RESUMO
Increased demands for sustainable water and energy resources in densely populated basins have led to the construction of dams, which impound waters in artificial reservoirs. In many cases, scarce field data led to the development of models that underestimated the seepage losses from reservoirs and ignored the role of extensive fault networks as preferred pathways for groundwater flow. We adopt an integrated approach (remote sensing, hydrologic modeling, and field observations) to assess the magnitude and nature of seepage from such systems using the Grand Ethiopian Renaissance Dam (GERD), Africa's largest hydropower project, as a test site. The dam was constructed on the Blue Nile within steep, highly fractured, and weathered terrain in the western Ethiopian Highlands. The GERD Gravity Recovery and Climate Experiment Terrestrial Water Storage (GRACETWS), seasonal peak difference product, reveals significant mass accumulation (43 ± 5 BCM) in the reservoir and seepage in its surroundings with progressive south-southwest mass migration along mapped structures between 2019 and 2022. Seepage, but not a decrease in inflow or increase in outflow, could explain, at least in part, the observed drop in the reservoir's water level and volume following each of the three fillings. Using mass balance calculations and GRACETWS observations, we estimate significant seepage (19.8 ± 6 BCM) comparable to the reservoir's impounded waters (19.9 ± 1.2 BCM). Investigating and addressing the seepage from the GERD will ensure sustainable development and promote regional cooperation; overlooking the seepage would compromise hydrological modeling efforts on the Nile Basin and misinform ongoing negotiations on the Nile water management.
RESUMO
Floods affect communities and ecosystems worldwide, emphasizing the importance of identifying their precursors and enhancing resilience to these events. Here, we calculated Antecedent Total Water Storage (ATWS) anomalies from the new 5-day (5D) Gravity Recovery and Climate Experiment (GRACE) and its Follow-On (GRACE-FO) satellite solutions to enhance the detection of pre-flood and active flood conditions and to map post-flood storage anomalies. The GRACE data were compared with ~ 3300 flood events reported by the Dartmouth Flood Observatory (2002-2021), revealing distinct ATWS precursor signals in 5D solutions, in contrast to the monthly solutions. Specifically, floods caused by saturation-excess runoff-triggered by persistent rainfall, monsoonal patterns, snowmelt, or rain-on-snow events-show detectable ATWS increases 15 to 50 days before and during floods, providing a valuable opportunity to improve flood monitoring. These 5D solutions also facilitate a more rapid mapping of post-flood storage changes to assess flood recovery from tropical cyclones and sub-monthly weather extremes. Our findings show the promising potential of 5D GRACE solutions, which are still in the development phase, for future integration into operational frameworks to enhance flood detection and recovery, facilitating the rapid analysis of storage changes relative to monthly solutions.
RESUMO
Gravity Recovery and Climate Experiment and its Follow On (GRACE (-FO)) missions have resulted in a paradigm shift in understanding the temporal changes in the Earth's gravity field and its drivers. To provide continuous observations to the user community, missing monthly solutions within and between GRACE (-FO) missions (33 solutions) need to be imputed. Here, we modeled GRACE (-FO) data (196 solutions) between 04/2002-04/2021 to infer missing solutions and derive uncertainties in the existing and missing observations using Bayesian inference. First, we parametrized the GRACE (-FO) time series using an additive generative model comprising long-term variability (secular trend + interannual to decadal variations), annual, and semi-annual cycles. Informative priors for each component were used and Markov Chain Monte Carlo (MCMC) was applied to generate 2,000 samples for each component to quantify the posterior distributions. Second, we reconstructed the new data (229 solutions) by joining medians of posterior distributions of all components and adding back the residuals to secure the variability of the original data. Results show that the reconstructed solutions explain 99% of the variability of the original data at the basin scale and 78% at the one-degree grid scale. The results outperform other reconstructed data in terms of accuracy relative to land surface modeling. Our data-driven approach relies only on GRACE (-FO) observations and provides a total uncertainty over GRACE (-FO) data from the data-generation process perspective. Moreover, the predictive posterior distribution can be potentially used for "nowcasting" in GRACE (-FO) near-real-time applications (e.g., data assimilations), which minimize the current mission data latency (40-60 days).
RESUMO
More extreme and prolonged floods and droughts, commonly attributed to global warming, are affecting the livelihood of major sectors of the world's population in many basins worldwide. While these events could introduce devastating socioeconomic impacts, highly engineered systems are better prepared for modulating these extreme climatic variabilities. Herein, we provide methodologies to assess the effectiveness of reservoirs in managing extreme floods and droughts and modulating their impacts in data-scarce river basins. Our analysis of multiple satellite missions and global land surface models over the Tigris-Euphrates Watershed (TEW; 30 dams; storage capacity: 250 km3), showed a prolonged (2007-2018) and intense drought (Average Annual Precipitation [AAP]: < 400 km3) with no parallels in the past 100 years (AAP during 1920-2020: 538 km3) followed by 1-in-100-year extensive precipitation event (726 km3) and an impressive recovery (113 ± 11 km3) in 2019 amounting to 50% of losses endured during drought years. Dam reservoirs captured water equivalent to 40% of those losses in that year. Additional studies are required to investigate whether similar highly engineered watersheds with multi-year, high storage capacity can potentially modulate the impact of projected global warming-related increases in the frequency and intensity of extreme rainfall and drought events in the twenty-first century.
Assuntos
Inundações , Rios , Mudança Climática , SecasRESUMO
We evaluate the impact of Gravity Recovery and Climate Experiment data assimilation (GRACE-DA) on seasonal hydrological forecast initialization over the U.S., focusing on groundwater storage. GRACE-based terrestrial water storage (TWS) estimates are assimilated into a land surface model for the 2003-2016 period. Three-month hindcast (i.e., forecast of past events) simulations are initialized using states from the reference (no data assimilation) and GRACE-DA runs. Differences between the two initial hydrological condition (IHC) sets are evaluated for two forecast techniques at 305 wells where depth-to-water-table measurements are available. Results show that using GRACE-DA-based IHC improves seasonal groundwater forecast performance in terms of both RMSE and correlation. While most regions show improvement, degradation is common in the High Plains, where withdrawals for irrigation practices affect groundwater variability more strongly than the weather variability, which demonstrates the need for simulating such activities. These findings contribute to recent efforts towards an improved U.S. drought monitor and forecast system.
RESUMO
Time-resolved satellite gravimetry has revolutionized understanding of mass transport in the Earth system. Since 2002, the Gravity Recovery and Climate Experiment (GRACE) has enabled monitoring of the terrestrial water cycle, ice sheet and glacier mass balance, sea level change and ocean bottom pressure variations and understanding responses to changes in the global climate system. Initially a pioneering experiment of geodesy, the time-variable observations have matured into reliable mass transport products, allowing assessment and forecast of a number of important climate trends and improve service applications such as the U.S. Drought Monitor. With the successful launch of the GRACE Follow-On mission, a multi decadal record of mass variability in the Earth system is within reach.
RESUMO
There is a general agreement that deep aquifers experience significant lag time in their response to climatic variations. Analysis of Temporal Gravity Recovery and Climate Experiment (GRACE), Soil Moisture and Ocean Salinity mission (SMOS), satellite altimetry, stable isotopic composition of groundwater, and precipitation and static global geopotential models over the Nubian Sandstone Aquifer System (NSAS) revealed rapid aquifer response to climate variability. Findings include: (1) The recharge areas of the NSAS (Northern Sudan Platform subbasin) witnessed a dry period (2002-2012), where average annual precipitation (AAP) was modest (85â¯mm) followed by a wet period (2013-2016; AAP: 107â¯mm), and during both periods the AAP remained negligible (<10â¯mm) over the northern parts of the NSAS (Dakhla subbasin); (2) the secular trends in terrestrial water storage (TWS) over the Dakhla subbasin were estimated at -3.8⯱â¯1.3â¯mm/yr andâ¯+â¯7.8⯱â¯1â¯mm/yr for the dry and wet periods, respectively; (3) spatial variations in TWS values and phase are consistent with rapid groundwater flow from the Northern Sudan Platform subbasin and Lake Nasser towards the Dakhla subbasin during the wet period and from the lake during the dry period; and (4) networks of densely fractured and karstified bedrocks provide preferential pathways for groundwater flow. The proposed model is supported by (1) rapid response in groundwater levels in distant wells (>280â¯km from source areas) and in soil moisture content in areas with shallow (<2â¯m) groundwater levels to fluctuations in Lake Nasser surface water, and (2) the isotopic composition (O, H) of groundwater along the preferred pathways, consistent with mixing of enriched (Lake Nasser water or precipitation over Sudan) and depleted (NSAS fossil water) endmembers. Findings provide new insights into the response of large, deep aquifers to climate variability and address the sustainability of the NSAS and similar fossil aquifers worldwide.
RESUMO
Recent acceleration of sand extraction for anthropic use threatens the sustainability of this major resource. However, continental erosion and river transport, which produce sand and sediment in general, lack quantification at the global scale. Here, we develop a new geodetic method to infer the sediment discharge to ocean of the world's largest rivers. It combines the spatial distribution of modern sedimentation zones with new high-resolution (~170 km) data from the Gravity Recovery and Climate Experiment (GRACE) mission launched in 2002. We obtain sediment discharges consistent with in situ measurements for the Amazon, Ganges-Brahmaputra, Changjiang, Indus, and Magdalena rivers. This new approach enables to quantitatively monitor the contemporary erosion of continental basins drained by rivers with large sediment discharges and paves the way toward a better understanding of how natural and anthropic changes influence landscape dynamics.
Assuntos
Sedimentos Geológicos/química , Gravitação , Oceanos e Mares , Rios/química , Comunicações Via Satélite , Geografia , Reprodutibilidade dos TestesRESUMO
Assessing reliability of global models is critical because of increasing reliance on these models to address past and projected future climate and human stresses on global water resources. Here, we evaluate model reliability based on a comprehensive comparison of decadal trends (2002-2014) in land water storage from seven global models (WGHM, PCR-GLOBWB, GLDAS NOAH, MOSAIC, VIC, CLM, and CLSM) to trends from three Gravity Recovery and Climate Experiment (GRACE) satellite solutions in 186 river basins (â¼60% of global land area). Medians of modeled basin water storage trends greatly underestimate GRACE-derived large decreasing (≤-0.5 km3/y) and increasing (≥0.5 km3/y) trends. Decreasing trends from GRACE are mostly related to human use (irrigation) and climate variations, whereas increasing trends reflect climate variations. For example, in the Amazon, GRACE estimates a large increasing trend of â¼43 km3/y, whereas most models estimate decreasing trends (-71 to 11 km3/y). Land water storage trends, summed over all basins, are positive for GRACE (â¼71-82 km3/y) but negative for models (-450 to -12 km3/y), contributing opposing trends to global mean sea level change. Impacts of climate forcing on decadal land water storage trends exceed those of modeled human intervention by about a factor of 2. The model-GRACE comparison highlights potential areas of future model development, particularly simulated water storage. The inability of models to capture large decadal water storage trends based on GRACE indicates that model projections of climate and human-induced water storage changes may be underestimated.