This paper presents a framework for analyzing the economic, health, and recreation implications of swim closures related to high fecal indicator bacteria (FIB) levels. The framework utilizes benefit transfer policy analysis to provide a practical procedure for estimating the effectiveness of recreational water quality policies. Evaluation criteria include the rates of intended and unintended management outcomes, whether the chosen protocols generate closures with positive net economic benefits to swimmers, and the number of predicted illnesses the policy is able to prevent. We demonstrate the framework through a case study of a Lake Michigan freshwater beach using existing water quality and visitor data from 1998 to 2001. We find that a typical closure causes a net economic loss among would-be swimmers totaling $1274-37 030/ day, depending on the value assumptions used. Unnecessary closures, caused by high indicator variability and a 24-h time delay between when samples are taken and the management decision can be made, occurred on 14 (12%) out of 118 monitored summer days. Days with high FIB levels when the swim area is open are also common but do relatively little economic harm in comparison. Also, even if the closure policy could be implemented daily and perfectly without error, only about 42% of predicted illnesses would be avoided. These conclusions were sensitive to the relative values and risk preferences that swimmers have for recreation access and avoiding health effects, suggesting a need for further study of the impacts of recreational water quality policies on individuals.

No abstract

We estimate the impacts of drought, as defined by the U.S. Drought Monitor (USDM), on crop yields and farm income in the United States during the 2001–2013 time period. Our empirical strategy relies on panel data models with fixed effects that exploit spatial and temporal variability in drought conditions and agricultural outcomes at the county level. We find negative and statistically significant effects of drought on crop yields equal to reductions in the range of 0.1% to 1.2% for corn and soybean yields for each additional week of drought in dryland counties, and 0.1% to 0.5% in irrigated counties. Region‐specific results vary, with some regions experiencing no yield impacts from drought, while yield reductions as high as 8.0% are observed in dryland counties in the Midwest for every additional week of drought in the highest USDM severity category. Despite this impact on crop yields, we find that additional weeks of drought have little to no effect on measures of farm income. While precipitation and temperature explain most of the variability in crop yields, we find that the USDM captures additional negative impacts of drought on yields.

There are important challenges associated with assessing potential groundwater vulnerability hazards that may result from regional scale applications of agrochemicals. The increasing availability of Geographic Information System (GIS) software to those involved in assisting with landuse decisions has resulted in the widespread production of multicolored risk management maps for many environmentally sensitive issues. Soil‐based GIS's have recently been coupled to various solute‐leaching models to make near‐surface groundwater vulnerability assessments for guidance in pesticide regulation in several states. In general, these assessments rest on soil, climatic, and chemical data that are extremely sparse and contain considerable uncertainty. It is also important to acknowledge the uncertainty associated with the transport/fate processes that are not accounted for by the modeling approach used to make the assessment. In this paper, we review the results from a series of papers that have focused on characterization of uncertainty in pesticide mobility estimates, using the attenuation and retardation indices (AF and RF), for the Pearl Harbor Basin on the Hawaiian island of Oahu. Relative to data error uncertainties, we discuss the impacts of: (i) soil, climatic, and chemical data base uncertainties, (ii) reductions in data base uncertainties, (iii) extrapolation of soil data base information based on soil taxonomy and soil survey, and (iv) importing information from outside the region of interest. Relative to model error uncertainties, we compare pesticide leaching estimates from the simple AF and RF mobility indices with simulations from the EPA's Pesticide Root Zone Model (PRZM) and field observations. Finally, we outline a Regional Integrated Risk Assessment approach for characterizing regional scale groundwater vulnerability for near‐surface nonpoint sources.“Hey farmer farmer put away that DDT” Joni Mitchell, “Big Yellow Taxi”

No abstract