The Gravity Recovery and Climate Experiment (GRACE) has been successfully used to monitor variations in terrestrial water storage (GRACE_TWS) and groundwater storage (GRACE_GWS) across the globe, yet such applications are hindered on local scales by the limited spatial resolution of GRACE data. Using the Lower Peninsula of Michigan as a test site, we developed optimum procedures to downscale GRACE Release-06 monthly mascon solutions. A four-fold exercise was conducted. Cluster analysis was performed to identify the optimum number and distribution of clusters (areas) of contiguous pixels of similar geophysical signals (GRACE_TWS time series); three clusters were identified (cluster 1: 13,700 km²; cluster 2: 59,200 km²; cluster 3: 33,100 km²; Step I). Variables (total precipitation, normalized difference vegetation index (NDVI), snow cover, streamflow, Lake Michigan level, Lake Huron level, land surface temperature, soil moisture, air temperature, and evapotranspiration (ET)), which could potentially contribute to, or correlate with, GRACE_TWS over the test site were identified, and the dataset was randomly partitioned into training (80%) and testing (20%) datasets (Step II). Multivariate regression, artificial neural network, and extreme gradient boosting techniques were applied on the training dataset for each of the identified clusters to extract relationships between the identified hydro-climatic variables and GRACE_TWS solutions on a coarser scale (13,700–33,100 km²), and were used to estimate GRACE_TWS at a spatial resolution matching that of the fine-scale (0.125° × 0.125° or 120 km²) inputs. The statistical models were evaluated by comparing the observed and modeled GRACE_TWS values using the R-squared, the Nash–Sutcliffe model efficiency coefficient (NSE), and the normalized root-mean-square error (NRMSE; Step III). Lastly, temporal variations in GRACE_GWS were extracted using outputs of land surface models and those of the optimum downscaling methodology (downscaled GRACE_TWS) (Step IV). Findings demonstrate that (1) consideration should be given to the cluster-based extreme gradient boosting technique in downscaling GRACE_TWS for local applications given their apparent enhanced performance (average value: R-squared: 0.86; NRMSE 0.37; NSE 0.86) over the multivariate regression (R-squared: 0.74; NRMSE 0.56; NSE 0.64) and artificial neural network (R-squared: 0.76; NRMSE 0.5; NSE 0.37) methods; and (2) identifying local hydrologic variables and the optimum downscaling approach for individual clusters is critical to implementing this method. The adopted method could potentially be used for groundwater management purposes on local scales in the study area and in similar settings elsewhere.

In the last few decades, harmful algal blooms (HABs, also known as “red tides”) have become one of the most detrimental natural phenomena in Florida’s coastal areas. Karenia brevis produces toxins that have harmful effects on humans, fisheries, and ecosystems. In this study, we developed and compared the efficiency of state-of-the-art machine learning models (e.g., XGBoost, Random Forest, and Support Vector Machine) in predicting the occurrence of HABs. In the proposed models the K. brevis abundance is used as the target, and 10 level-02 ocean color products extracted from daily archival MODIS satellite data are used as controlling factors. The adopted approach addresses two main shortcomings of earlier models: (1) the paucity of satellite data due to cloudy scenes and (2) the lag time between the period at which a variable reaches its highest correlation with the target and the time the bloom occurs. Eleven spatio-temporal models were generated, each from 3 consecutive day satellite datasets, with a forecasting span from 1 to 11 days. The 3-day models addressed the potential variations in lag time for some of the temporal variables. One or more of the generated 11 models could be used to predict HAB occurrences depending on availability of the cloud-free consecutive days. Findings indicate that XGBoost outperformed the other methods, and the forecasting models of 5–9 days achieved the best results. The most reliable model can forecast eight days ahead of time with balanced overall accuracy, Kappa coefficient, F-Score, and AUC of 96%, 0.93, 0.97, and 0.98 respectively. The euphotic depth, sea surface temperature, and chlorophyll-a are always among the most significant controlling factors. The proposed models could potentially be used to develop an “early warning system” for HABs in southwest Florida.

Persistent scatterer interferometric analyses were conducted on a stack of 84 Environmental Satellite's Advanced Synthetic Aperture Radar scenes spanning 7 years (2004 to 2010) over the entire Nile Delta of Egypt and surroundings (area: 40,416 km²) to monitor the ongoing spatial and temporal land deformation, identify the factors controlling the deformation, and model the interplay between sea level rise and land subsidence to identify areas and populations threatened by sea encroachment by the end of the 21st century. Findings include the following: (1) general patterns of subsidence (average rate: −2.4 mm/year) in the northern delta, near‐steady to slight subsidence in the southern delta (average rate: 0.4 mm/year), separated by a previously mapped flexure zone (minimum width: 20–40 km) undergoing uplift (average rate: 2.5 mm/year); (2) high subsidence rates (up to −8.9 mm/year) over the north central and northeastern delta (area: ~4,815 km²), possibly due to compaction of recent (5 m) silt and clay‐rich Holocene sediments; (3) high subsidence rates (up to −9.7 mm/year) in areas where the highest groundwater extraction rates were reported in southern delta (Menoufia governorate) and in reclaimed desert land in the western delta (Beheira governorate); (4) high subsidence rates (up to −9.7 mm/year) over onshore gas fields, notably the Abu Madi gas field, where high gas extraction rates have been recorded; and (5) using extracted deformation rates, high‐resolution TanDEM‐X digital elevation model, a eustatic sea level rise of 0.44 m, and applying a bathtub inundation model, an estimated 2,660 km² in northern delta will be inundated by year 2100.

The GRACE-derived terrestrial water storage (TWS_GRACE) provides measurements of the mass exchange and transport between continents, oceans, and ice sheets. In this study, a statistical approach was used to forecast TWS_GRACE data using 10 major African watersheds as test sites. The forecasted TWS_GRACE was then used to predict drought events in the examined African watersheds. Using a nonlinear autoregressive with exogenous input (NARX) model, relationships were derived between TWS_GRACE data and the controlling and/or related variables (rainfall, temperature, evapotranspiration, and Normalized Difference Vegetation Index). The performance of the model was found to be “very good” (Nash–Sutcliffe (NSE) > 0.75; scaled root mean square error (R*) < 0.5) for 60% of the investigated watersheds, “good” (NSE > 0.65; R* < 0.6) for 10%, and “satisfactory” (NSE > 0.50; R* < 0.7) for the remaining 30% of the watersheds. During the forecasted period, no drought events were predicted over the Niger basin, the termination of the latest (March–October 2015) drought event was observed over the Zambezi basin, and the onset of a drought event (January-March 2016) over the Lake Chad basin was correctly predicted. Adopted methodologies generate continuous and uninterrupted TWS_GRACE records, provide predictive tools to address environmental and hydrological problems, and help bridge the current gap between GRACE missions.

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 (85 mm) followed by a wet period (2013-2016; AAP: 107 mm), and during both periods the AAP remained negligible (280 km from source areas) and in soil moisture content in areas with shallow (<2 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.

An integrated approach [field, Interferometric Synthetic Aperture Radar (InSAR), hydrogeology, geodesy, and spatial analysis] was adopted to identify the nature, intensity, and spatial distribution of deformational features (sinkholes, fissures, differential settling) reported over fossil aquifers in arid lands, their controlling factors, and possible remedies. The Lower Mega Aquifer System (area 2 × 10⁶ km²) in central and northern Arabia was used as a test site. Findings suggest that excessive groundwater extraction from the fossil aquifer is the main cause of deformation: (1) deformational features correlated spatially and/or temporally with increased agricultural development and groundwater extraction, and with a decline in water levels and groundwater storage (− 3.7 ± 0.6 km³/year); (2) earthquake events (years 1985–2016; magnitude 1–5) are largely (65% of reported earthquakes) shallow (1–5 km) and increased from 1 event/year in the early 1980s (extraction 1 km³/year), up to 13 events/year in the 1990s (average annual extraction > 6.4 km³). Results indicate that faults played a role in localizing deformation given that deformational sites and InSAR-based high subsidence rates (− 4 to − 15 mm/year) were largely found within, but not outside of, NW–SE-trending grabens bound by the Kahf fault system. Findings from the analysis of Gravity Recovery and Climate Experiment solutions indicate that sustainable extraction could be attained if groundwater extraction was reduced by 3.5–4 km³/year. This study provides replicable and cost-effective methodologies for optimum utilization of fossil aquifers and for minimizing deformation associated with their use.