Assessing the Impacts of Dams on the Dynamic Interactions Among Distant Wetlands, Land Use, and Rural Communities in the Lower Mekong River Basin

Principal Investigator: 
Jiaguo Qi
Michigan State University, USA

Governments in Southeast Asia face the formidable challenge of rising economic aspirations of their growing populations in the context of climate change in a region where landscapes are still mainly agricultural. One potential solution involves the operation of dams built to produce electricity to also support agricultural intensification, minimize negative environmental impacts, and mitigate the effects of extreme weather events. Identifying such scenarios requires a robust understanding of past land change trajectories, accounting for physical and socioeconomic factors, within a framework that can project the potential consequences of future policy choices. The proposed project brings together state-of-the-art remote sensing techniques with appropriate approaches from climatological, hydrological, and social sciences to inform policies in the Lower Mekong River Basin (LMRB). The proposed research will be implemented in tandem with a funded NASA IDS project that will undertake hydrological modeling across the LMRB focusing on the nexus of dams, water, wetlands and society. The overall goal of this project is to use advanced remotely sensed information to improve our understanding of the dynamic interactions among hydropower dams, distant ecosystem services, and livelihoods in rural communities with an emphasis on economic, ecological, and social tradeoffs under a range of dam operation scenarios in the LMRB. The objectives of the proposed research are: Objective 1: Building upon existing land use/cover information, along with location, capacity, and flow regulation of hydroelectric dams in the LMRB, our team will identify detailed land use attributes critical to household land use decision making in three selected watersheds. Specific land attributes include detailed hydroperiods and thermal dynamics of lakes and wetlands and wetland structure and composition, which will serve as inputs to Objective 2. Objective 2: Building on existing hydrological models, our team will quantify ecosystem functions and services crucial to households. These include hydroperiod and cropping feasibility/potential of distant wetlands, thermal dynamics and linkages of affected lakes with river flows, and water resources for rural communities. This information, along with field surveys and historical land uses, will be used as inputs for analysis of societal effects and responses in Objective 3. Objective 3: Using innovative social science approaches our team will model social motivations, consequences, and adaptation strategies that result from land use changes, accounting for dynamic interactions among dams, ecosystem services, and livelihoods. Methods. Objective 1 will be accomplished using a combination of optical and radar imagery acquired by the Landsat and Sentinel platforms in combination with in-situ data from field surveys and ancillary information from local partners. Objective 2 will employ the dense temporal- and high spatial-resolution information from optical, thermal, and SAR sensors to develop n-dimensional “feature” signatures of land attributes, using the processed data and information from Objective 1 in combination with in-situ observations. Objective 3 will rely on a variety of quantitative and qualitative social science methodologies, including household surveys, ethnographic observation, in-depth and key informant interviews, participatory mapping, and scenario evaluation. Significance. The proposed project directly addresses the scope of the solicitation by quantifying land change trajectories in an important region in Southeast Asia, understanding the physical and social causes and impacts of these dynamics, thereby advancing land change science while providing policy relevant information on governance options. The project will further strengthen long term collaboration with a wide range of regional partners