Development and evaluation of a hydrological and hydraulic coupled flood prediction system enabled by remote sensing, numerical weather prediction, and deep learning technologies

Floods triggered by extreme precipitation are the most frequently occurring and disastrous natural hazards in the world. However, it is still challenging to provide accurate and flood mapping, flood damage estimation, and flood forecast. The purpose of this dissertation is to develop a hydrological and hydraulic coupled flood prediction system, inundation MApping and Prediction (iMAP), which can provide comprehensive flood simulation and prediction including channel flow rate, flood return period, flood extent, surface flow speed, and direction, as well as inundation depth and soil moisture. Up until now, the Coupled Routing and Excess STorage (CREST) model family has been well documented and established both in research and in real-world operation. As a new member of the CREST family, the work in this dissertation carries on the features of CREST model, as being robust, efficient, automated, and globally applicable. Moreover, the study also evaluates multiple remote sensing and precipitation prediction technologies during the historical event Hurricane Harvey. The results of the studies demonstrate that the CREST-iMAP system has the ability to provide comparable Harvey flood simulation as multiple real-time and operational flood monitoring systems in the world, and the best result comes from using Multi-Radar Multi Sensor (MRMS) Quantitative Precipitation Estimates (QPE), which the combination considers as the best practice in the Contiguous United States (USA). The results also indicate that the uncalibrated precipitation estimates perform better during extreme events like Hurricane Harvey, and precipitation forecasts still need more improvement to provide more information on flood prediction. However, the Numerical Weather Prediction (NWP) product can provide a preliminary forecast of the maximum flood extent, while the deep learning method could potentially improve the displacement issues from NWP forecasts

Storage requirements to mitigate intermittent renewable energy sources: analysis for the US Northeast

Moving away from fossil fuels is essential for a sustainable future. Carrying out this transition without reversing the improvements in the quality of life is the ultimate challenge. While minimizing the anticipated impacts of climate change is the primary driver of decarbonization, the inevitable exhaustion of fossil energy sources should provide just as strong or perhaps even stronger incentives. The vast majority of publications outlining the pathways to “net-zero carbon emission” fall short from leading to a truly “fossil fuel-free” future without falling back to some level of dependence on fossil fuels with carbon capture and sequestration. While carbon capture and sequestration might be a necessary step toward decarbonization, such intermediate goals might turn into a dead end without defining the end point. The main obstacle to wider adoption of renewable energy resources is their inherent intermittency. Solar and wind are, by far, the most abundant renewable energy sources that are expected to take the lion share in transitioning to a sustainable future. Intermittency arises at multiple levels. The most recognized are the short-term (minute-by-minute, hourly, or diurnal) variations that should be the easiest to address. Less frequently realized are the seasonal and inter-annual variabilities. Seasonality poses far greater challenges than minute-by-minute or hourly variations because they lead to the absence of energy resources for prolonged periods of time. Our interest is the feasibility of a future where all energy (100%) comes from renewable sources leaving no room for fossil fuels. We carry out rudimentary statistical analyses of solar radiation and wind speed time series records to quantify the degree of their intermittencies seasonally and inter-annually. We employ a simple but robust accounting of the shortfalls when the supplies do not meet demand via a modified cumulative supply/deficit analysis that incorporates energy losses arising from transporting excess energy to storage and retrieving it as needed. The presented analysis provides guidance for choosing between the installation of excess capacity or the deployment of energy storage to guarantee reliable energy services under the assumption that the energy system is powered exclusively by renewable energy sources. This paper examines the seasonal and inter-annual variability of hydropower and biofuel resources to estimate their potential to mitigate the intermittencies of solar and wind resources. The presented analyses are meant to provide crude, bulk part estimates and are not intended for planning or operational purposes of the actual energy infrastructures. The primary focus of this paper is the Northeast region of the United States using the conterminous United States as a reference to assess the viability of reducing the energy storage need in the study region via improved connectivity to the national grid. This paper builds on the modeling exercises carried out as part of the climate-induced extremes on food, energy, water systems studies

Can Remote Sensing Technologies Capture the Extreme Precipitation Event and Its Cascading Hydrological Response? A Case Study of Hurricane Harvey Using EF5 Modeling Framework

A new generation of precipitation measurement products has emerged, and their performances have gained much attention from the scientific community, such as the Multi-Radar Multi-Sensor system (MRMS) from the National Severe Storm Laboratory (NSSL) and the Global Precipitation Measurement Mission (GPM) from the National Aeronautics and Space Administration (NASA). This study statistically evaluated the MRMS and GPM products and investigated their cascading hydrological response in August of 2017, when Hurricane Harvey brought historical and record-breaking precipitation to the Gulf Coast (>1500 mm), causing 107 fatalities along with about USD 125 billion worth of damage. Rain-gauge observations from Harris County Flood Control District (HCFCD) and stream-gauge measurements by the United States Geological Survey (USGS) were used as ground truths to evaluate MRMS, GPM and National Centers for Environmental Prediction (NCEP) gauge-only data by using statistical metrics and hydrological simulations using the Ensemble Framework for Flash Flooding Forecast (EF5) model. The results indicate that remote sensing technologies can accurately detect and estimate the unprecedented precipitation event with their near-real-time products, and all precipitation products produced good hydrological simulations, where the Nash–Sutcliff model efficiency coefficients (NSCE) were close to 0.9 for both the MRMS and GPM products. With the timeliness and seamless coverage of MRMS and GPM, the study also demonstrated the capability and efficiency of the EF5 framework for flash flood modeling over the United States and potentially additional international domains.This study is partially funded by University of Oklahoma and also based upon work supported by the National Science Foundation under Grant No. 1545874. Open Access fees paid for in whole or in part by the University of Oklahoma Libraries.Ye

Clinical and molecular profiling of EGFR-mutant lung adenocarcinomas transformation to small cell lung cancer during TKI treatment

IntroductionSmall cell lung cancer (SCLC) transformation serves as a significant mechanism of resistance to tyrosine kinase inhibitors (TKIs) in advanced non-small cell lung cancer (NSCLC) with epidermal growth factor receptor (EGFR) mutations. To address this clinical challenge, we conducted a retrospective analysis at Zhejiang University School of Medicine, the First Affiliated Hospital, focusing on patients with EGFR sensitizing mutations.MethodsA total of 1012 cases were included in this retrospective analysis. The cohort primarily consisted of patients with EGFR sensitizing mutations. Biopsy-confirmed small cell transformation was observed in seven patients, accounting for 0.7% of the cases. All patients in this subset were initially diagnosed with stage IV adenocarcinoma (ADC), with four cases classified as poorly differentiated and three as moderately to poorly differentiated ADC. EGFR exon 19 deletions were identified in five of these cases. Next-generation sequencing (NGS) was performed on seven cases, revealing mutations in the tumor protein p53 (TP53) gene in four cases and loss of the retinoblastoma1 (RB1) gene in three cases.ResultsThe median duration from the initial diagnosis to small cell transformation was 35.9 months (interquartile range: 12.1–84 months). Following small cell transformation during EGFR inhibition, all patients received etoposide/platinum-based treatment, leading to a median progression-free survival (PFS) of 4.7 months (interquartile range: 2.7–10.1 months). Notably, most patients in this series had poorly differentiated adenocarcinomas at the outset. TP53 mutations and RB1 loss were common genetic alterations observed in patients with small cell transformation in this cohort.DiscussionThe findings underscore the clinical significance of SCLC transformation as a resistance mechanism to EGFR TKIs in NSCLC with EGFR mutations. The observed genetic alterations, including TP53 mutations and RB1 loss, suggest potential associations with the transformation process and warrant further investigation. Understanding the genetic landscape and clinical outcomes in patients experiencing small cell transformation can contribute to improved strategies for managing resistance in EGFR-mutant NSCLC

Effects of lower troposphere vertical mixing on simulated clouds and precipitation over the Amazon during the wet season

Planetary boundary layer (PBL) schemes parameterize unresolved turbulent mixing within the PBL and free troposphere (FT). Previous studies reported that precipitation simulation over the Amazon in South America is quite sensitive to PBL schemes and the exact relationship between the turbulent mixing and precipitation processes is, however, not disentangled. In this study, regional climate simulations over the Amazon in January-February 2019 are examined at process level to understand the precipitation sensitivity to PBL scheme. The focus is on two PBL schemes, the Yonsei University (YSU) scheme, and the asymmetric convective model v2 (ACM2) scheme, which show the largest difference in the simulated precipitation. During daytime, while the FT clouds simulated by YSU dissipate, clouds simulated by ACM2 maintain because of enhanced moisture supply due to the enhanced vertical moisture relay transport process: 1) vertical mixing within PBL transports surface moisture to the PBL top, and 2) FT mixing feeds the moisture into the FT cloud deck. Due to the thick cloud deck over Amazon simulated by ACM2, surface radiative heating is reduced and consequently the convective available potential energy (CAPE) is reduced. As a result, precipitation is weaker from ACM2. Two key parameters dictating the vertical mixing are identified, p, an exponent determining boundary layer mixing and λ, a scale dictating FT mixing. Sensitivity simulations with altered p, λ, and other treatments within YSU and ACM2 confirm the precipitation sensitivity. The FT mixing in the presence of clouds appears most critical to explain the sensitivity between YSU and ACM2.This work was primarily supported by grant no. 20163646499 from the Universidad Nacional de San Agustín de Arequipa (UNSA) of Peru through the IREES/LASI Global Change and Human Health Institute. The first author is partially supported by the National Mesonet Program grant #10558200 and DOE ASR project (DE-SC0021159). Ming Xue was also supported by NSF grants AGS-1917701.YesAn edited version of this paper was published by AGU. Published 2023, American Geophysical Union. Preprint available at https://doi.org/10.22541/essoar.167458066.61800879/v

Optimization of a supply chain network for bioenergy production from food waste

Food waste has potential to be recycled and converted to energy and other valuable products. In China, the food waste is partially collected and processed by illegal organizations to produce ‘gutter oil’, which is a serious public health and safety issue. Therefore, the city government plans to develop a central management system where the food waste from large number of restaurants and food vendors will be collected, pre-processed at existing facilities, and then converted into bioenergy and other usable products at a central treatment facility whose location is to be determined. A mixed integer linear programming (MILP) approach is present in this thesis to determine an optimal supply chain and processing network. We first develop a p-median model and determine an optimal grouping of the waste sources in multiple clusters where each cluster is served by a single preprocessing facility. This is considered as a proxy to the aggregate cost of delivering food waste to intermediate and final processing locations. The true minimum delivery cost is then determined by routing the delivery vehicles optimally within each cluster where the waste at all sources is collected by multiple delivery vehicles. This approach is a heuristic procedure. The difference between exact optimum and heuristic solution is about 12 percent. The empirical application of the MILP model is presented with a real data set involving a large number of food waste sources in City of Shenzhen China, and evaluate the economic viability of the centralized collection and precession system. The results show that such system is profitable and environmentally beneficial

Review of Basalt Fiber-Reinforced Concrete in China: Alkali Resistance of Fibers and Static Mechanical Properties of Composites

Research on three-dimensional, randomly distributed BFRC in China is analyzed and summarized in relative depth in this study. The results indicate that the effect of the fiber component and alkali corrosion temperature on the alkali resistance of BF is significant; the BF has little effect on the compressive strength of the concrete; the tensile and flexural strengths of the composites significantly increase compared with plain concrete, and the fiber content has a significant effect on the strength. In light of some problems in the current research, six possible research topics are suggested: (1) investigating the alkali resistance of the BF under dynamic temperatures, lower alkali concentrations, and longer alkali corrosion times; (2) improving the alkali resistance of the BF by increasing its hydrophobicity; (3) determining the optimal fiber distribution orientation of the BF with various characteristic parameters; (4) establishing the calculation formulas for the critical content and critical aspect ratio of various types of BF; (5) determining the optimal mixture ratio of two or more fibers in the FRC while studying the complementary mechanisms between each other; and (6) improving the dispersion of the BF and the BF/matrix interfacial properties