Hydrological Modelling in Upper Narmada River Basin Using SWAT Model

Abstract

Water is an essential resource for sustaining human livelihoods and natural ecosystems, but its availability is rapidly declining due to the growing population and variable weather patterns. The assessment of water availability is essential for sustainable development and management of water resources. The traditional and empirical methods are found complex and time consuming for the estimation of hydrological components of the water cycle. For this purpose, hydrological models play a crucial role in predicting streamflow, especially in regions where measured flow data is insufficient or unavailable. In the study, Hydrological Modelling in the upper Narmada Basin is applied using a semi-distributed hydrological model Soil and Water Assessment Tool (SWAT). One of the objective of study is to test the applicability of SWAT model by predicting streamflow in two ungauged watersheds (Assuming Dindori and Mohgaon as ungauged watersheds) using the regionalization method based on physical similarity and spatial proximity approach. The other objective of the study is to apply hydrological modelling in the multi-gauging basin for streamflow simulation, this objective is applied in the Manot watershed which consists of two gauging sites Dindori and Manot. The aim of applying modelling in the multi-gauging basin is to check the reliability of the calibration technique for the optimal model performance in large river basins. The water yield and water balance components for the respective watersheds are also estimated by the SWAT model for the development of sustainable water management strategies in semi-arid regions. For the simulation of streamflow on daily and monthly time scales in the study watershed using SWAT model requires various spatial and hydro-meteorological inputs like Cartosat-1 Digital Elevation Model (DEM), Land Use map developed by Landsat-8 satellite imagery, Soil Map by Food and Agricultural Organization (FAO) and meteorological data downloaded from Indian Meteorological Department (IMD). On application of all the data in the model, the SCS-CN method combines with the Hargreaves method for the estimation of runoff and Evaportranspiration and employed with Muskingum method for channel routing for the Streamflow simulation for respective watersheds. The sensitivity analysis is done by Global sensitivity method, Uncertainty analysis is performed by Sufi-2 algorithm and calibration and Validation of the model is performed by SWAT-CUP with Sufi-2 algorithm. The calibrated and validated model has been evaluated by global performance indexes such as R2, NSE, PBIAS, and RSR. The Model performed well for ungauged watersheds and the predicted outcomes match with the calibrated results for the same watershed on daily and monthly time scales. The Daily time step, statistical evaluation measures for the predicted simulation of ungauged watershed Dindori are: R2 = 0.476, NSE= 45.09%, PBIAS = -13.224 and RSR = 0.74 & the evaluation values for the calibrated model of gauged watershed Dindori are: R2 = 0.457, NSE= 45.09%, PBIAS = 16.9 and RSR = 0.741. On the monthly time scale, the statistical measure R2 and RSR for predicted simulation of ungauged Dindori are 0.84 and 0.45 matches with the calibrated model for gauged Dindori for which the value R2 and RSR are 0.80 and 0.40. The predicted model of ungauged watershed for streamflow simulation closely matches with the calibrated model of the same watershed. Similarly, the predicted flow for the Mohgaon watershed founds the same as the calibrated model of the Mohgaon watershed which indicates that this approach of regionalization performed well and can be used for ungauged catchments. For Manot watershed, the model parameters were optimized using multi gauging calibration technique. The impact of calibration of Dindori on Manot watershed resulted in increase in efficiency and accuracy of the model on daily and monthly time scales. NSE increased from 46.5% to 58.59% on the daily time scale, R2 increased from 0.87 to 0.899 on the monthly time scale and a reduction in RSR value also indicates less error in the simulated values for both time scales. R2and NSE values for the validation period are 0.91 and 90.82% and the error indexes indicate least error in the simulated results for this period. This shows that for downstream gauging sites the model performance can be improved if another gauged data is available in the upstream sites. The study emphasizes the importance of hydrological modelling in determining the availability of water resources for sustainable development. The Upper Narmada river basin is a crucial region for agriculture and industrial activities. However, the availability of water resources in the region is limited due to variable weather patterns and increasing demand. Accurate streamflow predictions can aid in the water resources planning and management in the region. The results of this study can be used to estimate streamflow in ungauged watersheds and provide insights into the hydrological processes governing the flow in Upper Narmada river basin.