PARTNERSHIPS FOR ENHANCED ENGAGEMENT IN RESEARCH (PEER) Cycle 5 (2015 Deadline) Implications of climate change, land use, and adaptation interventions on water resources and agricultural production in the transboundary Amu Darya River Basin PI: Zafar Gafurov (z.gafurov@cgiar.org), International Water Management Institute U.S. Partner: John Bolten, NASA Goddard Space Flight Center Project Dates: December 2016 - May 2020 Project Overview The transboundary Amu Darya and Syr Darya river basins draining to the Aral Sea in Central Asia witnessed widespread land use and land cover changes (LULCC) during 20th century as a result of political reforms of agrarian systems to enhance economic opportunities for a growing population. These developments produced drastic change in the hydrological regime of these two river basins, causing widespread ecosystem degradation. The need to sustain competing water uses at the local, national, and transboundary levels, including on upstream hydropower generation and downstream irrigation requirements under climate change, make the current situation more contentious. Realizing the need to balance and sustain competing water uses, national governments in Central Asia and international agencies are supporting numerous mitigation and adaptation interventions to improve overall water use efficiency in basins draining to the Aral Sea. However, successful interventions must be based on comprehensive understanding of the interactions in agro-hydrological systems at multiple scales covering sufficiently long time periods, and they must account for forecasted climate change impacts. Prior to this project, there were no openly available models and tools with detailed descriptions of such spatio-temporal changes and interactions of agro-hydrologic systems in the Amu Darya River Basin that could be used to inform evidence-based decision-making by national research organizations and donor agencies. Even if studies on these topics were undertaken in the past, their availability is restricted. This project promoted a greater understanding of past land use and land cover changes in the Amu Darya Basin, expected changes in the future, and basin-scale climate change impacts and adaptation interventions for water resources, using openly available long-term Earth observation datasets and a semi-distributed hydrological model (SWAT) detailing the agro-hydro-climatological system. The tools and models will act as vital management instruments for national water agencies and multilateral activities to assist in planning future interventions at basin or local scales. Final Summary of Project Activities The scope of work comprised primarily establishing partnerships, collecting data from research sites, reviewing literature and data to gather insights and gain a comprehensive understanding of water resources management in the region, establishing a database, reviewing water use issues in the region from primary and secondary data, evaluating existing water management practices in the region, and applying Geographic Information Systems (GIS) and earth observation (EO) based models, methodologies, and tools to study the management and use of water resources in the region. The project was led by IWMI in research partnership with: National Aeronautics and Space Administration (NASA), USA; Karakalpak branch of the Scientific Research Institute of Irrigation and Water Problems (KSRIIWP), Uzbekistan; Balkh University, Afghanistan; and the Institute of Water Problems, Hydropower Engineering, and Ecology of the Academy of Sciences, Republic of Tajikistan (GU TajikNIIGiM). Activities undertaken by the project team during the three years included the following: Collection of data from both upstream and downstream partner organizations in Uzbekistan, Tajikistan, and Afghanistan to be used as input for modeling. The partner organizations were actively involved and contributed with valuable information, data, and technical assistance. The data provided by partners was processed, cleaned and prepared for input to the SWAT model. Collection of remote sensing data and information from open sources and local partners, including satellite data from USGS for the Amu Darya river basin, and establishment of a database for further analyses of land cover and development of irrigated area mapping. Moreover, with the assistance of project partners, the team also collected ground truth data in the irrigated zones of the basin. Ground truth data was collected using GPS tools providing geographical locations of different crops and land cover types in irrigated zones of the study area. Development of Google Earth Engine scripting methods for modeling delineation of irrigated areas and spatio-temporal variation of vegetation coverage in the basin. Additionally, the team was able to set a model in ArcGIS model builder to automatize the process of vegetation change analysis. Collection of climate data for the Amu Darya river basin from the Centre of Hydrometeorological Service of Uzbekistan (UZHYDROMET) as well as from the database of the World Meteorological Organization (WMO). This data was used as input for the SWAT model and Evapotranspiration calculation using available methodologies. Development of digital elevation models for Amu Darya river basin, as well as Syrdarya river basin, which are located partly in the territory of Central Asian countries and Afghanistan. Based on prepared elevation maps, the team extracted slope information and its characteristics for the study area. Analyses on multiannual spatio-temporal variation of vegetation coverage for the period 2000 – 2016 was conducted using available MODIS satellite images. This analysis was done through scripting in Java API of Google Earth Engine and integrated with ArcGIS ModelBuilder. Irrigated area change analyses for Amu Darya and Syrdarya river basins were successfully calculated using LandSat satellite images for different years (1993, 2000, 2010 and 2016). Similar to the previous activity, scripting approaches were applied and integrated with ArcGIS. Additionally, ArcMap tool for Normalized Difference Vegetation Index (NDVI) calculation using satellite images were developed. This tool also allowed the team to delineate the point of interest in the study area. Historical climate variables (input data for the SWAT model) were retrieved from Global Weather Data for SWAT (https://globalweather.tamu.edu/), which provides daily Climate Forecast System Reanalysis (CFSR) data (precipitation, wind, relative humidity, and solar) in SWAT file format for a given location and time period. This data was used to set up the model for the study area. Additionally, climate data from meteostations were also obtained from UZHYDROMET. The team also collected available soil type data from various sources to use as soil input data for SWAT model. Soil type maps developed by FAO were analyzed for accuracy to meet the requirements of SWAT model. Moreover, soil maps for the territories of Uzbekistan and Tajikistan were obtained in paper format from Tajik Soil Science Research GIS and RS/EO based geodatabase and mapping tools for a region in Kashkadarya province, Uzbekistan (which is part of the Amu Darya river basin) were completed. The primary goal of the geodatabase creation was to convert raw data into graphics and maps (using GIS and RS/EO mapping tools) for visual interpretation so that they are user-friendly and can serve as a decision-support tool. It consists of various input data (land use, hydrologic data, climatological, infrastructure, basin characteristics, etc.), which were obtained from the domains of several government and non-government organizations. It shows the spatial and temporal distribution of water and land resources. The geodatabase also includes maps and tools on irrigation infrastructure (e.g., pump stations, irrigation canals, drainage network, etc.), irrigated areas by sources of irrigation, WUA boundaries, soil type and soil salinity, ground water table and its quality, digital elevation model, slope and aspect, irrigated land use change (for years 1977, 2000, 2015), and crop classification for 2016. The team also conducted a systematic literature review on socioeconomic conditions in the various sites of the Amu Darya river basin, which involved establishing a strategy for scanning and identifying relevant literature (i.e., search parameters, inclusion/exclusion criteria, coding, etc.), performing review and analysis of relevant open source databases, examining data and information collected through fieldwork and surveys, and drafting a comprehensive report with analytical findings and recommendations for next steps. The project employed the SWAT model to evaluate hydrological behavior of the Aral Sea basin and to provide remote sensing products, tools and information for the stakeholders in the region. This was one of the first attempts to run the SWAT model for entire Aral Sea basin. This model was developed using remotely sensed land use maps and soil data including climatic parameters. Outputs of the SWAT model will help better understand the use and management of water resources and serve as a decision-support tool. • The project team carried out several capacity building activities at Tashkent Institute of Irrigation and Agricultural Mechanization Engineers (TIIAME) involving students and researchers from TIIAME and UZHYDROMET, in which team members provided lectures and training sessions based on the findings from project activities. One of the major events was a two-week international summer school (Summer 2018) organized in collaboration with CAREC for students and researchers from Central Asian universities, in which team members provided lectures and training sessions based on the findings from project activities. These activities have been well received by participants, and following their success, the project team has been invited back to conduct more of these events.  • The project team also participated in numerous conferences, policy dialogues, seminars and exchange meetings to share and disseminate project outputs and discuss project findings in collaboration with ongoing PEER projects and other development projects in the region. Back to PEER Cycle 5 Grant Recipients