A case study for the assessment of the suitability of gridded reanalysis weather data for hydrological simulation in Beas river basin of North Western Himalaya

Tanmoyee Bhattacharya,Manohar Arora,Deepak Khare

doi:10.1007/s13201-019-0993-x

Tanmoyee Bhattacharya, Manohar Arora + Show 1 more

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https://doi.org/10.1007/s13201-019-0993-x

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Abstract

The major problem of estimating snowmelt runoff for Beas river basin is inadequacy of observed meteorological data distributed across the basin. In this study, ERA-Interim global reanalysis data have been used for assessing the stream flow and sediment yield in Beas river basin of North Western Himalaya. The snow module of ARCSWAT hydrology model has been simulated by integration of subbasin-wise elevation band files for modeling snowmelt runoff process including sediment yield due to rainfall and temperature change for different elevation bands varying from 361 to 6188 m. The gridded reanalysis (0.125° × 0.125°) dataset produces a decreased maximum and minimum temperature and increased precipitation at higher elevation in comparison with IMD gridded weather data. The outcome of this study conveys that the reanalysis data represent better snowmelt runoff (NSE = 0.76, 0.70 and R2 = 0.80, 0.70) and sediment yield (NSE = 0.50, 0.53 and R2 = 0.72, 0.57) mechanism at Pong and Pandoh dams than IMD gridded weather data (NSE = 0.50, 0.47 and R2 = 0.65, 0.60) for stream flow and (NSE = 0.50, 0.53 and R2 = 0.65, 0.60) sediment yield during the period 1996–1999 and 1999–2002 for these two locations.

Highlights

IntroductionClimate and global water cycle have a fundamental relation. The precise prediction of stream flow is greatly influenced by the quality of input weather data for hydrology models (Duncan et al 1993; Fekete et al 2004)
Weather, climate and global water cycle have a fundamental relation
The main focus of the study is to assess the impacts of ERA-Interim global climatic reanalysis data and gridded IMD dataset on ARCSWAT hydrological model simulation

Summary

Introduction

Climate and global water cycle have a fundamental relation. The precise prediction of stream flow is greatly influenced by the quality of input weather data for hydrology models (Duncan et al 1993; Fekete et al 2004). A lumped hydrology model was calibrated using weather data from CFSR, NARR, MERRA, ERA-Interim reanalysis and gridded observation database to estimate the stream flow in the continental USA. The main focus of the study is to assess the impacts of ERA-Interim global climatic reanalysis data and gridded IMD dataset on ARCSWAT hydrological model simulation. The study investigates the vigorous changes in extreme weather condition based on ERA-Interim reanalysis and gridded observation dataset (IMD gridded data). In catchments with less available data, the adequacy of the study is to validate the use of reanalysis dataset depending on high spatial variation of precipitation and temperature. The study evaluates the possible influence of climate change on stream flow and sediment yield of Beas river basin up to Pong dam using Geographical Information System and hydrological modeling tool. The temporal resolution of ERA-Interim is either 3 h (forecast) or 6 h (analysis) (Dee et al 2011)

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