Preprints
https://doi.org/10.5194/hess-2021-306
https://doi.org/10.5194/hess-2021-306

  23 Jun 2021

23 Jun 2021

Review status: this preprint is currently under review for the journal HESS.

Quantifying the impact of land cover changes on hydrological responses in India

Shaini Naha, Miguel A. Rico-Ramirez, and Rafael Rosolem Shaini Naha et al.
  • Civil Engineering Department, University of Bristol, Bristol, BS8 1TR, UK

Abstract. The objective of this study is to assess the impacts of Land Use 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) within a Monte Carlo Framework to generate behavioural models 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 Harmonisation (LUH2) to generate hydrological predictions and related uncertainties from behavioural model parameterisation. 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 (on the order of 30,000 km2) reduces the Leaf Area Index and 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 far future scenario ranges from 17 to 210 cumecs across subcatchments. This study indicates that the recurrent flood events occurring in the Mahanadi river basin might be influenced by the changes in LULC at the catchment scale and suggests that model parameterisation represents an uncertainty, which should be accounted for in the land-use change impact assessment.

Shaini Naha et al.

Status: open (until 18 Aug 2021)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on hess-2021-306', Anonymous Referee #1, 10 Jul 2021 reply

Shaini Naha et al.

Shaini Naha et al.

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Short summary
Rapid growth in population in developing countries leads to an increase in food demand and as a consequence, percentages of land are being converted to cropland which alters the river flow processes. This study describes how the hydrology of a flood prone river basin in India would respond to the current and future changes in land cover. Our findings indicate that the recurrent flood events occurring in the basin might be influenced by these changes in land cover at the catchment scale.