International LCLUC Regional Science Meeting in Central Asia

Transcription

1 International LCLUC Regional Science Meeting in Central Asia September 23, 2013 Samarkand, Uzbekistan NASA Astronaut picture from ISS Tashkent, Uzbekistan November 11-13, 2013 Shahid Habib, D.Sc., PE Chief, Office of Applied Sciences Earth Sciences Division NASA Goddard Space Flight Center

2 Contents Earth Science and Remote Sensing Data Emphases and Applications Some key studies: MENA HIMALA Nile Summary and Possible Areas for collaboration

3 Earth System Interdependencies Carbon Cycle and Ecosystem (Biosphere) Radiation and Temperature Variability Solid Earth and Interior (Lithosphere) Weather Water Cycle (Hydrosphere) Atmospheric Chemistry

4 The Shrinking Earth B people B 2013 By 2023 there will only be 4.7 ac per person 1972 Landsat 1 Launch 9.4 ac per person 1999 Landsat 7 Launch 6.2 ac 7.0 B Landsat 8 Launch 5.2 ac 7.4 B Landsat 8 Design Life End 4.9 ac 7.9 B 2023 Landsat 8 End of Consumables 4.7 ac J. Iron/GSFC

5 Earth s Response Land Cover and Land Use are changing at rates unprecedented in human history Driven by population, affluence, technology, and climate Changes to land cover/use and ecosystems are only likely to accelerate during the next 50 years These changes have profound societal consequences Food and Fiber Production Water Resource Management Human Health and Environmental Quality Habitation and Urbanization Biodiversity and also feed back to the physical climate system Atmospheric carbon Energy balance J. Iron/GSFC

6 NASA Earth Science Missions in Operation Hydrology Related Missions LCLUC Related Missions Landsat-8 (USGS) (Suomi)

7 NASA Earth Science Planned Missions ( ) SAGE-III (on ISS) 2014 OCO Grace-FO 2017 Hydrology Related Missions OCO-3 (on ISS) 2017 LCLUC Related Missions CLARREO 2023 L-Band SAR 2021 EVI GPM 2014 PACE 2020 SWOT 2020 ICESat-II 2016 EVM EVI SMAP 2014 TEMPO EVI-1, 2019 CYGNSS EVM-1, 2017

8 NASA Earth Science Data Policy is Open Source Satellite data and derived scientific products are available at no cost to all users NASA developed algorithms, models are open source, as applicable Data are made available to all users promptly Data product distribution can be within 3 hours of acquisition NASA puts great emphases on sharing data which benefits all parties including NASA i.e., Data shared is more valuable then data NOT shared

9 Areas Impacting Society Natural Disasters Agriculture Water Management Ecosystems Weather Air Quality Public Health

10 Benefits MODELS Research to Application GISS Model III GSFC GOCART Applied Research Domain GMAO Atmosphere LIS/LDAS Push Partnership Pull Data & data Products Decision Support Systems End User/ Decision Maker Terra Aura Aqua TRMM Validation & Calibration User Specific Operational Products QuikScat Landsat-7 Science and Research Products Remote Sensing Missions

11 Where to start?? Precipitation variability/drou ght Forest Fires Impact Economic and livelihood Change Albedo Problems are regional to local to urban scale Land degradation Floods Atmospheric transport Impact water quality Impact Air Quality Health impacts Mix with Dust and pollution Impact Smoke/A may be much larger involving erosols international coordination NASA observations are global NASA models are global Require regional adaptation with help from regional partners Depositi on glacier and snow Change stream flow Change radiation balance and precipitation Increase absorption Precipitation

12 Lake Chad: an icon of African Droughts Damming of river for hydroelectric Drop in precipitation Dust transport from Bodele depression Biomass burning impact precipitation Water management practices Ref: C. Ichoku/GSFC

13 Multi Agency Partnership THE WORLD BANK MENA Project Partnership MENA Middle East North Africa

14 MENA Project Address water resources issues, understand and adapt to climate change impacts for decision making and societal benefits Utilize NASA Earth Science satellite observations in conjunction with ground measurements Assist in building local expertise

15 Implementing Partners Country Egypt Jordan Implementing Organization NARSS - National Authority for Remote Sensing and Space Sciences MW&I - Ministry of Water and Irrigation MENA RJGC - Royal Jordan Geographic Center Lebanon CNRS - The National Center Remote Sensing Information System Platform Morocco CRTS - The Royal Center for Remote Sensing Project Annual Report ctober Tunisia 2011 September CRTEAN -The Regional 2012 Centre for Remote sensing of the States of North Africa CNCT - Centre National de la Cartographie et de la Te le de tection UAE International Center for Biosaline Agriculture

16 What are we after! Manage and Plan water resources in the MENA countries i.e., Know the water balance in near real time Water Storage Change Precipitation Evapotranspiration Ground Water Run Off

17 What is being addressed Thematic Areas Egypt Jordan Tunisia Lebanon Morocco Evapotranspiration x x x x x Drought x x x x x Floods Detection and Modeling Climate Change Impact Crop Mapping & Irrigation Hydrological Modeling and Analysis Locust Monitoring Fires (fuel loading) Crop Yield x x x x x x x x x x x x x x x x x

18 Formula for Success Engage Users: Must involve the users/decision makers from onset e.g., hydrological, meteorological and agricultural organizations Build Capacity: Establish subject matter champions who interfaces with NASA expert(s) in order to establish core capability per thematic area Empower Talent: Must involve young scientists and engineers in this process Involve Academia: Establish scholarships for involving students to work on real life problems Share Data: Apply in situ data to validate and calibrate NASA provided models

19 NASA Contribution Satellite data products from multibillion dollar investments in space Algorithms to generate data products Open source models: drought, evapotranspiration, flood detection and mapping, flood modeling, and hydrological modeling Climate data down scaling for conducting impact assessment Initial training on accessing and using data products and models

20 Crop Mapping and Irrigation South DeadSea irrigated agriculture North Jordan Valley irrigated agriculture Two stage approach MODIS-based mapping (at 500 meter) for regional land surface and hydrological modeling Landsat-based mapping for use in local scale water and crop growth assessment Natural Vegetation Permanent Vegetation-olives Spring irrigated Summer irrigated Ref: M. Ozdogan/Unin of Wisc

21 Morocco Precipitation and Flooding Morocco Flood, 30 th Nov CREST Model Simulation Ref: K. Thengumthara/GSFC

22 Prcp (mm/month) Climate Data Downscaling Future climate patterns are projected based on past variability patterns Climate change will alter the frequency and intensity of historically observed patterns Analyzing both Statistical downscaling and dynamical downscaling Statistical downscaling is more flexible and easily transferred Obs. Fit GCM Trends Apr: Trend fit: P-value=51%; Projected trend= mm/month/decade Time Calibration: Apr prcp anomaly at JENDOUBA, Tunisia using c1: R2=18%, p-value=2%. Ref: B. Zaitchik/JHU

23 GRACE Reveals Massive Depletion of Groundwater in NW India The water table is declining at an average rate of 33 cm/yr Trends in groundwater storage during , with increases in blue and decreases in red. During the study period, , 109 km 3 of groundwater was lost from the states of Rajasthan, Punjab, and Haryana; triple the capacity of Lake Mead Time series of total water from GRACE, rate of groundwater depletion is 4 cm/yr. Inset: Seasonal cycle. Ref: Rodell, Velicogna, and Famiglietti, Nature, 2009

24 Satellite-based Evapotranspiration LAI LST Meteosat analysis at 3km resolution, daily MODIS thermal bands to downscale to 1km Further downscaling possible with Landsat and ASTER ALEXI: Atmosphere-Land Exchange Inverse (ALEXI) model Ref: M. Anderson/USDA

25 Hydrological Modeling A Land Data Assimilation System (LDAS) is a computational tool that merges observations with numerical models to produce optimal estimates of land surface states and fluxes. SMAP + LDAS Outputs Soil Moisture Profile Fractional Snow Coverage Snow Depth and Water Equivalent Plant Canopy Soil Water Moisture Storage Soil Temperature Profile Surface Temperature Surface and Subsurface Runoff Evaporation from Soil, Snow, and Vegetation Canopy Transpiration Latent, Sensible, and Ground Heat Flux Snow Phase Change Heat Flux Snowmelt Snowfall and Rainfall (as % of Total Precipitation) Net Surface Shortwave Radiation Net Surface Longwave Radiation Aerodynamic Conductance Canopy Conductance Surface Albedo Evapotranspiration

26 5 Km simulation Nile LDAS

27 Drought Monitoring Modeling onset of 2011 Horn of Africa drought. Anderson et al. (2012) HESS

28 HIMALA ICIMOD (International Center for Integrated Mountain Development), a regional knowledge development and learning center eight regional member countries of the Hindu Kush-Himalayas Afghanistan, Bangladesh, Bhutan, China, India, Myanmar, Nepal, and Pakistan HIMALA focuses on providing new decision support capability that integrates information about snow and glacier ice melt water in stream flow models for hydrological managers ICIMOD has over a decade of experience mapping and monitoring glaciers in the region.

29 HIMALA Langtang Khola Watershed in Nepal Accumulation zone Bn > 0 Ablation zone Bn < 0 Test dataset for HIMALA Test dataset for HIMALA Glacier ELA Equilibrium Line Altitude for Mass balance Racoviteanu et al, WRR Mera glacier, Khumbu Mera glacier, Khumbu

30 HIMALA HIMALA Architecture Glacier extent (ASTER) Area-Volume relationship 1 Glacier (DEM) Equilibrium Line (DEM) 2-D gridded ICIMOD glacier cover Glacier: Initial conditions for UEB Water-Equivalent for glaciers (2006) Albedo Gridded (2006) Input Data (Dynamic Pars) for UEB (1980s to now) Relative humidity (GFS or gridded gauges) Temperature (GFS or gridded gauges) Precipitation (GFS or gridded gauges) Wind speed (GFS or gridded gauges) Short-wave Radiation (GFS or gridded gauges) Long-wave Radiation (GFS or gridded gauges) Daily albedo (MODIS, 2000-now) Why Utah Energy Balance (UEB)? -Enables integration of snow and ice into hydrological system -is simple with a small number of state variables Key Points for HIMALA: - Integrates UEB and GeoSFM - Can be run at 90m to capture glaciers - Will provide access to downscaled MERRA UEB model 2 for Glacier Melt Contribution by glacier melt (only for areas with glaciers) 3 (1-km from USGS/GLC) Land Cover (90 m) DEM (25 km from FAO) Soil Data Total Melt (in mm/day/pixel) Streamflow Model (GeoSFM) UEB model for Snow Melt Contribution by snow melt (for areas with no glaciers) Stream discharge Calibration / Comparisons with observed stream-flow - New GUI tool: MapWindow BASINS Why GeoSFM? A decade of use in the region Asia Flood Network with training of partners Notes: 1 Volume / Area relationship is need to estimate initial conditions for Glacier Water-Equivalent (This could be constant (e.g. 1.36) or based on models, empirical relationships) 2 Utah Energy Balance (UEB) model - It will be run at 90m resolution / 6-hour time-step Will be run sub-basin by sub-basin (start with sub-basin with largest glacier contribution) 3 (i) snow over ice, (ii) ice, or (iii) debris over ice (IF albedo=snow-albedo THEN this is snow-over-ice, so the regular (snow-melt) UEB will be run. IF albedo=ice-albedo THEN the new( glacier-melt) UEB model component will be run) 4 Initial conditions for SWE will be estimated based on precipitation SWE 4 (daily maps)

31 Function Research/Ap plication Path Forward (A) - my initial guess Kazakhstan Kyrgyzstan Tajikistan Turkmenistan Uzbekistan Start Precipitation change A x x x x x QS Evapotranspiration A x x x x x DS Crop Mapping A x x x x x SS Hydrological system R/A x x x x x DS Ground Water R/A????? DS Glacier-snow melt R/A? x x?? DS Drought/Food Security A x x x x x SS Land degradation R/A x??? x DS Desertification Aerosol transport Radiation balance Albedo R x??? x DS Climate Impact R x x x x x DS Invasive species R/A x??? x SS Floods A x x x x x SS Fires A x?? x x QS QS- Quick Start SS- Slow Start DS- Delayed Start

32 Path Forward (B) Integrated System Conduct systems engineering process: Build a baseline/per country or region - Analyze and evaluate what has been done - Identify the gaps - Develop a pathway to complete the gaps Identify data sets and tools - Identify in situ data sets - Identify local technical capacity - Get users involved Complete analysis - Conduct scenarios backward/ forward Start small Identify pilot projects - Identify Champions to lead - Continue to look for donors Gradually move on to bigger things Coming together is a beginning. Keeping together is progress. Working together is success. ~ Henry Ford

33 Visualizing Nile Basin Water Balance Utilizing NASA s multisensor observations and models help visualize critical parameters: soil moisture, precipitation, evapotranspiration and NDVI in understanding the water balance of the entire Nile basin. Ref: SVS/GSFC