Remote Sensing and Hydrometeorology
University of Texas at Arlington
Using GEFS ensemble model data and an Artificial Neural Network (ANN), we generate probabilistic precipitation forecasts across the contiguous United States. The model predicts a full Censored Shifted Gamma Distribution (CSGD) at every land grid point, producing calibrated exceedance probabilities for rolling 12-hour precipitation windows. Animations below show the full forecast horizon for the latest … Read more
Every day, volunteers across the country report rainfall, hail, and snowfall through the CoCoRaHS network. Using these community observations, we automatically generate an up-to-date precipitation map and dataset helping visualize where and which type of precipitation occurred, updated twice daily at 11:00 AM and 11:00 PM CST. Daily CoCoRaHS Map Last updated: · Updates twice … Read more
Summary The overarching aims of this project are three-fold. The first is to introduce enhancements to Noah-MP to remedy the key deficiencies of Noah-MP LSM identified by the UTA team. The second is to discern optimal combination of these enhancements that will maximize the skills of UFS S2S model for predicting major hydrometerological events in … Read more
Summary The proposed work will explorean innovative ML scheme based on the advanced recurrent neural networks – Long Short-TermMemory (LSTM) that will exploit the time-dependent skills rendered by additional predictorssuch as convective inhibition, convective available potential energy, and precipitable water. Thenetwork will incorporate embedding (a regularization approach) to sharpen the1predictor-predictand relationship. These innovations have the … Read more
NASA WR Project The UTA project team collaborates with NASA Goddard Space Flight Center in implementing a UTA-LIS that has been running daily to produce soil moisture product for the entire state of Texas and rainfall loss estimates. Soil Moisture Soil Moisture Surface Root Soil Moisture Anomaly Anomaly Surface Root LCRA Loss LCRA Constant Loss … Read more
Soil Moisture Summary Texas is the state that experiences frequency occurrence of extreme floods and droughts, and reservoirs are critical infrastructures for water supply and flood management. At present, reservoir operators in the state of Texas rely on HEC-HMS configured in event-base mode for predicting reservoir inflow. The major sources of error in the prediction … Read more
Summary This research project seeks to improve forecasts of inflow and water balance for reservoirs in New Mexico and Texas during extreme droughts and pluvial years, with the ultimate aim of developing more efficient reservoir operation strategies to alleviate the impacts of droughts on water supply. The research team will be part of the national … Read more
UTA hosted the second Joint Texas FIRO workshop in September 21-22 of 2023 in collaboration with Texas Water Development Board (TWDB), and National Oceanic and Atmospheric Administration (NOAA). The workshop was a follow-up to the first Texas FIRO workshop held in 2019 with the aims of reviewing progresses made in facilitating FIRO adoption in the … Read more
Summary UTA and Colorado State University collaborate to establish a regional S2S prediction system for the southern Plains, and use this system to assess potential predictability of precipitation anomalies at the subseasonal scale (week 3-6) that can be attained through assimilating soil moisture, vegetation state and sea surface temperature. The research will specifically examine the … Read more
Summary The US Gulf Coast and Texas in particular has an aging oil and gas infrastructure that is critical to the nation’s energy supply with major refineries and supporting industries. While these companies have robust safety and risk assessment plans in place for averting major industrial disasters, they are dependent on local and municipal infrastructures … Read more