The “contributing area” concept is one of several basic concepts in modeling hydrologic processes used to explain storm runoff production. The main difficulty in using this concept of variable source areas is the identification and characterization of saturated areas according to the temporal and spatial variability during a storm event. In this experiment a helicopter‐borne C band scatterometer has been used to locate the saturated areas within a small watershed. In contrast to the general results, where radar cross section increases with soil moisture, calibration shows a backscatter coefficient decreasing for the high gravimetric water contents of the saturated areas, which may be due to the increasing importance of specular reflection processes. It appears that a threshold on the backscatter coefficient may be determined which would allow the location of saturated areas, independent of the nature of the field surface (vegetation cover or slope). These experiments, which were intended partly as ERS 1 satellite simulations, show that active microwaves may be a good tool for partial hydrology.
Wind speed and direction are parameters that affect forest fire propagation dramatically. So, an accurate estimation of such parameters is crucial to predict the fire propagation precisely. WindNInja is a wind field simulator that can easily be coupled to a forest fire propagation simulator such as FARSITE. However, wind field simulators present to main drawbacks: They take too much time to compute the wind field and they require a lot of memory. So, a map partitioning strategy has been developed to compute partial wind field maps that can be aggregated afterwards. Each map part can be computed in parallel and the amount of memory required is available in a single node. In this work a methodology to determine the most adequate map partitioning is presented. The map part shape, map part size, amount of overlapping and number of parts have been studied considering execution time and effects on wind field estimation. The results are based on a wide experimentation and are validated with real case scenarios.
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