**Role of Hydraulic Conductivity Uncertainties in Modeling Water Flow through Forest Watersheds**

Marie-France Jutras and Paul A. Arp

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/56900

## **1. Introduction**

[103] Comstock JP, Sperry JS. Tansley rereview no. 119. Some theoretical considerations of optimal conduit length for water transport in plants. New Phytologist 2000;148

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[106] Hejnowicz Z. Anatomia i histogeneza roślin naczyniowych. Warszawa: Wydawnict‐

life forms. Plant Cell & Environment 2003;26 163-182.

195-218.

32 Hydraulic Conductivity

1994;75 1736-1752.

wo Naukowe PWN; 2002.

Soil hydraulic conductivities at saturation (Ksat) are highly variable in space and time. For example, Ksat varies along vertical and lateral flow paths depending on directional changes in soil texture, density, and structure [1, 2, 3]. Temporal changes are caused by changes in soil structure and bulk density (Db) in response to, e.g., (i) gradual soil formation processes, and (ii) operationally induced soil compaction or de-compaction due to various land-uses [4]. Changes in weather and climate also affect Ksat through freezing and thawing [5, 6], swelling and shrinking [7], extent of rooting and related organic matter build-up [8]. This chapter explores how changes in hydraulic conductivity may affect modelled rates of water flow through forested watersheds, with flows referring to infiltration, percolation, run-off, inter‐ flow, base flow, and stream discharge. This is done by way of sensitivity analyses centered on two well-studied watershed studies, referring to Moosepit Brook, Nova Scotia [1, 9] and Turkey Lakes, Ontario [1, 10]. Also addressed are:

Ksat impacts on the retention of soil water and the transmittance of the same towards streams as influenced by evapotranspiration from open conditions to forests [14];

the relationship between Ksat and the state of organic matter decomposition, as characterized by the von Post index from fibric (H1) to fully humified or sapric (H10) [11, 12, 13].

The sensitivity analysis is based on using the forest hydrology model ForHyM2 [1, 15] to determine how scenario-set Ksat variations affect soil water retention and flow including stream discharge through the watersheds. The scenarios vary Ksat by changing organic matter (OM) and sand content from their actual values within the 0 to 100% per soil weight range.

#### **2. Quantitative background**

The equations used for estimating the sensitivity of Ksat on account of changes in soil texture, structure, density and organic matter content is given by [16], as follows:

$$\log\_{10}{K\_{\text{sat}}} = a + 7.94 \log\_{10}{\text{(D}\_{\text{p}} \text{ - D}\_{\text{b}})} + 1.96 \text{ SAND} \tag{1}$$

$$\mathbf{D}\_{b} = \frac{1.23 \star \text{(D}\_{p} \cdot 1.23 \cdot 0.75 \,\text{SAND)} \text{(1} \cdot \exp\left\{- \, 0.0106 \,\text{DEPTH}\right\}}{1 \star 6.83 \,\text{OM}} \tag{2}$$

$$\frac{1}{\text{Dp}} = \frac{\text{OM}}{\text{Dp}\_{\text{com}}} + \frac{1 \cdot \text{OM}}{\text{Dp}\_{\text{min}}} \tag{3}$$

*ϕ* =100.38 - 76.7*Db* (R2

where vP is the von post index (Table 2) and ϕ is the soil porosity. Fig. 2 illustrates the relationship between the von Post adjusted log10Ksat(Eqs. 1, 4-7) and log10Ksat based on literature sources. Fig. 2 shows (i) a plot of actual versus best-fitted Ksat values (left), and actual as well as best-fitted Ksat values with increasing organic matter humification in peaty soils (right).

**condition log10Ksat**

**Fibric** H1 Water colourless 3.15 1406.48 0.05 1.44

*a* =(2.05 ± 0.2) - (0.046 ± 0.004)*vP*<sup>2</sup>

H3 Water brown, muddy; no peat

no peat

Water dark brown; 33% peat

brown, 50% peat

uniform

no water

**Table 1.** von Post humification index, with Ksat, Db and Dp for 100% OM content according to Eqs. 1 and 4 to 7;

**Sapric** H8 66% peat, Water pasty -0.32 0.48 0.16 1.34

H7 Any water very dark

H9 Nearly all peat; paste

H10 100% peat paste;

**Peat Class von Post Index Squeeze Test: Exudate**

**Mesic** H4 Water dark brown, muddy;

H6

Decomposition: none to slight; Amorphous content: low

Fibers still recognisable; Decomposition: moderate to strong; Amorphous content: medium

Fibers unrecognisable; Decomposition: very strong to complete; Amorphous content: high

1Eq. 1 from [16] 2Eqs. 4-5 from [12]

adapted from [21] and [11]

= 0.99) (6)

**Ksat <sup>1</sup> cm h-1**

2.55 356.24 0.08 1.39

2.15 141.08 0.10 1.37

1.09 12.40 0.13 1.36

0.43 2.72 0.15 1.35



**Db <sup>2</sup> g cm-1**

**Dp <sup>2</sup> g cm-1** 35

= 0.89) (7)

http://dx.doi.org/10.5772/56900

(R2

Role of Hydraulic Conductivity Uncertainties in Modeling Water Flow through Forest Watersheds

H2 Water yellowish 2.88 756.62 0.07 1.41

H5 Water muddy; some peat 1.66 46.20 0.11 1.36

where, Dpom is the particle density of OM (1.3 gcm-3), Dpmin is the particle density of mineral soils (2.65gcm-3), SAND and OM are dry soil weight fractions (fine earth fraction only), DEPTH is the mid depth of each soil layer (cm), "a" represents Ksat when Dp-Db = 1 g cm3 and SAND = 0%. Fig. 1 illustrates how variations in Db, OM, and SAND affect Ksat in general.

**Figure 1.** Left and middle: how log10Ksat varies with increasing OM, and sand fraction. Right: Changes in log10Ksat and Db when OM and Sand fraction = 0.

For organic soils, it is important to adjust a, Db, and Dp in Eqs. 1 to 3 by extent of organic matter decomposition and humification [12, 11, 17, 13, 18, 19]. These adjustments are based on the von Post humification index ([11, 20], Table 1) as follows:

$$D\_b = 0.035 + 0.0159 \, vP \, \text{(R2 = 0.93)}\tag{4}$$

$$D\_{pom} = \frac{D\_b}{1 - \phi} \tag{5}$$

Role of Hydraulic Conductivity Uncertainties in Modeling Water Flow through Forest Watersheds http://dx.doi.org/10.5772/56900 35

$$
\phi = 100.38 \text{--} 76.7 D\_b \text{ (R}^2 = 0.99\text{)}\tag{6}
$$

$$a = \text{(2.05} \pm 0.2) - \text{(0.046} \pm 0.004)vP^2 \text{ (R}^2 = 0.89) \tag{7}$$

where vP is the von post index (Table 2) and ϕ is the soil porosity. Fig. 2 illustrates the relationship between the von Post adjusted log10Ksat(Eqs. 1, 4-7) and log10Ksat based on literature sources. Fig. 2 shows (i) a plot of actual versus best-fitted Ksat values (left), and actual as well as best-fitted Ksat values with increasing organic matter humification in peaty soils (right).


2Eqs. 4-5 from [12]

**2. Quantitative background**

34 Hydraulic Conductivity

The equations used for estimating the sensitivity of Ksat on account of changes in soil texture,

1 - OM Dpmin

where, Dpom is the particle density of OM (1.3 gcm-3), Dpmin is the particle density of mineral soils (2.65gcm-3), SAND and OM are dry soil weight fractions (fine earth fraction only), DEPTH is the mid depth of each soil layer (cm), "a" represents Ksat when Dp-Db = 1 g cm3 and SAND =

0 0.25 0.5 0.75 1


0.0 0.5 1.0 1.5 2.0

Sand=0 OM=0

Predicted Db, g/cm


Predicted Log10 (Ksat, cm/h)

*Db* =0.035 + 0.0159 *vP* (R2 = 0.93) (4)

<sup>1</sup> - *<sup>ϕ</sup>* (5)

0

1

2

Sandwsoil

**Figure 1.** Left and middle: how log10Ksat varies with increasing OM, and sand fraction. Right: Changes in log10Ksat and

For organic soils, it is important to adjust a, Db, and Dp in Eqs. 1 to 3 by extent of organic matter decomposition and humification [12, 11, 17, 13, 18, 19]. These adjustments are based on the

*Dpom* <sup>=</sup> *Db*

<sup>D</sup>*<sup>b</sup>* <sup>=</sup> 1.23 <sup>+</sup> (Dp - 1.23 - 0.75 SAND)(1 - exp ( - 0.0106 DEPTH)

0%. Fig. 1 illustrates how variations in Db, OM, and SAND affect Ksat in general.

log10*Ksat* =*a* + 7.94log10(Dp - Db) + 1.96 SAND (1)

<sup>1</sup> <sup>+</sup> 6.83 OM (2)

(3)

structure, density and organic matter content is given by [16], as follows:

1 Dp <sup>=</sup> OM Dpom +


0 1 2

Predicted Log10 (Ksat, cm/h)

von Post humification index ([11, 20], Table 1) as follows:

0 0.25 0.5 0.75 1

OMwsoil

Db when OM and Sand fraction = 0.


Predicted Log10 (Ksat, cm/h)

**Table 1.** von Post humification index, with Ksat, Db and Dp for 100% OM content according to Eqs. 1 and 4 to 7; adapted from [21] and [11]

**6.** Double actual OM

9, Subsoil = 10.

**Watershed characteristics**

**7.** No OM throughout entire soil profile

**8.** 100% OM throughout entire soil profile using the von Post profile of FF = 3, A&B = 5, C =

Abbreviation MP TL

Latitude (N) 44°28' 47°03'

Longitude (W) 65°03' 84°25'

Area (ha) 1670 1050

Elevation (m) 100-150 350-400

Slope (%) 1 8

Rooting habit Medium Deep

Deciduous:coniferous 50:50 100:0

Forest floor depth (cm) 5 7

Subsoil: depth (cm); texture 70; LS 100; LS

greenschist slate

Mean yearly temperature (°C) 7.02 4.52

Mean yearly snow depth (cm) 5 23

**Table 2.** Site description for the Moosepit Brook and Turkey Lakes watersheds.

Mean yearly rainfall (mm) 1140 790

Model Run Years 1999-2004 1997-2004

Land Formation Glacial till Ablation till on basal till

Topography Rolling Undulating to rolling

Mineral soil: depth (cm); texture 50; SL 60; SilL

Bedrock Metamorphic

**Moosepit Brook Turkey Lakes Nova Scotia (NS) Ontario (ON)**

Role of Hydraulic Conductivity Uncertainties in Modeling Water Flow through Forest Watersheds

Metavolcanic basalt

http://dx.doi.org/10.5772/56900

37

**Figure 2.** Best-fitted log10Ksat versus actual data from New Brunswick and Nova Scotai, Canada, as seen in [1] and [16] (left), best-fitted log10Ksat versus von Post humification index from literature sources (right).

## **3. Methods**

The two study areas, Moosepit Brook and Turkey Lakes, have contrasting terrain (generally flat versus hummocky), climate (maritime versus continental), vegetation (mostly coniferous versus deciduous), and soil parent material (ablation till versus basal till) (Table 2, Fig. 3)

Eight scenarios were adopted to examine the impacts of Ksat variations on water flow through these locations, as follows: the actual soil conditions in terms of soil texture and organic matter (Scenario 1, Table 3), varying the soil texture sand, silt, or clay (Scenarios 2, 3, and 4), and varying the soil organic matter content (Scenarios, 5, 6, 7, and 8).

#### **Scenario 1:**

**1.** Actual soil texture and OM content

#### **Scenarios 2 to 4: Changing soil texture**


#### **Scenarios 5 to 8: Changing organic matter content**

**5.** Half actual OM

**6.** Double actual OM




**Figure 2.** Best-fitted log10Ksat versus actual data from New Brunswick and Nova Scotai, Canada, as seen in [1] and [16]

The two study areas, Moosepit Brook and Turkey Lakes, have contrasting terrain (generally flat versus hummocky), climate (maritime versus continental), vegetation (mostly coniferous versus deciduous), and soil parent material (ablation till versus basal till) (Table 2, Fig. 3)

Eight scenarios were adopted to examine the impacts of Ksat variations on water flow through these locations, as follows: the actual soil conditions in terms of soil texture and organic matter (Scenario 1, Table 3), varying the soil texture sand, silt, or clay (Scenarios 2, 3, and 4), and

0 2 4 6 8 10

Eq. 1 (R =0.89) Gafni and Brooks 1990 Maelstom 1923 Gafni 1986

2

von Post Humification Index


log10Ksat (cm hr-1)

0

2

4

Best-fitted log10Ksat (cm hr-1)

(left), best-fitted log10Ksat versus von Post humification index from literature sources (right).

varying the soil organic matter content (Scenarios, 5, 6, 7, and 8).

**1.** Actual soil texture and OM content **Scenarios 2 to 4: Changing soil texture 2.** Sand = 95% sand, 1% silt, 4% clay **3.** Silt = 7% sand, 87% silt, 6% clay

**4.** Heavy clay = 25% sand, 25% silt, 50% clay

**Scenarios 5 to 8: Changing organic matter content**


Actual log10Ksat

**3. Methods**

**Scenario 1:**

**5.** Half actual OM

 (cm hr-1)

1

3

36 Hydraulic Conductivity

R2 = 0.788



**Table 2.** Site description for the Moosepit Brook and Turkey Lakes watersheds.

shrub-covered bogs with no trees). This is to demonstrate how varying Ksat levels from high

Role of Hydraulic Conductivity Uncertainties in Modeling Water Flow through Forest Watersheds

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39

Each scenario was used for initializing the ForHyM2 requirements for soil texture and organic matter by soil layer, with the A and B layers representing the top soil conditions, and the C layer representing the subsoil conditions Table 2). Layer-specific values for Dp, Db and Ksat were then generated automatically via Eqs. 1 to 3. All other site-specific input requirements for daily weather (rain, snow air temperature), slope, aspect, elevation and soil layer depths were kept the same. Scenario 1 was used to refine the Eq. 1 estimates for Ksat, by adjusting the Ksat adjustment multipliers for surface run-off, interflow (forest floor, A&B layers combined), baseflow (C layers combined), infiltration, and soil percolation from the forest floor to the topsoil, and from the topsoil to the subsoil. The calibrations were done by matching modeled with actual stream discharge a the daily level, using local weather records for daily rain, snow and air temperature as model input. Modelled snowpack depth was also calibrated using daily snowpack data. The ForHyM2 model runs were done for 1999 – 2004 for Moosepit Brook, and

**Figure 4.** Mineral texture class triangle for fine soil showing texture classes for scenarios 1 - 4 (adapted from CANSIS

The results of this analysis are shown in Tables 3 to 8 and in Figs. 5 to 12 for the Moosepit Brook and Turkey Lakes study areas. Tables 3 and 4 inform about the Scenario-based changes on Dp, Db and Ksat for each of the two sites by topsoil and subsoil. The Db numbers indicate that the subsoil at both locations is compacted, with Ksat values typically 10 to 50 times lower in the

to low increase the amount of water available for evapotranspiration

for 1997-2002 for Turkey Lakes.

2000).

**4. Results**

**Figure 3.** Locator maps for the Turkey Lakes (left) and Moosepit Brook (right) study areas.



**Table 3.** Actual scenario soil input for Moosepit Brook and Turkey Lakes.

The sand texture percentages for scenarios 2-4 demonstrate the effects of varying texture on Ksat from sandy and sandy loam soils to silty and clayey soils (Fig. 4). The organic matter levels for scenarios 5-8 were chosen to demonstrate the effects of changing the organic matter on content from very small in mineral soils to fully organic soils. For the 100% organic soil condition (Scenario 8), three sub-scenarios were chosen to account for variations in forest cover from 100 % (fully forested), 50% (varying from forested to boggy) and 0% (open moss and shrub-covered bogs with no trees). This is to demonstrate how varying Ksat levels from high to low increase the amount of water available for evapotranspiration

Each scenario was used for initializing the ForHyM2 requirements for soil texture and organic matter by soil layer, with the A and B layers representing the top soil conditions, and the C layer representing the subsoil conditions Table 2). Layer-specific values for Dp, Db and Ksat were then generated automatically via Eqs. 1 to 3. All other site-specific input requirements for daily weather (rain, snow air temperature), slope, aspect, elevation and soil layer depths were kept the same. Scenario 1 was used to refine the Eq. 1 estimates for Ksat, by adjusting the Ksat adjustment multipliers for surface run-off, interflow (forest floor, A&B layers combined), baseflow (C layers combined), infiltration, and soil percolation from the forest floor to the topsoil, and from the topsoil to the subsoil. The calibrations were done by matching modeled with actual stream discharge a the daily level, using local weather records for daily rain, snow and air temperature as model input. Modelled snowpack depth was also calibrated using daily snowpack data. The ForHyM2 model runs were done for 1999 – 2004 for Moosepit Brook, and for 1997-2002 for Turkey Lakes.

**Figure 4.** Mineral texture class triangle for fine soil showing texture classes for scenarios 1 - 4 (adapted from CANSIS 2000).

## **4. Results**

Turkey Lakes, ONT

0 500 1,000 2,000

Kilometres

Kilometres

**Figure 3.** Locator maps for the Turkey Lakes (left) and Moosepit Brook (right) study areas.

**(cm) Sand (%) Silt (%) Clay (%) OM (%)**

**Table 3.** Actual scenario soil input for Moosepit Brook and Turkey Lakes.

**Moosepit Brook, NS Turkey Lakes, ONT**

A 21 66 24 10 4.5 15 66 24 10 5 B 21 66 24 10 9 30 66 24 10 3 C 50+ 82 12 6 4.5 50+ 22 65 13 2

The sand texture percentages for scenarios 2-4 demonstrate the effects of varying texture on Ksat from sandy and sandy loam soils to silty and clayey soils (Fig. 4). The organic matter levels for scenarios 5-8 were chosen to demonstrate the effects of changing the organic matter on content from very small in mineral soils to fully organic soils. For the 100% organic soil condition (Scenario 8), three sub-scenarios were chosen to account for variations in forest cover from 100 % (fully forested), 50% (varying from forested to boggy) and 0% (open moss and

**Depth (cm)**

**Sand**

0 1.25 2.5 5

*Actual watershed inputs: Scenario 1*

**Depth**

**Horizon**

38 Hydraulic Conductivity

Moosepit Brook, NS

0 2 4 8

Kilometres

**(%) Silt (%) Clay (%) OM (%)**

The results of this analysis are shown in Tables 3 to 8 and in Figs. 5 to 12 for the Moosepit Brook and Turkey Lakes study areas. Tables 3 and 4 inform about the Scenario-based changes on Dp, Db and Ksat for each of the two sites by topsoil and subsoil. The Db numbers indicate that the subsoil at both locations is compacted, with Ksat values typically 10 to 50 times lower in the subsoil than in the topsoil. Since the soil texture is sandier at Moosepit Brook than at Turkey Lakes,KsatvaluesremainhigherinthesubsoilatMoosepitBrookthanatTurkeyLakes.Changing the topsoil texture from the actual values changes Ksat by about 5x upwards, and by about 10x downwards at both locations. These Ksat changes are similar for the somewhat coarser subsoil at Moosepit Brook. In contrast, subsoil Ksat is not much affected by increasing the clay and silt content, but increases with increasing sand content towards 95% by a factor of 147

Figs. 6 to 9 inform about the changes in daily variations in run-off, interflow and baseflow for both locations as the soil texture changes from actual to sandy, silty and clayey (Scenarios 1 to 4,respectively, Figs. 6, 7), andsoil organicmatter content changes actualto 0.5 and2 x, and100% (Scenarios 1, and 5 to 8, Figs. 8, 9). As shown, these flows would peak faster with increasing Ksat (increasing sand and organic matter content), and would saturate the lower soil layers more quickly with decreasing Ksat and decreasing pore space, or increasing bulk density. Among the scenarios, the largest textural change on the flow regime was incurred by increasing the silt content within the already compacted subsoil at Moosepit Brook. Note that organic soils with 100% sapric organic matter would also have very low interflow and baseflow rates, and would

Role of Hydraulic Conductivity Uncertainties in Modeling Water Flow through Forest Watersheds

**%2 Interflow A&B (mm)**

 2.7 0.1 202.3 4.8 682.8 16.1 3341.2 79.0 4229.0 2.6 0.1 202.4 4.7 512.0 11.9 3580.4 83.3 4297.0 7.0 0.2 209.5 5.1 2653.0 64.4 1251.5 30.4 4121.0 2.7 0.1 202.4 4.8 1609.7 38.3 2391.4 56.9 4206.0 2.6 0.1 202.3 4.8 450.0 10.6 3578.0 84.5 4233.0 2.7 0.1 202.4 4.8 964.0 22.8 3054.8 72.3 4224.0 2.7 0.1 202.3 4.8 1675.8 39.8 2329.9 55.3 4210.7 0.0 0.0 594.8 13.2 3771.1 83.4 153.7 3.4 4519.6 0.0 0.0 612.4 11.6 4495.9 85.3 161.0 3.1 5269.3 0.0 0.0 668.6 10.6 5487.3 86.7 171.1 2.7 6327.0

 1.1 0.0 375.9 9.1 2990.0 72.2 772.9 18.7 4139.0 3.3 0.1 376.1 8.8 301.0 7.1 3588.5 84.1 4269.0 114.9 2.8 521.2 12.8 2635.0 64.8 796.5 19.6 4068.0 19.4 0.5 389.1 9.4 1965.0 47.3 1782.1 42.9 4156.0 2.2 0.1 376.1 9.1 2314.0 55.8 1454.4 35.1 4146.0 0.5 0.0 375.8 9.1 3273.0 79.2 485.6 11.7 4135.0 0.0 0.0 374.8 9.1 3457.0 83.9 290.7 7.1 4122.0 0.0 0.0 69.8 1.5 4250.5 92.1 292.9 6.3 4613.1 0.0 0.0 70.9 1.2 5463.3 93.6 305.0 5.2 5839.2 0.0 0.0 72.6 1.0 6609.0 94.6 305.0 4.4 6986.5

2 % values refer to the calculated percent contributions of run-off, FF interflow A&B interflow and baseflow to stream

**Table 5.** Lateral stream discharge by cumulative and percent runoff, interflow, and base flow for scenarios 1-8 for

Assessing the waterflow through peatland locations within each of the two watersheds, and setting the state of decomposition of the peat equal to H1, H4, H7 and H10 produced the results

**%2**

**Base flow (mm)**

**%2 Total Discharge (mm)**

http://dx.doi.org/10.5772/56900

41

therefore lead to relative fast soil saturation as well.

**%2 Interflow FF (mm)**

**Runoff (mm)**

**Site Scenario**

**Moosepit Brook**

**Turkey Lakes**

discharge.

¹ 50% coverage ² 10% coverage

Moosepit Brook (1999-2004) and Turkey Lakes (1997-2004).

Table 5 and Fig. 5 inform about the 5-year cumulative effects of the texture and OM changes on ForHyM2-modelled run-off, forest floor interflow, topsoil interflow, baseflow and stream discharge in terms of modelled mm per study period, and also in terms of modeled flow rate percentages per stream discharge. As shown, the interflow and baseflow percentage contribu‐ tions to stream discharge so compiled are very sensitive to Ksat as well as basin slope: for intermediate Ksat values, interflow would dominate the base flow contributions to stream dischargewithinthesteeperwatershedatTurkeyLakes (averageslope=8%).Thereversewould occur at the flatter Moosepit Brook watershed (average slope = 1%). Low subsoil permeability at Turkey Lakes would further accentuate this difference. In detail, base flow would domi‐ nate in both watersheds or at any location within the watersheds with high soil permeability and where the subsoil wouldnot be blockedby impervious bedrock.Incontrasts,locations with low overall soil permeability and low slopes would be most variable in terms of their cumula‐ tive run-off, interflow and baseflow contributions, varying from mostly baseflow to mostly interflow (Fig. 6). For example, mineral soils with high silt content (Scenario 3) would support more lateralflowinthe topsoil asopposedtosoilswithhighsandcontent(Scenario2).Doubling the OM in the mineral soil (Scenario 5) would also increase baseflow, whereas reducing OM (Scenario6)wouldinducetheopposite.TheextentofwaterinfiltrationinScenario4,asmodeled, would be midway between Scenarios 2 and 3


**Table 4.** Results for various levels of sand and OM against Ksat, Db and Dp for Moosepit Brook and Turkey Lakes.

Figs. 6 to 9 inform about the changes in daily variations in run-off, interflow and baseflow for both locations as the soil texture changes from actual to sandy, silty and clayey (Scenarios 1 to 4,respectively, Figs. 6, 7), andsoil organicmatter content changes actualto 0.5 and2 x, and100% (Scenarios 1, and 5 to 8, Figs. 8, 9). As shown, these flows would peak faster with increasing Ksat (increasing sand and organic matter content), and would saturate the lower soil layers more quickly with decreasing Ksat and decreasing pore space, or increasing bulk density. Among the scenarios, the largest textural change on the flow regime was incurred by increasing the silt content within the already compacted subsoil at Moosepit Brook. Note that organic soils with 100% sapric organic matter would also have very low interflow and baseflow rates, and would therefore lead to relative fast soil saturation as well.


¹ 50% coverage ² 10% coverage

subsoil than in the topsoil. Since the soil texture is sandier at Moosepit Brook than at Turkey Lakes,KsatvaluesremainhigherinthesubsoilatMoosepitBrookthanatTurkeyLakes.Changing the topsoil texture from the actual values changes Ksat by about 5x upwards, and by about 10x downwards at both locations. These Ksat changes are similar for the somewhat coarser subsoil at Moosepit Brook. In contrast, subsoil Ksat is not much affected by increasing the clay and silt

Table 5 and Fig. 5 inform about the 5-year cumulative effects of the texture and OM changes on ForHyM2-modelled run-off, forest floor interflow, topsoil interflow, baseflow and stream discharge in terms of modelled mm per study period, and also in terms of modeled flow rate percentages per stream discharge. As shown, the interflow and baseflow percentage contribu‐ tions to stream discharge so compiled are very sensitive to Ksat as well as basin slope: for intermediate Ksat values, interflow would dominate the base flow contributions to stream dischargewithinthesteeperwatershedatTurkeyLakes (averageslope=8%).Thereversewould occur at the flatter Moosepit Brook watershed (average slope = 1%). Low subsoil permeability at Turkey Lakes would further accentuate this difference. In detail, base flow would domi‐ nate in both watersheds or at any location within the watersheds with high soil permeability and where the subsoil wouldnot be blockedby impervious bedrock.Incontrasts,locations with low overall soil permeability and low slopes would be most variable in terms of their cumula‐ tive run-off, interflow and baseflow contributions, varying from mostly baseflow to mostly interflow (Fig. 6). For example, mineral soils with high silt content (Scenario 3) would support more lateralflowinthe topsoil asopposedtosoilswithhighsandcontent(Scenario2).Doubling the OM in the mineral soil (Scenario 5) would also increase baseflow, whereas reducing OM (Scenario6)wouldinducetheopposite.TheextentofwaterinfiltrationinScenario4,asmodeled,

> **Ksat, cm h-1 Db, g cm-1 Dp, g cm-1 Mineral Subsoil Mineral Subsoil Mineral Subsoil**

1: Actual 48.40 5.95 0.95 1.61 2.48 2.59 2: Sand 162.90 29.15 0.93 1.50 2.48 2.59 3: Silt 3.05 0.15 1.00 1.86 2.48 2.59 4: Heavy clay 7.15 0.50 0.99 1.80 2.48 2.59 5: Double OM 60.60 13.30 0.72 1.48 2.33 2.54 6: Half OM 31.35 2.70 1.14 1.70 2.56 2.62 7: No OM 12.60 0.75 1.41 1.83 2.65 2.65

1: Actual 39.80 0.10 1.09 1.85 2.55 2.61 2: Sand 136.25 14.70 1.06 1.54 2.55 2.61 3: Silt 2.50 0.05 1.15 1.92 2.55 2.61 4: Heavy clay 5.80 0.10 1.15 1.84 2.55 2.61 5: Double OM 56.05 0.30 0.90 1.68 2.45 2.57 6: Half OM 30.55 0.05 1.19 1.85 2.59 2.61 7: No OM 14.50 0.00 1.39 2.06 2.65 2.65

**Table 4.** Results for various levels of sand and OM against Ksat, Db and Dp for Moosepit Brook and Turkey Lakes.

content, but increases with increasing sand content towards 95% by a factor of 147

would be midway between Scenarios 2 and 3

**Site Scenarios**

40 Hydraulic Conductivity

**Moosepit Brook**

**Turkey Lakes**

2 % values refer to the calculated percent contributions of run-off, FF interflow A&B interflow and baseflow to stream discharge.

**Table 5.** Lateral stream discharge by cumulative and percent runoff, interflow, and base flow for scenarios 1-8 for Moosepit Brook (1999-2004) and Turkey Lakes (1997-2004).

Assessing the waterflow through peatland locations within each of the two watersheds, and setting the state of decomposition of the peat equal to H1, H4, H7 and H10 produced the results compiled in Table 6. As shown, organic soils mostly composed of fibric to mesic peat (H1) would support deep percolation and baseflow, whereas organic soils mostly composed of humic peat (H10) would contain pooled water from the subsoil upwards to the surface, thereby encouraging surface run-off

Note also from Table 4 and 6 that the changing Ksat values for decomposing peat would also have strong effects on forested peatland evapotranspiration and on stream discharge: the lower Ksat, the higher would be the rate of water retention and subsequent forest water uptake and evapotranspiration during the growing season (Fig. 10). In contrast, the higher Ksat, the faster water would be lost due to quick baseflow (Fig. 11). Outside the growing season, run-off increases, as modeled and as to be expected (Fig. 10 and 11)


**Table 6.** Lateral stream discharge by cumulative and percent runoff, interflow, and baseflow for scenario 8 to represent 100% peat surface deposits (von Post index set at H1, H4, H7, and H10 for the entire profile) underneath forest cover at each of the two locations.

0

0 40 80 120 160

**Figure 5.** Ksat of the A&B layers by cumulative stream discharge % for Moosepit Brook (top), and Turkey Lakes (bot‐

tom) across all 8 scenarios (vertical dashed line represents the actual scenario)

Ksat(A & B layers), cm h-1

0 40 80 120 160

Turkey Lakes, slope = 8%

Moosepit Brook, slope = 1%

Role of Hydraulic Conductivity Uncertainties in Modeling Water Flow through Forest Watersheds

Runoff (mm) Interflow FF (mm) Interflow A&B (mm) Base flow (mm)

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43

20

40

60

80

100

Cumulative flow rates / cumulative stream discharge, %

0

20

40

60

80

100

The extent water retention in terms of mm per soil layer is illustrated in Fig. 12 for the two study locations as modeled for the actual soil (Scenario 1) and for organic soil conditions (100% organic matter content, Scenario 8), starting the soil moisture content at field capacity for January 1. For the slowly draining peatland scenario (Scenario 8), subsoil moisture levels would increase from field capacity towards saturation in about one year. For the well-drained upland soil conditions (Scenario 1), Ksat values would be sufficiently high so that soil moisture conditions would fluctuate around the field capacity, depending on season as well as rainfall and snow melt events

compiled in Table 6. As shown, organic soils mostly composed of fibric to mesic peat (H1) would support deep percolation and baseflow, whereas organic soils mostly composed of humic peat (H10) would contain pooled water from the subsoil upwards to the surface, thereby

Note also from Table 4 and 6 that the changing Ksat values for decomposing peat would also have strong effects on forested peatland evapotranspiration and on stream discharge: the lower Ksat, the higher would be the rate of water retention and subsequent forest water uptake and evapotranspiration during the growing season (Fig. 10). In contrast, the higher Ksat, the faster water would be lost due to quick baseflow (Fig. 11). Outside the growing season, run-off

increases, as modeled and as to be expected (Fig. 10 and 11)

**Interflow FF (mm)**

**%**

**Interflow A&B (mm)**

H1 0.00 0.0 1.09 0.0 53.00 1.1 4618.27 98.8 4672.35

H4 0.00 0.0 20.27 0.4 222.67 4.9 4291.43 94.6 4534.38

H7 0.00 0.0 240.34 5.9 184.86 4.5 3676.06 89.6 4101.26

H10 3275.13 97.3 74.12 2.2 13.32 0.4 4.67 0.1 3367.25

H1 0.00 0.0 0.08 0.0 0.84 0.0 5954.36 100.0 5955.27

H4 0.00 0.0 1.03 0.0 7.64 0.1 5641.93 99.8 5650.61

H7 0.00 0.0 55.87 1.2 8.18 0.2 4655.45 98.6 4719.50

H10 3057.12 97.7 50.55 1.6 4.51 0.1 16.86 0.5 3129.03

**Table 6.** Lateral stream discharge by cumulative and percent runoff, interflow, and baseflow for scenario 8 to represent 100% peat surface deposits (von Post index set at H1, H4, H7, and H10 for the entire profile) underneath

The extent water retention in terms of mm per soil layer is illustrated in Fig. 12 for the two study locations as modeled for the actual soil (Scenario 1) and for organic soil conditions (100% organic matter content, Scenario 8), starting the soil moisture content at field capacity for January 1. For the slowly draining peatland scenario (Scenario 8), subsoil moisture levels would increase from field capacity towards saturation in about one year. For the well-drained upland soil conditions (Scenario 1), Ksat values would be sufficiently high so that soil moisture conditions would fluctuate around the field capacity, depending on season as well as rainfall

**%**

**Base flow (mm)**

**%**

**Total Discharge (mm)**

**%**

encouraging surface run-off

**Runoff (mm)**

forest cover at each of the two locations.

and snow melt events

**Site von Post**

42 Hydraulic Conductivity

**Moosepit Brook**

**Turkey Lakes**

**Figure 5.** Ksat of the A&B layers by cumulative stream discharge % for Moosepit Brook (top), and Turkey Lakes (bot‐ tom) across all 8 scenarios (vertical dashed line represents the actual scenario)

**Figure 6.** Run-off, forest floor and A&B interflow and base flow for Moosepit Brook, by scenario from actual to sandy, silty and clayey (Scenarios 1 to 4, respectively; 2003)

Silt Heavy clay Sand Status quo

Role of Hydraulic Conductivity Uncertainties in Modeling Water Flow through Forest Watersheds

Runoff

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45

FF Interflow

A&B Interflow

Baseflow

January March April June August October December

**Figure 7.** Run-off, forest floor and A&B interflow and base flow for Turkey lakes, by scenario from actual to sandy, silty

and clayey (Scenarios 1 to 4, respectively; 2000), no runoff for any of the scenarios

Lateral stream flow (mm/year)

0

2500

5000

7500

2500

5000

7500

2500

5000

75000

2500

5000

7500

Role of Hydraulic Conductivity Uncertainties in Modeling Water Flow through Forest Watersheds http://dx.doi.org/10.5772/56900 45

**Figure 7.** Run-off, forest floor and A&B interflow and base flow for Turkey lakes, by scenario from actual to sandy, silty and clayey (Scenarios 1 to 4, respectively; 2000), no runoff for any of the scenarios

silty and clayey (Scenarios 1 to 4, respectively; 2003)

January March April June August October December

2003

**Figure 6.** Run-off, forest floor and A&B interflow and base flow for Moosepit Brook, by scenario from actual to sandy,

Silt Heavy clay Sand Status quo

Runoff

FF Interflow

A&B Interflow

Baseflow

5000

10000

5000

10000

Lateral stream flow (mm/year)

5000

100000

5000

10000

44 Hydraulic Conductivity

Lateral stream flow (mm/year)

0

runoff for any of the scenarios.

2500

5000

7500

02500

5000

75000

2500

5000

7500

2500

5000

7500

2000

**Figure 9.** Run-off, forest floor and A&B interflow and base flow for Turkey Lakes, by scenario from actual to no, 0.5x and 2x actual organic matter content, and 100% sapric organic matter (Scenarios 1 and 5 to 8, respectively; 2000), no

January March April June August October December

Half OM Double OM No OM 100% OM Status quo

Role of Hydraulic Conductivity Uncertainties in Modeling Water Flow through Forest Watersheds

Runoff

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FF Interflow

A&B Interflow

Baseflow

**Figure 8.** Run-off, forest floor and A&B interflow and base flow for Moosepit Brook, by scenario from actual to no, 0.5x and 2x actual organic matter content, and 100 % sapric organic matter (Scenarios 1 and 5 to 8, respectively; 2003)

Role of Hydraulic Conductivity Uncertainties in Modeling Water Flow through Forest Watersheds http://dx.doi.org/10.5772/56900 47

**Figure 9.** Run-off, forest floor and A&B interflow and base flow for Turkey Lakes, by scenario from actual to no, 0.5x and 2x actual organic matter content, and 100% sapric organic matter (Scenarios 1 and 5 to 8, respectively; 2000), no runoff for any of the scenarios.

2003)

January March April June August October December

2003

**Figure 8.** Run-off, forest floor and A&B interflow and base flow for Moosepit Brook, by scenario from actual to no, 0.5x and 2x actual organic matter content, and 100 % sapric organic matter (Scenarios 1 and 5 to 8, respectively;

Half OM Double OM No OM 100% OM Status quo

Runoff

FF Interflow

A&B Interflow

Baseflow

5000

10000

05000

10000

Lateral stream flow (mm/year)

5000

100000

5000

10000

46 Hydraulic Conductivity

**Figure 10.** Evapotranspiration at Moosepit Brook (A) during 2003 and Turkey Lakes (B) during 2000, for Scenario 8 (100% OM), with actual (100% vegetation), Scenario 81 (50% vegetation), and Scenario 82 (10% vegetation). Note the difference in the extent of the growing season: wide for Moosepit Brook (maritime climate), and narrow for Turkey Lakes (continental climate).

January March April June August October December

**Figure 11.** ForHyM2 estimated rates for daily forest floor and A&B interflow and base flow for peatland locations with a fibric - mesic – sapric layer profile at Moosepit Brook and Turkey Lakes, with 100% forest cover. Also shown: upland

interflows and baseflows for the Moosepit Brook watershed (2000).

Moosepit Brook

Turkey Lakes

Upland Peat Peat

Role of Hydraulic Conductivity Uncertainties in Modeling Water Flow through Forest Watersheds

FF Interflow

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49

A&B Interflow

Baseflow

400

800

1200

5000

10000

Lateral stream flow (mm/year)

15000

20000 0

400

800

1200

1600

5

Evapotranspiration (mm)

0

Lakes (continental climate).

1

2

3

4

B

January March April June August October December

January March April June August October December

**Figure 10.** Evapotranspiration at Moosepit Brook (A) during 2003 and Turkey Lakes (B) during 2000, for Scenario 8 (100% OM), with actual (100% vegetation), Scenario 81 (50% vegetation), and Scenario 82 (10% vegetation). Note the difference in the extent of the growing season: wide for Moosepit Brook (maritime climate), and narrow for Turkey

100% 50% 10%

1

2

3

4

5

48 Hydraulic Conductivity

A

**Figure 11.** ForHyM2 estimated rates for daily forest floor and A&B interflow and base flow for peatland locations with a fibric - mesic – sapric layer profile at Moosepit Brook and Turkey Lakes, with 100% forest cover. Also shown: upland interflows and baseflows for the Moosepit Brook watershed (2000).

underneath the trails, which means more water retention upslope along the trails, therefore leading to weather-effected trail destabilization, unless ditches and cross drains are installed to divert the water away from the trail beds [31]. Changes in forest cover could lead to changes in rooting space, which would – in turn – reduce the organic matter content within top and subsoils. This reduction would then alter the overall interplay between surface runoff, interflow and baseflow. Similarly, variations in climate from wet to dry (induces soil shrinking, may reduce root biomass), from frozen to non-frozen (induces collapse of frozen soil struc‐ tures) would also affect Ksat and flow through soils by affecting the organic matter build-up, the state of soil organic matter humification, and overall changes in granular, blocky and

Role of Hydraulic Conductivity Uncertainties in Modeling Water Flow through Forest Watersheds

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51

The main advantage of the above Ksat formulation is that it allows for daily weather-related projections concerning downward and lateral water flow rates in forested to non-forested watersheds from times when soils are at saturation to times when soils are dry. At times of soil saturation, this quantification can then be used to estimate the effects of flow on soil stability and stream discharge. At times of drought, this quantification is can be used to estimate the effects of no flow on the remaining water reserves within soils and watersheds with and without peatland components (Fig. 12). Using ForHyM2 has the additional advantage of conducting these calculations year-round, summers through winters, based on already existing daily weather records, and extending these by way of daily, weekly, monthly or

Financial support for this research was received from Environment Canada, Alberta Sustain‐

Faculty of Forestry and Environmental Management, University of New Brunswick, Freder‐

[1] Jutras MF, Arp PA. Determination of hydraulic conductivity from soil characteristics and its application for modelling stream discharge in forest catchments. In (Ed.) LE,

able Resource Department, and NSERC (Discovery Grant and CRD project grants).

columnar soil structures

annual weather forecasts

**Acknowledgements**

**Author details**

icton, Canada

**References**

Marie-France Jutras and Paul A. Arp

\*Address all correspondence to: arp2@unb.ca

**Figure 12.** Soil water content on the surface, in the forest floor, in the mineral soil, and in the subsoil, as well as the cumulative discharge for Scenario 8 regarding organic soil (100% OM, top), and actual mineral soil conditions (bot‐ tom), for Moosepit Brook (2003, left) and Turkey Lakes (2000, right). Simulations start with unsaturated soil condition. Discussion

The above watershed-based Ksat evaluations have shown that the effective Ksat values for downward and lateral flow generally vary by a factor of 2 to 3 in comparison to corresponding values generated via Eqs. 1-3 [1]. As illustrated via Table 5 and subsequent figures, these variations lead to uncertainties in quantifying how water percolates through watersheds as run-off, interflow and baseflow (Fig. 5). These uncertainties also affect the flow response time, ranging generally from small delays to extended periods of flow as Ksat values decrease (Figs. 6 to 9). Across watersheds, however, flows tend to be well synchronized, regardless of major differences in texture, density, and organic matter content [28]. Typically, watersheds with the more compacted soils and therefore low Ksat values will be more peaked and will therefore be flashier than watersheds that allow deep percolation [25, 26, 27, 2]. The strongest impact of shallow to deep flow would deal with the water quality: deep water percolation during summer would lead to cooler and purer stream and seepage water with elevated pH than shallow water percolation [6]. During winter, deep percolation and persistent base flow would be warmer compared to the frost-affected surface water on poorly drained soils [6, 5]. Water flowing along the surface would also be more colored towards brown and more acidic than the more filtered and mineral-exposed water flowing at greater soil and subsoil depth [28]

While organic matter and soil density would not change drastically throughout undisturbed watersheds, such changes would occur during and after times of intense surface operations, especially under poor weather conditions. For example, forest operations during times of poor soil trafficability lead to ruts and increased soil compaction [29, 30]. In turn, soil compaction leads to lower Ksat values and therefore lower infiltration and hence higher surface run-off rates, thereby accelerating soil erosion and subsequent sediment transfer to streams and lakes [4]. Trails across the slopes of watersheds also affect downslope flow by compacting the soil underneath the trails, which means more water retention upslope along the trails, therefore leading to weather-effected trail destabilization, unless ditches and cross drains are installed to divert the water away from the trail beds [31]. Changes in forest cover could lead to changes in rooting space, which would – in turn – reduce the organic matter content within top and subsoils. This reduction would then alter the overall interplay between surface runoff, interflow and baseflow. Similarly, variations in climate from wet to dry (induces soil shrinking, may reduce root biomass), from frozen to non-frozen (induces collapse of frozen soil struc‐ tures) would also affect Ksat and flow through soils by affecting the organic matter build-up, the state of soil organic matter humification, and overall changes in granular, blocky and columnar soil structures

The main advantage of the above Ksat formulation is that it allows for daily weather-related projections concerning downward and lateral water flow rates in forested to non-forested watersheds from times when soils are at saturation to times when soils are dry. At times of soil saturation, this quantification can then be used to estimate the effects of flow on soil stability and stream discharge. At times of drought, this quantification is can be used to estimate the effects of no flow on the remaining water reserves within soils and watersheds with and without peatland components (Fig. 12). Using ForHyM2 has the additional advantage of conducting these calculations year-round, summers through winters, based on already existing daily weather records, and extending these by way of daily, weekly, monthly or annual weather forecasts

## **Acknowledgements**

50 Hydraulic Conductivity

Water content and discharge (mm)

Subsoil saturation

Subsoil saturation

On Surface In FF In mineral soil In subsoil Cumulative Discharge

Mineral Soil Slope 1%

Organic soil Slope 1 %

**Figure 12.** Soil water content on the surface, in the forest floor, in the mineral soil, and in the subsoil, as well as the cumulative discharge for Scenario 8 regarding organic soil (100% OM, top), and actual mineral soil conditions (bot‐ tom), for Moosepit Brook (2003, left) and Turkey Lakes (2000, right). Simulations start with unsaturated soil condition.

The above watershed-based Ksat evaluations have shown that the effective Ksat values for downward and lateral flow generally vary by a factor of 2 to 3 in comparison to corresponding values generated via Eqs. 1-3 [1]. As illustrated via Table 5 and subsequent figures, these variations lead to uncertainties in quantifying how water percolates through watersheds as run-off, interflow and baseflow (Fig. 5). These uncertainties also affect the flow response time, ranging generally from small delays to extended periods of flow as Ksat values decrease (Figs. 6 to 9). Across watersheds, however, flows tend to be well synchronized, regardless of major differences in texture, density, and organic matter content [28]. Typically, watersheds with the more compacted soils and therefore low Ksat values will be more peaked and will therefore be flashier than watersheds that allow deep percolation [25, 26, 27, 2]. The strongest impact of shallow to deep flow would deal with the water quality: deep water percolation during summer would lead to cooler and purer stream and seepage water with elevated pH than shallow water percolation [6]. During winter, deep percolation and persistent base flow would be warmer compared to the frost-affected surface water on poorly drained soils [6, 5]. Water flowing along the surface would also be more colored towards brown and more acidic than the more filtered and mineral-exposed water flowing at greater soil and subsoil depth [28]

While organic matter and soil density would not change drastically throughout undisturbed watersheds, such changes would occur during and after times of intense surface operations, especially under poor weather conditions. For example, forest operations during times of poor soil trafficability lead to ruts and increased soil compaction [29, 30]. In turn, soil compaction leads to lower Ksat values and therefore lower infiltration and hence higher surface run-off rates, thereby accelerating soil erosion and subsequent sediment transfer to streams and lakes [4]. Trails across the slopes of watersheds also affect downslope flow by compacting the soil

Subsoil Saturation

Subsoil Saturation

January March April June August October December Turkey Lakes, 2000

Mineral Soil Slope 8%

Organic soil Slope 8 %

Discussion

January March April June August October December Moosepit Brook, 2003

> Financial support for this research was received from Environment Canada, Alberta Sustain‐ able Resource Department, and NSERC (Discovery Grant and CRD project grants).

## **Author details**

Marie-France Jutras and Paul A. Arp

\*Address all correspondence to: arp2@unb.ca

Faculty of Forestry and Environmental Management, University of New Brunswick, Freder‐ icton, Canada

## **References**

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**Chapter 3**

**Eveluation of the Quality of the Soil From Soil Physical-**

Due to the high demand for food, farmers have intensified agriculture seeking high produc‐ tions. Hence, agriculture, amongst other activities, has been considered a highly potentially polluting activity of all the system water-soil-plant-environment. As a consequence, the intensive use of the soil causes its degradation. The accelerated waste will always exist if the farmer does not take proper measures to combat the causes related to various processes such as: chemical depleting and leaching, erosion, physical and biological degradation. The growing concern about the environment raised the concern about the quality of the soil. Ever since, several concepts of soil quality have been proposed, however, currently "soil quality" is defined as the capacity of the soil to keep biological productivity, environment quality and the vegetal and animal lives healthy on earth [1]. There has currently been a wide discussion towards environmental patterns and indicators, specially in Brazil, where there are very few studies and even a lack of systematization over the subject, since there is plenty of data that could provide support for an extensive discussion over the topic. The evaluation of the quality of the soil could be carried out by the monitoring of its features or physical, chemical and biological characteristics. In this approach, the expression "soil quality indicators" is being used, since it is the parameter or reference that best translate the conditions of a specific environment compartment. Among them, some attributes or physical indicators that might go through a few medium term changes have been recommended, such as density, porosity, aggregation and compression state. Hydrical conductivity, water retention, storage and density of water flow in the soil may also be indicators of great importance to assess the quality of the soil. Although such parameters are not frequently studied in Brazil, in foreign literature they are reported to vary according to different soil preparations and management. Detailed familiarity of the water dynamics during the development of a culture provides essential elements for the stablishment or improvement of agricultural management practices that aim

> © 2013 Libardi and Silva; licensee InTech. This is a paper distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use,

distribution, and reproduction in any medium, provided the original work is properly cited.

**Hydrical Indicators**

http://dx.doi.org/10.5772/56875

**1. Introduction**

Paulo Leonel Libardi and Flávia Carvalho Silva

Additional information is available at the end of the chapter

[31] Jamshidi R, Jaeger D, Raafatnia N, Tabari M. Influence of two ground-based skid‐ ding systems on soil compaction under different slope and gradient conditions. Int. J. For. Eng. 2008; 19: 9-16.
