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doi: 10.1029/2019WR024870pmid: N/A
The special section on socio‐hydrology is one of most successful in Water Resources Research, containing more than 30 articles, with many more submitted. As we would hope for a special section, this is just the start, and we continue to receive a flow of papers that either explicitly describe themselves as socio‐hydrology or are addressing the challenges of coupled human and water systems. In this Editorial, we reflect upon the scope and nature of those articles and make some tentative suggestions about future directions and the realistic ambition for socio‐hydrology.
Zhu, Tingju; Ringler, Claudia; Rosegrant, Mark W.
doi: 10.1029/2017WR021007pmid: N/A
Appropriate agricultural water management (AWM) is crucial not only for alleviating water scarcity but also for food and nutrition security and healthy ecosystems. The multidimensional nature of AWM and inherently complex feedbacks between its components necessitate a systems approach. This paper proposes six dimensions of AWM and illustrates the importance of a systems approach using six separate, but linked, classical AWM topics. By emphasizing the whole picture of AWM and interactions among its subsystems at multiple levels, a systems approach offers the opportunity to holistically scrutinize the pros and cons of proposed AWM interventions beyond their direct effects at the locus that a single‐dimensional approach foretells.
Meyer, Rena; Engesgaard, Peter; Sonnenborg, Torben O.
doi: 10.1029/2018WR023624pmid: N/A
Worldwide, aquifers in low‐lying coastal areas are threatened by saltwater occurrence, as a result of small head gradients, high groundwater abstraction rates, and drain management of the landscape, which is likely to intensify with climate change. Numerical models can serve as tools to identify the sources of the salt and thus to increase understanding of the driving mechanisms and important parameters controlling the extent of saltwater intrusions. This way, areas vulnerable to sea level rise can be identified and managed. Challenges include unknown initial salt concentrations, heterogeneous geology, and anthropogenic alterations. In this study, hydrogeological, geophysical, and geochemical data are used to develop a numerical density‐dependent groundwater flow and transport model with the objective to understand the history of a saltwater‐affected groundwater system and its likely response to historic and future changes. The extent of the simulated saltwater intrusion compares well with Airborne Electromagnetic data that show salt water up to 20 km inland. The results reveal that the salt water originates from a combination of laterally intruding seawater and vertically infiltrating transgression water. Main features controlling the progression of the modern seawater into the coastal aquifers are high permeable, deep Miocene sand aquifers, buried valleys that provide preferential flow paths in combination with extensive Miocene clay layers that delay saltwater intrusion. Anthropogenic activity enhances the saltwater inflow from the ocean and induces transient conditions. Future scenarios show that saltwater progression due to nonstationarity leads to enhanced contamination of the deeper aquifers. Climate change affects primarily the shallow aquifer systems.
Zwieback, S.; Westermann, S.; Langer, M.; Boike, J.; Marsh, P.; Berg, A.
doi: 10.1029/2018WR023247pmid: N/A
Knowledge of soil moisture conditions is important for modeling soil temperatures, as soil moisture influences the thermal dynamics in multiple ways. However, in permafrost regions, soil moisture is highly heterogeneous and difficult to model. Satellite soil moisture data may fill this gap, but the degree to which they can improve permafrost modeling is unknown. To explore their added value for modeling soil temperatures, we assimilate fine‐scale satellite surface soil moisture into the CryoGrid‐3 permafrost model, which accounts for the soil moisture's influence on the soil thermal properties and the surface energy balance. At our study site in the Canadian Arctic, the assimilation improves the estimates of deeper (>10 cm) soil temperatures during summer but not consistently those of the near‐surface temperatures. The improvements in the deeper temperatures are strongly contingent on soil type: They are largest for porous organic soils (30%), smaller for thin organic soil covers (20%), and they essentially vanish for mineral soils (only synthetic data available). That the improvements are greatest over organic soils reflects the strong coupling between soil moisture and deeper temperatures. The coupling arises largely from the diminishing soil thermal conductivity with increasing desiccation thanks to which the deeper soil is kept cool. It is this association of dry organic soils being cool at depth that lets the assimilation revise the simulated soil temperatures toward the actually measured ones. In the future, the increasing availability of satellite soil moisture data holds promise for the operational monitoring of soil temperatures, hydrology, and biogeochemistry.
Love, D. M.; Venturas, M. D.; Sperry, J. S.; Brooks, P. D.; Pettit, J. L.; Wang, Y.; Anderegg, W. R. L.; Tai, X.; Mackay, D. S.
doi: 10.1029/2018WR023468pmid: N/A
The reliance of 10 Utah (USA) aspen forests on direct infiltration of growing season rain versus an additional subsurface water subsidy was determined from a trait‐ and process‐based model of stomatal control. The model simulated the relationship between water supply to the root zone versus canopy transpiration and assimilation over a growing season. Canopy flux thresholds were identified that distinguished nonstressed, stressed, and dying stands. We found growing season rain and local soil moisture were insufficient for the survival of 5 of 10 stands. Six stands required a substantial subsidy (31–80% of potential seasonal transpiration) to avoid water stress and maximize photosynthetic potential. Subsidy dependence increased with stand hydraulic conductance. Four of the six “subsidized” stands were predicted to be stressed during the survey year owing to a subsidy shortfall. Since winter snowpack is closely related to groundwater recharge in the region, we compared winter precipitation with tree‐ring chronologies. Consistent with model predictions, chronologies were more sensitive to snowpack in subsidized stands than in nonsubsidized ones. The results imply that aspen stand health in the region is more coupled to winter snowpack than to growing season water supply. Winters are predicted to have less precipitation as snow, indicating a stressful future for the region's aspen forests.
Czuba, Jonathan A.; David, Scott R.; Edmonds, Douglas A.; Ward, Adam S.
doi: 10.1029/2018WR023527pmid: N/A
High‐resolution topography reveals that floodplains along meandering rivers in Indiana commonly contain intermittently flowing channel networks. We investigated how the presence of floodplain channels affects lateral surface‐water connectivity between a river and floodplain (specifically exchange flux and timescales of transport) as a function of flow stage in a low‐gradient river‐floodplain system. We constructed a two‐dimensional, surface‐water hydrodynamic model using Hydrologic Engineering Center's River Analysis System (HEC‐RAS) 2D along 32 km of floodplain (56 km along the river) of the East Fork White River near Seymour, Indiana, USA, using lidar elevation data and surveyed river bathymetry. The model was calibrated using land‐cover specific roughness to elevation‐discharge data from a U.S. Geological Survey gage and validated against high‐water marks, an aerial photo showing the spatial extent of floodplain inundation, and measured flow velocities. Using the model results, we analyzed the flow in the river, spatial patterns of inundation, flow pathways, river‐floodplain exchange, and water residence time on the floodplain. Our results highlight that bankfull flow is an oversimplified concept for explaining river‐floodplain connectivity because some stream banks are overtopped and major low‐lying floodplain channels are inundated roughly 19 days per year. As flow increased, inundation of floodplain channels at higher elevations dissected the floodplain, until the floodplain channels became fully inundated. Additionally, we found that river‐floodplain exchange was driven by bank height or channel orientation depending on flow conditions. We propose a conceptual model of river‐floodplain connectivity dynamics and developed metrics to analyze quantitatively complex river‐floodplain systems.
Zhou, Zhengzheng; Smith, James A.; Wright, Daniel B.; Baeck, Mary Lynn; Yang, Long; Liu, Shuguang
doi: 10.1029/2018WR023567pmid: N/A
Urban development, topographic relief, and coastal boundaries can all exert influences on storm hydroclimatology, making rainfall and flood frequency analysis a major challenge. This study explores heterogeneity in extreme rainfall in the Baltimore Metropolitan region at small spatial scales using hydrometeorological analyses of major storm events in combination with hydroclimatological analyses based on storm catalogs developed using a 16‐year record of high‐resolution bias‐corrected radar rainfall fields. Our analyses demonstrate the potential for rainfall frequency methods using storm catalogs combined with stochastic storm transposition (SST); procedures are implemented for Dead Run, a small (14.3 km2) urban watershed located within the Baltimore Metropolitan area. The results point to the pronounced impact of complex terrain (including the Chesapeake Bay to the east, mountainous terrain to the west and urbanization in the region) on the regional rainfall climatology. Warm‐season thunderstorm systems are shown to be the dominant mechanism for generating extreme, short‐duration rainfall that leads to flash flooding. The SST approach is extended through the implementation of a multiplier field that accounts for spatial heterogeneities in extreme rainfall magnitude. SST‐based analyses demonstrate the need to consider rainfall heterogeneity at multiple scales when estimating the rainfall intensity‐duration‐frequency relationships.
Quinn, Niall; Bates, Paul D.; Neal, Jeff; Smith, Andy; Wing, Oliver; Sampson, Chris; Smith, James; Heffernan, Janet
doi: 10.1029/2018WR024205pmid: N/A
In this paper we seek to understand the nature of flood spatial dependence over the conterminous United States. We extend an existing conditional multivariate statistical model to enable its application to this large and heterogenous region and apply it to a 40‐year data set of ~2,400 U.S. Geological Survey gauge series records to simulate 1,000 years of U.S. flooding comprising more than 63,000 individual events with realistic spatial dependence. A continental‐scale hydrodynamic model at 30 m resolution is then used to calculate the economic loss arising from each of these events. From this we are able to compute the probability that different values of U.S. annual total economic loss due to flooding are exceeded (i.e., a loss‐exceedance curve). Comparing these data to an observed flood loss‐exceedance curve for the period 1988–2017 shows a reasonable match for annual losses with probability below 10% (e.g., >1 in 10‐year return period). This analysis suggests that there is a 1% chance of U.S. annual fluvial flood losses exceeding $78Bn in any given year, and a 0.1% chance of them exceeding $136Bn. Analysis of the set of stochastic events and losses yields new insights into the nature of flooding and flood risk in the United States. In particular, we confirm the strong relationship between flood affected area and event peak magnitude, but show considerable variability in this relationship between adjacent U.S. regions. The analysis provides a significant advance over previous national flood risk analyses as it gives the full loss‐exceedance curve instead of simply the average annual loss.
Singh, Ankita; Armstrong, Ryan T.; Regenauer‐Lieb, Klaus; Mostaghimi, Peyman
doi: 10.1029/2018WR023342pmid: N/A
Modeling flow and transport in porous media using pore‐scale modeling is reliant on rock properties derived from digital rock images using segmentation techniques. These digital rock images obtained using computed tomography incorporate the variation in the intensity of phases depending on the attenuation of X‐rays. A standard technique is the segmentation of tomographic images based on user‐selected grayscale thresholding, allowing the identification of different phases. This threshold is subjective based on the operator and results in loss of essential information about the grayscale variation after segmentation. This paper implements the gray‐level co‐occurrence matrix (GLCM) incorporating the full range of grayscale information. The GLCM captures the relative occurrence of grayscale values in a spatial map. These maps show visually connected/disconnected populations of different phases such as pore space, quartz grains, minerals, and other features. We show that each rock has its own GLCM signature depending on the variations in gray‐level intensities. Several statistical measures are calculated: (1) GLCM contrast describing local variation in the gray‐level intensities, (2) GLCM angular second moment, describing the rock homogeneity; (3) GLCM mean, describing weighted average of the probability of occurrence of features based on their location on the GLCM map; and (4) GLCM correlation, measuring the linear dependencies of grayscale values and the degree of (an) isotropy in the micro–computed tomographic images of each of the rock types. The GLCM method provides a pathway to alleviate user biases and allow automation of micro–computed tomography analyses.
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