This research project aims at investigating modalities, limitations and potential of a seasonal hydrological forecasting system implementing a generic land surface model (LSM) to simulate regional-scale hydrological responses in South Africa. Its particular concern is investigating how to minimize the dilution of climate forecast skill during the process of translating climate data into hydrological information. Through this, the project aims to create a knowledge basis for an operational seasonal hydrological forecasting system enabling regular forecasts of runoff, streamflow, shallow groundwater and soil moisture, addressing aspects such as frequency and intensity of events, as well as mean conditions. The project is motivated by the possible contribution of a reliable seasonal hydrological forecast to management and operation of such elements of South African economy as water supply, hydropower generation, agricultural activities, disaster (flood and drought) prevention and preparedness.
The project is based on linking two land surface models (VIC and JULES) to three seasonal climate forecasts generated in South Africa: SAWS, CSIR and CSAG (and possibly others), and involves a range of activities:
- Design and implementation of data transfer, pre-processing and post-processing routines enabling integration of climate forecasts with the land surface models
- Design and implementation of model experiments allowing investigation of uncertainties associated with various data processing paths, aimed at arriving at robust operational configuration.
- Involvement of potential users of the seasonal hydrological forecast to ensure relevance of the forecasting system and project activities.
Time frames: Funded from July 2015 to April 2018
Funder: Water Research Commission
Partners: University of Pretoria
For further details: Piotr Wolski