**2. Data**

**Keywords:** climate change, Palmer Drought Severity Index, regional climate modeling,

The Fifth Assessment Reports of the Intergovernmental Panel on Climate Change [1] indicates that climate change is unequivocal, and this fact is clear from observations of increases in global average air and ocean temperatures, widespread melting of snow and ice and the rising global sea level. Global warming leads to warmer lower atmosphere and increased evaporation rates, resulting in an enhancement in the amount of moisture transport in the troposphere. An observed effect of higher water vapor concentrations is the increased frequency of extreme precipitation events over land areas. Warmer temperatures have led to increased drying of the land surface in some areas, with the effect of an increased incidence and severity of drought. Climate change is affecting the water cycle, enhancing droughts in some areas and wet conditions in others [1]. In parts of the Northern Hemisphere, spring conditions have the tendency to develop earlier, leading to a shift in peaks in snowmelt and river streamflow. As a consequence, summers tend to experience reduced water availability. Furthermore, these changes are likely to intensify in future under higher greenhouse gas

Even though the broad picture of climate-induced changes in water cycle is relatively clear, there are regional details that locally impact the water cycle, and this is the level where the adaptation measures have to be implemented for a sustainable development of the society. Climate impact assessments and local adaptation strategies require analysis based on numerical experiments using climate models with very high spatial resolution under scenarios of global climate change and robust evaluation of the results within the limits of reasonable uncertainty. However, few studies have documented water cycle-related changes at the river basin level based on the new regional climate modeling results in South Eastern Europe. A detailed analysis of future climate change projections exists for the Bârlad basin [2], considering the scenarios elaborated within the Fifth Report of the Intergovernmental Panel on Climate Change [1]. The results presented in [2] show that, under the climate change, the tendency toward more severe summer droughts is a significant feature of the Bârlad basin in the long run, despite the uncertainties related to global and regional models, parametrization of potential evapotranspiration in the Palmer model, and the soil data. This tendency seems to be a result of a basin-wide decrease in the precipitation and increase in the potential evaporation, which have been also identified as causes for the summer time drying in mid-latitudes in the CMIP 3 model results [3]. However, it is still an open question if these results apply for other

The main objective of this study is to propose a robust methodology for assessing the present and future-projected evolution of local water cycle components and their impacts on drought conditions at the basin level in mid-latitude areas, using results of regional climate experiments under the representative concentration pathway (RCP) scenarios [4]. The catchments selected as case studies are located in the mid- and low-Danube basin (**Figure 1**).

EURO-CORDEX, mid and lower Danube basin

**1. Introduction**

116 Engineering and Mathematical Topics in Rainfall

(GHG) global concentrations.

river catchments, too.

We extracted daily and monthly data from observations and model results covering the selected river basins. The time slices of simulated and observed available data are included in the interval 1951–2015. The future projections used here are computed under the representative concentration pathway (RCP) scenarios. The RCP scenarios describe the temporal evolution of the global greenhouse gas concentrations in the period 2006–2100. They illustrate the radiative forcing due to increased concentration of greenhouse gases. In 2100, the radiative forcing caused by increased levels of greenhouse gases reaches a value around 4.5 (8.5) W/m<sup>2</sup> above the pre-industrial level in the RCP 4.5 (RCP 8.5) scenario [4].

The CMIP5 results have a global coverage with a spatial resolution suitable for large-scale analysis. However, this resolution is not quite appropriate for a detailed description of local


provides regional climate projections for Europe at resolutions of 50 km (EUR-44) and 12.5 km (EUR-11). In this study, we use the available EURO-CORDEX results with very high resolution (EUR-11). The regional and global climate models used for numerical experiments analyzed in

Variability and Change in Water Cycle at the Catchment Level

http://dx.doi.org/10.5772/intechopen.74047

119

We used observation-derived gridded data in comparison with model results to see how the regional climate models simulate the present climate. Observed data were extracted from the ROCADA data set for the period 1970–2005. The ROCADA data set contains daily values and has a spatial resolution of 10 km × 10 km [7, 8]. We have also extracted gridded temperature, precipitation and potential evapotranspiration (resolution 0.5° x 0.5°) from the global data set developed at Climate Research Unit (CRU) [9]. The CRU potential evapotranspiration follows the Penman-Monteith approach [10]. A gridded precipitation data covering the entire transboundary basin of Prut river at the spatial resolution of 10 km × 10 km was built in the framework of IMDROFLOOD project, using observations from Romania, Republic of Moldova and data extracted from the Global Historical Climatology Network-Daily (GHCND-D) [11]. Monthly values of streamflow at stations from Romania and Republic and Moldova were also

In addition, we used available water capacities (AWCs) of soils. The AWC dataset consists of estimated topsoil and subsoil AWC values extracted from the European Soil Database (ESDB)

In this study, we averaged the sum of topsoil and subsoil AWCs from the ESDB on the 12.5 km × 12.5 km (50 km × 50 km) square cells centered in the climate model (CRU data) grids to provide the soil constants used as input data for PDSI calculation in each EURO-CORDEX (CRU) grid point of the selected basins. For example, the AWC data averaged at the EURO-CORDEX

In our approach, we define the local water cycle components (precipitation, potential evapotranspiration, and potential runoff) based on the two-level model of the soil exploit by the Palmer Drought Severity Index (PDSI) [14], like in the approach presented in [2]. The top layer of soil is assumed to hold 25.4 mm of moisture. The amount of moisture that can be held by the two-layered soil is a soil-dependent value—available water capacity (AWC)—which must

The PDSI measures the cumulative effect of monthly precipitation deficit/surplus with respect to a value that is climatologically appropriate for existing conditions (CAFECs) in a given region [14]. The computation of the PDSI requires precipitation, air temperature, soil characteristics (i.e., available water capacity—AWC), and the latitude of the location to estimate the length of day over which the solar radiation is received (for deriving potential evapotranspiration). In order to calculate the PDSI for a certain month (i), one has first to determine the

ZINDi = k (P–αPE–βPR–γPRO + δPL) (1)

this study are presented in **Table 1**.

used in the case of the Prut transboundary basin.

[12, 13] for the studied areas.

**3. Methodology**

resolution are illustrated in **Figure 2**.

be provided as an input parameter [14].

moisture anomaly index ZINDi for that month (i):

**Table 1.** Numerical experiments with regional and global climate models used to assess the influence of climate change on the future evolution of water cycle components in the selected basins.

**Figure 2.** Available water capacities (AWCs) (in mm water column/1 m soil) computed in the 12.5 km EURO-CORDEX grids (black circles) obtained as the sum of topsoil and subsoil AWCs (at 1 km × 1 km resolution) extracted from the European Soil Database (ESDB) and averaged over the 12.5 km × 12.5 km grid cells centered in the model grids for the areas of interest.

processes like those taking place in river catchments. That is why we used regional climate models from COordinated Regional Climate Downscaling Experiment (CORDEX) [6] driven by global models from the CMIP5. As part of CORDEX framework, EURO-CORDEX initiative provides regional climate projections for Europe at resolutions of 50 km (EUR-44) and 12.5 km (EUR-11). In this study, we use the available EURO-CORDEX results with very high resolution (EUR-11). The regional and global climate models used for numerical experiments analyzed in this study are presented in **Table 1**.

We used observation-derived gridded data in comparison with model results to see how the regional climate models simulate the present climate. Observed data were extracted from the ROCADA data set for the period 1970–2005. The ROCADA data set contains daily values and has a spatial resolution of 10 km × 10 km [7, 8]. We have also extracted gridded temperature, precipitation and potential evapotranspiration (resolution 0.5° x 0.5°) from the global data set developed at Climate Research Unit (CRU) [9]. The CRU potential evapotranspiration follows the Penman-Monteith approach [10]. A gridded precipitation data covering the entire transboundary basin of Prut river at the spatial resolution of 10 km × 10 km was built in the framework of IMDROFLOOD project, using observations from Romania, Republic of Moldova and data extracted from the Global Historical Climatology Network-Daily (GHCND-D) [11]. Monthly values of streamflow at stations from Romania and Republic and Moldova were also used in the case of the Prut transboundary basin.

In addition, we used available water capacities (AWCs) of soils. The AWC dataset consists of estimated topsoil and subsoil AWC values extracted from the European Soil Database (ESDB) [12, 13] for the studied areas.

In this study, we averaged the sum of topsoil and subsoil AWCs from the ESDB on the 12.5 km × 12.5 km (50 km × 50 km) square cells centered in the climate model (CRU data) grids to provide the soil constants used as input data for PDSI calculation in each EURO-CORDEX (CRU) grid point of the selected basins. For example, the AWC data averaged at the EURO-CORDEX resolution are illustrated in **Figure 2**.
