Assessing Rainwater Harvesting Potential in Seawater-Based Communities Using the Case Study of Poblacion Sitangkai, Philippines

Abstract:

A lack of fresh water is a serious issue in communities near or surrounded by seawater, such as Sitangkai Poblacion, where they rely heavily on the ocean for their water source. QGIS with vector grid as the tool will help to study the possibility of efficient rainwater harvesting. Data processing for analysis of rainfall data from Weatherlink station in Bongao, Tawi-Tawi, and roof area digitization conducted for Sitangkai Poblacion. The spatial distribution of rainwater harvesting was assessed systematically at the 200 m x 200 m vector grid level. Data was collected on monthly precipitation during June 2023 and March 2024 to estimate possible water collection volumes. The results present significant grid-to-grid variability in the potential for rainwater harvesting, driven by roof area and regional rainfall patterns. The months when there was a lot of rainfall during the rainy season are significantly associated with the month peak rainwater harvesting occurred; this means an ideal time to boost water collection. The study demonstrates the necessity of specific rainwater harvesting approaches that focus on dominant household variables in conjunction with improved storage and holistic water handling procedures for sustainable solutions for these areas. Vector grid in QGIS can be a potential methodology for researchers to spatially analyze and guide sustainable water resource planning addressing freshwater scarcity.

• Periodical: Engineering Innovations (Volume 13)
• Pages: 57-73
• DOI: https://doi.org/10.4028/p-h2WAGU
• Online since: February 2025
• Authors: Marie Fe Y. Lacsado*, Doris B. Montecastro
• Keywords: Digitized Roof Area, Geographic Information System, Rainfall Data, Rainwater Harvesting Potential, Seawater-Based Community, Spatial Analysis, Vector Grid

References

[1] D. M. Bushnell, "Halophytes/Saline Water/Deserts/Wastelands Nexus as a Scalable Climate Mitigation including Freshwater Impacts," Water, vol. 16, no. 3, p.373–373, Jan. 2024.

DOI: 10.3390/w16030373

[2] N. Afsari, S. B. Murshed, S. M. N. Uddin, and M. Hasan, "Opportunities and Barriers Against Successive Implementation of Rainwater Harvesting Options to Ensure Water Security in Southwestern Coastal Region of Bangladesh," Frontiers in Water, vol. 4, May 2022.

DOI: 10.3389/frwa.2022.811918

[3] P. Blanco-Gómez, C. Amurrio-Garcia, J. L. Jiménez-García, and J. M. Cecilia, "CPR Algorithm—A new interpolation methodology and QGIS plugin for Colour Pattern Regression between aerial images and raster maps," SoftwareX, vol. 22, p.101356, May 2023.

DOI: 10.1016/j.softx.2023.101356

[4] G. W. Pereira, D. S. M. Valente, D. M. de Queiroz, A. L. de F. Coelho, M. M. Costa, and T. Grift, "Smart-Map: An Open-Source QGIS Plugin for Digital Mapping Using Machine Learning Techniques and Ordinary Kriging," Agronomy, vol. 12, no. 6, p.1350, Jun. 2022.

DOI: 10.3390/agronomy12061350

[5] V. Saxena, P. Mundra, and D. Jigyasu, "Efficient Viewshed Analysis as QGIS Plugin," IEEE Xplore, December 01, 2020. https://ieeexplore.ieee.org/abstract/document/9362730 (accessed March 29, 2023).

DOI: 10.1109/icacccn51052.2020.9362730

[6] Kundan Dhakal, "An introduction to spatial data analysis: remote sensing and GIS with open source software. Martin Wegmann, Jakob Schwalb‐Willmann, and Stefan Dech. 2020. Pelagic Publishing, Exeter, United Kingdom. 365 pp. $40.28 paperback. ISBN: 978‐1‐78427‐213‐5," Journal of Wildlife Management, vol. 86, no. 7, Jul. 2022.

DOI: 10.1002/jwmg.22295

[7] Kundan Dhakal, "An introduction to spatial data analysis: remote sensing and GIS with open source software. Martin Wegmann, Jakob Schwalb‐Willmann, and Stefan Dech. 2020. Pelagic Publishing, Exeter, United Kingdom. 365 pp. $40.28 paperback. ISBN: 978‐1‐78427‐213‐5," Journal of Wildlife Management, vol. 86, no. 7, Jul. 2022.

DOI: 10.1002/jwmg.22295

[8] A. L. Muller, O. J. Gericke, and J. P. J. Pietersen, "Methodological approach for the compilation of a water distribution network model using QGIS and EPANET," Journal of the South African Institution of Civil Engineering, vol. 62, no. 4, p.32–43, Dec. 2020.

DOI: 10.17159/2309-8775/2020/v62n4a4

[9] L. Raimondi, G. Pepe, M. Firpo, D. Calcaterra, and A. Cevasco, "An open-source and QGIS-integrated physically based model for spatial prediction of rainfall-induced shallow landslides (SPRIn-SL)," Environmental Modelling & Software, p.105587, Nov. 2022.

DOI: 10.1016/j.envsoft.2022.105587

[10] D. Kumar, A. Dhaloiya, A. S. Nain, M. P. Sharma, and A. Singh, "Prioritization of Watershed Using Remote Sensing and Geographic Information System," Sustainability, vol. 13, no. 16, p.9456, Aug. 2021.

DOI: 10.3390/su13169456

[11] D. Kumar, A. Dhaloiya, A. S. Nain, M. P. Sharma, and A. Singh, "Prioritization of Watershed Using Remote Sensing and Geographic Information System," Sustainability, vol. 13, no. 16, p.9456, Aug. 2021.

DOI: 10.3390/su13169456

[12] J. Pérez-Padillo, J. G. Morillo, E. C. Poyato, and P. Montesinos, "Open-Source Application for Water Supply System Management: Implementation in a Water Transmission System in Southern Spain," Water, vol. 13, no. 24, p.3652, Dec. 2021, doi: https://doi.org/10.3390/ w13243652.

DOI: 10.3390/w13243652

[13] Wilian Rodrigues Ribeiro et al., "Water demand of central pivot-irrigated areas in Bahia, Brazil: management of water resources applied to sustainable production," vol. 24, no. 10, p.12340–12366, Nov. 2021.

DOI: 10.1007/s10668-021-01950-8

[14] A. Alamanos and S. Linnane, "Estimating SDG Indicators in Data-Scarce Areas: The Transition to the Use of New Technologies and Multidisciplinary Studies," Earth, vol. 2, no. 3, p.635–652, Sep. 2021.

DOI: 10.3390/earth2030037

[15] K. F. Darweesh et al., "Three decades of remote sensing habitat mapping, along the Egyptian Coast of Aqaba Gulf, Red Sea," Egyptian Journal of Aquatic Biology and Fisheries, vol. 25, no. 6, p.467–487, Dec. 2021.

DOI: 10.21608/ejabf.2021.214042

[16] M. Shamkhi, A. Jawad, and T. Jameel, "Comparison between Satellite Rainfall Data and Rain Gauge Stations in Galal-Badra Watershed, Iraq," Oct. 2019, doi: https://doi.org/10.1109/dese. 2019.00069.

DOI: 10.1109/dese.2019.00069

[17] T.T.B. Valeriano, G. de Souza Rolim, R.C. Bispo, J. R. da Silva Cabral de Moraes, and L.E. de O. Aparecido, "Evaluation of air temperature and rainfall from ECMWF and NASA gridded data for southeastern Brazil," Theoretical and Applied Climatology, vol. 137, no. 3–4, p.1925–1938, Nov. 2018.

DOI: 10.1007/s00704-018-2706-z

[18] S. Ali, Z. T. Xu, M. Henchirli, K. Wilson, and J. Zhang, "Studying of drought phenomena and vegetation trends over South Asia from 1990 to 2015 by using AVHRR and NASA's MERRA data," Environmental Science and Pollution Research, vol. 27, no. 5, p.4756–4768, Dec. 2019.

DOI: 10.1007/s11356-019-07221-4