A5057947877- Meteorological Phenomena and Simulations
- Flood Risk Assessment and Management
- Precipitation Measurement and Analysis
- Hydrology and Watershed Management Studies
- Climate variability and models
- Hydrology and Drought Analysis
- Soil Moisture and Remote Sensing
- Lightning and Electromagnetic Phenomena
- Fire effects on ecosystems
- Tropical and Extratropical Cyclones Research
- Power System Reliability and Maintenance
- Water resources management and optimization
- Infrastructure Resilience and Vulnerability Analysis
- Landslides and related hazards
- Hydrological Forecasting Using AI
- Energy Load and Power Forecasting
- Climate change impacts on agriculture
- Plant Water Relations and Carbon Dynamics
- Cryospheric studies and observations
- Atmospheric aerosols and clouds
- Geophysics and Gravity Measurements
- Groundwater flow and contamination studies
- Remote Sensing and LiDAR Applications
- Hydrology and Sediment Transport Processes
- Water-Energy-Food Nexus Studies
University of Connecticut
2015-2024
Guangxi University
2021
United States Geological Survey
2021
Institute of Arctic and Alpine Research
2021
University of Colorado Boulder
2021
Florida Institute of Technology
2020
California State University, Sacramento
2020
Eversource Energy (United States)
2020
National and Kapodistrian University of Athens
2018
Engineering (Italy)
2014-2015
The Mediterranean countries are experiencing important challenges related to the water cycle, including shortages and floods, extreme winds, ice/snow storms, that impact critically socioeconomic vitality in area (causing damage property, threatening lives, affecting energy transportation sectors, etc.). There gaps our understanding of cycle its dynamics include variability Sea budget feedback on continental precipitation through air–sea interactions, aquifer recharge, river discharge, soil...
Abstract. Intensity–duration–frequency (IDF) curves are widely used to quantify the probability of occurrence rainfall extremes. The usual rain gauge-based approach provides accurate for a specific location, but uncertainties arise when ungauged regions examined or catchment-scale information is required. Remote sensing records, e.g. from weather radars and satellites, recently becoming available, providing high-resolution estimates at regional even global scales; their uncertainty...
This paper introduces new developments in an outage prediction model (OPM) for electric distribution network the Northeastern United States and assesses their significance to OPM performance. The uses regression tree models fed by numerical weather outputs, spatially distributed information on soil, vegetation, utility assets, historical power data forecast number spatial of outages across grid. New modules introduced hereby consist 1) a storm classifier based variables; 2) multimodel...
Abstract. The changing climate and anthropogenic activities raise the likelihood of damage due to compound flood hazards, triggered by combined occurrence extreme precipitation storm surge during high tides exacerbated sea-level rise (SLR). Risk estimates associated with these event scenarios are expected be significantly higher than derived from a standard evaluation individual hazards. In this study, we present case studies hazards affecting critical infrastructure (CI) in coastal...
Power outages caused by extreme weather events cost the economy of United States billions dollars every year and endanger lives people affected them. These types could be better managed if accurate predictions storm impacts were available. While empirical power outage prediction models have been in development for many years, operational most impactful weather-related proven difficult to achieve several reasons. In this paper, we describe a data intensive modeling approach specifically...
The most common rainfall measuring sensor for validation of radar-rainfall products is the rain gauge. However, difference between area-rainfall and gauge point-rainfall estimates imposes additional noise in radar–rain statistics, which should not be interpreted as radar error. A methodology proposed to quantify error variance by separating area-point from ratio. this research defined ratio “true” estimated mean-areal Both multiplicative errors are assumed stochastic variables, lognormally...
Increasing climate variability as a result of change will be one the public health challenges to control infectious diseases in future, particularly sub-Saharan Africa including Ethiopia.To investigate effect on childhood diarrhea (CDD) and identify high risk periods diarrheal diseases.The study was conducted all districts located three Zones (Awi, West East Gojjam) Amhara Region northwestern parts Ethiopia. Monthly CDD cases for 24 months (from July 2013 June 2015) reported each district...
ABSTRACT The current statistical methods applied in flood frequency analysis require long data records to obtain reliable estimates, particularly for return periods. Moreover, the choice of model and parameter estimation procedure may introduce uncertainty estimates. In this work, we investigate sensitivity various sample sizes, models, over six major hydrological regions contiguous United States. Results show that estimates based on annual maximum series approach convergence reference...
This article compares two nonparametric tree‐based models, quantile regression forests (QRF) and Bayesian additive trees (BART), for predicting storm outages on an electric distribution network in Connecticut, USA. We evaluated point estimates prediction intervals of outage predictions both models using high‐resolution weather, infrastructure, land use data 89 events (including hurricanes, blizzards, thunderstorms). found that spatially BART predicted more accurate than QRF. However, QRF...
A growing number of electricity utilities use machine learning-based outage prediction models (OPMs) to predict the impact storms on their networks for sustainable management. The accuracy OPM predictions is sensitive sample size and event severity representativeness in training dataset, extent which has not yet been quantified. This study devised a randomized out-of-sample validation experiment quantify an OPM’s uncertainty different sizes representativeness. showed random error decreasing...
Abstract Most existing inundation inventories are based on surveys, news, or passive remote sensing imagery. Affected by spatiotemporal resolution weather conditions, these limited in spatial details coverage. Satellite synthetic aperture radar (SAR) data have recently enabled flood mapping at unprecedented resolution. However, the bottleneck producing SAR-based maps is requirement of expert manual processing to maintain acceptable accuracy most SAR-driven techniques. To fill vacancy, we...
Abstract. For this brief communication, we analyzed the crop area and number of livestock exposed to flooding from historic precipitation caused by Storm Daniel in central Greece on 3–8 September 2023. We derived near-real-time RAdar Produced Inundation Diary (RAPID) system an inundated totaling 1150 km2, located mainly Thessalian plain. By overlaying a land cover map RAPID inundation map, found that ∼ 820 km2 (70 %) was agricultural land. A detailed distribution type animal farms revealed...