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The Hindu Kush-Himalayan region is an important global freshwater resource
. The hydrological regime of the region is vulnerable to climatic variations, especially precipitation and temperature. In our study, we modelled the impact of climate change on the water balance and hydrological regime of the snow dominated Kaligandaki Basin. The Soil and Water Assessment Tool (SWAT) was used for a future projection of changes in the hydrological regimeof the Kaligandaki basin based on Representative Concentration Pathways Scenarios (RCP 4.5 and RCP 8.5) of ensemble downscaled Coupled Model Intercomparison Project's (CMIP5) General Circulation Model (GCM) outputs. It is predicted to be a rise in the average annual temperature of over 4 °C, and an increase in the average annual precipitation of over 26% by the end of the 21st century under RCP 8.5 scenario. Modeling results show these will lead to significant changes in the basin's water balance and hydrological regime. In particular, a 50% increase in discharge is expected at the outlet of the basin. Snowmelt contribution will largely be affected by climate change, and it is projected to increase by 90% by 2090.Water availability in the basin is not likely to decrease during the 21st century. The study demonstrates that the importantwater balance components of snowmelt, evapotranspiration, and water yield at higher elevations in the upper and middle sub-basins of the Kaligandaki Basin will be most affected by the increasing temperatures and precipitation
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Study Region: Brahmaputra River basin in South Asia
. Study Focus: The Soil and Water Assessment Tool was used to evaluate sensitivities and patterns in freshwater availability due to projected climate and land use changes in the Brahmaputra basin. The daily observed discharge at Bahadurabad station in Bangladesh was used to calibrate and validate the model and analyze uncertainties with a sequential uncertainty fitting algorithm. The sensitivities and impacts of projected climate and land use changes on basin hydrological components were simulated for the A1B and A2 scenarios and analyzed relative to a baseline scenario of 1988–2004. New hydrological insights for the region: Basin average annual ET was found to be sensitive to changes in CO2 concentration and temperature, while total water yield, streamflow, and groundwater recharge were sensitive to changes in precipitation. The basin hydrological components were predicted to increase with seasonal variability in response to climate and land use change scenarios. Strong increasing trends were predicted for total water yield, streamflow, and groundwater recharge, indicating exacerbation of flooding potential during August–October, but strong decreasing trends were predicted, indicating exacerbation of drought potential during May–July of the 21st century. The model has potential to facilitate strategic decision making through scenario generation integrating climate change adaptation and hazard mitigation policies to ensure optimized allocation of water resources under a variable and changing climate
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AbstractStudy region The Kalamazoo River Watershed, southwest Michigan, USA
. Study focus Climate change is projected to have significant impacts on agricultural production. Therefore, understanding the regional impacts of climate change on irrigation demand for crop production is important for watershed managers and agricultural producers to understand for effective water resources management. In this study, the Soil and Water Assessment Tool was used to assess the impact of climate change on corn and soybean irrigation demand in the Kalamazoo River Watershed. Bias-corrected statistically downscaled climate change data from ten global climate models and four emissions scenarios were used in SWAT to develop projections of irrigation demand and yields for 2020–2039 and 2060–2079. Six adaptation scenarios were developed to shift the planting dates (planting earlier and later in the growing season) to take advantage of periods with greater rainfall or lower temperature increases. New hydrological insights for the region Uncertainty in irrigation demand was found to increase moving from 2020–2039 to 2060–2079, with demand generally decreasing moving further into the future for corn and soybean. A shift in timing of peak irrigation demand and increases in temperature lead to corn yield reductions. However, soybean yield increased under these conditions. Finally, the adaptation strategy of planting earlier increased irrigation demand and water available for transpiration, while delaying planting resulted in demand decreases for both crops
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Water is most essential natural resource for life but in absence of rain fall drought occurs whereas excess rain fall causes floods and soil erosion
. In Nepal accurate information of water availability is lacking. Therefore, accurate simulation of hydrological parameter is important for water resource management. The present study has been conducted in Bagmati River Basin for hydrological simulation of runoff, one of most important parameter of hydrology using SWAT model. Input data for model as soil map, land use land cover map and meteorological parameter were prepared with the help of Arc-Gis, ERDAS and Ms-Excel software. The model was calibrated using field-measured discharge data at gauged station for six years (1997 to 2002) and validation was performed for two years (2003 to 2004). The monthly simulated runoff of the calibration and validation periods were found to match with their measured discharge value of coefficient with correlation (R2) in both the cases 0.917 and 0.92 respectively. The model simulated daily runoff is corroborated by reasonably high Nash–Sutcliffe simulation coefficients of 91.54% and 77.31% respectively for calibration and validation periods. Similarly, average annual surface runoff in 1997 to 2002 and 2003 to 2004 was 831.2 mm and 922mm, i.e. 40 and 43% of precipitation respectively. Similarly, total water yield and evapotranspiration was 71% and 23% of precipitation in both time period. Such type of runoff model plays vital role for water resource management. So, this model can be further utilized as a potential tool for water resource management of spring fed River Basin in Nepal
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Currently, there is a major concern about the future of nutrient loads discharged into the Baltic Sea from Polish rivers because they are main contributors to its eutrophication
. To date, no watershed-scale studies have properly addressed this issue. This paper fills this gap by using a scenario-modeling framework applied in the Reda watershed, a small (482 km2) agricultural coastal area in northern Poland. We used the SWAT model to quantify the effects of future climate, land cover, and management changes under multiple scenarios up to the 2050s. The combined effect of climate and land use change on N-NO3 and P-PO4 loads is an increase by 20–60 and 24–31 %, respectively, depending on the intensity of future agricultural usage. Using a scenario that assumes a major shift toward a more intensive agriculture following the Danish model would bring significantly higher crop yields but cause a great deterioration of water quality. Using vegetative cover in winter and spring (VC) would be a very efficient way to reduce future P-PO4 loads so that they are lower than levels observed at present. However, even the best combination of measures (VC, buffer zones, reduced fertilization, and constructed wetlands) would not help to remediate heavily increased N-NO3 loads due to climate change and agricultural intensification
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Resolution of data is a sensitive issue in environmental modeling
. Professionals from diverse background use Geographic Information Systems (GIS) for environmental modeling. Availability of GIS software and publicly available digital data make modeling more accessible to anyone, but without proper understanding of the resampling and resolution of the digital database, model results are of little practical significance. It is imperative that the government agencies and their contractors responsible for using GIS-based modeling to implement regulatory goals must have strong foundational knowledge of resolution of data and their implications. This study utilizes the SWAT (Soil and Water Assessment Tool) model integrated with ArcView to examine how sensitive the SWAT model was to the resolution of Digital Elevation Models (DEMs) while predicting the streamflow. This research uses a case study to demonstrate to the modeling community that resolution of data matters when predicting flow. If there were no effect of resolution on the modeled results then the original 90 m DEM and the original 30 m DEM resampled to 90 m would show similar trends. Initial input layers into SWAT were: DEMs, soils, landuse (LU) and meteorological data. The model-predicted streamflow was validated against USGS (US Geological Survey) stream gauge data. DEMs are available at 30, 90 and 300 m resolution originally; therefore, this study analysed the sensitivity of the predicted streamflow at 30, 90 and 300 m resolution. Results indicated that SWAT is indeed sensitive to the resolution of the DEMs: original 90 and 30 m DEM resampled to 90 m did not show the same trend. Therefore, the effects of resolution cannot be ignored and resampling may not be adequate in modeling stream flows using a distributed watershed model.
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The combined use of remote sensing and a distributed hydrological model have demonstrated the improved understanding of the entire water balance in an area where data are scarcely available
. Water use and crop water productivity were assessed in the Upper Bhima catchment in southern India using an innovative integration of remotely sensed evapotranspiration and a process-based hydrological model. The remote sensing based Surface Energy Balance Algorithm for Land (SEBAL) was used to derive an 8 month time series of observed actual evapotranspiration from October 2004 to May 2005. This dataset was then used in the calibration of the Soil and Water Assessment Tool (SWAT). This hydrological model was calibrated by changing 34 parameters to minimize the difference between simulated and observed actual evapotranspiration. The calibration efficiency was assessed with four different performance indicators. The calibrated model was used to derive a monthly basin water balance and to assess crop water productivity and crop water use for the irrigation year 2004-2005. It was found that evapotranspiration is the largest water loss in the catchment and total evaporative depletion was 38,172 Mm3 (835 mm). Of the total evaporative depletion 42% can be considered as non-beneficial and could be diverted to other beneficial utilization. Simulated crop water productivities for sugarcane, sorghum and winter wheat are relatively high at 2.9 kg/m3, 1.3 kg/m3 and 1.3 kg/m3, respectively. The frequency distributions of crop water productivity are characterised by low coefficient of variation, yielding limited scope for improvement in the agricultural areas under the current cropping systems. Further improvements in water productivity may however be achieved by shifting the crop base from sugarcane to a dual crop and introducing a fallow period from March to May or by converting non-productive rangelands to bio fuel production or other agricultural land uses. © 2007 Elsevier B.V. All rights reserved
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Calibrating spatially distributed hydrological models is complex due to the lack of reliable data, uncertainty in representing the physical features of a river catchment, and the implementation of hydrological processes in a simulation model
. In this paper, an innovative approach is presented which incorporates remote sensing derived evapotranspiration in the calibration of the Soil and Water Assessment Tool (SWAT) in a catchment of the Krishna basin in southern India. The Gauss–Marquardt–Levenberg algorithm is implemented to optimise different combination of land use, soil, groundwater, and meteorological model parameters. In the best performing optimisation, the r2 between monthly sub-basin simulated and measured actual evapotranspiration (ETact) was increased from 0.40 to 0.81. ETact was more sensitive to the groundwater and meteorological parameters than the soil and land use parameters. Traditional calibration on a limited number of discharge stations lumps all hydrological processes together and chances on the equifinality problem are larger. In this study we have shown this problem can be constrained by using spatially distributed observations with a monthly temporal resolution. At a spatial resolution below the sub-basin level further study is required to fine-tune the calibration procedure
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