| Popis: |
Southeast Asian lakes provide several ecosystem services and are an important natural resource for water supplies, industry, agriculture, shipping, fishing, and recreation. It has been demonstrated that they are highly vulnerable to anthropogenic and climate threats. Recent scientific findings clearly demonstrated that climate change has already significantly affected the SEA region and that these impacts will continue and expand as the pace of climate change accelerates. However, a deep understanding of "if" and "how" climate change as well as intensification of land uses may exacerbate those impacts on such vulnerable ecosystems across the whole region is lacking.To contribute towards filling some of the existing knowledge gaps, in a renowned data scarce region, we present the results of a 3-year-long interdisciplinary research project entitled Climate Change Risk Assessment for Southeast Asian Lakes (CCRASEAL), led by the Asian Institute of Technology and funded by the Asia Pacific Network for Global Research (APN).We present new insights on: i) historical, remote sensing derived, yearly land use changes from 1992 to 2021 estimated at basin scale across whole mainland SEA; ii) historical and future changes in climate respectively for the periods 1970-2006 and 2007-2100 using different downscaled CORDEX-SEA climate data at lake level; iii) detected and assessed climate and land use long-term trends and their coupled impacts on both monthly runoff at multi-basin scale level and lake surface areas of more than 700 water bodies. Finally, we detected and assessed the satellite-derived Lake Surface Water Temperature (LSWT) trends, an essential climate variable (ECV), within defined historical and future scenarios and across whole mainland SEA.To achieve our results, we used and integrated multi-source and multi-resolution datasets made of satellite derived water and land products along with available climatic CORDEX-SEA climate datasets. Furthermore, we used a combination of conventional remote sensing, GIS, machine- and deep learning based processing approaches. In our studies we analysis possible spatial and temporal linkages between observed alterations to multiple-threats, to understand “if”, “when”, “how” and “where” climate and land use changes had affected and will affect SEA lakes.Results have been validated using, when available, ground-based observation collected at national and regional scales. |
