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Second we compare with independent basin-scale estimates of TWS anomalies derived by means of combined atmospheric and terrestrial water -balance using atmospheric water vapor flux convergence and change in atmospheric water vapor content Mueller et al. Advanced signal separation techniques enable to isolate different sources of mass such as atmospheric and oceanic circulation or land hydrology. This method facilitates further studies of terrestrial water storage on a global scale. Our findings indicate that anthropogenic groundwater extraction has a minor influence in this region, while a decline in lake mass and natural depletion of groundwater play a key role. We integrated the GRACE observations into a hydrology model using an advanced technique called data assimilation.

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Accordingly, monitoring of the groundwater change is critical for sustainable water resources management. We compare water stress estimates derived using either renewable water or the total volume of water globally. The merging of satellite observations with numerical models has led to improved land surface predictions. Furthermore, appreciable relationships are observed between recession coefficient and past TWSA values implying that storage takes time to deplete completely.

This method can be used to monitor regions where large-scale aquifer depletion is ongoing, and in situ measurements are limited, such as the North China Plain or western India.

Our rainfall-runoff model confirms that northern Iraq suffered a drought between and and captures the annual cycle and longer trend of the observed GRACE data.

Large declining trends are found mostly in intensively irrigated basins and in some basins in northern latitudes. The results show the proper distribution of TWS change and identify the spatial distribution of significant rates and accelerations. We study how changes in atmosphere moisture stress and coupling of water storage components at different depth impact on the spatial and temporal correlation between TWS, SM and vegetation metrics.

However, the usually shallow groundwater compartment of the models presents a problem with GRACE assimilation techniques, as these satellite observations account for much deeper aquifers. We then quantify the linear relationship that exists between the modeled mass and the residual differences, defining a simple differential correction procedure that is applied to the modeled signals.

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Quantifiable metrics of groundwater storage are necessary to provide such evidence, yet in situ measurements are sparse at best. This study used a global hydrological model GHMPCR-GLOBWB, 202204 simulates surface water storage changes, natural and human induced groundwater storage changes, and the interactions between surface water and subsurface waterto generate scaling factors by mimicking low-pass filtering of GRACE signals. In contrast with microwave-based satellite missions that are only sensitive to near-surface soil moisture 0 – 5 cmthe Gravity Recovery and Climate Experiment GRACE mission provides accurate measurements of the entire vertically integrated terrestrial water storage column but, it is characterized by low spatial i.

This validation increases confidence level in the application of GRACE observations in monitoring large-scale storage changes in intensely irrigated areas in India and other regions around the world.

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There is possible soil-pore collapse, and land subsidence due to storage depletion in the study area. Together these data provide complementary metrics quantifying available plant water supply and have important implications for water resource management.

Our results also indicate reservoir leakage and groundwater recharge due to TGR filling and contamination from neighboring lakes are nonnegligible in the GRACE total water storage changes. The Ensemble Square-Root Filter EnSRF technique is applied, which showed stable performance in propagating errors during the assimilation period It is observed that storage -discharge relationship is exponential in nature, contrary to the general assumption that the relationship is linear.

The work presented here should provide a more realistic image of water stress by explicitly quantifying groundwater, defining water availability as total water supply, and using GRACE to more accurately quantify water use.

These cw will be used to initialize, calibration and potentially steer the hydrologic simulation. The spatiotemporal evolution of GRACE data reflects consistent patterns with that of several hydroclimatic variables and also shows that most of the water loss has occurred in the northern parts of India.

Latitudinal averages showed how precipitation dominates TWSC variations in the tropics, evapotranspiration is most effective in the midlatitudes, and snowmelt runoff is a key dissipating flux at high latitudes.

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Spatial analysis of drought risk from the end of to the beginning of showed that human activities hlue-03 an important role in the extent of drought hazards in the HRB. We provide an overview of the relative importance and spatial distribution of these components globally. Did the groundwater recover? The new scheme therefore better reflects submonthly variations in TWS errors.

To be consistent, we generated a climatology of estimated soil moisture and ground water based on a year Catchment model simulation, which was used to convert seven years of GRACE assimilated fields into drought indicator percentiles. The data assimilation routine produces a conditioned updated estimate that is more accurate and contains less uncertainty during both the snow accumulation phase of the snow season as well as during the snow ablation season.

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GRACE assimilated root zone soil moisture and TWS fields exhibited significant changes in their dryness rankings relative to those without data assimilation, suggesting that GRACE data assimilation could have a substantial impact on drought monitoring.

The procedure is as follows. Blur-03 model forecasts river flows by simulating surface runoff from snowmelt and the corresponding baseflow from groundwater discharge. Additional uncertainties are introduced by the models used in computing model-dependent indices. Daily storage -discharge relationship is highly dynamic, which generates large amount of scatter in storage -discharge plots. Combining GRACE -observed TWS changes and independent estimates of water change in soil and snow and surface reservoirs offers a means for estimating groundwater storage change.

The implications of utilizing finer resolution GRACE data for improving local and regional water resources management decisions and applications are clear, particularly in areas lacking in-situ hydrologic monitoring networks.