Waterscape Unveils New Project on Rural Drinking Water Supplies: 

Risk-based Economic Approaches to Rural Drinking Water Quality Optimization in a Transitioning Economy

Abstract

One-third of Lithuania’s 3.5 million residents rely on private water systems, predominantly untreated dug wells, for drinking water that expose consumers to high levels of nitrates and pathogens, contamination that leads to increased morbidity for gastrointestinal and other diseases.  Although alternative water supply options exist, methods do not exist to analyze the economic costs and health benefits of various alternatives in various hydrologic settings (World Health Organization and Guy Hutton 2001) .  In this research water supply options and their corresponding costs will be linked to health effects in various hydrologic settings.  Identifying which alternatives are optimal is vital for regulatory agencies and private water companies to allocate resources effectively to improve drinking water quality.

Specifically, this research entails the development of a decision-making model to characterize the health effects of various water supply options, allowing municipalities, community associations, and other groups to make a cost benefit determination in identifying water supply options.  The model will link the risk of drinking water to the water quality, the water quality to the water supply alternative, and the water supply alternative to the cost.  In addition to choosing the optimal water supply option, analysis of separate regions in series will enable decision-makers to identify which regions will benefit the most with the smallest investment.

The research will involve collecting data on the water quality benefits and economic costs of several alternatives, including: dug wells (status quo), drilled wells, point-of-use treatment, municipal supply extension, best management practices (BMPs), and bottled water.  While the Lithuanian Geological Survey and private water companies are willing to provide much of this information, site specific information on water quality indicators will be collected for dug wells.  Subsequent to an initial survey of dug well quality variability, the number of wells and geographic extent of the sampling area will be determined.

The outcome of this research will be a decision-making system that efficiently reduces morbidity associated with rural water supplies and evaluates water supply alternatives under economic constraints.  It will allow public and private institutions to understand the benefits of investment in rural drinking water supply and allow for the prioritization of investment early on.

I. Problem Statement and Objectives:

Approximately one-third of Lithuania’s 3.5 million inhabitants are exposed to contaminated drinking water through the abstraction of water from more than 100,000 private wells, mainly shallow dug wells.  These predominantly rural communities consume untreated groundwater that fails to meet Lithuanian Hygienic Norms for total coliforms, E. coli, nitrates, turbidity, and other water quality indicators (Domasevicius, Juodkazis et al. 2002) .  One recent monitoring study of dug wells in the county of Vilnius showed that 34% of samples (n=106) failed to meet the norm for nitrates (202.4 mg/L maximum), 21% (n=105) failed for turbidity (23.2 mg/L maximum), and 54% (n=230) failed for microbiological indicators (Vilnius Public Health Center 1998) .[1]  Although periodic monitoring of organic chemicals such as pesticides and other industrial contaminants is non-existent for private or small communal wells, national studies have shown significant contamination (Domasevicius, Juodkazis et al. 2002) .  The impact of these contaminants is significant, both on quality of life and on the economy (Ward, Mark et al. 1996; Schwartz 1997; World Health Organization 2000; World Health Organization 2002) . 

While the government of Lithuania has openly stated its commitment to improving rural water supply, there is no mechanism currently available to decide how to move one million Lithuanians away from shallow, unprotected wells (Domasevicius, Juodkazis et al. 2002) .   This research would develop a method to prioritize such interventions and appropriately allocate scare governmental and community resources to improve the water supply, enabling a decision-making system that provides the greatest benefit at the lowest cost.  This research will also assist Lithuania in meeting its commitments to the European Union as it becomes a new member in 2004 (European Union (EEC) 1980; European Union (EEC) 1992; European Union (EEC) 1995) .

II. Background:

This research builds off of 3 fields: (1) the economics of rural water supply, (2) the quality and management of selected rural water supply alternatives (Sobsey 2002) , and (3) health effects of drinking water contaminants (Office of Research and Development 1997; World Health Organization 1997) .  Although each field is fairly well-explored independently, the literature is largely absent any research that combines these fields to facilitate decision-making.  One notable exception is (World Health Organization and Guy Hutton 2001) which recognizes the same problem this research will address:  “. . . that appropriate methods for evaluating water and sanitation interventions have remained underdeveloped, and subsequently there are few published studies that have dealt with the economics of water and sanitation in a comprehensive or satisfactory way.”  Of a few studies that bridge these fields, emphasis has been on developing countries with little attention paid to transitioning economies, such as those in Eastern Europe (World Bank 1976; Cairncross 1990; Mensah 1998; Zekri and Dinar 2002) .  In Lithuania, demographics, groundwater conditions, standard of living, and a multitude of other factors would make it very difficult to apply the general principles learned from developing countries. 

Economics of Rural Water Supply

Economic optimization techniques are very important to decision-making in determining appropriate water management policies for agricultural, recreational, and drinking water uses (Braden and Ierland 1999) .  Several techniques are available to estimate the benefit derived from a change in environmental quality.  For agricultural water use, methods to predict the increase in crop yields and economic output are also well established (Dinar, Meinzen-Dick et al. 1997; Dinar and Xepapadeas 1998) .  For recreational and other non-market benefits, willingness to pay (WTP) and willingness to accept (WTA) studies are the most well established (Carson and Mitchell 1993; Bingham, Bondelid et al. 1997) , however, several other methods are also gaining in popularity (Smith 2000) .  For drinking water, there is not such a well established method in the literature.  There are presumably several reasons for this: (1) direct economic benefits, such as those from reduced healthcare costs, are difficult to estimate; (2) non-market benefits, such as WTP/WTA, might yield outcomes that are difficult to interpret in a policy making setting; and (3) drinking water policy, such as the water quality standard, is often predetermined by legislation rather than by some cost-benefit analysis. 

Extending the issue to rural (private or communal) drinking water supplies, the situation is more complicated because small drinking water systems are often not regulated.  Monitoring may not be required, standards are generally not enforced, and the entire decision-making process with regard to water supply alternatives often falls to the individual.  Despite the widespread occurrence of this problem, one-third of all Lithuanians, the literature is largely absent any guidance on the situation (e.g. what should a community consider to change water supply: options, costs, benefits, financing, etc).  In addition to formulating a model for initial decision-making with regard to selecting the best water supply alternative, it is also important to consider the long-term financing options for water supply sustainability.  My research will also borrow on studies that have examined various options for community and governmental financing of the water supply (Varis and Somlyody 1997; Katz and Sara 2002) . 

Quality and Management of Rural Groundwater Supplies

Building a model to identify alternatives will rely heavily on understanding groundwater conditions in Lithuania.  Fortunately the data available is substantial and extensive research of deep aquifers is available (Environmental Department of Siauliai City 1997; Kadunas, Domesevicius et al. 1997; Lietuvos Respublikos sveikatos apsaugos ministerija (Health Protection Ministry of the Republic of Lithuania) 1998; Lithuanian Water Suppliers Association 1998; Domasevicius, Juodkazis et al. 2002) .  Much less is known about the state of shallow, dug wells, and this research proposal envisions a significant dug well monitoring component.  On the management side, there is a fairly strong understanding of how management of the wellhead affects water quality (Centers for Disease Control and Prevention 1997) .  Wellhead protection principles for both private and public wells have proven vital to prevention contamination and costly remediation (U.S. Environmental Protection Agency 1989; U.S. Environmental Protection Agency 1994; U.S. Environmental Protection Agency. Office of Drinking Water 1994) .  One facet of this research could be to help identify the value of wellhead protection best management practices in Lithuania.  It will be important to recognize the need to continuous and comprehensive management with any potential alternative.

Health Effects of Rural Water Supplies

The third major component of the model and study is assessing the benefits of different water supplies on public health.  The epidemiological effects of variations in drinking water quality are complex and this study proposes to use several measures to quantify health effects from direct calculations of morbidity and risk (Hodges RG, McCorkle et al. 1956; Office of Research and Development 1997; Caltox Model 2000) , to more empirical and indirect measures (e.g. percentage exceeding water quality standards).  This approach should allow decision-makers to access significant research and incorporate it into determinations of which water supply option is better for protecting public health.

III. Research Questions:

The pragmatic question this research will answer is simply: How can areas and types of water supply improvement be prioritized?  Given that 1 million people obtain water from private water supplies including 100,000 dug wells, identifying which communities should receive priority and what methods of water supply are most suited to the local hydrologic situation is important.  In any locale that utilizes dug well water, an array of features, hydrologic and demographic, will make certain water quality improvements, e.g. drilled wells versus point of use treatment, more cost effective.  By selecting a diverse array of these sites, it will be possible to identify the effect of these site features on the optimal water quality improvement method.

Throughout the course of research, several other questions of independent value will need to be answered,  and hypotheses tested including:

• What is the quality dug well water in Lithuania and what factors affect the quality?
• How do water supply options vary in cost and benefit in Lithuania?
• Are BMPs a cost-effective tool?
• What is the WTP for water in Lithuanian cities?  What is the effect of income on WTP in rural areas?
• What levels of investment would be necessary to decrease morbidity by a given amount?
• What level of investment would be required to meet Lithuanian water quality standards?
• What role can low interest government loans have on the ability of communities to improve water supply?
• How do different methods of estimating benefit prioritize water supply interventions?

IV. Model Design and Analysis

The model will have three (3) major components:

(1)    Water Quality Index (risk or morbidity) function for each water supply alternative,

(2)    Cost functions for each water supply alternative, and

(3)    Function for regional comparison of several sites.

Water Quality Index (Risk or Morbidity) Functions: Approximately six (6) reasonable water supply alternatives including: dug wells (status quo), drilled wells, municipal connection, water trucks or bottled water, BMPs with the existing well, and point-of-use treatment have been identified.  For dug wells,[2] quality varies substantially from well to well and monitoring is limited, so it will be necessary to conduct monitoring of the dug well quality at the selected sites.  This research will rely on existing boreholes and data for the drilled well alternative.  For other options, such as point-of-use treatment and tanker water, published sources will be used.  With these data it will be possible to calculate a water quality index for selected water quality indicators (e.g. nitrates, phosphates, total coliforms, E.coli, turbidity, etc.).  A risk-based mechanism to relate water quality to health will also be devised.  There are several sources of information relating exposure to a change in morbidity, which could then be linked to the cost to the public health system.

Cost Functions: Cost functions will be written for each water supply option.  Some alternatives, such as dug wells, have a fairly simple cost function for initial installation and maintenance (although it would also be possible to consider transport costs).  Drilled wells with localized distribution systems will require investigation of companies that provide these services.  Municipal extension cost calculations will require cooperation with municipal water companies to obtain the necessary data and information to develop cost functions.  To identify per capita cost per liter, demographic data will be needed for each site to enable us to distribute over the representative population.  To understand the effect of the length of investment on the selection of the optimal water supply alternative, the length of the repayment period will be varied (e.g. 1-30 years)

Regional Comparison Function: The third component of the model will enable regional comparisons to identify which site improves water quality for the most people with the least investment.

Note on Site Selection: Although some analysis of the variability in conditions must be undertaken before specifying the number of sites, approximately 50-100 sites will be included.  These will range from individual farmsteads to small villages, and also include suburban areas not currently serviced by a public water system.

Analysis

The data and information collected will permit the design of a MathCad-based model that can optimize for the reduction in morbidity or water quality non-compliance given a particular set of conditions.  Together, these simple functions can form a powerful optimization and prioritization algorithm that links water supply options to public health while minimizing costs.  Five (5) major types of analysis that will be possible with the model have been identified:

(1)    A cost effectiveness measure of a change in the Water Quality Index versus investment per capita;

(2)    Minimization of investment per capita needed to come into compliance with drinking water standards;

(3)    Maximization of regional benefit, specifying what sites should be improved first to maximize the greatest benefit to the largest population;

(4)    A cost-benefit analysis in real dollar terms relating the reduced costs to the public health system to the increased costs of improved water supplies (assuming there is an appropriate measure to identify the benefit in dollar terms to public health and other indicators from improving water supply); and

(5)    A WTP-based analysis of the optimal water supply option (Depending on the availability of data, it may be possible to design a WTP model adjusted for income that could be used to predict what rural residents are willing to pay for improved water quality and convenience).

Another useful product of this research will be the development of general indices that can be used to suggest a water supply option with limited data.  Variables such as population density may drive the cost-benefit outcome.  With approximately 50 or more sites, it should be possible to do some basic form of regression analysis to determine what variables drive selection of the water supply alternative.  Having an ability to generalize will be useful for communities without the resources to perform a full analysis.

V. Outcomes and Deliverables

Despite a robust field of research on drinking water supply issues, several gaps are still present that this research seeks to bridge.  Importantly, there is no research in international journals addressing the challenge of rural water supply in transitioning economies.  Despite extensive research into water supply improvements in Africa and other developing countries, much less attention has been paid to Eastern European and former Soviet countries with overwhelming water quality problems and unique environmental and economic settings.  The research will provide insight into the transitioning economies of Eastern Europe that face significant water supply problems affecting public health.  The uniqueness of countries such as Lithuania requires a decision-making approach tailored to the region’s hydrology, governmental institutions, and economic conditions. 

Upon completion of this research there will be a clearer understanding of the costs and benefits associated with water supply interventions in Lithuania and priority-based approach for decision-making.  The methodology and any developed programs will be distributed to interested parties.   The development of these methods and tools should also be useful to institutions in the United States seeking to identify optimal water supply options in rural settings and maximize the effectiveness of investment.

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