Abstract

There are ongoing discussions about the appropriate level of complexity and sources of uncertainty in rainfall runoff models. Simulations for operational hydrology, flood forecasting or nutrient transport all warrant different levels of complexity in the modelling approach. More complex model structures are appropriate for simulations of land-cover dependent nutrient transport while more parsimonious model structures may be adequate for runoff simulation. The appropriate level of complexity is also dependent on data availability. Here, we use PERSiST; a simple, semi-distributed dynamic rainfall-runoff modelling toolkit to simulate flows in the Upper Ganges and Brahmaputra rivers. We present two sets of simulations driven by single time series of daily precipitation and temperature using simple (A) and complex (B) model structures based on uniform and hydrochemically relevant land covers respectively. Models were compared based on ensembles of Bayesian Information Criterion (BIC) statistics. Equifinality was observed for parameters but not for model structures. Model performance was better for the more complex (B) structural representations than for parsimonious model structures. The results show that structural uncertainty is more important than parameter uncertainty. The ensembles of BIC statistics suggested that neither structural representation was preferable in a statistical sense. Simulations presented here confirm that relatively simple models with limited data requirements can be used to credibly simulate flows and water balance components needed for nutrient flux modelling in large, data-poor basins.

Published in

Environmental Science: Processes and Impacts
2015, Volume: 17, number: 6, pages: 1070-1081
Publisher: ROYAL SOC CHEMISTRY

SLU Authors

• Futter, Martyn

  • Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences
    

Sustainable Development Goals

SDG13 Take urgent action to combat climate change and its impacts


UKÄ Subject classification

Environmental Analysis and Construction Information Technology
Oceanography, Hydrology, Water Resources


Publication identifier

DOI: https://doi.org/10.1039/c4em00613e

Permanent link to this page (URI)

https://res.slu.se/id/publ/76161