Water Resources Research Act Program

Details for Project ID 2004NY48B

Regional water quality tools for identifying high runoff risk areas in watersheds.

Institute: New York
Year Established: 2004 Start Date: 2004-03-01 End Date: 2006-02-28
Total Federal Funds: $45,360 Total Non-Federal Funds: $60,914

Principal Investigators: Todd Walter, Michael Walter

Abstract: Nonpoint source (NPS) pollution from agricultural land continues to be an acute regional problem. Phosphorus (P) from agriculture is especially ubiquitous and is a primary cause of the degradation of lakes and streams by eutrophication and related problems. Although implementing nutrient management plans has the potential to meaningfully address this problem by reducing nutrient inputs into watersheds, the pollutant transport components of most water quality management strategies continue to lag several decades behind current scientific understanding of the relevant hydrological and transport processes. P management strategies continue to focus on particulate P despite increasing evidence of the importance of dissolved P, and particulate P control is based on soil conservation practices developed primarily in the 1930s-1950s. These practices are not universally effective for protecting water quality, especially for dissolved pollutants. The overall goal is to develop and evaluate new GIS-based computational tools for identifying areas in the Northeastern US landscapes that are especially prone to generating runoff, i.e. hydrologically sensitive areas (HSA). The specific objectives are to: 1) develop a single HSA tool that can be applied over the entire Northeastern US by considering geographic precipitation differences and local watershed topography and soil characteristics; 2) investigate the reliability of a very simple HSA indicator that considers "stream proximity" and local land slope that can serve as an easy in-field HSA identification tool; and 3) determine the duration that temporal units must be to capture intra-annual changes in hydrological sensitivity. Four tasks will be carried out: 1) model six to twelve well defined watersheds to determine monthly probabilities of generating runoff for all points throught each watershed; 2) overlay "proxy parameters" on maps of runoff probability developed from the model and evaluate the statistical agreement between the model predicted runoff probability and the "proxy parameters;" 3) evaluate how similar relationships determine how regionally consistent proposed tools perform; and 4) determine which months are statistically different from each other in order to ascertain whether monthly, seasonal, or some other distribution of hydrological sensitivity is warranted.