Advancing the understanding of the changes in various water budget components is crucial for improved water resource assessment and management at the global, continental, and river basin scales. This is important, especially because the intensified hydrologic dynamics due to climate change and accelerated human activities are altering the terrestrial water cycle in unprecedented ways and over a range of scales. Land surface models (LSMs) are widely used to investigate the changes in water resources resulting from natural and human-induced alterations. However, these models are subject to inherent uncertainties, including those associated with climate forcing and model parameterizations. Therefore, there is an urgent need to address climate forcing induced uncertainties in hydrological simulations using process based LSMs. In addition, representing human impacts such as irrigation and groundwater pumping in LSMs is critical for improving hydrological simulations. This dissertation advances regional hydrological simulation, addressing climate forcing uncertainty, by leveraging the potential of emerging satellite data and using an advanced LSM. A comprehensive analysis is conducted using a fully-process based LSM to examine the propagation of precipitation uncertainty into hydrological simulations over the Mekong River Basin (MRB). The Community Land Model version 5 (CLM5) at a relatively high spatial resolution of 0.05℗ʻ (⁸́ơ5 km) and without any parameter calibration is implemented. Simulations conducted using different precipitation datasets are compared to investigate the discrepancies in streamflow, terrestrial water storage (TWS), soil moisture, and evapotranspiration (ET). Furthermore, this dissertation advances the simulation of basin wide groundwater dynamics in the MRB, providing key insights on the evolving groundwater system and improving process-based groundwater modeling capabilities by implementing CLM5 with groundwater and irrigation parameterizations. An in-depth analysis is℗ conducted to examine groundwater mechanisms in the MRB, focusing on groundwater flow processes that are modulated by climate variability and physiographic features, and primary drivers of groundwater-surface water interactions. Further, the influence of extensive irrigation and groundwater pumping on groundwater dynamics is quantified. Finally, global drought recovery and its drivers across different climate zones and biodiversity hotspots are investigated using multi-model hydrological simulations, enhancing the understanding of future drought risk and ecosystem resilience. The key findings from the aforementioned multi-scale analyses are: (1) precipitation is a key determinant of simulated streamflow and peak flow is particularly sensitive to precipitation input; notable differences are also found among TWS, soil moisture, and ET simulated using different precipitation products. (2) Precipitation data with a higher spatial resolution did not improve the simulations, contrary to the common perception that using meteorological forcing with higher spatial resolution would improve hydrological simulations. (3) High spatial heterogeneity in groundwater recharge and discharge across the MRB is governed by climate and subsurface characteristics; a pronounced seasonality is found in groundwater recharge; with substantial carryover to the consecutive dry season that alleviates soil moisture. (4) Groundwater discharge is a dominant source of streamflow all year round, and irrigation pumping is directly altering groundwater flows and storages. (5) Climate variability smoothens pumping effects over long times, but the model simulates region-wide groundwater depletion in the Mekong Delta during dry years. (6) The drought recovery time varies considerably across different climate regions globally, and there has been a notable increase in drought recovery time over the last few decades. This dissertation provides crucial insights on precipitation-induced uncertainties in hydrological modeling, also advancing process-based groundwater modeling capabilities for regional scale application.
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