Moderate Zones Research Articles

Impact of Climate Variability and Interventions on Malaria Incidence and Forecasting in Burkina Faso

Background: Malaria remains a climate-driven public health issue in Burkina Faso, yet the interactions between climatic factors and malaria interventions across different zones are not well understood. This study estimates time delays in the effects of climatic factors on malaria incidence, develops forecasting models, and assesses their short-term forecasting performance across three distinct climatic zones: the Sahelian zone (hot/arid), the Sudano-Sahelian zone (moderate temperatures/rainfall); and the Sudanian zone (cooler/wet). Methods: Monthly confirmed malaria cases of children under five during the period 2015–2021 were analyzed using Bayesian generalized autoregressive moving average negative binomial models. The predictors included land surface temperature (LST), rainfall, the coverage of insecticide-treated net (ITN) use, and the coverage of artemisinin-based combination therapies (ACTs). Bayesian variable selection was used to identify the time delays between climatic suitability and malaria incidence. Wavelet analysis was conducted to understand better how fluctuations in climatic factors across different time scales and climatic zones affect malaria transmission dynamics. Results: Malaria incidence averaged 9.92 cases per 1000 persons per month from 2015 to 2021, with peak incidences in July and October in the cooler/wet zone and October in the other zones. Periodicities at 6-month and 12-month intervals were identified in malaria incidence and LST and at 12 months for rainfall from 2015 to 2021 in all climatic zones. Varying lag times in the effects of climatic factors were identified across the zones. The highest predictive power was observed at lead times of 3 months in the cooler/wet zone, followed by 2 months in the hot/arid and moderate zones. Forecasting accuracy, measured by the mean absolute percentage error (MAPE), varied across the zones: 28% in the cooler/wet zone, 53% in the moderate zone, and 45% in the hot/arid zone. ITNs were not statistically important in the hot/arid zone, while ACTs were not in the cooler/wet and moderate zones. Conclusions: The interaction between climatic factors and interventions varied across zones, with the best forecasting performance in the cooler/wet zone. Zone-specific intervention planning and model development adjustments are essential for more efficient early-warning systems.

Multi-Scale Supply and Demand Relationships of Ecosystem Services Under Multiple Scenarios and Ecological Zoning to Promote Sustainable Urban Ecological Development in Arid Regions of China

Predicting and analyzing the supply and demand relationship of ecosystem services provides theoretical support for the improvement of the ecological environment. This paper takes Bortala, a typical oasis city with a fragile ecological environment in the arid northwest region, as a case study. Based on the GMOP-PLUS-InVEST coupled model, it predicts the coupling coordination and matching degree of the supply and demand connection of ecosystem services such as habitat quality (HQ), carbon storage (CS), water yield (WY), and soil erosion (SD) under four scenarios. The findings indicate that from 2020 to 2035, HQ, CS, and WY have basically achieved coupling coordination at both scales. However, there is a notable disparity in the supply and demand of water resource production and carbon emission production. To ensure the long-term balance of ecosystem service supply and demand (ESSD), the research area was ultimately divided into five ecological zones: ecological conservation zone, ecological agriculture zone, ecological moderate development zone, ecological improvement zone, and ecological protection zone. It could offer insights for guiding the sustainable growth of ecologically vulnerable zones in the future.

Intensification of flocculation efficiency in multi-stage reactors by optimizing the multi-cone segment configuration

Flocculation is widely used in water treatment, and creating an optimal environment for floc growth is essential to enhancing flocculation efficiency. In this paper, we developed a multi-stage flocculation reactor (MFR) with strong, moderate, and weak mixing zones. Specifically, multi-cone structures with varying diameter ratios (DR) were incorporated in the moderate zone to promote floc growth. Computational simulations revealed that an MFR with a DR of 0.5 generated a uniform and symmetric flow field, reducing zero-velocity zones and forming distinct vortices within cones. This environment facilitated gradual floc growth while minimizing breakage. When applied to treating fracturing flowback fluid, a complex and challenging wastewater, the MFR produced larger and denser flocs, with an average chord length of 180 μm and a fractal dimension of 1.7170. These flocs exhibited high viscoelasticity, with a strength factor of 68.22 and a recovery factor of 47.77, indicating superior shear resistance and recovery ability after breakage. Consequently, the MFR achieved COD and turbidity removal rates of 92.05% and 93.61%, respectively, outperforming a stirred flocculation reactor, which achieved rates of 72.29% and 83.53% for the same parameters. Additionally, the MFR demonstrated excellent pollutant removal efficiency for both mineral processing wastewater and dyeing wastewater. With gradually decreasing energy along the flow direction, the MFR provided appropriate mixing intensities for different stages of floc growth, promoting efficient formation. These findings underscore the MFR’s potential as a highly effective solution for wastewater treatment applications.

Geophysical and geospatial insights into surface and subsurface characteristics for groundwater potential analysis, Ras Sudr, West Sinai, Egypt

Ras Sudr has garnered significant interest owing to various initiatives aimed at expanding and developing this area. It holds considerable strategic importance, serving as a key development hub in Sinai and a focal point for tourism destination. Moreover, it has a remarkable event with flashfloods which can be utilized for groundwater or direct usage. Integrating geophysical and geospatial analyses to study the surface and subsurface characteristics as well as identify groundwater potential areas in Ras Sudr, west-central Sinai is the main objective of this study. Firstly, geophysical data including gravity and magnetic methods have a crucial importance in qualitative and quantitative interpretation of the subsurface elements. Filtering techniques were implemented to distinguish between regional and residual anomalies. Geophysical data were subjected to the radial average power spectrum technique and 3D Euler deconvolution to identify the depth of the subsurface sources. The structure pattern that characterizes the interested region was defined by employing bandpass filter and edge detection appoarches using residual anomaly maps, regional anomaly maps, tilt derivatives and total horizontal gradient maps reflecting four distinct structural trends; NW-SE parallel to the Gulf of Suez, NEE-SWW parallel to the Syrian arc system, N-S parallel to the the Nile Valley, and NNE-SSW parallel to the Gulf of Aqaba. A basement relief map was constructed using 3D magnetic modelling showing that the depth of the basement ranges from 1.6 to 6.3 km. Secondly, the remote sensing data including Sentienl-2 and SRTM datasets were employed to extract the surface analyses in the GIS environment to develop the occurrence of groundwater potentiality utilizing seven factors; LU-LC, soil, geology, slope, drainage network and lineament density and rainfall data of the study area which were ranked from 1 to 5 and weighted according to their effective contribution to the infiltration of groundwater using AHP-GIS based multi criteria method. The resulting Groundwater Potential zone (GWPZ) was categorized into five zones from poor to excellent and validated using 41 observed wells. A significant quantity of wells was identified in the areas of high potential located to the west of the region, while five wells were situated within the moderate potential zone. Thereby, the GWPZ map identifying locations with viable groundwater resources suitable for habitation, development and economic plans in Sinai for decision makers.

Application of remote sensing/GIS in the appraisal of geotechnical stability of civil engineering structures in cretaceous sedimentary units in Gombe, Northeastern, Nigeria

The increasing urbanization in Gombe township has necessitated the need for a city-wide assessment of the area to ascertain its spatial geotechnical stability. In this study, the geotechnical stability of Gombe township and environs, Northeastern, Nigeria, was appraised using the geospatial approach. Four different thematic maps (lithology, lineament, elevation, and slope) were generated in a GIS environment. Weights were allocated to the subclasses of the thematic maps based on their contribution to the stability of engineering structures. The thematic maps were integrated using ArcGIS 10.3 software to generate a geotechnical stability model of the study area, which was validated through an on-site inspection of the structures in the area. The study area was delineated into three zones: unstable (17.24%), moderate (77.2%), and stable (4.74%). The moderate zones characterised by medium elevation and slope, average lineament density, and underlain by sandstones were the predominant zones in the area. However, the stable and the unstable zones predominate in the western and eastern parts of the study area respectively. The stable zones that occur in the northwestern and southwestern zones of the study area are underlain by the Kerri-Kerri Formation while the poor and unstable areasare underlain by argillaceous materials of the Pindiga Formation. The validation of the model revealed numerous cracked buildings and bridges and a failed bridge in the unstable zones. The moderate stability zones suffer a mixed fortune, having some stable structures in some parts and failing structures in other parts. The buildings in the stable zones, however, are generally devoid of structural cracks.

Chemical Compound Identification of Lactic Acid Bacteria (LAB) From Porang Tubers Waste (A. muelleri blume) as Probiotic

The production of amylase produced by lactic acid bacteria (LAB) has better stability. The purpose of this study was to utilize and determine the characteristics of LAB isolates from porang skin waste which have the potential as probiotics and the activity of amylase enzymes. Isolation was done by fermentation method for 48 h with the addition of starter Pediococcus acidilactici that had been cultured. The results showed that the number of colonies of N1 isolates was 49 ×108 CFU/mL with regular small round colonies, having a convex elevation, the edges of the colonies were round, yellowish white, and Gram positive bacteria because they produced a purple color on Gram staining. Acid resistance test at pH 2.0; 3.0; 4.0; 5.0 and 6.0, the isolates N1 was able to survive at each pH because it showed turbidity in the growth medium. The antimicrobial activity test showed a strong zone of inhibition on S. aureus and S. pyogenes of 10,33 and 11,17 mm and a moderate zone of inhibition on K. pneumoniae, S. dysentriae, and P. aeruginosa, respectively, which was 6,33; 7,7 and 7,5 mm. The positive N1 isolate contained alkaloids as bioactive compounds from the results of phytochemical screening and the results of the FTIR analysis showed that specific groups of alkaloids were N-H, C-N, and C=O at wave numbers 3423.30 cm-1; 1235.45 cm-1; and 1634.81 cm-1.

Ecological Suitability Evaluation of City Construction Based on Landscape Ecological Analysis

Ecological suitability evaluation is a critical component of regional sustainable development and construction, serving as a foundation for optimizing spatial patterns of regional growth. This is particularly pertinent in karst mountainous regions characterized by limited land resources and heightened ecosystem vulnerability, where a quantitative assessment of ecological suitability for land development is both crucial and urgent. Based on the fundamental principles of structural and functional dynamics in landscape ecology, this study focuses on Gui’an New Area, a designated urban development zone situated in the karst landscape of Guizhou Province. An index system was established encompassing three dimensions: ecological elements, ecological significance, and ecological resilience, utilizing the integrated ecological resistance (IER) model to evaluate the suitability of regional development and construction. The results reveal that the eastern region exhibits higher suitability compared to the central and western regions, with the northwest region demonstrating the lowest suitability overall. Relatively speaking, the evaluation of geological environment suitability and the comprehensive ecological constraints associated with development and construction indicates that the areas currently planned and ongoing reflect flat terrain and low ecological risk. Furthermore, within the scope of ecosystem dynamic adaptation, developmental activities in these regions exert minimal impact on the natural ecosystem, thereby demonstrating a high suitability for development and construction. In terms of future key development zones, areas with gentle slopes ranging from 8 to 15 degrees are recommended, aligning with the actual requirements for cultivated land protection. The total area designated as prohibited development zones constitutes the smallest proportion, representing only 9.45%, which is significantly lower than that of priority development zones (38.75%) and moderate development zones (22.45%). From the perspective of landscape ecology, this paper provides a comprehensive investigation into the ecological suitability evaluation system for development and construction in the karst regions of Southwest China, offering valuable insights for assessing ecological suitability in similar areas.

Exploring an adaptive management model for “status-optimization-regulation” of mining city in transition: A case study of Huangshi, China

Mining cities face the challenges of ecological transformation and sustainable development after mineral depletion. Thus, ecological space optimization and adaptive management are pivotal after ecological restoration project, but easily neglected. Taking Huangshi in Hubei Province as an example, a top-down adaptive management model for regional mining ecological space integrating status-optimization-regulation (SOR) was established based on land system resilience (LSR) evaluation, circuit theory, complex network model and community discovery algorithm. The results showed that i) As the LSR increased, the land use structure shifted from non-ecological zones to forest and cropland, indicating that balancing agriculture and forest protection was crucial for increasing LSR in Huangshi. i) The ecological networks (ENs) of Huangshi had an irregular fishnet pattern, with densely intricate corridors in the south and broader, sparser ones in the north, and numerous ecological barriers near the mining area. Furthermore, the distribution of ecological sources and corridors displayed complementarity and hierarchy. iii) The optimized ENs exhibited higher connectivity and efficiency under disturbance, reducing corridor redundancy and migration costs. iv) The ENs clusters were classified into five types based on ecological connectivity: ecological buffer zone, priority restoration zone, moderate restoration zone, natural restoration zone, and moderate development zone, and tailored ecological regulatory strategies were proposed. The findings provide practice-oriented guidance for the sustainable development of mining cities, and offer a direct approach to support conscious, clear, and coherent adaptive management of ecological restoration in rapidly changing environments.

Geo-Spatial Technology for Identifying Optimal Well Locations in Kolugala Pahalagama Grama Niladhari Division for Effective Groundwater Management

This study utilized Geographic Information System (GIS) technology to pinpoint optimal locations for establishing wells, addressing the issue of declining water yields in the Kolugala Pahalagama Grama Niladhari Division (GND); a geographically diverse region. The research integrated geospatial data, including geolocations of sample wells, garbage pits and quarterly water level measurements collected through field surveys. Several thematic layers, namely, geology, elevation, slope, drainage density, soil type, and land use types were analysed to delineate groundwater potential zones within the GND. Satti's analysis hierarchy was employed to assign appropriate weights to these factors, reflecting their influence on groundwater recharge and well productivity. Spatial analysis revealed that 9.64% of the area displayed very good groundwater potential, 42.17% had good potential, 39.76% showed moderate potential, and 7.23% exhibited poor potential. The distribution of existing wells was also evaluated, showing that 6% were located in very good groundwater potential zones, 56% in good groundwater potential zones and 38% in moderate groundwater potential zones. Despite this, only 34% of the wells were placed in regions suitable for the establishment of wells, while the majority, 66%, were located in unsuitable areas. Notably, 18 wells displayed lower water levels, likely due to their excessive distance from neig-bouring wells. Further spatial analysis identified 29 hectares as unsuitable and 54 hectares as suitable for the future establishment of wells. These findings underscore the significance of geographic factors in the placement of wells, emphasising the need for strategic planning to ensure that wells are sited in areas with high groundwater potential, thus improving long-term water yield sustain-ability in the region.

Flood risk assessment under the shared socioeconomic pathways: a case of electricity bulk supply points in Greater Accra, Ghana

This study evaluates flood susceptibility and risk on Bulk Supply Points in the Greater Accra region (GAR) using a Frequency Ratio model based on 15 flood conditioning factors. The model explores the influence of natural, meteorological and anthropogenic factors on flooding occurrences under the Shared Socioeconomic Pathway (SSP) scenarios and assesses flood risks at Bulk Supply Points (BSPs). Flood susceptibility mapping was conducted for both current and future periods under various SSP scenarios. Results reveal that elevation, slope, soil type, distance from urban areas, and SPI are the most influential factors contributing to flooding susceptibility in the region. The current flood map, about 37% of the total area of GAR categorized under the moderate flood-susceptible zone category followed by about 30% categorized under the low flood-vulnerable zone. However, about 16% was categorized under the very high flood-vulnerable zone. The study projects increasing flood susceptibility under the SSP scenarios with intensification under SSP2 and SSP3 scenarios. For instance, the areas categorized as high and very high flood susceptibility zones are projected to expand to approximately 32% and 26% each by 2055 under SSP3. The study also assesses flood risks at Bulk Supply Points (BSPs), highlighting the escalating susceptibility of power assets to flooding under different scenarios. For instance, in the very high scenario, flooding is estimated to reach 640 h in 2045 and exceed 800 h in 2055—more than double the 2020 baseline. The analysis shows the bulk supply points face increasing flood susceptibility, with risks escalating most sharply under the severe climate change SSP3 and SSP5 scenarios. Over 75% of BSPs are expected to fall in the low- to medium-risk categories across SSPs while more than 50% of BSPs are within medium- to high-risk categories in all scenarios except SSP1, reflecting the impact of climate change. SSP3 and SSP5 stand out with over 60% of BSPs facing high or very high flooding risks by 2055. It indicates moderate resilience with proper adaptation but highlights potential disruptions in critical infrastructure, such as BSPs, during persistent flooding. The findings of the study are expected to inform Ghana’s contributions towards addressing Sustainable Development Goals (SDGs) 7, 11 and 13 in Ghana.

Assessment of shift in GWPZs in Kashmir Valley of Northwestern Himalayas

Groundwater is a critical resource for the Kashmir Valley, which is increasingly pressured by urbanization and climate change. This study aims to delineate Groundwater Potential Zones (GWPZs) in the Kashmir Valley using the Analytical Hierarchy Process (AHP) and Geographical Information Systems (GIS). The research integrates eight thematic layers, including geology, geomorphology, slope, drainage density, land use/land cover (LULC), lineament density, rainfall, and topographic wetness index (TWI), to assess GWPZs for 1995, 2010, and 2020. Weights for each layer were assigned based on their influence on groundwater dynamics. The generated GWPZs were classified into five classes: very high, high, moderate, low, and very low. Over 25 years, significant changes in GWPZs were observed: very low potential zones decreased by 45.17%, low potential zones by 26.17%, and very high potential zones by 72.95%. Conversely, moderate potential zones increased by 50.87%, and high potential zones saw a slight increase of 9.00%. Results indicated that high and very high GWPZs are predominantly located in the valley's alluvial plains, primarily covered by agricultural and partially horticultural land. Validation of the generated GWPZs using bore well locations, discharge data, and Receiver Operating Characteristic (ROC) curves demonstrated high accuracy, with Area Under the Curve (AUC) values of 0.915, 0.898, and 0.890 for the respective years. These findings underscore the adverse impact of urbanization on groundwater potential zonation and emphasize the need for sustainable water management practices. This study provides valuable insights into the long-term shifts in groundwater potential in response to urban expansion and climate change. It highlights the importance of continuous monitoring and adaptive management to safeguard groundwater resources.

Flood vulnerability analysis using geographic information system in the core zone of the Lore Lindu biosphere reserve, Indonesia

Floods are caused by the accumulation of several factors, such as global warming, climatological characteristics, hydrology, and physical conditions of an area. The purpose of this study was to map the level of flood vulnerability in the core zone of the Lore Lindu Biosphere Reserve using geographic information system (GIS) based spatial analysis with scoring and overlay. The research parameters consisted of rainfall, elevation, slope, soil type, land cover, and distance from the river. This research was conducted in the core zone divided into 13 subdistricts and 2 regencies. The results of the classification of flood vulnerability levels are divided into 4 (four) categories: not prone, low vulnerability, moderate vulnerability, and high vulnerability. The results of the analysis show that the core zone of the Lore Lindu biosphere reserve is dominated by a non-hazardous site with an area of 145,018’28 ha (67.23%), a low vulnerability zone of 65,430.10 ha (30.33%), a moderate vulnerability zone of 5,025.29 ha (2.33%), and a high vulnerability zone of 245.99 ha (0.11). Areas with a high level of vulnerability are at low elevations with flat to gentle slopes. Most land use is dominated by water, mining, and open land without vegetation and is located around rivers.

The role of artificial intelligence data in estimating the extent of gully erosion the basin is Wadi Khashm Al-Mujadar

Wadi Khashm Al-Mujadar basin is one of the dry valleys in the southern western plateau of Iraq, it is located astronomically between two latitudes (5314.191◦29) (2437.944◦29) north, and (102.327◦46) (02.79◦46) east. It is characterized by geomorphological, hydrological and natural resource characteristics, contributes to the development of the lands of the southern Western Plateau. The importance of the topic comes from the natural and human characteristics of this basin that contribute to development, with artificial intelligence data, it has become an important tool in the process of analyzing, linking, interpreting and modeling some natural risks, to which the soil and lands are exposed under varying climatic conditions that contribute to the variation in the quality and extent of erosion. The use of artificial intelligence data is an effective tool in achieving valuable and accurate results. The research aims to use artificial intelligence data to estimate the extent of erosion, determine its type, cases, and degree of severity, and model it, depending on the results of the calibrations used, especially the Bergsma criterion for determining groove erosion. Gully erosion in the basin varies from light gully erosion to high gully erosion, due to the variation in the amount of rain, its falling regime, and the characteristics of the soil in the region, in addition to the rock formations, the steepness of the slope, the density of natural vegetation and the role of humans in it. The study showed that there are (4) erosion zones: it is a very light erosion zone(13.03 km2 and a rate of 4.28%), the area of light erosion (218.35 km2, at a rate of 71.81%, the moderate erosion zone (68.71 km2, at a rate of 22.6%, and the high erosion zone (3.99 km2, at a rate of 1.31%. The majority of the area was located within the range of light and moderate erosion, requires finding ways to reduce soil erosion and the deterioration of its structure, composition and natural properties.

Rainwater Flood risk assessment in Zaatari Refugees Camp- Jordan: Towards Sustainable Solutions

Refugee settlements are frequently located in isolated and remote areas, characterized by poor-quality land and harsh climatic conditions. Zaatari camp in Jordan has suffered and continues to suffer from rainwater floods every winter. This study uses GIS analysis to assess flood risk in the camp, revealing that 61.1% of the area is moderately risky, while 0.84% and 22.42% are very high and high-risk zones respectively. The highest risk areas are near the camp boundary. This study recommends a structural intervention and first-class priority at the entrance area of the camp as it is located within a high-risk area and is of vital importance from a functional standpoint. These recommendations range to areas within high-risk zone in (1, 2, 7, 12) districts, to moderate risk zone in (4,8,11) districts with precautionary and preventive measures. In addition, some structural solutions can be implemented in several stages. This research is significant not only for managing flood risk in Zaatari but also for providing a replicable methodology for similar humanitarian settlements worldwide.

Applying the driver-pressure-state-impact-response model to ecological restoration: A case study of comprehensive zoning and benefit assessment in Zhejiang Province, China

Ecosystem degradation is a global problem that poses a significant threat to the sustainable development of human societies, particularly in developing countries, such as China. In response, China has implemented a series of ecological restoration (ER) policies over recent years. However, significant regional developmental disparities, pronounced spatial heterogeneity of ecological issues, and substantial historical debt for ER in China present considerable obstacles and financial burdens to the effective implementation of ER strategies. Delineating ER zones and assessing the ER benefits are essential for developing effective ER strategies and implementing ER projects. In this study, we constructed a comprehensive framework for ER utilizing the Driver-Pressure-State-Impact-Response (DPSIR) model, quantified the urbanization levels, ecological state, and restoration costs in Zhejiang Province to delineate ER zones, integrated the patch-generating land use simulation model with the ecosystem service value assessment method to quantify the benefits of ER, and ultimately developed tailored ER strategies. The results showed that: (1) The pattern of urbanization levels was characterized by high levels in the northeast and low levels in the southwest, which constrated with the ecological state. The areas of high restoration costs were located in the northeastern and southeastern regions, and the areas of low restoration costs were situated in the southwestern region. (2) The rate of construction land expansion is significantly curtailed under the ER scenario compared to the natural development scenario in 2035, while forest areas have seen effective protection and an increase from the levels of 2020. (3) The ER policy is projected to generate ecological benefits totaling CNY 8.23 billion by 2035, substantially reducing the rate of ecosystem degradation. (4) Zhejiang Province is divided into five zones at the county scale: ecological autonomous protection zone, ecological core protection zone, ecological priority restoration zone, ecological control zone, and moderate development zone. Strategies have been devised based on the forecasted benefits of ER, offering valuable insights into ecological management. These findings aim to enhance the understanding of ER and support the development and implementation of regional ecological policies.

A Multi-criterian Approach to Identify Groundwater Potential Zones in the Subarnarekha River Basin Using Integrated Analytical Hierarchy Process and Geospatial Technology

The intense extraction of groundwater and changing climate patterns have strained global groundwater supplies. As the demand for drinkable water rises worldwide, assessing groundwater availability and aquifer output becomes increasingly important. Geographic information systems (GIS) are being used more frequently for groundwater exploration due to their speed and provision of preliminary data. This study focuses on mapping groundwater availability in a minor tropical river basin in India, using a combination of GIS and the analytical hierarchy process (AHP). Ten thematic layers were generated and analyzed, including Geology, Geomorphology, Land use and land cover (LULC), Lineament density, Drainage density, Rainfall, Soil type, Slope, Topographic Wetness Index ( TWI), and curvature to delineate groundwater potential zones. AHP was employed to assign weights to each category based on their water retention properties. The resulting map was validated against existing groundwater data, demonstrating an accuracy of approximately 85%. The groundwater potential zones were classified as high, moderate, and, low. The moderate potential zone covered 59% of the basin, while the low and high potential zones constituted 29% and 11% respectively. High and low potential regions were limited to small sections of the basin. In conclusion, this research successfully mapped the groundwater availability in the Rarhu River watershed using GIS and AHP. The findings highlight the distribution of different groundwater potential zones, providing valuable information for sustainable water resource management in the area.

Delineation of potential zones for groundwater recharge using integrated GIS-based AHP and CSI techniques in Ogun Waterside, Southwestern Nigeria

ABSTRACT Ogun Waterside region of southwestern Nigeria experiences seasonal water stress stemming from groundwater overdraft. Therefore, it became imperative to effectively manage the existing groundwater resources to fulfill the anticipated demand for potable water. To achieve this goal, an analysis involving seven spatial parameters: geomorphology, land use/land cover, slope, lineament density, drainage density, soil types, and geology was conducted. These parameters were examined using a combination of geographic information system (GIS)-based analytical hierarchy process (AHP) and cumulative score index (CSI) techniques to delineate potential zones for groundwater recharge. The AHP methodology was employed to assign relative weights to the thematic layers and their corresponding features, reflecting their importance. The AHP results were integrated using a weighted linear combination within a GIS environment to generate the groundwater recharge potential map. Further, the CSI was used to reclassify the composite groundwater recharge potential map. The resultant map revealed three zones which were classified into high, moderate, and low potential zones founded on the CSI approximation. About 98.56 km2 (8.28%) of the study area is categorized as having low potential, 803.77 km2 (67.54%) falls within the moderate potential zone and 287.71 km2 (24.18%) falls in the high potential zone.

Groundwater quality prediction and risk assessment in Kerala, India: A machine-learning approach

Despite its critical importance for health, agriculture, and the economy, and its key role in supporting climate change adaptation, groundwater quality remains vulnerable to contamination and is often neglected until significant deterioration. The groundwater resources of Kerala, one of the southernmost states of India, are under escalating stress and scarcity, despite a high well density with 62% of the population relying on groundwater from approximately 6.5 million open wells. This study investigates the detailed hydrogeochemistry and predicts groundwater quality zones of the state using machine-learning techniques viz, extreme gradient boosting (XGBoost), support vector regression (SVR), artificial neural network (ANN) and random forest (RF) regression. The hydrogeochemical analysis reveals varying groundwater quality across the state. Among the different machine learning models, RF shows higher goodness of fit (R2: 0.922) with minimal prediction error (root mean square error: 6.29 and mean absolute error: 3.12). The predicted groundwater quality was validated using the spatially distributed stiff diagrams, visually representing water composition trends of each well. The very good, good, moderate and poor groundwater quality zones occupy 31.7%, 40.4%, 20.4%, and 7.4% of the state aligning accurately with the groundwater quality scenario of the state. Additionally, groundwater drinking risk assessment was conducted, considering that 7.4% of the state experiences poor-quality groundwater. Integrating groundwater quality maps with population data, the study assessed potential health risks due to consuming untreated water. Nearly 0.59 million people across 252 local self-government bodies (LSGs) are susceptible to consuming poor quality groundwater, which may pose potential health risks. This observation provides valuable insights for sustainable groundwater management and public health safeguarding and the findings of the present study are useful for achieving sustainable development goal (SGD) 6 (clean water and sanitation) and long-term groundwater management in Kerala.

Flood hazard assessment using machine learning and hydrodynamic modeling: case study in the Vu Ga–Thu Bon basin in Vietnam

ABSTRACT The objective of this study was the construction of a theoretical framework to evaluate flood hazards by integrating machine learning and hydrodynamic modeling in Vietnam's Vu Gia–Thu Bon basin. MIKE FLOOD was used to simulate historical floods in 2017 in order to obtain flood depth and velocity. Support vector machine-stochastic gradient descent (SVM-SGD), decision trees (DT), and dagging (DA) were used to determine flood susceptibility. Flood hazard was constructed by combining the flood depth, velocity, and susceptibility using the analytic hierarchy process technique. The statistical indices AUC, RMSE, MAE, and NASH were used to evaluate the precision of the hydrodynamic and machine learning models. The results showed that hydrodynamic modeling was highly accurate, with a NASH value of 0.86. The proposed models achieved AUC values of 0.98 for SVM-SGD, 0.93 for DT, and 0.92 for DA. The results showed that 7.59% of the flood zones is located in the very low flood hazard zone, 108.2 km2 in the low flood hazard zone, 24.59% in the moderate flood hazard zone, 22.53% in the high flood hazard zone, and 10.01% in the very high flood hazard zone.

Geospatial and geo-electrical assessment of groundwater vulnerability and potential in parts of Cross River, Southern Nigeria

Assessing groundwater vulnerability and potential is essential for sustainable management. This study evaluates these factors in southern Cross River, Nigeria, using geospatial and geo-electrical methods, including Vertical Electrical Sounding (VES), Geographic Information Systems (GIS), and Remote Sensing (RS). Twenty VES surveys were performed, revealing aquifer resistivity from 5.12 to 506.00 Ω/m, thickness from 6.60 to 34.30 m, and depth from 18.60 to 68.00 m. Rainfall was the most significant factor (38 %) affecting groundwater potential, followed by geology (24 %), slope (13 %), drainage density (8 %), land use/cover (6 %), lineament density (5 %), and soil type (3 %). With a Consistency Ratio (CR) of 0.043884, data consistency was high. Groundwater potential zoning (GWPZ) maps categorized the area into low, moderate, good, and excellent zones, highlighting high potential in western areas with high lineament density and moderate slopes. This research demonstrates the effectiveness of integrating geospatial and geo-electrical techniques for groundwater assessment.