Groundwater in Africa supports livelihoods and poverty alleviation 1,2 , maintains vital ecosystems, and strongly influences terrestrial water and energy budgets 3. However, hydrologic processes governing groundwater recharge sustaining this resource, and their sensitivity to climatic variability, are poorly constrained 4,5. Here we show, through analysis of multi-decadal groundwater hydrographs across sub-Saharan Africa, how aridity controls the predominant recharge processes whereas local hydrogeology influences the type and sensitivity of precipitation-recharge relationships. Some humid locations show approximately linear precipitation-recharge relationships with small rainfall intensity exceedance thresholds governing recharge; others show surprisingly small variation in recharge across a wide range of annual precipitation. As aridity increases, precipitation thresholds governing initiation of recharge increase, recharge becomes more episodic, and focussed recharge via losses from ephemeral overland flows becomes increasingly dominant. Extreme annual recharge is commonly associated with intense rainfall and flooding events, themselves often driven by largescale climate controls. Intense precipitation, even during lower precipitation years, produces substantial recharge in some dry subtropical locations, challenging the 'high certainty' consensus that drying climatic trends will decrease water resources in such regions 4. The likely resilience of groundwater in many areas revealed by improved understanding of precipitation-recharge

Seasonal water storage fluctuations are critical for evaluating water scarcity linked to climate forcing and human intervention. Here we compare seasonal changes in land total water storage anomalies using seven global hydrologic and land surface models (WGHM, PCR‐GLOBWB, and five GLDAS models) to GRACE satellite data in 183 river basins globally. This work builds on previous analysis that focused on total water storage anomaly trends. Results show that most models underestimate seasonal water storage amplitudes in tropical and (semi)arid basins and land surface models generally overestimate amplitudes in northern basins. Some models (CLM‐5.0 and PCR‐GLOBWB) agree better with GRACE than others. Causes of model‐GRACE discrepancies are attributed to missing storage compartments (e.g., surface water and/or groundwater) and underestimation of modeled storage capacities in tropical basins and to variations in modeled fluxes in northern basins. This study underscores the importance of considering water storage, in addition to water fluxes, to improve global models.

From the 1980s, Indian summer monsoon rainfall (ISMR) shows a decreasing trend over north and northwest India, and there was a significant observed reduction in July over central and south India in 1982–2003. The key drivers of the changed ISMR, however, remain unclear. It was hypothesized that the large-scale irrigation development that started in the 1950s has resulted in land surface cooling, which slowed large-scale atmospheric circulation, exerting significant influences on ISMR. To test this hypothesis, a fully coupled model, the CESM v1.0.3, was used with a global irrigation dataset. In this study, spatially varying irrigation-induced feedback mechanisms are investigated in detail at different stages of the monsoon. Results show that soil moisture and evapotranspiration increase significantly over India throughout the summertime because of the irrigation. However, 2-m air temperature shows a significant reduction only in a limited region because the temperature change is influenced simultaneously by surface incoming shortwave radiation and evaporative cooling resulting from the irrigation, especially over the heavily irrigated region. Irrigation also induces a 925-hPa northeasterly wind from 30°N toward the equator. This is opposite to the prevailing direction of the Indian summer monsoon (ISM) wind that brings moist air to India. The modeled rainfall in the irrigated case significantly decreases up to 1.5 mm day−1 over central and north India from July to September. This paper reveals that the irrigation can contribute to both increasing and decreasing the surface temperature via multiple feedback mechanisms. The net effect is to weaken the ISM with the high spatial and temporal heterogeneity.

125°S-60°S) are significantly impacted by the WT, showing a decrease in air temperature (−0.5 K over mid-latitudes and −1 K over tropics) and an increase in precipitation. The latter can be explained by more vigorous updrafts due to an increased meridional temperature gradient between the equator and higher latitudes, which transports more water vapour upward, causing a positive precipitation change in the ascending branch. Over the West African Monsoon and Australian Monsoon regions, the precipitation changes in both intensity (increases) and location (poleward). The more intense convection and the change of the large-scale dynamics are responsible for this change. Transition zones, such as the Mediterranean area and central North America, are also impacted, with strengthened convection resulting from increased ET.

Abstract. Continental- to global-scale hydrologic and land surface models increasingly include representations of the groundwater system. Such large-scale models are essential for examining, communicating, and understanding the dynamic interactions between the Earth System above and below the land surface as well as the opportunities and limits of groundwater resources. We argue that both large-scale and regional-scale groundwater models have utility, strengths and limitations so continued modeling at both scales is essential and mutually beneficial. A crucial quest is how to evaluate the realism, capabilities and performance of large-scale groundwater models given their modeling purpose of addressing large-scale science or sustainability questions as well as limitations in data availability and commensurability. Evaluation should identify if, when or where large-scale models achieve their purpose or where opportunities for improvements exists so that such models better achieve their purpose. We suggest that reproducing the spatio-temporal details of regional-scale models and matching local data is not a relevant goal. Instead, it is important to decide on reasonable model expectations regarding when a large scale model is performing “well enough” in the context of its specific purpose. The decision of reasonable expectations is necessarily subjective even if the evaluation criteria is quantitative. Our objective is to provide recommendations for improving the evaluation of groundwater representation in continental- to global-scale models. We describe current modeling strategies and evaluation practices, and subsequently discuss the value of three evaluation strategies: 1) comparing model outputs with available observations of groundwater levels or other state or flux variables (observation-based evaluation); 2) comparing several models with each other with or without reference to actual observations (model-based evaluation); and 3) comparing model behavior with expert expectations of hydrologic behaviors in particular regions or at particular times (expert-based evaluation). Based on evolving practices in model evaluation as well as innovations in observations, machine learning and expert elicitation, we argue that combining observation-, model-, and expert-based model evaluation approaches, while accounting for commensurability issues, may significantly improve the realism of groundwater representation in large-scale models. Thus advancing our ability for quantification, understanding, and prediction of crucial Earth science and sustainability problems. We encourage greater community-level communication and cooperation on this quest, including among global hydrology and land surface modelers, local to regional hydrogeologists, and hydrologists focused on model development and evaluation.

Recent evidence has shown that relations between soil moisture and precipitation at spatial and temporal aspect are contrary to each other: afternoon precipitation tends to occur at times in which conditions are overall wet and heterogeneous in the morning, but preferentially over those patches that are relatively drier than the surroundings. This study expands the notion of soil moisture‐precipitation spatial coupling by analyzing the preferred precipitation location over a range of different soil moisture patterns. Using global observations of precipitation and observationally constrained evaporative stress estimates, we confirm that relatively drier patches have more chances of receiving rain, but the preference is weakened under wetter soil conditions. During extremely wet times, wet patches have more chances of receiving rain. Moreover, the preference of precipitation to occur on drier soils is stronger when soil moisture conditions are heterogeneous. Such results indicate that the positive feedback mechanism becomes more positive as soil wetness increases and the negative feedback mechanism becomes more negative as soils become drier and more heterogeneous. The strength of these two feedback mechanisms jointly affects preferential precipitation location. Counterintuitively, analysis from 1 day after‐event soil moisture pattern shows that negative soil moisture‐precipitation coupling may in turn further heterogenize soil moisture patterns, because dry patch gets extremely wet with no or less rain in surrounding. Although results here do not necessarily imply a causal relationship, this work contributes to enhancing our understanding of soil moisture‐precipitation spatial coupling and exposes the complex nuances of these land‐atmosphere interactions.

The US state of Texas has experienced consecutive flooding events since spring 2015 with devastating consequences, yet these happened only a few years after the record drought of 2011. Identifying the effect of climate variability on regional water cycle extremes, such as the predicted occurrence of La Niña in winter 2017-2018 and its association with drought in Texas, remains a challenge. The present analyses use large-ensemble simulations to project the future of water cycle extremes in Texas and assess their connection with the changing El Niño-Southern Oscillation (ENSO) teleconnection under global warming. Large-ensemble simulations indicate that both intense drought and excessive precipitation are projected to increase towards the middle of the 21st century, associated with a strengthened effect from ENSO. Despite the precipitation increase projected for the southern Great Plains, groundwater storage is likely to decrease in the long run with diminishing groundwater recharge; this is due to the concurrent increases and strengthening in drought offsetting the effect of added rains. This projection provides implications to short-term climate anomaly in the face of the La Niña and to long-term water resources planning.

The interaction between surface water and groundwater is an important aspect of hydrological processes. Despite its importance, groundwater is not well represented in many land surface models. In this study, a groundwater module with consideration of surface water and groundwater dynamic interactions is incorporated into the distributed biosphere hydrological (DBH) model in the upstream of the Yellow River basin, China. Two numerical experiments are conducted using the DBH model: one with groundwater module active, namely, DBH_GW and the other without, namely, DBH_NGW. Simulations by two experiments are compared with observed river discharge and terrestrial water storage (TWS) variation from the Gravity Recovery and Climate Experiment (GRACE). The results show that river discharge during the low flow season that is underestimated in the DBH_NGW has been improved by incorporating the groundwater scheme. As for the TWS, simulation in DBH_GW shows better agreement with GRACE data in terms of interannual and intraseasonal variations and annual changing trend. Furthermore, compared with DBH_GW, TWS simulated in DBH_NGW shows smaller decreases during autumn and smaller increases in spring.These results suggest that consideration of groundwater dynamics enables a more reasonable representation of TWS change by increasing TWS amplitudes and signals and as a consequence, improves river discharge simulation in the low flow seasons when groundwater is a major component in runoff. Additionally, incorporation of groundwater module also leads to wetter soil moisture and higher evapotranspiration, especially in the wet seasons.