Water shortage risk assessment using spatiotemporal flow simulation

Abstract

Paddy irrigation practices in Taiwan utilize complicated water conveyance networks which draw streamflows from different tributaries. Characterizing and simulating streamflow series is thus an essential task for irrigation risk assessment and planning mitigation measures. It generally involves modeling the temporal variation and spatial correlation of streamflow data at different sites. Like many other environmental variables, streamflows are asymmetric and non-Gaussian. Such properties exacerbate the difficulties in spatiotemporal modeling of streamflow data. A stochastic spatiotemporal simulation approach capable of generating non-Gaussian ten-day period streamflow data series at different sites is presented in this paper. Historical flow data from different flow stations in southern Taiwan were used to exemplify the application of the proposed model. Simulated realizations of the spatiotemporal anisotropic multivariate Pearson type III distribution were validated by comparing parameters and spatiotemporal correlation characteristics of the simulated data and the observed streamflow data. Risks of irrigation water shortage were estimated and the effect of mitigation measures was assessed using the simulated data.