Seasonal hydrological and nutrient loading forecasts for watersheds over the Southeastern United States. (November 2015)

• Record Type: Journal Article
• Authors: Bastola, Satish; Misra, Vasubandhu
• Is Part Of: Environmental modelling & software. Volume 73(2015:Nov.)
• Page Start: 90
• Page End: 102
• Publication Date: 2015-11
• Subjects: Rainfall-runoff model -- Seasonal hydrologic forecasting -- Southeastern United States -- Water quality -- Seasonal predictability; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2015.08.005
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: We show useful seasonal deterministic and probabilistic prediction skill of streamflow and nutrient loading over watersheds in the Southeastern United States (SEUS) for the winter and spring seasons. The study accounts for forecast uncertainties stemming from the meteorological forcing and hydrological model uncertainty. Multi-model estimation from three hydrological models, each forced with an ensemble of forcing derived by matching observed analogues of forecasted quartile rainfall anomalies from a seasonal climate forecast is used. The attained useful hydrological prediction skill is despite the climate model overestimating rainfall by over 23% over these SEUS watersheds in December–May period. The prediction skill in the month of April and May is deteriorated as compared to the period from December–March (zero lead forecast). A nutrient streamflow rating curve is developed using a log linear tool for this purpose. The skill in the prediction of seasonal nutrient loading is identical to the skill of seasonal streamflow forecast. Highlights: We present ensemble hydrological forecasting method that accounts for the uncertainty in hydrological models. We evaluate the skill of seasonal hydrological and water quality prediction using both deterministic and probabilistic skill scores. The study emphasis the importance of bias correction in climate product for hydrological application.