Journal of The American Water Resources Association最新文献

Monitoring vegetation response to valley-scale floodplain restoration to evaluate effectiveness can be costly and time-consuming. We used publicly available National Agriculture Imagery Program (NAIP) data and commonly used ArcGIS software to assess land cover change over time at five study sites located in semi-arid environments of eastern Oregon and north-central California. Accuracy assessments of our unsupervised classifications were used to evaluate effectiveness. Overall accuracy across sites and years ranged from 64.2% to 89.2% with mean and median accuracy of 79.1% and 80.6%, respectively. Further, we compared our classifications with high-resolution uncrewed aerial systems (UAS)-based data collected in the same timeframe. Restored areas classified as dense vegetation were within 4% of the UAS study, water was within 6%, and post-restoration classifications of sparse vegetation and bare ground classes were within 6% and 4% of the UAS study, respectively. This comparison demonstrates that our unsupervised NAIP data classification of land cover change across entire valley-scale restoration projects can be used to monitor riparian vegetation change over time as accurately as UAS-based methods, but at lower cost. Additionally, our methods leverage existing fine-resolution, pre-restoration vegetation density data that were not collected as part of project planning.

This study investigates whether improvements could be achieved for the United States National Water Model (NWM) by using a data-driven reservoir operation simulation algorithm, that is, the generic data-driven reservoir operation model (GDROM), to replace the existing reservoir representation in NWM for reservoir routing in streamflow simulation. The evaluations of NWM versus NWM + GDROM are conducted using 41-year NWM retrospective simulation products during 1979 to 2020. The results show that NWM + GDROM exhibits significant improvement to NWM in both the entire Contiguous U.S. (CONUS) and various regions. It is found that the accuracy of reservoir inflow and storage values affects the NWM + GDROM improvement. When driven by observed storage (which is usually more accurate than modeled storage) or more accurately simulated inflow, NWM + GDROM produces more significant improvements in reservoir outflow simulations in all the study CONUS regions. Especially, since high flows are more accurately simulated by NWM than low flows, NWM + GDROM has larger improvement for the simulation of high flows than low flows.

This study proposes a comprehensive water quality assessment method for nine major plateau lakes in Yunnan Province, based on an improved CRITIC method combined with a multidimensional connectivity cloud model. Key water quality monitoring indicators (NH3-N, COD, TP, TN, permanganate index, DO, pH) were selected, and the weights were determined using the improved CRITIC method, highlighting the impact of NH3-N, COD, and TP. These weights were then integrated with a multidimensional connectivity cloud model to classify lake water quality levels. The results indicated the following water quality grades for the lakes: Dianchi (III), Fuxian Lake (I), Erhai (II), Xingyun Lake (I), Qilu Lake (II), Yilong Lake (II), Lugu Lake (I), Yangzonghai (II), and Chenghai (II). Compared to five conventional methods, the proposed approach better addresses the issues of fuzziness, randomness, and discreteness in water quality indicators, avoiding the boundary selection problems inherent in traditional methods. By combining the improved CRITIC method with a multidimensional connectivity cloud model, the study achieves more precise and reliable evaluations through objective weighting and comprehensive consideration of multiple indicators. This method offers a more accurate reflection of lake water quality conditions and provides a scientific basis for water quality management and decision-making, demonstrating significant potential for application in the field of environmental science.

Excess nutrient loads from streams drive primary production in downstream lakes, and managing these loads is key to achieving desired conditions in lakes. However, quantifying nutrient loads requires intensive sampling of both nutrient concentrations and streamflow. Total phosphorus measurements collected during routine stream monitoring are broadly available, but these data are thought to provide little information on annual nutrient loads because they are typically collected during low, baseflow conditions. Here, we demonstrate that these routine phosphorus measurements are correlated with annual nutrient loads. We also show that the average of these routine measurements of stream phosphorus within a watershed predict the average lake chlorophyll concentration in that same watershed. These relationships can then be used to set targets for stream phosphorus concentrations to achieve desired conditions in lakes.

The implement of water resources spatial equilibrium (WRSE) schemes is fundamental task of integrated water resources management in China, in which, the evaluation and simulation analysis of WRSE system is of great concern for understanding the overall variation and feedback characteristics of WRSE system. Therefore, we utilized the ordered degree, entropy and connection number coupling model to evaluate the variation of WRSE system, and also employed system dynamics (SD) and scenario simulation integrated method to reveal the feedback characteristics between different equilibrium variables and subsystems, and thus the set pair analysis-SD based approach for structure simulation and variation trend evaluation of WRSE system was constructed. The application results in Anhui province, China demonstrated that, the overall variation of provincial spatial equilibrium situation of WRSE system presented obvious improving trend, 2009–2019, the index of ordered degree and connection number entropy in Hefei, increased from the minimum of 0.6434 (Grade 3, unequilibrium) to maximum of 0.9985 (Grade 1, equilibrium). Moreover, the future variation of WRSE system will display stable improving trend during 2020 to 2029, in which, annual water resources availability and water resources utilization efficiency will have significant influence on WRSE system. And the research findings can be favorable to formulate water resources development and utilization strategies.

To address impacts of climate change and other stressors on stream ecosystems, managers must prioritize resources and locations for conservation actions to facilitate effective cross-boundary solutions. Through a science management partnership, we co-produced a spatially explicit landscape assessment framework for cold-water fish habitat and riparian corridors in three large watersheds of the southwestern United States. Using literature review and stakeholder workshops, we developed indicators of vulnerability and built spatial datasets depicting areas of low to high vulnerability based on exposure, sensitivity, and adaptive capacity for each resource. We found that, in general, vulnerability was greater for cold-water fish habitat than for riparian corridors. The Little Colorado River and San Juan River watersheds had the highest percentages of subwatersheds with high vulnerability of cold-water fish habitat. Conversely, the Upper Rio Grande watershed had the highest percentage with high vulnerability of riparian corridors. Assessments like ours facilitate the management of water resources at the scale of watersheds or river basins and incorporate physical characteristics, land-use history, current management practices, and status of imperiled species into actionable management plans.

Like many small island communities, the U.S. Virgin Islands (USVI), an unincorporated territory of the U.S., is naturally freshwater scarce. In recent decades, rapid land development in the USVI has increased water demand considerably, exerting extra pressure on freshwater resources. Freshwater quantity and quality data for the USVI are very scarce and scattered, which limits freshwater management capabilities. We draw attention to this information deficit and discuss its implications by reviewing the current state of knowledge of surface and groundwater quantity and quality for the USVI. Our review confirms that long-term records of surface and groundwater quantity and quality are limited and unreliable. For example, streamflow was most recently monitored in 2006, and the most extensive surface water quality records are from the 1960s and 1980s. Since 2016, mean groundwater levels have been recorded daily, but only for three wells (one on each island of the USVI). Importantly, this lack of information threatens water security for the territory and limits our understanding of how development has impacted water quality and availability over time. This could be addressed using models, such as a groundwater recharge model, in combination with remote sensing and updated field data (i.e., streamflow, groundwater, and ecohydrological characterizations of land use change).

High-resolution digital elevation models (HRDEMs), derived from LiDAR, are widely used for mapping hydrographic details in flat terrains. However, artificial flow barriers, particularly from roads, elevate terrain and prematurely end flowlines. Drainage barrier processing (DBP), such as HRDEM excavation, is employed to address this issue. However, there is a gap in quantitatively assessing the impact of DBP on HRDEM-derived flowlines, especially at finer scales. This study fills that gap by quantitatively assessing how DBP improves flowline quality at finer scales. We evaluated HRDEM-derived flowlines that were generated using different flow direction algorithms, developing a framework to measure the effects of flow barrier removal. The results show that the primary factor influencing flowline quality is the presence of flow accumulation artifacts. Quality issues also stem from differences between natural and artificial flow paths, unrealistic flowlines in flat areas, complex canal networks, and ephemeral drainage ways. Notably, the improvement achieved by DBP is demonstrated to be more than 6%, showcasing its efficacy in reducing the impact of flow barriers on hydrologic connectivity.

As water scarcity is worsened by drought and climate change, there is more interest in efficient management of urban irrigation, requiring understanding of the drivers of evapotranspiration (ET) and the role of irrigation inputs. We developed and validated a method to accurately measure ET of turfgrass lawns in contrasting climates using portable static chambers. We made in situ measurements of ET and irrigation inputs in lawns across three metropolitan areas in the United States with varying climatic conditions, water availability, and water conservation policies: Salt Lake Valley, Utah; San Fernando Valley, California; and Tallahassee, Florida. In full sun, mean daily ET estimates (ET_sun) were 0.7 ± 0.4 mm day⁻¹ in Tallahassee, 1.6 ± 0.8 mm day⁻¹ in Los Angeles, and 3.3 ± 1.1 mm day⁻¹ in Salt Lake Valley. In the shade, daily ET estimates (ET_shade) were two to three times lower. In all three regions, ET was primarily driven by solar radiation (I₀) and atmospheric vapor pressure deficit (D). Across the cities, irrigation rates were a key driver of ET, along with I₀ and D. Daily irrigation ranged from 0 mm day⁻¹ in Tallahassee (most were unirrigated) to 1.9 ± 1.2 mm day⁻¹ in Los Angeles and 5.1 ± 2.9 mm day⁻¹ in Salt Lake Valley. ET increased linearly with irrigation up to ~3 mm day⁻¹, after which ET remained relatively constant despite irrigation increases. Our results highlight the importance of accounting for nonlinear responses and shading effects on ET in developing accurate irrigation recommendations.

To attain a thorough examination of the dynamic interaction mechanism between China's utilization of water resources and its economic and social development, this paper innovatively introduces a Western theoretical framework within an Eastern context. The aim is to quantify the process of decoupling and synergistic evolution from 2006 to 2020. Decoupling signifies achieving economic growth while reducing resource use or mitigating environmental impacts, whereas synergy denotes enhancing economic efficiency while contributing to environmental protection. This paper employs the Tapio elastic coefficient method to construct a decoupling model. A collaborative model, based on the entropy weight Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and weighted average methods, also assesses the organization and coordination of subsystems within the complex water-economic-social system. The findings reveal a strong decoupling between China's water resource management and economic and social systems, as indicated by a consistently negative decoupling index. Similarly, the economic system exhibits a degree of inefficiency influenced by factors like economic cyclicality and resource allocation. In contrast, the social system experienced a decline, particularly during the pandemic (2019–2020), leading to a social instability. This study provides valuable policy formulation and sustainable development insights, contributing to a comprehensive understanding of the intricate dynamics between water utilization, economy, and society.