Application of a Distributed Hydrologic Model to Assess the Impact of Climate and Land-use Change on Surface Runoff from a Small Urbanizing Watershed

N. M. Sabitha (), Santosh G. Thampi () and D. Sathish Kumar ()
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N. M. Sabitha: National Institute of Technology Calicut
Santosh G. Thampi: National Institute of Technology Calicut
D. Sathish Kumar: National Institute of Technology Calicut

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2023, vol. 37, issue 6, No 8, 2347-2368

Abstract: Abstract The impact of future land-use and climate changes on the surface hydrology of a watershed was studied using an event-based hydrological model. Artificial Neural Network (ANN) and Monte-Carlo Cellular Automata (CA) based model was used to generate future land-use scenarios of an urbanizing watershed. Simulations were thereafter performed using a hydrological model to assess the expected changes in runoff. The spatial data inputs for the hydrological model were generated using satellite data, field observations, and data obtained from government agencies. Sensitivity analysis, calibration, and validation of the model were carried out using the observed storm and flow hydrographs, and the model performance was assessed using various statistical performance metrics. Historical land-use data for 2005, 2013, and 2017 was prepared using Landsat satellite imageries and Google Earth images. The land-use scenario generated for the year 2021 exhibited good agreement with the actual land-use map, with a Kappa value above 0.8. Future land-use scenarios were generated to assess the short-term (2025 and 2029) and long-term (2037, 2045, and 2053) changes in the characteristics of the flow hydrographs. The expected changes in the hydrographs due to urbanization were analyzed by applying a selected storm event and considering 2005 as the baseline year using the Two-Dimensional Runoff Erosion and Export (TREX) model. Results indicate that the peak discharge is likely to increase by 29%, and the time to peak is likely to decrease by 6% in 2053 when only land use change is considered. The corresponding values in the worst case considering the combined effect of climate and land use changes are 34.63% and 8.28%, respectively.

Keywords: Rainfall-runoff model; Urbanization; Storm hydrograph; Land-use change; Monte-Carlo Cellular Automata; Climate change (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s11269-022-03349-0

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