WMS:Stochastic Modeling: Difference between revisions
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The following steps outline the process for developing a stochastic model of floodplain boundaries using WMS, HEC-1, and HEC-RAS. | The following steps outline the process for developing a stochastic model of floodplain boundaries using WMS, HEC-1, and HEC-RAS. | ||
:1.[[WMS: | ===Develop a hydrologic model with HEC-1=== | ||
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The HEC-1 Interface tools in WMS can be used to develop a working HEC-1 model. It is important that this model be running effectively (i.e. calibrated and/or adjusted to give credible results) prior to using it for the Stochastic Modeling simulation. | |||
The only parameters at this point that can be varied within a range of probable answers are rainfall and CN (curve number for the different basins. This is done by setting the [[WMS:Basin HEC-1 Cards#Precipitation...|precipitation]] or [[WMS:Basin HEC-1 Cards#SCS Loss Method (LS)|CN]] to be a negative number in their respective dialogs. This negative number is a key number and should be unique for each stochastic variable you create. When running the stochastic simulation WMS will substitute the simulation specific parameter for the defined key. You can then setup a stochastic variable for HEC-1 in the ''Stochastic Run Parameters'' dialog. A key value (matching the key you defined in the materials property) starting value, min value, max value, standard deviation and distribution type. | |||
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Revision as of 21:44, 20 February 2013
There is always a great deal of uncertainty in hydrologic and hydraulic modeling and the parameters that are used to develop solutions. Despite this, a typical flood plain boundary is black and white in that you are either in or out of the flood plain. A good engineer might be able to dispute a flood plain boundary by performing a hydrologic/hydraulic analysis with a set of equally probable parameters that results in a difference in the flood plain delineation. Until recently, computer programs lacked the ability to consider multiple probable answers and report a probabilistic floodplain boundary, but with the Stochastic Modeling tools in WMS this is possible using a combination of HEC-1 for hydrologic analysis, HEC-RAS for 1D hydraulic river modeling, and the WMS flood plain delineation tools.
You can "connect" the results of HEC-1 to a developed HEC-RAS model and then run them as many times consecutively, with the results of the HEC-1 analysis feeding the boundary conditions for an HEC-RAS model. Certain parameters (at this point only basin CN and precipitation within HEC-1, and Manning's roughness within HEC-RAS) can be varied within a range of reasonable values using Monte Carlo or Latin Hypercube simulations in order to create a number of simulations. The results of each HEC-RAS model can then be used to delineate a series of flood plains. The combination of all floodplains can then be examined in order to derive a "probabilistic" flood plain where a region flooded by 100% of the model simulation combinations can be distinguished from an area that is flooded by only 50% of the models as shown in the figure below:
The following steps outline the process for developing a stochastic model of floodplain boundaries using WMS, HEC-1, and HEC-RAS.
Develop a hydrologic model with HEC-1
The HEC-1 Interface tools in WMS can be used to develop a working HEC-1 model. It is important that this model be running effectively (i.e. calibrated and/or adjusted to give credible results) prior to using it for the Stochastic Modeling simulation.
The only parameters at this point that can be varied within a range of probable answers are rainfall and CN (curve number for the different basins. This is done by setting the precipitation or CN to be a negative number in their respective dialogs. This negative number is a key number and should be unique for each stochastic variable you create. When running the stochastic simulation WMS will substitute the simulation specific parameter for the defined key. You can then setup a stochastic variable for HEC-1 in the Stochastic Run Parameters dialog. A key value (matching the key you defined in the materials property) starting value, min value, max value, standard deviation and distribution type.
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