scholarly journals A Catchment Scale Assessment of Water Balance Components: A Case Study of Chittar Catchment in South India

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.

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>


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.


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.


2021 ◽  
Vol 11 (24) ◽  
pp. 11791
Author(s):  
Megersa Kebede Leta ◽  
Tamene Adugna Demissie ◽  
Muhammad Waseem

Hydrological modeling is a technique for understanding hydrologic characteristics and estimation of the water balance of watersheds for integrated water resources development and management. The Soil and Water Assessment Tool (SWAT) model was used for modeling the hydrological behavior of the Nashe watershed in the north-western part of Ethiopia. The spatial data, daily climate, and stream flow were the required input data for the model. The observed monthly stream flow data at the outlet and selected sub-watersheds in the catchment were used to calibrate and validate the model. The model performance was assessed between the simulated and observed streamflow by using sequential uncertainty fitting-2 (SUFI-2), generalized likelihood uncertainty estimation, parameter solution (Parasol) and particle swarm optimization. The sensitivity of 18 parameters was tested, and the most sensitive parameters were identified. The model performance was evaluated using p and r- factor, coefficient of determination, Nash Sutcliffe coefficient efficiency, percent bias during uncertainty analysis, calibration and validation. Therefore, based on the set of proposed evaluation criteria, the SUFI-2 algorithm has been able to provide slightly more reasonable outcomes and Parasol is the worst compared to the other algorithms. An analysis of monthly and seasonal water balance has been also accomplished for the Nashe catchment. The water balance parameters were distinct for the three seasonal periods in the catchment. The seasonal water budget analysis reveals that the watershed receives around 19%, 69%, and 12% of rainfall through the short rain, long rain and dry seasons, respectively. The received precipitation was lost due to evapotranspiration by 29%, 34% and 37% for each season respectively. The surface runoff contributes to the catchment by 5%, 86% and 9% of the water yield.


Earth ◽  
2021 ◽  
Vol 2 (2) ◽  
pp. 225-247
Author(s):  
Mateso Said ◽  
Canute Hyandye ◽  
Ibrahimu Chikira Mjemah ◽  
Hans Charles Komakech ◽  
Linus Kasian Munishi

This study provides a detailed assessment of land cover (LC) changes on the water balance components on data constrained Kikafu-Weruweru-Karanga (KWK) watershed, using the integrated approaches of hydrologic modeling and partial least squares regression (PLSR). The soil and water assessment tool (SWAT) model was validated and used to simulate hydrologic responses of water balance components response to changes in LC in spatial and temporal scale. PLSR was further used to assess the influence of individual LC classes on hydrologic components. PLSR results revealed that expansion in cultivation land and built-up area are the main attributes in the changes in water yield, surface runoff, evapotranspiration (ET), and groundwater flow. The study findings suggest that improving the vegetation cover on the hillside and abandoned land area could help to reduce the direct surface runoff in the KWK watershed, thus, reducing flooding recurring in the area, and that with the ongoing expansion in agricultural land and built-up areas, there will be profound negative impacts in the water balance of the watershed in the near future (2030). This study provides a forecast of the future hydrological parameters in the study area based on changes in land cover if the current land cover changes go unattended. This study provides useful information for the advancement of our policies and practices essential for sustainable water management planning.


Water ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 1511
Author(s):  
Jung-Ryel Choi ◽  
Il-Moon Chung ◽  
Se-Jin Jeung ◽  
Kyung-Su Choo ◽  
Cheong-Hyeon Oh ◽  
...  

Climate change significantly affects water supply availability due to changes in the magnitude and seasonality of runoff and severe drought events. In the case of Korea, despite high water supply ratio, more populations have continued to suffer from restricted regional water supplies. Though Korea enacted the Long-Term Comprehensive Water Resources Plan, a field survey revealed that the regional government organizations limitedly utilized their drought-related data. These limitations present a need for a system that provides a more intuitive drought review, enabling a more prompt response. Thus, this study presents a rating curve for the available number of water intake days per flow, and reviews and calibrates the Soil and Water Assessment Tool (SWAT) model mediators, and found that the coefficient of determination, Nash–Sutcliffe efficiency (NSE), and percent bias (PBIAS) from 2007 to 2011 were at 0.92, 0.84, and 7.2%, respectively, which were “very good” levels. The flow recession curve was proposed after calculating the daily long-term flow and extracted the flow recession trends during days without precipitation. In addition, the SWAT model’s flow data enables the quantitative evaluations of the number of available water intake days without precipitation because of the high hit rate when comparing the available number of water intake days with the limited water supply period near the study watershed. Thus, this study can improve drought response and water resource management plans.


2018 ◽  
Vol 49 (3) ◽  
pp. 908-923 ◽  
Author(s):  
Richarde Marques da Silva ◽  
José Carlos Dantas ◽  
Joyce de Araújo Beltrão ◽  
Celso A. G. Santos

Abstract A Soil and Water Assessment Tool (SWAT) model was used to model streamflow in a tropical humid basin in the Cerrado biome, southeastern Brazil. This study was undertaken in the Upper São Francisco River basin, because this basin requires effective management of water resources in drought and high-flow periods. The SWAT model was calibrated for the period of 1978–1998 and validated for 1999–2007. To assess the model calibration and uncertainty, four indices were used: (a) coefficient of determination (R2); (b) Nash–Sutcliffe efficiency (NS); (c) p-factor, the percentage of data bracketed by the 95% prediction uncertainty (95PPU); and (d) r-factor, the ratio of average thickness of the 95PPU band to the standard deviation of the corresponding measured variable. In this paper, average monthly streamflow from three gauges (Porto das Andorinhas, Pari and Ponte da Taquara) were used. The results indicated that the R2 values were 0.73, 0.80 and 0.76 and that the NS values were 0.68, 0.79 and 0.73, respectively, during the calibration. The validation also indicated an acceptable performance with R2 = 0.80, 0.76, 0.60 and NS = 0.61, 0.64 and 0.58, respectively. This study demonstrates that the SWAT model provides a satisfactory tool to assess basin streamflow and management in Brazil.


2019 ◽  
Vol 23 (2) ◽  
pp. 1113-1144 ◽  
Author(s):  
Abolanle E. Odusanya ◽  
Bano Mehdi ◽  
Christoph Schürz ◽  
Adebayo O. Oke ◽  
Olufiropo S. Awokola ◽  
...  

Abstract. The main objective of this study was to calibrate and validate the eco-hydrological model Soil and Water Assessment Tool (SWAT) with satellite-based actual evapotranspiration (AET) data from the Global Land Evaporation Amsterdam Model (GLEAM_v3.0a) and from the Moderate Resolution Imaging Spectroradiometer Global Evaporation (MOD16) for the Ogun River Basin (20 292 km2) located in southwestern Nigeria. Three potential evapotranspiration (PET) equations (Hargreaves, Priestley–Taylor and Penman–Monteith) were used for the SWAT simulation of AET. The reference simulations were the three AET variables simulated with SWAT before model calibration took place. The sequential uncertainty fitting technique (SUFI-2) was used for the SWAT model sensitivity analysis, calibration, validation and uncertainty analysis. The GLEAM_v3.0a and MOD16 products were subsequently used to calibrate the three SWAT-simulated AET variables, thereby obtaining six calibrations–validations at a monthly timescale. The model performance for the three SWAT model runs was evaluated for each of the 53 subbasins against the GLEAM_v3.0a and MOD16 products, which enabled the best model run with the highest-performing satellite-based AET product to be chosen. A verification of the simulated AET variable was carried out by (i) comparing the simulated AET of the calibrated model to GLEAM_v3.0b AET, which is a product that has different forcing data than the version of GLEAM used for the calibration, and (ii) assessing the long-term average annual and average monthly water balances at the outlet of the watershed. Overall, the SWAT model, composed of the Hargreaves PET equation and calibrated using the GLEAM_v3.0a data (GS1), performed well for the simulation of AET and provided a good level of confidence for using the SWAT model as a decision support tool. The 95 % uncertainty of the SWAT-simulated variable bracketed most of the satellite-based AET data in each subbasin. A validation of the simulated soil moisture dynamics for GS1 was carried out using satellite-retrieved soil moisture data, which revealed good agreement. The SWAT model (GS1) also captured the seasonal variability of the water balance components at the outlet of the watershed. This study demonstrated the potential to use remotely sensed evapotranspiration data for hydrological model calibration and validation in a sparsely gauged large river basin with reasonable accuracy. The novelty of the study is the use of these freely available satellite-derived AET datasets to effectively calibrate and validate an eco-hydrological model for a data-scarce catchment.


Water ◽  
2019 ◽  
Vol 11 (3) ◽  
pp. 594 ◽  
Author(s):  
Majid Fereidoon ◽  
Manfred Koch ◽  
Luca Brocca

Hydrological models are widely used for many purposes in water sector projects, including streamflow prediction and flood risk assessment. Among the input data used in such hydrological models, the spatial-temporal variability of rainfall datasets has a significant role on the final discharge estimation. Therefore, accurate measurements of rainfall are vital. On the other hand, ground-based measurement networks, mainly in developing countries, are either nonexistent or too sparse to capture rainfall accurately. In addition to in-situ rainfall datasets, satellite-derived rainfall products are currently available globally with high spatial and temporal resolution. An innovative approach called SM2RAIN that estimates rainfall from soil moisture data has been applied successfully to various regions. In this study, first, soil moisture content derived from the Advanced Microwave Scanning Radiometer for the Earth observing system (AMSR-E) is used as input into the SM2RAIN algorithm to estimate daily rainfall (SM2R-AMSRE) at different sites in the Karkheh river basin (KRB), southwest Iran. Second, the SWAT (Soil and Water Assessment Tool) hydrological model was applied to simulate runoff using both ground-based observed rainfall and SM2R-AMSRE rainfall as input. The results reveal that the SM2R-AMSRE rainfall data are, in most cases, in good agreement with ground-based rainfall, with correlations R ranging between 0.58 and 0.88, though there is some underestimation of the observed rainfall due to soil moisture saturation not accounted for in the SM2RAIN equation. The subsequent SWAT-simulated monthly runoff from SM2R-AMSRE rainfall data (SWAT-SM2R-AMSRE) reproduces the observations at the six gauging stations (with coefficient of determination, R² > 0.71 and NSE > 0.56), though with slightly worse performances in terms of bias (Bias) and root-mean-square error (RMSE) and, again, some systematic flow underestimation compared to the SWAT model with ground-based rainfall input. Additionally, rainfall estimates of two satellite products of the Tropical Rainfall Measuring Mission (TRMM), 3B42 and 3B42RT, are used in the calibrated SWAT- model after bias correction. The monthly runoff predictions obtained with 3B42- rainfall have 0.42 < R2 < 0.72 and−0.06 < NSE < 0.74 which are slightly better than those obtained with 3B42RT- rainfall, but not as good as the SWAT-SM2R-AMSRE. Therefore, despite the aforementioned limitations, using SM2R-AMSRE rainfall data in a hydrological model like SWAT appears to be a viable approach in basins with limited ground-based rainfall data.


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