Accurately assessing groundwater storage changes in Niger is critical for long-term water resource management but is difficult due to sparse field data. We present a study of groundwater storage changes and recharge in Southern Niger, computed using data from NASA Gravity Recovery and Climate Experiment (GRACE) mission. We compute a groundwater storage anomaly estimate by subtracting the surface water anomaly provided by the Global Land Data Assimilation System (GLDAS) model from the GRACE total water storage anomaly. We use a statistical model to fill gaps in the GRACE data. We analyze the time period from 2002 to 2021, which corresponds to the life span of the GRACE mission, and show that there is little change in groundwater storage from 2002–2010, but a steep rise in storage from 2010–2021, which can partially be explained by a period of increased precipitation. We use the Water Table Fluctuation method to estimate recharge rates over this period and compare these values with previous estimates. We show that for the time range analyzed, groundwater resources in Niger are not being overutilized and could be further developed for beneficial use. Our estimated recharge rates compare favorably to previous estimates and provide managers with the data required to understand how much additional water could be extracted in a sustainable manner.

Coastal urban flooding presents significant challenges due to the complex interactions between surface runoff, storm tides, and drainage systems. In highly impervious urban areas, infiltration may seem negligible, particularly during extreme events when soil saturation is rapidly exceeded. However, for nuisance flooding-becoming more frequent due to sea level rise and shifting rainfall patterns-the role of infiltration warrants closer examination. This study aims to assess the impact of incorporating infiltration processes into an urban flood model by evaluating flood extent under 1-, 10-, 50-, and 100-years return periods. Specifically, we performed our test case over an urban coastal watershed in Norfolk, Virginia using a detailed 2D/1D hydrodynamic model. For the evaluation of the model, we incorporated community-sourced inputs from residents and drivers collected through data portal application and a mobile navigation platform. The results show that infiltration losses reduced the flooded areas by 33 % during the 1-year return period and by 12 %, 9 %, and 5 % during 10-, 50-, and 100-years return periods respectively. In terms of flood volume, infiltration led to a 29 % reduction for the 1-year event, while reductions were smaller for extreme events due to rapid soil saturation. We also found significant variability in water depth, with for example a nearly 20 cm difference between full and zero saturation conditions during the nuisance flooding event on a selected street in the Park Place neighborhood. While less intense nuisance storms did not achieve full soil saturation, thereby reducing flood impacts, extreme events rapidly overwhelmed infiltration capacity, leading to increased surface runoff and flood inundation. Finally, the study showed how crowdsourced flood reports can help to validate urban flood models. In our case, the model accurately predicted flood locations with 88 % of community reports and 89 % of driver reports of flooding aligning with simulated inundation maps.

Groundwater modeling is a useful tool for assessing sustainability in water resources planning. However, groundwater models are difficult to construct in regions with limited data availability, areas where planning is most crucial. We illustrate how remote sensing data can be used with limited in situ data to build and calibrate a regional groundwater model in the Goulbi Maradi alluvial aquifer in southern Niger in Western Africa. We used data from the NASA Gravity Recovery and Climate Experiment (GRACE) satellite mission to estimate recharge rates, the primary source of water to the aquifer. We used the groundwater storage changes obtained from GRACE data from 2009 to 2021 to establish an overall water budget. We used this water budget to back-calculate groundwater withdrawals from pumping in the region. There are only very limited historic data on withdrawals. This approach allowed us to calibrate the model and use it as a predictive tool to analyze the impact of various assumptions about future recharge and groundwater extraction patterns associated with the development of groundwater infrastructure in the region. The results indicate that water extraction from the Goulbi Maradi alluvial aquifer is sustainable, even if current groundwater extraction is increased by up to 28%.

Groundwater modeling is a useful tool for assessing sustainability in water resources planning. However, groundwater models are difficult to construct in regions with limited data availability. We illustrated how remote sensing data can be used leverage limited in situ data to build and calibrate a regional groundwater model in the Goulbi Maradi alluvial aquifer in Southern Niger in Western Africa. We used data from the NASA Gravity Recovery and Climate Experiment (GRACE) satellite mission to estimate recharge rates, the primary source of water to the aquifer. Additionally, we incorporated groundwater storage changes obtained from GRACE data from 2009 to 2021 to establish an overall water budget from which we could back-calculate groundwater withdrawals from pumping in the region. This approach allowed us to calibrate the model and then convert it to a predictive tool to analyze the impact of various assumptions about future recharge and groundwater extraction patterns associated with the development of groundwater infrastruction in the region. The results indicate that the Goulbi Maradi alluvial aquifer is sustainable, even an increase of groundwater extraction up to 28%.

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