Concurrent Flooding Research Articles

Power-Domain Interference Graph Estimation for Multi-hop BLE Networks

Traditional wisdom for network management allocates network resources separately for the measurement and communication tasks. Heavy measurement tasks may compete limited resources with communication tasks and significantly degrade overall network performance. It is therefore challenging for the interference graph, deemed as incurring heavy measurement overhead, to be used in practice in wireless networks. To address this challenge in wireless sensor networks, our core insight is to use power as a new dimension for interference graph estimation (IGE) such that IGE can be done simultaneously with the communication tasks using the same frequency-time resources. We propose to marry power-domain IGE with concurrent flooding to achieve simultaneous measurement and communication in BLE networks, where the power linearity prerequisite for power-domain IGE holds naturally true in concurrent flooding. With extensive experiments, we conclude the necessary conditions for the power linearity to hold and analyze several non-linearity issues of power related to hardware imperfections. We design and implement network protocols and power control algorithms for IGE in multi-hop BLE networks and conduct experiments to show that the marriage is mutually beneficial for both IGE and concurrent flooding. Furthermore, we demonstrate the potential of IGE in improving channel map convergence and convergecast in BLE networks.

Discerning the dynamics of urbanization-climate change-flood risk nexus in densely populated urban mega cities: An appraisal of efficient flood management through spatiotemporal and geostatistical rainfall analysis and hydrodynamic modeling

While the contribution of climate change towards intensifying urban flood risks is well acknowledged, the role of urbanization is less known. The present study, for the first time in flood management literature, explores whether and how unplanned-cum-urbanization may overshadow the contribution of extreme rainfall to flood impacts in densely populated urban regions. To establish this hypothesis and exemplify our proposed framework, the National Capital Territory (NCT) of Delhi in India, infamous for its concurrent flood episodes is selected. The study categorically explores whether the catastrophic 2023 urban flood could have resulted in a similar degree of urban exposure and damage, had it occurred anytime in the past. A comprehensive spatiotemporal and geo-statistical analysis of rainfall over 11 stations brought about through Innovative trend analysis, Omnidirectional and directional Semi-variogram analysis, and Gini Index indicates a rise in extreme rainfalls. High-resolution land-use maps indicate about 39.53 %, 52.66 %, 56.60 %, and 69.18 % of urban footprints during 1993, 2003, 2013, and 2023, while gradient direction maps indicate a prominent urban surge towards the North-West, West, and Southwest corridors. A closer inspection of the Greenness and Urbanity indices reveals a gradual decline in the green footprints and concurrent escalation in the urban footprints over the decades. A 3-way coupled MIKE+ model was set up to replicate the July 2023 flood event; indicating about 13 % of the area experience “high” and “very-high” flood hazards. By overlaying the flood inundation and hazard maps over land-use maps for 1993, 2003, and 2013, we further establish that a similar flood event would have resulted in lesser damage and building exposure. The study offers a set of flood management options for refurbishing resilience and limiting flood risks. The study delivers critical insights into the existing urban flood management strategies while delving into the urban growth-climate change-flood risk nexus.

Increasing risk of synchronous floods in the Yangtze River basin from the shift in flood timing

Floods are some of the most frequent and severe natural hazards worldwide. In the context of climate change, the risk of extreme floods is expected to increase in the future. While, the trends in flood timing and risk for flood synchronization remain unclear. In this study, the seasonality of flood peaks, annual maximum rainfall, and annual maximum soil moisture in the Yangtze River Basin were examined using observational and reanalysis data from 1949 to 2020. Changes in the timing of extreme events may increase the possibility of concurrent flooding, therefore the risk for synchronous floods were further explored. The results indicate that the seasonality of floods has a strong consistency with that of annual maximum rainfall. In the southern Yangtze River Basin, floods usually occur between early June and early July, with a delayed trend. However, they occur slightly later in the north, generally from late July to early August, with a tendency of advance. Overall, the timing of floods is positively correlated with rainfall and soil moisture peaks, and the correlation is much stronger for annual maximum rainfall. However, for more intense floods or for larger catchments, soil moisture plays an important role in modulating the variations in flood timing. Reverse latitudinal changes in flood timing are expected to result in more synchronous floods. The synchrony frequency exceeded 60 % for most of the stations, and the frequency was increasing for nearly half of the region, especially in the middle reaches, Poyang Lake and south of Dongting Lake. In addition, the flood synchrony scale in the south of the basin showed significant upward trends. These findings would provide important implications for flood risk management and adaptive strategy development.

Mitigation of Concurrent Flood and Drought Risks Through Land Modifications: Potential and Perspectives of Land Users

Modifications to land can serve to jointly reduce risks of floods and droughts to people and to ecosystems. Whether land modifications are implemented will depend on the willingness and ability of a diversity of actors. This article reviews the state of knowledge on land modification use in areas exposed to dual hydrologic risks and the land owners, managers, and users who directly make decisions about action on lands they control. The review presents a typology of land modifications and explains how land modifications interact with the hydrological cycle to reduce risks. It then addresses the roles and perspectives of the land owners, managers, and users undertaking land modifications, summarizing theories explaining motivations for, as well as barriers to and enablers of, land modification implementation. The analysis reveals geographical differences in narratives on land modifications as well as knowledge gaps regarding variation across actors and types of land modifications.

COFlood: Concurrent Opportunistic Flooding in Asynchronous Duty Cycle Networks

For energy constraint wireless IoT nodes, their radios usually operate in duty cycle mode. With low maintenance and negotiation cost, asynchronous duty cycle radio management is widely adopted. To achieve fast network flooding is challenging in asynchronous duty cycle networks. Recently, concurrent flooding, which allows a set of nodes (called concurrent senders ) to immediately broadcast the received packet without any backoff, is a promising approach to improve the flooding speed. We observe that selecting either large or small number of concurrent senders cannot achieve the optimal flooding speed in different deployments. There is a tradeoff between the degradation of concurrent broadcast efficiency and the missing of early receiving chance. In this article, we propose COFlood (Concurrent Opportunistic Flooding), a practical and efficient concurrent flooding protocol in asynchronous duty cycle networks. First, COFlood constructs a concurrent flooding tree in distributed manner. The non-leaf nodes are selected as concurrent senders and they can cover the entire network while reserving the most capacity of concurrent broadcast for later added opportunistic concurrent senders. Moreover, we find that exploiting both early wake-up nodes and long lossy links can speed up the concurrent flooding tree-based network flooding by increasing the early receiving chances. Then, COFlood develops a lightweight method to select the nodes that meet the conditions of these two opportunities as opportunistic concurrent senders. We implement COFlood in TinyOS and evaluate it on two real testbeds. In comparison with state-of-the-art concurrent flooding protocol, completion time and energy consumption can be reduced by up to 35.3% and 26.6%.

Modeling NaTech-related domino effects in process clusters: A network-based approach

Extreme disasters and their resulting cascading accidents are always being a considerable threat to process cluster safety. However, many current assessments of the domino effects within process clusters do not consider the uncertainty of the primary accidents triggered by natural hazards. Additionally, high-efficiency methods to model the complex dependencies of large-scale process clusters are still lacking. Hence, this paper expands a hazard scenario module at the front end of the assessment framework of a domino effect to consider the response of installations to hazard loads. Simultaneously, a network-based approach is developed to model the NaTech-related domino effect. The constructed network imposes two constraints, escalation and probability thresholds, to reduce the computational complexity of traversing potential propagation pathways. As a result, the proposed method can be applied to large-scale process clusters. The safety analysis of an oil storage base subject to hurricanes and concurrent flooding shows that the proposed method can clarify the role of each unit in a local and cross-community domino effect at the node and community levels, respectively. The results inform the implementation of emergency responses to accidents. Furthermore, sources of uncertainty indicate that the network structure of the NaTech-related domino effect is sensitive to hazard intensity.

Double Trouble: Examining Public Protective Decision-Making During Concurrent Tornado and Flash Flood Threats in the U.S. Southeast

Double Trouble: Examining Public Protective Decision-Making During Concurrent Tornado and Flash Flood Threats in the U.S. Southeast

Google Earth Engine for concurrent flood monitoring in the lower basin of Indo-Gangetic-Brahmaputra plains.

The present study focused on the recent flood inundation (July 2020) that occurred in the lower Indo-Gangetic-Brahmaputra plains (IGBP) using concurrent C-band Sentinel-1A Synthetic Aperture Radar images in Google Earth Engine. The study exhibited that a substantial proportion of IGBP (40,929 km2) was inundated primarily in Bangladesh (9.09% of the total inundation), Assam (8.99%), and Bihar (6.29%) during June–July 2020. The severe impact of flood inundation was observed in croplands (4.41% of the total cropland), followed by settlements (20.98% of the total settlements) that affected a large population (~ 10,046,262) in IGBP. The prevailing COVID-19 pandemic has debilitated the efforts of mitigation and responses to flooding risks. The study necessitates adopting an integrated, multi-hazard, multi-stakeholder approach with an emphasis on self-reliance of the community for sustenance with local resources and practices.

Bonnet Carré Spillway freshwater transport and corresponding biochemical properties in the Mississippi Bight

Large freshwater pulses to coastal ecosystems change local hydrologic regimes and alter biogeochemical processes. The Mississippi Bight coastal ecosystem, located in the northern Gulf of Mexico shelf, is influenced by extensive freshwater inputs: the Mississippi River (MSR) and several smaller rivers to the east. Under river flood conditions, MSR waters flow through the Bonnet Carré Spillway (BCS) to relieve pressure on levees in New Orleans, Louisiana. In 2015, mild wintertime temperatures and heavy rainfall throughout the MSR watershed led to extreme flooding and prompted an unusually early BCS opening on January 10, 2016 for 23 days. This study examines the effects of such intermittent freshwater diversions on local shelf circulation, planktonic distributions, and potential contaminant transport pathways. Physical, chemical, and remote sensing data collected one month after the BCS opening suggested the region was comprised of three water masses: shelf saltwater, MSR waters, and local river waters. Observations and circulation model results showed the BCS waters remained within the estuarine lakes and sounds, where winter wind patterns mixed the waters and prevented BCS waters from flowing onto the shelf. Freshwater within the Mississippi Bight was primarily from concurrent flooding of local rivers. Two distinct clusters of microplankton (offshore versus nearshore stations) and zooplankton (Chandeleur Sound versus other stations) community compositions were detected. No algal blooms were observed during this BCS opening. The 2016 wintertime BCS opening resulted in muted effects on the sounds and shelf because of its short duration and uncharacteristically early release.

Clustering of concurrent flood risks via Hazard Scenarios

The study of multiple effects of a number of variables, and the assessment of the corresponding environmental risks, may require the adoption of suitable multivariate models when the variables at play are dependent, as it often happens in environmental studies. In this work, the flood risks in a given region are investigated, in order to identify specific spatial sub-regions (clusters) where the floods show a similar behavior with respect to suitable (multivariate) criteria. The reason of the work is three-fold, and the outcomes have deep implications in the hydrological practice:(i) such a regionalization (as it is called in hydrology) may provide useful indications for deciding which gauge stations have a similar (stochastic) behavior; (ii) the spatial clustering may represent a valuable tool for investigating ungauged basins present in a given “homogeneous” Region; (iii) the estimate of extreme design values may be improved by using all the observations collected in a cluster (instead of only single-station data). For this purpose, a Copula-based Agglomerative Hierarchical Clustering algorithm – a key tool in geosciences for the analysis of the dependence information – is proposed. The procedure is illustrated via a case study involving the Po river basin, the largest Italian one. A comparison with a previous attempt to cluster the gauge stations present in the same spatial region is also carried out. The sub-regions picked out by the clustering procedure outlined here agree with previousresults obtained via heuristic hydrological and meteorological reasonings, and identify spatial areas characterized by similar floodregimes.

A computational method of critical well spacing of CO2 miscible and immiscible concurrent flooding

Abstract Based on the theory of non-Darcy seepage, a mathematical model for CO2 miscible and immiscible concurrent flooding considering changes of oil viscosity and threshold pressure gradient of oil and CO2 is established. A computational method of critical well spacing of CO2 miscible and immiscible concurrent flooding in ultra-low permeability reservoirs is deduced by solving the distribution of CO2 concentration in miscible flooding area with the mass transfer-diffusion-absorption equation and solving the saturation equation of immiscible affected area with characteristic line method. A critical well spacing example is built in the F142 and G89 reservoir blocks and the results show: (1) The critical well spacing increases with gas injection pressure, while decreases with gas injection speed; (2) The contribution of length in pure CO2 seepage area to the critical well spacing is the largest, the contribution of length in CO2-Oil effective mass transfer area and immiscible affected area is secondary, the contribution of pure oil area is the least, the gap of length between pure CO2 seepage area and CO2-Oil effective mass transfer area and immiscible affected area decreases with gas injection speed and it increases with the decreasing of gas injection speed, meanwhile, the law is more significant; (3) Pressure drop gradient of miscible affected area is significantly different from that of immiscible affected area and pressure drop gradient of CO2-Oil effective mass transfer area in miscible affected area is bigger than that of immiscible affected area.

Solution method of overtopping risk model for earth dams

Hydrologic risk analysis relies on a series of probabilistic analyses, and it is a complex problem in estimating the probability distributions of multiple independent and random variables. The goal of this study is to presents the procedure and application of a probability-based risk analysis methodology to evaluate earth dam overtopping risk that induced by concurrent flood and wind. The uncertainty arising from initial water surface level, flood, wind velocity, and dam height are discussed in this research. The improved Monte Carlo simulation and mean-value first-order second-moment method are used to solve the proposed dam overtopping risk model, respectively. The nonparametric kernel density estimation method, which can better learn the complex multimodal characteristic of probability density function than that of traditional parametric estimation method, is employed to improve the probability density function of initial water surface level. The latin hypercube sampling is introduced to generate uniform random number, which improves the efficient and stability compared with simple random sampling. Afterward, an application to the Dongwushi Reservoir in China illustrates that the dam overtopping risk computed using the improved Monte Carlo simulation is lower than that using mean-value first-order second-moment method. Furthermore, the sensitivity analysis show that initial water surface level is more sensitive to overtopping risk than wind velocity.

A new method to assess the risk of local and widespread flooding on rivers and coasts

AbstractTo date, national‐ and regional‐scale flood risk assessments have provided valuable information about the annual expected consequences of flooding, but not the exposure to widespread concurrent flooding that could have damaging consequences for people and the economy. We present a new method for flood risk assessment that accommodates the risk of widespread flooding. It is based on a statistical conditional exceedance model, which is fitted to gauged data and describes the joint probability of extreme river flows or sea levels at multiple locations. The method can be applied together with data from models for flood defence systems and economic damages to calculate a risk profile describing the probability distribution of economic losses or other consequences aggregated over a region. The method has the potential to augment national or regional risk assessments of expected annual damage with new information about the likelihoods, extent and impacts of events that could contribute to the risk.

Theory and application of loss of life risk analysis for dam break

The loss of life risk evaluation model for dam break is built in this paper. By using an improved Monte Carlo method, the overtopping probability induced by concurrent flood and wind is calculated, and the Latin Hypercube Sampling is used to generate random numbers. The Graham method is used to calculate the loss of life resulting from dam failure. With Dongwushi reservoir located at Hebei Province taken as an example, the overtopping probability induced by concurrent flood and wind is calculated as 4.77×10−6. Loss of life is 24 220 when the warning time is 0.25–1 h and flood severity understanding is vague, which indicates that the risk is intolerable. The losses of life under three other conditions are tolerable: warning time 0.25–1 h, and precise flood severity understanding; warning time more than 1 h, and vague flood severity understanding; warning time more than 1 h, and precise flood severity understanding.

Development of Flood Forecasting System Using Statistical and ANN Techniques in the Downstream Catchment of Mahanadi Basin, India

The floods in river Mahanadi delta are due to either dam release of Hirakud or due to contribution of intercepted catchment between Hirakud dam and delta. It is seen from post-Hirakud periods (1958) that out of 19 floods 14 are due to intercepted catchment contribution. The existing flood forecasting systems are mostly for upstream catchment, forecasting the inflow to reservoir, whereas the downstream catchment is devoid of a sound flood forecasting system. Therefore, in this study an attempt has been made to develop a workable forecasting system for downstream catchment. Instead of taking the flow time series concurrent flood peaks of 12 years of base and forecasting stations with its corresponding travel time are considered for analysis. Both statistical method and ANN based approach are considered for finding the peak to reach at delta head with its corresponding travel time. The travel time has been finalized adopting clustering techniques, there by differentiating high, medium and low peaks. The method is simple and it does not take into consideration the rainfall and other factors in the intercepted catchment. A comparison between both methods are tested and it is found that the ANN methods are better beyond the calibration range over statistical method and the efficiency of either methods reduces as the prediction reach is extended. However, it is able to give the peak discharge at delta head before 24 hour to 37 hour for high to low peaks.

Flood frequency and routing processes at a confluence of the middle Yellow River in China

AbstractFloods cause environmental hazards and influence on socio‐economic activities. In this study, we evaluated the historic flood frequency at a confluence in the middle Yellow River, China. A non‐parametric, multivariate, empirical, orthogonal function matrix model, which consists of time correlation coefficients of flood discharge at different gauge stations and flood events was used for the analysis of flood frequency. The model addresses the characteristics of confluent floods such as frequency and the probability in multiple tributary rivers. Flood frequency analysis is often coupled with studies of hydrological routing processes that reduce the flood capacity of the rivers. Flood routing to the confluence were simulated using kinematic wave theory. Results of this flood frequency analysis showed that flooding frequency has intensified in the past 500 years, especially during the 19th century. Flooding in streams above the confluence was more frequent than in streams below the confluence. Over the last 2000 years, concurrent flooding in multiple tributary rivers accounted for 67.5% of the total flooding in the middle Yellow River. Simulation of flood routing processes shows that the decreased flooding capacity and elevated river bed of the shrunken main channel leads to an increased flood wave propagation time (24–52.3 h) in the study area after 1995. The model indicates that human activities, such as constructions of the Sanmenxia Dam, have changed flood routing boundary conditions and have contributed to the increased flood frequency at the confluence. Copyright © 2007 John Wiley & Sons, Ltd.

Estimating a regional flood frequency distribution

When floods at different sites are assumed to arise from the same distribution except for scale (U.S. Geological Survey's Index Flood Method), one can attempt to identify the dimensionless flood‐flow frequency distribution by normalizing small samples by each sample's sample mean. Unfortunately, the resultant curve may be a poor description of the true dimensionless flood distribution. This problem can be overcome by working with the logarithms of the peak flow values and using unbiased moment or probability weighted moment estimators. However, the correlation among concurrent flood flows in a region is shown to place severe limits the accuracy with which a distribution's moments can be estimated with many such correlated records.