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<br />Data Sources <br /> <br />- <br />17 <br /> <br /> <br />directly measured by current meter surveys or are estimated by rating-curve <br />extension or indirect measurement techniques (Rantz and others, 1982). Jarrett <br />(1987) stresses the need to assess the reliability of extreme flood data, particularly <br />data collected before 1950. <br />Flood frequency analysis of systematic flood data typically assumes that the <br />data are independent and identically distributed in time (i.e., temporally uncorrelated <br />and stationary). Local human activities, such as land use changes or reservoir <br />construction, or climate change (regional or global) can make this assumption <br />untenable. There are relatively few gaged streams on watersheds that have not been <br />affected to some degree by human activities. At the same time, there are relatively <br />few cases where human impacts on flood magnitude and frequency have been <br />carefully documented. Lins and Slack (J 999) evaluated flood data from watersheds <br />that are considered to be relatively unimpacted by local human activities and did not <br />find compelling evidence of climate-induced non-stationarity for floods. Note, <br />however, that it is vel)' difficult to detect climate-induced non-stationarity in flood <br />data because of the high variability (Jarrett, 1994). <br /> <br />Precipitation Data <br /> <br />The National Weather Service is responsible for maintaining a network of <br />meteorological stations in the United States. The current network includes about 300 <br />primary stations staffed by paid technicians and over 8,000 cooperative stations <br />operated primarily by volunteers (NRC, 1998b). As of 1975 there were about 3,500 <br />non-recording precipitation gages with records of 50 years or more (Chang, 1981). <br />Precipitation data are published in Climatological Data and Hourly Precipitation Data <br />by the National Oceanic and Atmospheric Administration (NOAA). Digital records <br />can be obtained from the National Climatic Data Center, from regional climatic <br />centers, and various vendors. Note that many digital records do not include data <br />collected prior to 1940. <br />Another source of extreme precipitation data for the United States is a <br />catalog of extreme stonns maintained by the U.S. Anny Corps of Engineers, the US. <br />Bureau of Reclamation, and the National Weather Service. This catalog includes <br />infonnation on over 300 extreme stonns including the 1862 stonn in California and <br />the Pacific Northwest. For each stonn in the catalog, official climatic data as well as <br />rainfall bucket survey data (if available) were compiled and stonn characteristics <br />analyzed. It should be noted that extreme stonns and floods are not as well <br />documented today as they were in the past, in spite of technological improvements <br />that greatly facilitate such documentation. <br />Precipitation data are subject to large errors. The most serious problem is <br />the undenneasurement at all operational precipitation gages by amounts that depend <br />primarily on the type of gage (including wind shield), exposure, wind speed, and <br />whether the precipitation is rain or snow. Precipitation measurements during <br />snowfalls are particularly biased. For example, during a snowfall a wind-shielded <br />gage typically undenneasures precipitation by about 40% in a wind of 25 km/hr <br />(Larson and Peck, 1974). In the case of a systematic rainfall record, the problem may <br />be exacerbated if the location and type of precipitation gage is changed during the <br />