Chang, Chia-LingChia-LingChangLo, Shang-LienShang-LienLoChen, Ming-YingMing-YingChen2009-01-142018-06-282009-01-142018-06-28200701676369http://ntur.lib.ntu.edu.tw//handle/246246/96863https://www.scopus.com/inward/record.uri?eid=2-s2.0-33847644589&doi=10.1007%2fs10661-006-9268-8&partnerID=40&md5=11a097f3b8063ed4af663b5a0b534ea3Negligence to consider the spatial variability of rainfall could result in serious errors in model outputs. The objective of this study was to examine the uncertainty of both runoff and pollutant transport predictions due to the input errors of rainfall. This study used synthetic data to represent the "true" rainfall pattern, instead of interpolated precipitation. It was conducted on a synthetic case area having a total area of 20 km2 with ten subbasins. Each subbasin has one rainfall gauge with synthetic precipitation records. Six rainfall storms with varied spatial distribution were generated. The average rainfall was obtained from all of the ten gauges by the arithmetic average method. The input errors of rainfall were induced by the difference between the actual rainfall pattern and estimated average rainfall. The results show that spatial variability of rainfall can cause uncertainty in modeling outputs of hydrologic, which would be transport to pollutant export predictions, when uniformity of rainfall is assumed. Since rainfall is essential information for predicting watershed responses, it is important to consider the properties of rainfall, particularly spatial rainfall variability, in the application of hydrologic and water quality models. © Springer Science+Business Media, B.V. 2006.application/pdf425538 bytesapplication/pdfen-USPrecipitation; Rainfall; Spatial variability; Uncertainty; Watershed response[SDGs]SDG6Gages; Hydrology; Mathematical models; Precipitation (meteorology); Runoff; Storms; Water quality; Pollutant transport; Rainfall gauge; Spatial variability; Watershed response; Watersheds; rain; runoff; hydrological modeling; pollutant transport; precipitation (climatology); precipitation assessment; raingauge; runoff; spatial variation; watershed; analytical error; article; controlled study; information processing; precipitation; prediction; uncertainty; water pollutant; water quality; watershed management; Environmental Monitoring; Geography; Models, Theoretical; Rain; Taiwan; Uncertainty; Water Supplyjournal article171712912-s2.0-33847644589http://ntur.lib.ntu.edu.tw/bitstream/246246/96863/1/91.pdf