A GEOGRAPHIC INFORMATION SYSTEM TO PREDICT NON‐POINT SOURCE POLLUTION POTENTIAL¹

Abstract

Bacterial densities (total coliform, fecal coliform, and fecal streptococci) and suspended solids in runoff from a feedlot, pasture, and corn field were measured. Densities of fecal coliform were highest from the feedlot but were 1000 to 10,000 times greater than the water quality standard for swimmable waters from all three land uses. Densities of fecal streptococci were highest from the corn field, which suggests that wildlife are the source of bacteria. Fecal coliform/fecal streptococci ratios distinguished cattle from wildlife as the source of bacterial pollution both among land uses and among seasons of the year. Suspended solids concentrations in runoff ranged from 423 to 925 mg/l and were highest from the corn field. A Geographic Information System (GIS), which utilizes a raster or grid‐cell format, was developed to include algorithms associated with non‐point source pollution. The system accepts digitally mapped information on soil type, topography, and land use. It calculates characteristics such as slope and slope length, and relates these characteristics to soils and land use parameters in order to produce three dimensional maps of runoff potential, sediment pollution potential, and bacterial pollution potential. It offers the advantages of retaining the geographic character of pollution potential information and of conveying in three‐dimensional graphical terms the effects of topography, soil type, land use, and land management practices.

A comparative study on nitrogen-concentration dynamics in surface water in a heterogeneous landscape

“…It is of scientific significance to control nonpoint-source pollution, nutrient loss, and material transport, which may be achieved by studying the effect of landscape patterns on the origination and detention of nonpoint-source pollutants to seek a landscape ecosystem suitable for pollutant retention. Since the source and process of nonpoint-source pollution are unclear (Nikolaidis and others 1998), geographic information system (GIS) and mathematical models have proved to be useful tools to simulate the effect of landscape pattern and land management on nonpoint-source pollution, or nutrient loss and transport (Gilliland 1987;Leonard and others 1987;Young and others 1989;Heng and others 1998;Mankin and others 1999;Yan and Kahawita 2000;Leon and others 2001). In this study, water sampling in the field with GIS is used to focus the objectives on the seasonal characteristics of nonpoint-source pollution (particularly the nitrogen concentration in surface water) within heterogeneous landscapes at four typical watersheds, and the effects of watershed shape and landscape pattern on nitrogen concentration in surface water.…”

GIS Applications of Deterministic Solute Transport Models for Regional-Scale Assessment of Non-Point Source Pollutants in the Vadose Zone

“…Poiani and Bedford (1995) recently presented a cursory review of GE-based NPS pollution models emphasizing surface applications. Numerous hydrologic-water quality models of runoff and soil erosion have been used with a GIS to determine surface sources of NPS pollutants from watersheds (Pelletier, 1985;Potter et al, 1986;Oslin et al, 1988;Sivertun et al, 1988;DeRoo et al, 1989DeRoo et al, , 1992Rudra et al, 1991;Bhaskar et al, 1992;Drayton et al, 1992;Joao & Walsh, 1992;Tim et al, 1992;Walker et al, 1992;Wolfe, 1992;He et al, 1993;Heidtke & Auer, 1993;Levine et al, 1993;Mitchell et al, 1993;Warwick & Haness, 1994) agricultural areas (Hopkins & Clausen, 1985;Gilliland & Baxter-Potter, 1987;Hession & Shanholtz, 1988Panuska & Moore, 1991;Hamlett et al, 1992;Lee & White, 1992;Geleta et al, 1994;Tim & Jolly, 1994) and urban areas (Smith & Brilly, 1992;Smith, 1993;Ventura & Kim, 1993). In addition, several groundwater models have been coupled to a GIS to simulate water flow and/or NPS pol-lutants in aquifers (Kernodle & Philip, 1989;Baker & Panciera, 1990;Hinaman, 1993;Roaza et al, 1993;El-Kadi et al, 1994;Darling & Hubbard, 1994).…”

An erosion-based land classification system for military installations

“…The components of the USLE are geographic in nature, thus lending themselves to manipulation by cooaputerized geographic information systems (GIS). Integrations of the USLE with GIS have been accomplished for agricultural lands (Gilliland andBaxterPotter 1987, Spanner andothers 1982 Wischmeier (1976), Campbell (1987, and Walsh and others (1987), respectively.…”