Reference Evapotranspiration Retrievals from a Mesoscale Model Based Weather Variables for Soil Moisture Deficit Estimation

Prashant K. Srivastava, Dawei Han, Aradhana Yaduvanshi, George Petropoulos, Sudhir Kumar Singh, Rajesh Kumar Mall, Rajendra Prasad

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)
126 Downloads (Pure)

Abstract

Reference Evapotranspiration (ETo) and soil moisture deficit (SMD) are vital for understanding 18 the hydrological processes. Precise estimation of ETo and SMD are required for developing 19 appropriate forecasting system and hydrological modelling. In this study, the surface temperature 20 downscaled from Weather Research and Forecasting (WRF) model is used to estimate ETo using 21 the boundary conditions provided by the European Center for Medium Range Weather Forecast 22 (ECMWF). In order to understand the performance, the Hamon method is employed to estimate 23 the ETo using the temperature from meteorological station and WRF derived variables. After 24 estimating the ETo, a range of linear and non-linear models are utilized to retrieve SMD. The 25 performance statistics such as RMSE, %Bias, and Nash Sutcliffe Efficiency indicates that the 26 simplistic linear model is efficient for SMD estimation in comparison to other complex models. 27 Findings of this study also showed that the technique is performing better during the growing 28 season than the non-growing season for SMD
Original languageEnglish
Article number1971
JournalSustainability
Volume9
Issue number11
DOIs
Publication statusPublished - 28 Oct 2017

Keywords

  • evotranspiration
  • soil moisture deficit
  • WRF
  • Noah Land Surface model
  • seasonality

Fingerprint

Dive into the research topics of 'Reference Evapotranspiration Retrievals from a Mesoscale Model Based Weather Variables for Soil Moisture Deficit Estimation'. Together they form a unique fingerprint.

Cite this