Rainfall threshold determination for flash flood warning in mountainous catchments with consideration of antecedent soil moisture and rainfall pattern

Flash flood disaster is a prominent issue threatening public safety and social development throughout the world, especially in mountainous regions. Rainfall threshold is a widely accepted alternative to hydrological forecasting for flash flood warning due to the short response time and limited observations of flash flood events. However, determination of rainfall threshold is still very complicated due to multiple impact factors, particular for antecedent soil moisture and rainfall patterns. In this study, hydrological simulation approach (i.e., China Flash Flood-Hydrological Modeling System: CNFF-HMS) was adopted to capture the flash flood processes. Multiple scenarios were further designed with consideration of antecedent soil moisture and rainfall temporal patterns to determine the possible assemble of rainfall thresholds by driving the CNFF-HMS. Moreover, their effects on rainfall thresholds were investigated. Three mountainous catchments (Zhong, Balisi and Yu villages) in southern China were selected for case study. Results showed that the model performance of CNFF-HMS was very satisfactory for flash flood simulations in all these catchments, especially for multimodal flood events. Specifically, the relative errors of runoff and peak flow were within?±?20%, the error of time to peak flow was within?±?2 h and the Nash–Sutcliffe efficiency was greater than 0.90 for over 90% of the flash flood events. The rainfall thresholds varied between 93 and 334 mm at Zhong village, between 77 and 246 mm at Balisi village and between 111 and 420 mm at Yu village. Both antecedent soil moistures and rainfall temporal pattern significantly affected the variations of rainfall threshold. Rainfall threshold decreased by 8–38 and 0–42% as soil saturation increased from 0.20 to 0.50 and from 0.20 to 0.80, respectively. The effect of rainfall threshold was the minimum for the decreasing hyetograph (advanced pattern) and the maximum for the increasing hyetograph (delayed pattern), while it was similar for the design hyetograph and triangular hyetograph (intermediate patterns). Moreover, rainfall thresholds with short time spans were more suitable for early flood warning, especially in small rural catchments with humid climatic characteristics. This study was expected to provide insights into flash flood disaster forecasting and early warning in mountainous regions, and scientific references for the implementation of flash flood disaster prevention in China.     

Socioeconomic vulnerability and electric power restoration timelines in Florida: the case of Hurricane Irma

Large-scale damage to the power infrastructure from hurricanes and high-wind events can have devastating ripple effects on infrastructure, the broader economy, households, communities, and regions. Using Hurricane Irma’s impact on Florida as a case study, we examined: (1) differences in electric power outages and restoration rates between urban and rural counties; (2) the duration of electric power outages in counties exposed to tropical storm force winds versus hurricane Category 1 force winds; and (3) the relationship between the duration of power outage and socioeconomic vulnerability. We used power outage data for the period September 9, 2017–September 29, 2017. At the peak of the power outages following Hurricane Irma, over 36% of all accounts in Florida were without electricity. We found that the rural counties, predominantly served by rural electric cooperatives and municipally owned utilities, experienced longer power outages and much slower and uneven restoration times. Results of three spatial lag models show that large percentages of customers served by rural electric cooperatives and municipally owned utilities were a strong predictor of the duration of extended power outages. There was also a strong positive association across all three models between power outage duration and urban/rural county designation. Finally, there is positive spatial dependence between power outages and several social vulnerability indicators. Three socioeconomic variables found to be statistically significant highlight three different aspects of vulnerability to power outages: minority groups, population with sensory, physical and mental disability, and economic vulnerability expressed as unemployment rate. The findings from our study have broader planning and policy relevance beyond our case study area, and highlight the need for additional research to deepen our understanding of how power restoration after hurricanes contributes to and is impacted by the socioeconomic vulnerabilities of communities.     

Maritime tsunami evacuation guidelines for the Pacific Northwest coast of Oregon

Recent tsunamis affecting the West Coast of the USA have resulted in significant damage to ports and harbors, as well as to recreational and commercial vessels attempting to escape the tsunami. With the completion of tsunami inundation simulations for a distant tsunami originating from the Aleutian Islands and a locally generated tsunami on the Cascadia subduction zone (CSZ), the State of Oregon is now able to provide guidance on the magnitudes and directions of the simulated currents for the Oregon coast and shelf region. Our analyses indicate that first wave arrivals for an Aleutian Island event would take place on the north coast,?~?3 h 40 min after the start of the earthquake,?~?20 min later on the southern Oregon coast. The simulations demonstrated significant along-coast variability in both the tsunamis water levels and currents, caused by localized bathymetric effects (e.g., submarine banks and reefs). A locally generated CSZ event would reach the open coast within 7–13 min; maximum inundation occurs at?~?30–40 min. As the tsunami current velocities increase, the potential for damage in ports and harbors correspondingly increases, while also affecting a vessels ability to maintain control out on the ocean. Scientific consensus suggests that tsunami currents?<?1.54 m/s are unlikely to impact maritime safety in ports and harbors. No such guidance is available for boats operating on the ocean, though studies undertaken in Japan suggest that velocities in the region of 1–2 m/s may be damaging to boats. In addition to the effects of currents, there is the added potential for wave amplification of locally generated wind waves interacting with opposing tsunami currents in the offshore. Our analyses explore potential wave amplification effects for a range of generic sea states, ultimately producing a nomogram of wave amplification for a range of wave and opposing current conditions. These data will be useful for US Coast Guard and Port authorities as they evaluate maritime tsunami evacuation options for the Oregon coast. Finally, we identify three regions of hazard (high, moderate, and low) across the Oregon shelf, which can be used to help guide final designation of tsunami maritime evacuation zones for the coast.     

An agent-based evacuation model for the 2011 Brisbane City-scale riverine flood

In this study, an agent-based model is proposed in order to provide new insights into the policy analysis and strategy assessment of city-scale evacuation management. The proposed model is suitable for assessment of the influence of different departure times and communications among peer evacuees on the number of residents at risk who arrive at official shelters. A case study is applied to build a simulation model for the coastal city of Brisbane in Australia. The Brisbane River catchment experiences regular flooding almost every year; the second severest flood since the twentieth century occurred in 2011. During that event, over 15,000 properties were inundated and around 3600 households evacuated in metropolitan Brisbane alone. Making use of high-performance computing clusters, the evacuation simulation was coupled with results from a validated hydrodynamic model to test a variety of escaping scenarios based on the 2011 flood situation. This case study demonstrates the proposed model’s capacity to represent the dynamic evacuation process and also shows that the model is able to help develop flood emergency plans and evaluate response measures through exploring key elements in a range of scenarios.     

Effect of climatic oscillations on flood occurrence on Papaloapan River,México,during the 1550–2000 period

This study presents a chronology of historical and measured flood events in the Papaloapan River basin of Mexico during 450 years. Twenty-eight historical floods were recorded during the period 1550–1948 on this river and one flood event (1969) in the instrumental era (1949–2000), of which 14 were extraordinary floods and only 15 were catastrophic ones. There were several flood-rich decades during 1860–1870, 1880–1890, 1920–1930 and 1940–1950. Wavelet analysis found a significant flooding periodicity of 58 years. The wavelet coherence analysis found that flooding had an in-phase relationship with the Atlantic Multidecadal Oscillation and also with the Pacific Decadal Oscillation. Logistic regression corroborated that there exists a positive relationship between floods events and these two natural climatic oscillations. The logistic regression model predicted correctly 92% of flood events.     

Application on Floor Water Inrush Evaluation Based on AHP Variation Coefficient Method with GIS

The prediction and prevention of floor water inrush is directly related to the safety of the coal mine production. The previous evaluation method of floor water inrush was more one-sided and lacked main control factors related to mining conditions. In order to evaluate the floor water inrush more accurately, under the project background of geological data of Wanglou coal mine, stope width, mining depth, fault scale index, water pressure, water abundance and thickness of aquifer were selected as main controlling factors of floor water inrush. Combined with the subjective weight analytical hierarchy process and the objective weight variation coefficient method, the weight coefficients corresponding to the main controlling factors were obtained respectively. The thematic map of the risk assessment of coal seam floor water inrush was drawn by combining the constructed comprehensive weight vulnerability index model and geographic information system. The results show that: ① according to the actual geological data of mine, two fault related factors were removed. And stope width and mining depth were increased as the main controlling factors to evaluate floor water inrush. It is easier to compare and calculate the weight of evaluation factors. ② The constructed comprehensive weight vulnerability index model can comprehensively evaluate the risk of floor water inrush. And the results of the evaluation are more accurate. ③ The related thematic maps can directly reflect the risk of floor water inrush, which is of guiding significance for the prediction and prevention of coal seam floor water inrush.     

Numerical ANFIS-Based Formulation for Prediction of the Ultimate Axial Load Bearing Capacity of Piles Through CPT Data

This study explores the potential of adaptive neuro-fuzzy inference systems (ANFIS) for prediction of the ultimate axial load bearing capacity of piles (P_u) using cone penetration test (CPT) data. In this regard, a reliable previously published database composed of 108 datasets was selected to develop ANFIS models. The collected database contains information regarding pile geometry, material, installation, full-scale static pile load test and CPT results for each sample. Reviewing the literature, several common and uncommon variables have been considered for direct or indirect estimation of P_u based on static pile load test, cone penetration test data or other in situ or laboratory testing methods. In present study, the pile shaft and tip area, the average cone tip resistance along the embedded length of the pile, the average cone tip resistance over influence zone and the average sleeve friction along the embedded length of the pile which are obtained from CPT data are considered as independent input variables where the output variable is P_u for the ANFIS model development. Besides, a notable criticism about ANFIS as a prediction tool is that it does not provide practical prediction equations. To tackle this issue, the obtained optimal ANFIS model is represented as a tractable equation which can be used via spread sheet software or hand calculations to provide precise predictions of P_u with the calculated correlation coefficient of 0.96 between predicted and experimental values for all of the data in this study. Considering several criteria, it is represented that the proposed model is able to estimate the output with a high degree of accuracy as compared to those results obtained by some direct CPT-based methods in the literature. Furthermore, in order to assess the capability of the proposed model from geotechnical engineering viewpoints, sensitivity and parametric analyses are done.     

Laboratory Investigation of the Influence of Geotextile on the Stress–Strain and Volumetric Change Behavior of Sand

This paper presents the results of triaxial tests conducted for the investigation of the influence of geotextile on both the stress–strain and volumetric change behavior of reinforced sands. Tests were carried out on loose sand. The experimental program includes drained compression tests on samples reinforced with different values of both geotextile layers (1 ≤ Ng ≤ 3) and confining pressure (\(\upsigma_{\text{c}}^{\prime }\)) varying from 50 to 200 kPa. Tests show that the contribution of geotextile is negligible until an axial strain threshold that range between 2.5% for a confining pressure of 50 kPa to lower than 1% for 100 and 200 kPa confining pressure. At higher values of ε_a, geotextile induces a quasi-linear increase in the stress deviator (q) and volume contraction in the reinforced sand. Tests show a negligible influence of the number of geotextile layers (Ng) on the contribution of geotextile to both stress–strain and volumetric change, when normalized with Ng. Tests also show that the contribution of geotextile to the stress–strain mobilization augments with the increase in the confining pressure, while its contribution to the volume contraction decreases with the increase in the confining pressure. The reinforced soil becomes contracting in the case of 2 and 3 geotextile layers.     

Effects of providing measures against earthquakes: experimental studies on the perceived risks of disasters and disaster preparedness intentions in Japan

This research examined the effects of providing measures against disasters on recipients’ perceived risks and preparedness intentions by conducting two experimental studies. A provision of a set of emergency food was manipulated in the first experiment. Participants (N = 143) were randomly assigned to the provided condition or non-provided condition. In the second experiment (N = 123), provision of an emergency toilet kit was manipulated. The results of the two experiments consistently indicated that (1) the provision of a measure increased the recipients’ perceived risks of the disaster concerned, (2) it increased their preparedness intentions for the disaster, and (3) it had no effects on perceived risks of or preparedness intentions against disasters unrelated to the measure provided. These results were contrary to the prediction deduced from the protection effect and single action effect. The findings in this study encourage promoting the risk management policy of providing people with disaster measures as the first step in disaster preparedness.     

The role of social capital,personal networks,and emergency responders in post-disaster recovery and resilience: a study of rural communities in Indiana

The factors that explain the speed of recovery after disaster remain contested. While many have argued that physical infrastructure, social capital, and disaster damage influence the arc of recovery, empirical studies that test these various factors within a unified modeling framework are few. We conducted a mail survey to collect data on household recovery in four small towns in southern Indiana that were hit by deadly tornadoes in March 2012. The recovery effort is ongoing; while many of the homes, businesses, and community facilities were rebuilt in 2013, some are still under construction. We investigate how households in these communities are recovering from damage that they experienced and the role of social capital, personal networks, and assistance from emergency responders on the overall recovery experience. We used an ordered probit modeling framework to test the combined as well as relative effects of (a) damage to physical infrastructures (houses, vehicles, etc.); (b) recovery assistance from emergency responders (FEMA) as well as friends and neighbors; (c) personal network characteristics (size, network density, proximity, length of relationship); (d) social capital (civic engagement, contact with neighbors, trust); and (e) household characteristics. Results show that while households with higher levels of damage experienced slower recovery, those with recovery assistance from neighbors, stronger personal networks, and higher levels of social capital experienced faster recovery. The insights gained in this study will enable emergency managers and disaster response personnel to implement targeted strategies in facilitating post-disaster recovery and community resilience.