Are Groundwater Monitoring Networks Economical? Cost-Benefit Analysis on the Long-Term Groundwater Supply Project of South Korea

Abstract

Analyses of the relative economic efficiencies of surface-water and groundwater are important for policy-makers in many water-stressed countries. Groundwater is becoming an increasingly attractive and viable option as a supplementary water source, but its economic background must be understood before implementation. Employing the basic frameworks of the British and US Geological Surveys, we examined the economic viability of groundwater monitoring networks in South Korea, based on an analytic hierarchy process (AHP), pairwise comparison, and cost–benefit analysis. The total cost including installation, maintenance and servicing over the next 50 years is estimated to be US$ 0.79 billion, while the benefits are valued at US$ 2.31 billion. The monitoring network should provide benefits worth 292% of the costs, with the monitoring project thus clearly being economically viable. A sensitivity analysis indicates that the monitoring project is still economical, even if the network installation schedule is delayed slightly. As this study combines both economic and scientific perspectives, it might provide a concrete economic background for implementing groundwater utilization projects elsewhere.

1. Introduction

Water is becoming one of the most pressing societal and geopolitical issues for sustainable development in some Asian regions. It is projected that more than 40% of the world’s population will be living in seriously water-stressed areas by 2035, with the availability of ecosystems to provide fresh water becoming increasingly compromised [1]. United Nations University [1] warned that only 60% of water demand will be met by existing resources in the South and Southeast Asian regions by 2030. The World Bank [2] reported that unless government action is taken soon, water scarcity could cost some regions up to 6% of their GDP, spur migration and spark conflict, especially for East Asia and Central Africa.

The effectiveness of water management varies among countries, and rapid development of groundwater resources would be needed in most countries for them to become a viable water source. Groundwater is part of an overall hydrologic system including surface water, and is important in supplying water for irrigation, manufacturing and for other uses. While underground sources provide 80–90% of available water in the US and Europe, they supply only 11% of the total in Korea [1].

With increasing storage and distribution costs of surface-water, groundwater is becoming an increasingly attractive substitute for surface water [3], but the establishment of a national groundwater monitoring system to gauge the level, temperature, pH, and quality of groundwater is expensive. Since continuous monitoring of any changes in groundwater is a basic role of government, to ensure improvement in groundwater management for water supply as Korea shifts from a largely surface-water based economy to an increasingly groundwater based one, its economic feasibility has become more important. Many approaches based on economic perspectives have been applied to ground and surface water in the US, Spain, UK and other countries [4,5,6,7]. The control of underground aquifers, the intensive use of groundwater resources, and the potential changes in both groundwater quality and quantity command the attention of both scientific specialists and policy makers, with economic issues associated with establishing facilities for groundwater supply being important. The economic assessment of groundwater supplies therefore requires a multidisciplinary approach covering costs, water supply policy, water quantity and quality, and applications.

The economic analysis of groundwater based on data provided by monitoring networks should consider not only the efficient use and management of resources, but also the consequential improvements in the ability to cope with related adverse issues such as droughts, and their accompanying risks to the environment, property and life.

South Korea currently has relatively few groundwater monitoring networks compared with major European countries, although there is a national plan to increase monitoring over the next 30 years [8]. However, a systematic analysis of the long-term value of such networks has not yet been undertaken in South Korea, with no economic research into the value of national projects related to groundwater supply. One of the main objectives of this study is to investigate the economic feasibility of groundwater monitoring networks which require the lion’s share of the national budget in completing the long-term groundwater supply project; that is, the economic value of the information acquired from the networks is analysed with respect to its cost-benefit relationship, and the adequacy of the evaluation is reassessed through a sensitivity analysis.

1.1. Groundwater Monitoring Networks: Current Facts and Plans

South Korea has been constructing monitoring wells since 1995 to observe the level and quality of groundwater. All six types of groundwater monitoring networks are currently operated with their own objectives: the National Groundwater Monitoring Network (NGMN); the Subsidiary Groundwater Monitoring Network (SGMN); the Groundwater Quality Monitoring Network (GQM including GQMN (Basic Groundwater Quality Monitoring Network) and GPMN (Groundwater Pollution Monitoring Network)); the Local Groundwater Quality Monitoring Network (LQMN); the Groundwater Monitoring Network in Farming Areas (GMFA); and the Seawater Intrusion Monitoring Network (SIMN) [8,9,10].

The NGMN, GQMN, and GPMN are managed by the central government, and the others are operated by local governments or agencies. They are installed in representative sites according to field characteristics such as land type, topography, hydrogeological measures, background water quality, pollution source, and underground water disturbances. These monitoring networks essentially measure either groundwater levels or groundwater quality. The Groundwater Management Plan has each type of monitoring network scheduled to be installed at the same densities as developed countries by the year 2030 [8] (Figure 1). Therefore, the plan targets 0.10 wells per km² for SGMN, 0.33 wells per km² for GPMN, 0.01 wells per km² for GMFA, and 0.034 wells per km² for LQMN.

As a primary network, the purpose of the NGMN was to measure long-term trends in groundwater levels [11]. Its installation began in 1995 and the government plans to increase the number of wells to 530 by 2021 [8]. The GQMN, another primary network, was established to measure background groundwater quality in non-polluted areas. The established background level can be used as a target level when improving polluted groundwater. The Ministry of Environment plans to expand this to 435 sites by 2020 and to 1305 sites by 2030. Electrical conductivity, pH, and temperature are measured automatically, and water samples and analysis are taken twice a year. The GPMN, as a secondary monitoring system, was designed to detect and monitor groundwater contamination in areas likely to be contaminated, such as industrial complexes, closed mines, sanitary landfills, and golf courses. The Ministry of Environment plans to install 2164 of these monitoring wells by 2030. The GQM includes both the GQMN and the GPMN.

The number of these networks was not enough to detect local drawdowns of groundwater levels or contamination due to the complex geology in South Korea and therefore other networks (SGMN, LQMN, GMFA, and SIMN) were additionally proposed [11]. The SGMN was established to measure groundwater levels in the areas not covered by the NGMN, which was proposed to have 10,000 sites by 2031. The LQMN, which is managed by local governments, will be installed at 33,000 sites by 2030; its aim is to measure local groundwater quality. The GMFA will contain 1056 sites by 2021, and automatic measurement systems will be introduced to observe groundwater conditions related to crop production in rural cultivation areas. The SIMN measures seawater intrusions in coastal or island areas, and will contain 388 sites by 2043 [8].

1.2. Literature Review

Whereas the installation and management costs of the networks are fairly straightforward to assess, the benefits of the groundwater monitoring network are difficult to quantify because they include non-use value as well as use value and there is no complete assessment procedure for groundwater monitoring benefits. This means that an indirect approach, such as the analytic hierarchy process with a pairwise comparison, for the estimation of its benefits, can be a more effective tool than a direct estimation. In this study, geological information is used as a relative factor to compare with groundwater information acquired from the monitoring networks because the economic effects of geological information are well defined in many countries.

Studies by the British Geological Survey (BGS) showed two evaluation approaches for measuring the benefits of geological information: an anecdotal approach and a formal assessment as summarized below (

Table 1. Previous studies measuring the value of geological information [12,13].

Main Method	Study (Institution)	Case	Empirical Result
Anecdotal and Formal Cost-benefit (Cost-effectiveness) Approach	Ellison and Calow (1996) (BGS) [12]	Evaluates the impacts of information gained through geological mapping projects in the UK.	The annual national baseline value of mapping of the UK is £18.9 million. (B/C = 5.906)
	Bernknopf et al. (1996a) (USGS) [14]	Details the rigorous development of an economic model for valuing geologic map information.	The expected net benefit for the 1:100,000-scale Loudoun County geologic map ranges from $1.28 million to $3.50 million.
	Bernknopf et al. (1996b) [15]	Estimates the economic value of applying geologic map information to siting a waste disposal facility in Loudoun County.	The total benefit of the improved geologic map is approximately $1.5 million. The expected net benefit from use of the 1:100,000 scale map is $0.34 million.
	Reedman et al. (2002) (BGS) [13]	Contains an evaluation and quantification of the net benefits of different levels of detail and improvements in interpretive models contained on geologic maps.	Various results by Bolivia, Indonesia, Peru, Zimbabwe, and Nigeria.
	Halsing et al. (2004) (USGS) [16]	Assesses the costs and benefits of the national map and to estimate its net present benefit to society.	The national map has a net present value of benefits of $2.05 billion with a standard deviation of $490 million over 30 years.
	Kim et al. (2006) [17]	Applies the BGS model (1996) to estimate costs and benefits of the Korean geologic mapping program.	The total benefits ranges from 973 billion Won to 1330 billion Won. The costs were 82 billion Won for 40 years.
Analytical Hierarchy Process (Expert-based)	Booz Allen Hamilton (2005) [18]	Measures the value of geospatial interoperability standards in accessing NASA’s scientific information.	Opening geospatial standards had a risk-adjusted ROI of 119.0% which can be interpreted as for every $1 spent, $1.10 is saved.
	Tsangaratos and Koumantakis (2013) [19]	Illustrates the value of geological data and information used to produce landslide susceptibility maps in Greece.	Calculates weight of coefficient of each factor representing the estimation of landslide susceptibility.
Willingness-To-Pay	Bhagwat and Berg (1991) (Illinois State Geological Survey) [20]	Estimate the benefits and costs of geologic mapping conducted in 1980 in Illinois from interviewing with 36 individuals.	According to the most conservative projection, B/C ratio is 0.5 to 1.1.
	US Environmental Protection Agency (1995) [21]	Shows an empirical technique estimating changes in economic value associated with changes in groundwater services.	n.a.
	Bhagwat and Ipe (2000) (Illinois State Geological Survey) [22]	Estimates the value of the geological quadrangle maps (1:24,000-scale) in Kentucky.	The average willingness to pay (WTP) was reported to be $342 per map. The value of the map was at least 25 to 38 times higher than the cost of the mapping program.
Expected Utility Theorem	Bouma et al. (2009) [23]	Analyses the added value of an extended satellite monitoring system for the management of eutrophication, potentially harmful algal blooms and suspended sediment and turbidity in the North Sea.	The value of information is estimated to be €74,000 per week and the costs of the new system are only €50,000 per week.
	Castelein et al. (2010) [24]	Defines the geo-information sector and estimate its economic value in terms of turnover, employment, activities and the market in Netherlands.	The total economic value of the Dutch geo-information sector was estimated at €1.4 billion which takes a share of 0.23% in the Dutch economy.

).

The anecdotal approach has been employed by the BGS to evaluate the impacts of new geological information. This approach was based on the compilation of national, baseline information on policy, guidance, best practice, and government research recommending the use of the information in various sectors such as minerals, waste management, environmental assessment, regional planning, water management, construction industry, education and research, tourism and recreation, agriculture, and forestry [12,16].

As a formal approach, cost-benefit analysis is a simple method comparing the estimated costs and benefits of two or more alternatives. Both the BGS and the United States Geological Survey (USGS), in employing a cost-benefit analysis in their models, defined that the net benefits of each option can be represented as the “expected loss avoided” that arises from using the geological information, minus the costs of producing and disseminating the information [13,14,16,19]. The benefit assessment can be analyzed by comparing the economic impacts of decisions based on the already existing information. In the case of geological information, the potential value may come from: (a) direct savings in terms of avoided costs from contaminations or erosion; (b) reduced potential for liability; (c) lower costs for groundwater protection; (d) safer infrastructure; and (e) improved mineral exploration efficiency [19].

Additionally, an analytical hierarchy process (AHP) with pairwise comparison, through the interviewing of some researchers, senior-level government staff and private individuals, has been widely used to measure the value of geological and geospatial data [18,23].

Martinez-Paz et al. [25] also estimates the environmental and resource costs of groundwater by means of the Contingent Valuation Method and the Production Function Approach in the case of the Gavilán Aquifer. Face-to-face interviews were carried out to calculate use and non-use values, including open-ended questions about the WTP for protecting and preserving an aquifer located in Spain.

2. Research Methods

2.1. Research Process

Among the above four major methods of measuring the value of geological information, we chose to employ a formal cost-benefit analysis and AHP, since water supply projects have been managed not by private market but by public authorities as a public good in South Korea. The AHP is therefore an appropriate method in estimating both direct and indirect benefits of public services such as the water supply. The economic evaluation of groundwater monitoring networks is conducted by the following procedures in this study (Figure 2). First, the costs of each type of groundwater monitoring network, including the costs of construction, maintenance, replacement and water quality tests, are calculated with the existing data recorded by the management agencies or the government (see Appendix A). In the next step, the AHP method with a pairwise comparison, which is between surface water, groundwater, and geologic information, is used to estimate the relative value of the groundwater networks. In this step, the benefits of geologic information are estimated by applying the BGS model. In step 3, we examine the economic validity of the groundwater monitoring networks by comparing their benefits and costs. To ensure the validity of the economic analysis in step 4, as the sensitivity analysis, we reiterate the same analytic procedures and check how the cost-benefit (BC) ratio changes as the number of installed wells changes.

2.2. Cost–Benefit Analysis

Since a water-related system does not aim to generate profits but has the social goal of providing a public service, the cost–benefit ratio method is more appropriate for groundwater monitoring network evaluation than other methods, as shown in some studies of the BGS and the USGS. In the cost-benefit ratio method, the ratio is calculated using the following formula [26]:

$$\frac{B}{C}={\displaystyle \sum _{t=1}^n}\frac{B_t}{{\left(1+r\right)}^t}/{\displaystyle \sum _{t=1}^n}\frac{C_t}{{\left(1+r\right)}^t}$$

(1)

where B is present value of benefits, C is present value of costs, r is discount rate, and t is time. The ratio indicates how great the benefits will be per unit of costs for the project, which makes it useful in deciding whether the project should be undertaken under the condition of budget constraints or not.

This analysis is conducted under some limited assumptions according to the governmental institute’s guidelines [27]. The first assumption regards the planning horizon. This study sets the time frame for the scope of this project as a period of 50 years from the construction of the monitoring wells; therefore, the period of 2011–2060 is considered here as the period generating benefits. The next condition concerns the social discount rate of the costs and benefits. Discount rates have usually been set at between 5.0% and 6.5% in South Korea. The Korea Development Institute (KDI) has usually argued for a relatively low interest rate for water resource projects that could bring long-term costs and benefits. Therefore, two discount rates of 5.0% for the initial 30 years and 6.5% for the next 20 years are used in this research model on the grounds of the KDI’s guidelines which has to be applied to the evaluation of all government projects. This discount rate, as stipulated by the KDI, may not be optimal, considering Martinez-Paz et al. [28] findings following a survey of experts that discount rate for the first 30 years should in the range of 3.47%, and 2.84% for the period between 30 and 50 years. However, the 5%/6.5% rates in South Korea are required based on the KDI’s analysis of the current and future trend of the Korean economy.

2.3. Analytic Hierarchy Process and Pairwise Comparison

Saaty’s AHP is based on the assumption that when faced with a complex decision, the natural human reaction is to cluster the criteria according to their common characteristics. It involves building a hierarchy of criteria and then making comparisons between each possible pair in each cluster [27,29,30,31,32]. A pairwise comparison method between the various criteria (surface water, groundwater, and geologic information) is used to assign weights to the different criteria by using a questionnaire (Figure 3).

In order to compute the weights for the different criteria, the AHP starts creating a pairwise comparison matrix (

Table 2. An example of a pairwise comparison process for the secondary three criteria [30].

Evaluation Criteria	A Criteria	B Criteria	C Criteria	Geometric Mean	Weights
A criteria	1	$a_{12}$	$a_{13}$	$\sqrt[3]{\left(1\times a_{12}\times a_{13}\right)}$ = GM1	GM1/SumGM
B criteria	$\raisebox{1ex}{$1$}\!\left/ \!\raisebox{-1ex}{$a_{12}$}\right.$	1	$a_{23}$	$\sqrt[3]{\left(\raisebox{1ex}{$1$}\!\left/ \!\raisebox{-1ex}{$a_{12}$}\right.\times 1\times a_{23}\right)}$ = GM2	GM2/SumGM
C criteria	$\raisebox{1ex}{$1$}\!\left/ \!\raisebox{-1ex}{$a_{13}$}\right.$	$\raisebox{1ex}{$1$}\!\left/ \!\raisebox{-1ex}{$a_{23}$}\right.$	1	$\sqrt[3]{\left(\raisebox{1ex}{$1$}\!\left/ \!\raisebox{-1ex}{$a_{12}$}\right.\times \raisebox{1ex}{$1$}\!\left/ \!\raisebox{-1ex}{$a_{23}$}\right.\times 1\right)}$ = GM3	GM3/SumGM
Total				GM1 + GM2 + GM3 = SumGM

) [30]. The geometric mean is an appropriate measure for combining individual judgments to obtain the group judgment for each pairwise comparison. The matrix is a $m\times m$ matrix, where m is the number of evaluation criteria considered. The entries $a_{jk}$ and $a_{kj}$, which is a reciprocal of $a_{jk}$, satisfy the following constraint:

$$a_{jk}·a_{kj}=1$$

(2)

here, the entry $a_{jk}$ is the importance of the jth criterion relative to the kth criterion [30,33].

Assuming that each $F_{jk}$ is independent, the score of each criterion obtained from the experts can be added together. Here, $F_{jk}$ is the kth secondary criterion constituting the jth primary evaluation criterion. The total score is produced by adding these $F_{jk}$ values and the mean of the total score ($M{F}_{jk}$) can also be calculated from the total score. A pairwise comparison matrix for the secondary criteria with their relative values of importance can be produced. With the relative importance between the two criteria, geometric mean and weights were calculated (Table 2).

As described above, we use the relative values of importance to derive the benefit of groundwater monitoring networks.

To test a reliability of the AHP model with pairwise comparison, consistency index $\left\{CI=\frac{\left({\lambda }_{max}-n\right)}{\left(n-1\right)}\right\}$ and consistency ratio ($CR$) are calculated. Consistency ratio indicates how far the pairwise judgements deviate from a purely random matrix of pairwise comparisons, and is defined as:

$$CR=\raisebox{1ex}{$CI$}\!\left/ \!\raisebox{-1ex}{$RI$}\right.$$

(3)

where RI is called random index [30].

Two water sources, surface water and groundwater, are conceptually different from geologic information, and it is not easy to compare them to it because their policy fields, economic aspects, and expected effects are different. Therefore, multiple and diverse discussion on their concepts and effects based on some indicators explaining their characteristics is required to derive the relative importance between them. For a better discussion and understanding, the detailed indicators corresponding to the meanings of the information are derived from previous research and summarized systematically [4,12,26,34]. Subsequently, such research results were provided to the respondents of the questionnaire (

Table 3. Some selective indicators used for comparing the benefits of information in surface water, groundwater and geology [4,12,21,26,32].

Indicators	Surface Water	Groundwater	Geology **
Policy aspect	Governmental (long term) plan and future requirements Water supply (Domestic, Industrial, Agricultural) * Flood/drought control * Restoration of natural resources * Ecological diversity	Governmental (long term) plan and future requirements Water supply (Domestic, Industrial, Agricultural) * Drought control * Restoration of natural resources * Ecological diversity	Mineral waste management Environmental assessment Protection of seaside and water sources Protection of water quality and water supply Natural resources management
Economic aspect	Electricity production * Cost (Production, Water treatment, Supply, Management) * Transportation (Canal) *	Geothermal source Cost (Production, Water treatment, Supply, Management) *	Mineral production Development of local region Construction economy (Road, railway, port, building, etc.)
User aspect	Agricultural/industrial productivity User accessibility Recreational benefit * Land use *	Agricultural/industrial productivity User accessibility Land use * Water welfare	Real estate and insurance Health Education and Research Recreation/Tourism Agriculture/Forest
Others	Economic benefit * Future value Emergency use	Economic benefit * Future value Emergency use

Note: (1) Asterisks (*) denote items of water benefit proposed by the KDI (2008) [26] and ** denotes items of geology benefit proposed by the BGS; (2) Some of the above indicators are also discussed in Marcouiller and Coggins (1999) [34], Ellison and Calow (1996) [12], and Environment Agency (2007) [4].

). Consequently, a relative value of importance between the geological, groundwater, and surface water information is assessed by reviewing the provided indicators and comparing those values with the well-defined benefits of geologic information. In previous research, the benefits of information in surface water, groundwater, and geology consist of some selective indicators, as summarized in (Table 3).

3. Cost and Benefit of Groundwater Monitoring Networks

3.1. Cost

The costs of the groundwater monitoring network are determined according to the facility design, maintenance strategy, repair, and reinstallation (

Table 4. Unit costs of construction and management for groundwater monitoring networks.

Type of Network	Items and Unit Costs (unit: USD/single well)	Remarks
NGMN	Construction/drilling: 39,965 Equipment installation: 11,182 Service: 5386 RTU replacement: 3516 Battery replacement: 111	Service includes labor, travel cost, water analysis fee, reporting, etc. RTU: Remote terminal unit for data collection and transmission (11% of wells are replaced every year)
SGMN	Reuse of existing well(Manual installation): 30 Well installation: 14,567 RTU installation: 100 Service(manual): 713 Service(automatic): 2825 Equipment replacement: 65	Reuse means the existing well is used as a monitoring well Well installation means new well drilling Service (manual) includes sampling, reporting and water level measuring Service (automatic) means automatic measurements of water level and quality sensors as well as sampling and reporting
GMFA	Construction/drilling: 40,030 Equipment installation: 767 Service: 4612 Replacement (Device and Battery): 4744	Service includes management, sampling, manual measurements of level, reporting, etc. Equipment includes water level sensor, logger and telemetering
SIMN	Construction/drilling: 42,031 Equipment installation: 10,465 Service: 674 Replacement (Device and Battery): 3633	Equipment includes water level and quality sensors as well as telemetering Service includes sampling, water analysis, reporting, and level measurement
GQM	GQMN construction/drilling: 78,761 GPMN construction: 2902 GQMN labor and travel: 383 GPMN labor and travel: 43 Equipment replacement(GQMN): 338 Water sample(Fee): 1104 Water sample(Labor): 58	GQMN uses a new well and GPMN uses an existing well Labor and travel costs are needed for sampling, level measurement, etc. GQMN labor cost is high due to equipment inspection
LQMN	Reuse of existing well: 172 Service(labor and travel): 128 Equipment replacement: 296 Water sample(Fee): 128 Water sample(Labor): 51	Equipment replacement includes well protection apparatus, guide plate, etc.

Note: 1US$ = 1100 Korean Won.

). The design of a groundwater monitoring well depends on the purpose of each monitoring system. For example, the SIMN should have an electric conductivity sensor to detect sea-water intrusion, and the GQMN and the NGMN should have an automatic monitoring system for groundwater quality and quantity measurements. Construction and installation costs of the monitoring networks include a well drilling and remote terminal system and power battery. Maintenance costs include the replacement of old wells and all devices. Service costs include labor charges for replacement and maintenance, and travel expenses for collecting water samples (Table 4).

According to the Groundwater Promotion Act, the owner should report the end of groundwater use to the local government when both closing and drilling a well. By using the national statistics of this data on groundwater wells (www.gims.go.kr), 217,993 pumping wells, which were drilled during the period from 1970 to 1989, are analyzed to calculate their average life cycle (Figure 4). The average life cycle is calculated to be 29.7 years for their periods in service, where the equation is “service period = year of construction − year of removal + 1”. Considering the structural similarity of monitoring and pumping wells, the life cycle of groundwater monitoring wells are also considered to be 29.7 years, with the exception of a sensor and telemetering device with a shorter life cycle (Table 4). By using the above installation data and maintenance plan, the costs for each monitoring network for the period 2011–2060 are finally calculated with the total costs amounting to USD 793.6 million. The cost details by type of network are listed below (

Table 5. Present values of total costs for each type of groundwater monitoring network for 50 years (Appendix A).

Type		Construction, Installation, & Well Replacement	Maintenance & Service	Device Replacement	Water Sample Test *	Total
NGMN		7,528,404	70,758,976	3,908,395	-	82,195,775
SGMN	Manual	386,490	61,253,235	17,619	-	246,177,391
	Automatic	80,570,577	103,922,130	27,340	-
GMFA		37,086,424	126,068,647	8,140,240	-	171,295,311
SIMN		10,449,325	48,662,609	2,716,363	-	61,828,297
GQM	Quality (GQMN)	63,072,618	6,109,509	595,225	33,989,889	108,164,812
	Pollution (GPMN)	3,427,972	969,599
LQMN		52,744,882	15,300,180	3,906,735	51,989,311	123,941,108
Total						793,602,694

Notes: (1) Maintenance and service costs include fees for water sample tests for NGMN (National Groundwater Monitoring Network), SGMN (Subsidiary Groundwater Monitoring Network), GMFA (Groundwater Monitoring Network in Farming Areas), and SIMN (Seawater Intrusion Monitoring Network); (2) According to KDI (2008) [26], two discount rates of 5.0% for the initial 30 years and 6.5% for the next 20 years are used to calculate net present values.

).

3.2. Benefits

Each groundwater monitoring network has its own objective function, and therefore, the benefits can be different from each other. However, some of their functions, such as the measurement of groundwater level and basic quality observations, overlap for each network. For example, the NGMN and the SIMN have a similar purpose regarding water level observation, but the SIMN is more beneficial in protecting against seawater intrusion along the coastal line. Additionally, because the benefits of the monitoring networks include both use value and passive value, it is not easy to quantify as mentioned in the above section. Therefore, it is almost impossible to calculate the value of each monitoring network separately, and in this study the benefits are assessed for the whole network based on the network’s conceptual average benefits by being compared with the geological information.

When applying the AHP for the benefit estimation, a series of intensive discussions with groundwater and geology specialists in South Korea were conducted by reviewing some indicators for comparison in order to determine the primary and secondary criteria. A hierarchical value tree using the primary and secondary criteria for an assessment of groundwater value was finally proposed

To evaluate the value of groundwater information, a questionnaire survey was made to estimate the relative value of groundwater information compared with surface water and geological information as the second criteria, and also the relative importance of groundwater and surface water as the first criteria considering the proposed indicators. A total of 55 questionnaires were collected from hydrogeologists, surface water specialists and geologists. Interview participants were provided with the monetary value of geological mapping as estimated by Kim et al. [17]. Through several brainstorming sessions, all specialist participants were asked to respond to the relative economic value of groundwater information compared with geological mapping which is estimated to be USD 964.8 million. Therefore, they knew that if one answered “1” for geological information and “2” for groundwater information in the Likert scales, it meant that the monetary value of groundwater information was 2 times greater than that of geological information for the person.

The survey results show that the value of surface water information is 2.37 times more important than geological information, and groundwater information is 2.39 times greater than that of geological information (

Table 6. Relative values of groundwater information estimated by the AHP with pairwise comparison.

Item	Surface Water Information/Groundwater Information	Surface Water Information/Geological Information	Groundwater Information/Geological Information
Value	0.72	2.37	2.39

Note: Consistency index: 0.005, Random index: 0.58, Consistency ratio: 0.009.

). The consistency index is 0.005 and random index is 0.58. The calculated consistency ratio is nearly zero, i.e., 0.009. Because Saaty’s rule of thumb is to allow up to 10% inconsistency within the random matrix, this level of consistency is satisfactory.

Applying the BGS model, Kim et al. [10] calculates the value of geological information (1:50,000 scale maps) [12]. In total, seven sectors are considered in estimating the benefits of geological information: mineral products, waste facility construction, environmental impact, groundwater relations, regional development, coastal management, and social infrastructure (

Table 7. Estimation of total annual benefits of geological information in South Korea [12,16].

Benefit Sector	BGS’s Benefit Items and Key Statistics (USD)	BGS’s Contribution Rate	Annual Benefit (USD)	Percentage of Annual Benefit
Mineral Product & Management	- Aggregate production of mineral, sand & gravel (3161 M) × 0.1% - Mineral operators: 3161 M × 0.05%	0.15%	4,741,818	8.4
Waste Facility Construction	- Average costs of facility construction (0.91 M) × Nationwide sites (36 sites/year)	5%	1,636,364	2.9
Environmental Impact Assessment	- Average costs of Environmental Impact Assessment ($107,272 per site) × 250 sites/year	5%	1,340,909	2.3
Groundwater Development & Management	- Average costs of groundwater pumping wells ($9090 per well) × 30,000 wells/year	5%	13,636,364	24.0
Regional Development	- Saving costs of time for staff ($863/local government) × 199 local governments	£1500 per local government	171,818	0.3
Coastal Management	- National expenditure for coastal defense plan & project (207 M, 68 sites)	0.05%	103,636	0.2
Social Infrastructure	- National SOC investment (14,000 M/year)	0.25%	35,000,000	62.0
Total Annual Benefit			56,630,909	100.0

). The total annual benefits of Korean geological information are estimated as USD 56.6 million. Consequently, the total benefits of geological information for 50 years are calculated by multiplying and discounting the annual benefit based on the KDI guidelines such as the discount rate. Finally, the benefits for geological information in South Korea are estimated as USD 964.8 million.

The relative value of groundwater information provided by the monitoring networks, which means ultimately the benefit of the networks, can be estimated by multiplying the value of geological information by the relative importance value, 2.39, of groundwater information (Table 6). Therefore, the benefit of the monitoring networks can be estimated to be about USD 2314.7 million.

Based on interviews with geotechnical specialists, Ellison and Calow [12] argued that geological mapping information is worth at least 25% of the value of the site investigation, and considerably more where modern maps and databases are available to enable better decision making and risk assessment to be made. According to Kim et al. [17], the annual average costs for geological site investigation take 1% of the total expenditure of national SOC investment in Korea. We understand that Kim et al. [17] calculated the benefits by multiplying 25% × 1% × SOC investment, hence the 0.25% National SOC expenditure rate for social infrastructure.

4. Results and Sensitivity Test

As mentioned above, the cost of the groundwater monitoring network over the next 50 years is estimated to be USD 793.6 million in present value terms. Meanwhile, the present value of benefit obtained by the AHP analysis has a value of USD 2314.7 million. The BC ratio of the groundwater monitoring network is therefore 2.91, and thus the monitoring network’s benefits will greatly exceed the costs over the next 50 years. This high ratio means that the expansion of the existing groundwater monitoring networks is a highly economical solution of great value to an essential issue.

The original trends of the estimated costs and benefits of groundwater monitoring networks, which are calculated through the above process, are plotted in Figure 4.

The trends indicate that the benefits and the costs will increase by almost the same ratio until 2020, but the gap between benefits and costs grows annually after 2020 and until 2030, when the new constructions are fully installed as scheduled.

Future costs and benefits, on which the net present value is based, are predicted values with uncertainty. Therefore a sensitivity test is required to confirm the result and it is important to test the values under both ‘optimistic’ and ‘pessimistic’ scenario conditions. If the output values are shown to be very sensitive to changes in a given input value, the model should be checked for the appropriateness and impact of the given variable. The government schedule for the number of monitoring wells is a key point for the cost calculation and therefore additional BC analysis is performed again under the condition of a changed schedule, which means a delay of network installation, in calculating the BC ratio for a sensitivity test.

We run simple OLS (Ordinary Least Square) regressions to project the number of monitoring wells for the target year 2060, based on the previous installation trends, from the late 1990s to 2012, of six different networks (Figure 5). As a result of these regressions, by 2060 we estimate the number of wells by type as following: NGMN 530; SGMN 3977; LQMN 3149; SIMN 388; GMFA 347; and GQM 231. However, in cases of the NGMN and the SIMN, the original target numbers, 530 and 388, will be accomplished in 2018 and 2038 (Appendix B).

Considering these trends, the costs of the networks are recalculated with the same process, becoming about USD 265.6 million, or 33.4% of the total costs. On the other hand, this total number of monitoring wells, 8622, reaches only 17.8% of the planned number of 48,443. Following the previous trends of the above 6 types of wells as shown in Figure 5, we found that the reduction rates of both cost and numbers of wells are not proportionate because lower cost wells such as LQMN and SGMN take over 88% of the total number of wells. This is why the rate of cost reduction is much smaller than that of the number of wells reduced.

On the other hand, the benefits, in proportion to the number of wells, should be reduced to 17.8%, or USD 412.0 million, of the original total benefits. This indicates that the BC ratio is drastically reduced from 2.91 to 1.55 (= USD 412.0 million over USD 265.6) and it means the ratio, which will have decreased by about 47%, is relatively less sensitive than the reduced percentage of the number of monitoring wells (82%). Although the BC ratio is reduced, it is noteworthy that the benefits still outweigh the costs and the value of groundwater monitoring exists still. This result shows that new installations should continue to be made even if the number of monitoring wells remains below the planned target (

Table 8. Results and sensitivity test.

Scenarios	Benefit (1000 USD)	Cost (1000 USD)	B/C Ratio
Groundwater project	2,314,782	793,602	2917
Past trend	412,031	265,642	1551

).

In 2016, the numbers of monitoring networks become 412, 1838, 268, 64, 2021, and 163 for the NGMN, the SGMN, the GMFA, the GQM, the LQMN, and the SIMN, respectively (Figure 5). In the cases of the NGMN, the LQMN, and the SIMN, the actual installation does not meet the target number but the other networks have been installed over the predicted number as of 2016. The recent trend is roughly similar to the past trend from the late 1990s to 2012 and so it is still economical. Even though the recent trend of monitoring well installation may change according to the budget or national policy, it is shown that the continuous installation is important and valuable.

5. Conclusions and Discussion

Especially in water-stressed countries, water authorities have been struggling to design policies that address emerging physical, economic and environmental stress on groundwater resources. In order to contribute to policy discussion, we suggest some basic indicators and a framework, based on the BGS’ and the USGS’s models of groundwater, for measuring the costs and benefits of groundwater information. For our model, we have assumed, on the basis of Kim et al. [17], who based their calculations on Ellison and Calow [12], that benefits are equal to 25% of National SOC expenditure, which they claim to be on the conservative side and may in truth be more where more detailed and up-to-date maps and databases are used. However, our research goal was to introduce a viable model with which to estimate and analyze the costs involved in building and maintaining the monitoring networks and the various benefit streams expected from them. As shown above, the review of previous research shows significant economic benefits attached to the generation of this type of geological and groundwater information. It is, however, difficult to compare results across studies since they differ in scope and make assumptions regarding which sectors to cover. As much research has verified that benefit-cost ratio of geological information were much greater than one, this analysis of groundwater monitoring networks in South Korea also shows that the benefits are greater than the costs, and demonstrates the economic feasibility of the planned network project in the national groundwater master plan as promoted by the government. Groundwater information, which plays a key role in addressing the challenges of sustainable water supply, contributes to improved decision making processes.

One of the limitations of our research is that we apply the indirect method of estimation by calculating the relative value of groundwater monitoring networks through questionnaire. It is difficult to express the benefit of groundwater information, which is a public good, in monetary terms, because of the limited availability of the necessary information since its market price does not exist. Even more, the benefit assessment is complex due to different spatial and temporal scales on which many of the benefits of the groundwater information operate. This is the main reason why the benefit of each monitoring network cannot be measured separately.

The second limitation of our research is that our valuation of groundwater information, which considers a scope of 50 years, might be recalculated due to the currently unknown effects of climate change in the future, which has been linked to changes in the large-scale hydrological cycle in the long run. We expect that the most significant abnormal weather phenomenon due to climate change is the change of water circulation. Previous studies indicated that greenhouse gases accelerate global warming, resulting in an increase of moisture in the air which strengthens the water circulation process. The long-term change in the rainy season in the Korean peninsula has been studied in many aspects. According to Ryoo [35], comparing precipitation from the 1960s to that of the past 30 years during the rainy season, the number of precipitation days has decreased from 62 percent in the 1960s to 56 percent in the past 30 years. With higher than average temperatures and warmer air that can hold, a pattern might emerge of lengthy dry spells interspersed with brief but heavy precipitation and possible flooding in Korea. Indeed, Ryoo [35] concluded that sudden precipitation causing a greater likelihood of flooding is expected in the future, which would cause instability in surface water supply. Thus groundwater represents a reasonable reliable source of water under such an eventuality. Therefore, because much of the impact of climate change will be felt through changing patterns of water availability [36], groundwater resources are an essential source of water, especially for water-stressed and highly surface-water dependent countries like Korea in the future. In this respect, further research incorporating the factor of climate change in the long-time would be valuable to establish the water management capability on a sustainable basis.

Lastly, we did not discuss the environmental costs of groundwater as Martinez-Paz et al. [25] studied. They concluded that the environmental and resource costs as a result of depletion and degradation of groundwater were 0.454 €/m³ including the price of the services provided by the groundwater of an aquifer in Spain. As Korea currently uses about 3500 million tons of groundwater as of 2018, the costs would be 1589 million € according to Martinez-Paz’s study, which is approximately the same as the benefit we estimated above. However, their costs include the opportunity cost for recreation which may not occur in many groundwater pumping well sites in Korea because 57.2% of pumping wells are being used by households.

The government generally requires an economic validation of a new project. In particular, it is very difficult to explain or quantitatively calculate the importance of a new groundwater project because it is associated with many unknown variables such as hydraulic uncertainties and environmental forecasts such as climate change. This study represents a simple solution with an economic approach for the groundwater monitoring system providing groundwater information, which is a BC analysis and AHP with a pairwise comparison, which will be useful to decision-makers within water authorities not only in Korea but in water-stressed countries throughout the world.