Applicability of seasonal forecasts from dynamical models for reservoir management practices

Abstract

Despite the availability of reliable seasonal forecasts of Indian Summer Monsoon Rainfall (ISMR), the use of dynamical models driven by these forecasts for reservoir level management is limited. Reservoir water management can specially be useful if it can be done several months in advance, in view of an impending drought/flood scenario. The applicability of seasonal forecasts from the Monsoon Mission (MM) seasonal forecast model for seasonal and monthly inflow forecasts for tropical Indian reservoirs (Mula and Kangsabati) is studied using the Soil and Water Assessment Tool (SWAT) hydrological model, at a lead time of 3 months. Long-term observed inflow datasets are used for calibration and validation of SWAT-Calibration and Uncertainty Procedure (CUP) with Sequential Uncertainty Fitting (SUFI)-2 algorithm using insitumeteorological data. Observed inflows and inflow simulations are compared with simulated inflow using SWAT with same calibrated parameters, but with forcing derived from reforecasts from the MM model. The SWAT-CUP calibrated well with reasonable Nash Sutcliffe Efficiency (NSE) (Mula = 0.75, Kangsabati = 0.79) and Percentage Bias (PBIAS) (Mula = -28%, Kangsabati = 17%) for both reservoirs. The skill scores for streamflow predictions vary from 0.6-0.70 during the monsoon season, indicating reasonable accuracy for these predictions. The SWAT-MM model has a reasonable skill with 0.52-0.53 NSE and 26%-40% PBIAS. Therefore, SWAT-MM-based model has a good potential to forecast monthly and seasonal reservoir inflow for various agro-climatic zones of India. These forecasts when used in real-time, can serve as a guideline for managing the reservoir storage and release, and hence proving to be of great socio-economic importance.