Groundwater Overexploitation Causing Land Subsidence: Hazard Risk Assessment Using Field Observation and Spatial Modelling
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- Huang, B., Shu, L. & Yang, Y.S. Water Resour Manage (2012) 26: 4225. doi:10.1007/s11269-012-0141-y
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Hazard risk assessment of land subsidence is a complicated issue aiming at identifying areas with potentially high environmental hazard due to land subsidence. The methods of hazard risk assessment of land subsidence were reviewed and a new systematic approach was proposed in this study. Quantitative identification of land subsidence is important to the hazard risk assessment. Field observations using extensometers were used to determine assessment indexes and estimate weights of each index. Spatial modelling was also established in ArcGIS to better visualize the assessment data. These approaches then were applied to the Chengnan region, China as a case study. Three factors, thickness of the second confined aquifer, thickness of the soft clay and the annual recovery rate of groundwater level were incorporated into the hazard risk assessment index system. The weights of each index are 0.33, 0.17 and 0.5 respectively. The zonation map shows that the high, medium and low risk ranked areas for land subsidence account for 9.5 %, 44.7 % and 45.8 % of the total area respectively. The annual recovery rate of groundwater level is the major factor raising land subsidence hazard risk in approximately half of the study area.
KeywordsGroundwater overexploitation Land subsidence Hazard risk assessment Extensometers ArcGIS
Land subsidence occurs when groundwater has been over-exploited from porous sediments, such as fine-grained materials. Occurrences of land subsidence have been globally reported, such as in Spain (Molina et al. 2009), India (Sahu and Sikdar 2011), Thailand (Phienwej et al. 2006), Mexico (Ortiz-Zamora and Ortega-Guerrero 2010), USA (Holzer and Galloway 2005), Ravenna and Italy (Teatini et al. 2005); so is it in China (Li et al. 2006; Yang and Yu 2006; Shi et al. 2007; Wu et al. 2010; Liu et al. 2010). Land subsidence generally results in substantial damage, including loss of ground surface altitude, cracking of buildings, failure of underground pipelines, increase of flood hazards etc. A large number of studies have focused on land subsidence in order to reduce the associated damage and control of land subsidence.
Various methods have also been used to measure spatial variations and temporal rates of the regional and local subsidence. In the early studies, leveling was the main measurement to monitor land subsidence and now it is still commonly used in some studies (Abidin et al. 2001; Odijk et al. 2003). Recently, the satellite-based global positioning system (GPS), remote sensing (RS) and geographical information system (GIS) are gradually used in the regional subsidence studies (Gao et al. 2003; Marfai and King 2007). When more spatial detail is required, LiDAR (light detection and ranging) and InSAR (interferometric synthetic aperture radar) are applied for monitoring land subsidence (Gehlot and Hanssen 2008; Zhao et al. 2009; Hsieh et al. 2011). Extensometers are generally applied in measuring land subsidence (Harmon 2002; Buckley et al. 2003; Wang et al. 2009) which are used to measure continuous change in vertical distance.
To quantify land subsidence, numerous models have been developed (Chen et al. 2003; Ferronato et al. 2003; Kumarci et al. 2008; Zhang et al. 2010; Dong and Liu 2009; Vaezinejad et al. 2011; Ye et al. 2011), which can be categorized into three types, deterministic, stochastic, and artificial intelligence models. Deterministic models analyze the seepage action of groundwater, the soil deformation and the inter-coupling between them based on the mechanism of land subsidence. Plenty of factors cause the consolidation of loose soil, which is accompanied by randomness, so stochastic models are introduced on the basis of the periodical and random characteristics of land subsidence. With the development of computing, artificial intelligence model is gradually used in predicting land subsidence. In some instances, artificial intelligence models are designed to simulate stochastic behaviors. The stochastic data will be transferred into computer signal in artificial model, which is highly efficient and makes the results accurate and reliable.
These models just predict land subsidence in terms of land subsidence, or its maximum/minimum values. They assumed that there will be land subsidence at specific sites and then estimate the value of land subsidence according to the historical, current and prospective conditions. If the probability of the subsidence occurrence at the site is predicted beforehand and some counter measures are taken to reduce the probability, then there would be less hazard of land subsidence, which is more significant than solely modeling the subsidence. Hence it is necessary to introduce hazard risk assessment in this context, aiming at obtaining the probability of occurrence of the land subsidence risk at the spatial scale using modelling tools (e.g. ArcGIS). The distribution of the risk can be better understood as it will show where does not necessarily put us at risk.
Recently, there are a majority of studies on geologic hazards risk assessment, such as hazard risk assessment of landslide, debris flow, collapse etc. (Hürlimann et al. 2006; Bilgot and Parriaux 2009; Kawagoe et al. 2010; Wu et al. 2010; Kappes et al. 2011). But report about hazard risk assessment of land subsidence is rare.
The objective of this study is to present methods of hazard risk assessment of land subsidence caused by groundwater over-exploitation using field observation and ArcGIS spatial modeling. The hazard risk assessment of land subsidence were defined firstly according to geologic hazards risk assessment; then each part of the assessment contents was shown in detail including established methods and data acquisition; and the ArcGIS-based spatial assessment model was introduced, with a case study was presented finally.
2.1 Hazard Risk Assessment of Land Subsidence
To achieve hazard risk assessment of land subsidence at spatial scale, it is necessary to take the lessons from the approaches of other geologic hazards risk assessment. The index method of hazard assessment includes three steps: choosing indexes, estimating weights of each index and assessing hazard risk using a model; so the hazard risk assessment of land subsidence can be achieved.
2.2 The Extensometer Rationale
Multiple position borehole extensometers which incorporate magnetic markers anchored to the formation borehole have been used effectively to monitor land subsidence caused by groundwater exploitation, especially in China (Hwang et al. 2008), since the first application in Poland (Lofgren 1969; Riley 1986).
Galloway and Burbey (2011) noted that vertical borehole extensometers are used to measure the continuous change in vertical distance in the interval between land surface and a reference point or ‘subsurface bench mark’ at the bottom of a deep borehole. According to it, the monitoring principle of the multiple position borehole extensometers is achieved. Shi et al. (2007) and Wu et al. (2008) further applied these in the subsidence monitoring and calculations.
2.3 Index Selection: Extensometer-Based Observation
Index selection is a crucial step in assessing hazard risk using index method. The selection should reflect the occurrence and development process of land subsidence. Land subsidence is such a complicated phenomenon that it is hard to consider all the influence factors as evaluating indexes. It is hence significant to pick up the major factors in the hazard risk assessment. In addition, the selected indexes should be quantified and independent on other indexes (Huang et al. 2008).
The influencing factors of land subsidence can be divided into two categories: human activities and geological actions (Xue et al. 2005). In this study, the main focus is on land subsidence caused by groundwater overexploitation as a main human activity. The geological actions always include fracture structure, crust movement, Quaternary geological conditions, etc. In fact, in the areas where land subsidence happened, Quaternary geological conditions are the main geological actions. Therefore we will mainly consider the situation of groundwater overexploitation and Quaternary geological conditions in the selection.
There is a strong correlation between the development of land subsidence and the groundwater level of the main pumping aquifer. So the indexes related groundwater level (e.g. variation rate of groundwater level) can be used to reflect the human activities’ effect on land subsidence. In addition, land subsidence is the result of the consolidation of soil layers due to the long-term excessive groundwater pumping of the aquifers. So the indexes related main compressive layers also could be regarded as the evaluating indexes to reflect Quaternary geological conditions’ effect on land subsidence.
2.4 Weight Estimation
2.5 Spatial Analysis Tool: ArcGIS
3 Case Study
3.1 Quaternary Geology and Hydrogeology
The Quaternary deposits distribute widely with thickness of 130~170 m increasing from southwest to northeast in this area. The Quaternary sediment is primarily composed of sandy silts, medium-coarse sands and medium-coarse sands with gravels, with clay interlayers.
3.2 Land Subsidence and Groundwater Level
With the fast economy development, more and more groundwater has been exploited since 1980s, resulted in regional drawdown of groundwater pressure. In early 1990s, the study area became the centre of the cone of depression in the Su-Xi-Chang area when the groundwater depth fell to 87 m. After 1996, the depth and intensity of exploitation were adjusted and the pumping yields were restricted to control the subsidence in the downtown area. Moreover, government regulated completely prohibiting groundwater exploitation in the Su-Xi-Chang area since 2005. As a result, the rate of subsidence decreased and the groundwater level recovered in some areas.
3.3 Extensometers Setup
History of the accumulative subsidence of each extensometer (mm)
4.1 Indexes and Weights
4.2 Index Processing
The index system, weight, and grade of land subsidence hazard risk assessment indexes
Hazard risk level & Value
the thickness of the second confined aquifer
the thickness of the soft clay
the annual recovery rate of groundwater lever
4.3 Hazard Risk Assessment
The hazard risk zonation in the Chengnan region
Hazard risk level
Hazard risk index
The evaluation indexes of the land subsidence hazard risk were selected, following the principle of mutual independence. It is realistic to select the evaluation indexes according to subsidence of the individual layers from the extensometer monitoring data, reflecting the physical process of land subsidence explicitly. It is also objective to estimate weights based on the compaction characteristics of different soil layers.
The hazard risk level of each assessment index in individual land subsidence hazard risk zone
Hazard risk level of land subsidence
Hazard risk level of each assessment index
The thickness of the second confined aquifer
The thickness of the soft clay
The annual recovery rate of the groundwater level
In Zone I, the hazard risk levels of the three assessment indexes are all high. It could be regarded as the most hazardous area. Not all the hazard risk levels of assessment indexes are high in Zone II and III, but they are high hazard risk areas as well. The hazard risk level of the thickness of the soft clay and the second confined aquifer is medium in Zone II and III, respectively. That is to say the annual recovery rate of the groundwater level has a great effect on hazard risk of land subsidence in Zone II and III.
In Zone IV, both the hazard risk levels of the thickness of the second confined aquifer and the soft clay are high, whilst the hazard risk of the annual recovery rate of groundwater level is medium. It is known that the contribution of the hazard risk level of the later is much larger than that of the two formers. However, in Zone VI and VII, the hazard level of the annual recovery rate of the groundwater level is high, whereas the other two are medium or low. The contribution of the hazard risk level of the annual recovery rate of the groundwater level decreases. The thickness of the second confined aquifer and the soft clay becomes a major contribution factor.
It seems complicated in the zones of low subsidence hazard risk. In Zone VIII, though the hazard risk levels of the thickness of the second confined aquifer and the soft clay are high, the hazard risk level of land subsidence is low. That’s because the hazard risk level of the annual recovery rate of the groundwater level is low. On the contrary, in Zone XIII, the hazard risk level of the annual recovery rate of the groundwater level is high, but the hazard risk level of land subsidence is low. That is to say that contribution of the annual recovery rate of the groundwater level is smaller than that of other two assessment indexes in Zone XIII.
This study presents a comprehensive approach of hazard risk assessment of land subsidence caused by groundwater overexploitation using field observation of extensometers combining with spatial analyst tool, ArcGIS, which has been applied in a case study in the Chengnan region, China.
In comparison land subsidence caused by groundwater over-exploitation with other geologic hazards, this study addresses the focus upon the process of land subsidence in assessing hazard risk. To support this view, field observation from extensometers has been used in selecting evaluation indexes and estimating their weights for further modeling assessment. ArcGIS spatial modelling then was established for more efficient data handling and better visualization for regional water management.
The hazard risk map of land subsidence has been produced after selecting three factors, thickness of the second confined aquifer and the soft clay and the annual recovery rate of the groundwater level, as evaluating indexes and estimating the weight of each index based on the observation data of extensometers. The results of hazard risk assessment show that the hazard risk level decreases from the centre to the surrounding of the study area and high hazard risk areas account for 9.5 % of study area. The annual recovery rate of the groundwater level plays a main role in land subsidence hazard risk in some areas of 211.3 km2. Therefore, to manage and control land subsidence efficiently, local government should pay attention to these areas by taking some measures for groundwater level recovery. For other areas, it would be effective through monitor regularly and cope with harmful effect caused by land subsidence.
To monitor and control the development of land subsidence, the integrated land subsidence monitoring system (Wu et al. 2008), which consists of groundwater level monitoring network and displacement monitoring network, including benchmarks and extensometers, has been established in a number of major cities and areas with severe land subsidence. Therefore, the data needed by these assessment methods are available from existing database infrastructure, which makes the proposed approach more applicable.
The authors would like to express appreciation to the anonymous reviewers and editors for their valuable comments and suggestions. This paper is financially supported by the Colleges and Universities in Jiangsu Province Plans to graduate research and innovation, (grants No. CX10B_211Z) and the National Natural Science Foundation of China (grant no 41272255).
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