The traditional role of hydrologic models has been to estimate and predict water quantities, flow rates, water constituents, and to assess the effectiveness of Best Management Practices (BMPs). Hydrologic models are mostly used in the research stage of environmental projects. They provide information for development of new hydrologic designs or evaluation of existing designs. Models often supplement or replace on-site monitoring because of the expensive and time-consuming nature of monitoring. The people most likely to use hydrologic models are engineers and scientists with professional backgrounds in hydrology. These users become adept at overcoming the three big challenges of traditional hydrologic modeling; compiling the proper input files, running the model to create output files, and evaluating the output files. Within this traditional role, the public audience for most environmental projects rarely appreciates the hydrologic modeling accomplished behind the scenes.
However, as local officials and the general public become more active in environmental projects, hydrologic modeling is beginning to take on an educational or outreach role. Concerned citizens not only want to know what water quantity and quality levels are extreme, but how they became extreme. This requires improving their understanding of hydrology. Hydrologic models provide a way to improve this understanding by predicting water constituent levels for varying inputs. Existing hydrologic models, however, are too involved for the general public to learn and understand, because of the challenges of creating the input, running the model, and evaluating the output.
In an educational role, existing hydrologic models must be modified to overcome these challenges. First, the input to educational hydrologic models must be simplified, making use of pre-existing file sets built around specific educational standards. Users then choose the file sets geared toward their areas of interest. Second, running the model should be made as simple as possible. Third, the output from the model should be portrayed clearly and concisely, with examples and interpretative help. In addition, the entire model should be easy to use.
One way to overcome these challenges for educational hydrologic models is the use of the Internet, specifically the World Wide Web and web browsers. Web pages can easily accommodate features, like graphic user interfaces, that work on multiple computer platforms. This eliminates the need for model installation. Through the use of HTML coding and techniques like CGI scripting, JavaScripting, and Java, web pages can be constructed to do the computations needed for hydrologic models. The one major drawback of using the Internet is the difficulty of file input and output functions. Due to security and memory issues, current web-based modeling techniques require inputs to be hard-coded directly into the web page.
Another challenge of Internet-based hydrologic modeling is speed. The time it takes a web page to load in a browser depends on the speed of the Internet connection, the computer speed and platform of the user or the client, the setup and speed of the sending or server computer, and the size of the web page. Add to this the typical amount of time it may take a hydrologic model to run, and the client may have to wait hours for model output. Fortunately, there are several techniques to increase the speed. First, a web page can make use of client-side techniques like JavaScripting, which put the computing load on the client's computer, not the overburdened server. Second, models can be smaller or modular. Instead of having one model calculate all of the pertinent outputs, several sub-models can be developed which calculate only a select set of outputs. When the client requires only one particular output, the web page can use the proper sub-model. Third, output display can be simplified. For instance, if the client is only interested in whether a particular BMP caused a decrease in some water constituent level, the model can be constructed to only determine an increase or decrease in the level. Similarly various data visualization methods can be used to simplify or enhance model output for improved understanding. Fourth, the models can utilize techniques which increase calculation speed, like fuzzy logic or artificial neural networks. All of these techniques can help develop Internet-based hydrologic models which satisfy their emerging role as educational tools.
This research builds on the above-cited ideas by developing the Internet Watershed Educational Tool or InterWET. Geared toward local officials and concerned citizens, InterWET helps educate people about water resources, using the Spring Creek Watershed in central Pennsylvania as a case study. InterWET contains a series of web pages which cover runoff, groundwater, sediment, in-stream nutrients, and fish populations from the perspectives of a researcher, a conservationist, and a local official.
The next three chapters consist of three papers which cover different aspects of the development of InterWET. Chapter 2 looks at the theoretical development of InterWET. It focuses on the educational theory behind the design of InterWET and its application for general watershed education and for the Spring Creek Watershed. Chapter 3 presents the techniques available for hydrologic modeling on the Internet. Different client-side and server-side techniques are compared and contrasted. In addition, Chapter 3 details the combinations of techniques used by InterWET and several other Internet-based hydrologic modeling web pages. Chapter 4 give a description of the design and implementation of artificial neural networks to predict water resources changes for the local official perspective of InterWET. These three chapters taken together give a complete description of the educational theory, Internet techniques, and hydrologic modeling used to develop InterWET.
Chapter 5 provides a user’s guide to InterWET and use of the InterWET web site, completing the description of InterWET. Chapter 6 gives a summary of the conclusions of the three papers and areas of future research based on InterWET. Appendices A-C give the details and the references behind each water resource component for each perspective. Appendix D (on the computer disk in the pocket attached to the back cover) contains copies of the files used for the InterWET web site.