Extreme Flood Research Articles

How do agricultural polders modulate nutrient dynamics under extreme flooding: Insights for water management in lowland areas

How do agricultural polders modulate nutrient dynamics under extreme flooding: Insights for water management in lowland areas

Innovative trend analysis of precipitation changes over Nigeria: A case study of locations across the Niger and Benue Rivers

Precipitation has become a major topic of discussion in the subject of climate change. Studies have presented correlative relationships between climate change and the existing alterations in the global water cycle, leading to more extreme precipitation events, including both droughts and floods. This has shown severe impacts on agriculture, water resources, ozone levels, and human settlements. Accordingly, this study analyzes the trends in 40 years (1981-2020) of total monthly and annual precipitation data from six selected locations in Nigeria, using both the Mann-Kendall (MK) and new Sen's innovative trend analysis (ITA) method. The stations were chosen because of their close proximity to the Niger or Benue Rivers. The data were visually analyzed using boxplots to identify seasonal patterns and outliers, and the results of the MK test show that four of the six locations detected trends for annual and wet season precipitation variations. However, this was not applicable to dry season variations. The ITA test results show that only Kainji has an increasing trend in total annual and wet season precipitation, especially for high precipitation values, whereas other locations show decreasing trends for maximum precipitation values. A comparison of the two tests suggests that, the ITA test is more sensitive in detecting trends in precipitation data for the study locations. Overall, this study provides useful information for understanding the precipitation patterns in Nigeria, and can assist in planning and implementing appropriate water resource management strategies, with regards to the major rivers in the region.

Non-stationarity analysis of flood extremes under climate change and human activities in the Yuan River Basin, China

Non-stationarity analysis of flood extremes under climate change and human activities in the Yuan River Basin, China

An updated reference table for extreme flood hydrology methods at UK dams

An updated reference table for extreme flood hydrology methods at UK dams

Discussion: An updated reference table for extreme flood hydrology methods at UK dams

Discussion: An updated reference table for extreme flood hydrology methods at UK dams

INDOFLOODS: A Comprehensive Database for Flood Events in India Enhanced with Catchment Attributes

Abstract Despite floods causing significant loss of life and property, datasets to characterize flooding events in developing countries such as India are not widely available, hampered by limited hydrometric records. Current flood databases are limited to continental river basins, case studies, and government reports, which doesn’t represent the diversity of flooding in terms of climate, basin morphometry, and triggering mechanisms. This first-of-its-kind flood events database called INDOFLOODS is developed using a unique approach of combining long-term station discharge observations with official flooding thresholds for warning and danger water level. Flooding information include start and end time, peak flood level and discharge and its date of occurrence, flood volume, event duration, time to peak, and recession time. Along with metadata such as upstream catchment area, coordinates, shapefiles, river and tributary names, the database is augmented with large number of geomorphological, climatological, event-scale precipitation, landcover, soil, lithology, and anthropogenic characteristics derived at the catchment scale. Preliminary data analysis based on envelope curves shows that the magnitude of extreme floods in India is higher than those reported in the United States. While every dataset has limitations, this collation of flooding events with a plethora of causative hydrogeomorphic factors in a standardized format will be a major asset for the community and serve as an example for how inconsistent data records in developing countries can be turned into useful flood event databases for data-driven studies. This large sample database is expected to cater to a wide range of applications advancing flood research and management, such as trend analysis, hazard and severity assessment, calibration and validation of hydrological and hydraulic models, and developing new metrics for impact assessment.

SWOT Reveals How the 2024 Disastrous Flood in South Brazil Was Intensified by Increased Water Slope and Wind Forcing

AbstractClimate change is expected to increase the frequency and intensity of flooding, emphasizing the need to better understand these events. Satellite observations provide essential information, and the recent launch of SWOT offers new opportunities to investigate flood dynamics. Here, we use SWOT observations to detect significant hydrologic changes during an unprecedented 2024 flood in southern Brazil. In the Jacuí and Guaíba Rivers, water slopes increased dramatically–up to 11 times (from 0.82 to 9.59 cm/km) and 21 times (0.31–6.58 cm/km) compared to stable conditions. SWOT‐derived surface water elevations captured 99% of water level variability compared to in situ observations. Additionally, flooding in Patos Lagoon was intensified by NE–SW wind forcing, causing water levels to rise by up to 40 cm, worsening the flood event. SWOT proves a unique opportunity to understand extreme flooding events, providing new support for flood risk management in the context of climate change.

Using Machine Learning to Predict Suspended Sediment Transport under Climate Change

Abstract Sediment transport, an important element of the erosion‒sedimentation cycle, can be very high during extreme flood events and can cause hydromorphological changes within river networks. Therefore, improved sediment transport predictions are needed to establish sediment management at the catchment scale. A machine learning model (i.e., XGBoost) and a sediment rating curve method were tested for predicting the suspended sediment load in the Sora River catchment in Slovenia. The evaluation of the models based on the historical data for 2016–2021 revealed that XGBoost outperformed the sediment rating curve model and resulted in a lower bias (i.e., approximately 15%). The XGBoost model was used to predict future suspended sediment load dynamics. Three representative concentration pathway (RCP) scenarios (RCP2.6, RCP4.5, and RCP8.5) and several climate change models were used. The rainfall–runoff model was set up, calibrated, validated and applied to simulate future daily discharge data, as this was the required input for the XGBoost and sediment rating curve models. The simulation results indicate that suspended sediment load is expected to increase in the future in the range 15–20% under both the RCP4.5 and RCP8.5 scenarios. Additionally, the number of days with a suspended sediment concentration (SSC) greater than 25 mg/l, which is often used an indicator of inadequate water quality, is expected to increase by 2–4%, whereas some models indicate an increase of up to 8%. Erosion and sediment management mitigation measures need to be applied in the future to ensure adequate water quality and good ecological status of the river.

Mimořádné projevy počasí v Jeseníkách

The article describes detailed overview of significant meteorological events in the Jeseníky region, including extreme precipitation, floods, and temperature fluctuations from around 1500 to the present. In addition to the actual data from the CHMI database, historical flood events are included, which are better documented than meteorological extremes. The literature evidence is supplemented by values specific for the Jeseníky region, so the paper provides a broad overview of climatic extremes with an emphasis on long-term observations and historical contexts that reveal exceptional climatic situations in this part of the Czech Republic.

Ensuring Africa's Food Security by 2050: The Role of Population Growth, Climate-Resilient Strategies, and Putative Pathways to Resilience.

Africa is grappling with severe food security challenges driven by population growth, climate change, land degradation, water scarcity, and socio-economic factors such as poverty and inequality. Climate variability and extreme weather events, including droughts, floods, and heatwaves, are intensifying food insecurity by reducing agricultural productivity, water availability, and livelihoods. This study examines the projected threats to food security in Africa, focusing on changes in temperature, precipitation patterns, and the frequency of extreme weather events. Using an Exponential Growth Model, we estimated the population from 2020 to 2050 across Africa's five sub-regions. The analysis assumes a 5% reduction in crop yields for every degree of warming above historical levels, with a minimum requirement of 225 kg of cereals per person per year. Climate change is a critical factor in Africa's food systems, with an average temperature increase of approximately +0.3 °C per decade. By 2050, the total food required to meet the 2100-kilocalorie per adult equivalent per day will rise to 558.7 million tons annually, up from 438.3 million tons in 2020. We conclude that Africa's current food systems are unsustainable, lacking resilience to climate shocks and relying heavily on rain-fed agriculture with inadequate infrastructure and technology. We call for a transformation in food systems through policy reform, technological and structural changes, solutions to land degradation, and proven methods of increasing crop yields that take the needs of communities into account.

The Bio Steel Cycle Meets Indoor Farming - CCUS with the SusCiP Principle in Agriculture

The World climate is changing, with a great impact on global food production systems. Extreme weather events, floods, wildfires and draughts are phenomena of disrupted previously stable natural weather patterns, which are vital for crop production and animal husbandry alike. Most of the World’s food is produced in temperate climatic zones rich in arable land and those are affected by the increasing unpredictability of previously naturally occurring seasons and weather conditions. This work aims to provide a possible sustainable solution to food production challenges under the pressures of climate change. Changing food production methods by moving to indoor agriculture poses great challenges and immense opportunities at the same time. Technical solutions are currently researched and explored by innovators, governments and industry leaders alike. The previously developed Bio Steel Cycle can be seen as the nucleus for other industries, including food production, and could be the starting point for a new standard in all production systems: The SusCip principle.

Design of Combined Rainwater-Harvesting and Stormwater-Detention System with Passive Release for New Buildings in Taiwan

Taiwan experiences abundant rainfall, but faces significant water shortages, making rainwater harvesting (RWH) a potential alternative water source. Additionally, extreme rainfall events strain urban flood control systems, highlighting the need for integrated stormwater management. To address these challenges, Taiwan mandates stormwater detention (SWD) in new buildings. However, the current RWH and SWD systems are designed independently, with no combined design guidelines available. This study proposes three combined RWH and SWD systems, series, parallel, and enhanced parallel with a valve using a passive release mechanism. System performance was evaluated through short-term and long-term simulations. Short-term simulations were conducted to ensure the system’s compliance with the domestic flood control design standards. These simulations assessed the peak flow mitigation and lag times for 5-, 10-, and 25-year design storms under four scenarios. Long-term simulations used historical rainfall data to analyze the differences in the combined systems and operational plans for continuous rainfall events. Three performance indicators—volumetric reliability, the stormwater retention ratio, and the stormwater detention ratio—were employed to assess water supply and the stormwater detention performance. The short-term simulation results revealed that the system performance was sensitive to the initial conditions. The series and parallel systems performed well, while the enhanced parallel system outperformed the others under specific initial conditions and valve operations. In contrast, long-term simulations revealed that the series and parallel systems achieved higher stormwater retention and a more stable performance than the enhanced parallel system. Among the three systems, the parallel system offers reduced installation space, lower costs, and easier maintenance, making it the recommended option for Taiwan. This study provides valuable guidance for designing combined RWH and SWD systems.

Peatland Hydro-Climatological Parameters Variability in Response to 2019–2022 Climate Anomalies in the OKI Regency

Peatlands in OKI Regency are highly flammable during extreme dry seasons and experience flooding during extreme rainy seasons. Research related to peatlands is important to be carried out in disaster mitigation efforts on peatlands. In this study, we aimed to examine the impact of climate anomalies occurring between 2019 and 2022 on the Rainfall (RF), Groundwater Level (GWL), and Soil Moisture (SM) in this region. We analyzed data collected at the CJ2 station to understand the dynamics of these parameters throughout the occurrence of the ENSO and IOD phenomena in 2019–2022. The findings of this study indicate a positive correlation between RF and GWL. Specifically, a higher amount of RF resulted in a stronger correlation. Moreover, the rate of the GWL decline was 0.24 mm/d, while the rate of the SM decline was 0.06%/day. Furthermore, the soil moisture in CJ2 OKI must be maintained at a minimum of 20% to prevent fires. In addition, an empirical equation was derived to express the relationship between GWL (m) and SM (%) as SM = 49,044 GWL + 59,142. The findings of this study provide valuable in-sights for all stakeholders involved in efforts to mitigate the impact of natural disasters on peatlands.

A Year Marked by Extreme Precipitation and Floods: Weather and Climate Extremes in 2024

A Year Marked by Extreme Precipitation and Floods: Weather and Climate Extremes in 2024

Effects of increased nutrient loading and water level caused by extreme flooding on <i>Hydrilla </i><i>verticillata</i>, periphyton and water properties

Effects of increased nutrient loading and water level caused by extreme flooding on <i>Hydrilla </i><i>verticillata</i>, periphyton and water properties

Sustainable Development and Flood Risk Assessment in Haripur District: A Multicriteria Analysis Using AHP and Geospatial Techniques

Extreme flooding is becoming a more serious hazard to the world’s infrastructure, especially in high‐risk locations, and is linked to global warming and human activity. This research employs an analytical hierarchy process (AHP) model and geographic information system (GIS) analysis to delineate flood risk zones. An eight‐factor multiparametric method to flood risk susceptibility mapping includes precipitation, distance to river, the slope, elevation, land use/cover, topographic wetness index, type of soil, and curvature. An urban flood risk index (UFRI) is established based on vulnerability mapping, revealing that approximately 33% of Haripur District, Khyber Pakhtunkhwa, Pakistan, is prone to floods. Additionally, land use cover analysis indicates that 23% of the crop area in Haripur District is at risk from flood disasters. Recognizing the potential for costly damage to infrastructure, flood hazard mapping serves as a valuable tool to prioritize risk areas for urban and agricultural development. The outcomes of this study are anticipated to significantly contribute to predisaster flood control management in the studied area.

The role of wildfires and forest harvesting on geohazards and channel instability during the November 2021 atmospheric river in southwestern British Columbia, Canada

AbstractSediment mobilized to rivers during extreme flood events can influence channel stability and cause significant morphological changes. A prolonged and intense atmospheric river (AR) struck southwestern British Columbia, Canada in November 2021, leading to extreme flooding and landsliding over approximately 70 000 km2 of mountainous areas. Entire communities within the region were evacuated, and the transportation infrastructure connecting them was severely damaged. The locations of 1300+ geohazards (e.g., debris flows, debris flood, debris slides, shallow landslides and bank erosion) were mapped from helicopter, ground observations, orthoimagery, site photos and social media posts alongside rivers and large gravel‐bed streams that experienced lateral instability. Morphological changes in two of these gravel‐bed rivers were examined in more detail by comparing pre‐event and post‐event lidar data using three‐dimensional point‐based normal differencing. We found that geohazards occurred more frequently in burned areas and along forest harvesting resource roads, providing point sources of sediment that entered mainstem rivers. The geohazard mapping and lidar change detection revealed that bank erosion and lateral instability often occurred downstream of these mapped sediment sources. As the frequency of wildfires and extreme meteorological events is predicted to increase with continued climate change, future risk assessments in communities should consider sediment sources that can be mobilized by these events and the resulting downstream morphological impacts.

The Influence of Tropical Cyclones on Mixed-Population Flood Frequency Analysis

Abstract Floods induced by tropical cyclones (TCs) and their frequency analysis have received much attention at the regional scale, but little is known about the role of TCs in the mixed flood frequency analysis at the global scale, which is the key for hazard management. Here, we investigated the influence of TCs on the upper tail of flood frequency estimates using discharge observations at 3883 stations influenced by TCs alongside global discharge simulations from the second phase of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP2a). Our results show that TC-induced floods in inland areas are not always found along the TC path but can be located about 1000 km ahead, which is linked to TC-induced predecessor rain events. Extreme floods associated with TCs are generally larger in coastal areas compared to those in inland areas, whereas TC-induced floods in some inland areas tend to be more extreme relative to their local flood magnitude. The flood peaks generated by TCs and other mechanisms compose a mixed population flood series. However, the largest flood peaks in coastal areas are usually affected by TCs. These large TC-induced flood peaks play an important role in making the upper tail of the flood frequency curve heavier. In regions affected by TCs, the flood magnitude with an n-yr return period is greater when estimated from TC-induced floods only. Therefore, regions (especially inland regions) should thoroughly consider the extremity of TC-induced flooding when improving hydraulic infrastructures to ensure a more conservative design, thereby enhancing the safety of these hydraulic projects. Significance Statement Tropical cyclones (TCs) are responsible for extreme floods in coastal and inland areas influenced by TCs, which may play an important role in the flood frequency analysis and flood risk management. In this study, we investigated how TCs affect the upper tail of flood frequency estimates at the global scale. We find that extreme floods associated with TCs are generally higher in coastal areas, whereas TC-induced floods in some inland areas tend to be more extreme relative to their regional flood magnitude. These anomalously large TC-induced flood peaks control the upper tail of the flood frequency curve in coastal and inland areas and make the upper tail heavier. Globally, the flood magnitude once in n years is generally greater, estimated from only TC-induced flood peaks than that estimated from all flood peaks. Therefore, regions (especially inland regions) should thoroughly consider the extremity of TC-induced flooding when improving hydraulic infrastructures to ensure a more conservative design, thereby enhancing the safety of these hydraulic projects.

Natural or man-made disaster? Lessons from the extreme rain and flood disaster in Zhengzhou, China on "2021.7.20"

Driven by extreme weather events, precipitation-induced flood disasters are occurring more frequently, posing substantial threats to both economic development and public safety. Increased human production activities have further intensified the impact of flood disasters. However, understanding of the factors influencing flood disasters and their associated risk assessments remains limited. To better formulate flood prevention and disaster reduction strategies suited to local conditions, this paper takes the "7.20" extreme rainfall event in the main urban area of Zhengzhou, Henan Province, China, on July 20, 2021, as a case study and uses geographic detectors to incorporate human activities into the quantitative analysis of influencing factor contributions. Based on the three aspects of disaster incubation, disaster causation, and disaster bearing, this study proposes using the influence values obtained from geographic detectors as objective weight assignments for risk assessment, thereby conducting a locally adapted risk assessment of Zhengzhou's main urban area. Research results indicate that the "7.20" heavy rainstorm in Zhengzhou's main urban area involved a superposition of natural and human factors. Impervious surfaces had the highest explanatory power, followed by population density, confirming that this flood disaster arose from the interaction of multiple factors. The flood disaster risk assessment for Zhengzhou's main urban area shows higher risk levels in the central area and relatively lower levels in peripheral areas. The central area features flat terrain, with high population density and a large proportion of impervious surfaces. Among these, 22 subdistricts are located in extremely high-risk flood zones, while 6 subdistricts, classified as low-risk, account for over 60% of the low-risk area, making them relatively lower-risk communities. Comparison with flood waterlogging point data verifies the accuracy of the risk assessment through statistical analysis, allowing for further analysis of the spatial differentiation of flood risk. The findings of this study offer valuable insights for preventing and managing urban extreme rainfall disasters.

Urban landscape patterns and residents’ perceptions of safety under extreme city flood disasters

Urban landscape patterns and residents’ perceptions of safety under extreme city flood disasters