Flood Season Research Articles

Global Health, Climate Change, and Migration

This article examines the relationship between global health, climate change, and migration. It explores migration of both humans and animals, and its inverse. Many researchers directly link seasonal droughts, heatwaves, heavy rainfall, and floods to human health, observing, among other things, that these conditions increase contact with wildlife. As a result, there are serious concerns about the risk of future pandemics and epidemics. These issues primarily have a moral dimension because they relate to human well-being and test the fair distribution of healthcare resources. In this context, the development of a new ethic for a truly sustainable environment is deemed necessary, as the protection of the environment and global public health is a global moral responsibility and obligation. Moreover, there is a duty to protect all those displaced by a health crisis due to climate change, and the concept of a type of health asylum could be proposed, as we might soon talk about health refugees and migrants in combination with environmental ones.

2021~2023年象山不同区域汛期降水日变化特征分析

2021~2023年象山不同区域汛期降水日变化特征分析

The Images of Sacred Trees in Ancient Egyptian Fairy Tales

The paper examines the semantics of trees described in the ancient Egyptian fairy tales “Tale of Two Brothers” and in the “Story of Sinuhe”. The purpose of the study is to identify the semantics of trees in these fairy tales, their relationship with the religious ideas of the Egyptians and specifies of ideas about the calendar cycle displayed in these texts. The author traces literary parallels between the images of fairy-tale trees and the motifs of the “Book of the Dead”, which tells about the posthumous life of the soul of the deceased in the Netherworld. The study reveals that in the “Tale of Two Brothers”, the cedar and two persea trees are correlated with the Osiris and solar cults. The persea trees represent the rays of the sun, Osiris and the deceased as the blessed spirit Akh. The cedar inflorescence located at the top of the tree is also associated with the image of the sun. It was found that in this fairy tale, the description of tree life and the hero’s repeated birth reflect the change of calendar cycles from the flood season to the harvest season, from the period of visibility of celestial bodies and plants to the period of their invisibility. The sycamore, mentioned in the “Story of Sinuhe”, is the sacred tree of Hathor, Isis and Nut and appears as a symbol of the heaven with which these goddesses were associated.

Effect of Seasonal Floods on Farmers’ Household Food Security in the Kassena Nankana Municipal of Ghana.

The Kassena Nankana Municipality has experienced an increase in the frequency and severity of seasonal floods, threatening the livelihoods of local farmers. These floods disrupt agricultural activities and exacerbate regional food insecurity. This study examined the extent to which floods affected local farmers’ food security. Interviews were conducted with 150 farm households from five different communities. To understand the nature, scope of the flooding and damages caused by the floods, descriptive statistics were employed. The floods’ effect on farmers’ food security were examined using Ordinary Least Squares (OLS) econometric modelling. The Food and Nutrition Technical Assistance (FANTA) Household Dietary Diversity Score (HDDS) and Food and Agriculture Organization (FAO) Food Consumption Score (FCS) models were used to assess food security levels. The majority of the floods in the area were caused by heavy rains. These floods resulted in total asset losses of GHS 653,640.6 (USD 116,722.00), with maize crops bearing the brunt of the damage at GHS 106,712.00. (USD 19,056.00). Properties worth GHS 276,275.00 (USD 49,335.00) were destroyed, including houses, animal pens, storage rooms, bicycles, and motorbikes, and with estimated loss of 3,383 birds. Due to the floods, two people died and 201 people became ill. Food security was found to be positively associated with factors such as male-headed households, age, income, and access to credit. The size of a household had a negative impact on food security. The study recommended targeted policies to improve agricultural productivity and support smallholder farmers, such as loan and social security schemes, women’s empowerment, and the establishment of irrigation facilities to improve regional food security.

2022年强高温期长江中游通江湖泊干旱数据集

Due to global warming and climate change, affected by climate anomalies, Yangtze River basin in China experienced the strongest high-temperature process since the complete meteorological observation records in 1961. This process led to the continuous low water level of Yangtze River tributaries and the rare phenomenon of "anti-depletion of flood season" in Poyang Lake and Dongting Lake, both of which were influenced by this climate event. Lakes are indicators of global climate change, and water area changes in lakes have become one of the sensitive indicators of regional ecological environment and climate change. In this study, we used the GEE cloud computing platform to call Sentienl-1 SAR data to calculate the sentinel-1 dual-polarized water index (SDWI). Then, we determined the optimal threshold value using the OTSU algorithm to obtain the final water change monitoring data at 10m resolution for the main body of Poyang Lake, Dongting Lake and their surrounding areas during extremely high temperatures in 2022. This dataset has been validated to with an overall accuracy of over 96% and a Kappa coefficient of 0.92. The dataset includes spatiotemporal variations in arid water bodies in the middle and lower reaches of the Yangtze River during extremely high temperatures in 2022. The dataset can offer data support and serve as a scientific foundation for sustainable lake water resources during extreme weather events, as well as for research on global climate change and the ecological evolution of lakes.

Water Level Fluctuations Modulate the Microbiomes Involved in Biogeochemical Cycling in Floodplains.

Drastic changes in hydrological conditions within floodplain ecosystems create distinct microbial habitats. However, there remains a lack of exploration regarding the variations in microbial function potentials across the flooding and drought seasons. In this study, metagenomics and environmental analyses were employed in floodplains that experience hydrological variations across four seasons. Analysis of functional gene composition, encompassing nitrogen, carbon, and sulfur metabolisms, revealed apparent differences between the flooding and drought seasons. The primary environmental drivers identified were water level, overlying water depth, submergence time, and temperature. Specific modules, e.g., the hydrolysis of β-1,4-glucosidic bond, denitrification, and dissimilatory/assimilatory nitrate reduction to ammonium, exhibited higher relative abundance in summer compared to winter. It is suggested that cellulose degradation was potentially coupled with nitrate reduction during the flooding season. Phylogenomic analysis of metagenome-assembled genomes (MAGs) unveiled that the Desulfobacterota lineage possessed abundant nitrogen metabolism genes supported by pathway reconstruction. Variation of relative abundance implied its environmental adaptability to both the wet and dry seasons. Furthermore, a novel order was found within Methylomirabilota, containing nitrogen reduction genes in the MAG. Overall, this study highlights the crucial role of hydrological factors in modulating microbial functional diversity and generating genomes with abundant nitrogen metabolism potentials.

Selection of Inundation Vulnerable Areas Using the Risk Assessment: Case Study for Busan Near Urban Watershed and Coast

Recently, inundation damage in urban areas is increasing due to frequent heavy rain during the flood season. In this study, an IBA inundation risk assessment was performed for the 16 cities, counties and districts in Busan, where inundation damage frequently occurs due to heavy rain in the summer. In the risk assessment process, four evaluation items(Hazard, Exposure, Vulnerability, and Capacity) were established through detailed indicators that directly and indirectly affect inundation from 2019 to 2021. Also, normalization and entropy weight method were applied to each detailed indicator. Afterwards, the inundation risk index was calculated using the euclidean distance, and changes in the inundation risk of each city, county and district were confirmed by year using the inundation risk index. As a result, Haeundae-gu and Busanjin-gu were selected as inundation vulnerable areas in Busan. The results of this study are expected to be used as basic data in the process of establishing complementary measures establishment for flood disaster(inundation) in Busan in the future.

Effects of seasonal floods on teaching and learning activities in floods prone primary schools in Chemba District, Dodoma Region, Tanzania

This study assessed the floods related factors affecting teaching and learning activities in floods prone schools in Chemba district, Dodoma region, Tanzania. The findings revealed floods factors such as schools’ inaccessibility due to impassable roads accompanied by distance to teaching and learning activities in floods prone schools due to pupils' psychological impacts, disruption of the school calendar, and increased insecurity. Moreover, the communities and schools employed different strategies to increase access to primary education, such as roads and footpaths repairing and maintenance, community participation in drainage activities, establishing satellite schools, and enforcing by-laws and remedial classes. Therefore, the study recommends government-community partnerships to address challenges in flood-prone areas to increase school-age children’s access to primary education.

Dominant flood types in mountains catchments: Identification and change analysis for the landscape planning

The classification of floods may be a supporting tool for decision-makers in regard to water management, including flood protection. The main objective of this work is the classification of flood generation mechanisms in 28 catchments of the upper Vistula basin. A significant innovation in this study lies in the utilization of decision trees for flood classification. The methodology has so far been applied in the Alpine region. The analysis reveals that peak daily precipitation in the catchments mainly occurs in summer, particularly from June to August. Maximal daily snowmelt typically happens at the end of winter (March to April) and occasionally in November. Winter peaks are observed in March to April and, in some areas, in November to December, while summer peaks occur in May and, in specific catchments, in October. Higher peak flows for annual floods are noted in March to April and June to August. Most annual floods in the Upper Vistula basin are classified as Rain-on-Snow Floods (RoSFs) or Lowland River Floods (LRFs). LRFs contribute from 19% to almost 72%, while RoSFs range from 18% to 75%. In Season 1 (summer), most seasonal floods are identified as LRFs (51%–100%), with very few as RoSFs (0%–46.9%). In Season 2 (winter), the opposite pattern is observed, with most RoSFs (48.4%–97.9%) and fewer LRFs (0%–20.6%). While there are changes in flood patterns, they are not statistically significant. Conducted studies and obtained results can be useful for the preparation of flood prevention documentation and for flood management in general.

Research on stage–discharge relationship model based on random forest algorithm

Hydrological simulations and predictions are vital aspects of hydrological change research. Accurate predictions of hydrological factors such as stage and discharge are essential for water resources planning, reservoir dispatching and operation, shipping management and flood control. River discharge forecasting during flood seasons is an important issue in water resources planning and management. To improve the calibration accuracy and stability of the stage–discharge relationship model, the feasibility of integrated algorithms for studying the stage–discharge relationship was explored. A random forest (RF) algorithm based on a neural network (NN) was developed using a framework of integrated algorithms. First, the Levenberg–Marquardt (LM) algorithm was used to optimise the weight updating process of a back-propagation (BP) NN and improve the convergence speed. Then, the LM-BP algorithm was used as a decision tree to build an RF algorithm. The model was tested using hydrological data from Hongqi station on the Dadu River in China in the flood season. Results for the classical model, BP NN model, LM-BP NN model and optimised algorithm model were evaluated based on the mean absolute error (MAE), mean square error (MSE) and mean absolute percentage error (MAPE). The performance indicators showed that the optimised algorithm model (MAE = 3.13 m3/s, MSE = 19.28 m3/s and MAPE = 1.8%) was superior to the other models and showed high accuracy and good stability in flood-season flow forecasting.

Soils surrounding saline-alkaline lakes of Nhecolândia, Pantanal, Brazil: Toposequences, mineralogy and chemistry

The Nhecolândia subregion of the Brazilian Pantanal, subject to a highly seasonal climate, hosts a diverse range of freshwater and saline-alkaline lakes. The latter can be green due to cyanobacterial bloom, black due to dissolved organic matter, or crystalline. Over the past two decades, numerous studies in the region have explored the connections between the lake type, the surrounding soils, and water table dynamics. However, these insights emerged from independent studies conducted at multiple sites, making their synthesis challenging and leaving questions about the differences between lake types. Our research focuses on a representative Nhecolândia site, aiming to comprehensively understand soil and lake genesis and dynamics. For each lake type, we conducted detailed toposequence soil studies, assessing particle size distribution, chemistry and mineralogy of the <2 mm fraction of identified horizons. A 49-month temporal study utilizing PlanetScope satellite data examined lake connections to the hydrographic network affected by seasonal flooding. Our findings confirmed the general organization and mineralogy of soils around saline-alkaline lakes. Notably, we identified variations in soil toposequences corresponding to different lake type. Two types of silcrete were observed: one acidic, found at the upper slopes, and the other alkaline, located at the lower slopes. We determined that, for endorheism and lake alkalinization, the presence of a ridge around a lake is insufficient. Instead, deep impermeable horizons in the lower portion of the toposequences are essential. Additionally, crystalline lakes differentiate from black and green ones due to less efficient hydraulic isolation. Our comprehensive dataset from a single site provides a valuable resource for guiding and developing more specific studies on these alkaline systems.

RAU-Net++: River Channel Extraction Methods for Remote Sensing Images of Cold and Arid Regions

Extracting river channels from remote sensing images is crucial for locating river water bodies and efficiently managing water resources, especially in cold and arid regions. The dynamic nature of river channels in these regions during the flood season necessitates a method that can finely delineate the edges of perennially changing river channels and accurately capture information about variable fine river branches. To address this need, we propose a river channel extraction method designed specifically for detecting fine river branches in remote sensing images within cold and arid regions. The method introduces a novel river attention U-shaped network structure (RAU-Net++), leveraging the rich convolutional features of VGG16 for effective feature extraction. For optimal feature extraction along channel edges and fine river branches, we incorporate a CBAM attention module into the upper sampling area at the end of the encoder. Additionally, a residual attention feature fusion module (RAFF) is embedded at each short jump connection in the dense jump connection. Dense skip connections play a crucial role in extracting detailed texture features from river channel features with varying receptive fields obtained during the downsampling process. The integration of the RAFF module mitigates the loss of river information, optimizing the extraction of lost river detail feature information in the original dense jump connection. This tightens the combination between the detailed texture features of the river and the high-level semantic features. To enhance network performance and reduce pixel-level segmentation errors in medium-resolution remote sensing imagery, we employ a weighted loss function comprising cross-entropy (CE) loss, dice loss, focal loss, and Jaccard loss. The RAU-Net++ demonstrates impressive performance metrics, with precision, IOU, recall, and F1 scores reaching 99.78%, 99.39%, 99.71%, and 99.75%, respectively. Meanwhile, both ED and ED′ of the RAU-Net++ are optimal, with values of 1.411 and 0.003, respectively. Moreover, its effectiveness has been validated on NWPU-RESISC45 datasets. Experimental results conclusively demonstrate the superiority of the proposed network over existing mainstream methods.

Water storage capacity estimation for a large complex lake system incorporating the water levels during flooding season

Study regionDongting Lake, ChinaStudy focusWater storage capacity (WSC) of a large lake system plays a crucial role in flood control decision-making during the flood season. Dongting Lake, located downstream of Three Gorges Dam, has a significant influence over flood control in the middle and lower reaches of the Yangtze River (MLYR). To have a better WSC estimation of Dongting Lake, a multiple linear regression model was developed based on hydrodynamic simulation data of the typical flood processes in the past 3 decades.New hydrological insights for the regionThe multiple linear regression (MLR) model is developed by integrating of hydrodynamic simulation. Also, the effect of the water level (WL) at Chenglingji station and the WL difference in the lake (Yangliutan-Chenglingji) were investigated. The model can accurately estimate the WSC of Dongting Lake with an R2 of 0.984. The observation indicates that the WL difference within the lake has a great influence on the WSC and the flood regulation capacity ability with the same WL at Chenglingji station. The results of the study can provide a real-time estimation of the WSC of Dongting Lake which can provide useful information for flood control management.

Transformative Trends in Runoff and Sediment Dynamics and Their Influential Drivers in the Wuding River Basin of the Yellow River: A Comprehensive Analysis from 1960 to 2020

The correlation between runoff and sediment challenges ecological preservation and sustainable development in the Yellow River Basin. An understanding of the key factors influencing variations in runoff and sediment transport in crucial river basins is essential for effective soil erosion management within the context of ecological and economic development. The Mann–Kendall test, Pettitt test, and Morlet wavelet analysis were employed in the Wuding River Basin to analyze the trends in runoff and sediment changes from 1960 to 2020. We explored the double cumulative curve method to assess the contribution rates of precipitation and human activities to the variability of runoff and sediment transport. We explored the primary factors driving the changes in runoff and sediment transport through random forest regression analysis. (1) From 1960 to 2020, annual precipitation in the Wuding River Basin increased minimally, while annual runoff and sediment transport decreased strongly with abrupt changes. Abrupt changes in annual runoff and sediment transport occurred in 1971 and 1979, respectively. (2) The relationship between runoff and sediment transport changed in approximately 1972 and 2000. The distribution of monthly runoff became more uniform during Periods II (1973–2001) and III (2002–2020) compared to that during the baseline period (1960–1972, Period I), while sediment transport became increasingly concentrated in the flood season. (3) During Period II, the contribution rates of climate and human activities to runoff and sediment transport were 11.94% and −14.5%, respectively, compared to the baseline period. During Period III, the contribution rates of climate and human activities to runoff and sediment transport were −11.9% and −17.7%, respectively. Human activities substantially reduced runoff and sediment, with greater impacts on sediment reduction. Climate weakly influenced basin sediment transport variations. (4) The normalized difference vegetation index (NDVI) and grassland area extent had the greatest impact on runoff, while the NDVI and forest area extent affected sediment transport.

Freshwater resources around the reclaimed new land on the Eastern Hengsha Shoal in the Changjiang estuary

Reclaiming estuarine tidal flats is practiced to meet the growing demand for land. The reclaimed new land (RNL) on the Eastern Hengsha Shoal in the Changjiang Estuary is for agricultural production in Shanghai. Whether freshwater resources exist around the RNL has become a critical issue \caused by estuarine saltwater intrusion. In this study, the spatiotemporal saltwater intrusion and freshwater distribution around the RNL at different guarantee rates of river discharge using the improved 3D numerical model ECOM-si was investigated. Three water intakes on Hengsha Island and the northern edge of the RNL were set. The results showed that at different guarantee rates of river discharge during the dry season, there is a relatively sufficient suitable water intake time in the upper RNL. Nevertheless, there is a very limited suitable water intake time in the middle and lower RNL as the guarantee rate increases, especially in January and February. During the flood season, three water intakes can ensure sufficient suitable water intake time. The salinity around the RNL significantly increases under the combined effect of 50% and 95% guarantee rates with a 12 m/s northerly wind in February, resulting in a significant threat to the three water intakes. At the 50% guarantee rate, the suitable water intake times in February are 14.86, 9.78 and 3.53 days at three water intakes, respectively. At the 95% guarantee rate, the suitable water intake time in February is only 0.31 days in the upper RNL, and there is no freshwater in the middle and lower RNL. Overall, there is sufficient freshwater in the flood season and limited freshwater in the dry season for agriculture along the northern edge of the RNL.

Successes and challenges of fisheries governance in an African wetland fishery: A Case study of fishing camps on the Kafue flats of Zambia

AbstractDuring the last three decades, the Kafue flats floodplain fishery on the Kafue River in Zambia has been increasingly exploited due to more individuals settling in the area and seasonal travellers gaining access to the fishery during flood season. Despite successful governance arrangements that effectively regulated access to fish stocks for many generations, evidence shows that these arrangements are not working as new entrants continue to gain access and overexploit remaining fish stocks. Managing new entrants is a crucial factor in achieving sustainable use. Our objective was to gain an understanding of fisheries governance on the Kafue floodplain fishery, particularly in Shimungalu and Nyimba fishing villages, where different levels of government support for co‐management structures produced different outcomes. Our research approach was qualitative, by utilising the snowball sampling technique and incorporating interviews and documentary analysis. Our aim was to investigate discrepancies in the efficacy of resource access and utilisation in the two fishing camps, and to offer recommendations on how governance systems for the fishery could be refined to improve their efficacy. This comparative analysis of the two fishing communities, which share numerous characteristics with various small‐scale fisheries in Africa, provides an opportunity to understand how polycentric governance offers a solution by enabling other organisations to fill capacity gaps faced by relevant authorities. The lessons derived from this analysis offer valuable insights into enhancing fisheries governance and future research directions in Zambia, and Africa at large.

Pyrogenic carbon stocks are controlled by hydro-edaphic conditions in different forest types of the Northern Brazilian Amazon

Pyrogenic carbon (PyC) is considered one of the most stable components found in soil, corresponding to an expressive amount of refractory organic matter. Despite PyC significantly affect soil properties and processes, it has not been considered in global carbon cycle models due to uncertainties related to its quantification. To provide a greater understanding of PyC importance and its role in the Amazon carbon cycle, we estimate PyC soil stocks dispersed in the vertical soil column of different forest types (ombrophilous, deciduous and semideciduous) which occur in a hydro-edaphic gradient in the Maracá Island, northern Brazilian Amazon. Soil profiles measuring one meter in depth were sampled at 30 permanent plots arranged along the eastern portion of Maracá Island. The soil samples were fractioned in 10 subsamples corresponding to each 10 cm layer of the 1 m column and all of them were analyzed by the thermal method. We observed that PyC contributed to a mean of 1.92 % of the TOC (total organic carbon) present in the samples, and the PyC/TOC ratios have also evidenced a tendency to increase with depth. For absolute values, deciduous forests occurring in seasonal flooding soils had the highest stock of PyC (1.27 Mg PyC ha−1) when compared with ombrophilous (non-flooding) and semideciduous (predominance of deep rock fragments) forests. Our results indicate that atmospheric deposition was the major source of PyC entrances into the soil and that hydro-edaphic features control the spatial and vertical distribution of PyC in the study area. These findings are key points for reducing uncertainties regarding PyC stocks and improves our understanding on the carbon stocks variability in the Amazonian soil.

Assessing meteorological and agricultural drought characteristics and drought propagation in Guangdong, China

Study regionGuangdong, China Study focusDroughts have resulted in significant crop failure in Guangdong province, where annual crop yield exceed 12 million tons. However, there is a lack of a comprehensive assessment of both meteorological drought and agricultural drought in Guangdong, particularly regarding the influencing factors and drought propagation. This study aims to address this gap by utilizing the standardized precipitation evapotranspiration index (SPEI) and soil water deficit index (SWDI) to represent meteorological drought and agricultural drought, respectively. To examine the characteristics of drought in the past 50 years (1973–2022), the year is divided into flood and non-flood season based on the temporal distribution of precipitation. New hydrological insights for the regionOver the last five decades, the number of meteorological and agricultural drought days decreases from coastal to inland areas. Notably, agricultural droughts have become more pronounced in the last two decades. More agricultural drought days appears during the non-flood season than the flood season. Precipitation emerges as the most influential factor for meteorological drought, while potential evapotranspiration, actual evapotranspiration and temperature are identified as the primary factors for agricultural drought. The drought propagation time ranges from 10 to 45 days which is shorter in central Guangdong than other regions, and it is longer in non-flood season than in flood season.

Dynamic Control of Flood Limited Water Levels for Parallel Reservoirs by Considering Forecast Period Uncertainty

The objective of this study is to achieve the dynamic optimization of the flood limited water level (FLWL) in parallel reservoirs, using Luhun Reservoir and Guxian Reservoir as case studies. The innovation lies in establishing a dynamic control optimization model for the FLWL of parallel reservoirs, considering the uncertainty in the forecasting period of the flood forecast due to the varying locations of the rainstorm center from upstream to downstream. To commence, the Fisher optimal segmentation method is employed for flood season staging to determine the staged FLWL of each reservoir. Subsequently, considering the uncertainty in the foresight period, the upper range of the dynamic FLWL is determined through the improved pre-discharge capacity constraint method and Monte Carlo simulation. Finally, a multi-objective optimization model is established to determine the optimal dynamic FLWL control operation scheme for parallel reservoirs, utilizing the Non-Dominated Sorting Genetic Algorithm II (NSGA-II). This model takes into account both downstream flood control requirements and the water supply benefits of the parallel reservoirs. Through the optimization of the scheme, the water supply of the parallel reservoirs can be augmented by 15,347.6 m3 during the flood season. This optimization effectively achieves a harmonious balance between flood control and water supply, holding significant implications for mitigating drought risks amid changing conditions.

Rainfall-Induced Landslide Susceptibility Assessment and the Establishment of Early Warning Techniques at Regional Scale

This study builds upon deterministic evaluations of the extensive cumulative rainfall thresholds associated with shallow landslides in the Gaoping River Basin, with a specific focus on the necessary response times during typhoon and intense rainfall events. Following the significant impact of Typhoon Morakot on the Liugui area, our investigation enhances previous research by employing a downscaled approach. We aim to establish early warning models for village-level, intermediate-scale landslide cumulative rainfall thresholds and to create action thresholds for small-scale, key landslide-prone slopes. Our inquiry not only combines various analytical models but also validates their reliability through comprehensive case studies. Comparative analysis with the empirical values set by the Soil and Water Conservation Bureau (SWCB) and the National Center for Disaster Reduction (NCDR) provides a median response time of 6 h, confirming that our findings are consistent with the response time frameworks established by these institutions, thus validating their effectiveness for typhoon-related landslide alerts. The results not only highlight the reference value of applying downscaled cumulative rainfall thresholds at the village level but also emphasize the significance of the evaluated warning thresholds as viable benchmarks for early warnings in landslide disaster management during Taiwan’s flood and typhoon seasons. This research offers a refined methodological approach to landslide early warning systems and provides scientific support for decision making by local governments and disaster response teams.