Search

Harmful algal blooms (HABs) diminish the utility of reservoirs for drinking water supply, irrigation, recreation, and ecosystem service provision. HABs decrease water quality and are a significant health concern in surface water bodies. Near real‐time monitoring of HABs in reservoirs and small water bodies is essential to understand the dynamics of turbidity and HAB formation. This study uses satellite imagery to remotely sense chlorophyll‐a concentrations (chl‐a), phycocyanin concentrations, and turbidity in two reservoirs, the Grand Lake O′ the Cherokees and Hudson Reservoir, OK, USA, to develop a tool for near real‐time monitoring of HABs. Landsat‐8 and Sentinel‐2 imagery from 2013 to 2017 and from 2015 to 2020 were used to train and test three different models that include multiple regression, support vector regression (SVR), and random forest regression (RFR). Performance was assessed by comparing the three models to estimate chl‐a, phycocyanin, and turbidity. The results showed that RFR achieved the best performance, with R2 values of 0.75, 0.82, and 0.79 for chl‐a, turbidity, and phycocyanin, while multiple regression had R2 values of 0.29, 0.51, and 0.46 and SVR had R2 values of 0.58, 0.62, and 0.61 on the testing datasets, respectively. This paper examines the potential of the developed open‐source satellite remote sensing tool for monitoring reservoirs in Oklahoma to assess spatial and temporal variations in surface water quality. [ABSTRACT FROM AUTHOR]

In this paper, we use remotely sensed imagery to identify the location and size of animal feeding operations in the Maumee River Watershed, a key drainage area to Lake Erie's Western Basin, which has recently experienced severe harmful algal blooms. We then estimate the relationship between the intensity of animal feeding operations in the watershed and surface water body concentrations of dissolved reactive phosphorus (DRP), the pollutant most responsible for algal growth. We find that stream reaches with relatively larger increases in upstream animal feeding exposure experience significantly higher increases in concentrations of DRP. The average marginal upstream animal feeding operation in the watershed increases downstream DRP concentrations by between 10% and 15%. In contrast, when restricting the analysis to include only permitted operations, coefficient estimates are practically zero and statistically insignificant. Our work presents evidence that the increasing intensity of animal feeding operations contributes to water quality problems. Permitting and identification of animal feeding operations is therefore important for managing runoff and correctly attributing the causes of excess nutrients in surface water bodies. [ABSTRACT FROM AUTHOR]

Eutrophication, harmful algal blooms, and human health impacts are critical environmental challenges resulting from excess nitrogen and phosphorus in surface waters. Yet we have limited information regarding how wetland characteristics mediate water quality across watershed scales. We developed a large, novel set of spatial variables characterizing hydrological flowpaths from wetlands to streams, that is, "wetland hydrological transport variables," to explore how wetlands statistically explain the variability in total nitrogen (TN) and total phosphorus (TP) concentrations across the Upper Mississippi River Basin (UMRB) in the United States. We found that wetland flowpath variables improved landscape‐to‐aquatic nutrient multilinear regression models (from R2 = 0.89 to 0.91 for TN; R2 = 0.53 to 0.84 for TP) and provided insights into potential processes governing how wetlands influence watershed‐scale TN and TP concentrations. Specifically, flowpath variables describing flow‐attenuating environments, for example, subsurface transport compared to overland flowpaths, were related to lower TN and TP concentrations. Frequent hydrological connections from wetlands to streams were also linked to low TP concentrations, which likely suggests a nutrient source limitation in some areas of the UMRB. Consideration of wetland flowpaths could inform management and conservation activities designed to reduce nutrient export to downstream waters. [ABSTRACT FROM AUTHOR]

In this study, we demonstrate a physically based semi‐Lagrangian water temperature model known as the River Basin Model (RBM) coupled with the Variable Infiltration Capacity (VIC) hydrological model and Weather Research & Forecasting Model in the Mississippi River Basin (MRB). The results of this coupling compare favorably with observed water temperature data available from six river gages located in the MRB. Further sensitivity analysis indicates that the mean water temperatures may increase by 1.3, 1.5, and 1.8°C in northern, central, and southern MRB zones under a hypothetical uniform air temperature increase of 3.0°C. If air temperatures increase uniformly by 6.0°C in this scenario, then water temperatures are projected to increase by 3.3, 3.5, and 4.0°C. Lastly, downscaled air temperatures from a global climate model are used to drive the coupled VIC and RBM model from 2020 to 2099. Average stream temperatures from 2020 to 2099 increase by 1.0 to 8.0°C above 1950 to 2010 average water temperatures, with non‐uniform increases along the river. In some portions of the MRB, stream temperatures could increase above survival thresholds for several native fish species, which are critical components of the stream ecosystem. In addition, increased water temperatures interact with nutrient loadings from sources throughout the MRB, which is expected to exacerbate harmful algal blooms and dead zones in the Gulf of Mexico. [ABSTRACT FROM AUTHOR]