scholarly journals Evaluation of the CRU TS3.1, APHRODITE_V1101, and CFSR Datasets in Assessing Water Balance Components in the Upper Vakhsh River Basin in Central Asia

Atmosphere ◽  
2021 ◽  
Vol 12 (10) ◽  
pp. 1334
Author(s):  
Aminjon Gulakhmadov ◽  
Xi Chen ◽  
Manuchekhr Gulakhmadov ◽  
Zainalobudin Kobuliev ◽  
Nekruz Gulahmadov ◽  
...  

In this study, the applicability of three gridded datasets was evaluated (Climatic Research Unit (CRU) Time Series (TS) 3.1, “Asian Precipitation—Highly Resolved Observational Data Integration Toward the Evaluation of Water Resources” (APHRODITE)_V1101, and the climate forecast system reanalysis dataset (CFSR)) in different combinations against observational data for predicting the hydrology of the Upper Vakhsh River Basin (UVRB) in Central Asia. Water balance components were computed, the results calibrated with the SUFI-2 approach using the calibration of soil and water assessment tool models (SWAT–CUP) program, and the performance of the model was evaluated. Streamflow simulation using the SWAT model in the UVRB was more sensitive to five parameters (ALPHA_BF, SOL_BD, CN2, CH_K2, and RCHRG_DP). The simulation for calibration, validation, and overall scales showed an acceptable correlation between the observed and simulated monthly streamflow for all combination datasets. The coefficient of determination (R2) and Nash–Sutcliffe efficiency (NSE) showed “excellent” and “good” values for all datasets. Based on the R2 and NSE from the “excellent” down to “good” datasets, the values were 0.91 and 0.92 using the observational datasets, CRU TS3.1 (0.90 and 0.90), APHRODITE_V1101+CRU TS3.1 (0.74 and 0.76), APHRODITE_V1101+CFSR (0.72 and 0.78), and CFSR (0.67 and 0.74) for the overall scale (1982–2006). The mean annual evapotranspiration values from the UVRB were about 9.93% (APHRODITE_V1101+CFSR), 25.52% (APHRODITE_V1101+CRU TS3.1), 2.9% (CFSR), 21.08% (CRU TS3.1), and 27.28% (observational datasets) of annual precipitation (186.3 mm, 315.7 mm, 72.1 mm, 256.4 mm, and 299.7 mm, out of 1875.9 mm, 1236.9 mm, 2479 mm, 1215.9 mm, and 1098.5 mm). The contributions of the snowmelt to annual runoff were about 81.06% (APHRODITE_V1101+CFSR), 63.12% (APHRODITE_V1101+CRU TS3.1), 82.79% (CFSR), 81.66% (CRU TS3.1), and 67.67% (observational datasets), and the contributions of rain to the annual flow were about 18.94%, 36.88%, 17.21%, 18.34%, and 32.33%, respectively, for the overall scale. We found that gridded climate datasets can be used as an alternative source for hydrological modeling in the Upper Vakhsh River Basin in Central Asia, especially in scarce-observation regions. Water balance components, simulated by the SWAT model, provided a baseline understanding of the hydrological processes through which water management issues can be dealt with in the basin.

Atmosphere ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1641
Author(s):  
Aminjon Gulakhmadov ◽  
Xi Chen ◽  
Manuchekhr Gulakhmadov ◽  
Zainalobudin Kobuliev ◽  
Nekruz Gulahmadov ◽  
...  

The authors were not aware of errors that were made during the proofreading phase and would hence wish to make the below-mentioned corrections to this paper [...]


2020 ◽  

<p>Hydrological modeling of a watershed is necessary for water resources planning and management. The hydrology of upper Ribb watershed has been analyzed using spatially semi-distributed Soil and water assessment tool (SWAT) model. This study aimed to determine the water balance components and its relation with the rainfall which reaches to the surface of the earth. Different spatio-temporal (land use, soil, digital elevation model, climate data, river discharge) data were used for hydrological modelling of Upper Ribb watershed. The applicability of SWAT model in Upper Ribb watershed has been evaluated using coefficient of determination (R2) and Nash Sutcliff efficiency (NSE) parameters. The calibration results revealed the observed data showed a very good agreement with the simulated data with the R2 and NSE values of 0.90 and 0.84 respectively. Similarly, the validation results of streamflow were acceptable with the R2 and NSE values of 0.80 and 0.82 respectively. The monthly average streamflow from Upper Ribb watershed were found 13.39 m3/s. The major portion of the rainfall contributes to the surface runoff due to the major percentage of the watershed is covered with agricultural lands. The groundwater flow was high in forested areas, while evapotranspiration was found very high in water bodies (Ribb reservoir). In this study area the rainfall showed a direct relationship with the streamflow. The ratio of streamflow and evapotranspiration with rainfall was 0.61 and 0.36 respectively. Due to the presence of high amount of surface runoff and evapotranspiration the deep recharge which contributes to the ground water is not that much significant.</p>


Water resources planning and management of a region requires an understanding of the water balance in the region. The Soil and Water Assessment Tool (SWAT) with QGIS interface (QSWAT) has been used here to arrive at the water balance components in the Palapuzha watershed of Valapattanam river basin in Kerala. Valapattanam river drains an area of 1867 sq.km. with 456 sq.km. area in Karnataka State. The river basin receives an average annual rainfall of 3600 mm. The Palapuzha watershed drains an area of 237.25 sq.km with an average annual rainfall of 4562 mm. The QSWAT model has been calibrated and validated using data for a period of eight years (2000-2007) for which both rainfall and streamflow data are available. The model was successful in simulating monthly streamflow during the calibration and validation periods with Nash Sutcliffe efficiency and correlation co-efficient greater than 0.75 and percent bias less than 10%, showing that the model is very good for predicting streamflow in Valapattanam river basin. This calibrated model was used to arrive at the different water balance components in the Palapuzha watershed. The results obtained will be useful for the sustainable development and planning of the water resources system in the highland humid tropical watersheds


2021 ◽  
Author(s):  
Dinagarapandi Pandi ◽  
Saravanan Kothandaraman ◽  
K S Kasiviswanathan ◽  
Mohan Kuppusamy

Abstract Analyzing the Water Balance Components (WBCs) of catchment help in assessing the water resources for their sustainable management and development. This paper used Soil and Water Assessment Tool (SWAT) model mainly to analyze the variation in the WBCs through the change in the Land Use and Land Cover (LULC) and meteorological variables. For this purpose, the model used the inputs of LULC and meteorological variables between the year 2001-2020 at five year and daily time interval respectively from the Chittar river catchment. The developed models were evaluated using SWAT-CUP split-up procedure (pre-calibration and post-calibration). The model was found to be good in calibration and validation, yielding the coefficient of determination (R2) of 0.94 and 0.81 respectively. Furthermore, WBCs of the catchment were estimated for the near future (2021 - 2030) at monthly and annual scale. For this endeavour, LULC was forecasted for the year 2021 and 2026 using Celluar Automata (CA)-ANN and for the same period meteorological variables were also forecasted using the smoothing moving average method from the historical data.


Water ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 2626 ◽  
Author(s):  
Yongyu Song ◽  
Jing Zhang ◽  
Xianyong Meng ◽  
Yuyan Zhou ◽  
Yuequn Lai ◽  
...  

As a key factor in the water cycle and climate change, the quality of precipitation data directly affects the hydrological processes of the river basin. Although many precipitation products with high spatial and temporal resolutions are now widely used, it is meaningful and necessary to investigate and evaluate their merits and demerits in hydrological applications. In this study, two satellite-based precipitation products (Tropical Rainfall Measurement Mission, TRMM; Integrated Multi-satellite Retrievals for GPM, IMERG) and one reanalysis precipitation product (China Meteorological Assimilation Driving Datasets for the Soil and Water Assessment Tool (SWAT) model, CMADS) are studied to compare their streamflow simulation performance in the Qujiang River Basin, China, using the SWAT model with gauged rainfall data as a reference. The main conclusions are as follows: (1) CMADS has stronger precipitation detection capabilities compared to gauged rainfall, while TRMM results in the most obvious overestimation in the four sub-basins. (2) In daily and monthly streamflow simulations, CMADS + SWAT mode offers the best performance. CMADS and IMERG can provide high quality precipitation data for data-scarce areas, and IMERG can effectively avoid the overestimation of streamflow caused by TRMM, especially on a daily scale. (3) The runoff projections of the three modes under RCP (Representative Concentration Pathway) 4.5 was higher than that of RCP 8.5 on the whole. IMERG + SWAT overestimates the surface water resources of the basin compared to CMADS + SWAT, while TRMM + SWAT provides the most stable uncertainty. These findings contribute to the comparison of the differences among the three precipitation products and provides a reference for the selection of precipitation data in similar regions.


Author(s):  
Kidane Reda ◽  
Xingcai Liu ◽  
Gebremedhin Haile ◽  
Siao Sun ◽  
Qiuhong Tang

Spatial rainfall data is an essential input to physically based, parametrically distributed hydrological models, and a main contributor to hydrological model uncertainty. Two important issues should be addressed before use of satellite and reanalysis rainfall product at basin level: 1) how useful are these rainfall estimates as forcing data for regional hydrological modeling? 2) which should be preferred for hydrological modelling at high flow and low flow seasons? To this end, rainfall estimates from a satellite-based product, CHIRPSv8, and reanalysis data, EWEMBI, were used as input to SWAT model, and mode performances were evaluated against streamflow measured at three gauge stations in the Upper Tekeze River basin, northern Ethiopia for the period of 2006-2015. Results showed that (I) the daily rainfall from both CHIRPSv8 and EWEMBI are close to the rain gauge data, with relative errors 2.12% and 3.85%, respectively; (II) the monthly streamflow simulated by the SWAT model driven by the CHIRPSv8 and EWEMBI had a Kling-Gupta Efficiency value of 0.6-0.79 and 0.58-0.64, respectively; (III) the SWAT model calibrated with the CHIRPSv8 and EWEMBI rainfall estimates has shown an improvement in hydrological performance compared with that calibrated with interpolated ground observations; (IV) the hydrological performance during high flow seasons is superior to low flow seasons for both CHIRPSv8 and EWEMBI, thus promoting the use of the products for applications focusing on the high flow conditions. In particular, CHIRPSv8 showed relatively better hydrologic performance than EWEMBI. This study provides insight on the usefulness of the gridded rainfall products for hydrological modeling and under which conditions they can be used to generate a plausible level of adequacy and reliability over the Upper Tekeze River basin.


This study mainly focus on hydrological behavior of watersheds in The Manjira River basin using soil and water assessment tool (SWAT) and Geographical information system (GIS). The water balance components for watersheds in the Manjira River were determined by using SWAT model and GIS. Determination of these water balance components helps to study direct and indirect factors affecting characteristics of selected watersheds. Manjira River contains total 28 watersheds among them 2 were selected having watershed code as MNJR008 and MNJR011 specified by the Central Ground Water Board. The SWAT input data such as Digital elevation model (DEM), land use and land cover (LU/LC), Soil classification, slope and weather data was collected. Using these inputs in SWAT the different water balancing components such as rainfall, baseflow, surface runoff, evapotranspiration (ET), potential evapotranspiration (PET) and water yield for each watershed were determined. The evaluated data is then validated by Regression analysis, in which two datasets were compared. Simulated rain data from SWAT simulation and observed rain data from Global Weather Data for SWAT was selected for comparison for each watershed.


Water ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 2901
Author(s):  
Davy Sao ◽  
Tasuku Kato ◽  
Le Hoang Tu ◽  
Panha Thouk ◽  
Atiqotun Fitriyah ◽  
...  

Many calibration techniques have been developed for the Soil and Water Assessment Tool (SWAT). Among them, the SWAT calibration and uncertainty program (SWAT-CUP) with sequential uncertainty fitting 2 (SUFI-2) algorithm is widely used and several objective functions have been implemented in its calibration process. In this study, eight different objective functions were used in a calibration of stream flow of the Pursat River Basin of Cambodia, a tropical monsoon and forested watershed, to examine their influences on the calibration results, parameter optimizations, and water resources estimations. As results, many objective functions performed better than satisfactory in calibrating the SWAT model. However, different objective functions defined different fitted values and sensitivity rank of the calibrated parameters, except Nash–Sutcliffe efficiency (NSE) and ratio of standard deviation of observations to root mean square error (RSR) which are equivalent and produced quite identical simulation results including parameter sensitivity and fitted parameter values, leading to the same water balance components and water yields estimations. As they generated reasonable fitted parameter values, either NSE or RSR gave better estimation results of annual average water yield and other water balance components such as annual average evapotranspiration, groundwater flow, surface runoff, and lateral flow according to the characteristics of the river basin and the results and data of previous studies. Moreover, either of them was also better in calibrating base flow, falling limb, and overall the entire flow phases of the hydrograph in this area.


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