Assessment of water shortages in catchment areas under climate change: a conceptual modelling approach to quantifying the need for adaptation measures

Quantifying the impacts of adaptation measures against climate change is essential for water management authorities, farmers, and climate change research teams. There are many approaches to adaptation, ranging from the overall organisation of farming methods and field layouts to specific interventions targeted at particular problems. This study focuses on addressing the scarcity of water resources under pressure from human needs, particularly for agriculture. This is done through simulating hydrological balance under future climate change scenarios (CMIP6) using hydrological model BILAN that is calibrated with respect to both runoff and observed (satellite-derived) evapotranspiration. The impact of adaptation measures on the climate is reflected in changes to evapotranspiration, which can be measured. Therefore, evapotranspiration is the second calibrating variable. Daily evapotranspiration data were derived from MODIS land surface temperature (LST) data using the DisALEXI model at a spatial resolution of 500 metres. The study was performed on catchments in the Czech Republic and Austria, ranging in size from small (~10 km²) to large (~10,000 km²), in the Danube River tributary area. The total domain was approximately 45 000 km². Results show that multi-objective calibration has no significant negative effect on model performance in runoff and evapotranspiration generation, with NSE values of around 0.65 being calculated for runoff and evapotranspiration, respectively. A set of hydrological balance scenarios was developed and analysed from two complementary perspectives. The scenarios determine information on potential water shortages within a given catchment, quantifying the need for compensation through adaptation measures. And the assessment of the ability of the model to simulate compensation of runoff shortages within other hydrological balance components by calibrating the model using the historical observed meteorological data and scenario runoff data.

 

Acknowledgement: This work originated in the Centrum Voda project, funded by the Technology Agency of the Czech Republic (project no. SS02030027)