Michelle V. Japitana, Alexander T. Demetillo, Evelyn B. Taboada, Chul-Soo Ye, Marlowe Edgar C. Burce
Sustainable management of surface water systems requires systematic and comprehensive monitoring of water quality, however, the attempts to obtain this in developing countries are challenged due to the lack of an integrated framework and limited resources. Most of the developing countries' water quality monitoring and assessment (WQMA) program lacks facilities, equipment, manpower and expertise that results in an insufficient number of sampling data that lack temporal and spatial trends. The government-sponsored WQMA programs usually employ traditional procedures like field measurements and collection of water samples for subsequent laboratory analysis. While such conventional approach to WQMA data is accurate at a specific location and time, in most cases, it cannot provide enough information on the overall quality of water. Fortunately, the emerging technologies of Geoinformatics and Wireless Sensing, provide useful tools for a comprehensive WQMA program. Application of these advanced technologies engages communities and local leaders to implement best management practices in water quality monitoring. Hence, the main goal of this study is the implementation of a systematic and comprehensive WQ monitoring and assessment which combines the paradigm of Geoinformatics and Wireless Sensing. An integrated WQMA framework utilizing both wireless sensor-based and in-situ water quality data is conceptualized and pilot-tested in Tubay, Agusan del Norte's water catchment as proof of concept. In this study, methods and modeling techniques were presented to show that the proposed framework is effective and operational in performing WQ measurement, catchment characterization, water body mapping, and WQ data modeling and mapping. Results of this study prove that methods and models can be derived in the context of performing a comprehensive but cost-efficient WQMA using free Remote Sensing (RS) tools. By implementing the integrated WQMA framework and validating its results and performances, this study is able to present an operational WQMA system that enhances the traditional method by providing an improved spatial and temporal scale of water quality data collection allowing trend analysis, enhanced WQMA processes, and methods for a convenient and a low-cost monitoring and assessment processes. © 2020 40th Asian Conference on Remote Sensing, ACRS 2019: "Progress of Remote Sensing Technology for Smart Future". All rights reserved.
Univ. of San Carlos, Talamban, Cebu City, 6000, Philippines; Caraga State Univ., Ampayon, Butuan City, 8600, Philippines; Far East Univ., 76-32 Daehakgil, Gamgok-myeon, Eumseong-gun, Chungbuk, South Korea
