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Describing the distribution of aquatic habitats and the health of biological communities can be costly and time-consuming; therefore, simple, inexpensive methods to scale observations of aquatic biota to watersheds that lack data would be useful. In this study, we explored the potential of a simple "hydrogeomorphic" model to predict the effects of acid deposition on macroinvertebrate, fish, and diatom communities in 28 sub-watersheds of the 176-km2 Neversink River basin in the Catskill Mountains of New York State. The empirical model was originally developed to predict stream-water acid neutralizing capacity (ANC) using the watershed slope and drainage density. Because ANC is known to be strongly related to aquatic biological communities in the Neversink, we speculated that the model might correlate well with biotic indicators of ANC response. The hydrogeomorphic model was strongly correlated to several measures of macroinvertebrate and fish community richness and density, but less strongly correlated to diatom acid tolerance. The model was also strongly correlated to biological communities in 18 sub-watersheds independent of the model development, with the linear correlation capturing the strongly acidic nature of small upland watersheds (< 1 km2). Overall, we demonstrated the applicability of geospatial data sets and a simple hydrogeomorphic model for estimating aquatic biological communities in areas with stream-water acidification, allowing estimates where no direct field observations are available. Similar modeling approaches have the potential to complement or refine expensive and time-consuming measurements of aquatic biota populations and to aid in regional assessments of aquatic health.

In phosphorus-limited freshwater systems, small increases in phosphorus (P) concentrations can lead to eutrophication. To reduce P inputs to these systems, various environmental and agricultural agencies provide producers with incentives to implement best management practices (BMPs). In this study, we examine both the water quality and economic consequences of systematically protecting saturated, runoff-generating areas from active agriculture with selected BMPs. We also examine the joint water quality/economic impacts of these BMPs-specifically BMPs focusing on barnyards and buffer areas. Using the Variable Source Loading Function model (a modified Generalized Watershed Loading Function model) and net present value analysis (NPV), the results indicate that converting runoff-prone agricultural land to buffers and installing barnyard BMPs are both highly effective in decreasing dissolved P loss from a single-farm watershed, but are also costly for the producer. On average, including barnyard BMPs decreases the nutrient loading by about 5.5% compared with only implementing buffers. The annualized NPV for installing both buffers on only the wettest areas of the landscape and implementing barnyard BMPs becomes positive only if the BMPs lifetime exceeds 15 yr. The spatial location of the BMPs in relation to runoff producing areas, the time frame over which the BMPs are implemented, and the marginal costs of increasing buffer size were found to be the most critical considerations for water quality and profitability. The framework presented here incorporates estimations of nutrient loading reductions in the economic analysis, and is applicable to farms facing BMP adoption decisions., (Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.)

Agriculture often is considered to be a contributor of soluble reactive phosphorus (SRP) and nitrate-N (NO3- -N) to surface waters. This research analyzed SRP and NO3- -N concentrations in groundwater and in a creek fed by groundwater on a valley dairy farm in the Cannonsville basin of the New York City (NYC) watershed. A total of 37 groundwater piezometers were installed to depths of 0.3 to 1.5 m. Water-table depth and concentrations of SRP, NO3- -N, dissolved organic carbon (DOC), and dissolved oxygen were measured at regular intervals over a three-year period. A multivariate mixed model analysis of variance indicated that the SRP and NO3- -N concentrations were controlled primarily by three classes of variables: environmental variables, including precipitation and water table depth; source variables, including manure applied and crop type; and chemical variables, including DOC and dissolved oxygen concentrations in groundwater. The highest groundwater concentrations of N03- -N and SRP were found at the shallowest water-table depths, which has implications for agricultural nutrient management in areas with shallow groundwater.

Researchers have noted that current water quality protection strategies, like nutrient management plans, lack a sound hydrological underpinning for pollutant transport processes. This is especially true for areas like the northeastern U.S. where copious research has shown that variable source area hydrology largely governs runoff generation. The goal of this study was to develop a scientifically justified method to identify the locations that generate overland flow. Furthermore, this methodology must be computationally simple enough that it can be utilized or incorporated into nutrient management plans and other established water quality tools. We specifically tested the reliability of the 'distance from a stream,'D(s), and the 'topographic index,'lambda, to predict areas with a high propensity for generating overland flow, i.e. hydrologically sensitive areas (HSA). HSAs were defined by their probability of generating runoff, P(sat), based on 30 year simulations using a physically based hydrological model. Using GIS, each location's P(sat) was correlated with D(s) and lambda. We used three Delaware Co., NY watersheds in the New York City watershed system with areas varying in size from 1.6 to 37 km2 and with forested and agricultural land uses. The topographic index gave stronger, more regionally consistent correlations with P(sat) than did D(s). Equations correlating lambda and P(sat) for each month are presented and can be used to estimate hydrological sensitivity in the region surrounding our study watersheds, i.e. in Delaware Co. This work is currently being incorporated into an Internet Mapping System to facilitate user-friendly, on-line identification of HSAs.