Identification, prediction, and mitigation of sinkhole hazards in evaporite karst areas

Sinkholes usually have a higher probability of occurrence and a greater genetic diversity in evaporite terrains than in carbonate karst areas. This is because evaporites have a higher solubility and, commonly, a lower mechanical strength. Subsidence damage resulting from evaporite dissolution generates substantial losses throughout the world, but the causes are only well understood in a few areas. To deal with these hazards, a phased approach is needed for sinkhole identification, investigation, prediction, and mitigation. Identification techniques include field surveys and geomorphological mapping combined with accounts from local people and historical sources. Detailed sinkhole maps can be constructed from sequential historical maps, recent topographical maps, and digital elevation models (DEMs) complemented with building-damage surveying, remote sensing, and high-resolution geodetic surveys. On a more detailed level, information from exposed paleosubsidence features (paleokarst), speleological explorations, geophysical investigations, trenching, dating techniques, and boreholes may help in investigating dissolution and subsidence features. Information on the hydrogeological pathways including caves, springs, and swallow holes are particularly important especially when corroborated by tracer tests. These diverse data sources make a valuable database—the karst inventory. From this dataset, sinkhole susceptibility zonations (relative probability) may be produced based on the spatial distribution of the features and good knowledge of the local geology. Sinkhole distribution can be investigated by spatial distribution analysis techniques including studies of preferential elongation, alignment, and nearest neighbor analysis. More objective susceptibility models may be obtained by analyzing the statistical relationships between the known sinkholes and the conditioning factors. Chronological information on sinkhole formation is required to estimate the probability of occurrence of sinkholes (number of sinkholes/km² year). Such spatial and temporal predictions, frequently derived from limited records and based on the assumption that past sinkhole activity may be extrapolated to the future, are non-corroborated hypotheses. Validation methods allow us to assess the predictive capability of the susceptibility maps and to transform them into probability maps. Avoiding the most hazardous areas by preventive planning is the safest strategy for development in sinkhole-prone areas. Corrective measures could be applied to reduce the dissolution activity and subsidence processes. A more practical solution for safe development is to reduce the vulnerability of the structures by using subsidence-proof designs.     

Quantitative sinkhole hazard assessment. A case study from the Ebro Valley evaporite alluvial karst (NE Spain)

Quantitative sinkhole hazard assessments in karst areas allow calculation of the potential sinkhole risk and the performance of cost-benefit analyses. These estimations are of practical interest for planning, engineering, and insurance purposes. The sinkhole hazard assessments should include two components: the probability of occurrence of sinkholes (sinkholes/km² year) and the severity of the sinkholes, which mainly refers to the subsidence mechanisms (progressive passive bending or catastrophic collapse) and the size of the sinkholes at the time of formation; a critical engineering design parameter. This requires the compilation of an exhaustive database on recent sinkholes, including information on the: (1) location, (2) chronology (precise date or age range), (3) size, and (4) subsidence mechanisms and rate. This work presents a hazard assessment from an alluvial evaporite karst area (0.81 km²) located in the periphery of the city of Zaragoza (Ebro River valley, NE Spain). Five sinkholes and four locations with features attributable to karstic subsidence where identified in an initial investigation phase providing a preliminary probability of occurrence of 0.14 sinkholes/km² year (11.34% in annual probability). A trenching program conducted in a subsequent investigation phase allowed us to rule out the four probable sinkholes, reducing the probability of occurrence to 0.079 sinkholes/km² year (6.4% in annual probability). The information on the severity indicates that collapse sinkholes 10–15 m in diameter may occur in the area. A detailed study of the deposits and deformational structures exposed by trenching in one of the sinkholes allowed us to infer a modern collapse sinkhole approximately 12 m in diameter and with a vertical throw of 8 m. This collapse structure is superimposed on a subsidence sinkhole around 80 m across that records at least 1.7 m of synsedimentary subsidence. Trenching, in combination with dating techniques, is proposed as a useful methodology to elucidate the origin of depressions with uncertain diagnosis and to gather practical information with predictive utility about particular sinkholes in alluvial karst settings: precise location, subsidence mechanisms and magnitude, and timing and rate of the subsidence episodes.     

Karst database implementation in Minnesota: analysis of sinkhole distribution

This paper presents the overall sinkhole distributions and conducts hypothesis tests of sinkhole distributions and sinkhole formation using data stored in the Karst Feature Database (KFD) of Minnesota. Nearest neighbor analysis (NNA) was extended to include different orders of NNA, different scales of concentrated zones of sinkholes, and directions to the nearest sinkholes. The statistical results, along with the sinkhole density distribution, indicate that sinkholes tend to form in highly concentrated zones instead of scattered individuals. The pattern changes from clustered to random to regular as the scale of the analysis decreases from 10–100 km² to 5–30 km² to 2–10 km². Hypotheses that may explain this phenomenon are: (1) areas in the highly concentrated zones of sinkholes have similar geologic and topographical settings that favor sinkhole formation; (2) existing sinkholes change the hydraulic gradient in the surrounding area and increase the solution and erosional processes that eventually form more new sinkholes.     

Subsidence hazard avoidance based on geomorphological mapping in the Ebro River valley mantled evaporite karst terrain (NE Spain)

In the valley of the Ebro River to the southeast of the city of Zaragoza (NE Spain), the dissolution of evaporite sediments (gypsum, halite and Na-sulphates) which underlie alluvial deposits gives rise to numerous sinkholes. These sinkholes are a potential hazard to human safety, particularly where they develop in a catastrophic way. Even slow-developing sinkholes are problematic, as they damage urban and agricultural infrastructure, necessitating costly repairs and vigilant maintenance. To assist in developing avoidance strategies for these hazards, the factors controlling sinkhole occurrence have been assessed using geomorphological maps produced from aerial photographs for 1956 and 1981. Important controls on sinkhole development are found to include underlying geological structure (manifest in preferred orientations of sinkholes on the azimuths N130-150E and N30-40E), and the presence of glauberite in the groundwater flow path, which apparently promotes accelerated gypsum dissolution. Perhaps surprisingly, alluvium thickness does not appear to significantly correlate with the density of sinkholes on the floodplain in this area. The maps for 1956 and 1981 reveal that both human activity and natural processes can serve to obscure the true density of sinkhole development. For instance, a large number of sinkholes which were conspicuous in 1956 have since been back-filled by farmers. In the most fluvially active zone of the Ebro valley (the meander belt), the relatively low density of sinkholes compared with adjoining zones suggests that subsidence is being masked by morpho-sedimentary dynamic processes (aggradation and erosion). Careful geomorphological mapping for different time periods yields a much more accurate impression of the frequency of sinkhole development than would be gained from surveying currently visible sinkholes in the area of interest.     

Morphometric analysis of sinkholes in a karst coastal area of southern Apulia (Italy)

Salento, the southern portion of Apulia region (SE Italy), is a narrow and elongated peninsula in carbonate rocks, with prevailing low coastlines, locally interrupted by high rock cliffs. The long stretches of low coasts are marked by typical karst landforms consisting of collapse sinkholes. As observed in many other karst coastal settings worldwide, development of sinkholes may be particularly severe along the coasts, where both natural and anthropogenic processes contribute to accelerate the dissolution of carbonate rocks and subsidence processes, even influencing the coastline evolution. Following a previous study, where the main features of sinkholes at Torre Castiglione (Taranto province) were investigated and described, and a preliminary susceptibility map produced, at the light of updated data and elaborations in the present paper we perform a detailed morphometric analysis on the sample of identified sinkholes. The main morphometric parameters generally used for sinkhole characterization have been considered in this study: shape of the sinkhole, azimuth and length of maximum and minimum axes, depth, elongation ratio, and distance from the shorelines. Each of them is described, both as individual parameter and in conjunction with the others, in the attempt to identify the main factors controlling development of sinkholes in the area, and their evolution as well. With regard to this latter aspect, beside simple morphometry of the sample of sinkholes at Torre Castiglione, we also focused our attention on the likely relationships existing between distribution and shape of the sinkholes and the tectonic discontinuities. To investigate the matter, a three-stage analysis has been carried out in this study by means of: field measurements of the fractures bounding the sinkholes, field measurement of the long axes azimuth of the elongated sinkholes, comparison of the previously described sets with the strikes of the main regional geological structures. The obtained results show, in addition to the coincidence of the main regional discontinuity systems with the major axis of elongated sinkholes, a clear control exerted by development and evolution of the sinkholes on the formation of coastal inlets and bays. Eventually, the approach here presented may be applied in other karst coastal sinkhole-prone areas, to gain new knowledge on the genesis and evolution of coastal sinkholes, and to properly evaluate the hazard they pose to the anthropogenic environment.     

Validation and evaluation of two multivariate statistical models for predictive shallow landslide susceptibility mapping of the Eastern Pyrenees (Spain)

This paper deals with the quality of two multivariate statistical models based on the Geographical Information System for shallow landslide susceptibility assessment in a test area at La Pobla de Lillet (Eastern Pyrenees, Spain). The quality, which was guaranteed by a rigorous methodology based on a suitable diagnosis, validation, and evaluation of the models, ensured a reliable contrast of the final susceptibility maps. This enables us to transfer the best results to the end user. Landslide susceptibility models were carried out by logistic regression and discriminant analysis of the significant conditioning factors related to the characteristics of the slope and the upslope contributing area captured from the digital elevation model and landslide distribution. The explanatory variables were tested (KS test, principal components and one-way and T-test) to select the most statistically significant ones before being introduced into the logistic and discriminant analyses. Accuracy statistics and the receiver operating characteristic curve used for diagnosis and validation showed similar prediction skills and a good fit to the data with more than 85% of unfailed cells properly classified for the two models. The evaluation of the study area and the correlation function (R ² = 0.83) between the models revealed that the discriminant model overestimated the susceptibility of the most stable zones with respect to the logistic model. Different methods of producing susceptibility maps showed marked differences in matching the models. Substantial spatial agreement (Kappa = 0.741) between binary maps produced by the standard cut-off value descended moderately (Kappa = 0.540) as a result of superimposing maps with five susceptibility levels defined by landslide percentage. Despite the fact that the two statistical models are similar in assessing susceptibility in the study area, the implications for hazard and risk management can be different because of the conservative nature of the discriminant model.     

Geophysical prediction and following development sinkholes in two Dead Sea areas, Israel and Jordan

Geophysical methods—seismic refraction (SRFR), electrical resistivity tomography (ERT), and microgravity—were applied to the Dead Sea (DS) sinkhole problem in the Ein Gedi area at the earlier stage of the sinkhole development (1998–2002). They allowed determining the sinkhole formation mechanism and localizing the sinkhole hazardous zones. The SRFR method permitted to delineate the underground edge of a salt layer at the depth of 50 m. The salt edge was shaped like the sinkhole line on the surface. It was concluded that the sinkhole development is linked to the salt edge. Geoelectrical quasi-3D mapping based on the ERT technique detected large resistivity anomalies with 250–300 m² diameter and 25–35 m deep. The Ein Gedi area has been also mapped by the use of Microgravity method. The residual Bouguer gravity anomaly map shows negative anomalies arranged along the edge of the salt layer. Those gravity anomalies overall are very similar in plan to the resistivity distribution in this area. The results of forward modeling indicate that both high resistivity and residual gravity anomalies are associated with a subsurface decompaction of the soil mass and deep cavity at the sinkhole site. Following monitoring of the sinkhole development carried out by the Geological Survey of Israel confirmed our suggestions. The drilling of numerous boreholes verified the location of the salt edge. Geographical Information System (GIS) database testifies that during 2003–2009 new sinkholes are continuing to develop along the salt edge within a narrow 50–100 m wide strip oriented approximately in north–south direction (slightly parallel to the shoreline). No promotion in west–east direction (perpendicularly to the DS shoreline) was observed in Israel. Collapse of sinkholes and their clustering have been occurred within the area of high resistivity anomaly and negative residual gravity anomaly. Similar studies carried out at the Ghor Al-Haditha area (Jordan) have shown that sinkholes there are also arranged along the winding line conforming to the salt edge. In this area sinkholes are slowly moved to the Dead Sea direction. Results of geophysical studies in numerous DS sites indicate similar sinkhole development. It allowed generating of the sinkhole formation model based on ancient (10,000–11,000-year old) salt belt girding the Dead Sea along its shores     

Application of matrix analysis in delineating sinkhole risk areas along highway (I-70 near Frederick,Maryland)

Sinkhole collapse in the area of Maryland Interstate 70 (I-70) and nearby roadways south of Frederick, Maryland, has been posing a threat to the safety of the highway operation as well as other structures. The occurrence of sinkholes is associated with intensive land development. However, the geological conditions that have been developing over the past 200 million years in the Frederick Valley control the locations of the sinkholes. Within an area of approximately 8 km², 138 sinkholes are recorded and their spatial distribution is irregular, but clustered. The clustering indicates the existence of an interaction between the sinkholes. The point pattern of sinkholes is considered to be a sample of a Gibbsian point process from which the hard-core Strauss Model is developed. The radius of influence is calculated for the recorded sinkholes which are most likely to occur within 30 m of an existing sinkhole. The stochastic analysis of the existing sinkholes is biased toward the areas with intensive land use. This bias is adjusted by considering (1) topography, (2) proximity to topographic depressions, (3) interpreted rock formation, (4) soil type, (5) geophysical anomalies, (6) proximity to geologic structures, and (7) thickness of overburden. Based on the properties of each factor, a scoring system is developed and the average relative risk score for individual 30-m segments of the study area is calculated. The areas designated by higher risk levels would have greater risk of a sinkhole collapse than the areas designated by lower risk levels. This risk assessment approach can be updated as more information becomes available.     

Evaluation of susceptibility for terrain collapse and subsidence in karst areas,municipality of Iraquara,Chapada Diamantina (BA), Brazil

The morphological evolution of the karstic systems is associated with a set of physical and chemical processes, triggered by the dissolution of the rocks, related to percolation of groundwater and surface water, which consequently open underground voids and carve out peculiar forms of relief. Due to environmental and geotechnical aspects, this system is naturally more fragile and vulnerable than other natural systems and, therefore, has increasingly received the attention of the scientific community over the past decades. The objective of the study was to delimit zones with varying degrees of susceptibility for collapses and subsidence of sinkholes in the municipality of Iraquara, Chapada Diamantina (BA), Brazil, and to understand their geological and morphological determinant factors. Geological data, karst phenomenon map, and visual analysis in the field were used to categorize zones with different types of susceptibilities to the nucleation of new sinkholes based on a Hazard Index. This index was defined from the sum of geological hazard factors, lineament density, and sinkhole density. The areas that presented the highest susceptibility for terrain collapse and subsidence corresponded to regions where carbonate rocks outcrop, with high density of photolineaments and 2.62 sinkholes/km². Processes associated with terrain collapse and subsidence in karst areas consisted of a combination of various factors, hindering precise predictions. However, zones of different types of susceptibilities to terrain collapse and subsidence can be delimited when the relationships between these processes and their factors are understood. The Hazard Index proposed does not provide quantitative values for the probability of hazard susceptibility, but rather indicates areas that are more susceptible to terrain subsidence and collapse.     

Mapping the susceptibility to sinkholes in coastal areas, based on stratigraphy, geomorphology and geophysics

Sinkholes and land subsidence are among the main coastal geologic hazards. Their occurrence poses a serious threat to the man-made environment, due to the increasing density of population, pipelines and other infrastructures along the coasts, and to the catastrophic nature of the phenomena, which generally occur without any premonitory signs. To assess the potential danger from sinkholes along the coast, it is important to identify and monitor the main factors contributing to the process. This article reports a methodology based on sequential stratigraphic, hydrogeological and geophysical investigations to draw up a susceptibility map of sinkholes in coastal areas. The town of Casalabate situated in the Apulia region (southern Italy), affected by a long history of sinkhole phenomena, is here presented as an example. The approach proposed is based on sequential stratigraphical, geomorphological and geophysical surveys to identify the mechanisms of sinkhole formation and to provide a zonation of the areas in which further sinkhole phenomena may likely occur. Interpretation of the ground penetration radar and electrical tomography profiles has enabled us to identify the potentially most unstable sectors, significantly improving the assessment of the sinkhole susceptibility in the area. The proposed methodology is suitable to be exported in other coastal areas where limestone bedrock is not directly exposed at the surface, but covered by a variable thickness of recent deposits.     

Management and mitigation of sinkholes on karst lands: an overview of practical applications

When karst lands are developed for residential or commercial purposes, sinkholes are to be properly managed or mitigated. This paper discusses various types of sinkholes and their possible formation mechanisms, presents some guidelines for sinkhole management, and summarizes several engineering measures for sinkhole remediation. Because a sinkhole is often not an isolated feature but a component of an integrated groundwater and surface water system, knowledge of the sinkhole geology and hydrology is essential in selection of the proper management tools and remediation options. Adverse effects including flooding, additional sinkholes, and groundwater contamination can result from poorly managed or improperly repaired sinkholes.     

A GIS-based approach for gully erosion susceptibility modelling: a test in Sicily, Italy

The aim of this study is to analyze the susceptibility conditions to gully erosion phenomena in the Magazzolo River basin and to test a method that allows for driving the factors selection. The study area is one of the largest (225 km²) watershed of southern Sicily and it is mostly characterized by gentle slopes carved into clayey and evaporitic sediments, except for the northern sector where carbonatic rocks give rise to steep slopes. In order to obtain a quantitative evaluation of gully erosion susceptibility, statistical relationships between the spatial distributions of gullies affecting the area and a set of twelve environmental variables were analyzed. Stereoscopic analysis of aerial photographs dated 2000, and field surveys carried out in 2006, allowed us to map about a thousand landforms produced by linear water erosion processes, classifiable as ephemeral and permanent gullies. The linear density of the gullies, computed on each of the factors classes, was assumed as the function expressing the susceptibility level of the latter. A 40-m digital elevation model (DEM) prepared from 1:10,000-scale topographic maps was used to compute the values of nine topographic attributes (primary: slope, aspect, plan curvature, profile curvature, general curvature, tangential curvature; secondary: stream power index; topographic wetness index; LS-USLE factor); from available thematic maps and field checks three other physical attributes (lithology, soil texture, land use) were derived. For each of these variables, a 40-m grid layer was generated, reclassifying the topographic variables according to their standard deviation values. In order to evaluate the controlling role of the selected predictive variables, one-variable susceptibility models, based on the spatial relationships between each single factor and gullies, were produced and submitted to a validation procedure. The latter was carried out by evaluating the predictive performance of models trained on one half of the landform archive and tested on the other. Large differences of accuracy were verified by computing geometric indexes of the validation curves (prediction and success rate curves; ROC curves) drawn for each one-variable model; in particular, soil texture, general curvature and aspect demonstrated a weak or a null influence on the spatial distribution of gullies within the studied area, while, on the contrary, tangential curvature, stream power index and plan curvature showed high predictive skills. Hence, predictive models were produced on a multi-variable basis, by variously combining the one-variable models. The validation of the multi-variables models, which generally indicated quite satisfactory results, were used as a sensitivity analysis tool to evaluate differences in the prediction results produced by changing the set of combined physical attributes. The sensitivity analysis pointed out that by increasing the number of combined environmental variables, an improvement of the susceptibility assessment is produced; this is true with the exception of adding to the multi-variables models a variable, as slope aspect, not correlated to the target variable. The addition of this attribute produces effects on the validation curves that are not distinguishable from noise and, as a consequence, the slope aspect was excluded from the final multi-variables model used to draw the gully erosion susceptibility map of the Magazzolo River basin. In conclusion, the research showed that the validation of one-variable models can be used as a tool for selecting factors to be combined to prepare the best performing multi-variables gully erosion susceptibility model.     

Relations between sinkhole density and anthropogenic contaminants in selected carbonate aquifers in the eastern United States

The relation between sinkhole density and water quality was investigated in seven selected carbonate aquifers in the eastern United States. Sinkhole density for these aquifers was grouped into high (>25 sinkholes/100 km²), medium (1–25 sinkholes/100 km²), or low (<1 sinkhole/100 km²) categories using a geographical information system that included four independent databases covering parts of Alabama, Florida, Missouri, Pennsylvania, and Tennessee. Field measurements and concentrations of major ions, nitrate, and selected pesticides in samples from 451 wells and 70 springs were included in the water-quality database. Data were collected as a part of the US Geological Survey (USGS) National Water-Quality Assessment (NAWQA) Program. Areas with high and medium sinkhole density had the greatest well depths and depths to water, the lowest concentrations of total dissolved solids and bicarbonate, the highest concentrations of dissolved oxygen, and the lowest partial pressure of CO₂ compared to areas with low sinkhole density. These chemical indicators are consistent conceptually with a conduit-flow-dominated system in areas with a high density of sinkholes and a diffuse-flow-dominated system in areas with a low density of sinkholes. Higher cave density and spring discharge in Pennsylvania also support the concept that the high sinkhole density areas are dominated by conduit-flow systems. Concentrations of nitrate-N were significantly higher (p < 0.05) in areas with high and medium sinkhole density than in low sinkhole-density areas; when accounting for the variations in land use near the sampling sites, the high sinkhole-density area still had higher concentrations of nitrate-N than the low sinkhole-density area. Detection frequencies of atrazine, simazine, metolachlor, prometon, and the atrazine degradate deethylatrazine indicated a pattern similar to nitrate; highest pesticide detections were associated with high sinkhole-density areas. These patterns generally persisted when analyzing the detection frequency by land-use groups, particularly for agricultural land-use areas where pesticide use would be expected to be higher and more uniform areally compared to urban and forested areas. Although areas with agricultural land use and a high sinkhole density were most vulnerable (median nitrate-N concentration was 3.7 mg/L, 11% of samples exceeded 10 mg/L, and had the highest frequencies of pesticide detection), areas with agricultural land use and low sinkhole density still were vulnerable to contamination (median nitrate-N concentration was 1.5 mg/L, 8% of samples exceeded 10 mg/L, and had some of the highest frequencies of detections of pesticides). This may be due in part to incomplete or missing data regarding karst features (such as buried sinkholes, low-permeability material in bottom of sinkholes) that do not show up at the scales used for regional mapping and to inconsistent methods among states in karst feature delineation.     

Formation mechanism of large sinkhole collapses in Laibin,Guangxi, China

On June 3, 2010, a series of karst sinkholes occurred at Jili village surrounded by Gui-Bei highway, Wu-Ping highway and Nan-Liu High-Speed Railway in Laibin, Guangxi, China. The straight-line distances from an large sinkhole pit, 85 m in diameter and 38 m in depth, to the above mainlines are 200, 600 and 500 m, respectively. Several investigation methods including geophysical technology, borehole and well drilling, groundwater elevation survey and hydrochemistry analysis of groundwater were used to study the formation mechanisms of these sinkholes. Based on the results, the spatial distribution of the Jili underground river was confirmed with a strike of SN along the middle Carboniferous limestone bedrock and the Quaternary deposits controlled the sinkhole formation. In addition, both historical sinkhole events and analysis of the groundwater–air pressure monitoring data installed in the underlying karst conduit system indicate that sinkholes in this area are more likely induced by extreme weather conditions within typical karst geological settings. Extreme weather conditions in the study area before the sinkhole collapses consisted of a year-long drought followed by continuous precipitation with a daily maximum precipitation of 442 mm between May 31 and June 1, 2010. Typical geological conditions include the Jili underground river overlain by the Quaternary overburden with thick clayey rubble. Especially in the recharge zone of the underground river, a stabilized shallow water table was formed in response to the extreme rainstorm because of the presence of the thick clayey rubble. When the underground conduit was flooded through the cave entrance on the surface, air blasting may have caused the cave roof collapse followed by formation of soil cavities and surface collapses. Borehole monitoring results of the groundwater–air pressure monitoring show that the potential karst sinkhole can pose threats to Shanbei village, the High-Speed Railway and the Wu-Ping highway. Local government needs to be aware of any early indicators of this geohazard so that devastating sinkholes can be prevented in the future. The results also suggest that groundwater–air pressure monitoring data collected both the Quaternary deposits and the bedrock karst system provide useful indicators for potential sinkhole collapses in similar karst areas where sinkholes usually occur during rainy season or karst groundwater level is always under the rockhead.     

Landslide susceptibility mapping using a modified decision tree classifier in the Xanthi Perfection,Greece

The objective of this study was to validate the outcomes of a modified decision tree classifier by comparing the produced landslide susceptibility map and the actual landslide occurrence, in an area of intensive landslide manifestation, in Xanthi Perfection, Greece. The values that concerned eight landslide conditioning factors for 163 landslides and 163 non-landslide locations were extracted by using advanced spatial GIS functions. Lithological units, elevation, slope angle, slope aspect, distance from tectonic features, distance from hydrographic network, distance from geological boundaries and distance from road network were among the eight landslide conditioning factors that were included in the landslide database used in the training phase. In the present study, landslide and non-landslide locations were randomly divided into two subsets: 80 % of the data (260 instances) were used for training and 20 % of the data (66 instances) for validating the developed classifier. The outcome of the decision tree classifier was a set of rules that expressed the relationship between landslide conditioning factors and the actual landslide occurrence. The landslide susceptibility belief values were obtained by applying a statistical method, the certainty factor method, and by measuring the belief in each rule that the decision tree classifier produced, transforming the discrete type of result into a continuous value that enabled the generation of a landslide susceptibility belief map. In total, four landslide susceptibility maps were produced using the certainty factor method, the Iterative Dichotomizer version 3 algorithm, the J48 algorithm and the modified Iterative Dichotomizer version 3 model in order to evaluate the performance of the developed classifier. The validation results showed that area under the ROC curves for the models varied from 0.7936 to 0.8397 for success rate curve and 0.7766 to 0.8035 for prediction rate curves, respectively. The success rate and prediction curves showed that the modified Iterative Dichotomizer version 3 model had a slightly higher performance with 0.8397 and 0.8035, respectively. From the outcomes of the study, it was induced that the developed modified decision tree classifier could be efficiently used for landslide susceptibility analysis and in general might be used for classification and estimation purposes in spatial predictive models.     

GIS-based landslide susceptibility mapping with probabilistic likelihood ratio and spatial multi-criteria evaluation models (North of Tehran,Iran)

The aim of this study is to produce landslide susceptibility mapping by probabilistic likelihood ratio (PLR) and spatial multi-criteria evaluation (SMCE) models based on geographic information system (GIS) in the north of Tehran metropolitan, Iran. The landslide locations in the study area were identified by interpretation of aerial photographs, satellite images, and field surveys. In order to generate the necessary factors for the SMCE approach, remote sensing and GIS integrated techniques were applied in the study area. Conditioning factors such as slope degree, slope aspect, altitude, plan curvature, profile curvature, surface area ratio, topographic position index, topographic wetness index, stream power index, slope length, lithology, land use, normalized difference vegetation index, distance from faults, distance from rivers, distance from roads, and drainage density are used for landslide susceptibility mapping. Of 528 landslide locations, 70 % were used in landslide susceptibility mapping, and the remaining 30 % were used for validation of the maps. Using the above conditioning factors, landslide susceptibility was calculated using SMCE and PLR models, and the results were plotted in ILWIS-GIS. Finally, the two landslide susceptibility maps were validated using receiver operating characteristic curves and seed cell area index methods. The validation results showed that area under the curve for SMCE and PLR models is 76.16 and 80.98 %, respectively. The results obtained in this study also showed that the probabilistic likelihood ratio model performed slightly better than the spatial multi-criteria evaluation. These landslide susceptibility maps can be used for preliminary land use planning and hazard mitigation purpose.     

Development and morphometry of sinkholes in coastal plains of Apulia, southern Italy. Preliminary sinkhole susceptibility assessment

Evolution of coastlines in karst areas may be strongly controlled by dissolution processes which favour the development of surface and subsurface landforms. The generation of caves in these environments is commonly favoured by the mixing between fresh and brackish waters. The sinkholes resulting from the upward propagation of the caves may interfere with the anthropogenic environment and cause damage to human elements (property and activities). To highlight the often underestimated importance of karst phenomena in coastal areas, we have analyzed a coastal stretch of Apulia, in southern Italy. The study area, covering an extension of about 6 km², is situated in the Ionian coast, and presents several interesting karst landforms that are generally connected to caves. Tens of sinkholes were mapped through field surveys, multi-year aerial-photographs (dating back to the 1940s) and archival research. We have performed a morphometric analysis of the sinkholes. The analysis describes the main parameters of the sinkholes (area, length, width, and depth), and the control exerted by the main discontinuity systems in the area. The detrimental effects derived from interaction between human environment and these karst landforms is also under consideration. A sinkhole susceptibility map, which may provide useful information for planners, developers and the insurance industry has eventually been produced through application of a decision tree model.     

Sinkhole distribution in a rapidly developing urban environment: Hillsborough County, Tampa Bay area, Florida

Sinkhole formation in Florida is a common event. The Florida karst plain is significantly altered by human development and sinkholes cause considerable property damage throughout much of the state. We present in this paper a morphometric analysis of karst depressions in the Tampa Bay area, and the relation with the known distribution of sinkholes. We selected the Tampa Bay area because it is particularly susceptible to the evolution of karst depressions in relation with development of the built-up environment. Karst depressions were mapped from the 1:24,000 USGS topographic maps and a morphometric analysis was performed by using parameters such as shape, circularity index, perimeter, area, length, width, and orientation. Maps showing the distribution of depression density, and the sectors with greatest areas of karst depression were produced using a GIS. These results were compared with data compiled from the database of sinkhole occurrences in Florida maintained by the Florida Geological Survey. Our analysis demonstrates that the distribution of new sinkhole occurrences differs from the distribution of existing sinkholes, indicating that there are processes acting today that are influencing karst landscape formation that are different from those acting in the past.     

Logistic regression model for sinkhole susceptibility due to damaged sewer pipes

The occurrence of anthropogenic sinkholes in urban areas can lead to severe socioeconomic losses. A damaged underground sewer pipe is regarded as one of the primary causes of such a phenomenon. This study adopted the best subsets regression method to produce a logistic regression model that evaluates the susceptibility for sinkholes induced by damaged sewer pipes. The model was developed by analyzing the sewer pipe network as well as cases of sinkholes in Seoul, South Korea. Among numerous sewer pipe characteristics tested as explanatory variables, the length, age, elevation, burial depth, size, slope, and materials of the sewer pipe were found to influence the occurrence of sinkhole. The proposed model reasonably estimated the sinkhole susceptibility in the area studied, with an area value under the receiver-operating characteristics curve of 0.753. The proposed methodology will serve as a useful tool that can help local governments to choose a cavity inspection regime, and to prevent sinkholes induced by damaged sewer pipes.     

Natural and human-induced sinkhole hazards in Saudi Arabia: distribution,investigation, causes and impacts

Approximately 60 % of the 2,150,000 km² area of Saudi Arabia is underlain by soluble sediments (carbonate and evaporite rock formations, salt diapirs, sabkha deposits). Despite its hyper-arid climate, a wide variety of recent sinkholes have been reported in numerous areas, involving significant property losses. Human activities, most notably groundwater extraction, have induced unstable conditions on pre-existing cavities. This work provides an overview of the sinkhole hazard in Saudi Arabia, a scarcely explored topic. It identifies the main karst formations and the distribution of the most problematic sinkhole areas, illustrated through several case studies covering the wide spectrum of subsidence mechanisms. Some of the main investigation methods are presented through selected examples, including remote sensing, trenching and geophysics. Based on the available data, the main causal factors are identified and further actions that should be undertaken to better assess and manage the risk are discussed.