Abstract:A passive method for remote sensing of the nuisance green algae Cladophora glomerata in rivers is presented using an unmanned aerial vehicle (UAV). Included are methods for UAV operation, lens distortion correction, image georeferencing, and spectral analysis to support algal cover mapping. Eighteen aerial photography missions were conducted over the summer of 2013 using an off-the-shelf UAV and three-band, wide-angle, red, green, and blue (RGB) digital camera sensor. Images were post-processed, mosaicked, and georeferenced so automated classification and mapping could be completed. An adaptive cosine estimator (ACE) and spectral angle mapper (SAM) algorithm were used to complete the algal identification. Digital analysis of optical imagery correctly identified filamentous algae and background coverage 90% and 92% of the time, and tau coefficients were 0.82 and 0.84 for ACE and SAM, respectively. Thereafter, algal cover was characterized for a one-kilometer channel segment during each of the 18 UAV flights. Percent cover ranged from <5% to >50%, and increased immediately after vernal freshet, peaked in midsummer, and declined in the fall. Results indicate that optical remote sensing with UAV holds promise for completing spatially precise, and multi-temporal measurements of algae or submerged aquatic vegetation in shallow rivers with low turbidity and good optical transmission.

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An initial inquiry into model-based numeric nitrogen and phosphorus (nutrient) criteria for large rivers is presented. Field data collection and associated modeling were conducted on a segment of the lower Yellowstone River in the northwestern United States to assess the feasibility of deriving numeric nutrient criteria using mechanistic water-quality models. The steady-state one-dimensional model QUAL2K and a transect-based companion model AT2K were calibrated and confirmed against low-flow conditions at a time when river loadings, water column chemistry, and diurnal indicators were approximately steady state. Predictive simulation was then implemented via nutrient perturbation to evaluate the steady-state and diurnal response of the river to incremental nutrient additions. In this first part of a two-part series, we detail our modeling approach, model selection, calibration and confirmation, sensitivity analysis, model outcomes, and associated uncertainty. In the second part (Suplee et al., 2015) we describe the criteria development process using the tools described herein. Both articles provide a fundamental understanding of the process required to develop site-specific numeric nutrient criteria using models in applied regulatory settings.(KEY TERMS: nutrient criteria; model; large river; eutrophication; QUAL2K; AT2K; Monte Carlo; water quality; regulation; Yellowstone River.) Flynn, Kyle F., Michael W. Suplee, Steven C. Chapra, and Hua Tao, 2015. Model-Based Nitrogen and Phosphorus (Nutrient) Criteria for Large Temperate Rivers: 1. Model Development and Application.

Onsite wastewater systems (OWSs) are a significant source of nonpoint-source pollution to surface and groundwater in both rural and suburban settings. Methods to quantify their effect are therefore important. The mechanics of OWS biogeochemical processes are well studied. However, tools for their assessment, especially at the watershed scale, are limited. As part of this work, modeling capabilities were developed within the Soil Water Assessment Tool (SWAT) such that OWSs and their subsequent environmental impacts can be evaluated A case study was initiated on the Hoods Creek watershed in North Carolina to test the new SWAT algorithms. Included were: (1) field-scale simulations of groundwater quantity (water table height) and quality (N, P), (2) Monte Carlo evaluations of OWS service life to evaluate suggested calibration parameters, and (3) assessments of watershed-scale pollutant loadings within the model. Results were then analyzed at both the field and watershed scales. The model performed well in predicting both site groundwater table levels (R 2 = 0.82 and PBIAS = -0.8%) and NO 3 -N concentration in the groundwater (R 2 = 0.76, PBIAS = 2.5%). However, the performance for PO 4 -P simulations was less reliable due to difficulty in representing the mobility of soluble P in the soil. An advanced P algorithm is recommended to address the sophisticated physiochemical properties of soil particles and improve the model's performance.n rural areas, it is often inefficient to operate centralized wastewater systems for the purpose of domestic sewage treatment due to the sparse residential densities, uneven terrain, and/or limited water or energy supplies. In such instances, decentralized types of wastewater treatment systems (i.e., onsite wastewater systems) are typically used. In fact, more than 25% of existing homes and 37% of new developments in the U.S. use onsite wastewater systems (OWSs) for wastewater disposal (USEPA, 1997). The U.S. Census Bureau (1999) estimates that more than 60 million people depend on decentralized systems for their treatment needs. Hence, understanding the biophysical processes within OWSs, and the environmental impacts thereof, is of great importance to scientists, watershed managers, and regulatory agencies.