The Oum Er-Rbia Watershed Web Mapping System -- A Model for Open-Source Water Quality Dissemination.

The Oum Er-Rbia watershed faces a critical challenge in effectively disseminating the results of groundwater and surface water quality assessments to stakeholders and the public. This research aimed to address this challenge by developing a method for synthesizing and visualizing knowledge through web mapping. The methodology followed involved collecting data on surface and groundwater quality, hydrogeology, human impact, and topography. Subsequently, a needs analysis was conducted to identify the requirements of potential users (land managers, water users, researchers) to de- fine system functionalities. Spatial data was organized into thematic layers (e.g., hydrography, geology) with detailed attributes to address user queries and generate maps. Open-source technologies were employed to build a web-based system (SCIEM) allowing users to visualize, analyze, and explore water quality data. Finally, user evaluation confirmed SCIEM's effectiveness in disseminating and analyzing water quality information within the watershed. The developed web mapping system has successfully addressed the challenge of disseminating research results by establishing an online, interactive multi-scale mapping system for groundwater and surface water characterization. This system facilitates the presentation of maps with a simple click, making them accessible to both geospatial experts and non-specialists. As a result, stakeholders such as water managers, land-use planners, and even farmers and citizens can now access a comprehensive view of groundwater and surface water information. Additionally, the utilization of free and open-source software has proven to be a cost-effective and efficient approach. The interactive multi-scale mapping system (IMSMS) provides a valuable tool for disseminating water quality data within the Oum Er-Rbia watershed. Building on this success, future research can explore the potential of adapting the IMSMS framework to other regions facing water quality challenges. Additionally, incorporating new data types beyond water management could provide a more holistic understanding of the interconnected factors influencing water resources. [ABSTRACT FROM AUTHOR]