Natural Resources Modeling Using the Spatial Sciences

NON-TECHNICAL SUMMARY: A unique modeling approach for evaluating the effects of conservation practices on water quality from farm level to watershed scales, using established hydrologic and water quality models with geographic information systems (GIS) is needed. The tools and techniques developed in this project will be very helpful to evaluate alternative techniques and technology available to assess water quality impacts due to various land management scenarios.

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APPROACH: Objective 1: One of the important attributes of the field scale and watershed scale modeling linkages is to analyze the spatial and temporal impacts of various BMPs. The EPIC/APEX and SWAT models simulate processes such as hydrology, erosion, water quality, soil water interaction, crop growth and management on a daily time step (high temporal resolution) and continuously. The GIS capabilities available with the SWAT model allows for the study of the spatial variability associated with hydrologic processes at high resolutions (e.g. 30m resolution). These capabilities make the proposed modeling approach advantageous for this study in terms of analyzing the spatial and temporal issues associated with conservation practices implemented in a watershed. Unlike monitoring data based evaluation, with this proposed modeling approach, several what if questions can be answered and scenarios analyzed to support the decision-makers. The modeling approach is time-saving, cost-effective, repeatable and scalable in this regard. For example, in addition to the existing conservation practices implemented in watersheds, the effects of additional conservation practices can be evaluated as follows: - the effect of implementing alternative or additional conservation practices in a watershed, and targeting these practices in critical areas in order to maximize benefits - the effect of implementing existing practices in different locations so as to maximize benefits - the effect of implementing the current conservation practices over larger areas Objective 2: A real-time system has been developed for estimation of daily KBDI from remotely sensed data using Arc Macro Language (AML) scripts in ESRIs ArcInfo software. An automatic data processing system has been developed using PCI Geomatics remote sensing software to process NOAA 14 and 15 data for radiometric, geometric, and atmospheric corrections and computing NDVI and LST. In addition, algorithms developed by various researchers have been refined and are used for cloud detection. During cloudy days (cloud cover > 30%) it may not be possible to get maximum air temperature estimates from the AVHRR satellites. On these days maximum air temperature measured at sixty NWS weather stations across Texas is interpolated using a Regular Spline method, available in the ArcInfo system. The resulting maximum air temperature is used as a replacement for the satellite data during cloudy days. Stage III NEXRAD data is collected and archived by the NWS. The stage III data, obtained from the NWS River Forecasting Center (RFC) in Fort Worth, TX through a cooperative arrangement, is in an HRAP grid system, whereas the rest of the data are in a regular grid system. Hence, the precipitation data is remapped to the regular grid system using the ArcInfo. Once all of the input data is prepared, KBDI is computed using AML scripts, again, in ArcInfo. This entire system is completely automated and no longer requires manual data processing. Once the KBDI information is processed, it is distributed to forest fire managers across Texas through the World Wide Web (WWW) at http://twc.tamu.edu.