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<br />that give poor results, the model will eventually get to the parameter sets that give the most <br />reasonable results. Then, holding the most reasonable parameters fixed, you can move to <br />another event, simulate the variability and reject parameter values of the 2D model that don't <br />simulate well. And so on. <br /> <br />F2D Model Peak Flow Sensitivity: <br />Also showed example from the weather service remote sensing group in Minnesota. With <br />detailed floodplain DEM one can represent the probability of flooding for these events to show <br />areas that would be inundated under different scenarios. For example, assuming a given <br />overland or channel "n" (Mannings coefficient) is reasonably well known for a base case, then <br />we can look at variations in the system given different conditions such as initial soil moisture <br />conditions (dry curve shifts left, wet curve shifts right), hydraulic conductivity (slope of curve), <br />etc. In this example, for CDF = 0.5, peak flow estimates vary from - 45 m3/s (dry initial <br />conditions) to -80 m3/s (wet initial conditions) which is the kind of variability expect to see in <br />natural systems. <br /> <br />GIS for floodplain modeling: <br />This slide shows the intersection of flooding with the parcel information. It is an understandable <br />display because it is "visually intuitive." Using the best data available, we have a pretty good <br />idea where people live and can show the likelihood of a particular person's home being flooded. <br />Combined with a GIS Atlas this seems "more real" to most people. The risk of flooding can be <br />assessed for variations in terrain or hydraulic conditions and for multiple events including the <br />100- or SOO- Year Flood. And because it's all in an internally consistent GIS, then with the use of <br />computers it is fairly easy to update. Note: Alluvial fan hydrology requires detailed topography <br />because it is necessary to do detailed modeling. To adequately represent flooding in this situation <br />it is not just who is getting wet and who is not but need to know the statistical likelihood of <br />amount of flooding. <br />Alison commented: FEMA should like this approach because it does most of the work for the <br />newly mandated 6yr updates... think about stating this in the proposal to FEMA. <br /> <br />GIS for floodplain management: <br />Building on the GIS-Atlas (using the best data available for credibility), the hydrology and the <br />modeling, we could represent various mitigation measures at different locations and what their <br />effectiveness is. No more "data-wars". . .. Again because the risk is well modeled and the model <br />results are "visually intuitive." <br /> <br />Need to show: where people live, who might be flooded, likelihood of an event (50-, 100-, SOO- <br />yr events or whatever), terrain, hydraulics (reasonable degree of inundation) <br /> <br />GIS for Public Involvement: <br />Open access to information builds peoples' confidence and leads to consensus. A high quality <br />atlas leads to issues clarification, supports the "open debate" process such as is <br />common/necessary in Boulder and can help avert misunderstandings among the general public. <br />Use of the web to present data and modeling results will aid the process of understanding and <br />can help reduce both community and policymaker distrust. It can bring you to the heart ofthe <br /> <br />4 <br /> <br />