A Spatial Extrapolation Approach to Assess the Impact of Climate Change on Water Resource Systems

Abstract:

The typical approach to assess climate change impacts on water resources systems is based on a vertical integration/coupling of models: GCM models are run to project future precipitations and temperatures, which are then downscaled and used as inputs to hydrologic models whose outputs are processed by water systems models. From a decision-making point of view, this top-down vertical approach presents some challenges. For example, since the range of uncertainty that can be explored with GCM is limited, researchers are relying on ensembles to enlarge the spread, making the modeling approach even more demanding in terms of computation time and resource. When a particular water system must be analyzed, the question is to know whether this computationally intensive vertical approach is necessary in the first place or if we could extrapolate projections available in neighboring systems to feed the water system model? This would be equivalent to a horizontal approach. The proposed study addresses this question by comparing the performance of a water resource system under future climate conditions using the vertical and horizontal approaches. The methodology is illustrated with the hydropower system of the Gatineau River Basin in Quebec, Canada. Vertically obtained hydrologic projections available in those river basins are extrapolated and used as inputs to a stochastic multireservoir optimization model. Two different extrapolation techniques are tested. The first one simply relies on the ratios between the drainage areas. The second exploits the covariance structure found in historical flow data throughout the region. The analysis of the simulation results reveals that the annual and weekly energy productions of the system derived from the horizontal approach are statistically equivalent to those obtained with the vertical one, regardless of the extrapolation technique used.