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.

Freshwater is a vital resource that circulates between the atmosphere, the land and the sea. Understanding and quantifying changes to the partitioning of precipitation into evapotranspiration, runoff and water storage change in the landscape are required for assessing changes to freshwater availability. However, the partitioning processes and their changes are complex due to multiple change drivers and effects. This thesis investigates and aims to identify and separate the effects of atmospheric climate change and various landscape drivers on long-term freshwater change. This is done based on hydroclimatic, land-use and water-use data from the beginning of the twentieth century up to present times and across different regions and scales, from catchment to global. The analyzed landscape drivers include historic developments of irrigated and non-irrigated agriculture and flow regulation. The thesis uses and develops further a data-motivated approach to interpret available hydroclimatic and landscape data for identification of water change drivers and effects, expanding the approach application from local to continental and global scales. Based on this approach development, the thesis identifies hydroclimatic change signals of landscape drivers against the background of multiple coexisting drivers influencing worldwide freshwater change, within and among hydrological basins. Globally, landscape drivers are needed to explain more than 70% of the historic hydroclimatic changes, of which a considerable proportion may be directly human-driven. These landscape- and human-driven water changes need to be considered and accounted for also in modeling and projection of changes to the freshwater system on land. / <p>At the time of the doctoral defense, the following paper was unpublished and had a status as follows: Paper 4: Submitted.</p> / VR, project 2009-3221

Total water storage change (TWSC) reflects the balance of all water fluxes in a hydrological system. The Gravity Recovery and Climate Experiment/Follow-On (GRACE/GRACE-FO) monthly gravity field models, distributed as spherical harmonic (SH) coefficients, are the only means of observing this state variable. The well-known correlated noise in these observations requires filtering, which scatters the actual mass changes from their true locations. This effect is known as leakage. This study explores the traditional basin and grid scaling approaches, and develops a novel frequency-dependent scaling for leakage correction of GRACE TWSC in a unique, basin-specific assessment for the Indus Basin. We harness the characteristics of significant heterogeneity in the Indus Basin due to climate and human-induced changes to study the physical nature of these scaling schemes. The most recent WaterGAP (Water Global Assessment and Prognosis) hydrology model (WGHM v2.2d) with its two variants, standard (without glacier mass changes) and Integrated (with glacier mass changes), is used to derive scaling factors. For the first time, we explicitly show the effect of inclusion or exclusion of glacier mass changes in the model on the gridded scaling factors. The inferences were validated in a detailed simulation environment designed using WGHM fields corrupted with GRACE-like errors using full monthly error covariance matrices. We find that frequency-dependent scaling outperforms both basin and grid scaling for the Indus Basin, where mass changes of different frequencies are localized. Grid scaling can resolve trends from glacier mass loss and groundwater loss but fails to recover the small seasonal signals in trunk Indus. Frequency-dependent scaling can provide a robust estimate of the seasonal cycle of TWSC for practical applications such as regional-scale water availability assessments. Apart from these novel developments and insights into the traditional scaling approach, our study encourages the regional scale users to conduct specific assessments for their basin of interest.