Application of Soil Water Assessment Tool (SWAT) Model in Analyzing Nitrogen Transport Inside the Narmada River Basin

The Narmada River is one of the largest rivers in Western India encompassing a watershed area of 92,672 km2. It is one of the most important rivers for water needs of the state of Gujarat, Maharashtra, and Madhya Pradesh. The climate of the basin is humid and tropical but region surrounding this river watershed is predominantly dry and resembles semi-arid conditions. The population inside the states covering this watershed increased by an average of 23% from 1991 to 2011 causing multitude of water scarcity and water quality deterioration issues. These problems were caused by increase in sewage waste and untreated industrial discharge dumped into the river stream along with chemical fertilizers washing off from the farmlands flowing into the river. While there are several studies that model the watershed hydrology and water balance components, there has been no study that analyses the transport of nutrients inside the watershed. This study aims at using a semi-distributed hydrological model—Soil Water Assessment Tool (SWAT) to model the nitrogen (NO2 + NO3) transport and distribution inside the basin for 2001–2019. Nutrients and discharge data from Central Water Commission (CWC) of India were used to build this model along with other required input forcing obtained through remotely sensed datasets. We found that the subbasins near boundary of the Narmada watershed are experiencing significant increase in nitrogen concentrations at an estimated rate of 0.0001–0.002 mg/L/yr. The potential reason for such increase is high rate of conversion of forested land to agricultural land causing usage of fertilizers that are rich in nitrogen.

STREAMFLOW SIMULATION: COMPARISON BETWEEN SOIL WATER ASSESSMENT TOOL AND ARTIFICIAL NEURAL NETWORK MODELS

The present study compared the performance of two different models for streamflow simulation namely: Soil Water Assessment Tool (SWAT) and the Artificial Neural Network (ANN). During the calibration periods, the Nash-Sutcliff (NS) and Coefficient of Determination (R2) for SWAT was 0.74 and 0.81 respectively, whereas for ANN, it was 0.99 and 0.85 respectively. The ANN performs better during the validation period as the result revealed with NS and R2 having 0.98 and 0.89 respectively, while for the SWAT model it was 0.71 and 0.74 respectively. Based on the recommended comparison of graphical and statistical evaluation performances of both models, the ANN model performed better in estimating peak flow events than the SWAT model in the Upper Betwa Basin. Furthermore, the rigorous time required and expertise for calibration of the SWAT is much less as compared with the ANN. Moreover, the results obtained from both models demonstrate the performances of the

Use of the SWAT model for estimating reservoir volume in the Upper Navet watershed in Trinidad

In tropical small islands the application of hydrological modelling is challenged by the scarcity of input data. Using in-situ and statistically estimated data, a hydrological model was calibrated and validated for the Upper Navet watershed in Trinidad, a small Caribbean island. The model was built using the soil water assessment tool (SWAT). The sensitivity analysis, calibration and validation were performed in SWAT calibration and uncertainty program (SWAT-CUP) using sequential uncertainty fitting (SUFI-2). The results revealed that for the estimated volume of water flowing into the reservoir (Flow_In) there were six sensitive parameters. To estimate the reservoir volume (Res_Vol), a modification of only the effective hydraulic conductivity was required. The model’s performance for the Flow_In validation showed acceptable values (R2 = 0.91 and NSE = 0.81). The uncertainty analysis indicated lower than recommended values for both the R-factor (0.46) and P-factor (0.31). For Res_Vol, the model’s validation performance indicated acceptable values (R2 = 0.72 and NSE = 0.70) and the P- and R-factors were 0.80 and 0.64, respectively. Based on the statistical metrics, the uncertainty for the Res_Vol was regarded as reasonable. However, care must be taken with the model’s use in the dry season, as the simulated Flow_In was generally over-predicted. A second validation of the model was performed for the reservoir under different negative (removal) and positive (addition) water amounts which confirmed the model’s ability to estimate the Res_Vol. The hydrological model established can therefore serve as a useful tool for water managers for the estimation of the Res_Vol at the Navet reservoir.

Uso de suelo y su efecto en el escurrimiento modelado con SWAT

La importancia de los modelos de simulación para el monitoreo de los recursos naturales cada vez es mayor. El objetivo del presente estudio fue aplicar el modelo SWAT (Soil Water Assessment Tool) para evaluar el impacto del cambio de uso de suelo sobre el escurrimiento y sedimentos en la cuenca del Río Chapingo de 1999 a 2015. Se generaron dos mapas de uso de suelo mediante la fotointerpretación de imágenes Landsat y RapidEye con resoluciones de 15 y 5 m, respectivamente y recorridos de campo para verificación. Ante la falta de datos de escurrimiento confiable y reciente se utilizaron los registros mensuales de los períodos 1964-1970 y 1971-1975 para la calibración y validación del modelo. En este proceso los coeficientes de Nash-Sutcliffe fueron de 0.58 y 0.52, respectivamente. El uso de suelo de la cuenca en el período de estudio cambió: agricultura (-6.9 %) zona urbana (+2.89%), área de minería (+5.04 %) y pastizal (+7.75 %). La aplicación del SWAT calibrado y validado sólo para escurrimiento para el período 1999-2015 no detectó cambios en el escurrimiento (p = 0.2351) y sedimentos (p = 0.4430) en función del cambio de uso de suelo determinado. La correlación entre el escurrimiento y sedimentos anuales simulados con SWAT fue significativa (p = 0.0116) con un R2 bajo (0.36), atribuible a la falta de datos de campo de sedimentos para calibrar y validar el SWAT, además de la presencia de acciones de conservación de suelo y agua en la cuenca estudiada.

Inter-Comparison of Gauge-Based Gridded Data, Reanalysis and Satellite Precipitation Product with an Emphasis on Hydrological Modeling

Precipitation is essential for modeling the hydrologic behavior of watersheds. There exist multiple precipitation products of different sources and precision. We evaluate the influence of different precipitation product on model parameters and streamflow predictive uncertainty using a soil water assessment tool (SWAT) model for a forest dominated catchment in India. We used IMD (gridded rainfall dataset), TRMM (satellite product), bias-corrected TRMM (corrected satellite product) and NCEP-CFSR (reanalysis dataset) over a period from 1998–2012 for simulating streamflow. The precipitation analysis using statistical measures revealed that the TRMM and CFSR data slightly overestimate rainfall compared to the ground-based IMD data. However, the TRMM estimates improved, applying a bias correction. The Nash–Sutcliffe (and R2) values for TRMM, TRMMbias and CFSR, are 0.58 (0.62), 0.62 (0.63) and 0.52 (0.54), respectively at model calibrated with IMD data (Scenario A). The models of each precipitation product (Scenario B) yielded Nash–Sutcliffe (and R2) values 0.71 (0.76), 0.74 (0.78) and 0.76 (0.77) for TRMM, TRMMbias and CFSR datasets, respectively. Thus, the hydrological model-based evaluation revealed that the model calibration with individual rainfall data as input showed increased accuracy in the streamflow simulation. IMD and TRMM forced models to perform better in capturing the streamflow simulations than the CFSR reanalysis-driven model. Overall, our results showed that TRMM data after proper correction could be a good alternative for ground observations for driving hydrological models.

HYDROLOGIC ASSESSMENT OF FOOD USING SWAT AS GEOSPATIAL TECHNIQUES IN THE CATCHMENT AREA OF TERENGGANU MALAYSIA

Risks and hazards are two important issues currently threatening humanity and the environment. Flood has claimed many lives and destroyed properties in Malaysia and Africa and Nigeria. It is global catastrophe. The application of geospatial science is, therefore, very important advantages that it offers solutions to flood. This stud uses of Advanced Space-borne Thermal Emission and Reflection Radiometer Digital Elevation Model (ASTER-DEM), and the Soil Water Assessment Tool (SWAT) in visualizing floods disaster risk. The whole catchment area of Terengganu has been delineated. The 25 sub-basins have been identified and the flood risk zones have been modeled. The complete watersheds are characterized by different sub-basins and Hydrologic Respond Units (HRUs) which can be viewed in 3D environment.

Accurate Simulation of Ice and Snow Runoff for the Mountainous Terrain of the Kunlun Mountains, China

While mountain runoff provides great potential for the development and life quality of downstream populations, it also frequently causes seasonal disasters. The accurate modeling of hydrological processes in mountainous areas, as well as the amount of meltwater from ice and snow, is of great significance for the local sustainable development, hydropower regulations, and disaster prevention. In this study, an improved model, the Soil Water Assessment Tool with added ice-melt module (SWATAI) was developed based on the Soil Water Assessment Tool (SWAT), a semi-distributed hydrological model, to simulate ice and snow runoff. A temperature condition used to determine precipitation types has been added in the SWATAI model, along with an elevation threshold and an accumulative daily temperature threshold for ice melt, making it more consistent with the runoff process of ice and snow. As a supplementary reference, the comparison between the normalized difference vegetation index (NDVI) and the quantity of meltwater were conducted to verify the simulation results and assess the impact of meltwater on the ecology. Through these modifications, the accuracy of the daily flow simulation results has been considerably improved, and the contribution rate of ice and snow melt to the river discharge calculated by the model increased by 18.73%. The simulation comparison of the flooding process revealed that the accuracy of the simulated peak flood value by the SWATAI was 77.65% higher than that of the SWAT, and the temporal accuracy was 82.93% higher. The correlation between the meltwater calculated by the SWATAI and the NDVI has also improved significantly. This improved model could simulate the flooding processes with high temporal resolution in alpine regions. The simulation results could provide technical support for economic benefits and reasonable reference for flood prevention.