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Hydrogeodesy, a relatively new field within the earth sciences, is the analysis of the distribution and movement of terrestrial water at Earth's surface using measurements of Earth's shape, orientation, and gravitational field. In this paper, we review the current state of hydrogeodesy with a specific focus on Global Navigation Satellite System (GNSS)/Global Positioning System measurements of hydrologic loading. As water cycles through the hydrosphere, GNSS stations anchored to Earth's crust measure the associated movement of the land surface under the weight of changing hydrologic loads. Recent advances in GNSS‐based hydrogeodesy have led to exciting applications of hydrologic loading and subsequent terrestrial water storage (TWS) estimates. We describe how GNSS position time series respond to climatic drivers, can be used to estimate TWS across temporal scales, and can improve drought characterization. We aim to facilitate hydrologists' use of GNSS‐observed surface deformation as an emerging tool for investigating and quantifying water resources, propose methods to further strengthen collaborative research and exchange between geodesists and hydrologists, and offer ideas about pressing questions in hydrology that GNSS may help to answer.

The concept of adaptive capacity has received significant attention within social-ecological and environmental change research. Within both the resilience and vulnerability literatures specifically, adaptive capacity has emerged as a fundamental concept for assessing the ability of social-ecological systems to adapt to environmental change. Although methods and indicators used to evaluate adaptive capacity are broad, the focus of existing scholarship has predominately been at the individual- and household- levels. However, the capacities necessary for humans to adapt to global environmental change are often a function of individual and societal characteristics, as well as cumulative and emergent capacities across communities and jurisdictions. In this paper, we apply a systematic literature review and co-citation analysis to investigate empirical research on adaptive capacity that focus on societal levels beyond the household. Our review demonstrates that assessments of adaptive capacity at higher societal levels are increasing in frequency, yet vary widely in approach, framing, and results; analyses focus on adaptive capacity at many different levels (e.g. community, municipality, global region), geographic locations, and cover multiple types of disturbances and their impacts across sectors. We also found that there are considerable challenges with regard to the ‘fit’ between data collected and analytical methods used in adequately capturing the cross-scale and cross-level determinants of adaptive capacity. Current approaches to assessing adaptive capacity at societal levels beyond the household tend to simply aggregate individual- or household-level data, which we argue oversimplifies and ignores the inherent interactions within and across societal levels of decision-making that shape the capacity of humans to adapt to environmental change across multiple scales. In order for future adaptive capacity research to be more practice-oriented and effectively guide policy, there is a need to develop indicators and assessments that are matched with the levels of potential policy applications.

Feedbacks between geomorphic processes and riparian vegetation in river systems are an important control on fluvial morphodynamics and on vegetation composition and distribution. Invasion by nonnative riparian species alters these feedbacks and drives management and restoration along many rivers, highlighting a need for ecogeomorphic models to assist with understanding feedbacks between plants and fluvial processes, and with restoration planning. In this study, we coupled a network‐scale sediment model (Sediment Routing and Floodplain Exchange; SeRFE) that simulates bank erosion and sediment transport in a spatially explicit manner with a recruitment potential analysis for a species of riparian vegetation (Arundo donax) that has invaded river systems and wetlands in Mediterranean climates worldwide. We used the resulting ecogeomorphic framework to understand both network‐scale sediment balances and the spread and recruitment ofA. donaxin the Santa Clara River watershed of Southern California. In the coupled model, we simulated a 1‐year time period during which a 5‐year recurrence interval flood occurred in the mainstem Santa Clara River. Outputs identify key areas acting as sources ofA. donaxrhizomes, which are subsequently transported by flood flows and deposited in reaches downstream. These results were validated in three study reaches, where we assessed postflood geomorphic and vegetation changes. The analysis demonstrates how a coupled model approach is able to highlight basin‐scale ecogeomorphic dynamics in a manner that is useful for restoration planning and prioritization and can be adapted to analogous ecogeomorphic questions in other watersheds.

Non‐uniqueness in groundwater model calibration is a primary source of uncertainty in groundwater flow and transport predictions. In this study, we investigate the ability of environmental tracer information to constrain groundwater model parameters. We utilize a pilot point calibration procedure conditioned to subsets of observed data including: liquid pressures, tritium (³H), chlorofluorocarbon‐12 (CFC‐12), and sulfur hexafluoride (SF₆) concentrations; and groundwater apparent ages inferred from these environmental tracers, to quantify uncertainties in the heterogeneous permeability fields and infiltration rates of a steady‐state 2‐D synthetic aquifer and a transient 3‐D model of a field site located near Riverton, Wyoming (USA). To identify the relative data worth of each observation data type, the post‐calibration uncertainties of the optimal parameters for a given observation subset are compared to that from the full observation data set. Our results suggest that the calibration‐constrained permeability field uncertainties are largest when liquid pressures are used as the sole calibration data set. We find significant reduction in permeability uncertainty and increased predictive accuracy when the environmental tracer concentrations, rather than apparent groundwater ages, are used as calibration targets in the synthetic model. Calibration of the Riverton field site model using environmental tracer concentrations directly produces infiltration rate estimates with the lowest uncertainties, however; permeability field uncertainties remain similar between the environmental tracer concentration and apparent groundwater age calibration scenarios. This work provides insight on the data worth of environmental tracer information to calibrate groundwater models and highlights potential benefits of directly assimilating environmental tracer concentrations into model parameter estimation procedures.

Rainforest in protected areas in the Brazilian Amazon is at risk due to increasing economic pressures and recent weakening of environmental agencies and legislation by the federal administration. This study examines the impacts of deforestation in protected areas on dry‐season precipitation in the Brazilian state of Rondônia located in the southwestern Brazilian Amazon. Regional‐climate model simulations indicate that clearing protected forests in Rondônia would result in substantial changes to the surface energy balance, including increased sensible and decreased latent heat flux. Consequent changes to low‐level wind circulation would enhance moisture flux convergence and convection over the newly deforested areas, leading to enhanced rainfall in those areas. However, deforestation of protected areas would decrease dry season rainfall up to 30% in the existing agricultural region, with potentially important negative impacts on agricultural production. Additionally, our results indicate that following deforestation, the newly degraded areas will experience warmer and drier afternoons that could place the remaining natural vegetation under vapor deficit stress.

Sediment regimes, i.e., the processes that recruit, transport, and store sediment, create the physical habitats that underpin river‐floodplain ecosystems. Natural and human‐induced disturbances that alter sediment regimes can have cascading effects on river and floodplain morphology, ecosystems, and a river's ability to provide ecosystem services, yet prediction of the response of sediment dynamics to disturbance is challenging. We developed the Sediment Routing and Floodplain Exchange (SeRFE) model, which is a network‐based, spatially explicit framework for modeling sediment recruitment to and subsequent transport through drainage networks. SeRFE additionally tracks the spatially and temporally variable balance between sediment supply and transport capacity. Simulations using SeRFE can account for various types of watershed disturbance and for channel‐floodplain sediment exchange. SeRFE is simple, adaptable, and can be run with widely available geospatial data and limited field data. The model is driven by real or user‐generated hydrographs, allowing the user to assess the combined effects of disturbance, channel‐floodplain interactions and particular flow scenarios on the propagation of disturbances throughout a drainage network, and the resulting impacts to reaches of interest. We tested the model in the Santa Clara River basin, Southern California, in subbasins affected by large dams and wildfire. Model results highlight the importance of hydrologic conditions on postwildfire sediment yield and illustrate the spatial extent of dam‐induced sediment deficit during a flood. SeRFE can provide contextual information on reach‐scale sediment balance conditions, sensitivity to altered sediment regimes, and potential for morphologic change for managers and practitioners working in disturbed watersheds.

Changes in individual climate variables have been widely documented over the past century. However, assessments that consider changes in the collective interaction amongst multiple climate variables are relevant for understanding climate impacts on ecological and human systems yet are less well documented than univariate changes. We calculate annual multivariate climate departures during 1958–2017 relative to a baseline 1958–1987 period that account for covariance among four variables important to Earth’s biota and associated systems: annual climatic water deficit, annual evapotranspiration, average minimum temperature of the coldest month, and average maximum temperature of the warmest month. Results show positive trends in multivariate climate departures that were nearly three times that of univariate climate departures across global lands. Annual multivariate climate departures exceeded two standard deviations over the past decade for approximately 30% of global lands. Positive trends in climate departures over the last six decades were found to be primarily the result of changes in mean climate conditions consistent with the modeled effects of anthropogenic climate change rather than changes in variability. These results highlight the increasing novelty of annual climatic conditions viewed through a multivariate lens and suggest that changes in multivariate climate departures have generally outpaced univariate departures in recent decades.

Here we use Richards Equation models of variably saturated soil and bedrock groundwater flow to investigate first‐order patterns of the coupling between soil and bedrock flow systems. We utilize a Monte Carlo sensitivity analysis to identify important hillslope parameters controlling bedrock recharge and then model the transient response of bedrock and soil flow to seasonal precipitation. Our results suggest that hillslopes can be divided into three conceptual zones of groundwater interaction, (a) the zone of lateral unsaturated soil moisture accumulation (upper portion of hillslope), (b) the zone of soil saturation and bedrock recharge (middle of hillslope) and (c) the zone of saturated‐soil lateral flow and bedrock groundwater exfiltration (bottom of hillslope). Zones of groundwater interaction expand upslope during periods of precipitation and drain downslope during dry periods. The amount of water partitioned to the bedrock groundwater system a can be predicted by the ratio of bedrock to soil saturated hydraulic conductivity across a variety of hillslope configurations. Our modelled processes are qualitatively consistent with observations of shallow subsurface saturation and groundwater fluctuation on hillslopes studied in our two experimental watersheds and support a conceptual model of tightly coupled shallow and deep subsurface circulation where groundwater recharge and discharge continuously stores and releases water from longer residence time storage.

Environmental flow releases are an effective tool to meet multiple management objectives, including maintaining river conveyance, restoring naturally functioning riparian plant communities, and controlling invasive species. In this context, predicting plant mortality during floods remains a key area of uncertainty for both river managers and ecologists, particularly with respect to how flood hydraulics and sediment dynamics interact with the plants’ own traits to influence their vulnerability to scour and burial.