, momentum, and entropy. However, these equations are not complete. They require specification of "closure relations" that specify the boundary fluxes exchanged between these landscape elements in terms of their states and are parameterized by measurable properties of the landscape. These closure relations must represent the aggregate effect of the unresolved sub-REW heterogeneities and flow complexity without resolving them

explicitly, and they have been termed the "Holy Grail" of scientific hydrology [78].

An overarching objective of the LEO project is to develop closure relations for hillslope-scale hydrologic flux and transport [7]. These closure relations are parameterizations of the fluxes that cross boundaries between hydrologically relevant units of the landscape [78, 81]—an elementary example is a storage-discharge relation [84, 85]. Taken broadly, such parameterizations are a component of all hydrologic models, but LEO is a useful experimental tool for developing closure relations at the scale of hillslopes [7]. At LEO, it is possible to observe boundary fluxes—and how they emerge from the distribution of internal state variables—with a precision not possible in real landscapes and at a scale not possible in bench-top experiments. Through experimentation and iterative modeling using both lumped and highly resolved models, efforts at LEO are driving toward a suite of hillslope closure relationships that (ideally) can be parameterized on the basis of the observable physical structure of the landscape. Work at LEO has focused on developing hillslope-scale closure relationships for discharge and for transport both by building on and testing existing theory, as well as by developing new approaches. Hillslope closure relations predicting discharge have been developed from the principles of hydraulic groundwater theory [86–88] and are being compared to both the

**3.1. Changing paradigms for hydrologic prediction at the hillslope scale**

able at catchment scales using current technology.

**Figure 12.** Distribution of organic carbon (a), inorganic carbon (b), and total nitrogen (c) over a cross section of a LEO hillslope 3 years after inception (preliminary data). The cross section spans the depth (*z*-coordinate) and length (*x*-coordinate) of the hillslope through its central plane (i.e., *y*-coordinate equal to zero).
