Data-Driven Scale Extrapolation: Application on Continental Scale

Abstract:

Large-scale hydrological models and land surface models are so far the only tools for assessing current and future water resources. Those models estimate discharge with large uncertainties, due to the complex interaction between climate and hydrology, the limited availability and quality of data, as well as model uncertainties. A new purely data-driven scale-extrapolation method to estimate discharge for a large region solely from selected small sub-basins, which are typically 1–2 orders of magnitude smaller than the large region, has been developed. When tested in the Baltic Sea drainage basin, the method was able to provide accurate discharge estimation for the gauged area with sub-basins that cover 5% of the gauged area. There exist multiple sets of sub-basins whose climate and hydrology resemble those of the gauged area equally well. Those multiple sets estimate annual discharge for the gauged area consistently well with 6 % average error. The scale-extrapolation method is completely data-driven; therefore it does not force any modelling error into the prediction. The scale-extrapolation method is now further tested at continent scale in Europe and North America to exam its potential for climate change studies.