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date: 04 July 2022

Sinkhole Hazardsfree

Sinkhole Hazardsfree

  • Francisco GutiérrezFrancisco GutiérrezDepartment of Earth Sciences, University of Zaragoza


Sinkholes or dolines are closed depressions characteristic of terrains underlain by soluble rocks (carbonates and/or evaporites). They may be related to the differential dissolutional lowering of the ground surface (solution sinkholes) or to subsidence induced by subsurface karstification (subsidence sinkholes). Three main subsidence mechanisms may operate individually or in combination: collapse, sagging, and suffosion. Subsidence sinkholes may cause severe damage to human built structures, and the occurrence of catastrophic collapse sinkholes may lead to the loss of human life. Dissolution and subsidence processes involved in the development of subsidence sinkholes are controlled by a wide range of natural and anthropogenic factors. Recent literature reviews reveal that the vast majority of the damaging sinkholes are induced by human activities (e.g., water table decline, water input to the ground). The main steps in sinkhole hazard and risk assessment include: (a) construction of comprehensive sinkhole inventories and detailed sinkhole characterization; (b) development of independently tested sinkhole susceptibility and hazard models, preferably incorporating magnitude and frequency relationships; (c) assessing risk combining hazard and vulnerability data. Sinkhole risk models may be used as the basis to perform cost-benefit analyses that allow the cost-effectiveness of different mitigation strategies to be estimated. Three main concepts may be applied to reduce sinkhole risk: (a) avoiding sinkholes and sinkhole-prone areas (preventive planning); (b) diminishing the activity of dissolution and/or subsidence processes (hazard reduction); (c) incorporating special designs in the structures (vulnerability reduction). Although our capabilities to investigate sinkhole hazards and reduce the associated risks will continue to increase in the near future, the damage related to sinkholes will also increase, largely due to the adverse changes caused by human activities on the karst environments and the ineffective knowledge transfer between scientists, technicians, and decision-makers. This article presents the processes and factors involved in sinkhole development and reviews the main approaches used to assess and manage sinkhole hazards and risks.


  • Sinkholes
  • Subsidence

Karst terrains are characterized by unique hydrology and geomorphology, both at the surface and in the subsurface; these are mainly related to dissolution of carbonate and/or evaporite rocks (Ford & Williams, 2007). The main distinctive features of these areas of relevance from the applied perspective include: (a) high permeability aquifers in which groundwater together with pollutants can rapidly flow through conduits and caves generated by dissolution; (b) prevalence of underground drainage and a very limited or absent surface drainage network; (c) presence of enclosed depressions such as sinkholes and poljes, as well as swallow holes and major springs. Sinkholes or dolines are widely regarded as one of the main diagnostic landforms of karst (Ford & Williams, 2007). The word doline was widely used by European geomorphologists in the past century, whereas sinkhole is the most common term in the recent scientific literature. There is also a myriad of local names used to designate sinkholes in different regions (e.g., cenote in Mexico, obruk in Turkey, cockpit in Jamaica, or dahl in the Arabian Peninsula). Sinkholes are typically subcircular in plan view, show a wide morphological diversity (cylindrical-, conical-, bowl-, pan-shaped), and may reach hundreds of meters in diameter and depth. The largest known collapse sinkhole is Xiaozhai tiankeng in China, 662 m deep and 119.3 million m3 in volume (Zhu & Chen, 2005). Crveno Jezero in Crotia has a vertical dimension of 528 m, including the 280 m deep lake of its bottom (Fig. 1).

Figure 1. Crveno Jezero (Red Lake) in Croatia is a collapse sinkhole around 480 m across and with a vertical dimension of 528 m, including its 280 m deep lake.

Kizil obruk in Turkey reaches 710 m in length (Dogan & Yilmaz, 2011). Adjacent dolines may coalesce to form irregularly shaped depressions, commonly referred to as compound sinkholes or uvalas (Kranjc, 2013).

The term doline was first used by Austrian geologists in the middle of the 19th century, when they were investigating the classical Dinaric karst; in Serbo-Croat, it designates a valley or a hollow, not necessarily an enclosed depression (Sweeting, 1972). Cvijic (1893) devoted about half of his pioneering book on karst geomorphology (Das Karstphänomen) to dolines. He distinguished three morphological types: bowl-, funnel-, and well-shaped. Sweeting (1972) published an excellent and nicely illustrated book on karst landforms, which could be considered as the foundation of the modern karst geomorphology. Her book includes a valuable review on dolines. More recently, English-speaking authors produced benchmark textbooks on karst geomorphology and hydrology (Ford & Williams, 1989; Jennings, 1985; White, 1988). These days, the main reference books for karstologists are those authored or edited by Ford and Williams (2007), Gunn (2004), Palmer (2009) and Frumkin (2013). Milanovic’s (2004) book is the most useful reference for the application of engineering solutions to karst-related problems in dams and tunnels. A key landmark in the development of sinkhole investigations was the creation of the Sinkhole Research Institute in Florida and the initiation, in 1984, of biannual international sinkhole conferences led by Dr. Barry Beck. Sowers (1996) produced a brief book mainly focused on the design and construction of foundations in karst terrains. Recently, Waltham, Bell, and Culshaw (2005) published a comprehensive book on sinkholes mainly focused on carbonate karst, which essentially reviews the investigations conducted in the past century.

Sinkholes are the main hazard associated with karst areas (Gutiérrez, Parise, De Waele, & Jourde, 2014a). Subsidence related to the development of sinkholes may damage human built structures, potentially resulting in severe economic and societal consequences. For instance, in May 2012, a heavy rainfall event triggered 41 sinkholes at Maohe village, China, damaging 143 houses (69 collapsed) and leading to the relocation of 1,830 people (Lei, Jiang, & Guan, 2013). The oldest account of sinkhole victims probably are the kings of Sodom and Gomorrah in the Dead Sea area (Frumkin, 2013; and see Genesis 14:10). Moreover, sudden collapse sinkholes may cause loss of human lives. In the Far West Rand of South Africa, catastrophic sinkholes, mainly induced by dewatering of dolomite aquifers for gold mining, have caused a total of 39 fatalities (Heath & Constantinou, 2015). In February 2013, a citizen of Seffner, Florida, was abruptly entombed within a sinkhole that opened beneath his bedroom while he slept; this hole was filled, but remains active, and it reopened in August 2015. Other potentially hazardous processes and problems associated with sinkholes include: (a) differential compaction of sinkhole deposits, typically underlain by irregular rockhead; (b) flooding of depressions by runoff concentration, water table rise, or backflooding (Zhou, 2007); (c) water losses in reservoirs (Gutiérrez, Mozafari, Carbonel, Gómez, & Raeisi, 2015; Milanovic, 2004); and (d) sudden water inrushes in underground excavations. Sinkholes should be considered not only as undesirable problems, but also as potential natural, cultural, educational, and recreational resources that deserve well-informed protection and management. In some regions, they are the “karst windows” that provide the sole direct access to drinkable water, a factor that has determined the distribution of settlements and transportation routes (e.g., the Maya civilization in the Yucatán Peninsula, the Bedouins in the Arabian Peninsula; Munro & Melo-Zurita, 2011; Youssef et al., 2015) (Fig. 2).

Figure 2. Zacil-Ha cenote in Yucatán, Mexico, a bedrock collapse sinkhole related to the foundering of a cave roof. The cave formed in the Pleistocene, when the sea level was at a lower elevation, and was subsequently flooded due to the sea level rise related to the last deglaciation. Cenotes in most regions of Yucatan provide the only direct access to fresh water.

Modern dolines and paleosinkholes may host world-class archaeo-paleontological sites (e.g., Atapuerca in northern Spain). Sinkholes may also form exceptional landscapes of outstanding universal value (e.g., the cockpit karst of Jamaica).

Sinkholes may be related to the dissolution of carbonate and/or evaporite rocks. There are noteworthy differences between carbonate and evaporite karst systems with significant influence on the sinkhole hazard (Cooper & Gutiérrez, 2013; Frumkin, 2013; Gutiérrez & Cooper, 2013): (1) The solubilities of calcite (CaCO3) and dolomite (MgCa[CO3]2) in normal meteoric waters are commonly lower than 0.1 gL−1. By comparison, the equilibrium solubilities of gypsum (CaSO4 2H2O) and halite (NaCl) in distilled water are 2.4 gL−1 and 360 gL−1, respectively. Consequently, dissolution in evaporitic terrains is typically much faster, sinkhole frequency is commonly higher, and subsidence rates may reach greater values. (2) Gypsum and halite have much lower mechanical strength and a more ductile rheology than most carbonate rocks. Moreover, evaporites may experience considerable mechanical weakening occurring on a human-time scale caused by rapid dissolution. These factors explain the importance of the sagging subsidence mechanism in evaporite karst areas and the high rates that the rock collapse processes can reach. (3) Interstratal dissolution of highly soluble salts within the evaporitic successions may result in the development of large subsidence depressions, sinkholes, faults, and folds with high strain rates. These features are frequently erroneously attributed to gypsum dissolution due to the lack of adequate subsurface data and may be misleadingly ascribed to tectonic deformation (Gutiérrez, Carbonel, Kirkham, Guerrero, Lucha, & Matthews, 2014; and references therein).

Sinkhole hazards have a significant impact in numerous regions worldwide. Karst in carbonate and evaporite rocks occurs over 20% of the earth’s ice-free continental surface, and around a quarter of the global population depends on karst water (Ford & Williams, 2007). For instance, karst is found in more than 30% of mainland China (Lei et al., 2015), and 18% of the United Stateas is underlain by soluble rocks (Weary & Doctor, 2014). Despite the fact that the scientific community has substantially improved the ability to assess sinkhole hazards and manage the associated risks, in recent years the amount of sinkhole-related damage shows an overall rising trend. This apparent decoupling between our capabilities and achievements may be attributed to several factors (Gutiérrez, 2010): (a) The numbers of people and human structures in karst regions are increasing very rapidly; (b) The main human activities that contribute to the development of sinkholes (e.g., groundwater extraction, aquifer dewatering) have a progressively higher impact. In China, where the impact of sinkholes has increased dramatically in the last few years, around 75% of the damaging subsidence events are classified as human-induced (Lei, Gao, & Jiang, 2015); (c) The increasing demands for water and energy result in the development of large hydrological projects in problematic karst regions (e.g., Gutiérrez & Lizaga, 2015; Milanovic, 2002) (Fig. 3); and (d) Technical and political decisions are commonly taken without an adequate understanding of the karst systems.

Figure 3. Collapse sinkhole at Ambal ridge, a 4 km2 salt dome of the Miocene Gachsaran Formation in the Karun River valley, Zagros Mountains, Iran. Since 2011, this strongly karstifed salt dome is being submerged by the Gotvand Reservoir, one of the largest of the country and with an initial budget of 1.5 billion dollars. Rapid subsurface salt dissolution is causing the development of large collapse structures hundreds of meters across, numerous sinkholes, and an increase in the salinity of the water (See Gutiérrez & Lizaga, 2015 for additional information).

Sinkhole Types and Processes

There are numerous sinkhole classifications, most inspired by the characteristics of the sinkholes developed in carbonate terrains (e.g. Beck, 2005; Waltham et al., 2005; Williams, 2004;). Here, we follow a broader genetic classification that covers the subsidence mechanisms that occur in both evaporite and carbonate karst settings (Gutiérrez, Guerrero, & Lucha, 2008a; Gutiérrez et al., 2014a) (Fig. 4).

Figure 4. Genetic classification of sinkholes (adapted from Gutiérrez et al., 2008a, 2014a). Subsidence sinkholes are described indicating the material affected by downward displacement and the subsidence mechanism. The pattern of the bedrock reflects the rock types in which the different subsidence mechanisms are most commonly found; sagging in evaporites and the rest in both evaporites and carbonates.

Two main groups of sinkholes can be differentiated; solution sinkholes and subsidence sinkholes.

Solution sinkholes form by differential corrosional lowering of the ground surface where karst rocks are exposed at the surface (bare karst). Infiltration water within the epikarst tends to flow laterally towards higher permeability zones, resulting in focused and self-accelerating dissolution (Williams, 1985). Epikarst refers to a shallow zone beneath the ground surface where the rocks display a higher degree of karstification, related to the percolation of water that rapidly looses its aggressiveness. Solution dolines, which commonly have clay-rich residual deposits in their floor (karstic residue), may be prone to flooding but rarely pose ground stability problems.

Subsidence sinkholes collectively designate a wide spectrum of dolines generated by subsurface dissolution and the deformation and/or internal erosion of the undermined overlying material. These are the most important sinkholes from the hazard perspective, since their development involves the deformation of the ground. Subsidence sinkholes can be described using two terms (Gutiérrez et al., 2008a, 2014a) (Fig. 4). The first descriptor indicates the type of material affected by downward displacement (cover, bedrock or caprock), and the second term refers to the subsidence mechanism (collapse, suffosion or sagging). Cover refers to unconsolidated allogenic deposits (e.g. alluvium) or a residual soil mantle (e.g. saprolite), bedrock refers to karst rocks, and caprock to non-karst rocks. Collapse is the brittle deformation of soil or rock material through the development of well-defined failure planes or brecciation. Suffosion is the downward migration of cover deposits through voids accompanied by the progressive settling of the surface. Sagging is the ductile flexing (passive bending) of sediments related to the lack of basal support. Commonly, the development of subsidence sinkholes involves several subsidence mechanisms that may affect different materials. These complex sinkholes can be described using combinations of the proposed terms with the main material and/or process followed by the secondary one (e.g. cover and bedrock collapse sinkhole) (Fig. 5).

Figure 5. Example of a complex sinkhole exposed in a cutting of the high-speed Madrid-Barcelona highway in the outskirts of Zaragoza city, NE Spain. This is a bedrock sagging and collapse paleosinkhole developed on Tertiary evaporite sediments with thick halite and glauberite units in the subsurface. Thick and thin arrows indicate the approximate limits of the sagging and collapse structures, respectively.

A correct identification of the sinkhole typology constitutes an essential step for an adequate hazard assessment and the design of efficient mitigation measures.

Mantled karst indicates areas where the soluble bedrock is overlain by unconsolidated cover deposits. The covering soils may be affected by any of the three subsidence mechanisms. Differential lowering of the rockhead by progressive dissolution may result in the gradual ductile bending of the mantling deposits producing cover sagging sinkholes. This mechanism results in an irregular rockhead overlain by a folded cover with basin structures (centripetal dips) restricted to the surficial deposits (Fig. 6).

Figure 6. Adjoined cover sagging paleosinkholes recorded in Quaternary alluvium underlain by Tertiary salt-bearing evaporites (lower-left corner). Note that the synforms correspond to the two-dimensional view of basin structures with centripetal dips. Exposure associated with the high-speed Madrid-Barcelona railway in the vicinity of Zaragoza, NE Spain.

A clayey karstic residue commonly occurs between the fresh bedrock and the cover, which may be massive or display inherited pseudo-bedding. The resulting sinkholes are typically shallow, vaguely-edged and may reach hundreds of meters in diameter.

Cover deposits may migrate downward through conduits and cutters developed in the rockhead, which commonly shows a pinnacled geometry (Fig. 7).

Figure 7. Subhorizontal gypsiferous bedrock interrupted by solutional conduits filled by detrital sediments derived for the cover. The internal erosion process was accompanied by the ductile settling of the cover above the subsurface channels (suffosion). Cutting of the high-speed Madrid-Barcelona railway in the Ebro Cenozoic Basin, NE Spain.

These gaps are formed mainly by the dissolutional widening of discontinuity planes and their intersections. The internal erosion of the cover may take place through a wide range of processes, collectively designated as suffosion or raveling, that include: down washing of fine particles by percolating waters (seepage erosion); cohesionless granular flows (i.e., the hour-glass model); viscous sediment gravity flows; fall of particles; and turbulent sediment-laden water flows. Cover materials undermined by subsurface mechanical erosion may experience two subsidence mechanisms depending on their rheology. When the mantling deposits behave as a loose granular material or as a soft ductile layer, it may settle gradually, without the development of persistent failure planes generating funnel- or bowl-shaped cover suffosion sinkholes, typically a few meters in diameter (Fig. 8).

Figure 8. Cover suffosion sinkhole developed on loose detrital deposits consisting of well-sorted angular clasts generated by frost shattering, Villar del Cobo, Iberian Chain, Spain. The particles percolate through conduits in the limestone bedrock generating a funnel-shaped sinkhole resembling the depressions developed in hour glasses.

The size of the depressions and the slope of their margins are largely determined by the repose angle of the cover material.

When the cover is cohesive and dominated by brittle rheology, internal erosion of the mantling deposits results in the development of arched cavities above the subsurface drains. Upward propagation of the soil cavities by successive roof collapse ultimately leads to the formation of cover collapse sinkholes (Fig. 9).

Figure 9. Danvisky cover collapse sinkhole formed on January 1998, western Ukraine. The sinkhole resulted from the collapse of cover material into a cave developed in Miocene gypsum. Note the faulted stacked soils on the sinkhole wall.

Deflection of gravitational stresses around a cavity creates a tension zone over the roof that is overlain by an arched compression zone (voussoir arch). The tension zone controls the formation of failure zones that form with the shape of a hemisphere or a blunted cone. The stability of the resulting cavities largely depends on the roof thickness and cavity width ratio, Moreover, the stability generally increases as cavities propagate upwards due to the decrease in gravitational stresses (Drumm et al., 2009; Poppe, Holohan, Pauwels, Cnudde, & Kervyn, 2015; Shalev & Lyakhovsky, 2012). Analog and numerical modeling of cover collapse above cavities shows the development of outward dipping ring faults that propagate upwards from the edge of the voids until they merge, leading to the detachment and foundering of conical blocks. New failure planes tend to splay from the previous ring faults and attain steeper dips (Poppe et al., 2015). According to Shalev and Lyakhovsky (2012), in cover with a ductile component of deformation, surface collapse is preceded by slow ground settlement, whereas in highly cohesive and rigid cover collapse, sinkholes typically occur without any precursory surface settlement. These factors have relevant implications for the potential anticipation of catastrophic collapse sinkholes and the implementation of early-warning systems. On the other hand, ductile deformation above a cavity typically affects a larger area than that of the underlying void, determined by the angle of draw. Soil cavities may penetrate through very thick cover provided that there is sufficient volume of unfilled conduits in the bedrock to accommodate the collapse material and its volumetric expansion (e.g., Dogan & Yilmaz, 2011). Cover collapse sinkholes tend to occur in a sudden way, are usually less than 10 m across, and have scarped or overhanging margins at the time of formation. The presence of a resistant material like a duricrust or an artificial pavement favors the formation of larger sinkholes by the lateral expansion of the stoping cavities. Cover collapse sinkholes may enlarge rapidly by mass wasting and gullying processes acting on the unstable margins (Fig. 10).

Figure 10. Cover collapse sinkholes in the Dead Sea coast north of Al Hadithah, Jordan. The depressions have expanded by retrogressive rotational slides (hummocky surface around the saline ponds) eventually merging to form a compound sinkhole. The sinkholes have formed in a mud flat recently exposed by the rapid anthropogenic lowering of the lake level. The consequent lakeward migration of the interface between the brackish and saline groundwater (halocline) is causing rapid dissolution of salt beds and the development of hundreds of sinkholes along the Dead Sea coast of Israel and Jordan. In the Israeli lake margin, at least four people have fallen into sinkholes that formed suddenly beneath their feet.

Cover collapse sinkholes and cover suffosion sinkholes are responsible for the vast majority of the damage in most areas (e.g., Lei et al., 2015; Waltham et al., 2005), since these are the most frequent sinkhole types and the most sensitive to human influences.

Dissolution of soluble rocks (bedrock) overlain by non-karst rocks (caprock) is commonly referred to as interstratal karst. Bedrocks and caprocks in carbonate karst areas overlying cavities are typically affected by collapse processes. However, interstratal karstification in more ductile evaporitic sequences, and affecting broader areas, may lead to sagging subsidence. The type of subsidence mechanism in these lithostratigraphic contexts mainly depends on the geometry and size (span) of the cavity or dissolution zone, the thickness of the overlying rocks, and their mechanical properties, largely determined by the discontinuity planes. The collapse of rock cavities may take place through two main modes. One of them is the foundering of the cavity roof as a large block, with limited internal deformation, and bound by cylindrical or conical ring faults. This deformation style is favored by the presence of massive and resistant stratigraphic units. A much more common mechanism is the progressive collapse of the cavity roof through the detachment and fall of numerous blocks controlled by discontinuity planes (e.g., stratification and joints). This stoping process involves the upward migration of the cavity roof and the accumulation of a chaotic breakdown pile, which may fill large breccia pipes, also called collapse chimneys or breakdown columns. These transtratal structures may reach hundreds of meters in height, especially when they are rooted in thick evaporitic sequences (Warren, 2006). Whether a stoping void can reach the surface or not depends on the volume of the cavity, the overburden thickness, and the volumetric expansion associated with the breakdown processes (bulking effect; Ege, 1984). The collapse process may stop if the cavity roof and the breakdown pile meet, choking the collapse pipe. Collapse breccias can be classified considering the relative displacement of clasts (crackle, mosaic, chaotic), and whether they have a clast-supported (packbreccia) or matrix-supported texture (floatbreccia) (Warren, 2006; and references therein). These breccias may be highly pervious and act as preferential zones for groundwater flow and karstification. Dissolution may gradually transform chaotic packbreccias into floatbreccias, consisting of corroded clasts embedded in a karstic residue. This involves a volumetric depletion that may induce sustained or renewed subsidence. Bedrock collapse sinkholes and caprock collapse sinkholes are characterized by subvertical or overhanging margins and are commonly more than 10 m in diameter (Figs. 11, 12, and 13).

Figure 11. Air view of bedrock collapse sinkholes, Zenzano, Iberian Chain, NE Spain. The major axis of the largest depression is 170 m long.

Figure 12. Cirali obruk in the Obruk Plateau, central Anatolia, Turkey, is an old giant bedrock collapse sinkhole 320 m in diameter and ca. 100 m deep related to the collapse of large caverns generated by hypogene karstification of Pliocene limestone. The overhanging ledge in the lower part of the depression is subaqueous tufa formed before the recent lowering of the lake level by groundwater pumping. It consists of vertically elongated mammillary crusts. The holes in the sinkhole walls are ancient man-made caves. These karst windows where used in old times by the caravans as staging points in the trading routes.

Figure 13. Caprock collapse sinkhole formed in Neogene basalts underlain by karstified limestone, Al Issawiah area, Saudi Arabia.

These are normally catastrophic sinkholes with a high damaging potential, but typically with a very low probability of occurrence. In most cases, the volume of collapse sinkholes developed in both cover deposits and rock formations is significantly lower than the volume of the underlying cavities due to the bulking effect and the presence of unfilled voids (e.g., Poppe et al., 2015).

Sagging of bedrock or caprock is generally related to interstratal dissolution of evaporites. Progressive dissolution within the bedrock may be accompanied by continuous flexure of the overlying strata, resulting in disharmonic basin structures that do not affect the rocks underlying the karstification zone. This subsidence mechanism produces bedrock sagging sinkholes and caprock sagging sinkholes that may reach hundreds of meters in length (Fig. 14).

Figure 14. Bedrock sagging sinkholes in ‘Ar’ Ar, Saudi Arabia, related to interstratal karstification of gypsum beds within the Cretaceosu Badanah Formation. Note the dip of the strata towards the center of the depression. These dolines, locally known as khabras, were initially interpreted as deflation basins.

Passive bending of the strata involves horizontal shortening that may be counterbalanced through the development of small-throw normal faults, fissures, and grabens at the margins (e.g., Carbonel et al., 2014). The type of secondary faults (normal, reverse) may also be influenced by the geometry of the karstification zone (e.g., widening vs. narrowing upwards). The passive bending of rock strata may be accompanied by widespread fracturing (brecciation) and/or the development of superimposed collapse structures, preferentially in the more fractured central sector of the basins (Guerrero et al., 2013; Gutiérrez et al., 2008a) (Fig. 5). The development of sagging sinkholes does not require the formation of cavities, since subsurface dissolution and subsidence may act concomitantly. Subsidence is a gradual process that does not constitute a threat for human lives.

Controlling Factors and Human-Induced Sinkholes

Subsidence sinkholes result from the simultaneous or sequential activity of two processes: subsurface dissolution (hydrogeological component) and downward movement of the overlying material by internal erosion and/or gravitational deformation (mechanical component). In evaporite karst settings, dissolution may be very rapid and may have a significant impact within the lifetime of engineering projects (e.g., Cooper & Gutiérrez, 2013). In contrast, the effects related to active corrosion of carbonate rocks over a human time-scale are negligible in most cases (Beck, 2005). Subsidence processes are not necessarily related to active dissolution. They frequently occur above pre-existing voids that have remained stable until a natural agent or anthropogenic alteration initiates the ground instability process. Collapse is commonly catastrophic, suffosion may be very rapid, and sagging is typically a slow and gradual process.

The main geological factors that control the karstification of evaporites and carbonates include: (a) Composition of the karst rocks (lithology, mineralogy) and that of the adjacent lithologies. Karstification is often particularly intense next to the contact with non-karst rocks; that is, contact karst. (b) The structure (discontinuity planes, dip, folding, faulting) and texture (grain size, porosity) of the karst rocks. Dissolution is commonly guided by fractures and stratigraphic contacts. (c) The amount of water flowing in contact with the soluble rock and its physico-chemical properties (saturation index, pH, temperature). The solubility of carbonate rocks largely depends on the pH of the water, which in most cases is controlled by the dissolved CO2 derived from the air and the soil. Other potential sources of acidity include CO2- and H2S-rich rising fluids or the oxidation of sulfides. Moreover, groundwater may experience renewed aggressiveness due to mixing and temperature changes. (d) Hydrogeological and hydrodynamic conditions (gradient, hydraulic conductivity, phreatic or vadose, laminar or turbulent). The condition of the water as a static or dynamic medium has an important influence on the dissolution kinetics, especially in high-solubility minerals (like halite). Static water in contact with salts rapidly becomes saturated with the consequent cessation of the transport-controlled dissolution process. The transition from laminar to turbulent flow involves a significant increase in the dissolution rate due to thinning of the diffusion boundary layer. This is the reason why the change from laminar to turbulent flow in widening conduits or fissures is often considered the beginning of true cave development (Palmer, 2009). More detailed information on the role played by these factors may be found in Dreybrodt (2004), Ford and Williams (2007) and Palmer (2009).

The processes involved in the generation of subsidence sinkholes (dissolution, subsidence) can be activated or accelerated by natural and anthropogenic changes in the karst environment. In most cases, sinkhole activity should not be considered strictly as a problematic natural process, but a human-induced hazard. Nonetheless, the human contribution to the development of specific damaging sinkholes, an issue with relevent legal implications, is frequently difficult to demonstrate. Table 1 presents the main natural and artificial alterations that may promote the formation of sinkholes, together with their potential effects (Gutiérrez et al., 2014a). This table, including key references of case histories, can be used as a checklist to identify the factors that have contributed to sinkhole development.

Table 1. Changes in the Karst Systems and their Potential Effects that May Accelerate or Trigger the Development of Sinkholes.

Type of change


(1) Natural processes (2) Human activities

Increased water input to the ground (cover and bedrock)

Increases percolation accelerating suffosion.

Favors dissolution.

Increases the weight of sediments.

May reduce the mechanical strength and bearing capacity of sediments.


Rainfall (Gutiérrez-Santolalla et al., 2005; Keqiang et al., 2004; Youssef et al., 2012; Zhao, Ma, & Guo, 2010), floods (Hyatt & Jacobs, 1996), snow melting, thawing of frozen ground (Satkunas, Taminskas, & Dilys, 2006).


Irrigation (Atapour & Aftabi, 2002; Gutiérrez et al., 2007; Kirkham et al., 2003), leakages from pipes (Abdullah & Mollah, 1999; Dougherty, 2005; Fleury, 2009; Gutiérrez & Cooper, 2002; Jassim, Jibril, & Numan, 1997; McDowell, 2005; McDowell & Poulsom, 1996; Myers & Perlow, 1984; Scarborough, 1995; Shaqour, 1994), canals (Lucha, Gutiérrez, & Guerrero, 2008b; Swan, 1978) or ditches (Gutiérrez et al., 2007; Moore, 1988), impoundment of water (Milanovic, 2004), runoff concentration (urbanization, soakaways, drainage wells) or diversion (Crawford, 2001; Knight, 1971; White, Aron, & White, 1986), vegetation removal, drilling operations (Croxton, 2003; Johnson, 1989), unsealed wells and boreholes (Johnson, 2005; Johnson et al., 2003; Lambercht & Miller, 2006; Liguori, Manno, & Mortellaro, 2008), injection of fluids, solution mining (Ege, 1984).

Water table decline

Increases the effective weight of the sediments (loss of buoyant support).

Slow phreatic flow replaced by more rapid downward.

percolation favoring suffosion, especially when the water table is lowered below the rockhead.

Accelerates groundwater flow in areas affected by cones of depression.

May reduce the mechanical strength by desiccation and crystallization of salts.

Hydrofracturing of poorly drained deposits surrounding cavities (Tharp, 1995).

Suction effect.

Loose fine-grained deposits may be dragged with the pumped water causing internal erosion (e.g. Karimi & Taheri, 2010; Khanlari et al., 2014).


Climate change, sea level decline (Cooper & Keller, 2001), entrenchment of drainage network (Ortega et al., 2013), tectonic uplift, isostatic rebound, halokinetic uplift (Closson et al., 2007; Zarei, Raeisi, & Talbot, 2011).


Water abstraction (Aurit et al., 2013; Beck, 1986; Chen, 1988; Chen & Xiang, 1991; Currin & Barfus, 1989; Dogan & Yilmaz, 2011; Daoxian, 1987; Destephen & Benson, 1993; García-Moreno & Mateos, 2011; He, Liu, & Wang, 2003; Kaufmann & Quinif, 2002; Karimi & Taheri, 2010; Keqiang, Bin, & Dunyun, 2004; Kemmerly, 1980; Khanlari et al., 2014; LaMoreaux & Newton 1986; Lei et al., 2001; Newton, 1984; Shaquor, 1994; Taheri et al., 2015; Tihansky, 1999; Waltham, 2008; Waltham & Smart, 1988), de-watering for mining and excavation operations (Bezuidenhout & Enslin, 1970; Chen, 1988; Daoxian, 1987; De Bruyn & Bell, 2001; Foose, 1953; Jovanelly, 2014; Klimchouk & Andrejchuk, 2005; LaMoreaux & Newton, 1986; Li & Zhou, 1999; Pando, Pulgar, & Gutiérez-Claverol, 2013; Sprynskyy, Lebedynets, & Sadurski, 2009; Strum, 1999; Xu & Zhao, 1988; Zhou, 1997), decline of water level in lakes (Frumkin et al., 2011; Yechieli, Abelson, Bein, Crouvi, & Shtivelman, 2006;, excavations acting as drainages (Fidelibus et al., 2011), ground-source heat pumps (Cooper & Gutiérrez, 2013).

Impoundment of water

May create extremely high hydraulic gradients leading to rapid turbulent flows favoring internal erosion and dissolution.

The base level rise may change groundwater flow paths and location of discharge zones.

Major and continuous changes in the water table causing repeated flooding and drainage of karst conduits.

Imposes a load.


Natural lakes (Day & Reynolds, 2012).


Reservoirs (James, 1992 and references therein; Milanovic, 2004 and references therein, 2002; Uromeihy, 2000; Dogan & Cicek, 2002; Jarvis, 2003; Romanov et al., 2003; Bonacci & Roje-Bonacci, 2008; Johnson, 2008; Bonacci & Rubinić, 2009; Cooper & Gutiérrez, 2013; Gutiérrez et al., 2015; Gutiérrez & Lizaga, 2015), underground dams and reservoirs (Roje-Bonacci & Bonacci, 2013), ponds (Hunt et al., 2013), evaporation pans (Parise, Closson, Gutiérrez, Stevanovic, 2015), sewage lagoons (Alexander, Larson, Bomberger, Greenwaldt, & Alexander, 2013; Davis & Rahn, 1997; Newton, 1987).

Erosion or excavation

Reduces the thickness and mechanical strength of cavity roofs.

May concentrate runoff.

May create a new base level changing the path and rate of groundwater flows.

May create an outlet for internally eroded deposits.


Erosion processes (Cooper et al., 2011).


Excavations (Fidelibus et al., 2011; Guerrero, Gutiérrez, Bonachea, & Lucha, 2008; Lolcama, Cohen, & Tonkin, 2002; Walker & Matzat, 1999).

Underground excavations

Disturb groundwater flows.

May intercept phreatic conduits, distort groundwater flow paths.

May cause sudden inrushes of water and flooding in underground openings involving accelerated internal erosion and karstification.

May weaken sediments over voids.


Biogenic pipes


Conventional and solution mining (Andrejchuk, 2002; Autin, 2002; Bonetto et al., 2008; Daoxian, 1987; Dyni, 1986; Ege, 1984; Gongyu & Wanfang, 1999; Gowan & Trader, 2003; He et al., 2009; Johnson et al., 2003; Kappel et al., 1999; Land, 2013; Li & Zhou, 1999; Lucha et al., 2008a; Mesescu, 2011; Sharpe, 2003; Vigna et al., 2010; Wang et al., 2008; Warren, 2006; Xu & Zhao, 1988; Yin & Zhang, 2005), tunneling (Marinos, 2001; Milanovic, 2004; Song et al., 2012).

Static loads

Favors the failure of cavity roofs and compaction processes.

Unloading favors the formation of fractures and dilation of pre-existing one.


Aggradation processes. Glacial loading and unloading (Anderson & Hinds, 1997).


Engineered structures (Waltham, 2008), dumping (Fuleihan et al., 1997), heavy vehicles (Davis & Rahn, 1997; Grosch, Touma, & Richards, 1987; James, 1993; Waltham, Bell, & Culshaw, 2005).

Dynamic loads

Favors the failure of cavity roofs and may cause liquefaction-fluidization processes involving a sharp reduction in the strength of soils.

Fracturing with the consequent increase in permeability and strength reduction.


Earthquakes (Closson & Karaki, 2009; Del Prete, Di Crescenzo, G., Santangelo, N., & Santo, 2010a; Del Prete, Iovine, Parise, & Santo, 2010b; Kawashima et al., 2010), impact of extraterrestrial bodies (Perry et al., 1995), explosive volcanic eruptions.


Artificial vibrations (blasting, explosions) (Daoxian, 1987).


Weakens, punctures, and overloads cavity roofs.

Causes internal erosion favored by the holes, vibrations, drilling fluids, and pumping.

May induce localized and turbulent groundwater flows.


Borings (Meng et al., 2012), water wells, horizontal directional drilling for the installation of pipelines (Smith & Sinn, 2013).

Vegetation removal

Reduces mechanical strength of cover deposits (root cohesion).

Increases infiltration.


Wild fires.


Vegetation clearance (Newton, 1987; James, 1993).

Thawing of frozen ground

Favors dissolution.

Significant reduction in the strength of the sediments.


Climate change (Satkunas et al., 2006).


Development, deforestation, water storage (Eraso et al., 1995; Trzhtsinsky, 2002).

Water Table Decline

The recent scientific literature on sinkholes indicates that water table decline, related to aquifer exploitation or to mining-related dewatering, is the main anthropogenic cause of sinkhole occurrence. The negative impact of groundwater pumping on the sinkhole hazard will inevitably continue to increase in the near future, especially in drylands like extensive regions of the Middle East (e.g., Dogan & Yilmaz, 2011; Taheri et al., 2015; Youssef et al., 2015) (Figs. 15 and 16).

Figure 15. Cover collapse sinkhole in an irrigated crop field triggered by groundwater level decline related to pumping in the Hotamis Plain, central Anatolia, Turkey. The sinkhole developed in late Quaternary lacustrine deposits of the Konya pluvial lake underlain by Pliocene limestone. It was 25 m in diameter and 36 m deep at the time of formation in 2009. It has rapidly enlarged by reactivations in the bottom and mass wasting processes on the walls to reach a depth of 44 m and a dimeter of 47 m when the photograph was taken on September 2015. Two geomorphologists on the far edge of the sinkhole for scale.

Figure 16. Cover collapse sinkhole in an abandoned pivot-irrigation crop induced by groundwater level decline, Al Jouf Region, Saudi Arabia. Mass wasting processes and gullying are causing the rapid expansion of the sinkhole. Note fresh unloading cracks at the margin. The depression is used for waste disposal.

The main potential effects of lowering the groundwater level include the loss of buoyant support, increased groundwater velocity, and the replacement of phreatic flows by downward vadose flows with greater capability for internal erosion. The latter effect is particularly important when the water table declines below the rockhead. Newton (1984), in his pioneering paper on human-induced sinkholes, reported that more than 4,000 sinkholes have resulted from groundwater withdrawal in Alabama since 1900. In Florida, Aurit, Peterson, and Blanford (2013) found good temporal and spatial correlations between freeze events, strawberry farming regions, and sinkhole occurrence. Here, sinkholes are triggered by water level drops related to groundwater pumping for sprinkler irrigation to protect the crops from freezing damage. Daoxian (1987) and Li and Zhou (1999) review cases in China where mining-related dewatering has induced thousands of sinkholes resulting in the abandonment of mines, relocation of a village, demolition of buildings, destruction of reservoirs and railways, sudden inrushes of water in mines, and the sinking of a river into a mine through collapses.

A peculiar and dramatic example of human-induced catastrophic subsidence related to water table lowering is shown by the hundreds of sinkholes formed over the last 30 years in the Dead Sea shores of Israel and Jordan. Here, the cause of the water table lowering is related to the rapid decline of the lake level due to anthropogenic use of water in the catchment and lake. This has led to the seaward displacement of the brackish-saline water interface with the consequent circulation of unsaturated water though salt deposits, resulting in the formation of cavities and collapse sinkholes, mainly controlled by Quaternary faults and the salt edge (Yechieli et al., 2006; Closson, LaMoreaux, Abou-Karaki, & al-Fugha, 2007; Frumkin, Ezersky, Al-Zoubi, Akkawi, & Abueladas, 2011) (Fig. 10). A 12-km-long dike, built in the Lisan Peninsula, Jordan to create a 95 106 m3 salt evaporation pond has been severely impacted by sinkhole development. Potash salt is the second most lucrative export in the country, and the dike had an initial cost of 32 million dollars. Sinkhole damage forced the pond to be empty for five years,and the associated remedial works cost 12 million dollars. Recently, a subsidence area approximately 600 m across was identified as compromising the integrity of the dike and leading to the amputation of a significant portion of the evaporation pond (Closson & Karaki, 2015) (Fig. 17).

Figure 17. Satellite image of Dike 18 of a salt evaporation pan in the Lisan Peninsula, Dead Sea, Jordan. Note the sinkhole alignment next to the dike and the abandoned dike trace.

Water Input to the Ground

Sinkholes are also frequently induced by increased water input to the ground. Widespread or focused water infiltration enhances internal erosion processes and may adversely modify the mechanical strength and weight of sediments. Moreover, freshwater input may dramatically reduce the strength and bearing capacity of sabkha deposits due to rapid dissolution of salts (Abdulali & Sobhi, 2002; Youssef et al., 2012). In a dolomite karst area covering around 3.7 km2 in Gauteng Province, South Africa, 650 new sinkholes formed in 20 years between 1984 and 2004, of which 99% were associated with leaking water-bearing pipes (Buttrick, Trollip, Watermeyer, Pieterse, & Gerber, 2011). In Spain, Gutiérrez et al. (2007) calculated a minimum spatial-temporal frequency of 50 sinkholes/km2/yr, in an area where most of the subsidence events are related to massive sheet-flooding irrigation and leakage from unlined ditches and canals.

Impoundment of Water

The impoundment of water in reservoirs is a common cause of sinkhole development (Fig. 18).

Figure 18. Collapse sinkholes related to gypsum dissolution formed in 2014 in the Loteta Reservoir, Ebro Valley, NE Spain. A sinkhole alignment developed upstream of the left abutment, affected by significant leakage. Image taken on March 2014. See additional details in Gutiérrez et al. (2015).

The infill of a reservoir involves imposing a load and creating unnaturally high hydraulic gradients that may lead to rapid turbulent flows with a high capability to flush out sediments from conduits and enlarge them by dissolution (Milanovic, 2004; Romanov, Gabrovsek, & Dreybrodt, 2003). In addition, continuous changes in the reservoir level are accompanied by flooding and drainage cycles in the karst system, which favors both mechanical and chemical subsurface erosion. Pre-existing and newly created sinkholes in reservoirs and in the foundation of dams may result in severe water leakages and stability problems, compromising the operation and safety of the hydraulic structure. Milanovic (2004) and Gutiérrez et al. (2015) review a number of dam projects severely impacted or abandoned due to water losses through sinkholes functioning as ponors. The case of Anchor Reservoir, Wyoming, built despite the fact that more than 50 cover collapse sinkholes had been previously identified in the reservoir area, illustrates the potential consequences of disregarding or underestimating the presence of sinkholes and karst rocks in reservoirs and dam sites. Here, water drained through sinkholes and earth fissures associated with highly cavernous gypsum and carbonate rocks in the reservoir area before, during, and after construction of the dam. Moreover, large caves encountered in carbonate rocks of one of the abutments required costly grouting. After nearly 30 years applying expensive remedial measures, including the construction of a dike around a sinkhole 100 m across, the reservoir failed to ever store water (Jarvis, 2003). The 113 m high and 3.4 km long Mosul Dam on the Tigris River, Iraq, was built on a Miocene gypsum-bearing formation in 1984. The dam, located 50 km upstream of Mosul, a city with three million inhabitants, is one of the most strategic infrastructures of the country. Since the initial filling, and despite a permanent grouting program, reservoir water flowing through the foundation is causing major gypsum dissolution, sinkhole development, and significant settlement in the dam, compromising the safety of the structure and creating social alarm. Badush Dam is being constructed upstream of Mosul, to act as a backstop structure in the event of a dam burst (Guzina, Sarić, & Petrović, 1991; Sissakian, Al-Ansari, & Knutsson, 2014).


Surface and underground excavations may trigger or create favorable conditions for sinkhole activity. The main effects of lowering the ground surface by excavation include: (a) Reducing the thickness and mechanical strength of cavity roofs; (b) Creating topographic depressions for runoff concentration and enhanced infiltration; (c) Incorporating new local base levels that may modify the groundwater flow paths and rates. Fidelibus, Gutiérrez, & Spilotro (2011) analyze the complex interrelationships between the occurrence of collapse sinkholes impinging on a residential area in the Adriatic coast of Italy and the excavation of a canal through unknown cavernous gypsum overlain by a loose sandy cover. The canal, aimed at improving the connection between a lagoon and the sea, and effectively acting as a drainage trench, caused a number of hydrological changes that induced sinkhole development; these included lowering of the water table, distortion of the groundwater flow and increase in flow velocity, amplification of the water table oscillations controlled by the tidal regime, creation of an outlet for the sediments filling cavities, and their mobilization by internal erosion.

Tunneling and Mining

The excavation of tunnels and mine galleries, apart from dewatering by pumping, may cause dramatic changes in the local hydrogeology, leading to the formation of sinkholes (Bonetto, Fiorucci, Formaro, & Vigna, 2008; Marinos, 2001; Milanovic, 2004; Vigna, Fiorucci, Banzato, Forti, & De Waele, 2010; Wang, You, & Xu, 2008). The interception of conduits and cavernous rock by excavations performed below the water table may result in dangerous inrushes of water under pressure. The drainage of the aquifer towards underground artificial openings may lead to uncontrolled flooding of the excavation, rapid lowering of the water table, suspension of water supply from wells, enhanced internal erosion, and the development of sinkholes. In numerous mine districts in China, water inrushes and instability problems are especially common when the excavation works intercept pervious and mechanically weak breccia pipes rooted in deep-seated cavities developed in limestone or evaporites (Daoxian, 1987; He, Yu, & Lu, 2009; Li & Zhou, 1999; Lu & Cooper, 1997; Yin & Zhang, 2005). In northern Spain, the excavation of deep tunnels for a high-speed railway through a structurally complex karst aquifer caused the rapid lowering of the groundwater level and the occurrence of sinkholes in a river, functioning as ponors. The swallow holes have beheaded the downstream section of the river and captured the upstream section through karst conduits (Valenzuela et al., 2015). Sinkhole hazards may be particularly severe when fresh water flows into salt mines coming from an adjacent or overlying aquifer (Andrejchuk, 2002; Gowan & Trader, 2003; Kappel, Yager, & Todd, 1999) or from a surface water body (Autin, 2002; Lucha, Cardona, Gutiérrez, & Guerrero, 2008a). The highly aggressive water may cause massive dissolution of salt and uncontrollable sinkhole occurrence, leading to the abandonment of the mine. In the Cardona salt diapir, in northeastern Spain, the interception of a phreatic conduit by a shallow salt mine gallery (whose final goal was the disposal of hazardous wastes) caused the inflow of freshwater from a nearby river, rapid dissolution, formation of numerous collapse sinkholes, and ultimately the abandonment of the mine.

Solution Mining

Large collapse sinkholes may also form above cavities in salt formations created by solution mining, which involves the injection of fresh water and the recovery of a brine (Andrejchuk, 2002; Dyni, 1986; Ege, 1984; Johnson, 1997; Johnson, Collins, & Seni, 2003; Mancini, Stecchi, Zanni, & Gabbianelli, 2009; Mesescu, 2011; Warren, 2006). These cavities may propagate upward several hundred meters through overlying formations in a few decades, eventually leading to the sudden occurrence of sinkholes more than 100 m across (Ege, 1984; Johnson, 1997; Land, 2013). In 2008 and 2009, three large collapse sinkholes formed catastrophically above caverns created by solution mining in the Upper Permian Salado Formation of the Delaware Basin; two in Eddy County (JWS sinkhole and Loco Hills sinkhole), New Mexico, and another one near Denver City, Texas (Denver City sink) (Fig. 19).

Figure 19. The JWS collapse sinkhole around 110 m across formed on July 16, 2008 at the site of a brine well in Eddy County, New Mexico. The sinkhole results from the upward stoping of a large cavity generated in the Permian Salado Formation by injecting fresh water and extracting brine for use as oil drilling fluid. The top of the salt formation is 120 m deep. A seismograph located 13 km from the well recorded ground motion attributable to premonitory subsurface collapse before the abrupt occurrence of the depression. See additional details in Land (2013).

Image courtesy of Lewis Land.

A transportable seismograph, installed close to the JWS sinkhole before the surface failure, recorded seismic events related to the episodic upward stoping of the man-made cavity roof. A solution-mining cavern is located beneath residential areas and major infrastructure within the city limits of Carlsbad, New Mexico. The birne well has been closed, the cavern has been investigated by various geophysical methods, and a monitoring and alarm system has been developed to prevent loss of life in the event of a catastrophic collapse (Land, 2013; and references therein).

Static and Dynamic Loading

Natural and human-induced static and dynamic loading may trigger the collapse of pre-existing cavities under marginal stability conditions. The load imposed by heavy vehicles, drilling rigs, dumped material, and engineered structures may cause dangerous sinkhole events (e.g., Meng, Lei, Lin, Dai, & Guan, 2012). A similar effect may be expected from ground shaking related to explosions and earthquakes. Daoxian (1987) documents that exploration for groundwater in a limestone aquifer, using explosives, triggered 157 collapse sinkholes that resulted in the abandonment of Liangwu village, Guangxi, China. In the Apennines, Italy, Santo, Ascione, Del Prete, Di Crescenzo, and Santangelo (2010) identify a number of collapse sinkholes triggered or reactivated by destructive earthquakes (coseismic sinkholes) with intensities at the site higher than MCS VIII. Kawashima et al. (2010) document two bedrock collapse sinkholes triggered by the 2009 L’Aquila earthquake, Italy (Mw=6.2).

Other changes that may induce sinkhole development are vegetation removal and thawing of frozen ground. Vegetation clearance may increase infiltration and the susceptibility of cover deposits to internal erosion. Thawing of frozen ground (permafrost) involves a substantial change in the mechanical strength and permeability of sediments and the availability of liquid water to dissolve karst rocks. The Bratsk Reservoir, Siberia, has caused the partial thawing of the permafrost and the reactivation of a gypsum karst, resulting in the development of numerous collapse sinkholes along some coastal sectors. During reservoir impoundment (1963–1966), sinkhole occurrence reached a spatial-temporal frequency of 200 sinkholes/km2/year, causing severe damage to buildings and structures outside the reservoir area (Eraso, Trzhtsinskij, & Castrillo, 1995; Trzhtsinsky, 2002).

Sinkhole Mapping and Characterization

An essential step for sinkhole hazard assessment and risk management is the construction of comprehensive cartographic sinkhole inventories. Frequently, subsidence damage is related to the activity of pre-existing sinkholes, which may have been obliterated by human activity. Moreover, old sinkholes are commonly the best predictors for new sinkholes, especially where they show a clustered distribution. The reliability of sinkhole susceptibility and hazard maps and the effectiveness of the mitigation measures largely rely on the completeness, accuracy and representativeness of the sinkhole inventories on which they are based.

Sinkhole databases should preferably include information on the following aspects: (a) Precise geolocation of the sinkhole edges and the underlying subsidence structures. This is essential to accurately define potentially unstable areas, including a set-back distance around the sinkholes (Zhou & Beck, 2008). The size of the set-back distance should be conditioned by the accuracy/uncertainty of the mapped sinkhole limits. Moreover, it is important to consider that the ground affected by subsidence frequently covers an area larger than the recognizable topographic expression of the sinkhole, especially in the case of subsidence structures with a sagging component (e.g., Gutiérrez, Galve, Lucha, Bonachea, Jordá, & Jordá, 2009) (Fig. 5). (b) Morphometric parameters. These geometrical variables, together with the chronological data, constitute the basis on which to analyze magnitude and frequency relationships of sinkholes (Fig. 20), and to define design parameters for engineering structures.

Figure 20. (A) Magnitude and frequency relationship generated with an inventory of 41 sinkholes formed over 23 years (1989–2011) in Hamedan region, Zagros Mountains, Iran. In this area, a water table drop of more than 75 m, caused by aquifer overexploitation, is triggering a large number of sinkholes, threatening two highly vulnerable infrastructures (Hamedan power station and the military air base of Kabudar Ahang). Hazard values derived from this scaling relationship should be considered as optimistic estimates, since the sinkhole inventory is most probably incomplete. For instance, the minimum annual frequency of sinkholes larger or equal to 10 m is 0.85, and the maximum recurrence 1.2 years (see Taheri et al., 2015 for further details). (B) Cover collapse sinkholes more than 20 m across occurred in Hamedan region in the 1990s.

Image courtesy of Kamal Taheri.

(c) Genetic type; recording the subsidence process and material affected by subsidence (Fig. 4). This is a crucial aspect, since the subsidence mechanisms determine the applicability and effectiveness of different mitigation measures and the capability of the sinkholes to cause damage. (d) Chronology, either relative or numerical ages. The latter is indispensable to calculate rates of sinkhole occurrence and hazard estimates in terms of spatial and temporal probability. (e) Activity, including subsidence rates, kinematical behavior (gradual, episodic, or mixed), and age of the most recent deformation episode. (f) Relationship with conditioning and triggering factors. The analysis of the sinkhole hazard also requires as much information as possible on other karst features (e.g., caves, springs, ponors, subsidence damage), the geology and hydrogeology of the area, and human activities that may influence dissolution and subsidence processes.

Since the start of some pioneering initiatives like that of the Florida Sinkhole Research Institute (Beck, 1991), a number of institutions and associations have developed sinkhole and karst databases, mostly integrated in a Geographical Information System (e.g., Florea, 2005; Gao, Alexander, & Tipping, 2002; Parise & Vennari, 2013). The British Geological Survey is compiling a national karst database including features related to five different types of soluble rocks: limestone, dolomite, chalk, gypsum, and salt (Cooper & Keller, 2001; Cooper, Farrant, & Price, 2011; Farrant & Cooper, 2008). This database is used in combination with other datasets to develop sinkhole susceptibility models by means of a scoring system. Gao and Weary (2008) present a conceptual model for constructing and integrating karst databases from national to local scales, to be used in the production of a new national karst map of the United States. The sinkhole and karst databases, together with the datasets and maps derived from them (sinkhole susceptibility models), are a useful planning tool that may help decision-makers to manage karst areas minimizing environmental problems. It may be also a valuable source of information for private companies (insurance, geotechnical) and the general public, as well as an excellent platform for researchers.

The identification and precise mapping of sinkholes is commonly a difficult task. The geomorphic expression of the depressions may be masked by anthropogenic activities (filling, construction), natural processes such as aggradation, or dense vegetation. Moreover, shallow cavities and active subsidence structures that could lead to the generation of sinkholes in the near future may not have any surface expression. Consequently, the detection and adequate characterization of sinkholes and potentially unstable ground commonly requires the application of multiple surface and subsurface investigation methods. Table 2 includes the main investigation methods and the type data applicable to sinkhole hazard assessment that may be obtained through their application (Gutiérrez et al., 2014a).

Table 2. Main Surface and Subsurface Investigation Methods Used for Sinkhole Identification and Characterization.


Aerial and satellite images

Mapping depressions and patterns attributable to dissolution and subsidence features. Historical orthorectified aerial photographs, low-altitude oblique images (pictometry), recent orthoimages, and LIDAR-derived shaded relief models can be used in a complementary fashion on a GIS platform (Alexander et al., 2013; Panno & Luman, 2013).

Old images allow pinpointing masked sinkholes (Brinkmann, Wilson, Elko, Seale, Florea, & Vacher, 2007; Festa, Fiore, Parise, & Siniscalchi, 2012; Gutiérrez, Galve, Lucha, Castañeda, Bonachea, & Guerrero, 2011; Panno & Luman, 2013).

Automatic mapping and acquisition of morphometric parameters by direct measurement or using photogrammetric techniques (Dou et al., 2015).

Images taken on different dates may be used to constrain the chronology of recent sinkholes, calculate sinkhole occurrence rates, and analyze spatial and temporal evolution patterns (Festa et al., 2012). Airborne multispectral scanning has promise for showing vegetation and soil changes associated with sinkholes (Cooper, 1989).

Topographic maps

Identification of sinkholes (Angel et al., 2004; Brinkmann, Parise, & Dye, 2008; Kasting & Kasting, 2003). A large number of sinkholes may be overlooked depending on the size of the depressions and the scale and contour interval of the map (Applegate, 2003).

Old maps may help to map masked sinkholes (Basso, Bruno, Parise, & Pepe, 2013; Gutiérrez, Galve, Lucha, Castañeda, Bonachea, & Guerrero, 2011).

Morphometric parameters.

Swath bathimetry for studying underwater features in lakes or ocean floors (Taviani et al., 2012).

Field surveys

Locating sinkholes not identifiable in remote-sensed imagery and diagnosing features of uncertain origin (Bruno, Calcaterra, & Parise, 2008; Gutiérrez et al., 2007).

Morphometric characterization and qualitative evaluation of activity and age.

Signs of instability like cracks, scarplets, or pipes (precursors) may help to anticipate location of future sinkholes.

Local people may provide information on sinkholes (location, age, relationship with causal factors).

Paleokarst analysis

The dissolution and subsidence structures exposed in natural and artificial outcrops provide information on sinkhole formation (spatial distribution, subsidence mechanisms, size) (Gutiérrez et al., 2008a).

Identification of potentially unstable ground and sinkhole susceptibility assessment (Guerrero, Gutiérrez, Bonachea, & Lucha, 2008).

Subsidence damage maps

Provide information on the distribution and patterns of subsidence phenomena in built-up areas.

Help to infer the main natural and anthropogenic controlling factors (Cooper, 2008; Gutiérrez & Cooper, 2002).

LIDAR (Light Detecting And Ranging)

Detection of sinkholes and evidence of instability (scarps) even in forested areas by filtering. Automatic mapping over large areas (Miao, Qiu, Wu, Luo, Gouzie, & Xie, 2013; Rahimi & Alexander, 2013; Zhu, Taylor, Currens, & Crawford, 2014).

3D morphometric characterization.

Monitoring temporal changes and measuring subsidence rates.

Detection of subtle subsidence deformation as potential precursor of catastrophic collapse (Filin & Baruch, 2010; Filin, Baruch, Avni, & Marco, 2011).

InSAR (Synthetic Aperture Radar Interferometry)

Measuring remotely subsidence rates and ground deformation time-series over large areas. Small active sinkholes and rapid subsidence are generally overlooked. Allows obtaining retrospective deformation values (Abelson et al., 2003; Al-Fares, 2005; Baer et al., 2002; Castañeda, Gutiérrez, Manunta, & Galve, 2009; Closson, LaMoreaux, Abou-Karaki, & al-Fugha, 2007; Galve, Castañeda, & Gutiérrez, 2015; Paine, Buckley, Collins, Wilson, & Kress, 2009).

Detection of precursory deformation preceding collapse (Closson et al., 2003, 2005; Intrieri et al., 2015; Jones & Blom, 2014; Nof, Baer, Ziv, Raz, Atzori, & Salvi, 2013).


Detecting and locating subsurface gravitational deformation preceding the development of collapse sinkholes by recording shallow microearthquakes with seismographs (Dahm et al., 2011; Land, 2013; Land & Aster, 2008).

Ground-based monitoring

Precise levelling. Ground-based InSAR (Intrieri et al., 2015). Tiltmeters. Horizontal and vertical extensometers. Terrestrial LIDAR, real-time GPS networks (Kent & Dunaway, 2013). Optical time domain reflectometry (fiber optic technology) (Zhende, Xiaozhen, & Ming, 2013).

Hydrochemical modeling

Calculations with hydrogeochemical data to identify and assess quantitatively present-day dissolution processes conductive to sinkhole development, especially in evaporite karst (Acero et al., 2015; Campana & Fidelibus, 2015).


Speleological explorations

Examination and mapping of caves provide data on the distribution of accessible voids and the location of the points where the roof materials are affected by active deformation and internal erosion processes (cracking, collapse chimneys, sagging structures, sediment-filled pipes. and debris cones).

Anticipation of the location of future sinkholes (Andrejchuk & Klimchouk, 2002; Jancin & Clark, 1993; Klimchouk & Andrejchuk, 2005; Palmer, 2009; Parise, 2015; Parise &Trocino, 2005).

Geophysical surveys

Detection of anomalies, changes in the physical properties and geometrical features attributable to cavities, subsidence structures, irregular rockhead, or buried sinkholes. The type of karst setting largely determines the suitability of the different techniques (Stierman, 2004; Waltham, Bell, & Culshaw, 2005; Wightman & Zisman, 2008).

Provides the basis for better designing further drilling and trenching investigations and assessing safety condition for workers and equipment.

May be used for assessing and mapping sinkhole susceptibility (García-Moreno & Mateos, 2011; Margiotta et al., 2012; Samyn et al., 2014).

Most widely used methods include: electrical resistivity (Carbonel et al., 2014; Epting et al., 2009; Harro & Kruse, 2013; Neyamadpour et al., 2010; Park et al., 2014; Valois et al., 2011; Zhou, Beck, & Adams, 2002), ground penetrating radar (Batayneh et al., 2002; Frumkin, Ezersky, Al-Zoubi, Akkawi, & Abueladas, 2011; Pueyo-Anchuela et al., 2010; Rodríguez, Gutiérrez, Green, Carbonel, Horstmeyer, & Schmelzbach, 2014; Tallini et al., 2006), gravimetry (Ezersky et al., 2013; Kaufmann, 2014; Kaufmann & Romanov, 2009; Patterson et al., 1995; Tuckwell et al., 2008), magnetometry (Rybakov et al., 2005; Thierry et al., 2005), seismic reflection (Sargent & Goulty, 2009; Snyder, Evans, Hine, & Compton, 1989), seismic refraction (Higuera-Diaz et al., 2007; Valois et al., 2011), multichannel analysis of surface waves (Ezersky & Legchenko, 2014; Samyn et al., 2014).

Probing and drilling

Information on the nature and geotechnical properties of the ground.

Recognition of voids (loss of drilling fluid, lack of resistance; Patterson et al., 1995), buried sinkholes and sediments disturbed by subsidence processes (suffosion, collapse). Large cavities may be easily missed even with deep and closely spaced boring programs (Milanovic, 2004; Waltham & Fookes, 2003).

Subsurface characterization of sinkholes (limits, thickness of fill, depth of cavities and karstification zones, subsidence mechanisms).

Hydrogeological data; piezometric level and its variations, chemical (saturation index) and isotopic composition, flow rate, and direction (borehole flow meters; Song et al., 2012).

Downhole geophysical logging, cross-hole geophysics, and surveys with optical and acoustic cameras (Yuhr, Kaufmann, Casto, Singer, McElroy, & Glasgow, 2008).

Horizontal drilling in tunnels and mines to anticipate problematic zones (cavities, weak material, high permeability zones; Song et al., 2012).


Elucidating the origin of topographic features and geophysical anomalies of uncertain origin.

Defining the precise limits of sinkholes and subsidence structures.

Analyzing the subsidence mechanisms (deformation style) and the kinematical behavior (gradual vs. episodic).

Determining the age of sinkholes and subsidence episodes and calculating long-term subsidence rates (Carbonel et al., 2014, 2015; Gutiérrez et al., 2009, 2011).

Probably, the most innovative methodological advances developed in recent years are related to the acquisition of remote sensed geodetic data (LIDAR and InSAR) and the application of the trenching technique to the investigation of specific sinkholes in covered karst areas. Airborne LIDAR data (Light Detection and Ranging) has a great potential for the automatic mapping of sinkholes and the extraction of morphometric parameters (Fig. 21).

Figure 21. Shaded relief model of sinkholes in the Dead Sea coast, Israel, featuring their shape and dimensions.

Image courtesy of Sagi Filin.

The LIDAR technique allows accurate and rapid measuring features on the earth’s surface by emitting laser-light pulses and recording their returns. The light pulses can produce multiple returns from different reflection surfaces (e.g., tree canopy, ground surface). The automatic extraction of sinkholes from LIDAR data is commonly carried out through several steps in a Geographical Information System (GIS) platform (e.g., Filin, Baruch, Avni, & Marco, 2011; Miao, Qiu, Wu, Luo, Gouzie, & Xie, 2013; Zhu, Taylor, Currens, & Crawford, 2014): (a) Generating a high-resolution Digital Elevation Model (DEM) of the bare surface after removing the returns related to off-ground objects with a filtering algorithm (e.g., vegetation, buildings). (b) Delineating and extracting closed depressions using various algorithms and establishing threshold values (e.g., depth, area). The closed depressions can be extracted by substracting the original DEM from an additional DEM with filled depressions. (c) Filtering true sinkholes from the extracted closed depressions establishing thresholds for different geometric parameters (e.g., depth, area/depth ratio, circularity index), and considering spatial relationships with natural and anthropogenic features (e.g., streams, roads, non-karst bedrock). (d) Assessing the success rate by identifying true positives, false positives, and overlooked sinkholes. This can be carried out using detailed sinkhole maps produced by various methods, including visual examination of multiple remote sensed data and field inspection.

Doctor and Young (2013) compared depressions mapped automatically using LIDAR data with manually delineated sinkholes in a covered karst area of Virginia. The map produced through the fill-difference method overlooked around 30% of the sinkholes identified by visual inspection of aerial photographs and elevation models, mainly shallow depressions. Zhu et al. (2014), using LIDAR data in Kentucky, increased by a factor of four the number of sinkholes previously mapped with low-resolution topographic maps, attaining a success rate of 80–93%. Similar results were obtained by Rahimi and Alexander (2013) in Minnesota, where the actual number of sinkholes may be around four times higher than those depicted in previous maps. Here, automatic mapping of sinkholes with a LIDAR DEM yielded a success rate of 82%, and the proportion of missed sinkholes reached 9%. De Carvalho-Junior et al. (2014) applied a similar approach in Brazil, but using DEMs with much lower spatial resolution and accuracy generated from satellite data, obtaining a rather limited overall accuracy (40–50%).

A great advantage of the LIDAR technology is that it provides more accurate elevation data than photogrammetric methods and allows sinkhole mapping in densely forested areas (e.g., Kobal, Bertoncelj, Pirotti, & Kutnar, 2014; Miao et al., 2013). Moreover, DEMs generated with data acquired at different dates may be used to monitor the subsidence phenomenon and identify precursory deformation of collapse sinkholes, as illustrated in the Dead Sea area by Filin et al. (2011) (Fig. 22).

Figure 22. Incipient sinkhole expressed as a subcircular fissure (arrows) and a slightly settled area in recently exposed lake deposits in Hazanon area, Dead Sea, Israel. These surface deformation features reveal that the location of some collapse sinkholes may be anticipated by visual inspection and measuring precursory ground displacement through various methods such as airborne LIDAR. Image taken in 2011.

Some of the main drawbacks include that it does not allow the mapping of shallow depressions with depths lower than the vertical accuracy of the measurements (Faulkner, Stafford, & Bryant, 2013), or buried sinkholes, which may be recognizable in old aerial photographs and topographic maps. Attempts have also been carried out to map sinkholes semi-automatically with high-resolution aerial images. Dou et al. (2015) followed three main steps: (a) Image segmentation, grouping pixels into objects with homogeneous spectral and textural characteristics. (b) Object classification considering several features (e.g., tone, texture, shape). (c) Extracting the objects attributable to sinkholes by comparing their features with those of a case library of known sinkholes. Although the authors obtained satisfactory results in their study areas in China, the method requires a highly specific technical qualification and may generate a large number of false positives.

In SAR (Synthetic Aperture Radar Interferometry) is a geodetic method that measures the displacement of the ground surface using the phase difference between two radar acquisitions. Spaceborne radar data can be used to remotely assess sinkhole-related subsidence covering extensive areas. Moreover, the processing of multiple interferograms derived from a large set of radar images, including historical scenes, allows the generation of deformation time series including retrospective data. The main limitations of the technique include (e.g. Castañeda, Gutiérrez, Manunta, & Galve, 2009): (a) Loss of coherence in vegetated areas and zones affected by human alterations. This drawback can be locally overcome by installing artificial corner reflectors. The areas with appropriately oriented human structures and rock outcrops are generally the most favorable. Thus, the technique has yielded promising results for the monitoring of vulnerable human structures like dams (Closson, Karaki, Hussein, Al-Fugha, & Ozer, 2003) or high-speed railways (Galve, Castañeda, & Gutiérrez, 2015). (b) The spatial and temporal resolution of the deformation data is frequently insufficient for capturing active sinkholes of reduced size and/or characterized by catastrophic collapse. Nonetheless, the launching of new missions capable of acquiring radar data with much shorter revisit time and higher spatial resolution (such as TerraSAR-X, COSMO-SkyMed) is significantly contributing to reduce these constraints. Some authors have been able to detect precursory creep deformation preceding catastrophic collapse. Nof, Baer, Ziv, Raz, Atzori, and Salvi (2013) resolved subsidence kinematics during the pre-collapse and post-collapse stages of small collapse sinkholes in the Dead Sea (Fig. 22). Jones and Blom (2014) captured precursory surface deformation (>20 cm) before the sudden collapse of the ca. 110 m-diameter Bayou Corne sinkhole, in Louisiana, formed above a cavern generated by solution mining at more than 1,000 m depth. Recently, Intrieri et al. (2015), using high-resolution ground-based InSAR data, were able to measure precursory deformation (along the line of sight) in a road, allowing its closure before a collapse event on Elba Island, Italy. (3) The economic cost of the acquisition and processing of the data is frequently beyond the available budget, especially in the case of site investigations.

The trenching technique, mainly used in paleoseismology, has been recently applied to the investigation of active sinkholes in covered karst settings providing highly promising results (Figs. 23 & 24).

Figure 23. Cover sagging sinkhole in the city of Zaragoza, NE Spain, investigated by trenching (A) and ground penetrating radar (GPR), using 100 MHz unshielded antennas (B) and 180 MHz shielded antennas (C). The trench log shows an onlap arrangement in the sinkhole fill deposits, recording sinkhole expansion through time. Arrows in the radargrams point to the edges of the synformal structure. The 100 MHz unshielded antennas provide higher penetration profiles, but contaminated by above-surface reflections. Modified from Carbonel et al. (2014).

Figure 24. Trench excavated across a cover sagging and collapse sinkhole in the Ebro Valley, NE Spain.

The approach involves the analysis of the stratigraphic and structural relationships exposed in trenches in combination with geochronological data (retrodeformation analysis). This methodology provides a great deal of practical information on the subsidence phenomena difficult to achieve with other techniques, providing an objective basis for site-specific hazard assessments (Carbonel et al., 2014, 2015; Gutiérrez et al., 2009; GutiérrezGalve, Lucha, Castañeda, Bonachea, & Guerrero, 2011): (a) Elucidate the nature of geomorphic features or geophysical anomalies attributable to sinkholes. (b) Establish precisely the limits of sinkholes and the underlying subsidence structures. (c) Determine the subsidence mechanisms, assess quantitatively their contribution to the overall subsidence, and infer the spatial trend (e.g. sinkhole expansion). (d) Interpret the kinematic regime (gradual versus episodic) and quantify the cumulative subsidence and displacement-per-event values. (e) Calculate average subsidence rates and constrain the timing of subsidence events, especially the most recent event (MRE).

The geophysical methods most widely used in sinkhole investigation are ground penetrating radar (GPR) and electrical resistivity imaging (ERI), also called electrical resistivity tomography (ERT). These are synergistic near-surface exploration methods that enable the acquisition of complementary data (e.g. ; Carbonel et al., 2014; Frumkin, Ezersky, Al-Zoubi, Akkawi, & Abueladas, 2011; Kruse, Grasmueck, Weiss, & Viggiano, 2006; Nouioua et al., 2012). GPR provides profiles (radargrams) depicting electromagnetic wave reflections related to changes in the electromagnetic impedance of the subsurface materials. Thanks to its high vertical and horizontal resolution, under favorable conditions it allows accurate imaging of dissolution and subsidence features associated with sinkholes (e.g., cavities, sinkhole fills, collapse faults, fissures, sagging structures). Moreover, data acquisition is easy and fast compared with other methods (Rodríguez, Gutiérrez, Green, Carbonel, Horstmeyer, & Schmelzbach, 2014). However, it has a limited investigation depth and shows poor performance in areas underlain by highly conductive materials that attenuate the radar waves (e.g., clays and moist fine-grained sinkhole fills). ERI is a direct current geoelectrical imaging technique that measures spatial variations in the subsoil bulk resistivity by means of multi-electrode systems. It has much lower resolution than GPR, but higher penetration depth, and it records a broad resistivity range (e.g., Ezersky, 2008; Neyamadpour, Abdullah, Taib, & Neyamadpour, 2010; Park et al., 2014; Zhou Beck, & Adams, 2002). ERI may resolve relatively deep cavities and the root of subsidence structures (down to about 30 meters), whereas GPR may provide a detailed picture of shallow stratigraphic and structural indicators of subsidence.

Sinkhole Susceptibility, Hazard, and Risk Assessment

Sinkhole inventories, together with data on the factors that control sinkhole development, can be used as the basis to forecast the spatial and temporal distribution of future sinkholes and their characteristics. In the prognostic approaches based on past events, the underlying working hypothesis is that future sinkholes will have similar distribution patterns to those that occurred in the past (i.e., the past is the key to the future; reversed Uniformitarianism). Ideally, it would be desirable to assess, with a reasonable level of reliability, the probability of occurrence of sinkholes of each type and with different sizes at every location. Preferably, each sinkhole type should be analysed separately, since they are most likely controlled by different factors and have different distribution patterns and scaling relationships.

Depending on the information available, two types of models can be produced to predict the occurrence of future sinkholes: susceptibility models and hazard models. Susceptibility models represent the likelihood of a sinkhole occurring in any specific place in terms of relative probability (high, medium, low) (Fig. 25).

Figure 25. Example of a sinkhole susceptibility model in Hamedan region, Zagros Mountains, Iran. Susceptibility has been assessed by assigning relative weights to a set of controlling factors through the analytical hierarchy process. According to the model, the most susceptible zones essentially correspond to the areas underlain by carbonate rocks, where groundwater exploitation and water table are more significant.

Image courtesy of Dr. Kamal Taheri.

These models identify the a priori most and least hazardous areas. However, they do not provide quantitative probability values and consequently cannot be used as the basis for quantitative risk analyses. These are the types of predictions presented in most published works. Hazard models provide an estimation of the spatial-temporal probability of future sinkholes (Fig. 26).

Figure 26. Sinkhole hazard model for a sector of the Ebro Valley evaporite mantled karst indicating the spatial-temporal probability of cover collapse sinkholes. The hazard model has been generated transforming and independently validated susceptibility model, considering the temporal frequency of sinkholes in each equal-area susceptibility class (Modified from Galve et al., 2009).

That is, the probability for a given zone and time interval of being affected by a sinkhole event (sinkholes km-2 yr-1). Chronological information on the analyzed sinkholes, either a precise age or an age interval, is indispensable to calculate temporal frequency values (Beck, 1991; Galve et al., 2009; Parise & Vennari, 2013; Taheri, Gutiérrez, Mohseni, Raeisi, & Taheri, 2015; Tolmachev & Leonenko, 2011). In most cases, the calculated spatial-temporal probability values correspond to minimum or optimistic hazard estimates, since they are commonly derived from incomplete sinkhole inventories. Ideally, hazard models should incorporate magnitude and frequency scaling relationships accounting for the probability of occurrence of sinkholes with different diameters in each hazard zone (Galve, Remondo, & Gutiérrez, 2011). The development of these spatially distributed hazard models requires a large amount of data that rarely can be obtained. Other alternatives include considering an average sinkhole diameter and assuming a Poisson distribution (Tolmachev & Leonenko, 2011; Yolkin, 2015), or producing magnitude and frequency relationships for the whole study area, which would indicate the average temporal frequency of sinkholes with different diameters (Taheri et al., 2015) (Fig. 20). These scaling relationships typically follow a logarithmic distribution, like many other hazardous processes (Gutiérrez & Lizaga, 2015; Taheri et al., 2015; Tolmachev & Leonenko, 2011). Quantitative hazard estimates are essential for risk assessments, cost-benefit analyses of mitigation strategies, evaluation of insurance policies, or pre-purchase appraisal of land.

Susceptibility Models

Sinkhole susceptibility maps can be produced through several methods: (a) Direct mapping of susceptibility zonations based on expert criteria (Ardau, Balia, Bianco, & De Waele, 2007; Edmonds, Green, & Higginbottom, 1987). These maps have a significant subjective component related to the expert judgements, are not reproducible, and may lack an objective basis for substantiating the distribution and boundaries of the susceptibility zones. (b) The deterministic models are based on stability analyses that take into account a number of parameters involved in the subsidence processes (Koutepov, Mironov, & Tomachev, 2008). These models considerably simplify the complexity of the subsidence processes, are generally static, incorporate geometrical suppositions, and require a large amount of geotechnical data that is difficult and expensive to obtain, especially when analyzing large and heterogeneous areas. (c) Susceptibility models may be derived from parameters related to the spatial distribution of the inventoried sinkholes, including sinkhole density, distance to the nearest sinkhole, or preferred alignment and elongation directions. Generally, the underlying assumption of the susceptibility models based on sinkhole density, either number of sinkholes per unit area or percentage area affected by sinkholes, is that the likelihood of sinkhole occurrence is higher in the areas with higher sinkhole density (Angel, Nelson, & Panno, 2004; Brook & Allison, 1986; Galve, Gutiérrez, Remondo, Bonachea, Lucha, & Cendrero, 2009a; Kemmerly, 2007; Ogden & Reger, 1977). When using sinkhole density to appraise susceptibility, it should be borne in mind that the density values in geomorphic surfaces of different ages, or in areas where sinkholes have a variable preservation potential, are not directly comparable (e.g. Gutiérrez et al., 2007). The distance of each point to the nearest sinkhole may be used to assess susceptibility assuming that the likelihood of sinkhole occurrence increases with the proximity to existing sinkholes (Gao, Alexander, & Barnes, 2005; Galve, Gutiérrez, Remondo, Bonachea, Lucha, & Cendrero, 2009a; Galve et al., 2009). The practicality of this approach may be explored through the calculation of indexes such as the Nearest Neighbour Index (Clark & Evans, 1954), which allows the quantification of the degree of clustering-dispersion of the sinkholes. These spatial distribution indexes may be also applied to test whether new sinkholes tend to occur in the vicinity of the previously existing sinkholes or not (Denizman, 2003; Drake & Ford, 1972; Galve et al., 2009a; Gao, Alexander, & Lei, 2001; Gutiérrez-Santolalla, Gutiérrez-Elorza, Marín, Desir, & Maldonado, 2005; Hyatt, Wilkes, & Jacobs, 1999; Kemmerly, 1982; Magdalene & Alexander, 1995; McConnell & Horn, 1972; Palmquist, 1979; Williams, 1972). In areas where sinkholes are structurally controlled, showing statistically significant preferred orientations and alignments, the belts of land defined by two or more sinkholes aligned following a prevalent trend may be classified as more susceptible (Gutiérrez-Santolalla, Gutiérrez-Elorza, Marín, Desir, & Maldonado, 2005). The same concept can be applied where sinkholes occur associated with lithological contacts (contact karst) (e.g. Farrant & Cooper, 2008). An alternative group of methods of susceptibility assessment incorporate data on variables that control sinkhole development. (d) The heuristic approach involves establishing susceptibility classes by judging the relative contribution of a number of variables on sinkhole formation. Some authors differentiate susceptibility classes establishing threshold values for specific variables and using decision tree models (Gao & Alexander, 2003; Kaufmann & Quinif, 2002). Another widely used approach is to apply a weighting or scoring system to a group of conditioning factors (Brook & Allison, 1986; Buttrick & van Schalwyk, 1998; Dai, Lei, Liu, Tang, & Lai, 2008; Edmonds, 2001; Farrant & Cooper, 2008; Forth, Butcher, & Senior, 1999; Jiang, Lei, Li, & Dai, 2005; Kaufmann, 2008; Khanlari, Heidari, Momeno, Ahmadi, & Beydokhti, 2014; Lei, Jiang, & Yu, 2001; Ogden, 1984; Thorp & Brook, 1984; Taheri et al., 2015; Tolmachev & Leonenko, 2005; Tolmachev, Maximova, & Mamonova, 2005; van Rooy, 1989; Zisman, 2001) (Fig. 25). The main disadvantage of the heuristic methods is the subjective component of the susceptibility assessments. (e) The probabilistic methods allow the construction of susceptibility models analyzing the statistical relationships between the spatial distribution of known sinkholes and that of a set of controlling factors, and in some cases, the interrelationships among the factors. Several papers present bivariate analyses quantifying the spatial relationships between sinkholes, or parameters derived from this data layer (e.g., sinkhole density, distance to the nearest sinkhole), and specific variables governing their distribution (Hyatt,Wilson, Givens, & Jacobs, 2001; Orndorff, Weary, & Lagueux, 2000; Palmquist, 1977; Whitman, Gubbels, & Powell, 1999). These analyses were aimed at assessing the contribution of variables to the development of sinkholes, rather than to the production of susceptibility models. More recent publications present susceptibility models based on the statistical relationships between the sinkholes and highly diverse controlling factors applying different mathematical frameworks; favorability functions (Galve et al., 2009a; Galve, Remondo, & Gutiérrez, 2011), logistic regression (Ciotoli et al., 2015; Lamelas, Marinoni, Hoppe, & de la Riva, 2008), frequency ratio (Pradhan, Abokharima, Jebur, & Tehrany, 2014; Yilmaz, 2007), evidential belief function (Pradhan et al., 2014). The main advantages of these methods include their objective statistical basis, reproducibility, ability to quantitatively analyze the contribution of factors to sinkhole development, and their potential for continuous updating. These statistical techniques have been applied satisfactorily to landslides because data on the main conditioning factors (e.g., slope, lithology, land use) can be gathered easily. Conversely, in the case of sinkholes, the generation of sound probabilistic and heuristic models is more challenging due to the limited availability of information on the variables that control the subsidence phenomena, some of which are difficult and expensive to obtain due to their subsurface nature.

Prediction Capability of Models

The predictions on the future spatial distribution of sinkholes presented in sinkhole susceptibility models, regardless of the applied methodology, should be considered as un-tested hypotheses, however reasonable they might be. A susceptibility model developed through a complex and sophisticated methodology, but with a limited prognostic capability, may lead to inadequate planning, the application of ineffective mitigation measures and severe losses. The prediction capability of the models should be evaluated quantitatively and independently before their incorporation in the risk management process. Model evaluation implies comparing the distribution of susceptibility zones defined in a model with that of an independent sinkhole sample not used for the development of the model (Buttrick et al., 2011; Ciotoli et al., 2015; Galve et al., 2009a; Pradhan et al., 2014; Taheri et al., 2015). Commonly, sinkholes are split into two samples, one for modeling (training set) and the other one for carrying out the independent evaluation (testing set). Preferably, the testing set should correspond to a temporal sinkhole population developed under similar conditions to the present-day ones (sinkholes that have occurred in the last decade).

The cross-validation results can be presented quantitatively and graphically by means of confusion matrices and their derived statistics, receiver-operating characteristic (ROC) plots, and prediction-rate curves (PRC) (see Beguería, 2006 for discussion). Model evaluation through the calculation of statistical indexes or the construction of prediction curves allows procurement of the following practical information: (a) Quantitative assessment of the prediction capability of the model. (b) Identifiction of the prediction approach or mathematical functions that yield better predictions (Pradhan et al., 2014). Galve et al. (2009a) compared the predictive capability of multiple sinkhole susceptibility models produced by different methodologies, including probabilistic analyses, a heuristic approach, sinkhole density, and distance to the nearest sinkhole. Interestingly, independent evaluation revealed that the models based on the simplest methods (sinkhole density and proximity), without requiring data on the causal factors, are the ones that provide the most reliable spatial predictions and the highest benefit/effort ratio. (c) Assessment of the ability of the model to discriminate the most dangerous zones and, most importantly in many cases, the safest areas; lower and upper segments of the prediction-rate curve. (d) Selection of the most significant variables and evaluation of their contribution to the prediction/formation of sinkholes, providing clues on their genesis. This information may be highly valuable for the selection of mitigation measures. (e) Analysis of the effect of the accuracy of input variables on the models, helping to improve the quality/effort ratio in the commonly tedious and expensive data-gathering process.

Hazard Models

In areas where there is chronological information available on the inventoried sinkholes, the susceptibility models, once independently validated, can be transformed into hazard models considering the frequency of sinkholes in each susceptibility class (Galve et al., 2009, 2011) (Fig. 26). The resulting models generally provide minimum hazard estimates, since sinkhole inventories are rarely complete. Additionally, in case there is information on the size (diameter) of the sinkholes, there is also the possibility of incorporating an empirical magnitude and frequency relationship in the hazard model or an average diameter. Such hazard models provide estimates on the probability of occurrence of sinkholes with different diameters in each portion of the territory (Galve et al., 2011; Tolmachev & Leonenko, 2011). The ergodic assumption may be applied in case there is limited information on the frequency of rare large-magnitude sinkholes. That is, expanding virtually the length of the temporal record by enlarging the area, substituting time by space.

The magnitude and frequency scaling relationships constitute a relevant aspect for risk management, since the capability of a subsidence event to cause damage (sinkhole risk) and the cost-effectiveness of mitigation measures depend largely on the area affected by subsidence. For instance, one sinkhole 10 m in diameter impacts a much larger area (78.5 m2) than ten sinkholes 2 m across (31.4 m2). In Russia, where karst lands occupy around one third of the territory, national building guidelines recommend assessing sinkhole hazard considering six categories of probability and four categories of average sinkhole diameter (Tolmachev & Leonenko, 2011). Regardless of the methods used to develop and evaluate the sinkhole models, it is important to take into account that the reliability of the predictions may decrease substantially through time, especially in those areas where sinkholes are largely controlled by changeable human factors.

Risk Assessment

The expected annual sinkhole damage (e.g., euro yr-1, injuries or fatalities yr-1) can be calculated through the risk equation (modified after Crozier & Glade, 2005; Yolkin, 2015):

Risk=Hazard x Probability of Impact x Exposure x Vulnerability

where hazard is the annual probability of occurrence of a sinkhole in the study area. The probability of impact accounts for the likehood of a sinkhole interacting with a human element (spatial and temporal coincidence). Exposure corresponds to the elements at risk (monetary value, number of people). Vulnerability, also referred to as consequence, corresponds to the expected degree of damage in case a sinkhole impacts on a human element, ranging from 0 (no damage) to 1 (total damage). Vulnerability is a function of multiple variables, including sinkhole type and size. Relationships can be constructed establishing a correspondence between vulnerability and the intensity of the hazardous process (e.g., sinkhole diameter). It can be assessed on the basis of data about economic and human losses caused by sinkholes in the past or by numerical modeling. As a simplified theoretical example, let’s consider a 1 km2 study area with a road section covering 1 ha. The estimated probability of occurrence of sinkholes is 15 sinkholes km-2 yr-1. Here, collapse sinkholes have diameters ranging from 2 to 10 m. The road section has a value of 800,000 euros and vulnerabilities of 0.05 and 0.1 when impacted by sinkholes 2 m and 10 m across, respectively. Annual direct economic losses can be roughly estimated as follows:

Risk = 15  x (104 /106) x 800,000 x (from 0.05 to 0.1) = 6,000 - 12,000 euros/yr-1

Nonetheless, sinkholes may cause direct and indirect losses. For instance, where transportation infrastructure is affected by a collapse, the direct risk corresponds to the cost of repairing or reconstructing the structure and the injuries or fatalities caused by the subsidence event. The impact on the economic productivity caused by the temporal loss in serviceability, as well as the resulting delays in the transportation of people and goods, account for the indirect risk. Indirect losses, although difficult to identify and estimate, are frequently higher than the direct damage and are rarely covered by sinkhole insurance. Risk models preferably should indicate the expected economic and human losses due to sinkhole activity in each portion of the territory. These models allow the identification of the areas where sinkhole-related damage is expected to reach higher values and where the application of mitigation measures might yield higher benefit/effort ratios. Risk estimates can be also compared with established acceptable risk values to evaluate whether or not sinkhole mitigation measures should be applied (e.g. Tolmachev & Leonenko, 2011).

Cost-Benefit Analyses

Cost-benefit analyses can be performed to identify the optimum mitigation strategies from the economic perspective and their expected cost-effectiveness (Cooper & Calow, 1998; Galve, Gutiérrez, Guerrero, Alonso, & Ignacio, 2012). Cost-benefit analyses involve comparing the sinkhole-related costs generated over the lifetime of the project for the “without mitigation” scenario and the multiple “with mitigation” scenarios. Different mitigation strategies and engineering solutions may be considered in the latter. The costs computed in the “without mitigation” scenario correspond to the direct and indirect losses caused by sinkholes. The expenditures considered in the “with mitigation” scenarios are the extra investment on mitigation plus the direct and indirect damage caused by sinkholes that cannot be prevented with the applied measures (residual risk). For the estimation of the economic losses in future years, a discount factor is applied considering the time value of the money. The cost-effectiveness of a particular mitigation measure can be assessed calculating the financial index called Net Present Value, which is the amount of money the investment on the mitigation measure is worth, taking into account its cost, losses saved, and the time value of the money. By means of a cost-benefit analysis, Galve et al. (2012) identify the most profitable geosynthetic design for a road built in a sinkhole-prone area and assess its costs-effectiveness. This cost-benefit analysis considers: (a) The probability of occurrence of sinkholes with different diameters in each road section; (b) The stability of the road sections without geosynthetics or protected with geosynthetics of different resistances; (c) The expected direct and indirect economic losses for the different scenarios.

Sinkhole Risk Mitigation

The deformation of the ground related to active sinkholes may compromise the integrity of any human structure, including buildings, linear infrastructure, such as roads, railways, pipelines, canals (Fig. 27), dams (Fig. 18), and even nuclear power stations (e.g., Neckarwestheim, Germany, built upon karstified Triassic evaporites) (Table 3).

Figure 27. Examples of sinkholes impacting on human structures. (A) Cover collapse sinkhole occurred on November 2003 next to and beneath a five-story building in Calatayud city, NE Spain. This single sinkhole event lead to the demolition of the building, with direct economic losses estimated at ca. 5 million euro. (B) Cover collapse sinkhole suddenly formed within a factory in the Ebro Valley, close to Zaragoza city. Image taken on March 2001. (C) Cover collapse sinkhole formed on March 2003 affecting the high-speed Madrid-Barcelona railway in the vicinity of Zaragoza city. The image shows a truck pouring cement in the bucket of a backhoe for filling the depression. The sinkhole formed within a pre-existing subsidence structure with geomorphic expression. Arrow points to tilted Quaternary alluvium. (D) The Santa Ana canal disrupted by a sinkhole in the Noguera Ribagorzana valley, Spanish Pyrenees. Image taken in May 2003.

Furthermore, sudden collapse sinkholes may cause human life loss. The most infamous event corresponds to a collapse sinkhole induced in 1962 by dewatering for gold mining in the Far West Rand of South Africa, which engulfed a three-story crusher plant with the loss of 29 lives (Bezuidenhout & Enslin, 1970). The probability of a sinkhole forming right beneath a vehicle in a transportation structure is generally low, but the likelihood of an accident in case the structure is disrupted by a collapse is considerable. The application of risk mitigation measures, either of a preventive or corrective nature, is commonly justified from the economic and/or social perspective.

Table 3. Major Damaging Sinkhole Events. C: Carbonate karst, E: Evaporite karst.




Subsidence phenomenon


Relevant factors


1962 onwards

Zaragoza, Spain


Collapse and sagging sinkhole more than 100 m in diameter

Factory damaged and demolished. Building with 100 flats constructed in 2003 on well-known sinkhole. Euro € 30 M of compensation for owners

Known active sinkhole with infamous precedents obviated by decision makers

Gutiérrez et al. (2009)


West Driefontein Mine, Far West Rand, South Africa


Sudden bedrock collapse sinkhole, 55 m across

Engulfed a three-storey crusher plant with the loss of 29 lives

Induced by dewatering for gold mining

Bezuidenhout & Enslin (1970)


Liangwu village, Guixian, Guangxi, China


157 collapse sinkholes within an area 1800 m long and 250 m wide

Village abandoned

Induced by explosions conducted for groundwater exploration

Daoxian (1987)


Blyvoorruitzicht, Far West Rand, South Africa


Bedrock collapse sinkhole

Four houses damaged, with the loss of five lives

Induced by dewatering for gold mining

Bezuidenhout & Enslin (1970)


Bratsk Reservoir, Siberia


Numerous sinkholes

Severe damage to multiple buildings and infrastructure

Reactivation of gypsum karst by reservoir impoundment and associated permafrost thawing

Trzhtsinsky (2002)


Hutchinson, Reno County, Kansas


Cover and bedrock collapse sinkhole 90 m in diameter and 15 m deep (Cargill sink)

Missouri-Pacific railways suspended above the crater

Collapse of a cavern spanning 400 m and created by solution mining since 1908 at about 130 m below the surface

Johnson (2005)


Puilatos village, Gállego Valley, Spain


Widespread sinkhole activity

Complete evacuation of village and subsequent demolition

Presence of halite beds a shallow depth

Gutiérrez et al. (2008b)


Keban Dam, Firat River, Turkey


Sinkhole formed during impoundment on the left abutment and connected to a large cavern. Losses reached record values of 26 m3/s

Costly remedial works (cavern filling and watertightness treatment of the surface) and delay in reservoir operation

Induced by reservoir impoundment

Milanovic (2004)


Winter Park, Florida


Cover suffosion-collapse sinkhole 106 m across and 30 m deep

Destruction of streets, utilities, one house and several businesses

Accelerated by decline of the piezometric level by pumping

Ford & Williams (2007)

1982 onwards

Lisan Peninsula, Dead Sea, Jordan


Multiple sinkholes and large subsidence areas related to salt dissolution

Recurrent damage on large evaporation ponds for potash salt (>$40 million)

Induced by lake level decline and pond inpoundment

Closson & Karaki (2015)


Kuwait City, Kuwait


Three cover and bedrock collapse sinkholes up to 15 m across and 31 m deep

Evacuation of 133 houses

Goodings & Abdulla (2002)


Allentown, Pennsylvania


Two cover collapse sinkholes 9-15 m across beneath a street, office building (400 employees) and multi-story car park

Affected buildings demolished. More than $8 million worth of damage

Accelerated by the rupture of water pipes

Waltham, Bell & Culshaw (2005)


Fredericks Valley, Maryland


Cover collapse sinkhole 9 m wide

Accident on route 31 with one fatality. Compensation of $10.1 M

Martin (1995)


Camaiore, Italy

C, E

Cover collapse sinkholes 30 m across and 18 m deep

Destruction of several houses

Formed five days after a Mw 4.8 earthquake with epicentre located at 50 km

Buchignani et al. (2008)


Oviedo, Spain


Catastrophic collapse sinkholes

Demolition of one block with multi-storey buildings. Euro € 18 million

Dewatering for excavation

Pando et al. (2013)


Calatayud, Spain


Cover collapse sinkhole 6 m in diameter and 10 m deep

Demolition of five-storey building with 52 flats. Direct losses estimated at ca. Euro € 4.8 million

No clear triggering factor

Gutiérrez et al. (2008b)


Maohe village, Liuzhou, Guangxi, China


41 sinkholes, 11 large subsidence areas and numerous ground fissures

Damage on 143 residential housed (69 collapsed). 1830 people relocated

Event triggered by heavy rainfall

Lei et al. (2013)


Assumption Parish, Louisiana


Rapidly expanding sinkhole more than 350 m in diameter accompanied by methane gas escape

Around 350 residents affected by long-term evacuation. Lawsuit involving around $50 million

Collapse of a cavern more than 1,000 m deep at the edge of a salt diapir created by solution mining

Jones & Blom (2014)


Seffner, Florida


Abrupt cover collapse sinkhole a few meters in diameter beneath a house

Person entombed while he slept

Filled and subsequently reactivated in 2015

Mass media


Disney World, Lake County, Florida


Collapse sinkhole 30 m across

Three-storey building collapsed and 36 evacuated. No injuries

Mass media

Sinkhole risk management needs to be tackled through the synergistic integration of multidisciplinary teams. Several strategies may be adopted to eliminate or reduce the economic and social risk related to sinkhole activity. The safest option is to avoid the dissolution and subsidence features and the sinkhole-prone areas. An ample set-back distance should be established around the sinkhole edges, especially when there is some uncertainty regarding the precise boundaries of the subsidence structures and the underlying karstification zones (Zhou & Beck, 2008) (Fig. 5). This preventive measure may be applied by prohibiting or restricting development in the most hazardous areas through land-use planning and regulations based on sinkhole susceptibility and hazard maps (Buttrick, van Schalkwyk, Kleywegt, & Watermeyer, 2001; Paukstys, Cooper, & Arustiene, 1999; Richardson, 2003). However, prohibiting development in potentially hazardous areas is not practically feasible in many cases. For instance, between four and five million South Africans currently reside or work on sinkhole-susceptible dolomite land (Buttrick et al., 2011). When subsidence-prone areas are to be occupied by people or engineering structures, the risk should be assessed and mitigated in case it exceeds acceptable levels. Mitigation may be aimed at reducing the activity of the processes (hazard), the vulnerability of the human elements, or both. Frequently, controlling subsurface dissolution and subsidence processes involved in the generation of sinkholes is a difficult and uncertain task, and consequently, effective mitigation may require careful local planning and the incorporation of subsidence-resistant engineering designs. Some countries and regions have developed regulations and guidelines related to unstable ground in karst areas establishing investigation standards, recommendations, or constraints on the type of development and indications related to engineering designs, precautionary measures, and monitoring programs (Buttrick et al., 2001; Cooper et al., 2011; Heath & Constantinou, 2015; Paukstys et al., 1999; van Schalkwyk, 1998). Risk assessments and cost-benefit analyses based on sinkhole hazard models may be used for estimating the cost-effectiveness of different mitigation measures and for selecting the most economically and socially adequate one.

Some corrective measures aimed at reducing sinkhole hazard include: (a) Prevent or control water withdrawal and the decline of the water table (magnitude and number of fluctuations), especially when situated close to or above the rockhead. (b) Control irrigation to reduce the extra ingress of water to the ground. (c) Avoid surface soak-aways and install soak-aways and recharge wells cased below rockhead to prevent artificial water circulation through cover deposits and suffosion (Waltham & Fookes, 2003). (d) Line canals and ditches with impervious material. (e) Construct gutters and downspouts around buildings (Zisman, 2013). (f) Use flexible pipes with telescopic joints. In a dolomite karst area covering around 3,700 ha in Gauteng Province, South Africa, around 99% of the 650 new sinkholes reported between 1984 and 2004 were associated with leaking water-bearing infrastructure. Ground movement events were reduced by 90% after rigorous implementation of a hazard mitigation strategy (Buttrick et al., 2011). (g) Use efficient drainage systems and divert surface drainage (Zhou, 2007). (h) Reduce infiltration by blanketing the surface and rock outcrops with geosynthetics or shotcrete. (i) Fill cavities in the rock or soil by grouting (Kannan, 1999) or sealing the covered rockhead with cap grouting (Fig. 28).

Figure 28. Engineering measures that can be applied to reduce sinkhole hazard and prevent or ameliorate subsidence on human structures.

Pressurized water or air may be used to wash out the fine-grained sediments in the rock voids and surface before grouting (Milanovic, 2004). The main disadvantage of grouting is that it may block most of the flow paths, favoring back-flooding and focusing on internal erosion and dissolution (Cooper, 1998; Zhou & Beck, 2008). Large cavities may be filled with rock fills through shafts or large diameter boreholes (Milanovic, 2004) (Fig. 28). (j) Improve the ground with compaction grouting to increase the strength and bearing capacity of the soil (Figs. 28 and 29).

Figure 29. The conventional Zaragoza-Barcelona railway affected by an active sinkhole in the vicinity of El Burgo de Ebro, NE Spain. At this site, on 11th September 2011, a collapse sinkhole caused the derailment of a freight train. A: Southern flank of the structure reinforced by iron beams driven into the ground. B: Northern side of the structure with inclined borings and pipes used for compaction grouting.

(k) Prevent the inlet of water in swallow holes (ponors) and sinkholes by clogging them, constructing annular dikes, or installing concrete plugs that may be equipped with one-way valves in the case of estavelles (swallow holes that may function as springs during high water table periods) (Milanovic, 2004). (l) Apply dynamic compaction in order to collapse shallow cavities and detect soft material associated with karst features (Fischer, Fischer, & Greene, 1993) (Fig. 28). (m) Remediate sinkholes. Zhou and Beck (2008, 2011) propose several sinkhole remediation methods. The alternatives for the treatment of the sinkhole throat in shallow sinkholes (<5 m; depth reachable by a backhoe or trackhoe) include: (a) Excavating the throat and plugging it with large blocks and concrete or grout, and (b) excavating and filling the fractures by dental filling with grout. The throat of sinkholes too deep for excavation equipment may be treated by (a) compaction grouting, (b) jet grouting, or (c) cap grouting. The next step is to fill the sinkhole depression. Initially, the bottom and walls may be lined with a geotextile filter fabric, and a drainage structure is constructed if necessary. The sinkhole may be filled with compacted clay or granular material, with layers forming a fining-upward sequence following the inverted filter concept. The filled sinkhole is commonly capped by a layer of compacted clay or a rubber membrane, which may have a convex geometry with centrifugal slope. The cap may be also constructed with reinforced concrete in case it has to act as the foundation for a structure (e.g. Hunt, Smith, Adams, Hiers, & Brown, 2013) (Fig. 30).

Figure 30. Remediation of a cover collapse sinkhole developed on January 2012 within a stormwater retention pond at Arbor Trails, Texas. The works included the following steps: (1) excavation of the sinkhole to expose the rockhead; (2) lining the depression with a filter fabric (A); (3) filling the depression with boulders and layers of graded gravels applying the inverter filter concept (A and B); (4) capping the sinkhole with a geomembrane and a reinforced concrete slab (C and D); and (5) covering the cap with a compacted clay liner and a geomembrane. See additional explanations in Hunt et al. (2013).

Image courtesy of Brian Hunt.

Structures may be protected from sinkhole subsidence by different types of engineering measures. A critical design parameter is the maximum diameter of the sinkholes at the time of formation, as it determines the distance that has to be spanned to prevent deformation or collapse of the engineered structure. This parameter may be obtained from sinkhole inventories, the geological record, or geomechanical simulations (e.g. Makhnatov & Utkin, 2015). Special foundations for buildings include rafts, slabs, strips, and ring beams of reinforced concrete. These are strong foundations that distribute the load of the structures over large areas. Beam extensions to these foundations, especially at the corners of the structures, can offer more protection and prevent a cantilever situation on the edges of the structures. Skin-friction and end-bearing piles are commonly used to transfer the structural load to the soil cover or solid bedrock, respectively. Another option is the jackable foundations that allow leveling light structures (Cooper & Gutiérrez, 2013; Waltham et al., 2005). Transportation structures like roads and railways can be reinforced by installing geosynthetics with high tensile resistance in the sub-base and embankments (Briançon & Villard, 2008; Cooper & Saunders, 2002; Galve et al., 2012; Jones & Cooper, 2005). This technique temporarily prevents the formation of catastrophic sinkholes and accidents, serving as a warning system that allows the identification of subsurface cavities expressed as sags in the structure. A road section built upon a pre-existing sinkhole in Germany was reinforced with geosynthetics designed to span cavities up to 15 m in diameter. Eventually, the reactivation of the sinkhole caused sagging in the road which allowed the suspension of the traffic around 45 minutes before the formation of a collapse sinkhole 20 m across (Alexiew, Schröer, & Herold, 2006). Another alternative is the construction of ground bridges, such as reinforced concrete slabs and rafts (Cooper & Saunders, 2002). An added degree of security can be gained by piling the direct foundations. In areas with thin unconsolidated cover, the mantling soil may be excavated to expose the rockhead irregularities (pinnacles and cutters) and the shallow cavities. The karst openings may be sealed with rock fills, concrete, or with slush grouting (dental grouting; Fig. 28). Subsequently, the footings may be pinned to firm bedrock and the excavated area backfilled with engineered fills (Fischer et al., 1993; Knez & Slabe, 2004; Zhou & Beck, 2008). Sinkhole-resistant bridges can be built incorporating oversized foundation pads in the piers and a sacrificial pier design, so that the structure will withstand the loss of a supporting pier (Cooper & Saunders, 2002; Waltham et al., 2005).

Non-structural measures aimed at reducing economic losses and harm to people include (a) Insurance policies to spread the cost generated by sinkholes among the owners at risk. According to Zisman (2013), sinkhole coverage was included in standard homeowner’s insurance policies in Florida, where sinkhole claims are the most costly, following those related to hurricaines. Florida has statutes for the regulation of sinkhole insurances and the controversial resolution of claims. Commonly, litigations arise between homeowners and insurance companies due to the difficulty of demonstrating that distress on buildings is unambiguously due to sinkhole activity. Unfortunately, the Florida sinkhole statute was repealed in 2013. (b) The installation of monitoring and warning systems in critical locations (piezometers, strain gauges, geodetic measurements, seismometers, laser and light transmitters, and receptors) (Kent & Dunaway, 2013; Galve et al., 2015; Tolmachev, Pidyashenko, & Balashova, 1999). (c) Educational programmes oriented to inform the public and decision makers about the likelihood of sinkhole occurrence, in order to improve risk perception and awareness. (d) Active and passive self-protection measures adopted by individuals (Fig. 31)

Figure 31. Local people in some areas of the Ebro Valley, NE Spain, used to work with a high-strength stick tied on the shoulders or the waist to prevent being swallowed by sudden collapse sinkholes

(e) The installation of fences and warning signposts in specific sinkholes and sinkhole-prone areas.

Future Challenges

In the last few years, sinkhole hazards have received increased interest by the scientific and technical community, as well as by the general public. This trend may be attributed to several factors, including: (a) a general move in the focus of earth scientists from the old geological records to environmental problems and active hazardous processes with societal implications; (b) rapid technological development, that allows the application of new tools (e.g., remote sensing, GIS) in geohazard analysis; (c) substantial increase in the frequency of damaging sinkholes in numerous areas, mainly related to adverse human alterations; (d) higher visibility of the problem provided by the media and divulgation platforms (such as a documentary on sinkholes, Sinkholes—Buried Alive, by NOVA) stimulated by several high impact sinkhole events (e.g., Bayou Corne in Louisiana, as well as Seefner and Disney World in Florida) (Table 3). Despite the recent rise in the scientific production related to sinkholes, there is still ample room for knowledge improvement, technical innovation, and the development of effective risk analysis and management procedures. Some potential challenges for the future are indicated below:

Develop approaches and criteria to reliably differentiate between sinkholes related to subsurface dissolution and enclosed depressions generated by non-karstic processes (piping, liquefaction, permafrost thawing, ravelling above porous material and extensional fissures, man-made excavations, internal erosion associated with disrupted water mains).

Disentangle whether the problematic sinkholes are related to subsidence induced by active subsurface dissolution, or to internal erosion and/or gravitational deformation above relict cavities formed in the past and currently not affected by solutional enlargement.

Investigate the long-term history of sinkholes, taking advantage of the high preservation potential of their sedimentary fill (i.e., enclosed sediment traps). This may help to better understand the role played by natural and anthropogenic factors on their development and the impact of the Anthropocene on karst environments and sinkhole activity.

Gain deeper insight into the role played by salt dissolution on sinkhole development in areas underlain by evaporite formations. In these contexts, dissolution subsidence is often misleadingly ascribed to gypsum karstification because the high-solubility salts (e.g., halite, glauberite) rarely crop out at the surface. Their identification requires specific investigation methods such as deep boreholes drilled with saline water and expert core logging.

Most investigations related to development projects rely largely on the application of classical site-specific geotechnical methods. Due to the complexity of karst systems, the study areas should be significantly expanded, and the investigations should incorporate other less conventional approaches, such as the analysis of old subsidence structures from the geological record and speleological explorations. These may provide highly valuable information on the subsidence phenomena (mechanisms, sinkhole dimensions) at a low cost. Accessible caves offer the opportunity to examine actively forming sinkholes from beneath and identify locations and zones where new sinkholes are expected to occur in the near future.

Construct and update comprehensive sinkhole inventories including data on the timing of the subsidence events. The lack of chronological data precludes calculating sinkhole hazard (spatial-temporal frequency). Preferably, sinkhole inventories should be accessible for the general public.

Explore methods for the precise mapping of the sinkhole edges and the underlying subsidence structures (trenching) and develop approaches for the establishment of set-back distances based on objective data.

Improve our capability to foresee the impact of anthropogenic alterations in the hydrological systems on sinkhole hazard, particularly water-table decline and reservoir impoundment.

Assess quantitatively and independently the prediction capability of sinkhole susceptibility and hazard models using data on sinkholes formed after their development. It may come out that some of the models lack validity and have resulted in improper risk management. These potential situations offer an excellent opportunity to explore the weaknesses of the prediction models and the underlying approaches.

Develop magnitude and frequency relationships, and where possible, incorporate them into spatially distributed hazard models. This implies taking into account one of the factors with higher influence on the damaging potential of subsidence events (i.e., sinkhole diameter).

Incorporate indirect damage in risk assessments to avoid significantly underestimating the true economic impact of the sinkholes. Detrimental indirect effects, including off-site ones, usually account for greater damage than the direct consequences.

Monitor subsidence activity utilizing multiple techniques, including those applied to the investigation of other ground instability phenomena, like slope movements (e.g., ground-based LIDAR, fiber-optic technology), and assess their capabilities, limitations, and complementarity.

Develop real-time monitoring and early-warning systems capable of detecting subtle ground deformation preceding catastrophic collapse for the application of precautionary measures (e.g., evacuation, service interruption in infrastructure) mainly aimed at avoiding damage to people. The implementation of this type of non-structural mitigation measure would be highly advisable at critical locations or zones associated with highly vulnerable infrastructure such as high-speed railways, airports, or nuclear power stations. The effectiveness of the systems will depend mainly on the establishment of adequate strain thresholds and subsidence kinematics; that is, whether collapse is preceded by detectable creep deformation or not.

Critically assess the performance of mitigation measures applied in the past to improve our capability to select the most adequate and cost-effective mitigation solution and design for each situation.

Improve the awareness of sinkhole hazards among the general public, the technical community, and especially decision makers. The development of sound risk analysis and the design of adequate risk management strategies may be useless if they are not diligently incorporated into the planning process by decision makers. Moreover, the numerous actors involved in the risk analysis and management process should consider that sinkhole frequencies are likely to increase in the future at an unpredictable rate.


This work has been supported by project CGL2013-40867-P (Ministerio de Economía y Competitividad, Spain). Comments were provided by two reviewers, Mario Parise and Anthony Cooper. Dr. Susan Cutter provided editing assistance to considerably improve the work.


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