• Energy Research

Vegetation/Ecosystem Modeling and Analysis Project (VEMAP) Phase 2 model experiments investigated the response of biogeochemical and dynamic global vegetation models (DGVMs) to differences in climate over the conterminous United States. This was accomplished by simulating ecosystem processes using historical climate and atmospheric CO2 records from 1895–1993. We evaluated the behavior of six models (Biome‐BGC, Century, GTEC, LPJ, MC1, and TEM) by comparing simulated runoff in 13 watersheds to gauged streamflow from the Hydro‐Climatic Data Network. Metrics used to assess the “goodness of fit” between simulated and observed values were: (1) Pearson's r to evaluate the overall data set, (2) Kendall's τ to gauge seasonality trends as derived from a time‐series analysis of monthly runoff, and (3) three measures of absolute and relative error.We found small differences in performance among the six models over all watersheds. However, the models yielded highly divergent results depending upon the watershed analyzed. Performance of the ensemble of models in a watershed was positively correlated with observed streamflow: models in the wettest watersheds in this study were associated with the highest model correlations and largest absolute errors, and models in the driest watersheds were associated with the lowest correlations and smallest absolute errors. Mean relative error was small and nearly constant across watersheds. A bias estimator showed that the models tended to underestimate runoff in wet watersheds and overestimate runoff in dry watersheds. Analysis of long‐term trends in runoff using a moving‐average approach demonstrated the ability of the models to reproduce temporal variation in observed data, even though quantitative differences among models were large.Models relying on prescribed vegetation (Biome‐BGC, Century, and TEM) outperformed the two DGVMs (LPJ and MC1); GTEC gave the poorest fit to observations due to the absence of an evaporation function and a snow routine. Across all 13 watersheds, TEM ranked the highest in model performance. The validation results presented here suggest that improvements in the simulation of hydrologic processes in land‐surface models will come, in part, from a more realistic representation of subgrid‐scale soil moisture and from a more detailed understanding and representation of subsurface processes.

Satellite data may enable improved management of regional groundwater reserves.

AbstractHumans and ecosystems are deeply connected to, and through, the hydrological cycle. However, impacts of hydrological change on social and ecological systems are infrequently evaluated together at the global scale. Here, we focus on the potential for social and ecological impacts from freshwater stress and storage loss. We find basins with existing freshwater stress are drying (losing storage) disproportionately, exacerbating the challenges facing the water stressed versus non-stressed basins of the world. We map the global gradient in social-ecological vulnerability to freshwater stress and storage loss and identify hotspot basins for prioritization (n = 168). These most-vulnerable basins encompass over 1.5 billion people, 17% of global food crop production, 13% of global gross domestic product, and hundreds of significant wetlands. There are thus substantial social and ecological benefits to reducing vulnerability in hotspot basins, which can be achieved through hydro-diplomacy, social adaptive capacity building, and integrated water resources management practices.

Freshwater availability is changing worldwide. Here we quantify 34 trends in terrestrial water storage observed by the Gravity Recovery and Climate Experiment (GRACE) satellites during 2002-2016 and categorize their drivers as natural interannual variability, unsustainable groundwater consumption, climate change or combinations thereof. Several of these trends had been lacking thorough investigation and attribution, including massive changes in northwestern China and the Okavango Delta. Others are consistent with climate model predictions. This observation-based assessment of how the world's water landscape is responding to human impacts and climate variations provides a blueprint for evaluating and predicting emerging threats to water and food security.

As the world’s largest distributed store of fresh water, ground water plays a central part in sustaining ecosystems and enabling human adaptation to climate variability and change. The strategic importance of ground water for global water and food security will probably intensify under climate change as more frequent and intense climate extremes (droughts and floods) increase variability in precipitation, soil moisture and surface water. Here we critically review recent research assessing the impacts of climate on ground water through natural and human-induced processes as well as through groundwater-driven feedbacks on the climate system. Furthermore, we examine the possible opportunities and challenges of using and sustaining groundwater resources in climate adaptation strategies, and highlight the lack of groundwater observations, which, at present, limits our understanding of the dynamic relationship between ground water and climate.

Episodic recharge as a result of infrequent, high intensity precipitation events comprises the bulk of groundwater recharge in arid environments. Climate change and shifts in precipitation intensity will affect groundwater continuity, thus altering groundwater recharge. This study aims to identify changes in the ratio of groundwater recharge and precipitation, the R:P ratio, in the arid southwestern United States to characterize observed changes in groundwater recharge attributed to variations in precipitation intensity. Our precipitation metric, precipitation intensity magnification, was used to investigate the relationship between the R:P ratio and precipitation intensity. Our analysis identified significant changes in the R:P ratio concurrent with decreases in precipitation intensity. The results illustrate the importance of precipitation intensity in relation to groundwater recharge in arid regions and provide further insights for groundwater management in nonrenewable groundwater systems and in a changing climate.