Geoenvironmental Characteristics Research Articles

Spatial distribution of Japanese encephalitis cases and correlated geo-environmental factors in southern and northern counties of China

Japanese encephalitis (JE) is a mosquito-borne disease with a spatial distribution that is linked to geo-environmental factors. The spatial distribution of JE cases and correlated geo-environmental factors were investigated in two critical counties in southern and northern China. Based on maps, enhanced thematic mapper (ETM) remote sensing datasets from Landsat and spatial datasets of JE cases, spatial distribution and spatial cluster analyses of JE cases at the village scale were performed by using the standard deviational ellipse and Ripleys K-function. Global and regional spatial cluster analyses of JE cases were also performed by using Moran's index. Regression analysis was used to analyze the relationships between geo-environmental characteristics and the risk of JE cases. At the study sites, the JE cases were not spatially clustered at the village or district (global) level, whereas there was a spatial cluster at the district (local) level. Diversity-related features for JE patients at the district and village levels were detected at two sites. In the southern counties, the distance of a village from a road was related to the village-level JE risk (OR: 0.530, 95 CI: 0.297–0.947, P = 0.032), and the number of township-level JE cases was linked to the distance of the district center from the road (R =-0.467, P = 0.025) and road length (R = 0.516, P = 0.012) in the administrative area. In northern China, the modified normalized difference water index (MNDWI) in the 5 km buffer around the village was related to village-level JE risk (OR: 0.702, 95% CI: 0.524–0.940, P = 0.018), and the number of township-level JE cases was related to the MNDWI in the administrative region (R =-0.522, P = 0.038). This study elucidates the spatial distribution patterns of JE cases and risk, as well as correlated geo-environmental features, at various spatial scales. This study will significantly assist the JE control efforts of the local Centers for Disease Control and Prevention (CDC), which is the base-level CDC, particularly concerning the allocation of medicine and medical staff, the development of immunological plans, and the allocation of pesticides and other control measures for the mosquito vectors of JE.

Geochemical, mineralogical, and geophysical methods to establish the geoenvironmental characteristics of the King River delta, Queenstown, Western Tasmania

Throughout most of the 20th century, the Mount Lyell Mining and Railway company discharged tailings from the Mount Lyell mine into the Queen River. Tailings migrated downstream of the King River and deposited on riverbanks, the riverbeds and in the King River delta in Macquarie Harbour. This research combines mineralogical, geochemical, and geophysical techniques to characterise the King River delta and to constrain the volume of mine tailings on the King River delta. For this purpose, 25 trenches were excavated across the delta with 145 sediments samples and 20 water samples collected.Tailings in the delta are abundant in quartz (average 50 wt %), muscovite (average 16 wt %), chlorite (mean 11 wt %), pyrite (average 4 wt %), Fe-oxyhydroxides such as goethite (average 0.8 wt %), hematite (average 0.4 wt % and ferrihydrite (average 0.2 wt %), jarosite (average 0.8 wt %) and chalcopyrite (average 0.1 wt %). Sediments are dominated by Fe (average 77,468 ppm) and include high concentrations of Cu (average 1425 ppm) and trace elements such as Co (average 350 ppm). Chalcopyrite is the primary Cu mineral whereas pyrite is the main mineral host for Co. Geoenvironmental tests show tailings in the delta have acid-forming potential, as validated by pore water analyses with pH between 3.1 and 6.3. These conditions enable metal dissolution, with high contents of dissolved heavy metals, especially Fe, Cu, Co and Zn, detected in the pore waters.Apparent resistivity and shear wave profiles suggest the base of tailings is located at depths of 3–5 m. Low resistivity (i.e., <2 Ωm) indicate a saltwater intrusion into likely natural sediments below the tailings, whereas resistivity values between approximately 5 to 12 Ωm, below 15 m depth, suggests a transition to bedrock. The volume of tailings is estimated at ∼14.0 Mt and concentrations of Cu and Co imply that reprocessing of this material could be a feasible option with significant economic and environmental benefits.

Geo-Environmental Models of In-Situ Leaching Sandstone-Type Uranium Deposits in North China: A Review and Perspective

Since the 1990s, sandstone-type uranium in the northern basin of China has become the main target for mining. Uranium mining can cause a series of impacts on the environment. A conceptual model of the geo-environment for sandstone-type uranium in northern China was described, which covers the changes in the geo-environmental characteristics in the natural state, in the mining process, during decommissioning and after treatment. Sandstone-type uranium is mainly distributed in the Songliao, Erlian, Ordos, Turpan–Hami and Ili Basins, which have arid climates and poor stratum permeability. Pitchblende is the main uranium-bearing mineral and is associated with iron, copper, coal, organic matter and other minerals. The mineral often has a low ore grade (0.01–1.0%) and high carbonate content (2–25%). Uranyl carbonate accounts for more than 90% of the total uranium in groundwater. The uranyl content is closely related to the TDS. The TDS of groundwater in the eastern and central ore belts is usually lower than 2 g/L, while in the western region, such as Xinjiang, it can exceed 10 g/L. In situ leaching (ISL) is the main mining method that results in groundwater pollution. Acid leaching leads to a pH decrease (&lt;3), and heavy metals represented by U and Fe exceed the background values by hundreds of times, resulting in groundwater pollution. CO2 leaching is more environmentally friendly, and the excess ions are usually Ca2+, Mg2+, NO3− and HCO3−. Soil chemical anomalies originate mostly from wind erosion and precipitation leaching of decommissioned tailings. Uranium pollution is mainly concentrated within 20 cm of the surface, and the exceedance generally varies from two to 40 times. During ISL, a series of environmental measures will be taken to prevent pollution from being exposed to the surface. After treatment, the decommissioned uranium mines will likely have no impact on the surrounding environment. In the future, the protection of groundwater should be strengthened during production, and remediation methods based on electrokinetic, microbial and permeable reactive barrier (PRB) technology should be further researched.

Exploring the Application of a Debris Flow Likelihood Regression Model in Mediterranean Post-Fire Environments, Using Field Observations-Based Validation

Post-fire geomorphic processes and associated risks are an important threat in Mediterranean environments. Currently, post-fire mass movement prediction has limited applications across the Mediterranean despite the abundance of both forest fires and landslide/debris flow disasters. This work applies a debris flow generation likelihood model to evaluate the probability of mass movement phenomena in different catchments of a burnt area, after a catastrophic fire near Schinos (Attica, Greece) in 2021. Then, it uses field observations from the area, recording mass movement phenomena after high-intensity rainfall events, to validate the results. The findings show that the model is successful in determining the probability of debris flow generation in the 21 basins of the study area, ranging from 0.05 to 0.893. The probability values show a statistically significant correlation (sig. = 0.001) with the actual debris flow occurrences in the area, and satisfactory results in terms of the model’s predictive ability, functioning well within the particular geo-environmental characteristics of the Mediterranean environment. The results establish the reliability of the approach as a tool to assess mass movement risks in a region with an abundance of post-fire related hazards and disastrous events.

A critical evaluation of anthropological, biochemical, and geo-climatic factors related to chronic kidney disease with unknown etiology in Sri Lanka

Background: Chronic kidney disease of unknown etiology (CKDu) is a critical health issue among farming communities of the dry zone in Sri Lanka. Aims and Objectives: This study was conducted to identify the possible anthropological, biochemical, and geo-environmental characteristics of CKDu, comparing an affected and nonaffected community. Materials and Methods: Serum creatinine (SC) levels were measured and estimated glomerular filtration rate values were calculated in both communities based on a stratified sampling method. Anthropological data, such as population structure, farming behavior, and poverty statistics, were obtained from the respective government officials. Geo-climatic data including elevation, monthly average temperature, rainfall, humidity, ultraviolet intensity, and sunshine hours were obtained for study areas. Results: The most striking difference between the two communities is significantly high SC in male individuals between the age categories of 40–60 in the CKDu endemic area in comparison to nonendemic participants in the same age category from the nonendemic area. Conclusion: Significant differences were observed in migration, drinking water sources, and hot humid environment between the two studied regions.

Assessment of flood susceptibility prediction based on optimized tree-based machine learning models

Abstract Due to the physical processes of floods, the use of data-driven machine learning (ML) models is a cost-efficient approach to flood modeling. The innovation of the current study revolves around the development of tree-based ML models, including Rotation Forest (ROF), Alternating Decision Tree (ADTree), and Random Forest (RF) via binary particle swarm optimization (BPSO), to estimate flood susceptibility in the Maneh and Samalqan watershed, Iran. Therefore, to implement the models, 370 flood-prone locations in the case study were identified (2016–2019). In addition, 20 hydrogeological, topographical, geological, and environmental criteria affecting flood occurrence in the study area were extracted to predict flood susceptibility. The area under the curve (AUC) and a variety of other statistical indicators were used to evaluate the performances of the models. The results showed that the RF-BPSO (AUC=0.935) has the highest accuracy compared to ROF-BPSO (AUC=0.904), and ADTree-BPSO (AUC=0.923). In addition, the findings illustrated that the chance of flooding in the center of the area in question is greater than in other points due to lower elevation, lower slope, and proximity to rivers. Therefore, the ensemble framework proposed here can also be used to predict flood susceptibility maps in other regions with similar geo-environmental characteristics for flood management and prevention.

MO388: A Critical Evaluation of Anthropological, Biological and Geo-Environmental Factors on Chronic Kidney Disease of unknown Aetiology in Affected Area Against Unaffected Area

Abstract BACKGROUND AND AIMS Chronic kidney disease of unknown etiology (CKDu) has been a critical health issue among the farming communities of Sri Lanka for decades [1]. However, the distribution of CKDu in Sri Lanka is geographically significant by representing endemicity on its own [2]. This study was conducted to identify the anthropological and geo-environmental characteristics of CKDu, in relation to the biochemical profile between known CKDu endemic and non-endemic communities. METHOD A total of 214 male individuals from Wilgamuwa (endemic) and 102 male individuals from Mathurata (non-endemic) of 30–60 years were recruited. For each participant, blood pressure (BP), random blood sugar (RBS), serum creatinine (μmol/L) and serum cholesterol (mg/dL) were tested using standard methods. Anthropological data including population structure, farming behaviour and poverty statistics were obtained from the respective government officials. Geo climatic data including elevation, monthly average (Avg.) temperature (°C), monthly Avg. rainfall (mm), monthly Avg. humidity (%) and monthly Avg. UV intensity, monthly Avg. Sun hours (hrs.) were obtained for the two study areas. RESULTS Most striking difference between two communities is significantly high serum creatinine (t = 3.5175, P = 0.0005) in male individuals between the age category of 40 to 65 years in CKDu endemic area (M = 109.00, SD = 66.41) in comparison to non-endemic participants in the same age category from non-endemic area for CKDu (M = 85.41, SD = 18.78). The non-endemic area for CKDu, Maturata was colonized since the 16th century due to natural population migrations while the colonization of Wilgamuwa was implemented in a more drastic manner, parallel to the green revolution after the 1960s. Mathurata is located at a high elevation level of 976 m, whereas Wilgamuwa is located at an elevation level of 528 m. In comparison with meteorological variables for the year of 2019, monthly Avg. rainfall (mm) (P = 0.005), monthly Avg. temperature (°C) (P = 0.001), monthly Avg. cloud cover (%) (P = 0.004), monthly Avg. Humidity (%) (P = 0.007), monthly Avg. Sun hours (hrs) (P = 0.001) were highly significant between the two geographical areas. CONCLUSION We report comparably adverse weather conditions, higher exposure to natural and artificial toxic exposure in genetically and behaviourally vulnerable group in the CKDu endemic area in comparison with non-endemic area for CKDu.

A GEO-ENVIRONMENTAL STUDY ON CULTIVATION, PRODUCTION AND MARKETING OF BANANA IN GOALPARA DISTRICT OF ASSAM, INDIA

Goalpara district covering an area of 1,824sq.km.in the western part of south bank of the Brahmaputra in Assam extends between 25o 54/N to 26o 17/N latitude and 90o3/E to 91o6/E longitude. The district along with its surrounding areas basically the south central parts are very suitable for the cultivation of banana one of the important fruit crop of the district. The district is not only rich in the cultivation and production of banana but also it has some big collecting centers mainly at Daranggiri, Dhupdhara, Rongjuli, Dudhnoi, etc. The century-old Daranggiri banana market in Goalpara district has now reached the peak of selling with rank first as the largest banana market in Asia. Bananas from Daraggiri are being supplied to Bangladesh, Nepal, Bhutan, Bihar, West Bengal, Uttar Pradesh, and many other places of India and abroad. The present paper is a modest attempt to analyse the geo-environmental characteristics of Cultivation, Production and Marketing of Banana in Goalpara District of Assam.

Microstructural Evaluation of the Effect of Initial pH on Geotechnical and Geoenvironmental Characteristics of Marl Soils

Microstructural Evaluation of the Effect of Initial pH on Geotechnical and Geoenvironmental Characteristics of Marl Soils

Effects of lead contaminants on engineering properties of Iranian marl soil from the microstructural perspective

Most of the industries in the south of Iran and north of the Persian Gulf are built on marl bedrocks and these industries are major sources of heavy metal pollutants. Therefore, the engineering properties of marl soils contaminated with heavy metals (particularly lead ions) are worthy of thorough investigation. This was accomplished by artificial contamination of marl soil with varying lead concentrations and measurment of some geotechnical (granularity, Atterberg limits, compressive strength, and permeability) and geo-environmental (CEC, pH, and contaminant retention) characteristics. In addition, with the aid of X-ray diffraction (XRD) patterns and scanning electron microscopy (SEM) images the changes in mineralogy and microstructural behavior of lead-contaminated soil were investigated. According to the findings of the present study, marl soil can hold about 200 cmol/kg-soil of lead concentration. As seen by SEM images, the lead precipitation changed the soil's geotechnical properties by altering the structure and texture of soil (notably flocculation). At 100 cmol/kg-soil lead concentration, the compressive strength was reduced by about 85%, while the hydraulic conductivity increased up to 170 times. Adding lead to the marl soil decreased the intensity of X-ray diffraction peaks for the main clay minerals and created new peaks associated with precipitated cerussite, shannonite, and leadhillite.

Bone histology of human remains from the Late Holocene of Northwestern Patagonia, Argentina: a multidimensional taphonomic approach

This study presents the first histological results on human remains recovered from Late Holocene archaeological sites from Northwestern Patagonia, Argentina, from a multidimensional taphonomic perspective. The burial sites come from different geoenvironmental contexts. The main purpose of this work is to assess the influence of geoenvironmental factors on taphonomic history of human bones. The bone microstructure of eleven human femora was analyzed through thin sections and four of them also with scanning electron microscopy. The relationship of these parameters with a set of geoenvironmental variables was assessed by means of different uni-, bi-, and multivariate statistical analysis. Results indicate that the geoenvironmental contexts led to different preservation of the microstructure of skeletal remains, represented by two different patterns. Bones with the best histological preservation were associated with semi-arid to arid geoenvironmental characteristics and the worst preserved ones with subhumid to humid features. Interestingly, samples from the better-preserved pattern showed staining and microcracks, whereas bioerosion is associated with the poorly preserved ones. A weak incidence of sex and chronology was found on microstructure preservation. Finally, the effects of weathering on naturally unearthed bones were deeply destructive in a short period of time. This work highlights the power of a multidisciplinary approach to discern the taphonomical pathways in archaeological sites.

A Geotechnical Investigation of 2017 Chattogram Landslides

In this study, an attempt is made to uncover and discuss the geo-environmental characteristics, triggers, and consequences of a landslide disaster in the Chattogram Hill Tracts (CHT) region of Bangladesh. The hilly areas are composed of Tertiary and Quaternary sediments which have been folded, faulted, uplifted and, then deeply dissected by rivers and other water bodies. This paper presents a case study on the geotechnical investigation and numerical modeling of the landslides of 13 June 2017. A field visit and soil sample collection, followed by laboratory testing were conducted at the landslide-afflicted areas. The study revealed that the soil type was an important factor behind landslides, while high precipitation, hill cutting, deforestation, and unplanned human settlements act as contributing factors behind the landslide disaster. Extensive analysis of the geotechnical facts has been carried out, and an attempt is made to pinpoint the cause. A finite element modeling was conducted using PLAXIS 2D to investigate the failure mechanism. The numerical modeling results have suggested that most of the hill slopes were susceptible to failure after heavy rainfall. A conclusion is drawn that the landslides were triggered by incessant rainfall infiltrating into the subsoil, which led to a notable increase in its degree of saturation and a simultaneous reduction in suction and shear strength of the soil.

Experimental investigation of correlations between electrical resistivity, moisture content and voltage values for leachate contaminated clayey sand

Leachate leakage from landfill sites has become a significant environmental problem in recent years, polluting soil layers and groundwater aquifers. A considerable number of dumpsites near cities are operated traditionally and are not designed as landfills, which increases the risk of leakage. Leachate leakage also changes geotechnical and geo-environmental characteristics of soil, often increases soil permeability. Geo-electrical methods are one of the most common methods in leachate leakage investigation in recent years, which are considered as non-destructive methods. Despite recent studies, there are still challenges in applying geo-electrical methods to study leachate leaking from landfill sites that can be addressed through small-scale laboratory studies. One of the critical parameters in the laboratory study of soil resistivity is the voltage of current injected into the soil sample. In this research, the effect of voltage changes applied to the soil samples contaminated by solutions with different contaminant concentrations was investigated. Also, the relation between soil moisture content and resistivity was studied. It was found that there was a sudden change in the reduction rate of soil resistivity for moisture content larger than 13%, which is equal to soil plastic limit. The results showed that by increasing the voltage injected into the soil sample, fluctuation of resistivity values decreased and the transparency of the results increased.

Sustainable stabilization/solidification of arsenic-containing soil by blast slag and cement blends

Arsenic (As) is a naturally occurring trace element that may pose a threat to human health and the ecosystem, while effective remediation and sustainable reuse of As-containing soil is a challenge. This study investigated the geoenvironmental characteristics of a geogenic As-rich soil, and green binders (ground granulated blast slag (GGBS) and cement blends) were employed for the stabilization/solidification (S/S) of the soil under field-relevant conditions. Results indicate that the use of 10% binder could effectively immobilize As and chemical stabilization/physical encapsulation jointly determined the leaching characteristics of the S/S soils. The geogenic As could be effectively immobilized at the pH range of 5.5–6.5. The increasing use of GGBS enhanced the strength of the 28-d cured S/S soils because of long-term pozzolanic reaction, but also slightly improved the As leachability. Besides, the moisture content of the contaminated soils should be suitably adjusted to allow for desirable compaction of S/S soils, which resulted in high compressive strength and low of As leachability. Results show that soil moisture content of 20% was the most appropriate, which resulted in the highest strength and relatively lower As leaching. In summary, this study presents a sustainable S/S binder for recycling As-contaminated soil by using a combination of cement and GGBS.

Gestão territorial e zoneamento ambiental na Bacia Hidrográfica do Rio Coruripe-AL: embates territoriais e perspectivas geográficas

RESUMO: O presente artigo resulta de um recorte da dissertação de mestrado defendida em março de 2020 no Programa em Dinâmicas Territoriais e Cultura (PRODIC) da Universidade Estadual de Alagoas-Uneal, o qual tem como objeto de estudo a Bacia Hidrográfica do Rio Coruripe-AL. O Zoneamento ambiental apresenta-se em detrimento do uso e ocupação do solo, calcado na apropriação de recursos naturais numa bacia hidrográfica, enquanto fator de análise e instrumento de gestão territorial no contexto das características geoambientais de uma bacia hidrográfica possui, com vistas a sistematizar as principais atividades desenvolvidas no campo socioambiental, potencializando o desenvolvimento socioeconômico, com enfoque no planejamento e gestão territorial. Tal estudo propõe um zoneamento ecológico-econômico (ZEE), embutido na acepção do decreto 4.297/2002 à luz dos direitos humanos e ambientais, com base em instrumentos adotados na caracterização da Bacia Hidrográfica do Rio Coruripe (BHRC) em Alagoas, os quais baseam-se em percepções geográficas dos recursos naturais existentes .Para tanto, o estudo teve como parâmetro metodológico e de conceitos abordados, trabalhos realizados sobre Bacias Hidrográficas, a exemplo de: Carvalho (2006), Cunico (2007), Pereira (2010), Lopes (2013), Peres (2016), Santos (2018), Jacó (2019), entre outros. Para a identificação dos impactos socioambientais, foram utilizados inicialmente imagens obtidas via satélite em sites à confecção de mapas elaborados pelo softaware Qgis, no qual o uso e ocupação do solo é enfatizado na BHRC, trazendo áreas de destaques provenientes de antropização por parte do uso das terras. A Bacia do Rio Coruripe, por sua vez, apresenta uma variação de cultivos, distribuídos nos mais de 19 municípios por onde se estendem seus leitos e margens. Para tal análise do mau uso das terras foram analisados os elementos naturais:geolologia e geomorfologia. Essas influenciadas, consubstancialmente, pela topografia e por fatores de ordem geoclimática e antrópica. Os principais problemas de impactos socioambientais, decorrem necessariamente da emissão de: resíduos sólidos, de esgoto in natura jogados ao rio e aos afluentes, das pastagens na criação do gado e do pisoteio em áreas próximas às nascentes, culturas em uso das águas do rio, do assoreamento dos mananciais, tudo isso indicando a vulnerabilidade socioambiental da BHRC.&#x0D; PALAVRAS-CHAVE: eutrofização, vulnerabilidade socioambiental, reflorestamento.

Scrutinizing Relationships between Submarine Groundwater Discharge and Upstream Areas Using Thermal Remote Sensing: A Case Study in the Northern Persian Gulf

Nutrient input through submarine groundwater discharge (SGD) often plays a significant role in primary productivity and nutrient cycling in the coastal areas. Understanding relationships between SGD and topo-hydrological and geo-environmental characteristics of upstream zones is essential for sustainable development in these areas. However, these important relationships have not yet been completely explored using data-mining approaches, especially in arid and semi-arid coastal lands. Here, Landsat 8 thermal sensor data were used to identify potential sites of SGD at a regional scale. Relationships between the remotely-sensed sea surface temperature (SST) patterns and geo-environmental variables of upland watersheds were analyzed using logistic regression model for the first time. The accuracy of the predictions was evaluated using the area under the receiver operating characteristic curve (AUC-ROC) metric. A highly accurate model, with the AUC-ROC of 96.6%, was generated. Moreover, the results indicated that the percentage of karstic lithological formation and topographic wetness index were key variables influencing SGD phenomenon and spatial distribution in the northern coastal areas of the Persian Gulf. The adopted methodology and applied metrics can be transferred to other coastal regions as a rapid assessment procedure for SGD site detection. Moreover, the results can help planners and decision-makers to develop efficient environmental management strategies and the design of comprehensive sustainable development policies.

Deep learning neural networks for spatially explicit prediction of flash flood probability

Flood probability maps are essential for a range of applications, including land use planning and developing mitigation strategies and early warning systems. This study describes the potential application of two architectures of deep learning neural networks, namely convolutional neural networks (CNN) and recurrent neural networks (RNN), for spatially explicit prediction and mapping of flash flood probability. To develop and validate the predictive models, a geospatial database that contained records for the historical flood events and geo-environmental characteristics of the Golestan Province in northern Iran was constructed. The step-wise weight assessment ratio analysis (SWARA) was employed to investigate the spatial interplay between floods and different influencing factors. The CNN and RNN models were trained using the SWARA weights and validated using the receiver operating characteristics technique. The results showed that the CNN model (AUC = 0.832, RMSE = 0.144) performed slightly better than the RNN model (AUC = 0.814, RMSE = 0.181) in predicting future floods. Further, these models demonstrated an improved prediction of floods compared to previous studies that used different models in the same study area. This study showed that the spatially explicit deep learning neural network models are successful in capturing the heterogeneity of spatial patterns of flood probability in the Golestan Province, and the resulting probability maps can be used for the development of mitigation plans in response to the future floods. The general policy implication of our study suggests that design, implementation, and verification of flood early warning systems should be directed to approximately 40% of the land area characterized by high and very susceptibility to flooding.

Spatial characterization of the targeting’s worst-off au Burkina Faso

Abstract Introduction In 2014, the Government of Burkina Faso received technical and financial support from the World Bank to test the PBF project with various equity measures. Health equity measures included community based selection of worst-off and user fee exemption for them at the point of service. This selection was carried out in 8 health districts. More than 110,000 worst-off have been selected. Several analyses show that their use of care remains low. Our study aims to characterize the selection of the indigent by considering geographical determinants in order to better understand the weakness of access to care. Methods We have mapped the selection of the indigent based on the geolocation data collected with a GIS. We carried out spatial analyses to measure access to localities, health center and the main access roads. We have also integrated population data and geo-environmental characteristics. All these data were aggregated in 500 m cells to provide all variables on a single scale. A total of 9 variables were generated to characterize the spatial targeting’s worst-of. We combined two cluster analyses, i.e., k-means, and hierarchical clustering. Results We obtain a characterization of the selection into four classes. These classes highlight that the community-based selection of the worst-off is unequal in terms of distances to localities, health centres, and isolation. The results refine our knowledge of geographical accessibility to health centres by illustrating that distances to the health care centre are not the only geographical determinants to be considered. Conclusions This study is a contribution to the analysis of the characterization of the targeting of the worst-off. The results suggest that it is important to strengthen support for the most isolated worst-off for an access care. More broadly, this study shows that it is necessary to integrate the geographical dimension into the definition of targeting the worst-off. Key messages It is necessary to integrate the geographical dimension into the definition of targeting the worst-off. It is important to strengthen support for the most isolated worst-off for an access care.

Flood susceptibility mapping in Dingnan County (China) using adaptive neuro-fuzzy inference system with biogeography based optimization and imperialistic competitive algorithm

Flooding is one of the most significant environmental challenges and can easily cause fatal incidents and economic losses. Flood reduction is costly and time-consuming task; so it is necessary to accurately detect flood susceptible areas. This work presents an effective flood susceptibility mapping framework by involving an adaptive neuro-fuzzy inference system (ANFIS) with two metaheuristic methods of biogeography based optimization (BBO) and imperialistic competitive algorithm (ICA). A total of 13 flood influencing factors, including slope, altitude, aspect, curvature, topographic wetness index, stream power index, sediment transport index, distance to river, landuse, normalized difference vegetation index, lithology, rainfall and soil type, were used in the proposed framework for spatial modeling and Dingnan County in China was selected for the application of the proposed methods due to data availability. There are 115 flood occurrences in the study area which were randomly separated into training (70% of the total) and verification (30%) sets. To perform the proposed framework, the step-wise weight assessment ratio analysis algorithm is first used to evaluate the correlation between influencing factors and floods. Then, two ensemble methods of ANFIS-BBO and ANFIS-ICA are constructed for spatial prediction and producing flood susceptibility maps. Finally, these resultant maps are assessed in terms of several statistical and error measures, including receiver operating characteristic (ROC) curve and area under the ROC curve (AUC), root-mean-square error (RMSE). The experimental results demonstrated that the two ensemble methods were more effective than ANFIS in the study area. For instance, the predictive AUC values of 0.8407, 0.9045 and 0.9044 were achieved by the methods of ANFIS, ANFIS-BBO and ANFIS-ICA, respectively. Moreover, the RMSE values for ANFIS, ANFIS-BBO and ANFIS-ICA using the verification set were 0.3100, 0.2730 and 0.2700, respectively. In addition, as regards ANFIS-BBO and ANFIS-ICA, a total areas of 39.30% and 35.39% were classified as highly susceptible to flooding. Therefore, the proposed ensemble framework can be used for flood susceptibility mapping in other sites with similar geo-environmental characteristics for taking measures to manage and prevent flood damages.

DISCUSSION ON FAILURE MECHANISM FOR COMPLEX MOVEMENT OF SHUIMATUO LANDSLIDE IN GUIZHOU PROVINCE

At the beginning of 2011, affected by multi-periods of heavy rainfall, many geohazards were developed on the accumulated layer slopes in Shuimatuo Town, Sinan County. They include ground surface rupture, wall inclination, deformation aggravation of fissures on ground and walls. Once influenced by the heavy rainfall and other unfavorable factors, the unstable slopes would slide continuously, posing a serious threat to the 509 persons and 556 houses of Datong Community, and a significantly negative impact to the local society. Based on the field survey and indoor analysis, this paper elaborates the geo-environmental characteristics of the Shuimatuo landslide region and clarifies the important effects of geological structures and topographic conditions to the seepage field of the slope. With the help of local meteorological data, we continue to research the deformation and failure process of the slope under the rainfall condition with the SEEP/W module and the FLAC3D software. We preliminarily expound the formation mechanism of the thrust-type landslide(H1) and secondary tractive landslide(H2)triggered by the multi-period of rainfall. The preliminary research results believe that induced by the rare heavy rainfall in the history, the major landslide begins to deform, but limited by the terrain condition, showing characteristics of part and progressive failure. During the long-term creep deformation process of landslide, rainfall causes a fluctuation of the groundwater level, strengthening the creep of sliding mass. Controlled by the free surface condition, the evolutionary process of secondary tractive landslide shows obvious correlation and certain lag comparing to the major landslide. For the thrust-type accumulated layer landslide, affected by the terrain, groundwater and loading conditions, it takes a long time from strength decrease of sliding belt to the formation of sliding plane. While tractive accumulated layer landslide lasts shortly as it is a backward movement generated by slope stress redistribution due to the lack of key anti-slide body.