Toward Improved Parameter Estimation of Variable Infiltration Capacity Model Under the Impacts of El Niño Events

Indian summer monsoon rainfall (ISMR) contributes 80% of the annual rainfall in South Asian countries and is strongly influenced by El Niño Southern Oscillation (ENSO) phenomenon. The most recent El Niño event during 2015-2016, with an Oceanic Niño Index (ONI) of 2.6 had enormous effects on rainfall and water resources in South Asia. Thus, agricultural output, economy, water resources and societal well-being of South Asian Region heavily rely on the impacts of ENSO on the variability of ISMR. Godavari River Basin (GRB) is the second largest river basin in India with an annual runoff yield around 81 Gm³ and thus important in terms of agriculture and food security. Uncertainty of the ENSO-monsoon relationship and its implications on rainfall variations in GRB necessitates the importance of modelling the impacts of ENSO on changing rainfall, hydrology and agricultural productivity. Hence, this study focused on the understanding of the variations in hydrological processes under the scenario of pre, ongoing and post El Niño events in the Godavari GRB using the Variable Infiltration Capacity (VIC) model. Accurate estimation of VIC parameters is pivotal to produce reasonable simulations of catchment responses under the impact of El Niño events. In this regard, a framework with enhanced calibration methods is presented for estimating VIC parameters (Baseflow and runoff both). Using this framework, we identified the most critical parameters, which could represent the landscape and climatic characteristics of GRB in response to El Niño events. The proposed framework also reduced the number of parameters needing to be calibrated and hence increased computational efficiency. The parameters identified strengthened the accuracy of VIC simulations to examine the relative changes in hydrological processes with respect to magnitude of ONI. Improved understanding of impact pathways of El Niño in the GRB can help water resource managers to reduce El Niño-induced vulnerabilities and to better prepare in meeting the irrigation water supply and power demands under different El Niño conditions.