Integrating Spatial Data to Develop Sustainable Policies for Managing Domestic Water Quality

Authors

  • Tawatchai Boonkird Public Sector Development Group
  • Suparerk Suerungruang ndependent Researcher Nontaburi
  • Nithirat Boontanon Regional Health Promotion Center 1 Chiangmai
  • Ratchaphadung Damrongpingkasakul Bureau of Food and Water Sanitation

Keywords:

คุณภาพน้ำอุปโภคบริโภค, การบูรณาการข้อมูลเชิงพื้นที่, นโยบายยั่งยืน, ระบบสารสนเทศภูมิศาสตร์, แบบจำลองเศรษฐมิติเชิงพื้นที่

Abstract

 Access to clean water is a fundamental human right, yet spatial disparities in tap water quality remain a significant challenge in Thailand. The lack of spatial analysis and integrated data often leads to inefficient resource allocation. Objective: To evaluate spatial disparities in water quality across 77 provinces, identify socioeconomic and environmental determinants, and develop sustainable water management policies through stakeholder engagement. Methods: A Sequential Explanatory Mixed-Methods design was employed. Phase 1 analyzed provincial-level spatial data (2020-2024) using Moran's I and spatial econometric models (OLS, SLM, SEM). Phase 2 involved an intensive multi-stakeholder workshop with 35 representatives from 14 organizations. Results: Significant spatial clustering of water quality issues was identified, highlighting 7 hotspot provinces in the North. The OLS model exhibited the best fit, revealing Nighttime Light density (ß = -1.84, p < 0.001) and the proportion of agricultural land (ß = -0.09, p < 0.05) as negative predictors. Workshop outcomes demonstrated a strong consensus, with stakeholders prioritizing the development of a National Water Quality Dashboard (85% agreement). Conclusion: Integrating spatial evidence with practitioners' perspectives mitigates siloed operations and yields highly practical, data-driven policy recommendations for targeted resource allocation.

References

World Health Organization (WHO) and United Nations Children’s Fund (UNICEF). Progress on household drinking water, sanitation and hygiene 2000-2022: special focus on gender. Geneva: World Health Organization; 2023.

Prüss-Ustün A, Wolf J, Bartram J, Clasen T, Cumming O, Freeman MC, et al. Burden of disease from inadequate water, sanitation and hygiene for selected adverse health outcomes: An updated analysis with a focus on low- and middle-income countries. Int J Hyg Environ Health. 2019;222(5):765-777.

Deshpande A, Miller-Petrie MK, Lindstedt PA, et al. Mapping geographical inequalities in access to drinking water and sanitation facilities in low-income and middle-income countries, 2000-17. Lancet Glob Health. 2020;8(9):e1162-e1185.

Tapia KM, Wright J, Dreibelbis R, Langdown L. Spatial inequalities in access to drinking water in low and middle income countries. Water Res. 2023;229:119485.

Maantay JA, McLafferty S. Geospatial Analysis of Environmental Health. New York: Springer; 2011.

VoPham T, Hart JE, Laden F, Chiang YY. Emerging trends in geospatial artificial intelligence (geoAI): potential applications for environmental epidemiology. Environ Health. 2018;17(1):40.

Jitla P, Banjongrat N, Phannarus S, Thammapalo S. Spatial distribution and environmental factors associated with water quality in Southern Thailand. J Health Res. 2018;32(4):289-301.

Nilkarnjanakul W, Kanchanakool N, Laortanakul P. Assessment of drinking water quality in rural areas of Thailand. Environ Monit Assess. 2021;193(8):512.

Anselin L. Spatial econometrics: methods and models. Dordrecht: Kluwer Academic Publishers; 1988.

LeSage J, Pace RK. Introduction to spatial econometrics. Boca Raton: CRC Press; 2009.

Qiu L, Zhu J, Pan Y, et al. Spatial analysis and sanitary risk of groundwater quality in rural areas: a case study from China. Environ Geochem Health. 2022;44(7):2213-2228.

Schaider LA, Swetschinski L, Campbell C, Rudel RA. Environmental justice and drinking water quality: are there socioeconomic disparities in nitrate levels in US drinking water? Environ Health. 2019;18(1):3.

Onda K, LoBuglio J, Bartram J. Global access to safe water: accounting for water quality and the resulting impact on MDG progress. Int J Environ Res Public Health. 2012;9(3):880-894.

Kumpel E, Nelson KL. Intermittent water supply: prevalence, practice, and microbial water quality. Environ Sci Technol. 2016;50(2):542-553.

Bain R, Cronk R, Wright J, Yang H, Slaymaker T, Bartram J. Fecal contamination of drinking-water in low- and middle-income countries: a systematic review and meta-analysis. PLoS Med. 2014;11(5):e1001644.

Park Y, Kramer B. A spatial analysis of drinking water quality in the United States. Water Res. 2023;218:118487.

Hu Y, Cheng H, Tao S. Environmental and human health challenges of industrial livestock and poultry farming in China and their mitigation. Environ Int. 2019;130:104902.

Allaire M, Wu H, Lall U. National trends in drinking water quality violations. Proc Natl Acad Sci USA. 2018;115(9):2078-2083.

Jalan J, Ravallion M. Does piped water reduce diarrhea for children in rural India? J Econom. 2003;112(1):153-173.

Foster T, Willetts J, Lane M, Thomson P, Katuva J, Hope R. Risk factors associated with rural water supply failure: a 30-year retrospective study of handpumps on the south coast of Kenya. Sci Total Environ. 2018;626:156-164.

World Health Organization. Participatory approaches in health policy development: a practical guide. Geneva: WHO; 2021.

Downloads

Published

2026-04-07

How to Cite

Boonkird, T., Suerungruang, S., Boontanon, N., & Damrongpingkasakul, R. (2026). Integrating Spatial Data to Develop Sustainable Policies for Managing Domestic Water Quality. Lanna Journal of Health Promotion and Environmental Health, 16(1), 156–167. retrieved from https://he01.tci-thaijo.org/index.php/lannaHealth/article/view/285470

Issue

Section

Research article