Rain and rainfall

This study focuses on developing optimization models to estimate missing precipitation data at twenty-two sites within Kentucky State. Various optimization formulations and regularization models are explored in this context. The performance of these models is evaluated using a range of performance measures and error metrics for handling missing records. The findings revealed that regularization models performed better than optimization models. This superiority is attributed to their ability to reduce model complexity while enhancing overall performance. The study underscores the significance of regularization techniques in improving the accuracy and efficiency of precipitation data estimation.

CASCADE 2001 is a multi-basin flood routing program used in areas of flat terrain. CASCADE was used for different situational elements including the Florida Keys, Broward County, and Pensacola. The goal for this screening tool was to create flood inundation watershed mapping for the Florida Division of Emergency Management (FDEM). After showing the risks of flooding that could occur in Florida, the thought of how useful CASCADE can be in other environmental conditions. The Rocky Mountains were selected to show the effect of flood inundation that can be mirrored in an opposite condition from prior experimentation. We chose to test this program in an area with mountainous terrain like the region of Grand Lake, Colorado.
Rainfall, in collaboration with groundwater tables, ground soil storage and topography have the most effect on the CASCADE modeling program. Effects that were not used in the Florida models but added for Grand Lake included snowmelt. Snowmelt in the Rocky Mountains affects the flow of the Colorado River causing excess discharge that flows throughout the valleys and into Shadow Mountain Lake. WINSRM was a recommended model that could be used to simulate snowmelt during different months of Colorado’s spring season. The effects of snowmelt and rainfall flooding can be compared in relation to each other.

Rain attenuation is the most dominant cause of signal degradation in satellite links operating at Ka-band. A review of rain measurements and effects of rain attenuation on satellite links will be discussed and will be followed by the latest developments in prediction and modeling of rain attenuation. Then an adaptive rain fade countermeasure based on the effective utilization of the channel capacity will be presented. In order to determine the outage rates both in terms of channel capacity and bit error rate (BER), Manning's rain attenuation prediction model, based on the rain history of the transmitting and receiving stations, will be employed. Finally, a comprehensive statistical model for Land-Mobile Satellite Systems (LMSS) in the presence of rain attenuation will be proposed.

Accuracy in estimation of precipitation can be achieved by utilizing the combination of spatial radar reflectivity data (Z) and the high resolution temporal rain gage based rainfall data (R). The study proposes the use of optimization models for optimizing the Z-R coefficients and exponents for different storm types and seasons. Precipitation data based on reflectivity, collected from National Climatic Data Center (NCDC) and rain gage data from Southwest Florida Water Management District (SWFWMD) over same temporal resolutions were analyzed using the Rain-Radar- Retrieval (R3) system developed as a part of the study. Optimization formulations are proposed to obtain optimal coefficients and exponents in the Z-R relationships for different seasons and objective selection of storm-type specific Z-R relationships. Different approaches in selection of rain gage stations and selection of events for optimization are proposed using gradient based solver and genetic algorithms.