Floodplain Research Articles

Early Holocene occurrence of loess in Folldal, east-central southern Norway: Identification, origin and palaeoclimatic significance

Identified for the first time in Norway, windblown yellowish-brown dust in Folldal, east-central southern Norway, fulfils physical and geochemical criteria for sensu stricto loess, including a high carbonate content. Two extant and one relict marl pond located on low-carbonate rocks are investigated. An allochthonous origin for the marl ponds is suggested and explained by the deposition of suspended clastic carbonate as loess by aeolian processes. The scattered geographical distribution of loess and the need for a calcareous source area suggest a W-SW provenance from a relict valley sandur/existing flood plain in upper Grimsdalen. The mean grain size (~22.4 µm) of the aeolian silt is in the finer range of average loess, explained by the up to 25–30 km long transport and approximately 250–300 m airborne uphill move from the suggested source area to the marl ponds. Based on age-depth modelling using 9 AMS radiocarbon dates, loess deposition occurred from ca. 10,390 to 9780 cal. yr BP (610 years). Two prominent periods of loess accumulation occurred from ca. 10,390 to 10,190 (200 years) and ca. 10,020–9950 (70 years) cal. yr BP. Loess deposition results from W-SW wintertime winds in a dry to semi-arid climate. In southern Norway, W-SW winds in winter are associated with a positive mode of the North Atlantic Oscillation (NAO). From source to deposition, the response time to erode, transport and accumulate loess is suggested to be seasonal to 1 year. An immediate increase in organic production followed loess deposition as early initiation of a warmer and wetter Holocene climatic optimum.

A study on climate‐driven vulnerabilities in the Ranganadi river basin: Sand‐Casting impacts on rural households

AbstractThe Ranganadi river basin, spanning a catchment area of 2335 km2 in the North Lakhimpur region of Assam is one of the worst flood‐affected areas in the North Eastern region of India. The basin is densely populated and the land around this river is extensively used for cultivation. Progressive migration of the banklines leads to the loss of cultivable land. Breach in embankments protecting agricultural fields during the monsoon, as well as the presence of infertile sand in agriculture fields are some of the most dominant facets of riverine hazards directly connected with the loss of livelihood in the study area The objective of this research is to assess the vulnerability of the population residing in these flood plains to the impacts of sand casting, utilizing Livelihood Vulnerability Index (LVI) approach. The research included 377 households, and a comprehensive analysis was carried out. The analysis revealed varying degrees of vulnerability for 0.306 (socio‐demographic profile), 0.489 (livelihood strategies), and 0.413 (social networks). Sensitivity values were 0.495 (health), 0.487 (food security), 0.368 (water availability), and 0.391 (psychological factors). Exposure was rated high at 0.494, indicating vulnerability to natural disasters and climate variability. These values highlighted the most vulnerable components of the population due to the disaster and helped to suggest vulnerability reduction measures. The novelty of the study based on the result is that the LVI was meticulously formulated and adapted specifically for the study area. This localized approach allowed the unique socio‐economic and environmental dynamics of the affected population to be captured very well.

Sea−level rise and arsenic−rich soils: A toxic relationship

In the United States, dangerously high arsenic (As) levels have been found in drinking water wells in more than 25 states, potentially exposing 2.1 million people to drinking water high in As; a known carcinogen. The anticipated sea−level rise (SLR) is expected to alter soil biogeochemical and hydrological conditions, potentially impacting their ability to sequester As. In our study of coastal Wilmington, DE, an area projected to experience a 1 −meter SLR by 2100, we examined the spatial distribution, speciation, and release possibilities of As due to SLR. To understand the complex dynamics at play, we employed a comprehensive approach, including bulk and micro X−ray absorption spectroscopy measurements, hydrological pattern evaluation, and macroscopic stirred−flow experiments. Our results suggest that introducing reducing and saline conditions can increase As release in both river water and seawater inundation scenarios, most likely due to ionic competition and the dissolution of As−bearing Fe/Mn oxides. Regardless of the salinity source, the released As concentrations consistently exceeded the EPA threshold for drinking water. Our results provide valuable insights for developing appropriate remedial and management strategies for this site and numerous others facing similar environmental challenges. Environmental ImplicationWith nearly two hundred million individuals living within coastal flood plains and with two million square kilometers of land and one trillion dollars' worth of assets lying less than 1 m above current sea level, sea–level rise (SLR) is one of the significant socio–economic threats associated with global warming. Arsenic is a prevalent contaminant in coastal areas impacted by industrial activities, many of which are susceptible to being impacted by SLR. This study examines SLR's impact on arsenic fate and speciation in a densely populated coastline in Wilmington, DE, expecting 1 meter of SLR by 2100.

Suitability Evaluation of Pedons from Some Agricultural Communities on the Niger River Flood Plains in Bayelsa State, Nigeria

Farmers under modern agriculture are expected to have direct or indirect knowledge of soil chemical and physical characteristics as well as their suitability for intended uses. This, however, is lacking in Bayelsa State, hence this study examined the potentials and limitations of some lower Niger River plain soils of southern Nigeria and their suitability for maize production. Based on landform differences, landscape segments were separated into three mapping units per location while profile pits were dug in each unit and morphologically described. Horizon differentiation guided soil sample collection followed by laboratory analysis. Silt loam dominated soil texture while Ca dominated the exchange complex but exchangeable bases concentration was generally low. Organic C, total N and available P concentrations were closely related and low which was attributed to land clearing and frequent bush burning. Excessive rainfall and inadequate length of day were the most limiting factors under climatic factors while temperature and relative humidity were highly suitable. The ELM3 and TFN3 pedons flooded each year by Nun and Forcados Rivers, respectively, were marginally suitable S3f. Texturally, ELM1, ELM2 and TFN1 were highly suitable (S1) while ELM3, TFN2 and TFN3 were moderately suitable (S2). Due to insufficient length of dry days and wetness challenges owing to excessive rainfall, all pedons were placed under actually not suitable but potentially suitable (N1) class. Improvement measures recommended included planting early in the dry spell to avoid excessive wetness and making available more dry days as well as organic matter conservation, avoiding frequent land clearing and bush burning.

APPLICATION OF REMOTE SENSING DATA AND GEOGRAPHIC INFORMATION SYSTEM FOR FLOOD MODELING IN WAI RUHU WATERSHED AMBON CITY BASED ON GEOGLE EARTH ENGINE

Flood hazard modeling in watersheds is an important step in natural disaster risk mitigation, especially in vulnerable areas such as Ambon City. This research focused on the Wai Batu Gantung, Wai Batu Gajah, Wai Tomu, Wai Batu Merah, and Wai Ruhu watersheds, using JRC Global Surface Water Mapping Layers data, NASA SRTM Digital Elevation 30 m data, and USGS Landsat 8 Level 2, Collection 2, Tier 1 data analyzed on the Google Earth Engine (GEE) platform. Prediction of built-up land in flood-prone areas was conducted by utilizing flood history analysis, hydrological modeling, and flood zone mapping. The results show that flood hazard modeling provides a better understanding of flood risk, assists in the development of safer land use planning, and increases public awareness of flood risk in Ambon City. It is hoped that the results of this research can contribute to flood risk management and sustainable regional development in the future.

MODELING FLOOD HAZARDS IN AMBON CITY WATERSHEDS: CASE STUDIES OF WAI BATU GANTUNG, WAI BATU GAJAH, WAI TOMU, WAI BATU MERAH AND WAI RUHU

Flood hazard modeling in watersheds is an important step in natural disaster risk mitigation, especially in vulnerable areas such as Ambon City. This research focused on the Wai Batu Gantung, Wai Batu Gajah, Wai Tomu, Wai Batu Merah, and Wai Ruhu watersheds, using JRC Global Surface Water Mapping Layers data, NASA SRTM Digital Elevation 30 m data, and USGS Landsat 8 Level 2, Collection 2, Tier 1 data analyzed on the Google Earth Engine (GEE) platform. Prediction of built-up land in flood-prone areas was conducted by utilizing flood history analysis, hydrological modeling, and flood zone mapping. The results show that flood hazard modeling provides a better understanding of flood risk, assists in the development of safer land use planning, and increases public awareness of flood risk in Ambon City. It is hoped that the results of this research can contribute to flood risk management and sustainable regional development in the future.

Monitoring the Landscape Pattern Dynamics and Driving Forces in Dongting Lake Wetland in China Based on Landsat Images

Dongting Lake wetland is a typical lake wetland in the Middle and Lower Yangtze River Plain in China. Due to the influence of natural and human activities, the landscape pattern has changed significantly. This study used 12 Landsat images from 1991 to 2022 and applied three common classification methods (support vector machine, maximum likelihood, and CART decision tree) to extract and classify the landscape information, with the latter having a superior annual accuracy of over 90%. Based on the CART decision tree classification results, the dynamic characteristics of wetland spatial patterns were analyzed through the landscape pattern index, dynamic degree model, and transition matrix model. Redundancy and grey correlation analysis were employed to investigate the driving factors. The results showed increased landscape fragmentation, reduced heterogeneity, and increased complexity from 1991 to 2022. The water and mudflat areas exhibited three distinct stages: gradual decline until 2001 (−3.06 km2/a); sharp decrease until 2014 (−19.44 km2/a); and steady increase (22.93 km2/a). Vegetation conversion, particularly between sedge and reed, dominated the change in landscape pattern. Reed area initially increased (18.88 km2/a), then decreased (−35.89 km2/a), while sedge showed the opposite trend. Woodland area fluctuated, peaking in 2016 and declined by 2022. The construction of the Three Gorges Dam significantly altered landscape dynamics through water level changes, reflected by a 4.03% comprehensive dynamic degree during 2001–2004. Potential evaporation also emerged as a significant natural factor, exhibiting a negative correlation with the landscape index. During 1991–2001 and 2004–2022, the comprehensive explanatory rates of temperature, precipitation, potential evaporation, and water level on landscape pattern dynamics were 88.56% and 52.44%, respectively. Other factors like policies and socio-economic factors played a crucial role in wetland change. These findings offer valuable insights into the dynamic evolution and driving mechanisms of Dongting Lake wetland.

Geomorphological and Bioclimatic Relationships in the Occurrence of Species of Agro-Extractivist Interest in the Cerrado Biome

The distribution of species of agro-extractivist interest and their ecological relationship with the physical environment geomorphological and bioclimatic allow supporting strategies aimed at socioeconomic and environmental development. We evaluated the contribution of high spatial resolution topographic variables in ecological niche models and the relationship of the distribution of five tree species with the geomorphological units and bioclimatic variables. The variables related to temperature variation and water availability proved to be important in predicting the areas of occurrence of the target species, with increased suitability of occurrence in regions with higher isothermality, located in the plateau and table geomorphological units. The predictions showed a significant difference when high spatial resolution variables were used, generating a more conservative scenario in the indication of suitable regions for the occurrence of species, important for local scale studies. The geomorphological units of plateau and tableland showed high suitability of occurrence, while the fluvial plains and dissected depressions did not present suitability for the occurrence of the species. The results allow us to strategically define areas with the greatest productive potential and prioritize areas for conservation, management, ecological restoration of forests, and targeting areas for the implementation of community agro-industries, essential for territorial planning within traditional communities.

Geogenic Phosphorus Enrichment in Groundwater due to Anaerobic Methane Oxidation-Coupled Fe(III) Oxide Reduction.

Accumulation of geogenic phosphorus (P) in groundwater is an emerging environmental concern, which is closely linked to coupled processes involving FeOOH and organic matter under methanogenic conditions. However, it remains unclear how P enrichment is associated with methane cycling, particularly the anaerobic methane oxidation (AMO). This study conducted a comprehensive investigation of carbon isotopes in dissolved inorganic carbon (DIC), CO2, and CH4, alongside Fe isotopes, microbial communities, and functions in quaternary aquifers of the central Yangtze River plain. The study found that P concentrations tended to increase with Fe(II) concentrations, δ56Fe, and δ13C-DIC, suggesting P accumulation due to the reductive dissolution of FeOOH under methanogenic conditions. The positive correlations of pmoA gene abundance versus δ13C-CH4 and Fe concentrations versus δ13C-CH4, and the prevalent presence of Candidatus_Methanoperedens, jointly demonstrated the potential significance of Fe(III)-mediated AMO process (Fe-AMO) alongside traditional methanogenesis. The increase of P concentration with δ13C-CH4 value, pmoA gene abundance, and Fe concentration suggested that the Fe-AMO process facilitated P enrichment in groundwater. Redundancy analysis confirmed this assertion, identifying P concentration as the primary determinant and the cooperative influence of Fe-AMO microorganisms such as Candidatus_Methanoperedens and Geobacter on P enrichment. Our work provided new insights into P dynamics in subsurface environments.

Flexible migration and habitat use strategies of an endangered waterbird during hydrological drought

AbstractWildlife species confront threats from climate and land use change, exacerbating the influence of extreme climatic events on populations and biodiversity. Migratory waterbirds are especially vulnerable to hydrological drought via reduced availability of surface water habitats. We assessed how whooping cranes (Grus americana) modified habitat use and migration strategies during drought to evaluate their resilience to changing conditions and adaptive capacity. We categorized >8000 night‐roost sites used by 146 cranes from 2010 to 2022 and examined relative use during non‐drought, moderate drought, and extreme drought conditions. We found cultivated and uncultivated palustrine and lacustrine wetlands were generally used less during droughts than non‐drought conditions. Conversely, impounded palustrine and lacustrine systems and rivers served more frequently as drought refugia (i.e., used more during drought than non‐drought conditions). Night roosts occurred primarily on private lands (86% overall); public land use decreased with latitude and increased with drought severity, with greatest use (56%) occurring during severe autumn drought in the southern Great Plains. Quantifying use of identified critical habitats in the United States indicated that Cheyenne Bottoms State Waterfowl Management Area and Quivira National Wildlife Refuge were used less during drought, and the Central Platte River and Salt Plains National Wildlife Refuge received similar use during drought compared to non‐drought conditions. Our findings provide insights into compensatory use of habitats, where impounded surface water may function in a complementary fashion with natural wetlands. Collectively, these and other types of wetlands distributed across the migration corridor provided a reliable network of habitat available across the Great Plains. A diversity of wetlands available during variable environmental conditions would be useful in supporting continued recovery of whooping cranes and likely have benefits for a wide array of migratory birds.

Study on River Protection and Improvement Based on a Comprehensive Statistical Model in a Coastal Plain River Network

When considering the contradictions between river management and protection in a typical plain river network, it is always confirmed that the river area has usually been encroached upon due to the development of human society. Based on the analysis of multiple attributes of the river network, a statistical model has been proposed in this study in order to determine the river network protection indices such as river area ratio, storage capacity and flux. In this study, a numerical method is proposed to improve the structure and connectivity of the river network by calculating the occupation and supplement balance. According to the principle of water area dynamic balance, the river network structure and its connectivity are improved through water area adjustment in a typical coastal city. As the simulation results show, the water surface ratio equals 8.17%, the storage capacity equals 112.6 million m3 and the water flux equals to 656.06 m3/s in the selected study area. The flood drainage capacity is introduced as the priority function, other functions are also improved due to river management and protection. The harmonious and sustainable coexistence between human society and the river network is then promoted. This comprehensive statistical model proved to be a good tool for the coastal area to enhance the comprehensive attributes of the coastal plain river network and the sustainable development of the local area in the future.

Environmental justice implications of flood risk in the contiguous United States – a spatiotemporal assessment of flood exposure change from 2001 to 2019

ABSTRACT Flood hazard is one of America’s most frequent and expensive natural hazards and causes enormous economic losses in the United States every year. Flood hazards disproportionately affect marginalized and socioeconomically disadvantaged populations. This disproportionate flood exposure constitutes a form of environmental injustice. Few studies have undertaken a large-scale assessment of the long-term change of flood exposure. To fill this gap, this study utilized land use and flood zone data from 2001 to 2019 at a 5-year interval to analyze spatiotemporal changes in flood exposure in the Contiguous United States (CONUS). Two indices, the Deviational Exposure Index and Socioeconomic Disparity Index, were introduced to measure flood exposure and the socioeconomic disparities associated with flood exposure. At the national level, the overall flood exposure in the CONUS decreased in the past two decades, indicating increasing awareness of flood risk in the country. But the local variations of flood exposure and its changing trends vary among communities. In general, coastal and riverine counties show a general avoidance of developing urban areas in flood zones, while inland counties show an opposite tendency of urban development in floodplains. The results of this study reveal socioeconomic and demographic disparities between communities in and out of flood zones and evaluate environmental injustice among disadvantaged populations. The knowledge learned from this study can not only help address environmental justice issues but also benefit the decision-making of the federal government and local authorities in urban development and smart growth when faced with flood risk.

ПРИМЕНЕНИЕ РАДАРНЫХ И ОПТИЧЕСКИХ ДАННЫХ ДЗЗ ДЛЯ ОЦЕНКИ КОЛИЧЕСТВА ПОСТРАДАВШИХ ДОМОВ, ПЛОЩАДИ И ГРАНИЦ ЗОН ЗАТОПЛЕНИЯ

The article presents the result of determining the flooding zone and the affected houses and buildings of the town of Atbasar from the spring floods of 2017. This result was obtained using three available remote sensing data Sentinel-2A, Landsat-8 and Sentinel-1B of medium spatial resolution. At the first stage, remote sensing data of the near, short-wave, thermal infrared (IR) range and polarization by contrast level were visually analyzed. Images were selected based on a high level of contrast between two classes: a water object and a non-water object (land). At the second stage, threshold values were calculated from a sample of pixels related to water bodies, and then binary images were created. In the third stage, binary images were logically summarized to eliminate the cloud effect and find the resulting binary image of the flood zone from spring floods. In the fourth stage, the resulting binary image was superimposed on the GIS data of the town of Atbasar, where the locations and the number of affected houses and buildings were located. According to this study, it was found that more than 200 country houses were flooded in the northern part, and 9 houses in the eastern part of the town of Atbasar. According to media reports and official bodies, the number of affected houses in Atbasar was about 400. The number of affected houses found by the method of logical summation with three remote sensing data was 52%. The accuracy of the location can be significantly improved by using high spatial resolution remote sensing data. The results of this study may be useful for the emergency service, local government agencies, and insurance companies in assessing damage from spring floods.

Assessment of Flood Vulnerability and Coping Strategies of Communities Living along River Tana in Madogo Ward, Kenya

Purpose: Flood is a natural disaster that occurs due to the sudden onset of rainfall that causes runoff waters from high to low altitude area. Community living along the River Tana in Madogo ward, Tana River County are affected by the floods when it occurs. It was therefore important to assess factors contributing to their flood vulnerability and assess their flood coping and adaptation strategy for current and future planning. This study assessed the factors contributing to flood vulnerability, adaptation and coping strategies along River Tana in Madogo Ward, Tana River County, Kenya. The research objectives were to assess the trends of flood occurrence in Madogo Ward between 2000 and 2020 as well as the coping and adaptation strategies of communities to floods in Madogo Ward.
 Materials and Methods: A descriptive research design approach was used. Data collection approaches involved the use of questionnaires to identify coping strategies by communities. Key informant interviews were also conducted with government officers within the study area to provide information on factors contributing to flood vulnerability, flood trends, occurrence adaptation and coping strategies. Secondary data was acquired through journals, books, and maps. The Statistical Package for Social Science was used to analyze the quantitative data. The analyzed data was presented through maps, tables, figures and graphs.
 Findings: The results indicated that the floods occur after every two years in the study area with different magnitudes and durations. The main coping strategies employed by the community living along River Tana in Madogo Ward was relocation to the higher grounds. It was also established that the community in the area had developed adaptive strategies to flood by putting barriers round their houses. Further findings indicated that the major flood vulnerability factor was topography of the area.
 Implications to Theory, Practice and Policy: Based on the findings, it is being recommended that community leaders and county government of Tana River should not allocate plots in the flood zone area. Hence, there is a need for flood zone mapping for resident to know whether they are living within flood zone or not. Additionally, the people’s economic power should be enhanced through entrepreneurial training and giving them first priority in job opportunities. There is also a need to improve the quality of the infrastructures in the area to enhance their resilience to the negative impact of floods.

Soil Bacterial and Archaeal Communities of the Periodic Flooding Zone of Three Main Reservoirs in the South Ural Region (Russia)

Studying the soils in the periodical flood zone of three reservoirs is of promising importance for their subsequent return to economic activities. Research on the bacterial and archaeal communities of soils that are periodically or continuously flooded by reservoirs is still insufficient. To evaluate the chemical status of soils and their microbiota, the study was conducted in the Yumaguzino, Nugush, and Slak reservoir sites in the South Ural area (Russian Federation). The bacterial and archaeal communities of periodically flooded and non-flooded soils were investigated after a comparative investigation of chemical, hydrological, and climatic factors. It was discovered that flooded soils had anoxic conditions during the whole of the year, with brief drying intervals of limited length and low levels of effective temperatures. In terms of chemistry, flooded soils are distinguished by increased acidity, a fall in organic matter, and an increase in alkali-hydrolysable nitrogen. Compared to their counterparts in non-flooded soils, bacterial and archaeal communities in flooded soils are significantly different. Generally speaking, the biodiversity of flooded soils rises with the duration and depth of floods. Significant variations at the phylum level are mostly caused by a decline in the relative presence of Thaumarchaeota and an increase in Proteobacteria and Chloroflexi representation. It was discovered that the Euryarchaeota phylum was either absent or had a significantly decreased relative prevalence at the sites of intermittently flooding soils.

Deciphering spatial-temporal dynamics of flood exposure in the United States,

Extracting baseline information on flood exposure and its temporal evolution is essential to formulate flood risk reduction strategies. At present, comprehensive, long-term spatial-temporal flood exposure research in the United States is lacking. The objective of the study is to evaluate county-wide flood exposure in the US and unravel its spatial-temporal dynamics from 2001 to 2019 to answer three research questions via hypothesis testing. First, how have human settlement areas exposed to flood threats in the US changed over the past two decades? Second, has the occurrence of floods and their resulting damage influenced the growth of developed areas in flood zones? Third, do disparities exist in the sensitivity to flood threats among urban-rural communities? Results show that the overall rate of development in flood zones in the contiguous United States has steadily decreased from 2001 to 2019. The Local Moran's I analysis discovers pockets of emerging, expanding, shrinking, and changing clusters of communities that show a rapid increase or decrease of developed areas within flood zones over time. Most counties that experienced more frequent flooding events demonstrate greater responsiveness to flood hazards by avoiding development in flood zones. Finally, urban communities exhibit a higher exposure and sensitivity to flood hazards compared to rural areas.

Identification of agricultural surface source pollution in plain river network areas based on 3D-EEMs and convolutional neural networks.

Agricultural non-point sources, as major sources of organic pollution, continue to flow into the river network area of the Jiangnan Plain, posing a serious threat to the quality of water bodies, the ecological environment, and human health. Therefore, there is an urgent need for a method that can accurately identify various types of agricultural organic pollution to prevent the water ecosystems in the region from significant organic pollution. In this study, a network model called RA-GoogLeNet is proposed for accurately identifying agricultural organic pollution in the river network area of the Jiangnan Plain. RA-GoogLeNet uses fluorescence spectral data of agricultural non-point source water quality in Changzhou Changdang Lake Basin, based on GoogLeNet architecture, and adds an efficient channel attention (ECA) mechanism to its A-Inception module, which enables the model to automatically learn the importance of independent channel features. ResNet are used to connect each A-Reception module. The experimental results show that RA-GoogLeNet performs well in fluorescence spectral classification of water quality, with an accuracy of 96.3%, which is 1.2% higher than the baseline model, and has good recall and F1 score. This study provides powerful technical support for the traceability of agricultural organic pollution.

A Numerical Expedition through the Mathematical Representation of Complex Braided Morphometry—A Case Study of Brahmaputra River in India

The present work explores the process of mathematical representation for the complex geometry of a wide alluvial river with high braiding intensities. It primarily focuses on an approach to developing a numerical solution algorithm for representing the complex channel geometry of the braided Brahmaputra River. Traditional elliptic PDEs with boundary-fitted coordinate transformation were deployed, converting the non-uniform physical plane into a transformed uniform orthogonal computational plane. This study was conducted for the river channel reach with upstream and downstream nodes at Pandu and Jogighopa (reach length ~100 km), respectively, within the Assam flood plain in India, with fourteen measured river cross-sections for the year of 1997. The geo-referenced image covering the river stretch in 1997 was delineated using a ArcGIS software 9.0 tool by digitizing the bank lines. Stream bed interpolation was conducted by interpolating bed elevation from a bathymetrical database onto code-generated mesh nodes. Discretization of the domain was performed through the developed computer code, and the bed-level matrix was generated by the IDW method as well as the MATLAB tool using the nearest neighborhood technique. A mathematical representation of a digital terrain model was thus developed. This generated model was employed as a geometrical data input to simulate secondary flow utilizing 2D depth-averaged equations with the flow dispersion stress tensor as an extra source component, coming from curvilinear flow patterns caused by severe river braiding. The developed model may further be useful in mathematically representing the geometrical complexities of braided rivers with a relatively realistic assessment of the various parameters involved if deployed with improved river modeling with morphometric evolution.

Tracing the land use specific impacts on groundwater quality: a chemometric, information entropy WQI and health risk assessment study.

Understanding the nexus of land use and water quality can potentially underline the influences within the groundwater management. The study envisages land use-specific qualitative assessment of the groundwater resources in Ghaziabad district, in western Uttar Pradesh, India. For encountering the relative impacts of land use on the groundwater quality, chemometric analysis has been employed to apportion the pollution sources. The integration of quality parameters, in the information entropy index modeling, has segregated the quality classes and visualized the seasonal suitability trends as per potability standards along with non-carcinogenic health hazard risk assessment (HHRA). The qualitative assessment of the groundwater resources, along with spatial distribution, has deciphered a polluting impact, specifically in western and south western parts of district, and observed the linkages with direct and indirect discharges/seepages from densely populated residential and industrial land use types localized in urbanized areas. Statistically significant annual and seasonal variations have been found exclusively for EC, Mg2+, F-, Cd, Cr(total), Ni, and Pb which inferred variable concentrations, whereas land use types showed a non-significant variation within groundwater quality. Chemometric-based source apportioning and hierarchical cluster analysis (HCA) have derived salinization and enrichment of dissolved salts, arising from mixed sources and contributes to metal pollution, i.e., mainly from anthropogenic sources. Information EWQI derived poor to extremely poor category represented degraded potability specifically for fewer sites located within western and southern parts on the Yamuna-Hindon flood plains for limited sites of residential, industrial, and agricultural in an urbanized region. However, majority of the samples fall under excellent to good groundwater quality, recommendable in the north and north-eastern (peri-urban) regions. Non-carcinogenic HHRA has shown that majority of the samples categorized under unsafe value for hazard index (HI > 1), for females and children and thus, presumed probable health hazard risk from metal groundwater pollution in south-western part, eastern, and northern regions.

Discharge estimation in compound channels with converging and diverging floodplains using an optimised Gradient Boosting Algorithm

ABSTRACT River discharge estimation is vital for effective flood management and infrastructure planning. River systems consist of a main channel and floodplains, collectively forming a compound channel, posing challenges in discharge calculation, particularly when floodplains converge or diverge. In the present study, ML algorithms such as XGBoost, CatBoost, and LightGBM were developed to predict discharge in a compound channel. PSO algorithm is applied for optimization of hyperparameters of gradient boosting models, denoted as PSO-XGBoost, PSO-LightGBM, and PSO-CatBoost. ML model discharge predictions were validated with existing empirical models and feature importance was explored using SHAP and sensitivity analysis. Results show that all three gradient-boosting algorithms effectively predict discharge in compound channels and are further enhanced by application of PSO algorithm. The R2 values for XGBoost, PSO-XGBoost, CatBoost, and PSO-CatBoost exceed 0.95, whereas they are above 0.85 for LightBoost and PSO-LightBoost. PSO-CatBoost performance is better than other models based on findings of statistical performance parameters, uncertainty analysis, reliability index, and resilience index for prediction of discharge in a compound channel with converging and diverging flood plains. The findings of this study validate the suitability of the proposed models especially optimized with PSO is recommended for predicting discharge in a compound channel.