Journal of The American Water Resources Association最新文献

Fluvial geomorphology, which describes the form and processes of rivers, is increasingly being incorporated into river assessment procedures. However, the complexity of geomorphic processes makes a single universal and standardized assessment protocol a challenging and possibly impractical task. In this paper, we present a set of recommendations for choosing appropriate river assessment procedures and measuring geomorphic indicators to effectively capture important geomorphic processes required to support river management goals. We outline steps for building a river assessment procedure based on an adaptive approach rather than a one-size-fits-all approach, where the geomorphic indicators, spatial and temporal scale, and methodologies used are carefully chosen based on the goals of the management project; the assessment aims to support. Guidance for choosing the appropriate geomorphic indicators is based on their significance (usefulness in characterizing the system), ease of measurement, and temporal scale needs. We also present recommendations on measurement techniques for each indicator while highlighting recent technological and methodological advancements that help overcome resource challenges often faced in river assessment. Given the wealth of scientific and technological developments in the field of geomorphology, it is possible to improve how geomorphic form and function are measured and incorporated into river assessments that support watershed management goals.

Accurate simulation of evapotranspiration (ET) is essential to enhance efficient irrigation management in the maize field. Here, we evaluated the performance of four mathematical models for estimating the ET of maize. The four models based on surface resistance calculate ET from different vapor sources, which are Penman-Monteith (PM) through the “big leaf” model, the Shuttleworth-Wallace (SW) model for distinguishing between soil and canopy, the clumping (C) model for distinguishing between canopy, soils under the canopy and bare soil, and the seasonal clumping (Cj) model for dividing ET into transpiration of sunlit leaves and shaded leaves, evaporation of bare soil surface, sunlit soil surface of canopy gap fraction, and canopy shaded soil surfaces. The models were calibrated by ET measured from a weighing lysimeter, transpiration by the sap flux method, and soil evaporation by micro-lysimeters in 2014, 2015, and 2017. Results showed that the measured daily transpiration was 3.32 mm/day during the full-grown stage of maize, and the mean measured daily soil evaporation was 1.46 mm/day. The performance of the sap flow for transpiration plus micro-lysimeter for soil evaporation method was consistent with the large-weighted lysimeter method in measuring daily ET. For simulating versus measuring hourly transpiration, the Cj model performed better than the C model with a slope of 0.94, determination coefficient (R²) of 0.85, mean absolute error (MAE) of 0.08 mm/h, and modified agreement index (d) of 0.81. In simulating daily soil evaporation, the Cj model also had a higher slope and less MAE than the C and SW models. Nevertheless, the Cj model yielded increased slope and d and decreased MAE between simulated and measured daily ET. The most sensitive environmental factor in the Cj model is temperature. With a 50% increase in temperature, ET, transpiration, and evaporation increase by 45%, 36%, and 69%, respectively. In summary, the Cj model improved the accuracy for hourly and daily ET of maize and helped separate plant transpiration and soil evaporation, thus giving an available approach for precision irrigation in water management of maize planting systems.

Despite geomorphic processes being increasingly recognized as a vital component of river management projects, evidence suggests that they may not be adequately captured in common river assessment procedures. We reviewed 91 river assessment procedures from around the world to evaluate their effectiveness in capturing geomorphic processes relevant for river management goals. Our objectives were to summarize which common geomorphic indicators are measured and how in different types of river assessments categorized based on their main focus: geomorphic, physical habitat, mixed geomorphic and habitat, and hydromorphology. Our analysis identified differences in the types of geomorphic indicators included and measurement methodologies between the types of assessment procedures. Some geomorphic processes, such as sediment transport, are nearly completely absent from all assessments, despite their importance for geomorphic processes. The variability among assessment procedures suggests that a single procedure is unlikely to capture all geomorphic components required to support every river management programs. Here, we discuss how the strengths and limitations of different assessment types can be used to guide decisions around how to select assessments and geomorphic indicators to support management project goals. A companion paper expands the discussion of how to plan effective river assessment procedures to support unique management goals.

Flooding is a dominant physical process that drives the form and function of river-floodplain ecosystems. Efficiently characterizing flooding dynamics can be challenging, especially over geographically broad areas or at spatial and temporal scales relevant for ecosystem management activities. Here, we empirically evaluated a low-complexity geospatial model of floodplain inundation in six study segments of the Upper Mississippi River System (UMRS) by pairing spatially extensive, temporally limited and spatially limited, temporally extensive sampling designs. We found little evidence of systematic bias in model performance although discrepancies between model predictions and empirical data did occur locally. Assessments of model predictions revealed low segment-wide discrepancies of wetted extent under contrasting flow conditions and agreement for inundation event detection and duration. Model performance for predicting event frequency and duration was similar among sites expected to exhibit contrasting patterns of hydrologic connectivity with the main channel. Our results suggest that low-complexity models can efficiently characterize a critical physical process across geographically broad, complex river-floodplain ecosystems. Such tools have the potential for advancing scientific understanding of landscape-scale ecological patterns and for prioritizing management actions in large, complex river-floodplain ecosystems like the UMRS.

The shallow, Memphis, and Fort Pillow aquifers are the three major water-bearing strata beneath Memphis, Tennessee, where the Memphis aquifer serves as the primary groundwater source. The upper Claiborne confining unit (UCCU) separates shallow and Memphis aquifers across the majority of Shelby County, acting as an upper protective layer for the Memphis aquifer. However, hydrogeologic breaches within the UCCU create a hydraulic connection and provide an avenue for potential contaminant migration from the shallow to the Memphis aquifer. This research aims to minimize contaminant migration, mitigate risks, extend existing wells' life that may face water contamination, and find suitable locations for future well construction. Several strategies are developed addressing well depth, seasonal well operation, and mapping no-drilling or red zones to provide practical solutions. A numerical groundwater modeling technique is developed for each strategy that includes stochastic simulation–optimization and customized simulation models depending on the strategy. The models result in thousands of numerical simulations for each scenario to identify recurring patterns of contaminant movement to and through the Memphis aquifer. The results indicate that optimum well positions (spatially and vertically) and modification to pumping can increase the life expectancy of wellfields, offer sustainable management of the Memphis aquifer, and reduce contaminant migration through 2050.

The open data movement represents a major advancement for informed water management. Data that are findable, accessible, interoperable, and reusable—or FAIR—are now prerequisite to responsible data stewardship. In contrast to FAIR, accessibility and usability case studies and guidelines designed around human access and understanding are lacking in the literature, especially for water resources. Such decision support guidelines are critical because (i) inherent visual design trade-offs are not best made using intuition or feedback (perceived preference), and (ii) choosing designs requires a nuanced understanding of why and how the design works (revealed effectiveness). Thus, the goal of this commentary is to highlight knowledge gaps and discuss a general usability testing method which can be applied to any water resources decision support product. The user-testing approach includes (i) interviews about visualization goals, audiences, and the uses and decisions made with the data products, (ii) diagnosis of usability challenges, and (iii) redesign of decision support products given best practices and control versus treatment with intended end-user audiences. We illustrate the method using high-profile U.S. Geological Survey water science products. In sum, optimizing and testing for usability and understandability are as central to stakeholder use as FAIR standards are, and warrant being part of the development of data products and geovisualizations.

The Chesapeake Bay Land Change Model (CBLCM) is an open-source pseudo-cellular automata land change model tailored for loose coupling with watershed models. The CBLCM simulates infill development, residential and commercial development, natural land and agricultural land conversion, and growth served by sewer or septic wastewater treatment. The CBLCM is unique among land change models by simulating multiple types of development and explicitly accounting for infill development and the spatial patterns of development densities. The CBLCM was used to simulate five future land use scenarios, holding population constant, for all counties within and adjacent to the Chesapeake Bay watershed from 2013 to 2055. Results are presented here for the state of Maryland over the period 2013–2025 to illustrate model functionality and validation. The growth management (GM) scenario achieved the least development and potential impacts to natural and agricultural lands while accommodating the same amount of population growth as the other four scenarios. Scenarios focusing exclusively on natural or agricultural land protection shifted development to unprotected areas resulting in unforeseen water quality consequences. Simultaneously achieving more compact development while protecting the most valued natural and agricultural lands requires a combination of GM and land conservation policies and actions.