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IMPROVING IRRIGATION WATER
PRODUCTIVITY AND USE EFFICIENCY
USING NEW TECHNOLOGIES
RAGAB RAGAB1, RAG@CEH.AC.UK
CENTRE FOR ECOLOGY AND HYDROLOGY, CEH, UK
VICE PRESIDENT H., INTERNATIONAL COMMISSION ON IRRIGATION AND DRAINAGE, ICID
CONTRIBUTERS
EVANS1, J.G., BATTILANI2, A., AND SOLIMANDO2, D.
1. CENTRE FOR ECOLOGY AND HYDROLOGY, CEH, WALLINGFORD, OX10 8BB, UK
2. CONSORZIO DI BONIFICA DI SECONDO GRADO PER IL CANALE EMILIANO ROMAGNOLO – CER
“Integrating bio‐treated wastewater reuse and valorisation with
enhanced water use efficiency to support the Green Economy in
EU and India”.
Water4Crops
EU Consortium (21 Partners from 8 Countries):
5 Universities, 8 Research Institutes, 6 SMEs, 2 Consultant Comp.
TM SOLUTION LTD
W4Cs objectives
 Valorizing agri-food-industry wastewater by recovering or producing
valuable chemicals
 Increasing water availability by treating and reusing wastewater
 Saving water in agriculture by enhancing water use efficiency through
• improved agronomics
• plant breeding
• innovative irrigation techniques
 Enhancing stakeholders participation by co-creation process as well as through
Mirror Cases and INNOVA Platforms tools
Similar Structure
of EU and India W4Cs projects
WP5-I: Enabling green growth using water
treatment and reuse innovations (TERI)
WP6-I: Dissemination and
technology exchange (EIRC)
WP2-I: Municipal wastewater
biotreatment and reuse (NEERI)
Sub-Humid
Climate
Mediterranea
n
Climate
Efficient water use in irrigated agriculture
http://www.water4crops.org/
http://www.water4crops.org/
W4Cs crop rotation 2013-2015
http://www.water4crops.org/
Saving water by irrigating half of the root zone, the PRD method
Partial Root Drying , PRD
Maize 2014
Conclusion
When compared with RDI, the PRD irrigation
strategy in 2013, the potato used 15% less
irrigation, in the year 2014, maize received
17% less irrigation, in 2015, PRD received 28%
less water. The yield obtained under PRD was
equal or insignificantly less than RDI.
Towards accurate estimation of
crop water requirement without
the crop coefficient: new
approach using modern
technologies
http://www.water4crops.org/
http://www.water4crops.org/
Scintillometer (transmitter left-receiver right)
Experimental site and instruments locations.
What is scintillation?
Refractive index changes because of air
density differences – heat and moisture.
a typical scintillometer path
Transmitter
Receiver, measures
‘heat shimmer’
Atmospheric Turbulence Changes Air Density
infrared light and radio-waves
6 km Path length
Infra-red Light
Transmitter
0.00
1.00
2.00
3.00
4.00
5.00
6.00
7.00
8.00
9.00
10.00
12/12/2013 22/03/2014 30/06/2014 08/10/2014 16/01/2015 26/04/2015 04/08/2015 12/11/2015
EVAPOTRANSPIRATION,MMDAY-1
Reference Evapotranspiration, ETo , Actual Evapotranspiration by Eddy Covariance, ETa
Eddy and by Scintillometer, ETa Scint
Eta Eddy ETa Scint ET0
Eta Eddy/Eto % Eta Scint/Eto %
44.46 34.38
Comparison between actual evapotranspiration measured by Eddy Covariance and by the Scintillometer versus the
reference evapotranspiration calculated by Penman-Monteith equation.
Receiver
Transmitter
The Scintillometer footprint at the CER experimental farm (Mezzolara). Contribution to Eta increases from green to yellow to
red areas.
Actual evapotranspiration, ETa, measured by Eddy Covariance and the relative contribution of the crops within the
footprint to the total ETa for the 2014 season.
0.00
2.00
4.00
6.00
8.00
10.00
12.00
12/12/2013 22/03/2014 30/06/2014 08/10/2014 16/01/2015 26/04/2015 04/08/2015 12/11/2015
EVAPOTRANSPIRATION,MMDAY-1
Reference Evapotranspiration, ETo, Crop Evapotranspiration, ETc , Actual
Evapotranspiration by Eddy Covariance, ETa Eddy and by Scintillometer, ETa Scint
Eta Eddy ETa Scint ET0 ETC
Eta Eddy/Eto % Eta Scint/Eto % Eta Eddy/Etc % Eta Scint/Etc %
44.46 34.38 45.14 34.91
Comparison between actual evapotranspiration measured by Eddy Covariance and Scintillometer, reference
evapotranspiration estimated from Penman-Monteith equation and crop evapotranspiration calculated from ETo and the
weighted mean of the crop coefficient Kc.
Conclusion
The ETc and ETo showed higher values than those of
ETa obtained by Eddy Covariance and Scintillometer.
On average the actual evapotranspiration of Eddy
Covariance and Scintillometers for the cropping
seasons 2014 and 2015 represented 45% and 35% of
the ETo and ETc, respectively. These are quite
significant differences.
• Calculating the reference evapotranspiration, ETo, or
the crop evapotranspiration, ETc, from meteorological
data, produces potential evapotranspiration that would
represent the atmospheric demand for water rather than
the crop demand for water.
• Accurate crop water requirement should be based on
crop and soil demand not on atmospheric demand for
water.
• Another benefit is, these modern technologies of
measuring the actual evapotranspiration do not need the
crop coefficient Kc, obtaining Kc is a major problem to
many irrigation practitioners.
• Other methods for measuring actual evaporation can
also be useful (e.g. weighing lysimeters, etc.).
• Short term monitoring of actual evaporation could be
used to derive a relationship with the commonly used
Eto or Etp that are easily obtainable from the standard
weather stations.
ESTIMATING CROP WATER REQUIREMENT
USING THE COSMIC-RAY SOIL MOISTURE
OBSERVATION SYSTEM (COSMOS)
http://cosmos.ceh.ac.uk/
Soil cores Cosmic rays
Neutron Probe
Profile Probe
ERT, Electric Resistivity Tomography
Profile Probe
College Field Top Transect
Sheepdrove Farm
21-04-2006
64 electrode ERT transect at
0.5m spacing crossing 3
distinct vegetation types –
winter cereal (foreground),
‘beetle-belt’ (centre), spring
cereal (distance)
College Top
21 April 2006
23 Aug 2006
Winter Barley Compacted Grass Beetle Belt Compacted Grass Spring Wheat
(Short) (Long)
0.2 0.25 0.3 0.35 0.4 0.45
10 (cm)
20 (cm)
30 (cm)
40 (cm)
50 (cm)
60 (cm)
80 (cm)
100 (cm)
120 (cm)
140 (cm)
160 (cm)
180 (cm)
200 (cm)
230 (cm)
NPDepth
Soil Moisture Fraction
Aug
April
COSMOS soil moisture sensors
• Large scale: 300-700 m radius of
sensitivity
• Non-invasive, completely passive
• Uses background fast neutrons
generated by Cosmic rays, which
are scattered (slowed) by H
atoms.
http://cosmos.ceh.ac.uk/
http://www.water4crops.org/
The volumetric soil moisture content, θ (m3 m-3) was calculated using
Desilets et al. (2010) analytically derived equation: The neutron counting
rate (counts hr-1), N, the corrected neutron counting rate over dry soil
under the same reference conditions, No, Three fitting parameter factors
that control the shape the soil moisture-neutron count rate relation, ao,
a1, and a2, being 0.0808, 0.372 and 0.115, respectively. No is determined
by field volumetric sampling and laboratory analysis within the Cosmos
footprint. 𝜽𝜽 𝑵𝑵 =
𝒂𝒂𝒂𝒂
𝑵𝑵
𝑵𝑵𝑵𝑵
−𝒂𝒂𝟏𝟏
− 𝒂𝒂𝒂𝒂
The effective depth of Cosmos measurement is defined as the thickness of
soil from which 86% of counted neutrons arise (Zreda et al., 2008).
The effective depth, z (cm), was calculated according to the hypothetical
equation of Franz et al. (2012) as:
𝒛𝒛 =
𝟓𝟓. 𝟖𝟖
𝝆𝝆 𝝉𝝉 + 𝜽𝜽 + 𝟎𝟎. 𝟎𝟎𝟎𝟎𝟎𝟎𝟎𝟎
The recorded data was transmitted in real time to the USA Cosmos web site:
http://Cosmos.hwr.arizona.edu/Probes/StationDat/098/index.php
Cosmos soil water content, effective depth and SMD for 2014-15 seasons. Cosmos water content was not adjusted for
biomass water content at this stage.
Cosmic ray probe calibration: Profile Probe access tubes distribution over the Cosmos probe dominated area in 2015.
http://www.water4crops.org/
Cosmos soil water content after correction for biomass water content
Cosmos soil water content compared with cores soil moisture (0-50cm average) under all crops sprinkler and drip
irrigated in 2014-2015.
Cosmos soil water content compared with Profile probe soil moisture for plot 12 (100 m from Cosmos probe) at
different depths up to 100 cm.
Cosmos soil water content compared with Profile probe soil moisture averaged for all plots for 0-40 cm and 0-60cm
depths.
Cosmos soil water content compared with soil moisture sensors averaged for all plots and for 0-60 cm depth. 2014 cropping
season.
Cosmos soil water content compared with averaged soil moisture sensors, averaged soil cores and SALTMED
simulated soil moisture for maize, 2014 averaged for 0 -60 cm depth.
Method description Measurement details RMSE
Method
Measureme
nt
Year
Selected
plots
Number
of values
Depth, cm
No of
depths
averaged
Profile
probe
In situ-
2015
1 to 9 324 0-40 4 0.0426
Non-
continuous
1 to 9 405 0-60 5 0.0452
10, 11, 12 108 0-40 4 0.0363
10, 11, 12 135 0-60 5 0.0369
10 36 0-40 4 0.0384
10 45 0-60 5 0.0394
11 36 0-40 4 0.0356
11 45 0-60 5 0.0370
12 36 0-40 4 0.0374
12 45 0-60 5 0.0376
1 to 12 432 0-40 4 0.0330
1 to 12 540 0-60 5 0.0339
Sensors
In situ- 2014 4 plots 388 0-50 2 0.0423
continuous 2014-15 8 plots 792 0-50 2 0.0667
Soil cores Laboratory
2014-15 45 spots 930 0-50 5 0.0393
2015 40 spots 800 0-50 5 0.0290
Overall average 0.0394
Water content adjusted for biomass for 60 cm effective depth as verified and tested by field measurements.
Conclusion
• The Cosmos technology is one step in the right direction as it provides continuous,
integrated, area based values and solves the problem of spatial variability often found in
point measurements in relation to the soil spatial heterogeneity.
• This method could also be used to determine the soil moisture deficit, hence determine when
and how much to irrigate.
• The results showed that Cosmos soil moisture falls within the top 0-60 cm soil layer
verified by the soil moisture measured by sensors, soil cores and profile probes supported
by the SALTMED model. This indicates that there is a possibility that the Cosmos probe’s
effective depth could be within the top 0-60 cm of the irrigated lands.
• Knowing that almost 80% of the crop root system is accommodated within
the top 50-60 cm, the Cosmos measurement could be useful for
monitoring the soil water status and subsequently soil moisture deficit in
the root zone.
• The Cosmos technology could be made operational for irrigation managers
to determine when and how much to irrigate to avoid harmful water stress.
• In summary, these results support the use of Cosmos as an integrated area
based, non-destructive and hazard free method of measuring soil moisture
and for crop water requirement determination.
Thanks for your attention
http://www.water4crops.org/

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Ragab R 1 - UEI Day 1 - Kochi Jan18

  • 1. IMPROVING IRRIGATION WATER PRODUCTIVITY AND USE EFFICIENCY USING NEW TECHNOLOGIES RAGAB RAGAB1, RAG@CEH.AC.UK CENTRE FOR ECOLOGY AND HYDROLOGY, CEH, UK VICE PRESIDENT H., INTERNATIONAL COMMISSION ON IRRIGATION AND DRAINAGE, ICID CONTRIBUTERS EVANS1, J.G., BATTILANI2, A., AND SOLIMANDO2, D. 1. CENTRE FOR ECOLOGY AND HYDROLOGY, CEH, WALLINGFORD, OX10 8BB, UK 2. CONSORZIO DI BONIFICA DI SECONDO GRADO PER IL CANALE EMILIANO ROMAGNOLO – CER
  • 2. “Integrating bio‐treated wastewater reuse and valorisation with enhanced water use efficiency to support the Green Economy in EU and India”. Water4Crops
  • 3. EU Consortium (21 Partners from 8 Countries): 5 Universities, 8 Research Institutes, 6 SMEs, 2 Consultant Comp. TM SOLUTION LTD
  • 4. W4Cs objectives  Valorizing agri-food-industry wastewater by recovering or producing valuable chemicals  Increasing water availability by treating and reusing wastewater  Saving water in agriculture by enhancing water use efficiency through • improved agronomics • plant breeding • innovative irrigation techniques  Enhancing stakeholders participation by co-creation process as well as through Mirror Cases and INNOVA Platforms tools
  • 5. Similar Structure of EU and India W4Cs projects WP5-I: Enabling green growth using water treatment and reuse innovations (TERI) WP6-I: Dissemination and technology exchange (EIRC) WP2-I: Municipal wastewater biotreatment and reuse (NEERI)
  • 6. Sub-Humid Climate Mediterranea n Climate Efficient water use in irrigated agriculture http://www.water4crops.org/
  • 8. W4Cs crop rotation 2013-2015 http://www.water4crops.org/
  • 9. Saving water by irrigating half of the root zone, the PRD method
  • 12.
  • 13. Conclusion When compared with RDI, the PRD irrigation strategy in 2013, the potato used 15% less irrigation, in the year 2014, maize received 17% less irrigation, in 2015, PRD received 28% less water. The yield obtained under PRD was equal or insignificantly less than RDI.
  • 14. Towards accurate estimation of crop water requirement without the crop coefficient: new approach using modern technologies
  • 18. Experimental site and instruments locations.
  • 19. What is scintillation? Refractive index changes because of air density differences – heat and moisture. a typical scintillometer path Transmitter Receiver, measures ‘heat shimmer’ Atmospheric Turbulence Changes Air Density infrared light and radio-waves 6 km Path length Infra-red Light Transmitter
  • 20. 0.00 1.00 2.00 3.00 4.00 5.00 6.00 7.00 8.00 9.00 10.00 12/12/2013 22/03/2014 30/06/2014 08/10/2014 16/01/2015 26/04/2015 04/08/2015 12/11/2015 EVAPOTRANSPIRATION,MMDAY-1 Reference Evapotranspiration, ETo , Actual Evapotranspiration by Eddy Covariance, ETa Eddy and by Scintillometer, ETa Scint Eta Eddy ETa Scint ET0 Eta Eddy/Eto % Eta Scint/Eto % 44.46 34.38 Comparison between actual evapotranspiration measured by Eddy Covariance and by the Scintillometer versus the reference evapotranspiration calculated by Penman-Monteith equation.
  • 21. Receiver Transmitter The Scintillometer footprint at the CER experimental farm (Mezzolara). Contribution to Eta increases from green to yellow to red areas.
  • 22. Actual evapotranspiration, ETa, measured by Eddy Covariance and the relative contribution of the crops within the footprint to the total ETa for the 2014 season.
  • 23. 0.00 2.00 4.00 6.00 8.00 10.00 12.00 12/12/2013 22/03/2014 30/06/2014 08/10/2014 16/01/2015 26/04/2015 04/08/2015 12/11/2015 EVAPOTRANSPIRATION,MMDAY-1 Reference Evapotranspiration, ETo, Crop Evapotranspiration, ETc , Actual Evapotranspiration by Eddy Covariance, ETa Eddy and by Scintillometer, ETa Scint Eta Eddy ETa Scint ET0 ETC Eta Eddy/Eto % Eta Scint/Eto % Eta Eddy/Etc % Eta Scint/Etc % 44.46 34.38 45.14 34.91 Comparison between actual evapotranspiration measured by Eddy Covariance and Scintillometer, reference evapotranspiration estimated from Penman-Monteith equation and crop evapotranspiration calculated from ETo and the weighted mean of the crop coefficient Kc.
  • 24. Conclusion The ETc and ETo showed higher values than those of ETa obtained by Eddy Covariance and Scintillometer. On average the actual evapotranspiration of Eddy Covariance and Scintillometers for the cropping seasons 2014 and 2015 represented 45% and 35% of the ETo and ETc, respectively. These are quite significant differences.
  • 25. • Calculating the reference evapotranspiration, ETo, or the crop evapotranspiration, ETc, from meteorological data, produces potential evapotranspiration that would represent the atmospheric demand for water rather than the crop demand for water. • Accurate crop water requirement should be based on crop and soil demand not on atmospheric demand for water.
  • 26. • Another benefit is, these modern technologies of measuring the actual evapotranspiration do not need the crop coefficient Kc, obtaining Kc is a major problem to many irrigation practitioners. • Other methods for measuring actual evaporation can also be useful (e.g. weighing lysimeters, etc.). • Short term monitoring of actual evaporation could be used to derive a relationship with the commonly used Eto or Etp that are easily obtainable from the standard weather stations.
  • 27. ESTIMATING CROP WATER REQUIREMENT USING THE COSMIC-RAY SOIL MOISTURE OBSERVATION SYSTEM (COSMOS) http://cosmos.ceh.ac.uk/
  • 28. Soil cores Cosmic rays Neutron Probe Profile Probe ERT, Electric Resistivity Tomography Profile Probe
  • 29. College Field Top Transect Sheepdrove Farm 21-04-2006 64 electrode ERT transect at 0.5m spacing crossing 3 distinct vegetation types – winter cereal (foreground), ‘beetle-belt’ (centre), spring cereal (distance)
  • 30. College Top 21 April 2006 23 Aug 2006 Winter Barley Compacted Grass Beetle Belt Compacted Grass Spring Wheat (Short) (Long) 0.2 0.25 0.3 0.35 0.4 0.45 10 (cm) 20 (cm) 30 (cm) 40 (cm) 50 (cm) 60 (cm) 80 (cm) 100 (cm) 120 (cm) 140 (cm) 160 (cm) 180 (cm) 200 (cm) 230 (cm) NPDepth Soil Moisture Fraction Aug April
  • 31. COSMOS soil moisture sensors • Large scale: 300-700 m radius of sensitivity • Non-invasive, completely passive • Uses background fast neutrons generated by Cosmic rays, which are scattered (slowed) by H atoms.
  • 33.
  • 35. The volumetric soil moisture content, θ (m3 m-3) was calculated using Desilets et al. (2010) analytically derived equation: The neutron counting rate (counts hr-1), N, the corrected neutron counting rate over dry soil under the same reference conditions, No, Three fitting parameter factors that control the shape the soil moisture-neutron count rate relation, ao, a1, and a2, being 0.0808, 0.372 and 0.115, respectively. No is determined by field volumetric sampling and laboratory analysis within the Cosmos footprint. 𝜽𝜽 𝑵𝑵 = 𝒂𝒂𝒂𝒂 𝑵𝑵 𝑵𝑵𝑵𝑵 −𝒂𝒂𝟏𝟏 − 𝒂𝒂𝒂𝒂
  • 36. The effective depth of Cosmos measurement is defined as the thickness of soil from which 86% of counted neutrons arise (Zreda et al., 2008). The effective depth, z (cm), was calculated according to the hypothetical equation of Franz et al. (2012) as: 𝒛𝒛 = 𝟓𝟓. 𝟖𝟖 𝝆𝝆 𝝉𝝉 + 𝜽𝜽 + 𝟎𝟎. 𝟎𝟎𝟎𝟎𝟎𝟎𝟎𝟎
  • 37. The recorded data was transmitted in real time to the USA Cosmos web site: http://Cosmos.hwr.arizona.edu/Probes/StationDat/098/index.php
  • 38. Cosmos soil water content, effective depth and SMD for 2014-15 seasons. Cosmos water content was not adjusted for biomass water content at this stage.
  • 39. Cosmic ray probe calibration: Profile Probe access tubes distribution over the Cosmos probe dominated area in 2015. http://www.water4crops.org/
  • 40.
  • 41. Cosmos soil water content after correction for biomass water content
  • 42. Cosmos soil water content compared with cores soil moisture (0-50cm average) under all crops sprinkler and drip irrigated in 2014-2015.
  • 43. Cosmos soil water content compared with Profile probe soil moisture for plot 12 (100 m from Cosmos probe) at different depths up to 100 cm.
  • 44. Cosmos soil water content compared with Profile probe soil moisture averaged for all plots for 0-40 cm and 0-60cm depths.
  • 45. Cosmos soil water content compared with soil moisture sensors averaged for all plots and for 0-60 cm depth. 2014 cropping season.
  • 46. Cosmos soil water content compared with averaged soil moisture sensors, averaged soil cores and SALTMED simulated soil moisture for maize, 2014 averaged for 0 -60 cm depth.
  • 47. Method description Measurement details RMSE Method Measureme nt Year Selected plots Number of values Depth, cm No of depths averaged Profile probe In situ- 2015 1 to 9 324 0-40 4 0.0426 Non- continuous 1 to 9 405 0-60 5 0.0452 10, 11, 12 108 0-40 4 0.0363 10, 11, 12 135 0-60 5 0.0369 10 36 0-40 4 0.0384 10 45 0-60 5 0.0394 11 36 0-40 4 0.0356 11 45 0-60 5 0.0370 12 36 0-40 4 0.0374 12 45 0-60 5 0.0376 1 to 12 432 0-40 4 0.0330 1 to 12 540 0-60 5 0.0339 Sensors In situ- 2014 4 plots 388 0-50 2 0.0423 continuous 2014-15 8 plots 792 0-50 2 0.0667 Soil cores Laboratory 2014-15 45 spots 930 0-50 5 0.0393 2015 40 spots 800 0-50 5 0.0290 Overall average 0.0394
  • 48. Water content adjusted for biomass for 60 cm effective depth as verified and tested by field measurements.
  • 49. Conclusion • The Cosmos technology is one step in the right direction as it provides continuous, integrated, area based values and solves the problem of spatial variability often found in point measurements in relation to the soil spatial heterogeneity. • This method could also be used to determine the soil moisture deficit, hence determine when and how much to irrigate. • The results showed that Cosmos soil moisture falls within the top 0-60 cm soil layer verified by the soil moisture measured by sensors, soil cores and profile probes supported by the SALTMED model. This indicates that there is a possibility that the Cosmos probe’s effective depth could be within the top 0-60 cm of the irrigated lands.
  • 50. • Knowing that almost 80% of the crop root system is accommodated within the top 50-60 cm, the Cosmos measurement could be useful for monitoring the soil water status and subsequently soil moisture deficit in the root zone. • The Cosmos technology could be made operational for irrigation managers to determine when and how much to irrigate to avoid harmful water stress. • In summary, these results support the use of Cosmos as an integrated area based, non-destructive and hazard free method of measuring soil moisture and for crop water requirement determination.
  • 51. Thanks for your attention http://www.water4crops.org/