ABSTRACT:

Numerous studies have examined the changes in streamflow in the Mekong River Basin (MRB) using observations and hydrological modeling; however, there is a lack of integrated modeling studies that explicitly simulate the natural and human‐induced changes in flood dynamics over the entire basin. Here we simulate the river‐floodplain‐reservoir inundation dynamics over the MRB for 1979–2016 period using a newly integrated, high‐resolution (~5 km) river hydrodynamics‐reservoir operation model. The framework is based on the river‐floodplain hydrodynamic model CaMa‐Flood in which a new reservoir operation scheme is incorporated by including 86 existing MRB dams. The simulated flood extent is downscaled to a higher resolution (~90 m) to investigate fine‐scale inundation dynamics, and results are validated with ground‐ and satellite‐based observations. It is found that the historical variations in surface water storage have been governed primarily by climate variability; the impacts of dams on river‐floodplain hydrodynamics were marginal until 2009. However, results indicate that the dam impacts increased noticeably in 2010 when the basin‐wide storage capacity doubled due to the construction of new mega dams. Further, results suggest that the future flood dynamics in the MRB would be considerably different than in the past even without climate change and additional dams. However, it is also found that the impacts of dams can largely vary depending on reservoir operation strategies. This study is expected to provide the basis for high‐resolution river‐floodplain‐reservoir modeling for a holistic assessment of the impacts of dams and climate change on the floodpulse‐dependent hydro‐ecological systems in the MRB and other global regions.

ABSTRACT:

Manmade reservoirs are important components of the terrestrial water balance. Thus, considering the hydro‐climatic effects of reservoirs is important in water cycle studies at a river basin to global scales; yet, reservoirs are represented poorly in large‐scale hydrological and climate models. Here we present a high‐resolution (5 km) continental‐scale reservoir storage dynamics and release scheme by enhancing existing schemes and adding critical novel parameterizations to improve reservoir storage and release simulations. The new scheme simulates river‐floodplain‐reservoir storages in an integrated manner considering their spatial and temporal variations. A new calibration scheme is also incorporated to better simulate reservoir dynamics considering cascade‐reservoir effects. Further, since no reservoir bathymetry data are available over large domains, we use a state‐of‐the‐art digital elevation model and reservoir extent data to derive reservoir bed elevation. The new scheme is integrated within the river‐floodplain routing scheme of a continental hydrological model LEAF‐Hydro‐Flood. Results from the simulation of ~1,900 reservoirs within the contiguous United States suggest that the model well captures the observed reservoir storage‐release dynamics. Comparison of our results with those from the existing schemes suggest a significant improvement; importantly, the new scheme reduces the excessive and frequent reservoir overfilling and underfilling. Comparison of results with satellite‐based surface water data shows that the model accurately reproduces the large‐scale patterns of reservoir‐floodplain inundation extents. It is expected that the results of this study will inform the incorporation of reservoirs in hyper‐resolution models to improve simulations of terrestrial water storage and flow and examine reservoir‐atmosphere interactions over large domains.

ABSTRACT:

Irrigation representation in land surface models has been advanced over the past decade, but the soil moisture (SM) data from SMAP satellite have not yet been utilized in large-scale irrigation modeling. Here we investigate the potential of improving irrigation representation in the Community Land Model version-4.5 (CLM4.5) by assimilating SMAP data. Simulations are conducted over the heavily irrigated central U.S. region. We find that constraining the target SM in CLM4.5 using SMAP data assimilation with 1-D Kalman filter reduces the root-mean-square error of simulated irrigation water requirement by 50% on average (for Nebraska, Kansas, and Texas) and significantly improves irrigation simulations by reducing the bias in irrigation water requirement by up to 60%. An a priori bias correction of SMAP data further improves these results in some regions but incrementally. Data assimilation also enhances SM simulations in CLM4.5. These results could provide a basis for improved modeling of irrigation and land-atmosphere interactions.

ABSTRACT:

Irrigation representation in land surface models has been advanced over the past decade, but the soil moisture (SM) data from SMAP satellite have not yet been utilized in large-scale irrigation modeling. Here we investigate the potential of improving irrigation representation in the Community Land Model version-4.5 (CLM4.5) by assimilating SMAP data. Simulations are conducted over the heavily irrigated central U.S. region. We find that constraining the target SM in CLM4.5 using SMAP data assimilation with 1-D Kalman filter reduces the root-mean-square error of simulated irrigation water requirement by 50% on average (for Nebraska, Kansas, and Texas) and significantly improves irrigation simulations by reducing the bias in irrigation water requirement by up to 60%. An a priori bias correction of SMAP data further improves these results in some regions but incrementally. Data assimilation also enhances SM simulations in CLM4.5. These results could provide a basis for improved modeling of irrigation and land-atmosphere interactions.

ABSTRACT:

Terrestrial water storage (TWS) modulates the hydrological cycle and is a key determinant of water availability and an indicator of drought. While historical TWS variations have been studied, future changes in TWS and the linkages to droughts remain unexamined. Here, using ensemble hydrological simulations, we show that climate change could reduce TWS in many regions, especially those in the Southern Hemisphere. Strong inter-ensemble agreement indicates high confidence in the projected changes that are driven primarily by climate forcing, rather than land and water management activities. Declines in TWS translate to increases in future droughts. By the late twenty-first century, global land area and population in extreme-to-exceptional TWS drought could more than double, each increasing from 3% during 1976-2005 to 7% and 8%, respectively. Our findings highlight the importance of climate change mitigation to avoid adverse TWS impacts and increased droughts, and the need for improved water resource management and adaptation.

ABSTRACT:

Numerous studies have examined the reliability of various precipitation products over the Mekong River Basin (MRB) and modeled its basin hydrology. However, there is a lack of comprehensive studies on precipitation-induced uncertainties in hydrological simulations using process-based land surface models. This study examines the propagation of precipitation uncertainty into hydrological simulations over the entire MRB using the Community Land Model version 5 (CLM5) at a high spatial resolution of 0.05° (~5 km) and without any parameter calibration. Simulations conducted using different precipitation datasets are compared to investigate the discrepancies in streamflow, terrestrial water storage (TWS), soil moisture, and evapotranspiration (ET) caused by precipitation uncertainty. Results indicate that precipitation is a key determinant of simulated streamflow in the MRB; peak flow and soil moisture are particularly sensitive to precipitation input. Further, 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. In addition, since high flow indicators are particularly influenced by precipitation data, the choice of precipitation data could directly impact flood pulse simulations in the MRB. Notable differences are also found among TWS, soil moisture, and ET simulated using different precipitation products. Moreover, TWS, soil moisture, and ET exhibit a varying degree of sensitivity to precipitation uncertainty. This study provides crucial insights on precipitation-induced uncertainties in process-based hydrological modeling and uncovers these uncertainties in the MRB.

ABSTRACT:

Groundwater depletion is a worldwide concern and an emerging issue in regions such as the Mekong River Basin (MRB). However, even the natural dynamics of groundwater in the MRB is yet to be fully explored, making the quantification of groundwater response to climate variability and anthropogenic activities a major scientific challenge. Here, we examine various groundwater mechanisms in the MRB, focusing on groundwater flow processes that are modulated by climate variability, physiographic features, and key drivers of groundwater-surface water interactions. We further quantify the influence of anthropogenic activities on groundwater dynamics. We use the Community Land Model version 5 (CLM5) at 0.05° (~5km) spatial resolution with an improved representation of groundwater processes, including lateral groundwater flow and aquifer pumping for irrigation. Results indicate high spatial heterogeneity in groundwater recharge and discharge across the basin governed by climate and subsurface characteristics. A pronounced seasonality is found in groundwater recharge due to precipitation; ~52% of wet season precipitation recharges groundwater, with substantial carryover to the consecutive dry season that alleviates soil moisture. Importantly, groundwater discharge is a dominant source of streamflow all year round, which suggests a strong surface water-groundwater coupling in the MRB. Finally, our results indicate that irrigation pumping is directly altering groundwater flows and storages; climate variability smoothens pumping effects over long times, but the model simulates region-wide groundwater depletion (up to 1 m/year) in the Mekong Delta during dry years. Our study provides key insights on the evolving groundwater systems in the MRB, also advancing process-based groundwater modeling capabilities.