River Basin Export Reduction Optimization Support Tool; a tool to screen options for reducing nutrient loads while minimizing cost.

Excess loading of nitrogen and phosphorus to river networks causes environmental harm, but reducing loads from large river basins is difficult and expensive. We develop a new tool, the River Basin Export Reduction Optimization Support Tool (RBEROST) to identify least-cost combinations of management practices that will reduce nutrient loading to target levels in downstream and mid-network waterbodies. We demonstrate the utility of the tool in a case study in the Upper Connecticut River basin in New England, USA. The total project cost of optimized lowest-cost plans ranged from $18.0 million to $41.0 million per year over 15 years depending on user specifications. Plans include both point source and non-point source management practices, and most costs are associated with urban stormwater practices. Adding a 2% margin of safety to loading targets improved estimated probability of success from 37.5% to 99%. The large spatial scale of RBEROST, and the consideration of both point and non-point source contributions of nutrients, makes it well suited as an initial screening tool in watershed planning.

Temporal and spatial variability in water quality of wetlands in the Minneapolis/St. Paul, MN metropolitan area: Implications for monitoring strategies and designs.

Temporal and spatial variability in wetland water-quality variables were examined for twenty-one wetlands in the Minneapolis/St. Paul metropolitan area and eighteen wetlands in adjacent Wright County. Wetland water quality was significantly affected by contact with the sediment (surface water vs. groundwater), season, degree of hydrologic isolation, wetland class, and predominant land-use in the surrounding watershed (p<0.05). Between years, only nitrate and particulate nitrogen concentrations varied significantly in Wright County wetland surface waters. For eight water-quality variables, the power of a paired before-and-after comparison design was greater than the power of a completely randomized design. The reverse was true for four other water-quality variables. The power of statistical tests for different classes of water-quality variables could be ranked according to the predominant factors influencing these: climate factors>edaphic factors>detritivory>land-use factors>biotic-redox or other multiple factors.For two wetlands sampled intensively, soluble reactive phosphate and total dissolved phosphorus were the most spatially variable (c.v.=76-249%), while temperature, color, dissolved organic carbon, and DO were least variable (c.v.=6-43%). Geostatistical analyses demonstrated that the average distance across which water-quality variables were spatially correlated (variogram range) was 61-112% of the mean radius of each wetland. Within the shallower of the two wetlands, nitrogen speciation was explained as a function of dissolved oxygen, while deeper marsh water-quality variables were explained as a function of water depth or distance from the wetland edge. Compositing water-quality samples produced unbiased estimates of individual sample means for all water quality variables examined except for ammonium.