scholarly journals Application of SWAT Model for Assessing Water Availability in Surma River Basin

2019 ◽  
Vol 5 (1) ◽  
pp. 29
Author(s):  
Syeda Zehan Farzana ◽  
Md. Abu Zafor ◽  
Jabed Al Shahariar
Keyword(s):  
Model Simulation ◽  
Water Discharge ◽  
Swat Model ◽  
Model Performance ◽  
Coefficient Of Determination ◽  
Water Balance Components ◽  
Time Step ◽  
Discharge Data ◽  
Space Agency ◽  
Physically Based

Water discharge is a significant hydrological parameter because it defines the shape, size and course of the stream. This study was initiated to evaluate the performance and applicability of the physically based SWAT model in analyzing the influence of hydrologic parameters on the streamflow variability and estimation of water balance components at the outlet of Kanaighat streamflow station (SW266) of Surma basin. A 30-m resolution digital elevation model (DEM) has been used to delineate catchment boundary. Land use map obtained from global source GLOBCOVER (Europe Space Agency) has been reclassified to match the SWAT land classes. The model was first calibrated for the period from 2003 to 2008 and then validated for the period from 2009 to 2013 using the observed monthly discharge data. Statistical model performance measures, coefficient of determination (R2) of 0.780, the Nash–Sutcliffe Index (NSI) of 0.47 and Percent bias (PBIAS) of -53.5%, for calibration and 0.878, 0.74 and -31.7%, respectively for validation, indicated good performance of the model simulation on monthly time step. The results showed that SWAT can simulate the hydrologic characteristics of the watershed very well.

scholarly journals Hydrological modeling of Upper Ribb watershed, Abbay Basin, Ethiopia.

2020 ◽  
Keyword(s):  
Surface Runoff ◽  
Hydrological Modeling ◽  
Assessment Tool ◽  
Swat Model ◽  
Simulated Data ◽  
Coefficient Of Determination ◽  
Climate Data ◽  
Water Balance Components ◽  
Discharge Data ◽  
Forested Areas

<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>

scholarly journals Simulating surface flow and baseflow in Poko catchment, Kon Tum province, Vietnam

2018 ◽  
Vol 10 (3) ◽  
pp. 494-503
Author(s):  
Vo Ngoc Quynh Tram ◽  
Nguyen Duy Liem ◽  
Nguyen Kim Loi
Keyword(s):  
Water Resources ◽  
Water Discharge ◽  
Swat Model ◽  
Surface Flow ◽  
Time Step ◽  
Filter Parameter ◽  
Discharge Data ◽  
Filtering Algorithm ◽  
Statistical Measures ◽  
Central Highland

Abstract Estimating the volume of water resources has important significance in assessing water availability in a basin, particularly in mountainous areas. The Poko catchment, a sub-basin of Se San river basin, is located in the Central Highland of Vietnam with an area of about 3,210 km2. This study focused on evaluating the performance of SWAT model and baseflow filtering algorithm in simulating surface flow and baseflow in Poko catchment. The model was calibrated and validated for the period 1996–2004 and 2005–2013, respectively, using the observed water discharge data at Dak Mot stream gauge. Statistical measures including R2 (coefficient of determination), NSI (Nash–Sutcliffe index), and PBIAS (percent bias) indicated good performance of the model in simulating water discharge on monthly time step during the calibration and validation period. Using baseflow filtering algorithm with filter parameter (0.925), surface flow and baseflow were separated from water discharge. The results demonstrated good performance in capturing the patterns of surface flow and baseflow, which confirmed the appropriateness of the model for future scenario simulation. These findings provide useful information for water resources planning in Poko catchment, in particular, and other basins, which have a hydro-meteorological response similar to this catchment, in general.

scholarly journals Can We Calibrate a Daily Time-Step Hydrological Model Using Monthly Time-Step Discharge Data?

Water ◽  
2019 ◽  
Vol 11 (9) ◽  
pp. 1750 ◽  
Author(s):  
Soham Adla ◽  
Shivam Tripathi ◽  
Markus Disse
Keyword(s):  
Hydrological Modeling ◽  
Hydrological Model ◽  
Swat Model ◽  
Computation Time ◽  
Agricultural Watershed ◽  
Coefficient Of Determination ◽  
Computational Time ◽  
Time Step ◽  
Discharge Data ◽  
Monthly Data

Hydrological models are generally calibrated at longer time-steps (monthly, seasonal, or annual) than their computational time-step (daily), because of better calibration performance, lower computational requirements, and the lack of reliable temporally-fine observed discharge data (particularly in developing countries). The consequences of having different calibration and computation time-steps on model performance have not been extensively investigated. This study uses the Soil and Water Assessment Tool (SWAT) model to explore the correctness of calibrating a hydrological model at the monthly time-step even if the problem statement is suited to monthly modeling. Multiple SWAT models were set up for an agricultural watershed in the Indo-Gangetic basin. The models were calibrated with observed discharge data of different time-steps (daily and monthly) and were validated on data with the same or different time-steps. Intra- and inter-decadal comparisons were conducted to reinforce the results. The models calibrated on monthly data marginally outperformed the models calibrated on daily data when validated on monthly data, in terms of P- f a c t o r , R- f a c t o r , the coefficient of determination ( R 2 ), and Nash–Sutcliffe Efficiency ( N S E ). However, the monthly-calibrated models performed poorly as compared to daily-calibrated models when validated on daily discharge data. Moreover, the daily simulations from the monthly-calibrated models were unrealistic. Analysis of the calibrated parameters revealed that the daily- and monthly-calibrated models differed significantly in terms of parameters governing channel and groundwater processes. Thus, though the monthly-calibrated model captures the patterns in monthly discharge data fairly well, it fails to characterize daily rainfall-runoff processes. The results challenge the existing practice of using different calibration and computation time-steps in hydrological modeling, and suggest that the two time-steps should be the same, irrespective of the time-step required for modeling.

Global BROOK90: validation, uncertainties, current progress and future outline.

2021 ◽  
Author(s):  
Ivan Vorobevskii ◽  
Rico Kronenberg
Keyword(s):  
Water Balance ◽  
Model Performance ◽  
Low Flow ◽  
Easy Access ◽  
Climate Projections ◽  
Seasonal Forecasts ◽  
Water Balance Components ◽  
Discharge Data ◽  
Small Catchment ◽  
Wide Range

&lt;p&gt;&amp;#8216;Just drop a catchment and receive reasonable model output&amp;#8217; &amp;#8211; still stays as motto and main idea of the &amp;#8216;Global BROOK90&amp;#8217; project. The open-source R-package is build-up on global land cover, soil, topographical, meteorological datasets and the lumped hydrological model as a core to simulate water balance components on HRU scale all over the world in an automatic mode. First introduced in EGU2020 and followed by GitHub code release including an publication of methodology with few examples we want to continue with the insights on the current state and highlight the future steps of the project.&lt;/p&gt;&lt;p&gt;A global validation of discharge and evapotranspiration components of the model showed promising results. We used 190 small (median size of 64 km&lt;sup&gt;2&lt;/sup&gt;) catchments and FLUXNET data which represent a wide range of relief, vegetation and soil types within various climate zones. The model performance was evaluated with NSE, KGE, KGESS and MAE. In more than 75 % of the cases the framework performed better than the mean of the observed discharge. On a temporal scale the performance is significantly better on a monthly vs daily scale. Cluster analysis revealed that some of the site characteristics have a significant influence on the performance. Additionally, it was found that Global BROOK90 outperforms GloFAS ERA5 discharge reanalysis (for the category with smallest catchments).&lt;/p&gt;&lt;p&gt;A cross-combination of three different BROOK90 setups and three forcing datasets was set up to reveal uncertainties of the Global BROOK90 package using a small catchment in Germany as a case study. Going from local to regional and finally global scale we compared mixtures of model parameterization schemes (original calibrated BROOK90, EXTRUSO and Global BROOK90) and meteorological datasets (local gauges, RaKlida and ERA5). Besides high model performances for a local dataset plus a calibrated model and weaker results for ERA5 and the Global BROOK90, it was found that the ERA5 dataset is still able to provide good results when combined with a regional and local parameterization. On the other side, the combination of a global parameterization with local and regional forcings gives still adequate, but much worse results. Furthermore, a hydrograph separation revealed that the Global BROOK90 parameterization as well as ERA5 discharge data perform weaker especially within low flow periods.&lt;/p&gt;&lt;p&gt;Currently, some new features are added to the original package. First, with the recent release of the ERA5 extension, historical simulations with the package now are expanded to 1950-2021 period. Additionally, an alternative climate reanalysis dataset is included in the framework (Merra-2, 0.5x0.625-degree spatial resolution, starting from 1980). A preliminary validation shows insignificant differences between both meteorological datasets with respect to the discharge based model performance.&lt;/p&gt;&lt;p&gt;Further upgrades of the framework will include the following core milestones: recognition of forecast and climate projections and parameter optimization features. In the nearest future we plan to utilize full power of the Climate Data Store for easy access to seasonal forecasts (i.e. ECMWF, DWD, NCEP) as well as climate projections (CMIP5) to extend the package&amp;#8217;s scope to predict near and far future water balance components.&lt;/p&gt;

scholarly journals Using artificial neural network (ANN) for prediction of sediment loads, application to the Mellah catchment, northeast Algeria

2017 ◽  
Vol 33 (1) ◽  
pp. 47-55 ◽  
Author(s):  
Housseyn Bouzeria ◽  
Abderrahmane N. Ghenim ◽  
Kamel Khanchoul
Keyword(s):  
Suspended Sediment ◽  
Time Series Data ◽  
Water Discharge ◽  
Absolute Error ◽  
Coefficient Of Determination ◽  
Series Data ◽  
Sediment Discharge ◽  
Statistical Parameters ◽  
Discharge Data ◽  
Sediment Loads

AbstractIn this study, we present the performances of the best training algorithm in Multilayer Perceptron (MLP) neural networks for prediction of suspended sediment discharges in Mellah catchment. Time series data of daily suspended sediment discharge and water discharge from the gauging station of Bouchegouf were used for training and testing the networks. A number of statistical parameters, i.e. root mean square error (RMSE), mean absolute error (MAE), coefficient of efficiency (CE) and coefficient of determination (R2) were used for performance evaluation of the model. The model produced satisfactory results and showed a very good agreement between the predicted and observed data. The results also showed that the performance of the MLP model was capable to capture the exact pattern of the sediment discharge data in the Mellah catchment.

scholarly journals Performance of HEC-HMS and SWAT to simulate streamflow in the sub-humid tropical Hemavathi catchment

2021 ◽  
Author(s):  
N. C. Sanjay Shekar ◽  
D. C. Vinay
Keyword(s):  
Model Calibration ◽  
Assessment Tool ◽  
Swat Model ◽  
Model Performance ◽  
Curve Number ◽  
Coefficient Of Determination ◽  
Hydrological Models ◽  
Daily Streamflow ◽  
Compensation Factor ◽  
Elevation Model

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.

scholarly journals Effect of length of the observed dataset on the calibration of a distributed hydrological model

2015 ◽  
Vol 368 ◽  
pp. 305-311 ◽  
Author(s):  
X. Cui ◽  
W. Sun ◽  
J. Teng ◽  
H. Song ◽  
X. Yao
Keyword(s):  
Hydrological Model ◽  
Assessment Tool ◽  
Swat Model ◽  
Model Performance ◽  
Hydrological Models ◽  
Distributed Hydrological Model ◽  
Discharge Data ◽  
One Year ◽  
Parameter Values ◽  
Discharge Measurements

Abstract. Calibration of hydrological models in ungauged basins is now a hot research topic in the field of hydrology. In addition to the traditional method of parameter regionalization, using discontinuous flow observations to calibrate hydrological models has gradually become popular in recent years. In this study, the possibility of using a limited number of river discharge data to calibrate a distributed hydrological model, the Soil and Water Assessment Tool (SWAT), was explored. The influence of the quantity of discharge measurements on model calibration in the upper Heihe Basin was analysed. Calibration using only one year of daily discharge measurements was compared with calibration using three years of discharge data. The results showed that the parameter values derived from calibration using one year’s data could achieve similar model performance with calibration using three years’ data, indicating that there is a possibility of using limited numbers of discharge data to calibrate the SWAT model effectively in poorly gauged basins.

scholarly journals SWAT use of gridded observations for simulating runoff – a Vietnam river basin study

2011 ◽  
Vol 8 (6) ◽  
pp. 10679-10705 ◽  
Author(s):  
M. T. Vu ◽  
S. V. Raghavan ◽  
S. Y. Liong
Keyword(s):  
Swat Model ◽  
Model Performance ◽  
Tropical Rainfall Measuring Mission ◽  
Global Precipitation Climatology Project ◽  
Data Availability ◽  
Coefficient Of Determination ◽  
Reanalysis Dataset ◽  
Station Data ◽  
Rural And Urban ◽  
Grid Points

Abstract. Many research studies that focus on basin hydrology have used the SWAT model to simulate runoff. One common practice in calibrating the SWAT model is the application of station data rainfall to simulate runoff. But over regions lacking robust station data, there is a problem of applying the model to study the hydrological responses. For some countries and remote areas, the rainfall data availability might be a constraint due to many different reasons such as lacking of technology, war time and financial limitation that lead to difficulty in constructing the runoff data. To overcome such a limitation, this research study uses some of the available globally gridded high resolution precipitation datasets to simulate runoff. Five popular gridded observation precipitation datasets: (1) Asian Precipitation Highly Resolved Observational Data Integration Towards the Evaluation of Water Resources (APHRODITE), (2) Tropical Rainfall Measuring Mission (TRMM), (3) Precipitation Estimation from Remote Sensing Information using Artificial Neural Network (PERSIANN), (4) Global Precipitation Climatology Project (GPCP), (5) modified Global Historical Climatology Network version 2 (GHCN2) and one reanalysis dataset National Centers for Environment Prediction/National Center for Atmospheric Research (NCEP/NCAR) are used to simulate runoff over the Dakbla River (a small tributary of the Mekong River) in Vietnam. Wherever possible, available station data are also used for comparison. Bilinear interpolation of these gridded datasets is used to input the precipitation data at the closest grid points to the station locations. Sensitivity Analysis and Auto-calibration are performed for the SWAT model. The Nash-Sutcliffe Efficiency (NSE) and Coefficient of Determination (R2) indices are used to benchmark the model performance. This entails a good understanding of the response of the hydrological model to different datasets and a quantification of the uncertainties in these datasets. Such a methodology is also useful for planning on Rainfall-runoff and even reservoir/river management both at rural and urban scales.

scholarly journals Climate change impacts on hydrology in the Dak B’la watershed, Central Highland Vietnam based on SWAT model

2020 ◽  
pp. 22-31 ◽  
Author(s):  
Nguyen Kim Loi ◽  
Vo Ngoc Quynh Tram ◽  
Nguyen Thi Tinh Au
Keyword(s):  
Climate Change ◽  
Assessment Tool ◽  
High Reliability ◽  
Water Discharge ◽  
Swat Model ◽  
Climate Change Impacts ◽  
Agricultural Watershed ◽  
Coefficient Of Determination ◽  
Central Highland ◽  
Average Water

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.

scholarly journals Calibration and validation of SWAT model and estimation of water balance components of Shaya mountainous watershed, Southeastern Ethiopia

2013 ◽  
Vol 10 (11) ◽  
pp. 13955-13978 ◽  
Author(s):  
A. A. Shawul ◽  
T. Alamirew ◽  
M. O. Dinka
Keyword(s):  
Best Management Practices ◽  
Management Practices ◽  
Assessment Tool ◽  
Swat Model ◽  
Watershed Modeling ◽  
Coefficient Of Determination ◽  
Water Yield ◽  
Time Step ◽  
Monthly Streamflow ◽  
Mountainous Watershed

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.

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