Journal of The American Water Resources Association最新文献

This study provides step-by-step guidance for practitioners and local stakeholders on how to use existing study results to conduct benefit transfer (BT), and ultimately make informed predictions of how improvements in lake water clarity may benefit surrounding communities. The procedures are demonstrated using a publicly available meta-dataset developed by the United States Environmental Protection Agency, and a subsequent meta-analysis that synthesizes the literature on how improvements in water clarity impact home values. The BT procedures are demonstrated using a case study of 14 large lakes in Kosciusko County, Indiana. Lake-specific average increases in home values, as well as the value of the housing stock in aggregate, are calculated for illustrative improvements in lake water clarity. This analysis provides a critical bridge to better connect high-quality, academic research with real-world policy analysis, and ultimately serves to better equip local governments and stakeholders to make more informed policy and land use decisions.

Uncertainty in water quality trading (WQT) markets is frequently cited as a deterrent for participation, with few studies focusing on uncertainty in future water quality credit needs. To reduce this uncertainty, we present a geographic information system (GIS)-based methodology for estimating an upper bound of water quality credit needs for a set of spatially referenced planned construction projects over a large geographic region. We demonstrate the methodology by applying it to estimate future credit needs for the Virginia Department of Transportation's (VDOT) 6-year improvement program. The results show that 25% of the state's 6-digit hydrologic unit code (HUC) basins lack sufficient current credit supply to meet the estimated future credit need from VDOT's planned projects alone. Furthermore, while 70% of the 8-digit HUCs containing planned projects have a sufficient current credit supply to meet VDOT credit needs, this is true for only 20% of the 10-digit HUCs. Finally, nearly 25% of the planned transportation projects, representing potentially $9 million in credit purchases at current market rates, will be constructed in catchments with impaired water bodies. State regulations will initially limit these projects to trade with credit banks collocated at the 12-digit HUC level. This application demonstrates how the GIS-based methodology can be applied to reduce uncertainty about future WQT credit needs and how needs are aligned with current credit supply.

Aligning water supply with demand is a challenge, particularly in areas with large seasonal variation in precipitation and those dominated by winter precipitation. Climate change is expected to exacerbate this challenge, increasing the need for long-term planning. Long-term projections of water supply and demand that can aid planning are mostly published as agency reports, which are directly relevant to decision-making but less likely to inform future research. We present 20-year water supply and demand projections for the Columbia River, produced in partnership with the Washington State Dept. of Ecology. This effort includes integrated modeling of future surface water supply and agricultural demand by 2040 and analyses of future groundwater trends, residential demand, instream flow deficits, and curtailment. We found that shifting timing in water supply could leave many eastern Washington watersheds unable to meet late-season out-of-stream demands. Increasing agricultural or residential demands in watersheds could exacerbate these late-season vulnerabilities, and curtailments could become more common for rivers with federal or state instream flow rules. Groundwater trends are mostly declining, leaving watersheds more vulnerable to surface water supply or demand changes. Both our modeling framework and agency partnership can serve as an example for other long-term efforts that aim to provide insights for water management in a changing climate elsewhere around the world.

Providing adequate water supply to the growing number of urban residents will be a challenge faced by many utility managers throughout the remainder of this century. Though traditionally, water managers have looked toward supply-based solutions (e.g., expanding reservoirs), recent trends indicate a shift toward demand-side management (e.g., encouraging conservation behaviors). Here, we present an agent-based model (ABM) that simulates water supply as a function of the local climatic conditions and water consumption, which is, in part, determined based on water conservation attitudes. Our results indicate the ABM performs well (normalized root mean squared error <10%) for the study area. Further, we explore various hypothetical demand management scenarios by changing the water conservation attitudes of the households (i.e., the archetypes). This scenario testing reveals a statistically significant improvement to water availability after successfully changing water conservation attitudes to be more participatory. Ultimately, this study aims to understand the nuances of water conservation attitudes and aid utilities in their goal to better manage urban water demand.

This study proposes an approach to evaluate the efficiency of low impact development (LID) in reducing urban runoff using a rainfall generator to disaggregate daily rainfall into sub-hourly rainfall data, which are used as input of a hydrological model at the urban watershed scale. Twelve scenarios are analyzed combining four percentages of impervious area retrofitted with LIDs (25%, 50%, 75% and 100%), and three LID combinations of green roofs (GRs) and rain gardens (RGs). The rainfall generator Rainsim V.3 is used to generate 500 years of rainfall data with a 15-min time step to analyze the performance of LIDs in the long-term with the LID module of the Soil and Water Assessment Tool hydrological model. An urban watershed of 3 km² located in Florence (Italy) is selected as a case study. Results show the performances of GRs and RG on peak flow reduction, highlighting a maximum flow reduction of single facilities ranging between 15% and 60% that can improve in case of their combination. The hydrological performances of LID combinations are very sensitive to the intensity of rainfall events, as well as percentages of area treated underlining the importance of simulating multiple scenarios of intervention to determine the most efficient combination of LIDs for a given case study and support their proper design from a urban water hydrology perspective.

The National Weather Service (NWS) Office of Water Prediction (OWP), in conjunction with the National Center for Atmospheric Research and the NWS National Centers for Environmental Prediction (NCEP) implemented version 2.1 of the National Water Model (NWM) into operations in April of 2021. As with the initial version implemented in 2016, NWM v2.1 is an hourly cycling analysis and forecast system that provides streamflow guidance for millions of river reaches and other hydrologic information on high-resolution grids. The NWM provides complementary hydrologic guidance at current NWS river forecast locations and significantly expands guidance coverage and water budget information in underserved locations. It produces a full range of hydrologic fields, which can be leveraged by a broad cross section of stakeholders ranging from the emergency responder and water resource communities, to transportation, energy, recreation and agriculture interests, to other water-oriented applications in the government, academic and private sectors. Version 2.1 of the NWM represents the fifth major version upgrade and more than doubles simulation skill with respect to hourly streamflow correlation, Nash Sutcliffe Efficiency, and bias reduction, over its original inception in 2016. This paper will discuss the driving factors underpinning the creation of the NWM, provide a brief overview of the model configuration and performance, and discuss future efforts to improve NWM components and services.

The Western United States (U.S.) relies heavily on scarce water resources for both ecological services and irrigation. However, the response of irrigation water use during drought is not well documented. Irrigation decision-making is complex and influenced by human and environmental factors such as water deliveries, crop yields, equipment, labor, crop prices, and climate variability. While few irrigation districts have plans to curtail water deliveries during droughts, water rights, fallowing patterns, crop rotations, and profit expectations also influence irrigation management at the farm scale. This study uses high-resolution satellite data to examine the response of irrigators to drought by using a novel measure of irrigation management, the Standardized Irrigation Management Index. We assess the state of drought at the field and basin scales in terms of climate and streamflow and analyze the importance of variations in crop price and drought status on decision-making and water use. We show significant variability in field-scale response to drought and that crop type, irrigation type, and federal management explain regional and field-scale differences. The relative influence of climate and prices on crop transitions indicate prices more strongly drive crop planting decisions. The study provides insights into irrigation management during drought, which is crucial for sustainable water supply in the face of the ongoing water supply crisis in the U.S. Southwest.

Regulatory practitioners use hydroclimatic data to provide context to observations typically collected through field site visits and aerial imagery analysis. In the absence of site-specific data, regulatory practitioners must use proxy hydroclimatic data and models to assess a stream's hydroclimatology. One intent of current-generation continental-scale hydrologic models is to provide such hydrologic context to ungaged watersheds. In this study, the ability of two state-of-the-art, operational, continental-scale hydrologic modeling frameworks, the National Water Model and the Group on Earth Observation Global Water Sustainability (GEOGloWS) European Centre for Medium-Range Weather Forecasts (ECMWF) Streamflow Model, to produce daily streamflow percentiles and categorical estimates of the streamflow normalcy was examined. The modeled streamflow percentiles were compared to observed daily streamflow percentiles at four United States Geological Survey stream gages. The model's performance was then compared to a baseline assessment methodology, the Antecedent Precipitation Tool. Results indicated that, when compared to baseline assessment techniques, the accuracy of the National Water Model (NWM) or GEOGloWS ECMWF Streamflow Model was greater than the accuracy of the baseline assessment methodology at four stream gage locations. The NWM performed best at three of the four gages. This work highlighted a novel application of current-generation continental-scale hydrologic models.

Water quality credit trading has been advanced as a cost-effective means of achieving regulatory compliance. However, the volume of trading activity in operational programs is typically less than estimated by empirical analysis. The compliance behavior of Virginia Municipal Separate Storm Sewer Systems (MS4s) is studied in response to the Chesapeake Bay total maximum daily load (TMDL) to understand the circumstances in which trading is adopted, the extent to which trading is adopted, and the factors contributing to trading's use or nonuse. Results indicate that MS4s generally prefer to install their own pollutant control measures rather than trade. Many MS4s, however, rely on trade as a backup compliance option. MS4s favor bay compliance options that help meet other local management objectives (erosion control, infrastructure protection, and reductions toward local water quality objectives) and provide long term pollutant control benefits. Low cost term credits do not provide such benefits. For perpetual credits, MS4s use a variety of strategies to substantially reduce the cost differences between trade and nontrade compliance options.

Improvements in simulating and communicating the evolutionary trajectory of river morphology in response to environmental forcing over multi-decadal timeframes would foreshadow the development of “foresight competency” in river management, whereby resource managers could strategically plan toward the most preferred of several plausible futures. Of the six steps in foresight competency, visioning, which involves translating scientific forecasts into a format useable by resource managers via a user-friendly and interactive decision support tool that supports transparent decision-making, is the least well developed. The approach requires converting forecasting model outputs into metrics of channel evolution that highlight transitions either within or between channel morphology states. Here, seven process-based state transition metrics are proposed covering channel planform, morphological stability, corridor belt width, floodplain connectivity, bank erosion rate, bedform habitat diversity, and ecohydraulic diversity. To aid decision support, the metrics are converted into graphical indicators that are intuitive for management use and assembled into several prototype dashboard-style graphical user interfaces designed to facilitate interactivity. A proof-of-concept illustration is provided and priorities in development toward a fully operational decision support tool are discussed. Such developments are critical in ensuring the practical relevance of geomorphology.