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Satellites for Hydrology
Prem Chand Pandey
School of Earth, Ocean and Climate Sciences
Indian Institute of Technology Bhubaneswar
Khurda, Jatni, 752050
Odisha
PPT:courtesy Parag Narvekar (Aapah Innovations), Abhisek Rai IITBBS &
Mihir K. Dash, IIT Kharagpur
GRACE:GRAVITY RECOVERY AND CLIMATE
EXPERIMENT
• GRACE is the first Earth Monitoring Mission in the History whose key
measurements are not derived from Electromagnetic Waves
• INSTEAD
• The mission uses Microwave Ranging System to accurately measure
changes in speed and distance between two identical spacecraft
flying in a Polar Orbit about 220 km apart at ~500km above the Earth.
The Global Water Cycle: What are the Main
Challenges!
What are some key issues that cannot be addressed without a next
generation gravity mission?
•Is the global water cycle accelerating?
•Land contributions to global mean sea level rise
•Global freshwater availability and sustainability
•Emergence of long-term trends
•Enhanced space-time resolution for better utilization in hydrological
applications
Obstacles to Using Satellite Gravity for
Applications
1) Product latency
• Near-real time information is vital for operational applications
2) Low spatial resolution
• Most practical applications require observations at scales of 0.01 –
2500 km
3) Lack of vertical information
• Groundwater, soil moisture, surface water, or snow
4) Low temporal resolution
• Most hydrological processes operate on hourly to weekly timescales
Potential Applications
• Water Resources Assessments
• Drought monitoring
• Ground water depletion
• Seasonal snow load
• Streamflow forecasting (based on upland water storage)
• Transboundary water resources sharing
• Weather and Climate Prediction -Via improved forecast model land surface state
initialization -Implications for Water Resources, Aviation Safety, Agriculture, and
Disaster Preparedness
• Solid Earth
• Ocean
• Ice sheet Dynamics
EXAMPLE-APPLICATION
GRACE is unique among Earth observing missions in its ability to monitor variations in all water stored on
land, down to the deepest aquifers
Rodell, Velicogna, and Famiglietti,
Nature, 2009
Groundwater Monitoring Example: NW India
The water table is declining at an average rate of 33 cm/yr
During the study period, 2002-08, 109 km3of groundwater was lost
from the states of Rajasthan, Punjab, and Haryana;
EXAMPLE-MASCON APPROACH
Save, H., S. Bettadpur, and B.D. Tapley (2016), High resolution
CSR GRACE RL05 mascons, J. Geophys. Res. Solid Earth, 121,
GRACE L2 [JPL04] 400 by 600km filtered
Trend fitted from GRACE L2 solution
[JPL04 with 400km by 600km nonisotropic
filtered]
COMPARISION WITH MODEL
Potential Solutions
1) Product latency
• - Near-real time information is vital for operational applications
• Solutions: More rapid processing of raw data; Data assimilation
2) Low spatial resolution
• - Most practical applications require observations at scales of 0.01 – 2500 km
• Solutions: Lower altitude, drag-free, laser ranging (sans aliasing) mission; DA
3) Lack of vertical information
• - Groundwater, soil moisture, surface water, or snow
• Solutions: Combine with other observations (e.g., SMOS, SMAP); DA
4) Low temporal resolution
• Most hydrological processes operate on hourly to weekly timescales
• Solutions: Mascons; Constellation of satellites; DA
Conclusions
• GRACE is already proving to be valuable for practical applications including
drought monitoring, regional water resources assessments, and estimating
rates of groundwater depletion
• Obstacles to using satellite gravimetry for practical applications include
data latency, coarse spatial and temporal resolutions, and lack of vertical
structure
• Some of these obstacles may be overcome with a high performance follow-
on to GRACE; others will require more efficient and innovative processing
of level-1 data or data integration/assimilation
• An emerging obstacle is the lack of commitment to a follow-on mission,
such that water managers may be afraid to rely on GRACE
• GRACE-FO Expected in 2017
TAKE HOME MESSAGE
• GRACE data currently provide an accurate measurement of the
worldʼs water reservoir mass change with a spatial resolution longer
than 500 km (half-wavelength) and monthly sampling or finer
• GRACE twin-satellite sensor is a relatively new measurement – and
still requires substantial efforts to further refine data processing – is
anticipated to revolutionize the terrestrial hydrologic research and
applications
• Water is the lifeblood of Earth, and GRACE time series, for the
whole earth, for the continents, for river basins or for
watersheds, should emerge as one of several critical indicators
of regional health and sustainability
Surface Soil Moisture Observations
• GRACE mission provides groundwater assessment over the spatial
resolution of two degrees.
• Therefore, to understand the hydrological impact at medium to
higher spatial resolution surface soil moisture data, being variable at
land atmosphere boundary is of particular significance.
• Dr. Parag Narvekar (student of Prof. Pandey) has developed an radar
algorithm for NASA’s aircraft and satellite missions to provide near
real-time soil moisture product.
Bare-Soil to Full-Vegetation is a Mixing Model Using RVI :
Roughness ks Modifies the Parameter Magnitude According to RRI:
And the λ Power Term Depends on Vegetation Density as;
λ = RVI for RVI >0.3 and λ = 0.3, for RVI <= 0.3.
rs
VV
v
VVVV RVIRVIdB   )1()(
    
 mvSksRVIRVIdBVV  01log1)1()(
    vf
VV
s
VV RVIksCRVI   )1log(1 0
16
Overview of L-band Radar Model
Narvekar et al. IEEE TGRS 2015
Aquarius Radar Estimates with NCEP (Coarser Resolution 90 km)
 Global 7-days data compared.
 Density distribution of more than 55000 points.
SMAP Soil Moisture mv Map Example (3km spatial resolution)
PALSAR Data (25 meter) High-Res projected in Karnataka watershed
Additional Important Variables
• The Algorithm developed in Narvekar et al 2015 also provide high
resolution vegetation and surface roughness effects
• This information is also useful for generating root zone maps.
• The moisture level at surface and root zone could provide unique
opportunity to accurately model ground water predictions using
home made satellites such as NISAR (see upcoming root-zone slide).
21
Roughness from PALSAR, Berambadi Watershed
• Water bodies appears blue indicating areas with lower roughness.
• Roughness is useful parameter for mapping erosion processes.
• Also changing roughness in the field scale could be studied.
Narvekar et al. JGRS 2016
22
Vegetation from PALSAR, Berambadi Watershed
• Radar based vegetation information is estimated from volumetric properties
• This provide essential component based on quantity of vegetation.
Narvekar et al. JGRS 2016
Average root-zone moisture of the month
• The contributing of root-zone soil moisture is computed based on soil water content estimated at the end of
the day.
• Root-zone is computed using simplified solutions to Richard’s equations.
ROOT ZONE SOIL MOISTURE MAY 2016– ESA-
SMOS
Aapah Innovations, Pvt. Ltd.
INNOVATIONS
contact@aapahinnovations.com
www.aapahinnovations.com
Dr. Parag Narvekar is presently with
We Strive to Serve for Government and Research Institutions
Providing software and mathematical algorithm development applicable for Indian
conditions
Dr. Sat Kumar Tomer
Technical Director
PhD: Indian Institute of Science,
Bangalore
Research Experience:
•CESBIO, Toulouse, France
Dr. Parag Narvekar
Head R&D
PhD: Berman University, Germany
Research Experience:
•JPL, NASA, USA
•Massachusetts Institute of Technology (MIT), USA
Thiyaku S.
GIS Engineer
M Tech – Remote sensing
and GIS
Research Experience:
•NRSC, Hyderabad
Our Core Team
Our Technical Advisory Board
Prof. Bimlesh Kumar
Associate Professor
IIT Guwahati
Prof. M. Sekhar
Professor
IISc, Bangalore
Dr. C. T. Dhanya
Assistant Professor
IIT Delhi
Dr. Gulab Singh
Assistant Professor
IIT Bombay
Our Solutions
•User-friendly software (of complex Algorithms) for near real-time satellite products
•Ability to provide data science solutions for water resources and local weather
Our Team
•Professionals from premiere institutions of India and abroad
•Highly experienced and trained personnel
Project Delivery
•Reliable delivery mechanism and project management
•Automation leading to project duration compression
•Long term support
Our Products
•Competitive pricing
•Tailored products
•Only company with higher spatial resolution soil moisture
www.aapahinnovations.com
contact@aapahinnovations.com
+91 (0) 40 2300 4414

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IUKWC Workshop Nov16: Developing Hydro-climatic Services for Water Security – Session 6 – Item 1 PC_Pandey

  • 1. Satellites for Hydrology Prem Chand Pandey School of Earth, Ocean and Climate Sciences Indian Institute of Technology Bhubaneswar Khurda, Jatni, 752050 Odisha PPT:courtesy Parag Narvekar (Aapah Innovations), Abhisek Rai IITBBS & Mihir K. Dash, IIT Kharagpur
  • 2. GRACE:GRAVITY RECOVERY AND CLIMATE EXPERIMENT • GRACE is the first Earth Monitoring Mission in the History whose key measurements are not derived from Electromagnetic Waves • INSTEAD • The mission uses Microwave Ranging System to accurately measure changes in speed and distance between two identical spacecraft flying in a Polar Orbit about 220 km apart at ~500km above the Earth.
  • 3. The Global Water Cycle: What are the Main Challenges! What are some key issues that cannot be addressed without a next generation gravity mission? •Is the global water cycle accelerating? •Land contributions to global mean sea level rise •Global freshwater availability and sustainability •Emergence of long-term trends •Enhanced space-time resolution for better utilization in hydrological applications
  • 4. Obstacles to Using Satellite Gravity for Applications 1) Product latency • Near-real time information is vital for operational applications 2) Low spatial resolution • Most practical applications require observations at scales of 0.01 – 2500 km 3) Lack of vertical information • Groundwater, soil moisture, surface water, or snow 4) Low temporal resolution • Most hydrological processes operate on hourly to weekly timescales
  • 5. Potential Applications • Water Resources Assessments • Drought monitoring • Ground water depletion • Seasonal snow load • Streamflow forecasting (based on upland water storage) • Transboundary water resources sharing • Weather and Climate Prediction -Via improved forecast model land surface state initialization -Implications for Water Resources, Aviation Safety, Agriculture, and Disaster Preparedness • Solid Earth • Ocean • Ice sheet Dynamics
  • 6. EXAMPLE-APPLICATION GRACE is unique among Earth observing missions in its ability to monitor variations in all water stored on land, down to the deepest aquifers Rodell, Velicogna, and Famiglietti, Nature, 2009
  • 7. Groundwater Monitoring Example: NW India The water table is declining at an average rate of 33 cm/yr During the study period, 2002-08, 109 km3of groundwater was lost from the states of Rajasthan, Punjab, and Haryana;
  • 8. EXAMPLE-MASCON APPROACH Save, H., S. Bettadpur, and B.D. Tapley (2016), High resolution CSR GRACE RL05 mascons, J. Geophys. Res. Solid Earth, 121,
  • 9. GRACE L2 [JPL04] 400 by 600km filtered
  • 10. Trend fitted from GRACE L2 solution [JPL04 with 400km by 600km nonisotropic filtered]
  • 12. Potential Solutions 1) Product latency • - Near-real time information is vital for operational applications • Solutions: More rapid processing of raw data; Data assimilation 2) Low spatial resolution • - Most practical applications require observations at scales of 0.01 – 2500 km • Solutions: Lower altitude, drag-free, laser ranging (sans aliasing) mission; DA 3) Lack of vertical information • - Groundwater, soil moisture, surface water, or snow • Solutions: Combine with other observations (e.g., SMOS, SMAP); DA 4) Low temporal resolution • Most hydrological processes operate on hourly to weekly timescales • Solutions: Mascons; Constellation of satellites; DA
  • 13. Conclusions • GRACE is already proving to be valuable for practical applications including drought monitoring, regional water resources assessments, and estimating rates of groundwater depletion • Obstacles to using satellite gravimetry for practical applications include data latency, coarse spatial and temporal resolutions, and lack of vertical structure • Some of these obstacles may be overcome with a high performance follow- on to GRACE; others will require more efficient and innovative processing of level-1 data or data integration/assimilation • An emerging obstacle is the lack of commitment to a follow-on mission, such that water managers may be afraid to rely on GRACE • GRACE-FO Expected in 2017
  • 14. TAKE HOME MESSAGE • GRACE data currently provide an accurate measurement of the worldʼs water reservoir mass change with a spatial resolution longer than 500 km (half-wavelength) and monthly sampling or finer • GRACE twin-satellite sensor is a relatively new measurement – and still requires substantial efforts to further refine data processing – is anticipated to revolutionize the terrestrial hydrologic research and applications • Water is the lifeblood of Earth, and GRACE time series, for the whole earth, for the continents, for river basins or for watersheds, should emerge as one of several critical indicators of regional health and sustainability
  • 15. Surface Soil Moisture Observations • GRACE mission provides groundwater assessment over the spatial resolution of two degrees. • Therefore, to understand the hydrological impact at medium to higher spatial resolution surface soil moisture data, being variable at land atmosphere boundary is of particular significance. • Dr. Parag Narvekar (student of Prof. Pandey) has developed an radar algorithm for NASA’s aircraft and satellite missions to provide near real-time soil moisture product.
  • 16. Bare-Soil to Full-Vegetation is a Mixing Model Using RVI : Roughness ks Modifies the Parameter Magnitude According to RRI: And the λ Power Term Depends on Vegetation Density as; λ = RVI for RVI >0.3 and λ = 0.3, for RVI <= 0.3. rs VV v VVVV RVIRVIdB   )1()(       mvSksRVIRVIdBVV  01log1)1()(     vf VV s VV RVIksCRVI   )1log(1 0 16 Overview of L-band Radar Model Narvekar et al. IEEE TGRS 2015
  • 17. Aquarius Radar Estimates with NCEP (Coarser Resolution 90 km)  Global 7-days data compared.  Density distribution of more than 55000 points.
  • 18. SMAP Soil Moisture mv Map Example (3km spatial resolution)
  • 19. PALSAR Data (25 meter) High-Res projected in Karnataka watershed
  • 20. Additional Important Variables • The Algorithm developed in Narvekar et al 2015 also provide high resolution vegetation and surface roughness effects • This information is also useful for generating root zone maps. • The moisture level at surface and root zone could provide unique opportunity to accurately model ground water predictions using home made satellites such as NISAR (see upcoming root-zone slide).
  • 21. 21 Roughness from PALSAR, Berambadi Watershed • Water bodies appears blue indicating areas with lower roughness. • Roughness is useful parameter for mapping erosion processes. • Also changing roughness in the field scale could be studied. Narvekar et al. JGRS 2016
  • 22. 22 Vegetation from PALSAR, Berambadi Watershed • Radar based vegetation information is estimated from volumetric properties • This provide essential component based on quantity of vegetation. Narvekar et al. JGRS 2016
  • 23. Average root-zone moisture of the month • The contributing of root-zone soil moisture is computed based on soil water content estimated at the end of the day. • Root-zone is computed using simplified solutions to Richard’s equations.
  • 24. ROOT ZONE SOIL MOISTURE MAY 2016– ESA- SMOS
  • 25. Aapah Innovations, Pvt. Ltd. INNOVATIONS contact@aapahinnovations.com www.aapahinnovations.com Dr. Parag Narvekar is presently with We Strive to Serve for Government and Research Institutions Providing software and mathematical algorithm development applicable for Indian conditions
  • 26. Dr. Sat Kumar Tomer Technical Director PhD: Indian Institute of Science, Bangalore Research Experience: •CESBIO, Toulouse, France Dr. Parag Narvekar Head R&D PhD: Berman University, Germany Research Experience: •JPL, NASA, USA •Massachusetts Institute of Technology (MIT), USA Thiyaku S. GIS Engineer M Tech – Remote sensing and GIS Research Experience: •NRSC, Hyderabad Our Core Team Our Technical Advisory Board Prof. Bimlesh Kumar Associate Professor IIT Guwahati Prof. M. Sekhar Professor IISc, Bangalore Dr. C. T. Dhanya Assistant Professor IIT Delhi Dr. Gulab Singh Assistant Professor IIT Bombay
  • 27. Our Solutions •User-friendly software (of complex Algorithms) for near real-time satellite products •Ability to provide data science solutions for water resources and local weather Our Team •Professionals from premiere institutions of India and abroad •Highly experienced and trained personnel Project Delivery •Reliable delivery mechanism and project management •Automation leading to project duration compression •Long term support Our Products •Competitive pricing •Tailored products •Only company with higher spatial resolution soil moisture