scholarly journals Impending Hydrological Regime of Lhasa River as Subjected to Hydraulic Interventions—A SWAT Model Manifestation

2021 ◽  
Vol 13 (7) ◽  
pp. 1382
Author(s):  
Muhammad Yasir ◽  
Tiesong Hu ◽  
Samreen Abdul Hakeem

The damming of rivers has altered their hydrological regimes. The current study evaluated the impacts of major hydrological interventions of the Zhikong and Pangduo hydropower dams on the Lhasa River, which was exposed in the form of break and change points during the double-mass curve analysis. The coefficient of variability (CV) for the hydro-meteorological variables revealed an enhanced climate change phenomena in the Lhasa River Basin (LRB), where the Lhasa River (LR) discharge varied at a stupendous magnitude from 2000 to 2016. The Mann–Kendall trend and Sen’s slope estimator supported aggravated hydro-meteorological changes in LRB, as the rainfall and LR discharge were found to have been significantly decreasing while temperature was increasing from 2000 to 2016. The Sen’s slope had a largest decrease for LR discharge in relation to the rainfall and temperature, revealing that along with climatic phenomena, additional phenomena are controlling the hydrological regime of the LR. Reservoir functioning in the LR is altering the LR discharge. The Soil and Water Assessment Tool (SWAT) modeling of LR discharge under the reservoir’s influence performed well in terms of coefficient of determination (R2), Nash–Sutcliffe coefficient (NSE), and percent bias (PBIAS). Thus, simulation-based LR discharge could substitute observed LR discharge to help with hydrological data scarcity stress in the LRB. The simulated–observed approach was used to predict future LR discharge for the time span of 2017–2025 using a seasonal AutoRegressive Integrated Moving Average (ARIMA) model. The predicted simulation-based and observation-based discharge were closely correlated and found to decrease from 2017 to 2025. This calls for an efficient water resource planning and management policy for the area. The findings of this study can be applied in similar catchments.

Water ◽  
2018 ◽  
Vol 10 (8) ◽  
pp. 1004 ◽  
Author(s):  
Guihua Liu ◽  
Zhiming He ◽  
Zhaoqing Luan ◽  
Shuhua Qi

Water supply availability has significant impacts on the biggest base for commodity grain production: The Sanjiang Plain in northeast China. The SWAT (soil and water assessment tool) model and IHACRES (identification of unit hydrographs and component flows from rainfall, evapotranspiration and streamflow data) model were used for modelling streamflow variability in the upper Naoli River watershed to determine the applicability of hydrological models to the marsh rivers. Both the SWAT and IHACRES models were suitable for streamflow simulation, having R2 (coefficient of determination) and NS (Nash–Sutcliffe) values greater than 0.7, and PBIAS (percent bias) smaller than 25%. The IHACRES model was easy to use, with less data-preparation, and was found to be a better choice for runoff simulation in a watershed less affected by human activity. The simulation result was better in primeval times, i.e., 1956–1966, than the period 1967–2005, when its performance was found to be unfavorable. In contrast, the complex, processes-based SWAT model was found to be more appropriate for simultaneously simulating streamflow variability. In addition, the effects of land use change and human activities in the watershed—where agricultural activities are intensive—were evaluated. The study found that the SWAT model was potentially suitable for water resource planning and management.


Author(s):  
B. Bade ◽  
D. R. Gyawali ◽  
S. Timilsina

Abstract. This study details climate change assessment of the hydrological regime of Indrawati basin of Nepal. The study uses Soil and Water Assessment Tool (SWAT) model to delineate, discretize and parameterize the Indrawati basin to compute model’s input parameters. The model was then run for 1990–2014 to simulate the discharge at the outlet (Dholalghat). The coefficient of determination R2 and Nash-Sutcliffe (ENS) were used to evaluate model calibration and validation. The results found were satisfactory for the gauging station R2 = 0.951 and ENS = 0.901 for calibration and R2 = 0.937 and. ENS = 0.906 for validation. The calibrated hydrological model was run for the future climate change scenario using the RegCM4-LMDZ4 data and the relative changes with the baseline scenarios were analyzed. The comparison suggests that the historical trend of flow is decreasing at the rate of 0.55 m3/s per year. According to RegCM4-LMDZ4 simulations, the trend is going to continue but at a flatter rate. The decreasing trend is observed to be very less. The characteristic peak flow month in the historical scenario is August but the RegCM4-LMDZ4 led simulated flows suggest a shift in monthly peak to October suggesting decrease in monsoon flows and a subsequent significant increase in flows from October to January.


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.


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.


Agronomy ◽  
2019 ◽  
Vol 9 (10) ◽  
pp. 576 ◽  
Author(s):  
Adrián López-Ballesteros ◽  
Javier Senent-Aparicio ◽  
Raghavan Srinivasan ◽  
Julio Pérez-Sánchez

Best management practices (BMPs) provide a feasible solution for non-point source pollution problems. High sediment and nutrient yields without retention control result in environmental deterioration of surrounding areas. In the present study, the soil and water assessment tool (SWAT) model was developed for El Beal watershed, an anthropogenic and ungauged basin located in the southeast of Spain that drains into a coastal lagoon of high environmental value. The effectiveness of five BMPs (contour planting, filter strips, reforestation, fertilizer application and check dam restoration) was quantified, both individually and in combination, to test their impact on sediment and nutrient reduction. For calibration and validation processes, actual evapotranspiration (AET) data obtained from a remote sensing dataset called Global Land Evaporation Amsterdam Model (GLEAM) were used. The SWAT model achieved good performance in the calibration period, with statistical values of 0.78 for Kling–Gupta efficiency (KGE), 0.81 for coefficient of determination (R2), 0.58 for Nash–Sutcliffe efficiency (NSE) and 3.9% for percent bias (PBIAS), as well as in the validation period (KGE = 0.67, R2 = 0.83, NS = 0.53 and PBIAS = −25.3%). The results show that check dam restoration is the most effective BMP with a reduction of 90% in sediment yield (S), 15% in total nitrogen (TN) and 22% in total phosphorus (TP) at the watershed scale, followed by reforestation (S = 27%, TN = 16% and TP = 20%). All effectiveness values improved when BMPs were assessed in combination. The outcome of this study could provide guidance for decision makers in developing possible solutions for environmental problems in a coastal lagoon.


Author(s):  
N. C. Sanjay Shekar ◽  
D. C. Vinay

Abstract The present study was conducted to examine the accuracy and applicability of the hydrological models Soil and Water Assessment Tool (SWAT) and Hydrologic Engineering Center (HEC)- Hydrologic Modeling System (HMS) to simulate streamflows. Models combined with the ArcGIS interface have been used for hydrological study in the humid tropical Hemavathi catchment (5,427 square kilometer). The critical focus of the streamflow analysis was to determine the efficiency of the models when the models were calibrated and optimized using observed flows in the simulation of streamflows. Daily weather gauge stations data were used as inputs for the models from 2014–2020 period. Other data inputs required to run the models included land use/land cover (LU/LC) classes resulting from remote sensing satellite imagery, soil map and digital elevation model (DEM). For evaluating the model performance and calibration, daily stream discharge from the catchment outlet data were used. For the SWAT model calibration, available water holding capacity by soil (SOL_AWC), curve number (CN) and soil evaporation compensation factor (ESCO) are identified as the sensitive parameters. Initial abstraction (Ia) and lag time (Tlag) are the significant parameters identified for the HEC-HMS model calibration. The models were subsequently adjusted by autocalibration for 2014–2017 to minimize the variations in simulated and observed streamflow values at the catchment outlet (Akkihebbal). The hydrological models were validated for the 2018–2020 period by using the calibrated models. For evaluating the simulating daily streamflows during calibration and validation phases, performances of the models were conducted by using the Nash-Sutcliffe model efficiency (NSE) and coefficient of determination (R2). The SWAT model yielded high R2 and NSE values of 0.85 and 0.82 for daily streamflow comparisons for the catchment outlet at the validation time, suggesting that the SWAT model showed relatively good results than the HEC-HMS model. Also, under modified LU/LC and ungauged streamflow conditions, the calibrated models can be later used to simulate streamflows for future predictions. Overall, the SWAT model seems to have done well in streamflow analysis capably for hydrological studies.


2020 ◽  
pp. 22-31 ◽  
Author(s):  
Nguyen Kim Loi ◽  
Vo Ngoc Quynh Tram ◽  
Nguyen Thi Tinh Au

Climate is the main factor affecting hydrology in a watershed. For purely agricultural watershed, hydrological assessment and management play a very important role in the region's agricultural development. In this study, the hydrological was simulated by the Soil and Water Assessment Tool (SWAT) model. This paper aimed to calibrate and validate the SWAT model in Dak B’la watershed in Central Highland Vietnam and assess the climate change on water discharge. The coefficient of determination (R²) and Nash-Sutcliffe index (NSI), and Percent BIAS (PBIAS) during the calibration process was 0.75, 0.72, and -1.15 respectively and validation process was 0.82, 0.83, 3.67 respectively. It proved the high reliability of the SWAT model after calibration. The two climate scenarios were selected in this investigation: scenario A is the existing climate using the data from 2001 to 2018 and scenario B is the A1B emission scenario for the future period from 2020 to 2069. Compared to the average water discharge from 2001-2018 and average water discharge from 2020 to 2069, the results indicated that climate change increases the average water discharge (0.55%), especially in 2050, the water discharge in the flood season (in November) is 584 m3/s, which higher than the largest flood in 2009 of 450 m3/s.


2013 ◽  
Vol 10 (11) ◽  
pp. 13955-13978 ◽  
Author(s):  
A. A. Shawul ◽  
T. Alamirew ◽  
M. O. Dinka

Abstract. To utilize water resources in a sustainable manner, it is necessary to understand the quantity and quality in space and time. This study was initiated to evaluate the performance and applicability of the physically based Soil and Water Assessment Tool (SWAT) model in analyzing the influence of hydrologic parameters on the streamflow variability and estimation of monthly and seasonal water yield at the outlet of Shaya mountainous watershed. The calibrated SWAT model performed well for simulation of monthly streamflow. Statistical model performance measures, coefficient of determination (r2) of 0.71, the Nash–Sutcliffe simulation efficiency (ENS) of 0.71 and percent difference (D) of 3.69, for calibration and 0.76, 0.75 and 3.30, respectively for validation, indicated good performance of the model simulation on monthly time step. Mean monthly and annual water yield simulated with the calibrated model were found to be 25.8 mm and 309.0 mm, respectively. Overall, the model demonstrated good performance in capturing the patterns and trend of the observed flow series, which confirmed the appropriateness of the model for future scenario simulation. Therefore, SWAT model can be taken as a potential tool for simulation of the hydrology of unguaged watershed in mountainous areas, which behave hydro-meteorologically similar with Shaya watershed. Future studies on Shaya watershed modeling should address the issues related to water quality and evaluate best management practices.


Author(s):  
Moh Sholichin ◽  
Tri Budi Prayogo

Lake Tondano is the largest natural lake in North Sulawesi, Indonesia, which functions as a provider of clean water, hydroelectric power, rice field irrigation, inland fisheries, and tourism. This research aims to determine the effect of land cover types from the Tondano watershed on the lake water quality. The Soil and Water Assessment Tool (SWAT) model was used to evaluate the rate of soil erosion and the pollutant load of various land types in the watershed during the last ten years. Rainfall data is obtained from two rainfall stations, namely Paleloan Station and Noonan Station. The model is calibrated and validated before being used for analysis. We use climatological data from 2014 to 2019. The process of the SWAT model calibration and validation was carried out with the statistical formulas of the coefficient of determination (R2) and Nash-Sutcliffe efficiency (NSE). The results show that the potential for pollution load from the Tondao watershed is organic N of 0.039 kg/ha and organic P of 0.006 kg/ha coming from the agricultural land. The results of this study conclude that the fertility conditions of Lake Tondano are at the eutrophic level, where the pollutant inflow is collected in the lake waters, especially for the parameters of total N (1503697.44kg/year) and total P (144831.36kg/year). The SWAT simulation results show deviation between the modeling and field data collected with the value of R2 = 0.9303, and the significant level ≤ 10.


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