Predicting hydrology in ungauged basins using the DDD model
Prediction of hydrology in ungauged basins remains a great challenge even after 10 years of dedicated international efforts during PUB decade of IAHS (International Association of Hydrological Sciences). Predicting hydrology in ungauged basins means that the model structure is physically based (at the catchment scale) and those model parameters are determined using information from digitized map such as the river network and landscape types.
A hydrological model successful at predicting in ungauged basins is needed for hydrological estimation for the million basins around the globe that are ungauged and has a great potential for better predicting the hydrological consequences of climate change.
This study will continue the work published in Skaugen et al. (2015), where the DDD model was tested for its skill in predicting for ungauged catchments in southern Norway. Since 2015, the model has been further developed and more processes in the model, such as snowmelt and evapotranspiration, has an improved calibration-free physical founding.
In the study, we will relate model parameters that are not directly estimated from information at hand (i.e. calibrated parameters) to different catchment- and climate characteristics using multiple regression equations. The suitability of the model parameters will be tested using an independent set of catchments.
An additional benefit from such a study is that the results can be used to identify weak points in the model structure of DDD and hence contribute to its improvement.
- Skaugen, T., I. O. Peerebom and A. Nilsson, 2015. Use of a parsimonious rainfall-runoff model for predicting hydrological response in ungauged basins. Hydrol. Process. 29, 1999-2013, DOI:10.1002/hyp.10315.