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Tropical cyclones (TCs) are intense atmospheric vortices that form over the warm tropical oceans. They are recognized for their ability to generate intense precipitation that may in turn create disastrous floods. This article first assesses the suitability of a regional atmospheric model, the Weather Research and Forecasting (WRF) model, to simulate the intense precipitation depth (PD) fields of six North Atlantic TCs that affected the eastern United States during 2002–2016. Due to the strong nonlinearity involved in tropical cyclones' dynamics and thermodynamics, which causes tropical cyclones' tracks to be very sensitive to the different modeling choices, placing the PD fields in the observed locations was challenging. This involved trying several simulation start dates and combinations of the WRF model's parameterization schemes for each storm simulated. Model performance was evaluated by comparing the simulated PD fields with the observed PD fields obtained from the NCEP Stage IV precipitation dataset. In addition to qualitative comparisons, three quantitative metrics were used to quantify the WRF model performance in simulating a PD field's location, structure and intensity. The sensitivity of the simulation results to the choice of the parameterization schemes was then illustrated using Hurricane Gustav (2008). Eventually, the most satisfactory simulations were used to investigate the mechanisms responsible for the generation of intense precipitation in these TCs. More specifically, the vertically integrated vapor transport field and its divergence were calculated using the model outputs, and it was found that horizontal moisture convergence played a central role in the generation of intense precipitation in these TCs.

In this article, a method for the storm transposition of tropical cyclones is presented. This method is physically based as it uses a regional atmospheric model to reconstruct the precipitation depth field from a tropical cyclone, thus crucially conserving the mass, momentum and energy in the system. In this physically based storm transposition method, the tropical cyclone vortex in the simulation initial conditions is first shifted spatially. More precisely, the tropical cyclone at the simulation start date is first separated from its background environment, then shifted, and finally recombined with the background environment. Afterwards, the regional atmospheric model is run as usual to simulate the shifted tropical cyclone and its precipitation depth field. The storm transposition method was then applied to four hurricanes which spawned torrential precipitation in the United States: Hurricanes Floyd (1999), Frances (2004), Ivan (2004), and Isaac (2012), in order to maximize the 72-h precipitation depth over the drainage basin of the city of Asheville, NC. It was observed that the precipitation depth fields changed in both structure and intensity after the physically based storm transposition. Besides, the tropical cyclone tracks were generally very sensitive to changes in the initial conditions, which is expected for a storm system whose dynamics is strongly nonlinear. In particular, it was found that a small change in the location of the initial tropical cyclone vortex may result in a very different track, allowing the tropical cyclone's precipitation depth field to move over the target area.

Many hydrologic and hydraulic (H&H) engineering applications require spatial rainfall distribution over a watershed, but point precipitation frequency estimates, such as those provided by NOAA Atlas 14, are only applicable for relatively small areas. For larger areas, areal reduction factors (ARFs) are commonly used to transform a point precipitation frequency estimate of a given duration and frequency to a corresponding areal estimate. The most common source of ARFs for the United States is Technical Paper 29 (TP-29), published in 1958, although there have been significant increases in record length and types of available data and several new methods for computing ARFs have been proposed over the last several decades. This study applied up-to-date precipitation data products and analysis methods with a watershed-based approach to investigate factors that affect ARF variabilities, and to compare ARFs across multiple US hydrologic regions. Our overall findings are in line with other recent studies showing that ARFs decrease with increasing area, increase with increasing duration, and decrease with increasing return period. In particular, we found a strong geographical variability across different US hydrologic regions, suggesting that ARF are specific to regional climate patterns and geographical characteristics and should not be applied arbitrarily to other locations. The results also reveal the importance of record length, especially for long return period ARFs. The study demonstrates the need to improve ARFs with new data and methods to support more reliable areal precipitation frequency estimates for H&H applications.

An in situ recovery of uranium operation involves circulating reactive fluids through an underground uranium deposit. These fluids contain chemicals that dissolve the uranium ore. Uranium is recovered from the fluids after they are pumped back to the surface. Chemicals used to accomplish this include complexing agents that are organic, readily degradable, and/or have a predictable lifetime in an aquifer. Efficiency is increased through development of organic agents targeted to complexing tetravalent uranium rather than hexavalent uranium. The operation provides for in situ immobilization of some oxy-anion pollutants under oxidizing conditions as well as reducing conditions. The operation also artificially reestablishes reducing conditions on the aquifer after uranium recovery is completed. With the ability to have the impacted aquifer reliably remediated, the uranium recovery operation can be considered inherently safe.