This site allows the user to download climate and hydrology modules to be used with the SLEUTH urban growth model developed by Professor Keith Clarke at the University of California, Santa Barbara. This model can be accessed at http://www.ncgia.ucsb.edu/projects/gig/. The work presented below enhances the urban growth model's abilities. The new modules provide a means for assessing the impacts of urban change on local surface temperature, soil moisture and stormwater runoff. This information can allow the user to determine a more sustainable level of future development for a region. The modules are:
1) CLIMATE CHANGE
2) BASIN SCALE RUNOFF TO RAINFALL RATIO
3) SCS DIRECT RUNOFF PER PIXEL
Brief explanations of each module are given below. The header for each provides a link to a site with that module's actual code, which can then be downloaded. Detailed instructions and examples for each module are also given on its linked site. The code is C++ and has been run under NT with Borland compilers and on a Sun sparc 10, Solaris 7. To move files between the SLEUTH model and the climate and hydrology modules, Keith Clarke has provided two algorithms that are compiled with a Makefile. These can be downloaded from the "Data Preparation" link below. To download the landuse maps that were used in developing these modules, click here. Any questions or comments about this work should be addressed to tnc@essc.psu.edu.
The SLEUTH model output includes land use maps in the form of gif images for each year of predicted growth. These images form the basis for running the climate and hydrology modules. Algorithms are provided for converting the gif images to the ascii format required by the modules, as well as returning the module outputs to a visualizable gif format. Anyone ready to run the climate and hydrology modules with SLEUTH output should start with this Data Preparation link. The user should note that both the SLEUTH model and the associated modules presented here require a good deal of data processing and organization by the user, as well as basic familiarity with GIS manipulations.
This module has evolved from work with Landsat TM and NOAA AVHRR satellite data. Analysis of urbanizing areas in southeastern Pennsylvania demonstrated that urban development induces predictable changes in the local microclimate, as long as certain features of the development are known. Specifically, the vegetation changes that accompany the development must be noted, as well as the initial climatic state of the land parcel. For example, development of a landscaped subdivision on dry, barren agricultural fields will have a different climatic response than the development of a commercial shopping center on land that was previously forested. Such facts are reflected in the choice of independent variables for the multiple linear regression analysis that was used to develop the predictive equations within the climate module.
Climate layers can be generated for each year of the SLEUTH model's predicted land use. The scaled surface temperature, fractional vegetation cover and evapotranspiration fraction (an indicator of surface moisture) are estimated for each 1-km2 land parcel. As regions experience significant urban growth, their climate variables are updated. The user of the module is able to establish the type of development that occurs; choices are given ranging from a strong impact on the local vegetation to the most 'friendly' form of development - that which actually increases the vegetation. The module outputs ascii files that contain each land parcel's actual climate values, as well as gif images for visualization purposes.
RUNOFF TO RAINFALL RATIO MODULE
This module is based on techniques that were developed for quantifying the effects of urbanization on the surface hydrology at a watershed scale using both satellite and ground-based data. Eleven southeast Pennsylvania basins, ranging in size from 5 to 325 square miles, were examined over a 10-year period. The urbanization process was monitored using satellite imagery and its derivative land cover maps. Corresponding streamflow and precipitation data were then used to determine the general ratio of stormwater runoff to rainfall for each basin, along with any changes in this ratio over time. These plots of runoff vs. rainfall for gauged basins were interpreted in terms of the proportion of the basin contributing to a storm event's runoff signal. For a particular basin, four distinct runoff responses separated by season and antecedent moisture conditions were noted.
During the non-summer months under typical antecedent moisture conditions, the ratio of runoff to rainfall was found to be most representative of and responsive to a basin's land use patterns. For a given basin, this particular ratio can be associated with the proportion of urbanized, forested and agricultural land, as well as the size of the basin and various measures of the basin's terrain. The ratio can thus be estimated for each year of the SLEUTH model's predicted land use. The module output is in the form of a text file that summarizes each year's landuse patterns and the runoff to rainfall ratio. Increases in a watershed's runoff response will indicate when a basin, with its predicted growth patterns, starts to lose more and more of its precipitation input to storm runoff from the basin outlet within 24 hours of typical rain events. This loss of water from the system could lead to soil moisture deficits and vegetation stress, less comfortable local climates, lower stream flows during dry periods, increased water shortages and a greater reliance on imported sources.
This module is based on the Soil Conservation Service's (SCS) curve number (CN) method. This technique, now technically that of the Natural Resources Conservation Service, was introduced by the USDA in the mid-1950s and is one of the most widely used direct runoff estimation techniques. Its purpose here is to provide within-basin resolution of surface runoff. The user specifies a 24-hour design storm depth, and for each year of SLEUTH predicted land use, the module estimates the direct runoff depth per grid cell. This addition to the SLEUTH model can thus help to identify sites where, in future growth scenarios, localized flooding could become a problem due to land use change.
The module requires information on the hydrologic characteristics of the study site's soils, as well as a table of curve numbers. The user has the option to 1) work with layers that specifically designate the percentage of each of the hydrologic soils groups per pixel or 2) designate a typical hydrologic soil class for the entire basin. A standard curve number table based on land types that are compatible with the SLEUTH model output is included as part of the module; the curve numbers within this table are based on typical literature values for Pennsylvania. Alternatively, the user has the option to input new CN values that have been calibrated for their study region. The module outputs ascii files that contain each grid cell's actual direct runoff depth, as well as gif images for visualization purposes.