Abstract

Land use and land cover change (LULC) has significant impact on hydrologic response at the river basin/watershed level. Quantitative assessment of LULC impacts on runoff generations on river basin scale is important for water resources development and impact assessment of extreme events. Based on the historical LULC changes, the future LULC can be projected, and its impacts can be assessed using a hydrologic model. In this study, the future LULC of Periyar river basin in Western Ghats in South India is projected using multi-layer perceptron–artificial neural network (MLP-ANN) technique in land change modeler (LCM) of TerrSet model. The soil and water assessment tool (SWAT) model was used to study the effect of LULC change on streamflow. The model was calibrated for the period 1984–2004 and then validated for 2006–2012. The results show good co-relation for streamflow with R2, NSE, and PBIAS, 0.92, 0.84, and 6.5% for calibration period, and 0.85, 0.67, and 11.8% for validation period, respectively. The impact of LULC change for far future is analyzed, and change was compared at monthly, seasonal, and annual scale. The results suggested an increase in streamflow annually. Also it suggests an increase in streamflow in winter and monsoon season whereas a slight decrease in summer season. This information will be useful for planners and researchers to understand the impacts of future LULC changes on river basin hydrology. Further, it will be helpful in decision-making for preparing future development strategies.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call