作者: Jeffrey C. Davids , Nick van de Giesen , Martine Rutten
DOI: 10.1007/S00267-017-0872-X
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摘要: Hydrologic data has traditionally been collected with permanent installations of sophisticated and accurate but expensive monitoring equipment at limited numbers sites. Consequently, observation frequency costs are high, spatial coverage the is limited. Citizen Hydrology can possibly overcome these challenges by leveraging easily scaled mobile technology local residents to collect hydrologic many However, understanding how decreased observational impacts accuracy key streamflow statistics such as minimum flow, maximum runoff To evaluate this impact, we randomly selected 50 active United States Geological Survey gauges in California. We used 7 years historical 15-min flow from 2008 2014 develop values for each gauge. mimic lower observations, developed a bootstrap randomized subsampling replacement procedure. calculated same statistics, their respective distributions, subsample iterations four different frequencies ranging daily monthly. Minimum flows were estimated within 10% half 39 (daily) 23 (monthly) only 0 Runoff volumes 44 12 Watershed flashiness most strongly impacted estimates subsampled data. Depending on questions being asked, observations provide useful information.