Floods in a Changing Climate: Extreme Precipitation by Ramesh S. V. Teegavarapu

By Ramesh S. V. Teegavarapu

Dimension, research and modeling of maximum precipitation occasions associated with floods is essential in knowing altering weather affects and variability. This booklet offers tools for evaluation of the developments in those occasions and their affects. It additionally offers a foundation to advance tactics and directions for climate-adaptive hydrologic engineering. educational researchers within the fields of hydrology, weather switch, meteorology, environmental coverage and probability overview, and pros and policy-makers operating in danger mitigation, water assets engineering and weather model will locate this a useful source. This quantity is the 1st in a suite of 4 books on flood catastrophe administration concept and perform in the context of anthropogenic weather swap. The others are: Floods in a altering weather: Hydrological Modeling by means of P. P. Mujumdar and D. Nagesh Kumar, Floods in a altering weather: Inundation Modeling via Giuliano Di Baldassarre and Floods in a altering weather: chance administration through Slodoban Simonović.

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The attenuation of the radar’s signal is greater at shorter wavelengths, and hence the range is shorter; however, a smaller, cheaper dish and installation is required. Most operational weather radars are either C-band or S-band, although X-band radars are sometimes used to fill in gaps locally in the national network (Sene, 2009). gov/). Exhaustive discussion about radar-based precipitation measurements can be obtained from reference books by Raghavan (2003), Meischner (2005), and Strangeways (2007).

Z = aR b ) via optimization considering the realized storm events. The minimum and maximum values of coefficients and exponents need not be fixed a priori for optimization formulations. Improved estimates of precipitation can be realized when a temporal window preceding the window in which the optimal relationship of Z–R is applied. In real time, this information about the window will depend on the amount of information available about the elapsed time interval with observed precipitation at rain gages.

13) where θim is the estimated rainfall rate at a rain gage station; no is the number of candidate events or all the events available in the database for which reflectivity and rainfall rate data are available; a and b are the coefficient and exponent values in the Z– R relationship; au is the upper bound on the coefficient and bu is the upper bound on the exponent; Zi is the reflectivity; and φˆ im is the observed rainfall rate at a gage. The above formulation can be used to obtain the optimal coefficient and exponent values.

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