A two-sample nonlinear heteroscedastic regression model is described and proposed for the purpose of evaluating a sewer basin rehabilitation by quantifying the reduction in rain-derived inflow and infiltration RDII . The proposed methodology is used at the second stage of RDII studies after RDII volumes of individual rain events are estimated. The proposed methodology utilizes boundary conditio...

Systems exposed to hydroclimatic variability, such as the integrated electric system in Uruguay, increasingly require real-time multiscale information optimize management. Monitoring of precipitation field is key inform future hydroelectric energy availability. We present an operational implementation algorithm that merges satellite estimates with rain gauge data, based on a 3-step technique: (...

Bartman et al., (2022). PySDM v1: particle-based cloud modeling package for warm-rain microphysics and aqueous chemistry. Journal of Open Source Software, 7(72), 3219, https://doi.org/10.21105/joss.03219

— This paper introduces a new rain removal model based on the shrinkage of the sparse codes for a single image. Recently, dictionary learning and sparse coding have been widely used for image restoration problems. These methods can also be applied to the rain removal by learning two types of rain and non-rain dictionaries and forcing the sparse codes of the rain dictionary to be zero vectors. H...

Rain attenuation is a major shortcoming of microwave transmission. J.S Ojo1, 2, M.O Ajewole1, S.K Sarkar2. An improved approach of predicting rain attenuation cumulative. rain attenuation formula Approach for determining the values of rain attenuation at different.Attenuation due to rain is an important constraint in the designing of the microwave. The paper presents a new prediction model of r...

This letter proposes a simple method of transferring rain structures of a given exemplar image (rain image) into a target image (non‐rain image). Given the exemplar rain image and its corresponding masked rain image, rain patches including real‐life rain structures are extracted randomly, and then residual rain patches are obtained by subtracting those rain patches from their mean patches. Next...

In this paper, we address a rain removal problem from a single image, even in the presence of heavy rain and rain streak accumulation. Our core ideas lie in the new rain image models and a novel deep learning architecture. We first modify an existing model comprising a rain streak layer and a background layer, by adding a binary map that locates rain streak regions. Second, we create a new mode...