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An Integrated Hydrological and Water Management Study of the Entire Nile River System – Lake
Victoria to Nile Delta
(IGARSS paper 1198: Session FR3-TR10)July 29, 2011
Vancouver, Canada
Shahid Habib, NASA Goddard Space Flight CenterBen Zaitchik, Johns Hopkins UniversityClement Alo, Johns Hopkins UniversityMutlu Ozdogon, University of WisconsinMartha Anderson, US Department of AgricultureFritz Policelli, NASA Goddard Space Flight Center
• Countries of the Nile basin face challenges related to hydrologic extremes and water resource planning.
• NASA observations and tools can provide consistent, reliable estimates of hydrological states and fluxes, even in remote areas. This information can be applied to early warning systems and decision support.
• Improved information on floods, droughts, and climate-induced changes in hydrology are critical for all countries.
Lower Nile
UpperNile
BlueNile
WhiteNile
LakeVictoria
LakeNasser
Introduction
Partners, Users and Interested Parties
PartnersNASAJohns Hopkins Global Water ProgramUSDA Hydrology and Remote Sensing LabUniversity of Wisconsin
UsersThe Regional Center for Mapping of Resources for Development(The Nile Basin Initiative and Eastern Nile Technical Regional Office)Addis Ababa UniversityFuture University, KhartoumEthiopian Mapping Authority, Ethiopian Environmental AuthorityEthiopian Meteorology
Interested EntitiesThe World BankUSAIDU.S. Department of StateUNESCO
The Nile Basin
• 3.35 million km2
• 6,650 km longLowerNile
Atbara
BlueNile
SobatWhiteNile
TheLakes
Sudd
Bahrel-Ghazal
The Nile Basin
• 3.35 million km2
• 6,650 km long• Climates range from
humid tropical to hyper-arid
The Nile Basin
• 3.35 million km2
• 6,650 km long• Climates range from
humid tropical to hyper-arid
• The vast majority or precipitation falls in the Ethiopian and Lake Victoria headwaters regions
The Nile Basin• Annual flow at Aswan: 84 BCM• 86% Ethiopia; 14% Equatorial
Lakes• Large seasonal variability in the
Blue Nile and Atbara• Interannual variability can affect
both the Blue and the White Nile
July 10, 2011Bottom of Tissisat falls
July 8, 2011Choke Mountain gorge
The Nile Basin
• 190 million people– 50% below the poverty line
• 10 nations– 8 are defined as Least Developed
Countries– 4 are nationally water scarce
today– 6 are predicted to be water scarce
by 2025– 7 have experienced war in the
past 20 years
• At present, there is no water sharing agreement or joint management plan
Lower Nile night view from satellite
NILE Basin Countries
Ref: UNEP Project GNV011,Jan-Jun 2000, Diana Karyabwite
Semi-distributedhydrological model
Dynamic water budget and allocation model
Resource analysis
Multicriteria analysis and optimization
Scenario definition
Static Parameters: Topography, Soil Types, WatershedsAtmospheric Data: Precipitation, Air Temperature, Wind speed, Incoming radiationManagement Parameters: Land cover, Crop type, Irrigation status
Routing information:River NetworkReservoirsWithdrawals
Water Allocations
Socio-economic and environmental parameters
Sectoral, spatial, temporal and
frequency distribution of benefits and
impacts
Hydrological states and
fluxes
Information Management System
Model System
Analysis System
* *
*
*
NASA’s Project Nile
Components: 1. Customized Land
Data Assimilation System
2. Land cover mapping and simulation
3. Satellite-derived evapotranspiration
4. Integration to Decision Support
Goal: improved hydrometeorological information for research, planning, and water management
LDAS
Land Cover Mapping Evapotraspiration
Decision Support System
Land Surface Model
Meteorological Data
Landscape Information
LDAS Output
SM ET Runoff
Update Observations
A Land Data Assimilation System (LDAS) is a computational system that merges observations with numerical models to produce optimal estimates of land surface states and fluxes.
LDAS Outputs
Soil Moisture Profile
Fractional Snow Coverage
Snow Depth and Water Equivalent
Plant Canopy Water 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
LDAS Early Results - 2001-2009 climatology
(Using Noah Land Surface Model)Precipitation input: Rain Fall Estimate at 10 km-3 hourly, WMO Stations
Evapotranspiration at 5 km resolution
Precipitation – Evapotranspiration = Surface and Subsurface runoff -5 km
LDAS Early ResultsUsing last 30 years (1980-2010) ENSO data
C. Alo, JHU
El Nino years 4 months precipitation- Jun, Jul, Aug, & Sep
La Nina years 4 months precipitation- Jun, Jul, Aug, & Sep
Warmer years produce less precipitation over E. Africa
Cooler years produce more precipitation over E. Africa
Land Cover Mapping
A Nested Approach:• Continental scale maps (from MODIS) with
general land cover categories (used for deriving the model)– Used for landscape scale sampling
• Regional maps (from Landsat - agriculture) with detailed land use categories– 1:25,000 scale– Detailed description of the land cover
• Local scale mapping (commercial)– For detailed analyses and true area estimation
M. Ozdogan, Univ. of Wisconsin
MODIS-based regional map(VIS to 2.4 micron – reflected domain)
Friedl et.al., 1999 IEEE TGARS
• Collect one year of 8-day composited MODIS surface reflectance data
• Identify representative temporal profiles for general land cover classes
• Apply an automated Decision Tree algorithm (using band comparison) to classify each pixel
• Use this map as a guide for sampling the landscape for detailed analyses
Root
Leaf nodes
Internal nodes
M. Ozdogan, Univ. of Wisconsin
Data
Decision criteria
Final classified label
forestshrublandgrasslandagriculturebarren
M. Ozdogan, Univ. of Wisconsin
Yearly product based on MODIS 8-day composite at continental scale - 2005
forestshrublandgrasslandagriculturebarren
Landsat footprint for regional mapping
Landsat – 30M Scale - 2005Winter - December
ShrubsAgriculture
Forest
Clouds
Spring, Summer, Fall and Winter averaged
Topographic view
Choke Mountain Caldera
Landsat
MODIS
Commercial with 0.5 m resolution
Northern Ethiopia heterogeneous landscape requires high resolution imagery
TSoilTSoil
Tsoil & Tveg Tsoil & Tveg
Given known radiative energy inputs, how much water loss is required to keep the soil and vegetation at the observed temperatures?
transpiration & evaporation
soil evaporation
SURFACE TEMPERATURESURFACE TEMPERATURE
TvegTveg
Satellite-derived Evapotranspiration
M. Anderson, USDA
Regional scaleΔTRAD - Geostationaryfc - MODIS (vegetation cover function)
Landscape scaleTRAD - TM, ASTER, MODISfc - TM, ASTER, MODIS
Rsoil
TcTac
Hs
Ts
RaH = Hc + Hs
Rx
Hc
Ta
ABL
Ta
ALEXI DisALEXI
5 km30 m
Tw
o-S
ou
rce M
odel
TRAD (φ), fc
TRAD,i(φi), fc,i
i
Ra,i
Blending height
Rsoil
TcTac
Hs
Ts
RaH = Hc + Hs
Rx
Hc
TaTa
ABL
Ta Ta
ALEXI DisALEXI
5 km30 m
Tw
o-S
ou
rce M
odel
TRAD (φ), fc
TRAD,i(φi), fc,i
i
Ra,i
Blending height
Surface temp:Cover fraction:
ET: The Atmosphere-Land Exchange Inverse (ALEXI) Model
(Atmospheric Boundary Layer)
Sensible Heat:Canopy Heat:
(from Landsat thermal band 100m)
Early Results: clear-sky ET composites (2008)
June JulyWm-2
M. Anderson, USDA
(~ 6 km resolution)
2009 FEBRUARY
Average ALEXI ET Average LDAS ET
(MJ m-2 d-1)
Note ET from Sudd and Nile Delta in ALEXI, not captured in LDAS.
2009 JANUARY-DECEMBER
Average ALEXI ET (MJ m-2 d-1) Average ALEXI ET/PET
Nile-LDAS
Applications: Decision Support
Management and DSS
Lan
d C
over
Map
sS
ate
llit
e E
TP
recip
itati
on
• Drought monitoring• Water resource analysis• Early warning systems• Planning for change
Summary
• Many researchers have studied this region over the last three decades
• NASA is taking another integrated look at the entire region using satellite observations and multitude of land surface/hydrological models
• The most significant aspect of this work is to validate using in situ measurements and depends on the regional partners willingness to share in situ data
• As a starting point, we are working with Ethiopian hydrology and Meteorology offices to get such data for the Blue Nile head waters
• We also plan to simulate future climate impact on hydrology using IPCC scenarios
• Our work will be published on a scientific basis Ancient map drawn by Ptolemy