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PROJECT APPROACH <br />The data inventory step is an essential precursor to establishing a reasonable scope and data <br />collection strategy that fits within the available project resources. Riverside and AMEC <br />anticipate that more data sources will be inventoried than are included in the Phase I Flood DSS. <br />Data sources that cannot be integrated within available project resources maybe re-evaluated in <br />Phase IL <br />Riverside and AMEC will contact the data sources listed in the prototype data inventory to <br />determine if more recent data layers are available for the NFIP and Weather Modification data <br />categories. <br />Riverside assumes that including flood maps, historical flood data, and flood control structures in <br />the Flood DSS is a fixed requirement of the system. Therefore, little work will be done under the <br />data inventory for these data types; rather, most of the effort will be spent in the Data Collection <br />task to assemble available DFIRMs and call county and local personnel to identify available <br />datasets. <br />For the prototype Flood DSS, Riverside utilized base data layers and some operational data from <br />the CDSS. Depending on the technologies that are selected for the Phase I Flood DSS, this <br />approach may be retained, or external web services may be utilized instead, mostly for base data. <br />As requested in the RFP, Riverside will re-evaluate the Flood Outlook data category. Based on <br />the data included in the prototype, this is the category that is the most dynamic, requiring <br />frequent updates to display current hydrologic and flood outlook conditions. In addition to <br />including the snow water equivalent (SWE) data grid from the Snow Data Assimilation System <br />(SNODAS), .Riverside recommends evaluating the snowmelt and sublimation data grids for <br />inclusion in the Flood DSS. From a hydrologic perspective, a combination of streamflow, <br />current SWE conditions, recent changes in SWE, snowmelt, and sublimation losses for a given <br />location can provide information about whether recent snowpack changes are likely to translate <br />into significant streamflow that may pose a flood threat. For example, Table 4-3 shows summary <br />streamflow and snowpack information for six gages in the Upper Rio Grande Basin. The one- <br />week summary information from SNODAS shows that the area is both melting and accumulating <br />snowpack, and that significant sublimation losses have occurred over the past week. <br />Table 4-3. SNODAS Summary for the Upper Rio Grande Basin <br />U per Rio Grande Basin SNODAS Snow ack Summa <br />Februar 18 -Februar 25, 2009 <br />Value [ac-ft] CONMOGCO PINDELCO SANORTCO CONPLACO RIODELCO LOSORTCO <br />Current SWE 284 999 45 711 73,266 51 616 787 363 136,012 <br />1-Week SWE Chan a 11 353 1,734 -299 2 429 35 346 5 088 <br />1-Week snowmelt 2 734 319 2775 0 6347 2503 <br />1-Week Sublimation Loss 4 100 1 303 1942 528 15 136 2902 <br />1-Week streamflow 1,241 112 1,147 0.1 12,193 429 <br />Many of the SNOTEL stations in the state have been equipped with soil moisture sensors <br />(Figure 4-5). Riverside recommends that these data be considered for inclusion in the Flood <br />DSS, in addition to the SWE observational data, since soil moisture is a significant predictor of <br />runoff. <br />DNR RFP PDA-923 36 R I V E R S I D E <br /> <br /> <br />n <br />~' <br /> <br />n <br /> <br /> <br /> <br /> <br /> <br /> <br />n <br /> <br /> <br />it <br />