Web-Based Decision Support System for Managing the Food–Water–Soil–Ecosystem Nexus in the Kolleru Freshwater Lake of Andhra Pradesh in South India

Sustainability

Christian Opp¹  Daniel Karthe²  Meena Kumari Kolli³  Nallapaneni Manoj Kumar⁴ 

[1] Faculty of Geography, Philipps-Universität Marburg, Deutschhausstraße 10, 35037 Marburg, Hesse, Germany;Institute for Integrated Management of Material Fluxes and of Resources, United Nations University, Ammonstr. 74, 01067 Dresden, Saxony, Germany;National Academy of Agricultural Sciences, NASC, Pusa Campus, New Delhi 110012, India;School of Energy and Environment, City University of Hong Kong, Kowloon, Hong Kong;

关键词: Kolleru Lake;    land use;    aquafarming;    fishponds;    illegal fishponds;    food–water–soil–ecosystem nexus;   

DOI  :  10.3390/su14042044

来源: DOAJ

【 摘 要 】

Most of the world’s freshwater lake ecosystems are endangered due to intensive land use conditions. They are subjected to anthropogenic stress and severely degraded because of large-scale aquafarming, agricultural expansion, urbanization, and industrialization. In the case of India’s largest freshwater lake, the Kolleru freshwater ecosystem, environmental resources such as water and soil have been adversely impacted by an increase in food production, particularly through aquaculture. There are numerous instances where aqua farmers have indulged in constructing illegal fishponds. This process of aquafarming through illegal fishponds has continued even after significant restoration efforts, which started in 2006. This underlines the necessity of continuous monitoring of the state of the lake ecosystem in order to survey the effectiveness of restoration and protection measures. Hence, to better understand the processes of ecosystem degradation and derive recommendations for future management, we developed a web mapping application (WMA). The WMA aims to provide fishpond data from the current monitoring program, allowing users to access the fishpond data location across the lake region, demanding lake digitization and analysis. We used a machine learning algorithm for training the composite series of Landsat images obtained from Google Earth Engine to digitize the lake ecosystem and further analyze current and past land use classes. An open-source geographic information system (GIS) software and JavaScript library plugins including a PostGIS database, GeoServer, and Leaflet library were used for WMA. To enable the interactive features, such as editing or updating the latest construction of fishponds into the database, a client–server architecture interface was provided, finally resulting in the web-based model application for the Kolleru Lake aquaculture system. Overall, we believe that providing expanded access to the fishpond data using such tools will help government organizations, resource managers, stakeholders, and decision makers better understand the lake ecosystem dynamics and plan any upcoming restoration measures.

【 授权许可】

Unknown