Summary
Radar provides high-resolution input of spatially and temporally variable inputs. Rain gauge networks are used alone or together with radar to provide representative rainfall over a watershed. Understanding how radar measures rainfall requires a probabilistic view of rainfall that describes the distribution of drop sizes per unit volume of the atmosphere. Both radar reflectivity and rainfall rate are sensitive to drop size distributions. The relationship between reflectivity and rainfall is expressed by the Z-R relationship. Once an appropriate Z-R relationship is applied, systematic error known as bias is removed by comparison with rain gauges. Rain gauge adjustment of radar removes the bias while random errors remain. The advantage of radar over rain gauge networks is the density of measurement. Combined use of radar and gauge networks produces more accurate precipitation measurements. Considering the importance of rainfall input to both distributed and lumped models, radar rainfall is proving to be a significant advance in hydrologic modeling.
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(2004). Precipitation Measurement. In: Distributed Hydrologic Modeling Using GIS. Water Science and Technology Library, vol 48. Springer, Dordrecht. https://doi.org/10.1007/1-4020-2460-6_8
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