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Multi-Model Approach to Assess the Dynamics of Hydrologic Components in a Tropical Ecosystem
Authors:Srivastava  Ankur  Deb  Proloy  Kumari  Nikul
Affiliation:1.School of Engineering, The University of Newcastle, Callaghan, NSW, 2308, Australia
;2.Centre for Water, Climate and Land (CWCL), School of Environmental and Life Sciences, Faculty of Science, University of Newcastle, Callaghan, NSW, 2308, Australia
;
Abstract:

Estimation of terrestrial water budget at global and regional scales are essential for efficient agricultural water management, flood predictions, and, hydrological modeling. In hydrological modeling, it is a challenging task to quantify the major hydrological components like runoff, evapotranspiration (ET), and total water storage (TWS) due to improper and limited availability of detailed meteorological datasets. Furthermore, there has been no consensus to answer a-decade-long critical question that a less data-intensive models can be an alternate to robust data-intensive models in data scarce conditions. This study aims at multi-model approach over the single models usage for representing the hydrological behaviour in the Kangsabati River Basin (KRB), India. It is done by applying the standard model selection criteria over various hydrological models. Two hydrological models are selected, a semi- distributed model, Variable Infiltration Capacity (VIC-3 L), and a conceptually lumped model, Identification of unit Hydrograph and Component flows from Rainfall, Evapotranspiration and Streamflow (IHACRES). Both models were calibrated against the observed daily discharge at the KRB outlet for the period of 2001–2006 and validated for 2008–2010. The results show that both VIC-3 L and IHACRES produce reasonable runoff estimates at daily and monthly time scale in the KRB. The ET estimates show that VIC-3 L and IHACRES captured the seasonal variations with the percent change of 0.4% and 6.6% respectively. As IHACRES is simpler, parsimonious, fewer parameters, and better performances, it can be useful for hydrological modeling in data-scarce regions.

Keywords:
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