Impact of Extreme Events on Transportation Infrastructure in Iowa: A Bayesian Network Approach

Author(s):  
Abhijit R. Kulkarni ◽  
Behrouz Shafei

Iowa’s roadway network is an important part of the state’s transportation infrastructure and plays a critical role in the functionality and economic development of the entire state. This network primarily consists of three interstate highways that pass through Iowa, connecting it to the neighboring states and eventually Canada. Various businesses are located near this roadway network and rely on it for everyday operation. In recent years, however, the growth of agricultural and biofuel industries has intensified the demand on the roads and bridges in Iowa. The state’s roads and bridges have also witnessed a number of flooding events, which have caused extensive traffic disruptions and economic losses. Thus, it is imperative to develop a fundamental approach to evaluate the impact of extreme events on the transportation infrastructure of Iowa and other similar states. Towards this goal, the current study investigates the existing condition of Iowa’s transportation infrastructure, possibility of occurrence of extreme weather events, and scenarios that may lead to the failure of transportation infrastructure components. For this purpose, the capabilities of Bayesian belief networks are utilized to quantify the effects of extreme precipitation and extreme temperature on the performance of transportation infrastructure and then predict the probability of damage to roads and bridges. This will be achieved through the identification of the most influential factors using a set of sensitivity analyses, assessment of overall vulnerability with evidence-based propagation analyses, and quantification of response to extreme weather events, taking into consideration climate projections.

Climate ◽  
2020 ◽  
Vol 8 (4) ◽  
pp. 48 ◽  
Author(s):  
Rawshan Ali ◽  
Alban Kuriqi ◽  
Ozgur Kisi

This study aimed to assess the interrelationship among extreme natural events and their impacts on environments and humans through a systematic and quantitative review based on the up-to-date scientific literature. Namely, the main goal was to add additional knowledge to the existing evidence of the impacts related to floods, droughts, and landslides on humans and the environment in China; this in order to identify knowledge gaps in research and practice to aid in improving the adaptation and mitigation measures against extreme natural events in China. In this study, 110 documents were analyzed in the evaluation of several impacts triggered by extreme events. Records were obtained from Scopus and Web of Science and examined with a text mining instrument to assess the pattern of publications over the years; the problems linked to extreme weather events were investigated, and the study gaps were discussed. This paper extends work by systematically reviewing recent evidence related to floods, droughts, and landslides in China. We listed the critical studies that focused on the impact of extreme events on both humans and the environment described in current reviews. The findings revealed that goods safety, social safety, and financial losses are of significant concern to the scientific community due to extreme natural events, which from our analysis resulted in being more frequent and intense. It is still underdeveloped to implement distant sensing and imaging methods to monitor and detect the impact of severe weather occurrences. There are still significant study gaps in the fields of the effects of extreme weather events. The analysis result shows that extreme events are increased during the time, so more in-depth investigation and efforts on adaptation, mitigation measures, and strategical governance plans are desperately required.


2011 ◽  
Vol 16 (2) ◽  
pp. 177-198 ◽  
Author(s):  
KARL PAUW ◽  
JAMES THURLOW ◽  
MURTHY BACHU ◽  
DIRK ERNST VAN SEVENTER

ABSTRACTExtreme weather events such as droughts and floods have potentially damaging implications for developing countries. Previous studies have estimated economic losses during hypothetical or single historical events, and have relied on historical production data rather than explicitly modeling climate. However, effective mitigation strategies require knowledge of the full distribution of weather events and their isolated effects on economic outcomes. We combine stochastic hydrometeorological crop-loss models with a regionalized computable general equilibrium model to estimate losses for the full distribution of possible weather events in Malawi. Results indicate that, based on repeated sampling from historical events, at least 1.7 per cent of Malawi's gross domestic product (GDP) is lost each year due to the combined effects of droughts and floods. Smaller-scale farmers in the southern region of the country are worst affected. However, poverty among urban and nonfarm households also increases due to national food shortages and higher domestic prices.


2018 ◽  
Author(s):  
Junxi Zhang ◽  
Yang Gao ◽  
Kun Luo ◽  
L. Ruby Leung ◽  
Yang Zhang ◽  
...  

Abstract. The Weather Research and Forecasting model with Chemistry (WRF/Chem) was used to study the effect of extreme weather events on ozone in US for historical (2001–2010) and future (2046–2055) periods under RCP8.5 scenario. During extreme weather events, including heat waves, atmospheric stagnation, and their compound events, ozone concentration is much higher compared to non-extreme events period. A striking enhancement of effect during compound events is revealed when heat wave and stagnation occur simultaneously and both high temperature and low wind speed promote the production of high ozone concentrations. In regions with high emissions, compound extreme events can shift the high-end tails of the probability density functions (PDFs) of ozone to even higher values to generate extreme ozone episodes. In regions with low emissions, extreme events can still increase high ozone frequency but the high-end tails of the PDFs are constrained by the low emissions. Despite large anthropogenic emission reduction projected for the future, compound events increase ozone more than the single events by 10 % to 13 %, comparable to the present, and high ozone episodes are not eliminated. Using the CMIP5 multi-model ensemble, the frequency of compound events is found to increase more dominantly compared to the increased frequency of single events in the future over the US, Europe, and China. High ozone episodes will likely continue in the future due to increases in both frequency and intensity of extreme events, despite reductions in anthropogenic emissions of its precursors. However, the latter could reduce or eliminate extreme ozone episodes, so improving projections of compound events and their impacts on extreme ozone may better constrain future projections of extreme ozone episodes that have detrimental effects on human health.


2019 ◽  
Vol 11 (9) ◽  
pp. 2547 ◽  
Author(s):  
Alessia Cogato ◽  
Franco Meggio ◽  
Massimiliano De Antoni Migliorati ◽  
Francesco Marinello

Despite the increase of publications focusing on the consequences of extreme weather events (EWE) for the agricultural sector, a specific review of EWE related to agriculture is missing. This work aimed at assessing the interrelation between EWE and agriculture through a systematic quantitative review of current scientific literature. The review analysed 19 major cropping systems (cereals, legumes, viticulture, horticulture and pastures) across five continents. Documents were extracted from the Scopus database and examined with a text mining tool to appraise the trend of publications across the years, the specific EWE-related issues examined and the research gaps addressed. The results highlighted that food security and economic losses due to the EWE represent a major interest of the scientific community. Implementation of remote sensing and imagery techniques for monitoring and detecting the effects of EWE is still underdeveloped. Large research gaps still lie in the areas concerning the effects of EWE on major cash crops (grapevine and tomato) and the agronomic dynamics of EWE in developing countries. Current knowledge on the physiological dynamics regulating the responses of main crops to EWE appears to be well established, while more research is urgently needed in the fields of mitigation measures and governance systems.


2019 ◽  
Vol 32 (2) ◽  
pp. 244-266
Author(s):  
Edimilson Costa Lucas ◽  
Wesley Mendes-Da-Silva ◽  
Gustavo Silva Araujo

Purpose Managing the risks associated to world food production is an important challenge for governments. A range of factors, among them extreme weather events, has threatened food production in recent years. The purpose of this paper is to analyse the impact of extreme rainfall events on the food industry in Brazil, a prominent player in this industry. Design/methodology/approach The authors use the AR-GARCH-GPD hybrid methodology to identify whether extreme rainfall affects the stock price of food companies. To do so, the authors collected the daily closing price of the 16 food industry companies listed on the Brazilian stock exchange (B3), in January 2015. Findings The results indicate that these events have a significant impact on stock returns: on more than half of the days immediately following the heavy rain that fell between 28 February 2005 and 30 December 2014, returns were significantly low, leading to average daily losses of 1.97 per cent. These results point to the relevance of the need for instruments to hedge against weather risk, particularly in the food industry. Originality/value Given that extreme weather events have been occurring more and more frequently, financial literature has documented attempts at assessing the economic impacts of weather changes. There is little research, however, into assessing the impacts of these events at corporate level.


Atmosphere ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 133 ◽  
Author(s):  
Lijun Liu ◽  
Yuanqiao Wen ◽  
Youjia Liang ◽  
Fan Zhang ◽  
Tiantian Yang

The impact of extreme weather events on the navigation environment in the inland waterways of the Yangtze River is an interdisciplinary hotspot in subjects of maritime traffic safety and maritime meteorology, and it is also a difficult point for the implementation of decision-making and management by maritime and meteorological departments in China. The objective of this study is to review the variation trends and distribution patterns in the periods of adverse and extreme weather events that are expected to impact on inland waterways transport (IWT) on the Yangtze River. The frequency of severe weather events, together with the changes in their spatial extension and intensity, is analyzed based on the ERA-Interim datasets (1979–2017) and the GHCNDEX dataset (1979–2017), as well as the research progresses and important events (2004–2016) affecting the navigation environment. The impacts of extreme weather events on IWT accidents and phenomena of extreme weather (e.g., thunderstorms, lightning, hail, and tornadoes) that affect the navigation environment are also analyzed and discussed. The results show that: (1) the sections located in the plain climate zone is affected by extreme weather in every season, especially strong winds and heat waves; (2) the sections located in the hilly mountain climate zone is affected particularly by spring extreme phenomena, especially heat waves; (3) the sections located in the Sichuan Basin climate zone is dominated by the extreme weather phenomena in autumn, except cold waves; (4) the occurrence frequency of potential flood risk events is relatively high under rainstorm conditions and wind gusts almost affect the navigation environment of the Jiangsu and Shanghai sections in every year; (5) the heat wave indices (TXx, TR, and WSDI) tend to increase and the temperature of the coldest day of the year gradually increases; (6) the high occurrences of IWT accidents need to be emphasized by relevant departments, caused by extreme weather during the dry season; and (7) the trends and the degree of attention of extreme weather events affecting IWT are ranked as: heat wave > heavy rainfall > wind gust > cold spell > storm. Understanding the seasonal and annual frequency of occurrence of extreme weather events has reference significance for regional management of the Yangtze River.


2018 ◽  
Vol 2 (1) ◽  
pp. 9-24
Author(s):  
Edoardo Bertone ◽  
Oz Sahin ◽  
Russell Richards ◽  
Anne Roiko

Abstract A decision support tool was created to estimate the treatment efficiency of an Australian drinking water treatment system based on different combinations of extreme weather events and long-term changes. To deal with uncertainties, missing data, and nonlinear behaviours, a Bayesian network (BN) was coupled with a system dynamics (SD) model. The preliminary conceptual structures of these models were developed through stakeholders' consultation. The BN model could rank extreme events, and combinations of them, based on the severity of their impact on health-related water quality. The SD model, in turn, was used to run a long-term estimation of extreme events' impacts by including temporal factors such as increased water demand and customer feedback. The integration of the two models was performed through a combined Monte Carlo–fuzzy logic approach which allowed to take the BN's outputs as inputs for the SD model. The final product is a participatory, multidisciplinary decision support system allowing for robust, sustainable long-term water resources management under uncertain conditions for a specific location.


2020 ◽  
Author(s):  
Keh-Jian Shou

<p>Due to active tectonic activity, the rock formations are young and highly fractured in Taiwan area. The dynamic changing of river morphology makes the highly weathered formations or colluviums prone to landslide and debris flow. For the past decade, the effect of climate change is significant and creates more and more extreme weather events. The change of rainfall behavior significantly changes the landslide behavior, which makes the large-scale landslides, like the Shiaolin landslide, possible. Therefore, it is necessary to develop the new technologies for landslide investigation, monitoring, analysis, early warning, etc.</p><p>Since the landslide hazards in Taiwan area are mainly induced by heavy rainfall, due to climate change and the subsequent extreme weather events, the probability of landslides is also increased. Focusing on the upstreams of the watersheds in Central Taiwan, this project studied the behavior and hazard of shallow and deep-seated landslides. Different types of susceptibility models in different catchment scales were tested, in which the control factors were analyzed and discussed. This study also employs rainfall frequency analysis together with the atmospheric general circulation model (AGCM) downscaling estimation to predict the extreme rainfalls in the future. Such that the future hazard of the shallow and deep-seated landslide in the study area can be predicted. The results of predictive analysis can be applied for risk prevention and management in the study area.</p>


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