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July 10, 2007 NASA quarterly briefing Geoprocessing using GEOLEM and HSPF in the RPC Framework Vladimir Alarcon Chuck O’Hara.

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Presentation on theme: "July 10, 2007 NASA quarterly briefing Geoprocessing using GEOLEM and HSPF in the RPC Framework Vladimir Alarcon Chuck O’Hara."— Presentation transcript:

1 July 10, 2007 NASA quarterly briefing Geoprocessing using GEOLEM and HSPF in the RPC Framework Vladimir Alarcon Chuck O’Hara

2 July 10, 2007 NASA quarterly briefing GEOLEM Library of basic geoprocessing functions, e.g., “flow direction”, “reclassify” Library of complex geoprocessing logic, e.g., “make map of hillslopes”, “make map of affected areas” Knowledge handling infrastructure System to encode modeling knowledge into metadata Metadata handling infrastructure

3 July 10, 2007 NASA quarterly briefing GEOLEM and HSPF GEOLEM was customized to provide landuse and topographical parameters to be ingested by HSPF How was it modified? –GEOLEM main code: changes to include new schema files: config.xml concept.xml instance.xml –New methods codes were written: SlopeHspfMethod.java LanduseHspfMethod.java ReclassLanduseHspfMethod.java

4 July 10, 2007 NASA quarterly briefing GEOLEM and HSPF

5 July 10, 2007 NASA quarterly briefing GEOLEM and HSPF How was it modified? (continued) –New parameter java codes were written: LandUseHspfParameters.java SlopeHspfParameters.java ReclassHspfLanduseParameters.java –New providers to parameters: LandUseHspfParametersProvider.java SlopeHspfParametersProvider.java ReclassHspfLanduseParametersProvider.java

6 July 10, 2007 NASA quarterly briefing GEOLEM and HSPF

7 July 10, 2007 NASA quarterly briefing GEOLEM and HSPF How was it modified? (continued) –New commands were coded into existing JacobCommands class: SlopePercent TabulateArea ReclassHSPF

8 July 10, 2007 NASA quarterly briefing GEOLEM and HSPF

9 July 10, 2007 NASA quarterly briefing GEOLEM and HSPF How was it modified? (Version without changes)

10 July 10, 2007 NASA quarterly briefing GEOLEM and HSPF How was it modified? (changed version) getParam: HSPFLanduseArea getParam: HSPFSlope getParam: HSPFLanduseArea getParam: HSPFSlope return: Area return: Slope getDimension: Sub_basin return: Sub_basin Subbasin: HSPFslope Zonal Statistics: Slopes and landuse area per sub-basin ParamHspfSlope ParamHspfLanduseArea Now the user has the option of re-using EXISTING Delineated subbasins instead of delineating all over again several times OPTIONAL LandUseParam.dbf SlopeParam.dbf ASCII HSPF input files

11 July 10, 2007 NASA quarterly briefing HSPF in RPC Vladimir Alarcon Chuck O’Hara

12 July 10, 2007 NASA quarterly briefing GEOLEM Watershed boundary polygon Delineated watershed polygon Land use MODIS, VIIRS Topography SRTM GenScen WDMutil User Control Input file UCI LIS-generated data: Precip., ET, Soil Moist. Rainfall, ET, Soil Moisture time series Modified Land use Topography GEOLEMGEOLEM User’s domain Server’s domain How does HSPF fit into RPC?

13 July 10, 2007 NASA quarterly briefing HSPF in RPC How can HSPF be used within the RPC environment? –Study the effects of topographical datasets in hydrograph Some results were presented in previous briefings –Alarcon and O’Hara, 2006 –Alarcon, O’Hara et al., 2006 –Study the effects of landuse datasets in hydrograph Some results were presented in previous briefings –Diaz, Alarcon, O’Hara, et al. –For this quarterly report we have prepared what could be a typical RPC application using Geolem HSPF Concurrent effects of landuse and topographical datasets on streamflow hydrograph simulation in a coastal watershed

14 July 10, 2007 NASA quarterly briefing HSPF in RPC: research question Question: if NASA would like to design/launch/release a sensor/mission/product related with topographical and landuse data, what resolution would be useful for watershed hydrology modeling? A factorial experiment with existing LULC and topography datasets has been performed. GEOLEM was used to generate 12 concurrent scenarios of topographical/LULC cases for HSPF ingestion. HSPF was used to simulate streamflow hydrograph for each of these 12 cases. Those simulated streamflow hydrographs were compared to measured streamflow and the simulated- output reliability was assessed

15 July 10, 2007 NASA quarterly briefing HSPF in RPC: factorial experiment Topography\Landuse MODIS (1000 m) GIRAS (900 m) NLCD (30 m) DEM (300 m) NED (30 m) SRTM (30 m) IFSAR (5 m) Statistical indicators of fit between HSPF simulated streamflow and measured streamflow Nash-Sutcliff (NS) number Coefficient of determination R 2 Model reliability coefficient: Good fit when these coefficients are close to 1

16 July 10, 2007 NASA quarterly briefing Jourdan River: –Located in the Saint Louis Bay watershed (Mississippi Gulf coast) Largest contributor of flow to the Saint Louis Bay Drains 882 sq. km Average flow: 24.5 cms HSPF in RPC: Study area

17 July 10, 2007 NASA quarterly briefing HSPF in RPC: NED & NLCD (GOOD FIT)

18 July 10, 2007 NASA quarterly briefing HSPF in RPC: DEM & MODIS (BETTER FIT)

19 July 10, 2007 NASA quarterly briefing HSPF in RPC: fit between simulated and measured streamflow

20 July 10, 2007 NASA quarterly briefing HSPF in RPC: fit between simulated and measured streamflow

21 July 10, 2007 NASA quarterly briefing HSPF in RPC: fit between simulated and measured streamflow

22 July 10, 2007 NASA quarterly briefing Conclusions from the experiment The combination of low resolution topographical datasets (such as DEM, 300m) and low resolution landuse datasets (such as MODIS, 1000m) produce good statistical fit between simulated and measured streamflow hydrographs. Also: the finer the topographical grid (such as IFSAR, 5m) combined with coarse resolution landuse datasets (such as MODIS or GIRAS) seem to produce good statistical fit. Medium-resolution topographical datasets(such as SRTM or NED, 30m) combined with medium-resolution landuse datasets (NLCD, 30 m) give the lowest goodness of fit.

23 July 10, 2007 NASA quarterly briefing Future steps Include simulated VIIRS in similar topography/LULC and streamflow hydrograph assessments Include distributed meteorological forcings in the exploration: –NASA LIS precipitation –NASA LIS soil moisture –NASA LIS evapotranspiration


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