nium and distinctive damage to waterfowl hatchlings in Kesterson Reservoir as causes for concern. Even though man's activities in the San Joaquin Valley have exacerbated the selenium problem, the ultimate cause can be traced to the natural geochemical environment in the mountains west of the valley. Understanding the geochemical control on the occurrence of selenium in this region may lead to the anticipation of possible problems in other areas and to actions that could prevent those problems.

The climate in and around the San Joaquin Valley is conducive to the solution and mobilization of selenium, but the rocks on the east side of the valley,

West

granites of the Sierra Nevada, do not contain a significant source of selenium, and this situation produces selenium-deficiency problems rather than selenium-toxicity problems. In fact, the sediments derived from these mountains are so low in selenium that cattle feeding in this area do not get sufficient selenium from plants grown on the soils or from local water supplies, and their diets must be supplemented with selenium. As shown in the diagrammatic cross section of the San Joaquin Valley and the surrounding mountains (fig. 3), the rocks in the Coast Ranges on the west side of the valley are the ultimate source of selenium in the soils and waters of the valley.

Figure 3. Idealized cross section across the San Joaquin Valley of California showing different compositions of source rocks in mountains on both sides of the valley.

Figure 4. Map of part of the San Joaquin Basin showing the location of the San Luis Drain and Kesterson Reservoir. Area in orange shows where underground tile drains have been constructed.

Solution of selenium from the many diffuse sources in these rocks has led to the present problems in the valley. The rocks are primarily sediments of marine origin and contain scattered metal-sulfide deposits. Iron, lead, zinc, mercury, molybdenum, and other metals are found in this area, combined with sulfur as sulfide minerals. Selenium, which is chemically similar to sulfur, is mostly found in these sulfurcontaining minerals substituting for some of the sulfur. For example, pyrite, a chemical compound consisting of iron and sulfur, may have up to 1,000 parts per million of selenium substituting for the sulfur. Selenium can also substitute for sulfur in gypsum, in organic compounds such as proteins, and in many other minerals.

As a result of weathering processes, the seleniumcontaining minerals within rocks of the Coast Ranges are slowly dissolved and the now-soluble form of selenium, called selenate, is slowly removed by flowing surface and ground waters. Under natural conditions that prevailed before intensive farming in the valley and water diversion projects, the soluble salts were transported in solution during wet periods down to the valley where they were either precipitated out in the valley sediments due to evaporation or occasionally carried by streams into San Francisco Bay. Runoff from large storms transported both fresh and weathered rock containing selenium minerals to the valley floor, which created the large fans of sediment, such as the Panoche Fan, along the western edge of the San Joaquin Valley. Because of the arid climate within the valley, the selenium in the water and sediments transported to the fans is concentrated by evaporation. The selenium occurs in the fans as unweathered selenium-containing minerals, precipitated soluble-selenate-containing salts, and coatings adhering to clays, iron oxides, and fine sediments.

Before the advent of water control projects and farming in the valley, soluble selenium and other salts built up gradually in the valley soils and shallow sediments. The recent intensively irrigated agriculture and water control projects in the valley attempted to flush salt from the soils, but a nearsurface clay caused waterlogging and salt buildup at the land surface that eventually damaged crops. This buildup of salts is still going on in much of the San Joaquin Valley. As shown in figure 4, in this area, underground tile drains have been constructed in

part of the Panoche Fan to remove the saline waters that build up in the soils. Even with the relatively small amount of tile drainage in the Panoche Fan, there is a large amount of saline drainage water being moved from the area into Kesterson Reservoir. The highly saline water moving into Kesterson Reservoir contains large amounts of selenium. Besides selenium, other chemical elements are present at high concentrations and may be harmful to plants and animals. Before the water in Kesterson Reservoir reaches levels toxic to organisms living in it, certain plants and animals in this environment concentrate some chemical elements sufficiently to be toxic to other organisms that use them as a food source. The selenium toxicity noted in waterfowl is believed to result from the bioaccumulation of selenium in the food chain; for example, the accumulation occurs from algae to insects to fish to birds.

Summary

Large areas in the Western United States, with its climate that often promotes the solubilization of selenium, are underlain by geologic formations containing high concentrations of selenium. Understanding the geochemical controls on the occurrence and movement of selenium in Kesterson Reservoir will help make possible the recognition of potential selenium problems in other areas so that mitigation measures can be taken. This knowledge will serve to alert persons in similar areas to the probability of selenium toxicity, both in the natural environment and in the environment altered by man's activities.

Introduction

Today, Federal and State agencies must quickly respond to complicated problems involving natural resources data for a variety of geographic areas. Administrative and regulatory responsibilities assigned to governmental agencies have placed tremendous pressure on existing information delivery systems. The traditional methods of acquiring, storing, and analyzing natural resources data are proving to be too costly and inflexible in meeting these growing needs. Computerized geographic information systems (GIS) are emerging as the spatial data handling tools for solving complex geographical problems.

A geographic information system is a computer system designed to allow users to collect, manage, and analyze large volumes of spatially referenced data. The use of GIS technology has revolutionary implications for the way the Geological Survey conducts research and presents the results. As the Nation's primary producer of cartographic, geographic, hydrologic, and geologic data, the Geological Survey is using advanced GIS technologies to greatly improve its ability to perform traditional missions of earth science data collection, research, and information delivery.

The Geological Survey and other bureaus and offices of the Department of the Interior have created a number of digital spatial data bases that are being used in geographic information systems. Among these are the National Digital Cartographic Data Base, the Federal Mineral Land Information System, the Land Use and Land Cover Mapping Program, the National Coal Resources Data System, the National Uranium Resources Evaluation System, the Rock Analysis Storage System, and the National Water Data System. The Geological Survey is increasingly being required to serve as a central repository as well as the Federal authority on information regarding such critical issues as the Nation's energy and mineral potential, the assessment of risks from natural hazards, and questions of the quantity and quality of water supplies. Because GIS technology allows scientists to process and interrelate many more kinds of data than were previously feasible, GIS applications research can provide new scientific understanding of these issues.

Characteristics of Spatial Data

A GIS cannot function without digital spatial data. Spatial data consist of the various features that are associated with a geographic location. These features can be points, lines, or areal characteristics that are visually discernible, such as wells, roads, or lakes, or invisible boundaries, such as county lines or school districts. A GIS must be capable of storing and manipulating these types of point, line, and areal data. The association of a given spatial feature with a data type depends on the scale of the map or image. For example, a river can be shown as an area at large scale but only as a line at a smaller scale.

Two major methods, or data structures, are used to organize spatial data within a computer for use by a GIS: the raster data structure and the vector data structure. Each of these structures has distinct advantages and disadvantages that affect cost and efficiency.

A raster data structure is formed by partitioning the study area into a set of grid cells that are usually square. Each cell is assigned a code describing the feature contained within the cell, as in type of land use, elevation, or county name. The size of cell is selected on the basis of the resolution needed, or available, in the case of remote sensing satellites such as Landsat, and the capacity of the system.

Explicit x,y coordinates are not given to each cell because the cell location is implicit in its row and column in the grid. Separate thematic data sets over the same area, such as land use and counties, can be easily merged (overlaid) by combining the attribute codes, cell by cell, of each data set. The raster data structure is popular in large part because of the ease of programming the overlaying and other analytical operations. However, the cell-by-cell nature of the raster structure makes it difficult to retrieve information about specific areal or linear features (for example, the length of the shoreline of Great Salt Lake) or to traverse a network of linear features (for example, routing a train from Atlanta to Denver). Vector data structures use a series of x,y coordinates to describe the point, line, and area (or polygon) features. In addition, information about the connections and relationships among the features portrayed on a map (the topology of the map) is

calculated and stored with the coordinates. Thus, system users can derive relationships such as adjacency and connectedness easily. This data structure is computationally more demanding than a raster structure but is being used increasingly in GIS's because of the decreasing cost of computers and the greater information inherent in such data. The digital line graph structure used in the National Digital Cartographic Data Base is an example of this type of data organization.

Functional Characteristics of a GIS

The principal functions commonly found in geographic information systems are given in table 1. Each functional component has counterparts that work on vector or raster data types. No known system contains all the possible functions given in the table, and it may be argued that no one system should. The functional components present in any particular GIS vary considerably according to its application. For example, one system might emphasize the creation of publication-quality map products, while another might stress statistical generation.

Data Requirements

Although GIS technology has been in use for more than a decade, the level of acceptance and use has, until recently, remained relatively low. Since data collection is perhaps the most expensive phase of GIS operations, it is likely that the lack of detailed base map and thematic information in digital form has hampered GIS growth. Efforts by the Geological Survey to link its various spatial data bases and to provide rapid, convenient, and cost effective access to the data will help alleviate this problem. In particular, the national data base of transportation and hydrologic features digitized from 1:100,000-scale base maps will serve not only as a fundamental data base for GIS studies but also as a catalyst for the addition of thematic data.

Application of a GIS

In 1984, the Geological Survey and the Natural Resources Center, Connecticut Department of Environmental Protection, agreed to test jointly the use of a GIS as a means to improve the traditional methods of obtaining, storing, updating, analyzing, and dis

playing mapped natural resources data. This effort was a logical outgrowth of the extensive cooperative studies that the State and the Geological Survey have conducted in Connecticut over the last 50 years. The results of this test were presented at the Association of American State Geologists Annual Meeting held in Mystic, Conn., in June 1985.

A project area covering the Broad Brook and Ellington 7.5-minute quadrangles in north-central Connecticut was selected (fig. 1).1 The area had been used in earlier studies on the application of mapped natural resources data in environmental planning and management. From 1968 to 1972 the Ellington quadrangle was the focus of the Connecticut Geology and Soil Task Force in demonstrating resource map overlay techniques for selecting potential landfill sites, and in the early 1970's both quadrangles had been included in the Geological Survey/State cooperative Connecticut Valley Urban Area Project. This project produced numerous interpretive and basic resource maps for use in local and regional planning. More recently, the Broad Brook subregional drainage basin, of which approximately half lies in each quadrangle, was selected by the University of Connecticut as a major hydrologic and meteorologic research

area.

The ARC/INFO geographic information system developed by Environmental Systems Research Institute, Redlands, Calif., was the primary GIS used for the project. ARC/INFO consists of two major programs: ARC maintains the topologically structured vector data base in which points, lines, or areas are used to represent mapped features, and INFO stores and processes attribute information (land use, surficial materials, etc.) about the geographic features maintained by ARC. The State of Connecticut was already using INFO as its data base management system.

Data entered into the GIS came from existing digital data bases and from digitizing information from hard-copy maps. Digitizing was done at the Geological Survey's Eastern Mapping Center and Earth Resources Observation Systems Data Center. Source materials used in the digitizing process were 1:24,000-scale mylar overlays supplied by the Eastern Mapping Center and Connecticut's Natural Resources Center.

Approximately one-third of the data base was developed from existing digital data. These data included 1:24,000-scale digital line graphs for 1980

1Figures 1 through 7 were produced by an ink jet plotter and are

copies of images shown on a color display terminal. As such, they

represent the types of graphic output an analyst would see while using a GIS on an applications project.