Abstract

Abstract. The objective of this study is to assess the impacts of land cover change on the hydrological responses of the Mahanadi river basin, a large river basin in India. Commonly, such assessments are accomplished by using distributed hydrological models in conjunction with different land use scenarios. However, these models, through their complex interactions among the model parameters to generate hydrological processes, can introduce significant uncertainties to the hydrological projections. Therefore, we seek to further understand the uncertainties associated with model parameterization in those simulated hydrological responses due to different land cover scenarios. We performed a sensitivity-guided model calibration of a physically semi-distributed model, the Variable Infiltration Capacity (VIC) model, within a Monte Carlo framework to generate behavioural models that can yield equally good or acceptable model performances for subcatchments of the Mahanadi river basin. These behavioural models are then used in conjunction with historical and future land cover scenarios from the recently released Land-Use Harmonization version 2 (LUH2) dataset to generate hydrological predictions and related uncertainties from behavioural model parameterization. The LUH2 dataset indicates a noticeable increase in the cropland (23.3 % cover) at the expense of forest (22.65 % cover) by the end of year 2100 compared to the baseline year, 2005. As a response, simulation results indicate a median percent increase in the extreme flows (defined as the 95th percentile or higher river flow magnitude) and mean annual flows in the range of 1.8 % to 11.3 % across the subcatchments. The direct conversion of forested areas to agriculture (of the order of 30 000 km2) reduces the leaf area index, which subsequently reduces the evapotranspiration (ET) and increases surface runoff. Further, the range of behavioural hydrological predictions indicated variation in the magnitudes of extreme flows simulated for the different land cover scenarios; for instance, uncertainty in scenario labelled “Far Future” ranges from 17 to 210 m3 s−1 across subcatchments. This study indicates that the recurrent flood events occurring in the Mahanadi river basin might be influenced by the changes in land use/land cover (LULC) at the catchment scale and suggests that model parameterization represents an uncertainty which should be accounted for in the land use change impact assessment.

Highlights

  • IntroductionMany studies have attempted to evaluate the hydrological responses to different land use/land cover (LULC) patterns on specific geographic locations (Abe et al, 2018; Chu et al, 2013; Eum et al, 2016; Li et al, 2015; Ma et al, 2010; Rodriguez and Tomasella, 2016; Viola et al, 2014; Woldesenbet et al, 2017) including Indian river basins (Babar and Ramesh, 2015; Dadhwal et al, 2010; Das et al, 2018; Gebremicael et al, 2019; Wilk and Hughes, 2002)

  • A considerable variation is observed especially in the magnitudes of extreme flows simulated for the different land cover scenarios

  • In this study an attempt is made to quantify the hydrologic response of the subcatchments of the Mahanadi river basin, owing to different land cover scenarios obtained from the Land-Use Harmonization version 2 (LUH2) dataset, through the implementation of a sensitivitybased calibrated semi-distributed hydrological model

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Summary

Introduction

Many studies have attempted to evaluate the hydrological responses to different LULC patterns on specific geographic locations (Abe et al, 2018; Chu et al, 2013; Eum et al, 2016; Li et al, 2015; Ma et al, 2010; Rodriguez and Tomasella, 2016; Viola et al, 2014; Woldesenbet et al, 2017) including Indian river basins (Babar and Ramesh, 2015; Dadhwal et al, 2010; Das et al, 2018; Gebremicael et al, 2019; Wilk and Hughes, 2002) Most of these studies used physically distributed hydrological models (e.g., SWAT, VIC, MIKESHE) to simulate the complex hydrological processes and to examine the impact of LULC changes on those processes. 2. to understand the contribution of uncertainty from hydrologic parameterization to the hydrologic projections due to LULC change

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