Modeling Agricultural Nonpoint Source Pollution Using a Geographic Information System Approach

Agricultural non-point source (NPS) pollution, primarily sediment and nutrients, is the leading source of water-quality impacts to surface waters in North America. The overall goal of this study was to develop geographic information system (GIS) protocols to facilitate the spatial and temporal modeling of changes in soils, hydrology, and land-cover change at the watershed scale. In the first part of this article, we describe the use of GIS to spatially integrate watershed scale data on soil erodibility, land use, and runoff for the assessment of potential source areas within an intensively agricultural watershed. The agricultural non-point source pollution (AGNPS) model was used in the Muddy Creek, Ontario, watershed to evaluate the effectiveness of management strategies in decreasing sediment and nutrient [phosphorus (P)] pollution. This analysis was accompanied by the measurement of water-quality parameters (dissolved oxygen, pH, hardness, alkalinity, and turbidity) as well as sediment and P loadings to the creek. Practices aimed at increasing year-round soil cover would be most effective in decreasing sediment and P losses in this watershed. In the second part of this article, we describe a method for characterizing land-cover change in a dynamic urban fringe watershed. The GIS method we developed for the Blackberry Creek, Illinois, watershed will allow us to better account for temporal changes in land use, specifically corn and soybean cover, on an annual basis and to improve on the modeling of watershed processes shown for the Muddy Creek watershed. Our model can be used at different levels of planning with minimal data preprocessing, easily accessible data, and adjustable output scales.     

Urbanization and its impact on groundwater: a remote sensing and GIS-based assessment approach

The perils of unplanned urbanization and increasing pressure of human activities on hydro-geomorphologic system often result in modification of the existing recharge mechanism, which leads to many environmental consequences. In the present research, an attempt has been made to investigate the applicability of remote sensing and geographical information system (GIS) in dealing with spatial and temporal variability of dynamic phenomena, like urbanization and its impact on groundwater. This paper covers primarily, quantitative and qualitative impacts of urban growth on the behavior of aquifer in Ajmer city (India). Urban growth of the Ajmer city in last 17 years has been estimated from the satellite images. Database related to urbanization and groundwater has been created in GIS. Groundwater recharge has been computed using a water balance approach known as Water Level Fluctuation Methodology. Recharge estimation methodology has been implemented in GIS to introduce the spatial variability of hydro-geological characteristics. Further, temporal and spatial variations in groundwater quality and quantity have been correlated with urban growth using overlay analysis in GIS. The study reveals a general decline in water table and quality with urbanization. Further, remote sensing and GIS technologies have been found useful in assessment of spatial and temporal phenomena of urbanization and its impact on groundwater system.     

RUNOFF PREDICTION USING REMOTE SENSING IMAGERY1

ABSTRACT: Percent imperviousness is an important parameter in modeling the urban rainfall-runoff process and is usually determined using manual methods such as random sampling or conventional accounting methods. In this study two computerized methods are used for estimating the percent imperviousness of urban watersheds using high altitude remote sensing imagery. These methods include the Laser Image Processing Scanner and the Video-Tape Camera system. Imperviousness is directly estimated in the former method while in the latter it is estimated as a function of the statistics of the responses on emulsions of the imagery. The percent imperviousness computed by utilizing remote sensing imagery was used with the conceptual models of rainfall-runoff models. The models were applied to four urban watersheds and the runoff prediction results indicate that imperviousness determined by using remote sensing imagery was as accurate as that obtained by the manual methods, and that the use of remote sensing imagery requires significantly less time and money.     

Trends in Soil Erosion and Woody Shrub Encroachment in Ngqushwa District,Eastern Cape Province,South Africa

Woody shrub encroachment severely impacts on the hydrological and erosion response of rangelands and abandoned cultivated lands. These processes have been widely investigated at various spatial scales, using mostly field experimentation. The present study used remote sensing to investigate spatial and temporal patterns of soil erosion and encroachment by a woody shrub species, Pteronia incana, in a catchment in Ngqushwa district, Eastern Cape Province, South Africa between 1998 and 2008. The extreme categories of soil erosion and shrub encroachment were mapped with higher accuracy than the intermediate ones, particularly where lower spatial resolution data were used. The results showed that soil erosion in the worst category increased simultaneously with dense woody shrub encroachment on the hill slopes. This trend is related to the spatial patterning of woody shrub vegetation that increases bare soil patches—leading to runoff connectivity and concentration of overland flow. The major changes in soil erosion and shrub encroachment analysed during the 10-year period took place in the 5–9° slope category and on the concave slope form. Multi-temporal analyses, based on remote sensing, can extend our understanding of the dynamics of soil erosion and woody shrub encroachment. They may help benchmark the processes and assist in upscaling field studies.     

Assessing Surface Water Quality and Its Relation with Urban Land Cover Changes in the Lake Calumet Area, Greater Chicago

Urban land use and land cover change significantly affect spatial and temporal patterns of runoff, which in turn impacts surface water quality. With the exponential growth in urban areas over the past three decades, changes in land use and land cover to cater for the growth of cities has been a conspicuous spectacle in urban spaces. The main goal of this study was to assess the impacts of land cover change on runoff and surface water quality using a partial area hydrology framework. The study employed ArcHydro GIS extension and a modified version of Long-Term Hydrologic and Nonpoint Source Pollution model (L-THIA-NPS) in estimating runoff and nonpoint source pollutant concentration around Lake Calumet between 1992 and 2001. Data employed include National Land Cover Data set, rainfall data, digital elevation model (DEM), Soil Survey Geographic (SSURGO) data, and The United States Environmental Protection Agency’s STORET (storage and retrieval) water quality data. The model was able to predict surface water quality reasonably well over the study period. Sensitivity analysis facilitated a manual calibration of the model. Model validation was executed by comparing simulated results following calibration and observed water quality data for the study area. The study demonstrates that the level of concentration of nonpoint source pollutants in surface water within an urban watershed heavily depends on the spatiotemporal variations in areas that contribute towards runoff compared to the spatial extent of change in major land use/land cover.     

MACROSCALE HYDROLOGIC MODELING FOR REGIONAL CLIMATE ASSESSMENT STUDIES IN THE SOUTHEASTERN UMTED STATES1

ABSTRACT: A macroscale hydrologic model is developed for regional climate assessment studies under way in the southeastern United States. The hydrologic modeling strategy is developed to optimize spatial representation of basin characteristics while maximizing computational efficiency. The model employs the “grouped response unit” methodology, which follows the natural drainage pattern of the area. First order streams are delineated and their surface characteristics are tested so that areas with statistically similar characteristics can be combined into larger computational zones for modeling purposes. Hydrologic response units (HRU) are identified within the modeling units and a simple three‐layer water balance model, Soil and Water Assessment Tool (SWAT), is executed for each HRU. The runoff values are then convoluted using a triangular unit hydrograph and routed by Muskingum‐Cunge method. The methodology is shown to produce accurate results relative to other studies, when compared to observations. The model is used to evaluate the potential error in hydrologic assessments when using GCM predictions as climatic input in a rainfall‐runoff dominated environment. In such areas, the results from this study, although limited in temporal and spatial scope, appear to imply that use of GCM climate predictions in short term quantitative analyses studies in rainfall‐runoff dominated environments should proceed with caution.     

Assessing Watershed-Scale, Long-Term Hydrologic Impacts of Land-Use Change Using a GIS-NPS Model

Land-use change, dominated by an increase in urban/impervious areas, has a significant impact on water resources. This includes impacts on nonpoint source (NPS) pollution, which is the leading cause of degraded water quality in the United States. Traditional hydrologic models focus on estimating peak discharges and NPS pollution from high-magnitude, episodic storms and successfully address short-term, local-scale surface water management issues. However, runoff from small, low-frequency storms dominates long-term hydrologic impacts, and existing hydrologic models are usually of limited use in assessing the long-term impacts of land-use change. A long-term hydrologic impact assessment (L-THIA) model has been developed using the curve number (CN) method. Long-term climatic records are used in combination with soils and land-use information to calculate average annual runoff and NPS pollution at a watershed scale. The model is linked to a geographic information system (GIS) for convenient generation and management of model input and output data, and advanced visualization of model results. The L-THIA/NPS GIS model was applied to the Little Eagle Creek (LEC) watershed near Indianapolis, Indiana, USA. Historical land-use scenarios for 1973, 1984, and 1991 were analyzed to track land-use change in the watershed and to assess impacts on annual average runoff and NPS pollution from the watershed and its five subbasins. For the entire watershed between 1973 and 1991, an 18% increase in urban or impervious areas resulted in an estimated 80% increase in annual average runoff volume and estimated increases of more than 50% in annual average loads for lead, copper, and zinc. Estimated nutrient (nitrogen and phosphorus) loads decreased by 15% mainly because of loss of agricultural areas. The L-THIA/NPS GIS model is a powerful tool for identifying environmentally sensitive areas in terms of NPS pollution potential and for evaluating alternative land use scenarios for NPS pollution management.     

Land-Use and Land-Cover Dynamics in the Central Rift Valley of Ethiopia

Understanding the complexity of land-use and land-cover (LULC) changes and their driving forces and impacts on human and environmental security is important for the planning of natural resource management and associated decision making. This study combines and compares participatory field point sampling (pfps) and remote sensing to explore local LULC dynamics. The study was conducted in two peasant associations located in the central Ethiopian Rift Valley, which is a dry-land mixed farming area exposed to rapid deforestation. From 1973–2006, the area of cropland doubled at the expense of woodland and wooded-grassland in both of the study sites. Major deforestation and forest degradation took place from 1973–1986; woodland cover declined from 40% to 9% in one of the study sites, while the other lost all of its original 54% woodland cover. Our study concludes that assessing LULC dynamics using a combination of remote sensing and pfps is a valuable approach. The two methods revealed similar LULC trends, while the pfps provided additional details on how farmers view the changes. This study documents dramatic trends in LULC over time, associated with rapid population growth, recurrent drought, rainfall variability and declining crop productivity. The alarming nature of these trends is reflected in a decrease in the livelihood security of local communities and in environmental degradation. Given these dry-land conditions, there are few opportunities to improve livelihoods and environmental security without external support. If negative changes are to be halted, action must be taken, including building asset bases, instituting family planning services, and creating opportunities outside these marginal environments.     

Land use change analysis in the Zhujiang Delta of China using satellite remote sensing,GIS and stochastic modelling

Rapid land use change has taken place in many coastal regions of China such as the Zhujiang Delta over the past two decades due to accelerated industrialization and urbanization. In this paper, land use change dynamics were investigated by the combined use of satellite remote sensing, geographic information systems (GIS), and stochastic modelling technologies. The results indicated that there has been a notable and uneven urban growth and a tremendous loss in cropland between 1989 and 1997. The land use change process has shown no sign of becoming stable. The study demonstrates that the integration of satellite remote sensing and GIS was an effective approach for analyzing the direction, rate, and spatial pattern of land use change. The further integration of these two technologies with Markov modelling was found to be beneficial in describing and analyzing land use change process.     

Rainwater harvesting planning using geospatial techniques and multicriteria decision analysis

Growing water scarcity and global climate change call for more efficient alternatives of water conservation; rainwater harvesting (RWH) is the most promising alternative among others. However, the assessment of RWH potential and the selection of suitable sites for RWH structures are very challenging for the water managers, especially on larger scales. This study addresses this challenge by presenting a fairly robust methodology for evaluating RWH potential and identifying sites/zones for different RWH structures using geospatial and multicriteria decision analysis (MCDA) techniques. The proposed methodology is demonstrated using a case study. The remote sensing data and conventional field data were used to prepare desired thematic layers using ArcGIS© software. Distributed Curve Number method was used to calculate event-based runoffs, based on which annual runoff potential and runoff coefficient maps were generated in the GIS (geographic information system) environment. Thematic layers such as slope, drainage density, and runoff coefficient and their features were assigned suitable weights and then they were integrated in a GIS to generate a RWH potential map of the study area. Zones suitable for different RWH structures were also identified, together with suitable sites for constructing recharge structures (check dams and percolation tanks along the streams). It was found that the study area can be classified into three RWH potential zones: (a) ‘good’ (241 km²), (b) ‘moderate’ (476 km²), and (c) ‘poor’ (287 km²). About 3% of the study area (30 km²) is suitable for constructing farm ponds, while percolation tanks (on the ground) can be constructed in about 2.7% of the area (27 km²). Of the 83 sites identified for the recharge structures, 32 recharge sites are specially suited to the inhabitants because of their proximity. It is concluded that the integrated geospatial and MCDA techniques offer a useful and powerful tool for the planning of rainwater harvesting at a basin or sub-basin scale.     

ESTIMATING NONPOINT SOURCE POLLUTION LOADS WITH A GIS SCREENING MODEL1

ABSTRACT: The St. Johns River Water Management District (SJR-WMD) is using a Geographic Information System (GIS) screening model to estimate annual nonpoint source pollution loads to surface waters and determine nonpoint source pollution problem areas within the SJRWMD. The model is a significant improvement over current practice because it is contained entirely within the district's GIS software, resulting in greater flexibility and efficiency, and useful visualization capabilities. Model inputs consist of five spatial data layers, runoff coefficients, mean runoff concentrations, and stormwater treatment efficiencies. The spatial data layers are: existing land use, future land use, soils, rainfall, and hydrologic boundaries. These data layers are processed using the analytical capabilities of a cell-based GIS. Model output consists of seven spatial data layers: runoff, total nitrogen, total phosphorous, suspended solids, biochemical oxygen demand, lead, and zinc. Model output can be examined visually or summarized numerically by drainage basin. Results are reported for only one of the SJRWMD's ten major drainage basins, the lower St. Johns River basin. The model was created to serve a major planning effort at the SJRWMD; results are being actively used to address nonpoint source pollution problems.     

Remote Sensing of Landscape-Level Coastal Environmental Indicators

Advances in technology and decreases in cost are making remote sensing (RS) and geographic information systems (GIS) practical and attractive for use in coastal resource management. They are also allowing researchers and managers to take a broader view of ecological patterns and processes. Landscape-level environmental indicators that can be detected by Landsat Thematic Mapper (TM) and other remote sensors are available to provide quantitative estimates of coastal and estuarine habitat conditions and trends. Such indicators include watershed land cover, riparian buffers, shoreline and wetland changes, among others. With the launch of Landsat 7, the cost of TM imagery has dropped by nearly a factor of 10, decreasing the cost of monitoring large coastal areas and estuaries. New satellites, carrying sensors with much finer spatial (1-5 m) and spectral (200 narrow bands) resolutions are being launched, providing a capability to more accurately detect changes in coastal habitat and wetland health. Advances in the application of GIS help incorporate ancillary data layers to improve the accuracy of satellite land-cover classification. When these techniques for generating, organizing, storing, and analyzing spatial information are combined with mathematical models, coastal planners and managers have a means for assessing the impacts of alternative management practices.     

Stormwater Runoff Characterized by GIS Determined Source Areas and Runoff Volumes

Runoff coefficients are usually considered in isolation for each drainage area with resulting large uncertainties in the areas and coefficients. Accurate areas and coefficients are obtained here by optimizing runoff coefficients for characteristic Geographic Information Systems (GIS) subareas within each drainage area so that the resulting runoff coefficients of each drainage area are consistent with those obtained from runoff and rainfall volumes. Lack of fit can indicate that the ArcGIS information is inaccurate or more likely, that the drainage area needs adjustment. Results for 18 drainage areas in Milwaukee, WI for 2000–2004 indicate runoff coefficients ranging from 0.123 for a mostly residential area to 0.679 for a freeway-related land, with a standard error of 0.047. Optimized runoff coefficients are necessary input parameters for monitoring, and for the analysis and design of in situ stormwater unit operations and processes for the control of both urban runoff quantity and quality.     

WATERSHED WEIGHTING OF EXPORT COEFFICIENTS TO MAP CRITICAL PHOSPHOROUS LOADING AREAS1

ABSTRACT: The Export Coefficient model (ECM) is capable of generating reasonable estimates of annual phosphorous loading simply from a watershed's land cover data and export coefficient values (ECVs). In its current form, the ECM assumes that ECVs are homogeneous within each land cover type, yet basic nutrient runoff and hydrological theory suggests that runoff rates have spatial patterns controlled by loading and filtering along the flow paths from the upslope contributing area and downslope dispersal area. Using a geographic information system (GIS) raster, or pixel, modeling format, these contributing area and dispersal area (CADA) controls were derived from the perspective of each individual watershed pixel to weight the otherwise homogeneous ECVs for phosphorous. Although the CADA‐ECM predicts export coefficient spatial variation for a single land use type, the lumped basin load is unaffected by weighting. After CADA weighting, a map of the new ECVs addressed the three fundamental criteria for targeting critical pollutant loading areas: (1) the presence of the pollutant, (2) the likelihood for runoff to carry the pollutant offsite, and (3) the likelihood that buffers will trap nutrients prior to their runoff into the receiving water body. These spatially distributed maps of the most important pollutant management areas were used within New York's West Branch Delaware River watershed to demonstrate how the CADA‐ECM could be applied in targeting phosphorous critical loading areas.     

Modelling of light pollution in suburban areas using remotely sensed imagery and GIS

This paper describes a methodology for modelling light pollution using geographical information systems (GIS) and remote sensing (RS) technology. The proposed approach attempts to address the issue of environmental assessment in sensitive suburban areas. The modern way of life in developing countries is conductive to environmental degradation in urban and suburban areas. One specific parameter for this degradation is light pollution due to intense artificial night lighting. This paper aims to assess this parameter for the Athens metropolitan area, using modern analytical and data capturing technologies. For this purpose, night-time satellite images and analogue maps have been used in order to create the spatial database of the GIS for the study area. Using GIS advanced analytical functionality, visibility analysis was implemented. The outputs for this analysis are a series of maps reflecting direct and indirect light pollution around the city of Athens. Direct light pollution corresponds to optical contact with artificial night light sources, while indirect light pollution corresponds to optical contact with the sky glow above the city. Additionally, the assessment of light pollution in different periods allows for dynamic evaluation of the phenomenon. The case study demonstrates high levels of light pollution in Athens suburban areas and its increase over the last decade.     

Developing the interaction matrix technique as a tool assessing the impact of traffic on air quality

This paper develops a technique which can be used as a preliminary tool for assessing air quality related to urban traffic. It combines a Geographic Information System (GIS) with an interaction matrix-type methodology based on a system analysis approach. The matrix identifies and quantifies interactions between all selected variables involved in a system as well as their interaction with the system as a whole. This matrix is used to determine the weightings to apply to spatial datasets within a GIS to develop a pollution vulnerability map. The focus of the paper is to introduce and assess a more versatile coding of the interaction matrix with respect to previously used coding. A case study is presented in which the modified interaction methodology is applied to data for a busy urban location. The resulting vulnerability map, in terms of pollution vulnerable hot spots, was compared to a pollution map derived from an advanced dispersion model. The interaction matrix technique with GIS can be used as a tool complementary to sophisticated numerical modelling and has potential as an analytical tool to evaluate multidisciplinary systems.     

Downward shortwave radiation estimation and spatial assessment on sites over complex terrain applying integrative approach of MTCLIM-XL,interpolation, RS and GIS

Downward shortwave radiation (DSR) is a highly variable solar source on spatiotemporal basis and essential for energy and agriculture systems, while its calculations are helpful in the environment-related studies, climatology, and monitoring fire risk. Statistical methods developed to extrapolate values of climatic variables and radiation could fail to generate reliable findings of DSR over a complex terrain without considering local topographic factors. In the present study, we proposed an integrative approach of MTCLIM-XL extrapolation with remote sensing (RS) and geographic information system (GIS) to estimate real-time DSR and its spatial potential over surfaces of contrasting elevated sites on a mountainous terrain of Quetta (Pakistan).Based on methodological approach, remote sensing data product of high-resolution DEM (SRTM 30m) was processed to extract topographic data, and meteorological data were obtained from a base site, Subsequently, MTCLIM-XL executed the simulation to calculate the daily-based DSR (W/m²).Spatial distribution of DSR was generated by applying deterministic interpolation with complementing quantification of Hillshade analysis for spatially obstructive surfaces, and resultant spatial hotspot-based potential was assessed on basis of specified threshold level (above 250 W/m² = 2 kW h/m²) over the specified area. We observed usable potential of DSR at target sites and its spatial distribution during the study period of 2015 to April 2016. Using EUMETSAT CMSAF data as a standard, the validation demonstrates agreeable results of low RMSE and high correlation coefficient values for selected sites, except some sites with relatively high elevations and irregular gradients. Analysis of solar zenith angle to evaluate its inverse relation with increment in DSR values shows agreeable high inverse relation, while the negative trend for only some sites features relatively high rugged topography. In conclusion, MTCLIM-XL with RS and GIS integration manifests as a reliable approach for estimation and spatial potential assessment-based exploration of DSR over complex terrain having no ground data, while prospectively it will complement to the environment-related studies on local to mesoscale.     

SPATIALLY DISTRIBUTED MODELING OF STREAM FLOW DURING STORM EVENTS1

ABSTRACT: The purpose of this paper is to present a new approach for the spatially distributed modeling of water flow during storm events. Distributed modeling of flow during storm events is an important basis for any environmental modeling, including turbidity or sediment transport. During the initial phase of a rainstorm, surface runoff is the main contributor of flow. To provide the spatial components for distributed hydrological modeling a Geographic Information System (GIS) was used to map and visualize contributing areas around a stream channel. Stream segments were defined using the hydrologic response unit (HRU) concept. Lateral flows were derived from GIS output for each segment of the stream and at each time interval of the rain storm and were routed using the kinematic routing equation. This approach is new in hydrological modeling and can be used to enhance many existing simulations. The model is also unique in the fine time scale (i.e., intervals are on the order of minutes). Model results showed good correlation with measured discharge values; however, further studies of contributing area behavior, its relationship with soil types and slope categories, and the influence of watershed size are needed to improve model performance. This model will be used in the future as the basis to model turbidity in streams.     

Decision-tree and rule-induction approach to integration of remotely sensed and GIS data in mapping vegetation in disturbed or hilly environments

The integration of Landsat TM and environmental GIS data sets using artificial intelligence rule-induction and decision-tree analysis is shown to facilitate the production of vegetation maps with both floristic and structural information. This technique is particularly suited to vegetation mapping in disturbed or hilly environments that are unsuited to either conventional remote sensing methods or GIS modeling using environmental data bases.     

Application of land-use data and screening tests for evaluating pesticide runoff toxicity in surface waters

Survey information on pesticide usage in New Zealand during 1985–1989 is summarized by regions and principal applications. Two screening tests, one based on a simple water-balance method and the other based on a semiempirical runoff formula, have been used to identify 18 pesticides with application rates that may yield runoff concentrations that are harmful to aquatic fauna. These are predominantly associated either with intensive applications in horticulture or extensive applications to cereal crops and pasture. The purpose of the screening tests was to calculate typical edge-of-field concentrations in runoff and, by comparing them with known aquatic toxicity values, determine which compounds are applied at rates that may yield toxic runoff. While it may be possible to extend these methods to calculate typical surface water concentrations, further studies will be needed to evaluate pesticide persistence and assimilation in stream channels.