Direct Economic Losses Research Articles

An automated machine learning approach for earthquake casualty rate and economic loss prediction

This study presents an automated machine learning (AutoML) framework to predict the casualty rate and direct economic loss induced by earthquakes. The AutoML framework enables automated combined algorithm selection and hyperparameter tuning (CASH), reducing the manual works in the model development. The proposed AutoML framework includes 5 modules: data collection, data preprocessing, CASH, loss prediction, and model analysis. The AutoML models are learned from the dataset that is composed of earthquake information and social indicators. The optimal algorithm and hyperparameter setting of models are determined by the CASH module. A two-step model including a classifier and a regression model is designed for the casualty rate to address zero-casualty cases and also minimize their impacts on data distribution. The proposed AutoML framework is implemented on the seismic loss dataset of mainland China to demonstrate its practicability. A comparison study is conducted to show the high predictive abilities of the AutoML model compared with the traditional seismic risk model and other AutoML models. Models learned from the complete dataset achieve the ultimate performance compared with subsets that are composed of partial features. The model interpretation results indicate that earthquake magnitude, position, and population density are leading indicators for loss prediction.

The true global burden of trauma: a call for a comprehensive trauma research platform

The true global burden of trauma: a call for a comprehensive trauma research platform

Amplifying Flood Risk Across the Lower Yellow River Basin, China, Under Shared Socioeconomic Pathways

The ecological conservation and high-quality development of the Yellow River basin (YRB) has been adopted as a major national strategy of China. However, the YRB is still afflicted by floods. Here, we proposed a flood risk indicator using direct economic loss degree and improved the SNRD (station-based nonlinear regression downscaling model) and simulated extreme precipitation processes. The correlation coefficient of downscaled average extreme precipitation of CMORPH and CMIP6 data reached 0.817. Moreover, we evaluated flood risk and flood hazard across the YRB based on the sixth phase Coupled Model Intercomparison Project (CMIP6) data under different SSPs. Under SSP126, SSP245, and SSP585 scenarios, the areas with increasing flood hazards during 2015–2045 accounted for 65.2, 69.0, and 64.5% of the entire YRB. In the spatial pattern, flood hazards decreased from southeastern to northwestern parts of the YRB. When compared with the spatial pattern of flood risks in 2015, regions with high flood risks expanded slightly and regions with low flood risks shrunk slightly. Higher flood risks can be observed in the middle and lower YRB and particularly in the lower YRB. These findings are critical for the mitigation of flood risk across the YRB under warming climate.

Warming of 0.5 °C may cause double the economic loss and increase the population affected by floods in China

Abstract. Based on future scenario data and an improved quantitative natural-disaster risk assessment model, in this study, we analysed the response of the characteristics of flood events in China to 1.5 and 2 ∘C of global warming, quantitatively assessed the population affected and the economic risks of floods, and determined the integrated risk levels. The results indicate that, for the RCP4.5 (Representative Concentration Pathway) and RCP8.5 scenarios, the probability and distribution area of the floods increase with increasing temperature and the influence range of the floods of different levels expands more rapidly under the RCP4.5 scenario. The floods mainly affect the social economy in the regions with lower altitudes and smaller slopes in eastern China. As the increase in temperature intensifies, the population affected and the direct economic losses are aggravated. For 2 ∘C of global warming, under the RCP8.5 scenario, the population affected by floods increases by 2 million, and the economic risk nearly doubles compared with 1.5 ∘C of global warming. The economic risk under the RCP4.5 scenario even reaches 3 times that for 1.5 ∘C of global warming, but its proportion to the gross domestic product (GDP) is lower than that under the RCP8.5 scenario. Under both scenarios, the ranges of the zones of medium–high flood risk gradually expand westward and northward.

The SeaRAS AquaSense™ System: Real-Time Monitoring of H2S at Sub µg/L Levels in Recirculating Aquaculture Systems (RAS)

Hydrogen sulfide (H2S) is toxic to all species used in aquaculture. The extensive fish mortalities inflicted by H2S-poisoning can cause significant direct economic losses. Called the silent killer among scholars and fish farmers, H2S is highly soluble in aquatic environments and has significant damage potential; once detected, the time for mitigation actions is limited as fish stocks are rapidly impacted by the gas. The detection of H2S at low concentrations is challenging with the state-of-the-art sensors used today. Despite its significant damage potential, the industry has not been able to provide a reliable yet user-friendly system to address this. The aim of this paper is to provide a step forward in this direction by introducing a system for real-time monitoring of H2S at sub µg/L levels in RAS. The SeaRAS AquaSense System (AQS) utilizes real-time monitoring of H2S in parallel with other water quality parameters, such as CO2, O2, pH, and temperature, through a set of autonomous wireless-based sensor units installed in multiple locations in RAS. The system is calibrated and verified further by an autonomous calibration system where substrates of known values are brought to the sensor at a defined interval, offering the user data confidence that is exceptional and of high value. The H2S levels are measured in real-time at high-temporal resolution (down to 0.05 µg/L). By having units located in distinct locations in the water treatment loop, a true real-time monitoring of water treatment processes in RAS is given. Preliminary results provide new insights to the mechanisms behind H2S formation in operational RAS, and, more important, provide a basis for the development of risk-reducing actions and means for risk mitigation through degassing processes. By measuring real time simultaneously in multiple locations and in the exhaust of the degasser, a true mass balance of the system can be formulated by the given amount of feed, measured parameters by sensors and the known flow rate. By using the SeaRAS AquaSense System it is also possible to track the amount of H2S that leaks to the recirculating water per m2 of biofilm in RAS. This is a critical parameter and of high priority to be considered in the context of coping with the H2S-induced risks in RAS. The finding of this work highlights that the formation of toxic H2S is inevitable in RAS-process, ergo, the focus of the industry should instead go toward how to cope with it. In this regard, the SeaRAS AquaSense System provides a step forward towards a practical solution for managing H2S-poisoning risk in aquaculture. This work suggests a need for future research on determining acceptable limits for H2S in water quality context in RAS and investigating a new insight on interaction between H2S and other water quality parameters such as CO2.

Assessing Heavy Precipitation Risk Associated with Tropical Cyclones in China

Abstract Tropical cyclone precipitation (TCP), accounting for some of the most extreme rainfall events, can lead to severe flooding and landslides, which often occur together as compound natural hazards during a tropical cyclone landfall. The impact due to TCP is largely associated with its intensity and spatial extent as the storm approaches landfall. Yet it is not entirely clear how TCP intensity and spatial extent vary from one tropical cyclone to another. In this study, we employ an advanced geostatistical framework to determine the TCP intensity and spatial extent along cyclone tracks for different cyclone categories, defined using the wind speed and tropical cyclone lifetime maximum intensity (LMI) at each track point (“point intensity-LMI”). The results show that when a tropical cyclone with an LMI of a supertyphoon makes landfall and has weakened to tropical storm strength it usually produces the most intense rainfall and covers the largest spatial extent. The total TCP amount estimated using the varying spatial extent helps to determine more accurately the amount of seasonal rainfall that is from tropical cyclones in China. We also determined the rainfall trend from 1951 to 2019 for TCP and found that when compared with the inland stations the historical TCP rainfall trend in those stations near the coastline of China is significantly increasing. Significance Statement Heavy rainfall caused by tropical cyclones has caused huge direct or indirect economic losses in the coastal areas of China. This impact is particularly significant when the rainfall intensity is high and the area of heavy rainfall is extensive. Here we investigate the rainfall intensity and spatial extent by classifying and comparing the different types of tropical cyclones impacting China with varying intensities. To do this, we group the tropical cyclone tracks of the western North Pacific Ocean during the last seven decades according to the strength of wind speed across the cyclone tracks. We found that the largest areas and heaviest intensities of rainfall occur when a supertyphoon has weakened to a tropical storm at landfall. When considering all tropical cyclones and their rainfall contribution to rainfall over land stations, we found that tropical cyclone rainfall has become heavier in most coastal areas of China.

Novel deterministic and probabilistic resilience assessment measures for engineering and infrastructure systems based on the economic impacts

Engineering and infrastructure systems are commonly subjected to various types of destructive events that disrupt their functionalities and cause direct and indirect economic losses. The resilience assessment enables stakeholders and decision-makers to identify how a system copes with a disruptive event, how it adjusts to the new disrupted condition, and how it is capable of recovering its functionality swiftly and inexpensively. Although different indices have been proposed to quantify system resilience in recent years, developing a comprehensive and reliable index is an ongoing subject. By considering the importance of the economic aspects of engineering and infrastructure systems, the current research employs three variables of: functionality level, time, and cost, simultaneously, to define novel comprehensive, comparative, and comprehensible indices for resilience and its features. In this regard, the resilience curve of an engineering system is described in functionality-time-cost (FTC) coordinates, and deterministic indices are defined for absorptive capacity, adaptive capacity, recoverability, and resilience of a system. Additionally, the Bayesian Network approach is used to account for the inherent uncertainties in the resilience assessment process and to develop probabilistic indices for the mentioned features. Finally, a case study is presented to demonstrate how ignoring the economic impacts of disruptive events might be misleading when evaluating resilience.

A data-driven framework to evaluate the indirect economic impacts of transportation infrastructure disruptions

Transportation systems are critical to the sustainable development and economic vitality of cities. However, they are vulnerable to disruptions that can result from natural and man-made disasters as well as maintenance activities that may require temporary closure of road segments. Previous research indicated that transportation disruptions can cause not only significant direct economic losses, but also substantial indirect impacts, which are difficult to analyze and quantify. The comprehensive estimation of the indirect economic impacts calls for interdisciplinary research frameworks. This study introduces a new analytical framework for estimating the indirect economic impacts that are caused by various direct effects of transportation disruptions, including building and content losses, business interruptions, freight flow perturbations, and passenger flow perturbations. One of the state-of-the-art Computable General Equilibrium (CGE) models, the TERM model, is leveraged to calculate the indirect economic impacts, fed with information on transportation disruptions generated by explicit transportation network models through a series of well-built model linkages. These linkages are set based on a thorough investigation of the potential indirect impacts due to transportation disruptions. Besides, critical data that are required to achieve a comprehensive and accurate estimation of the indirect economic impacts are identified. Potential double counting issues related to the implementation of the framework and mitigation solutions are discussed. To deploy the framework, a case study of a hypothetical earthquake scenario in the Greater Los Angeles Area was conducted. The indirect economic impacts of transportation disruptions caused by earthquake-induced bridge damages were estimated and analyzed. Simulation results indicated that millions of dollars could be lost in this case due to road transportation network disruptions, and the geographical distribution of those losses could be quantified. This study lays a foundation for further interdisciplinary research on the integration of transportation system analyses with economic models.

Economic impact of a peste des petits ruminants outbreak and vaccination cost in northwest Ethiopia.

Peste des petits ruminants (PPR) is an important endemic disease of small ruminants in Ethiopia. While vaccination is widely used in the country to control the disease, quantitative estimates of the actual economic losses due to outbreaks and costs of vaccination are scarce. This study assessed the economic impact and costs of PPR vaccination in Metema district, northwest Ethiopia. The economic impact of the disease was estimated from an outbreak investigation including interviews with 233 smallholder farmers in PPR-affected kebeles (subdistricts). The cost of PPR vaccination was obtained from vaccination programs in six kebeles of the district and from secondary data in the district veterinary office. In the investigated PPR outbreak, animal-level PPR morbidity and mortality rates were 51% and 22%, respectively, in sheep and 51% and 25%, respectively, in goats. The flock level morbidity rate was 83% for sheep flocks and 87% for goat flocks. The mean flock level loss was Ethiopian Birr (ETB) 7835 (USD 329 in 2018 average exchange rate) (95% CI: 5954-9718) for affected sheep flocks and ETB 7136 (USD 300) (95% CI: 5869-8404) for affected goat flocks. The losses in all study flocks during the outbreak were ETB 319 (USD 13.4) per sheep and ETB 306 (USD 12.9) per goat. Mortality accounted for more than 70% of the total losses in both sheep and goat flocks. Vaccination costs for PPR were estimated at ETB 3 per correctly vaccinated animal. Based on the estimated animal-level direct economic losses and vaccination cost, it can be conjectured that vaccination will pay if a district PPR outbreak occurs more than once every 13 years. This does not account for additional benefits from vaccine-derived herd immunity reducing disease burden in the wider population. In conclusion, PPR caused high morbidity and mortality in the affected flocks and resulted in high economic losses, equivalent to 14% of annual household income, dramatically affecting the livelihoods of affected flock owners. The vaccination practised in the district is likely to have a positive economic return, with strengthened vaccination programmes bringing reduced economic impact and improved livelihoods.

Extreme Flood Disasters: Comprehensive Impact and Assessment

Evaluating extreme flood disasters is a prerequisite for decision making in flood management. Existing extreme flood disaster assessments fail to either consider or evaluate comprehensive impacts from social, economic, and environmental aspects. This study first analyzes the causes of extreme flood disasters and subsequently the potential flood consequences in depth. On the basis of this comprehensive analysis, an extreme flood disaster indicator system is developed by taking into account social, economic, and environmental consequences. To assess the comprehensive impacts, we propose a refined social and economic impact evaluation method and a semi-quantitative environmental impact evaluation method, which are applied to Jingjiang Flood Diversion District (JFDD) located in the Yangtze River Basin, and analyze two extreme flood scenarios. The results show that almost all of the JFDD area is flooded with inundation areas of 901.36 km2 and 879.49 km2, respectively. The corresponding affected populations are 0.51 million and 0.5 million. The direct economic losses are 18.83 billion and 14.33 billion, respectively. Moreover, 5 potential pollutant sources and 11 protected areas are inundated under two scenarios. Extreme floods have relatively serious impacts on local ecology and the environment. The proposed methodology can provide effective support for decision makers.

The importance of indirect losses in the seismic risk assessment of industrial buildings – An application to precast RC buildings in Portugal

Observations from past destructive earthquakes indicate that indirect economic losses can greatly exceed the direct economic losses. However, the influence of indirect losses is often neglected in seismic risk studies due to the complexity associated with their evaluation, as well as the fact that direct losses tend to gather public attention due to human losses and the visual impact of structural damage. This issue is particularly evident in the assessment of indirect losses linked to industrial activities, which can represent a significant portion of the economy. The present study presents a comprehensive framework for the assessment of indirect economic losses based on the impact of business interruption and interdependency between the different economic sectors. The application of the proposed model to precast reinforced concrete buildings constitutes the first seismic risk study of this typology in Portugal, and highlights the critical need to pursue risk mitigation measures to address both the potential direct and indirect effects in the Portuguese economy.

Experimental and analytical investigation on the lateral response of ball rubber bearing isolators

Recent earthquakes demonstrated that modern seismic design and retrofit of constructions should target damage containment to reduce the direct and indirect economic losses and downtime. In this context, the use of base isolation as seismic protection strategy is becoming popular. A variety of devices is available on the market. Elastomeric and metallic sliding devices are the most common type of isolators. Ball rubber bearings (BRBs) combine the practical use and the low maintenance cost of elastomeric bearings with a friction-based dissipation due to the steel balls of the inner core. Although many tests were performed to characterize the lateral response of BRBs, their stiffness, the maximum displacement capacity and the damping, further studies are needed to clearly identify the main variables and their effects on the lateral response. This research paper aims at developing a design-oriented formulation to estimate the equivalent damping, the characteristic strength and the lateral stiffness of BRBs. In order to calibrate and validate the proposed formulation, experimental tests are performed varying the axial load pressure and maximum imposed displacement. Furthermore, all the tests available in literature are collected in a unique database. Simple considerations on the influence of the different design parameters are discussed and used to calibrate reliable design formulations to be used in the design practice. • Tests were carried out on Ball Rubber Bearings to investigate the effect of maximum imposed displacement and axial pressure. • Damping, characteristic and maximum strength of BRBs are sensitive to axial load pressure and imposed maximum displacement. • Design-oriented formulations for the damping, the characteristic strength and the lateral stiffness of BRBs are proposed. • The outcomes of this study can be used for the selection of BRB design parameters.

The effect of retained placenta on the reproductive performance and its economic losses in a Holstein dairy herd

Retention of placenta (RP) is a failure of the fetal membrane to be expelled and remained from 8 to 48 hours, average 12 hours after parturition. There are a variety of risk factors for the occurrence of RP. So, the aim of this study was to quantify the relative risk of calving season, parity, and gestation length on the occurrence of RP, and assess the impact of RP on the subsequent reproductive parameters, and the economic losses. A data of 2940 purebred Holstein-Friesian cows were collected from reliable records of large commercial dairy farm, Sharkia governorate, Egypt. These cows calved during the period extended from January 2018 to December 2019. Cows that did not release the fetal membranes within the first 12 hours after calf expulsion were diagnosed with RP.Results of logistic regression analysis revealed that the important risk factors for the occurrence of RP were summer calving season and short gestation period. Odds ratio estimation for summer calving season compared to spring calving was 2.84. The probability of RP incidence in cows with shorter gestation period was 0.19 times more than cows with longer gestation length, and the total direct economic losses from RP was 47 $/cow.Finally, we can conclude that short gestation length and summer calving season are strongly correlated with the development of RP in dairy cows. Subsequently, the occurrence of RP significantly affects reproductive parameters resulting in economic losses in dairy herds.

Prevalence and Financial Losses of Cystic Echinococcosis in Slaughtered Goats at Gumbo Slab in Juba County, South Sudan

A cross-sectional study was conducted at Gumbo slaughter slab in Juba, Central Equatoria State (CES) in South Sudan, between October and December 2015, to determine the prevalence of cystic echinococcosis (CE) and to estimate the direct economic losses associated with condemnation of infected organs in slaughtered goats. A thorough postmortem examination was conducted on carcasses of a total of 1126 goats selected by systematic random sampling for detection of CE in the lungs, liver, heart, kidneys, and the spleen. Moreover, CE-related direct financial losses were estimated by using a standardized formula. The overall prevalence of CE was found to be 281 (24.9%, 95% CI 22.5–27.6). Furthermore, old age (OR = 2.61, p value < 0.001), Mubende breed (OR = 2.97, p value < 0.001), and Ugandan geographical origin (OR = 2.97, p value < 0.001) were associated with higher prevalence of CE. The lungs were the most affected organ with a prevalence of 55.2% followed by liver (44.1%), and the spleen (0.07%). A direct CE-related monetary loss of 78,820 South Sudanese Pounds (SSP) per year was estimated. This loss is equivalent to USD 43,788. In conclusion, CE is considerably prevalent and is associated with significant direct financial losses among goats slaughtered at Gumbo slaughter slab in Juba, CES, South Sudan.

Poverty control policy may affect the transition of geological disaster risk in China

The Chinese government has implemented measures to reduce poverty in the country. Specifically, the Targeted Poverty Alleviation (2013–2020) policy is a set of unique, large-scale and precise poverty control measures undertaken by China in an effort to eliminate absolute poverty. Deeply impoverished areas in the mountainous regions of Southwest China are also particularly prone to geological disasters. A poverty control policy might reduce risk from natural disasters in this region by changing human behaviour. However, it is unclear how the risk might change under the government’s poverty control measures. This paper uses power-law relations and negative binomial regression to analyse primary economic losses from geological disasters in Yunnan Province between 2009 and 2017. The results of the analysis show that the relation between the level of economic development and disaster losses in Yunnan Province changed from an inverted-U shape to a U shape in this period. While direct economic losses from geological disasters are falling, we find that losses in wealthy counties Yunnan Province have not decreased significantly and might even be increasing. In impoverished areas, poverty alleviation policies reduce the economic losses of geological disasters by reducing the vulnerability and exposure, and increasing the resilience. On the contrary, poverty reduction measures promote a concentration of population and wealth in non-poor areas, increasing the vulnerability and exposure, which in turn lead to an increase in direct economic losses from geological disasters. Therefore, in order to consolidate the achievements of poverty alleviation projects, the government needs to pay attention to the transfer of geological disaster risk caused by the policy-driven transformation of human social behaviour.

Projections of corrosion and deterioration of infrastructure in United States coasts under a changing climate

Climate change can accelerate infrastructure deterioration in coastal areas because increased temperature and humidity can promote steel corrosion. This study (1) projects corrosion rate changes for reinforced concrete and steel structures in 223 coastal counties, (2) assesses the impact of corrosion rate changes on the useful life of structures, and (3) evaluates direct economic losses due to shortened useful life of highway bridges over the period 2000-2100. The results show that the useful life of concrete structures may decrease by 1.7-2.7% under the representative concentration pathway (RCP) 8.5 and decrease by 0.7-1.1% under RCP 4.5 by the end of the 21st century. The useful life of steel structures may decrease by 7.9-15.9% under RCP 8.5 and 3.3-6.7% under RCP 4.5. Concrete bridges may suffer an average loss of $6.5-11.7/m2 under RCP 8.5 and $3.3-16.5/m2 under RCP 4.5 due to shortened useful life. Steel bridges may suffer an average loss of $73.4-111.3/m2 under RCP 8.5 and $46.9-81.2/m2 under RCP 4.5. In both climate scenarios, 10% of counties may have negative losses and 10% of counties may have losses greater than $20 million due to corrosion rate changes for concrete and steel bridges. The results reveal the spatial difference of climate change impacts on infrastructural deterioration and suggest the importance of developing regional specific adaptation strategies.

Valuation of ecosystem damage induced by soil-groundwater pollution in an arid climate area: Framework, method and case study

Groundwater is an important source of water, even the only source in some arid areas. However, climate changing and ecosystem damage induced by pollution aggravate water resource crisis. The “polluter pays” principle is deeply rooted in efforts to manage the polluted sites, particularly in the soil-groundwater environment. Unfortunately, there is no ecosystem damage compensation mechanism generally accepted by all stakeholders. In this study, we establish an assessment framework and valuation methods for ecosystem damage induced by soil-groundwater pollution in an arid climate area based on a “pollution source → target (soil-groundwater) → receptor (humans, animals, and plants) → damages → stakeholders (human society and ecosystem)” model that is usually applied in groundwater risk assessment research. Five economic loss are included in the valuation methods: (1) human health loss, (2) emergency disposal cost, (3) direct economic loss, (4) ecological restoration cost, and (5) ecosystem services loss. We apply the framework to a case study in an arid climate area, northwest China and calculate the total economic loss from ecosystem damage in the case study at 12.6 million yuan. The largest proportion of the total loss was the ecological restoration cost (85.6%), followed by the emergency disposal cost (11.2%), and finally ecosystem services loss (3.2%). Valuation of ecosystem damage from environmental pollution is essentially a socioeconomic issue. This study supplies a new framework and methods for valuing ecosystem damage induced by pollution, and offers suggestions for environmental management to reduce the damage caused by soil-groundwater pollution to health and ecosystems.

Assessing the economic burden of multi-causal respiratory diseases in broiler farms in Iran.

The aim of this study was to find the direct economic losses due to the three viral causes of the avian respiratory syndrome, including Newcastledisease (ND), H9N2 influenza, and infectious bronchitis (IB) in stamped-out broiler farms during 2016-2017 across the country. This study was carried out on the information on cross-sectional monitoring in the years 2016-2017. The statistical society of the study was all the active broiler farms of the country stamped out due to respiratory syndrome. This study used compensation insurance data, and other sources. One-way ANOVA or Kruskal-Wallis tests were used to analyze normally and non-normally distributed data. In total, during the study period, 132 broiler farms and 1,723,131 fowls were stamped out. According to the results of the present investigation, the sum of costs and losses due to respiratory complex was 9.47 $US Million, 2016-2017 (5.72 from $US Million chicken meat losses and 3.75 $US Million was the total cost). ND was the main cause of economic losses and costs with 3.86 $US equal to 40.8% of the total. Cost of feeding was the highest followed by veterinary services and medicines, vaccination, and 1-day-old chicks costs with 2.27, 1.11, 0.33, and 0.036 $US Million, 2016-2017. In conclusion, we need to improve the preventive measures against respiratory viruses, especially NDV. Additionally, as the cost of feeding was the largest, it is important to shorten the time interval between disease occurrence and stamping out to reduce the cost.

The Utilization of Modified Zeolite for the Removal of Cs Ions in an Aqueous Solution: Adsorption Capacity, Isotherms, Kinetics and Microscopic Studies

Nuclear energy is a double-edged technology, which has a significant role in the chemical industry, but may bring about radioactivity and destruction. The 2011 Fukushima nuclear power plant accident caused by a tsunami, which flooded and led to tens of millions of disaster debris and tsunami deposits, severely disrupted the electricity supply in Japan and induced USD 211 billion worth of direct economic losses. Cs+ was easily dissolved in this accident, had a high chemical activity, and thus required an appropriate adsorption method. Zeolite is an effective removal adsorbent, which is suitable to be investigated. The present study uses natural zeolite and three inorganic modified zeolites. Furthermore, the effects of various factors are investigated. Kinetic models and the isothermal adsorption mechanism are also conducted. For microscale studies for the adsorption mechanism, scanning electron microscope (SEM) and X-ray diffraction (XRD) were involved in the study. The results indicate that the optimal dosage is 1.1 g and the maximum adsorption rate is around 80%. An alkaline environment is more conducive to the occurrence of adsorption. As for the isotherm and kinetic studies, the data fits better with the Redlich–Peterson isothermal model and intragranular diffusion model. In this small-scale experiment, the highest adsorption capacity was for Mg-zeolite at 6.53 mg/g. Finally, Mg-Zeolite presents the best adsorption capacity.

Risk Assessment and Prediction of Rainstorm and Flood Disaster Based on Henan Province, China

To reasonably evaluate and predict the loss of rainstorm and flood disaster, this study is based on the rainfall data and rainstorm and flood disaster data of 18 cities in Henan Province from 2010 to 2020, using GIS technology and weighted comprehensive evaluation method to analyze the risk of rainstorm and flood disaster factors in various regions. The four risk factors of hazard risk, hazard-pregnant environment sensitivity, hazard-bearing body vulnerability, and disaster resilience were analyzed in compartment analysis. At the same time, a new rainstorm and flood disaster prediction model was constructed in combination with the hybrid PSO-SVR algorithm. The research results show that there are many rivers in Henan Province, the terrain tends to be higher in the west and lower in the east, and most areas are low plains, making most cities in Henan Province at a moderate risk level. For the more developed cities such as Zhengzhou, Luoyang, and Nanyang, the hazard risk, sensitivity, vulnerability, and disaster resistance are high, and they are prone to heavy rains and floods. For the economically underdeveloped, the terrain is high or hills, such as Sanmenxia City; Xinyang City and other places have low hazard risk and are not prone to rainstorms and floods. By constructing a hybrid PSO-SVR model, selecting two representative cities of Zhengzhou and Luoyang, and predicting the daily rainfall, the number of disasters, and the direct economic loss, the calculated RMSE and MAPE values are both less than GA-SVR, the traditional SVR, and BPNN models, which have verified the superiority of the model proposed in this study and the practical value it brings. To further verify the prediction accuracy of the hybrid model, the average value of RMSE and MAPE of other 16 cities are calculated, and the result is still smaller than other three models, and the study can provide some decision-making references for the urban rainstorm and flood management.