Surface Water Hydrology Technical Committee – författare

Radar Rainfall Data Estimation and Use, MOP 139, provides a detailed look at the basic philosophy and principles for estimating radar rainfall data and analyzing data. Radar-derived rainfall estimation is one of the most significant recent advances in hydrologic engineering and practice. Manual of Practice 139 provides a framework for researchers and practicing engineers working in hydrologic engineering to develop radar rainfall data sets and analyze them according to their varied goals and resources. This manual will be a valuable resource for government agencies, engineering firms, and practicing engineers working in the hydrologic engineering field.|Radar Rainfall Data Estimation and Use, MOP 139, provides a detailed look at the basic philosophy and principles for estimating radar rainfall data and analyzing data. Radar-derived rainfall estimation is one of the most significant recent advances in hydrologic engineering and practice. Manual of Practice 139 provides a framework for researchers and practicing engineers working in hydrologic engineering to develop radar rainfall data sets and analyze them according to their varied goals and resources. This manual will be a valuable resource for government agencies, engineering firms, and practicing engineers working in the hydrologic engineering field.|Prepared by the Standard Practice on Radar Rainfall Estimation Task Committee of the Environmental and Water Resources Institute of ASCERadar Rainfall Data Estimation and Use, MOP 139, provides a detailed look at the basic philosophy and principles for estimating and analyzing radar rainfall data and analyzing data. Radar-derived rainfall estimation is one of the most significant recent advances in hydrologic engineering and practice. Rain gauges provide point values of rainfall depth and intensity but are not cost effective in providing information about the spatial distribution of rainfall, whereas radar-derived rainfall data provides a density of measurements that are not obtainable by rain gauges alone. Combining these two sensor systems produces better rainfall estimates that more accurately characterize rainfall across a watershed. This Manual of Practice provides a framework for researchers and practicing engineers working in hydrologic engineering to develop radar rainfall data sets and analyze them according to their varied goals and resources. Topics includeAn introduction to and examples of radar rainfall estimation, Temporal and spatial characteristics of radar rainfall data,Methodology for radar rainfall data quality evaluation and improvement,Use of radar rainfall data in hydrologic modeling,Rainfall data augmentation and design of rainfall monitoring networks, andExamples of radar rainfall data analysis and data applications.MOP 139 will be a valuable resource for government agencies, a framework for engineering firms, practicing engineers, researchers, and students working in the hydrologic engineering field.