Regional water balance modelling using flow-duration curves with observational uncertainties
- 1Department of Civil Engineering, University of Bristol, Queen's Building, University Walk, Clifton, BS8 1TR, UK
- 2Department of Earth Sciences, Uppsala University, Villavägen 16, 75236 Uppsala, Sweden
- 3IVL Swedish Environmental Research Institute, P.O. Box 210 60, 10031 Stockholm, Sweden
- 4Lancaster Environment Centre, Lancaster University, Lancaster, LA1 4YQ, UK
- 5Department of Geography, University of Zurich, Winterthurerstrasse 190, 8057 Zurich, Switzerland
- 6CINAV – Escola Naval, Base Naval de Lisboa, Alfeite, 2810-001 Almada, Portugal
- 7Department of Geosciences, University of Oslo, Postboks 1047 Blindern, 0316 Oslo, Norway
Abstract. Robust and reliable water-resource mapping in ungauged basins requires estimation of the uncertainties in the hydrologic model, the regionalisation method, and the observational data. In this study we investigated the use of regionalised flow-duration curves (FDCs) for constraining model predictive uncertainty, while accounting for all these uncertainty sources. A water balance model was applied to 36 basins in Central America using regionally and globally available precipitation, climate and discharge data that were screened for inconsistencies. A rating-curve analysis for 35 Honduran discharge stations was used to estimate discharge uncertainty for the region, and the consistency of the model forcing and evaluation data was analysed using two different screening methods. FDCs with uncertainty bounds were calculated for each basin, accounting for both discharge uncertainty and, in many cases, uncertainty stemming from the use of short time series, potentially not representative for the modelling period. These uncertain FDCs were then used to regionalise a FDC for each basin, treating it as ungauged in a cross-evaluation, and this regionalised FDC was used to constrain the uncertainty in the model predictions for the basin.
There was a clear relationship between the performance of the local model calibration and the degree of data set consistency – with many basins with inconsistent data lacking behavioural simulations (i.e. simulations within predefined limits around the observed FDC) and the basins with the highest data set consistency also having the highest simulation reliability. For the basins where the regionalisation of the FDCs worked best, the uncertainty bounds for the regionalised simulations were only slightly wider than those for a local model calibration. The predicted uncertainty was greater for basins where the result of the FDC regionalisation was more uncertain, but the regionalised simulations still had a high reliability compared to the locally calibrated simulations and often encompassed them. The regionalised FDCs were found to be useful on their own as a basic signature constraint; however, additional regionalised signatures could further constrain the uncertainty in the predictions and may increase the robustness to severe data inconsistencies, which are difficult to detect for ungauged basins.