Towards scale independent hydrological forecasting in regulated semi-arid regions

Semi-arid regions are characterized by low annual precipitation that exhibit large seasonal fluctuations. While semi-arid regions cover 3.6% of the globe, 13% of world’s documented reservoirs (GRanD database) are within 100 km of semi-arid regions to fulfill water demand year-round. Reservoirs are known to increase evaporation and significantly change hydrologic regime downstream. Accurate representation of reservoirs and scale independent modeling is indispensable for reliable hydrologic forecasting systems in semi-arid regions. To address this, the mesoscale hydrological model (mHM, git.ufz.de/mhm) is augmented with a new lake/reservoir module (multiscale lake module, mLM). The objective is to measure the performance of a scalable seasonal forecasting model chain with and without reservoirs.

The experimental setup constitutes the SaWaM (http://grow-sawam.org/) project study regions encompassing seven semi-arid basins and 15 reservoirs of high significance across three continents (Sao Francisco, Jaguaribe, Piranhas in Brazil, Blue Nile, Atbara in Sudan, Karun in Iran, Chira-Catamayo in Ecuador).The calibration of mHM parameters and its initial conditions for forecsating are obtained using the spatially disaggregated ERA5 (ERA-SD, ≈ 10 km, starting 1981) climate reanalysis data. The calibrated model is forced with an ensemble of 25 realisations of ECMWF-SEAS5 seasonal hindcasts which are bias corrected and spatially disaggregated (BCSD, ≈10 km) using ERA-SD. The 2010–2016 hindcasting experiment generates hydrological forecasts with lead time of upto six months. The performance of the model chain BCSD-mHM-mLM and BCSD-mHM are evaluated using the Brier Skill Score.

Preliminary results show that incorporating reservoirs in the model improves the performance of mHM (average NSE improvement ≈ +0.1 for the period 1990–2010) and the overarching forecasting model chain. Sub-grid level lake delineation and in-/outflow calculations of mLM result in scalable reservoir states and fluxes and thus overall scalable basin hydrology. Seamless forecasts for soil moisture, streamflow, reservoir inflow and reservoir water level are achieved across scales (≈10 km to ≈1 km) showing skills to up to two months lead time. This study is the first step towards an operational hydrological seasonal forecasting system which has potential to significantly improve water management, specially in semi-arid regions.