The Dams of California as a Case Study

 

In

 

Using Geographic Information Systems in Environmental History and Politics

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Kenneth Worthy

ESPM 275

5 December 2000


1         Introduction

 

Water has always played a crucial role in the formation of the modern California state (see Marc Reisner, Cadillac Desert). It is evident that none of the large cities of the state, particularly Los Angeles, could exist in anything like their current form without a remarkably extensive control of water resources. The entire current population of the state depends on a controlled source of water. To that end, there are approximately 1300 dams in California, ranging in size from very small to extremely large, such as the one creating Lake Shasta. Dams regulate the flow of water, providing a buffer against seasonal and other variations, in addition to providing a large, perpetual on-demand supply for fire fighting and other urgencies. The vast majority of flowing water in the state has come under the control of public and private water systems of all sorts, with dams as the central feature of those water systems. Little water reaches the ocean without having been held back by several of these dams.

Yet, few people have a realistic, informed conception of the extensive nature of the dams (and their own dependence on them). Because of their great number, distribution and range of factors in use, construction size, etc., it is difficult to get a strong grasp of the overall characteristics of the dams of California without the use of GIS tools. These tools allow for the spatial representation of geographic distribution, size, time period, drainage area size, etc. The rarity of the use of these tools for education and policy making concerning the dams probably contributes to a general ignorance about the extent of dams in California; this is probably also the case with most of the other public works projects upon which citizens depend.

2         Purpose

 

The purpose of this project is to demonstrate the use of GIS in elucidating general trends, scope and other characteristics of dams in California for the purpose of general education and policy making and to spawn questions for further research. Such data in an aggregate state is either inaccessible to the public because it is in a dense tabular form or because it is presented in interspersed, discontinuous form throughout the public media. This study hopes to provide an example of presenting such data in ways that enables a “gestalt” view of the overall system of dams in the state, allowing the perusal of the information in meaningful aggregate forms. In other words, rather than providing many abstract, numeric statistics, or decontextualized, partial views of the system of dams in the state, these methods are meant to allow for the presentation of the dam data in such a way that general characteristics of the dams can begin to emerge. Thus, this project will hopefully work as an example and prototype for using GIS data about large-scale public works projects to create a broader understanding among the public and politicians about the control over, and environmental history of, the natural resources upon which they depend.

3         Method

 

The core data for the project was initially found in the extensive University of California Digital Library dam database, which was constructed via an optical character recognition conversion of a database of the dams of California published by the California Department of Water Resources. The site for that database can be found at: http://elib.cs.berkeley.edu/kopec/b17/html/home.html. Because the published schema for that online database was found to be error prone (fields described in the wrong order, etc.), I used instead the California state section of the National Inventory of Dams (NID), provided free online by the United States Geological Survey. The site for this database can be found at http://crunch.tec.army.mil/nid/webpages/nid.cfm. The NID also provided a more extensive set of data for each dam, including lat-long coordinates for each dam, owner, county, and various dam metrics such as maximum storage, drainage area feeding the dam, etc. The full data dictionary and schema of the NID database can be found at: http://www.nws.noaa.gov/oh/hod_whfs/documentation/damcat_dict.html.

Arcview was used as the primary GIS tool. The California dams database was added as a table and then processed in numerous ways described below to extract data presentations. The dams database was supplemented by stock Arcview data such as California state and county maps and databases, etc. Because of the limitations of Arcview, I also used Excel, PowerPoint and RealPlayer as data processing and presentation tools. These tools together were used to present the dams data in multiple forms: 1) as static themes in Arcview views, 2) as Arcview and Excel charts, 3) as an animated display in PowerPoint.

            Several views of the dam database were produced in the study. A dynamic view was produced with an Excel animation; the rest were static views which could be manipulated by an Arcview user. Examples of all of the views have been printed out in color and attached as an appendix to this document. Arcview views were formatted using the layout facility. For a more professional presentation, additional information might be printed on these displays, including additional legend values, etc. For example, the legend values for the “dams by year completed” view were difficult to include in full in the printout due to their great number; the range of legend values is dark blue at 1850 to dark red at 2000.

            The following is an abbreviated list of views, with description, produced for this study. Unless otherwise noted, the view includes a plain gray base map of California.

1.      100 biggest dams by maximum storage, with DEM (Digital Elevation Model) base map: a point for each of the 100 biggest dams by maximum storage volume in acre-feet, sized proportionally to the maximum storage volume.

2.      Dams by year complete, with DEM base map: a point for each dam, with color dependent on year. Colors range from deep blue for the oldest dams (1850 being the oldest) through yellow to deep red for the newest.

3.      Dams by height, with DEM base map: a point for each dam, with color dependent on dam height. Colors range from the shortest in blue, through yellow, to the tallest in red.

4.      Dams by maximum storage: a point for each dam, with size proportional to the maximum storage volume of the dam in acre-feet.

5.      Dams by year completed: a point for each dam, with color dependent on year. Colors range from deep blue for the oldest dams (1850 being the oldest) through yellow to deep red for the newest.

6.      Dams by height: a point for each dam, with color dependent on dam height. Colors range from the shortest in blue, through yellow, to the tallest in red.

7.      100 biggest dams by maximum storage: a point for each of the 100 biggest dams by maximum storage volume in acre-feet, sized proportionally to maximum storage volume.

8.      Number of dams per county: Counties shaded according to the number of dams in the county (darker = greater volume), overlaid with dams sized proportionally to maximum storage.

9.      Total dam volume per county: Counties shaded according to total dam volume, overlaid with dams sized proportionally to maximum storage.

10.  Total dam drainage area as a percentage of total county area: Counties shaded by percentage of total dam drainage area over county area. Drainage area is defined as the total area feeding into the dam. Percentages range from 0 to 1,436.

11.  A chart of the top 15 dam owners by total volume of water dammed. In acre-feet.

12.  A chart of the number of dams built per decade from 1850 to 2000.

13.  A chart comparing the number of dams built for each combination of purposes. A table defining the set of single-letter purpose codes follows below.

14.  The PowerPoint slide of dams completed by the 1880’s. Color-coded by decade.

15.  The PowerPoint slide of dams completed by 2000. Color-coded by decade.

 

The creation of Arcview views was accomplished primarily using the NID data as well as stock data of U.S. states and counties provided with Arcview. The NID database is rich, with up to fifty-seven fields provided for each dam. These fields include such things as geographic location, owner, purpose, construction specifics, storage size, drainage areas, regulatory specifics, and emergency action plan. Only a small (but interesting) subset of the data was included in this study. In each case, the dam data was brought in to a view as an event theme—a possibility enabled by the database’s geographic orientation, with its inclusion of latitude and longitude. (See the results section for discussion of invalid coordinates.) For some images, a Digital Elevation Model of California was used as a base map, allowing the viewer to ascertain dam locations relative to geographic features, such as the central valley, mountain ranges and lakes. The resultant static views of dam data, which are listed above, can be viewed by users of Arcview; eventually, these could be exported as web pages for access to a broader audience.

Charts, which were used to augment the GIS data, were produced primarily in Excel due to the better chart production facility in that program compared with Arcview. In several cases, data were selected and then exported from the tables in Arcview, read into Excel, and then formatted into charts and tables. Charts are useful as an auxiliary to GIS for data which is not immediately spatially oriented. They are particularly useful for direct comparison of quantities such as number of dams built per decade.

An animation of dam construction rates and locations was produced by successively layering themes containing dams from individual decades and then exporting the resulting graphical representations from the Arcview view as JPEG files. Initially, RealPlayer was used as a viewer for the images, by creation of a “playlist” file which lists the source files and timing, but there was a significant problem with this method: RealPlayer unfortunately displayed a black screen between each image, disrupting the animation. The problem was solved by importing each image into PowerPoint and then setting up an automated “transition” of two seconds between slides. By ensuring that the images were placed in identical locations on each page, a reasonable animation of the dam completion over the years was created. Animating the process of the addition of dams to the landscape can give an audience a feeling for the history of dam building, in as much as the change in rate of dam construction over time is readily perceptible. As an extension of this project, the views for the animation could be changed to incorporate dam volumes, and the animation could perhaps be accomplished directly in Arcview using Avenue, with resolution at the year, rather than decade, level.

   The following table specifies the dam purposes encoded in the National Inventory of Dams:

Dam Purpose Code

Purpose

I

Irrigation

H

Hydroelectric

C

Flood Control And Storm Water Management

N

Navigation

S

Water Supply

R

Recreation

P

Fire Protection, Stock, Or Small Farm Pond

F

Fish and Wildlife Pond

D

Debris Control

T

Tailings

O

Other

 

These values and combinations of them are used in the chart which analyzes the major combination of purposes of dams.

4         Results

 

The results are basically as intended, though there were several problems in the production of the various types of views, most of which could be circumvented. The worst problem occurred when the animation attempt using RealPlayer was thwarted by that program’s display of a black screen between images. The problem was solved by using PowerPoint to display the animation. The JPEG-formatted images were each read into an individual slide, with title, and then an automated “slide transition” with a period of two seconds was set up. When the slide show is started, the slides automatically proceed. Using  a common alignment of the JPEG image among all of the slides ensured a realistic animation.

Another problem with the animation is the quality of the converted JPEG photos. Due to image compression, a blurring of the dam points occurred. Since the maps include a very large number of points, this makes the view less clear. In future developments, this problem could perhaps be circumvented by the use of an alternative image format, which may be facilitated by the use of alternative viewer software, as well.

Some problems were encountered with the use of the lat-long data from the NID dams database. Several dams in California were found outside of the land area of California, including a few which were found in the Pacific Ocean. There were two classes of data error that contributed to this result. One is that there were significant rounding errors in the latitude and longitude values. The other is that the latitude and longitude data in some cases were found to be far off from expected values, possibly due to data corruption or capture problems. With over 1300 entries in the database, it is perhaps not surprising that several location fields were invalid, given the wide range of source types for the data. A related problem was the mismatch of projection types between the dam data and the DEM base map; this was solved by converting  the projection of the DEM base map to geographic, with matching scale measures.

Another minor problem was the lack of accessibility in the legend editor to joined fields in an Arcview table. This was circumvented by exporting the table, quitting Arcview, copying over the original table with the exported table and restarting Arcview. The fields could then be used for legend construction. It is possible that further learning of Arcview techniques would present other possibilities, as well. Also, it was difficult to construct a legend for the DEM theme of California which clearly portrayed the contours of the geography. This is perhaps due to the very large scale of pixel size used in the only DEM that I was able to find; it would perhaps require extensive work to aggregate a more precise DEM of the entire state, though perhaps this has been done and could be found with more extensive searching. In addition, Arcview occasionally crashed.

These setbacks were minor compared to the amount of success in producing views with these methods. The tools used—Arcview, Excel and PowerPoint—are powerful in spite of the occasional difficulties in using them. They enabled the construction of several methods of graphically viewing what is otherwise merely alphanumeric data in a large database.

5         Discussion

 

The intent in producing these graphical views of the dam data is to provoke thought—questions and observations—about the general topic of dams in California. Through this process, it is hoped that new knowledge pertaining to policy, ethics and environmental history can come to light. The following are some examples of questions and ideas catalyzed by viewing this data.

For instance, viewing the map of all California dams by size, one notices that not only are the largest dams predominantly in the mountainous regions, as one would expect, but they are also primarily in Northern California. This perhaps has implications in the old controversy about the movement of water from the north to the south. Viewing the map of the 100 biggest dams by volume with DEM base map shows a distinct concentration of the largest dams at the periphery of the central valley; this perhaps highlights the ultimate purpose of many of those dams—the collection of water for use in agriculture in the central valley. The map of all dams color-coded by year similarly shows a large concentration of recent dams in the mountains and hills just East of the middle of the central valley.

The map of dam completion years, with its predominance of red, demonstrates also the accelerated dam building in the last fifty years. The dam heights view demonstrates clearly that virtually all very large and very small dams tend toward the northern half of the state, with predominantly only mid-sized dams in the southern half of the state; this is perhaps related to topology or maybe to geography of water use. The top 100 big dams view clearly shows them mainly in the mountainous regions, confirming that big dams require valleys. Presenting only the top 100 dams shows how a simplified view can lend additional clarity to the presentation.

The number of dams per county and the dam volume per county maps show a clear preponderance of the latter, but not the former, in the northern half of the state; while there are many dams in Los Angeles county (with one of the highest dam densities), one can see that its total storage of dam water is relatively low, further exemplifying the dependence of the south on the north. Also of note is the great number of counties, particularly in the north, whose dam drainage areas greatly outstrip the amount of land in the county; i.e., counties are collecting water from much greater areas than they have in their jurisdiction. Although this is surely partly due to the iterative damming of waterways, it may lead one to inquire into the politics of collecting water which ultimately came from distant areas. In addition, a database query to count the total dam drainage area for all dams in California, 211005 square miles, is significantly greater than the total land area of California, 155,973 square miles. These observations signify one of the salient characteristic of the collection and use of water, which will no doubt be central to the water wars of the future: it is an inherently mobile resource; projects such as the Colorado River system aside, California certainly collects water that never precipitated in the state.

Dam ownership is interestingly portrayed by the Excel chart. The top owner, DOI BR, the U.S. Bureau of Reclamation, owns more stored water in California than the next fourteen top owners combined. This perhaps demonstrates vividly the immensity of the California Water Project, built mainly to irrigate the state’s farms. Another interesting observation from this chart is that one of the top fifteen owners appears to be a private individual: Who is “C. Bruce Orvis” and why does he own about a million acre-feet of water in the state? This observation could lead to further inquiry on large-scale private water ownership.

The Excel chart of dam building supports the Arcview view of dams by decade as well as the animation. Large peaks of dam completion are evident in the 1910’s, 1920’s, 1950’s and 1960’s, with a valley in the 1930’s and 1940’s. These peaks perhaps follow economic cycles to some extent, with the valley coinciding with the great depression, and the 50’s and 60’s peaks coinciding with the post-war economic expansion. The chart of dam purposes is complicated by the large number of purpose combinations and would need further refinement and simplification to be of much use; however, it does show the vague qualitative aspect of the top seven or so combinations (of several dozen) taking up the majority of dams. Producing this chart and looking at the database did bring up the interesting fact that the dam in the Hetch Hetchy valley, constructed by San Francisco in 1923, does not have listed as one of its purposes fire control; this is curious, since in the immense political struggle over its construction—exemplified by the war between John Muir and Gifford Pinchot—fire protection was cited as one of the primary motivations for its construction. Indeed, the issue of the damming of Hetch Hetchy valley only arose after the huge earthquake-induced fires which devoured San Francisco in 1905.

The previously mentioned dam building (by decade) animation allows the user a time-oriented intuitive feel for the progress of dam construction, as also reflected in the dams built per decade chart. Such a visualization tool helps to broaden viewers’ conceptualization of the evolution of dam construction through history. Upon viewing, the user may perhaps be startled by the large number of dams appearing in certain decades.

 

6         Conclusion

 

This project demonstrates the utility of GIS in public awareness, and hence policy and education, about natural resource use. The case examined, California dams, has been a rich subject matter because of the availability of extensive data about the dams in the National Inventory of Dams. The view examples produced for the project illustrate only part of the range of possibilities available for the presentation of historical and other complex data about large resource-oriented public projects. These views enable the user to develop an initial, intuitive understanding of the scope, scale and extent of dams in the state as well as some of the politics involved in the dams and water system. This information could be crucial as water continues to become a growing concern for California residents. Similar projects could be undertaken to demonstrate emergent aspects of other resource-oriented public works.

7         References

 

The California Department of Water Resources dam database:

http://elib.cs.berkeley.edu/kopec/b17/html/home.html.

The National Inventory of Dams:

http://crunch.tec.army.mil/nid/webpages/nid.cfm.

Schema for the National Inventory of Dams:

http://www.nws.noaa.gov/oh/hod_whfs/documentation/damcat_dict.html.

Marc Reisner, Cadillac Desert.