Modeling Annual Water Balance In The Seasonal Budyko Framework

In this thesis, the role of soil water storage change on the annual water balance is evaluated based on observations at a large number of watersheds located in a spectrum of climate regions, and an annual water balance model is developed at the seasonal scale based on Budyko hypthesis. The annual water storage change is quantified based on water balance closure given the available data of precipitation, runoff, and evaporation estimated from remote sensing data and meteorology reanalysis. The responses of annual runoff, evaporation, and storage change to the interannual variability of precipitation and potential evaporation are then analyzed. Both runoff and evaporation sensitivities to potential evaporation are higher under energy-limited conditions, but storage change seems to be more sensitive to potential evaporation under the conditions in which water and energy are balanced. Runoff sensitivity to precipitation is higher under energylimited conditions; but both evaporation and storage change sensitivities to precipitation are higher under water-limited conditions. Therefore, under energy-limited conditions, most of precipitation variability is transferred to runoff variability; but under waterlimited conditions, most of precipitation variability is transferred to storage change and some of precipitation variability is transferred to evaporation variability. The main finding of this part is that evaporation variability will be overestimated by assuming negligible storage change in annual water balance, particularly under water-limited conditions. Budyko framework which expresses partitioning of water supply at the mean annual scale, is adapted to be applicable in modeling water cycle in short terms i.e., iv seasonal and interannual scales. Seasonal aridity index is defined as the ratio of seasonal potential evaporation and the difference between precipitation and storage change. The seasonal water balance is modeled by using a Budyko-type curve with horizontal shifts which leads prediction of seasonal and annual storage changes and evaporation if precipitation, potential evaporation, and runoff data are available.