Monica Hubbard

Annotated Bibliography for GEO 565

Winter 2007

Nonpoint Source Pollution and Geographic Information Systems

Waste from Residential and Urban                                               Runoff from construction sites

Runoff from Agriculture                                                                                          Runoff from Mining

OVERVIEW

Unlike pollution from industrial and wastewater treatment plants, nonpoint source pollutants (NPS) comes from many sources, such as residential homes, streets, construction sites, and rural areas. It’s caused when rainfall or snowmelt moving over and through the ground and picks up and carries away natural and human-made pollutants, finally depositing them into lakes, rivers, wetlands, coastal waters, and aquifers. NSP includes: Excess fertilizers, herbicides, and insecticides from residential and agricultural lands; oil, grease, toxic chemicals and waste pharmaceuticals from residents; sediment from construction sites; salt from roads; and others.

Throughout the United States NPS is the leading cause of water quality problems. The effects are visible on drinking water, aquatic species, and wildlife. The following bibliography looks at some studies where Geographic Information Systems (GIS) were used to help mitigate, and or track nonpoint source pollutants.

Obvious point sources of pollution could be found and were controlled. For further increase of water quality, it is also necessary to reduce the non-point source pollution. This is more difficult because these sources are not discrete places but diffuse areas somewhere on the Earth’s surface. Use of Geographic Information Systems can be, and currently are, valuable tools to reduce these pollutants.

BIBLIOGRAPHY

Basnyat, P., L. D. Teeter, et al. (1999). "Relationships Between Landscape Characteristics and Nonpoint Source Pollution Inputs to Coastal Estuaries." Environmental Management 23(4): 539-549.

This study looked at the relationship of nitrate and sediment loads, both nonpoint pollutants, in water from areas of agriculture, and urban and residential. Then it looked to see how the nitrate and sediment loads changed as it came into contact with forests. The location of the study was selected basins Fish River, Alabama. GIS was used to delineate the basins, provide land use and land cover types, and identified contributing zones. From the GIS data a linkage model was created which linked nonpoint pollutants to land use.

 The results of the study found that forests act as a sink for some nonpoint source pollutants, like nitrates and total suspended solids. Residential and urban areas were the strongest contributor of nitrate, and agriculture was the second largest contributor. The authors also found the integration of GIS into the modeling process helped with providing information on vegetation, slope, soil type, watershed boundaries and others that can integrated with other environmental variables for the evaluation of land management. It also helped with the identification of risk areas. The study used 30 meter DEMs and the authors felt that resolution did not provide enough detail, and recommended a further study using 10 meter DEMs.

Benaman, J., C. A. Shoemaker, et al. (2001). Modeling Non-Point Source Pollution Using a Distributed Watershed Model for the Cannonsville Reservoir Basin, Delaware County, New York. World Water and Environmental Resource Congress 2001, World Water Congress.

This paper looked at the possible use of a model in order to deal with nonpoint pollution in the Cannonsville Reservoir, which serves as a major source of drinking water to New York City. At the time of publication, the Reservoir was under a phosphorous loading restriction. The view is the phosphorous is due to agriculture practices in the area.  In order to implement a best management practice the management agencies need a modeling tool for evaluation in addition to anticipate the impacts of future land use changes.   The model to be used is the Soil and Water Assessment Tool (SWAT).  Developed for use on agricultural lands, it integrates a Geographical Information System.

Foster, J. A. and A. T. McDonald (2000). "Assessing pollution risks to water supply intakes using geographical information systems (GIS)." Environmental Modeling and Software 15(3): 225-234.

 This study looked at the use of GIS in the process of pollution risk assessments for drinking water from surface waters in Britain. Nonpoint source pollution risk assessments requires analyzing data that are spatially variable, making geographical information systems (GIS) an ideal tool. This paper described how the researchers used WINGS and MapInfo Profession GISs for the risk assessments. There are four elements of risk assessments: hazard identification; hazard estimation; risk evaluation; and risk management. The GISs were used throughout the four stages. The analysis of spatial data was used to identify what hazards exist and where they were located (hazard identification). The coupling of a GIS to suitable models provided estimates of hazard probability and consequence, and risk management recommendations were tested using the GIS prior to final decisions being implemented. To assess the significance of hazards, a Runoff Potential Index was calculated in GIS to identify those hazards. Two examples include the identification of the pathogen Cryptosporidium parvum and road traffic accidents that can impact water supplies. The major problem experienced in the project was acquiring digital data, of which came in large variations of spatial resolution.

He, C. (2003). "Integration of geographic information systems and simulation model for watershed management." Environmental Modeling & Software 18(8-9): 809-813.

The researcher in this study, Chansheng He, integrated GIS with the Agriculture Nonpoint Source (AGNPS) pollution model to analyze the impact of land use change on nonpoint pollution in a watershed. The new model was called ArcView nonpoint source pollution modeling (AVNPSM). The location of the study was the Dowagiac River, a major tributary of the St Joseph River in southwestern Michigan that flows into Lake Michigan.

The results of the study found that urban expansion will lead to increases in surface runoff, peak flow, and soil erosion. Urbanization closer to water will magnify these events. The researcher found with the interface of AGNPS and ArcView land use change scenarios are easily explored and will help resource managers make decisions and plan to mitigate the impacts of land use on the waterways.

Kelsey, H., D. E. Porter, et al. (2004). "Using geographic information systems and regression analysis to evaluate relationships between land use and fecal coliform bacterial pollution." Journal of Experimental Marine Biology and Ecology 298(2): 197-209

This study took place at Murrells Inlet, a small, urbanized, estuary located between Myrtle Beach and Georgetown, SC. Geographic Information Systems (GIS) were used in conjunction with regression modeling techniques to identify specific land use characteristics that may contribute to nonpoint source fecal coliform bacterial pollution in order to develop a targeted water quality management plan.

Using GIS to examine land use impacts on coliform densities, several “distance or proximity” land use variables were considered to have a potential impact on water quality. These included relating distance from the sampling locations to land-use characteristics such as population density, housing unit density, total population, area of developed and undeveloped land, number of septic tanks, sewage system lift stations, roads, boating intensity, boat landings and marinas.

The findings of the study indicate the major source of fecal pollution in Murrells Inlet appears to be stormwater runoff, especially from areas with urban land-use characteristics, and with septic tanks.   The water quality management implications of this research include identification of strategies to reduce or intercept urban stormwater runoff, and reduction of septic tanks.  

Lasserre, F., M. Razack, et al. (1999). "A GIS-linked model for the assessment of nitrate contamination in groundwater." Journal of Hydrology 224(3-4): 81-90.

The objective of the study was to develop a modeling approach that could assess nitrate pollution, easy to apply and require minimal input information. The increase of nitrate pollution in groundwater has led to the abandonment of numerous wells in agricultural zones. Because of the complexity of the processes and the costs, a GIS-based evaluation tool was developed by coupling an existing root-zone model with a GIS-integrated transport model.

 The study found the GIS transport model combination was successful in assessing nonpoint nitrate contamination in groundwater, and allowed for fast and user-friendly computation of nitrate distribution in aquifers. However, the approach did not incorporate processes such as preferential flow, by-pass flow, hydrodynamic dispersion or adsorption-desorption reactions. The model can be easily applied to local groundwater systems where the required parameters are generally measured near a pumping station. It is particularly well-suited for shallow groundwaters which are often highly vulnerable to agricultural nitrate pollution.

León, L. F., E. D. Soulis, et al. (2001). "Nonpoint source pollution: a distributed water quality modeling approach." Water Research 35(4): 997-1007.

This study looked at distributed water quality models for nonpoint source pollution (NPS) modeling in agricultural watersheds. It took existing nonpoint pollution modeling approaches and built in GIS. The study was conducted on Duffins Creek, a 293 km2 watershed that drains into Lake Ontario at Ajax, east of Toronto, Ontario, Canada. The land cover in the watershed is mainly agricultural with growing urban areas in the southern parts at Pickering and Ajax.

A water quality component was developed for WATFLOOD (a flood forecast hydrological model) to deal with sediment and nutrient transport. WATFLOOD uses a distributed group response unit approach for water quantity and quality modeling. Runoff, sediment yield and soluble nutrient concentrations were calculated separately for each land cover class. The data extracted from GIS was used to calibrate the hydrologic response and validate the water quality component of WATFLOOD. GIS graphical interfaces were built to allow interaction with the model and estimate the input data based on digital maps. The advantage of the GIS approach was the automatic extraction of the cell data for the variables that depend on topography, soil type and land cover. Essentially, three sources of information, Digital Elevation Model, soil and land use data were required to take full advantage of the automatic extraction of input data. With the connection to GIS the model portability increases substantially, which will improve nonpoint source modeling at the watershed-scale level.

Mitchell, G. (2005). "Mapping hazard from urban non-point pollution: a screening model to support sustainable urban drainage planning." Journal of Environmental Management 74(1): 1-9.

The goal of this study was to develop a planning and assessment model for identifying urban nonpoint pollution “hot spots” for river basins. With this model, installation of sustainable urban drainage systems (SuDS) can be prioritized and thus be most cost effective.

 The GIS model used MapInfo with the Vertical Mapper extension. It addressed: Impervious area, estimated using land use data and corresponding land use-impermeability coefficients; urban land use; residential density data; rainfall acceptance potential variable; annual rainfall; and catchment area.  The study found that the GIS-model acted as intended and was a good tool for site appraisal for SuDS planning.

Morari, F., E. Lugato, et al. (2004). "An integrated non-point source model-GIS system for selecting criteria of best management practices in the Po Valley, North Italy." Agriculture, Ecosystems & Environment 102(3): 247-262.

The purpose of this study was to integrate the model CropSyst with GIS to develop a best management practice which encourages sustainable farming systems to reduce nonpoint pollution in the Minicio River Basin in Po Valley, Italy. The GIS system used was ArcInfo from ESRI. The integrated model simulated the effects of cropping systems on crop yield and the environmental impacts, such as nitrogen and erosion.  The water balance was computed using inputs of rainfall and irrigation, and outputs of evaporation, transpiration, and runoff.

The study found that the GIS–CropSyst integration allowed alternative territorial scenarios to be analyzed within relatively short times. Improvements  to the system architecture would be to introduce water transport models in the water systems.

Sivertun, Å. and L. Prange (2003). "Non-point source critical area analysis in the Gisselö watershed using GIS." Environmental Modeling & Software 18(10): 887-898.

The location of this study was a small fjord-like bay in Slätbaken Sweden, which has a narrow outlet to the Baltic Sea. The water quality in Slätbaken depends greatly on the water quality of the streams that flow in it, which is impacted by the nonpoint pollution from agriculture areas. The fertilizer from the agriculture areas will run off and deposit pollutants like phosphorus in the streams.  Since the transport of nonpoint pollutants is based on the same hydrological processes as erosion and sediment transport the study used the Universal Soil Loss Equation (USLE) combined with a GIS.

 The software the study used was the commercial standard GIS software ArcView from ESRI. Because the USLE model needs raster overlay functions, the Spatial Analyst extension for ArcView was also needed. In addition the 3D Analyst extension was used to improve the elevation model. The input data was a vector soil map, a digital elevation model for slope length, a land use factor map, and a watercourse map with different vector layers of lakes, streams, channels and coastlines. The four factor maps were combined according to the simplified USLE by a simple multiplication of its raster values. The GIS analysis identified “risky areas” which could be changed over to wetlands, or other non-agriculture uses. It also identified thresholds for the amount of fertilizers to reduce risks. The study found that using GIS did not require special skills and it made updating the model easy and time efficient.

ADDITIONAL INFORMATION

To learn more about nonpoint source pollution visit these sites.  

The United States Environmental Protection Agency

http://www.epa.gov/ebtpages/watewaternonpointsources.html

Oregon Department of Environmental Quality

http://www.deq.state.or.us/wq/nonpoint/nonpoint.htm

ESRI

http://www.esri.com/industries/water/business/literature.html

Non-Point Source Pollution

http://www.protectingwater.com/

NOAA

http://www.oceanservice.noaa.gov/education/kits/pollution/welcome.html

CONTACT

Please Email me with comments and recommendations.

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