Root zone soil moisture Estimates at the daily and agricultural parcel scales for Crop irrigation management and water use impact – a multi-sensor remote sensing approach

Project Information

REC

Grant agreement ID: 645642

DOI

10.3030/645642

Project closed

EC signature date 19 November 2014

Start date 1 March 2015

End date 28 February 2019

Funded under

• EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions

Total cost

€ 895 500,00

EU contribution

€ 895 500,00

Coordinated by

ISARDSAT SL
Spain

Periodic Reporting for period 2 - REC (Root zone soil moisture Estimates at the daily and agricultural parcel scales for Crop irrigation management and water use impact – a multi-sensor remote sensing approach)

Reporting period: 2017-03-01 to 2019-02-28

Summary of the context and overall objectives of the project

Sustainable water use is a growing concern in Europe. Nowadays, agriculture is an important pressure on water resources especially Mediterranean countries where irrigation can represent up to 80% of the consumptive uses of water. Increasing water use efficiency in agriculture has been thus identified as one of the key themes relating to water scarcity and drought. It now becomes necessary to improve on-farm irrigation management by adjusting irrigation to crop water requirements along the growing season.

Modern irrigation agencies rely on in situ root zone soil moisture measurements to detect the onset of crop water stress and to trigger irrigations. However, in situ point measurements are generally not available over extended areas and may not be
representative at the field scale. If remote sensing provides cost-effective techniques for monitoring broad areas, there is currently no algorithm dedicated to root zone soil moisture monitoring at the parcel scale.

REC proposes a solution to the need of root-zone soil moisture at the crop scale for irrigation management. It is based on an innovative operational algorithm that aims to:
1) to map root zone soil moisture on a daily basis at the field scale and
2) to quantitatively evaluate the different components of the water budget at the field scale from readily available remote sensing data.

The methodology relies on the coupling between a surface model representing the water fluxes at the land surface atmosphere interface (infiltration, evaporation, transpiration) and in the soil (drainage), and remote sensing data composed of land surface temperature, and near-surface soil moisture retrieved from microwave radiometers and radars.

These estimates will be integrated in an irrigation management system that will be used to trigger irrigation. In addition, these estimates will allow making an impact assessment of the consumptive use of water and water footprint.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

The following specific objectives have been fulfilled:

Objective INNOVATIVE EO: To define, develop and implement innovative algorithms to estimate high spatial resolution near surface soil moisture from Earth Observation data. NSSM has been obtained at both high-spatial (field scale) and high-temporal (every 3 days) resolutions by developing synergies between SMOS passive microwave, Sentinel-1 active microwave, and Sentinel-3/MODIS/Landsat optical data.
As a result, we are able to provide high-resolution NSSM every 3 days in all weather conditions.

Objective VALIDATION: To perform validation experiments on a regular basis using in situ, EO and modelling activities for all REC estimates.
In coordination with the respective irrigation agencies of the Segarra-Garrigues (ASG) and of the irrigated perimeter of the Haouz Plain (ORMVAH), intensive field campaigns have been implement during 2015, 2016, 2017 and 2018.
As a result, we have the means to fully validate EO products and water fluxes covering a wide range of soil moisture and irrigation conditions.

Objective NETWORK: To build a network for inter-sectorial knowledge sharing and long-term collaboration in the field of remote sensing applications for water resources management.
REC builds on existing or completed European R&D projects aiming at optimizing irrigation management and the partners have already collaborated in international projects. The framework of this project is strengthening these links and helps reaching institutions and enterprises working in the irrigation sector.
We have organised 3 project Open Days and a Final International Workshop with an increasing number of experienced attendants.
A framework that enables a strong tightly knit community (scientific/operational; research/industry) in multi-disciplinary water resources research (hydrologists, agronomists, water resources managers, etc.) is being put into place.
As a result, synergetic international on-going activities for irrigation and water use impact are more easily encompassed.

Objective OUTREACH: To promote the REC project results, using open workshops and seminars, webinars, scientific peer-review articles, a web-portal, brochures, newsletters and films for the stimulation of results in future operational services.
The following promotion actions have been undertaken:
• Three Open Days and one Final Workshop
• 8 Workshops
• Several Field Trainings, 4 Webinars and presential courses
• 6 PhD Lectures and 3 PhD Lectures scheduled for 2019, 6 PhD on-going
• Presence at more than 50 conferences in more than 10 countries
• 21 Publications in peer-reviewed international scientific journals
• Two films
• Presence in 18 Brokerage Events and 5 Fair
As a result, we have seen an increasing number of assistants to open seminars and webinars and we have reinforced REC’s network.

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

The team had already implemented and validated a disaggregation algorithm (DISPATCH) to provide 1 km resolution NSSM data from SMOS and MODIS data (Merlin et al. 2013).
During the project development, the following aspects have been addressed:
• Improving the temporal resolution of 1 km resolution DISPATCH data by assimilating data into a land surface model (Malbéteau et al. 2017)
• Identifying strengths and weaknesses of existing soil moisture downscaling methods to open new research avenues (Peng et al. 2017)
• Investigate different approaches to model backscatter data for NSSM estimation (Gao et al. 2017)
• Developing an innovative approach to take advantage of the complementarity between thermal-disaggregated SMOS NSSM (no need for calibration) and Sentinel-1 derived NSSM (with a need for calibrating the radiative transfer model) at 100 m resolution (Escorihuela et al. 2017)
As a result, we are able to provide high-resolution NSSM every 3 days in all weather conditions.

During the second reporting period of REC, the following aspects have been addressed:
• Investigating possible synergies between Sentinel-1 data and a NSSM proxy derived from LandSat-7/8 thermal data (Amazirh et al. 2018)
• A better representation of the partitioning between soil evaporation and plant transpiration (AïtHssaine et al. 2018)
• Improving the spatial resolution of MODIS/Terra LST by integrating the high spatial resolution of NSSM derived from Sentinel-1 (Amazirh et al., 2019).
As a result, we are able to provide high-resolution RZSM every 3 days in all weather conditions.

To precisely estimate all the components of the surface water cycle by developing an innovative coupling between a land surface model (LSM) representing the water fluxes at the land surface-atmosphere interface and in the soil, and remotely sensed NSSM and RZSM.
During the second reporting period of REC, the following aspects have been addressed:
• Assimilating LST and Fc data in the FAO-2Kc model and simulates the RZSM as the state variable of the water budget resulting from input (irrigation, precipitation) and output (transpiration, evaporation and drainage) water fluxes (Olivera et al. 2018).
• Improving our understanding of the plant transpiration by using the FAO formalism (Ayyoub et al. 2017).
• Proposing a new soil evaporation model driven by near-surface soil moisture and with calibration capabilities from soil texture or LST information (Merlin et al. 2018).
• Addressing the representation of drainage within the FAO-56 water budget model (Nassah et al. 2018).
As a result, there is a clear improvement of LSM with respect to the state-of-art.

Field Work at Agramunt demonstrative plot

Field Work at R3

Field Work at Foradada demonstrative plot