CRSA - Postdoctoral position on high- resolution root zone soil moisture estimation by assimila[...]

Mohammed VI Polytechnic University; Occitanie; Sur place; EUR 30 000 - 45 000; Plein temps

Résumé du poste

Mohammed VI Polytechnic University offers a postdoctoral position focusing on high-resolution root zone soil moisture estimation through the assimilation of microwave-derived data. This role is crucial for advancing research in food and water security in Africa and involves collaboration, data analysis, and publication of findings.

Qualifications

• Ph.D. in relevant field is required.
• Experience with satellite imagery required.
• Strong background in land surface modeling and remote sensing data analysis.

Responsabilités

• Assess land surface models for soil moisture estimation.
• Publish findings and present research.
• Supervise Master's and PhD students.

Connaissances

Land surface modeling

Remote sensing data analysis

Image processing

Geospatial analysis

Data assimilation techniques

Communication skills

Formation

Ph.D. in Earth Sciences

Ph.D. in Remote Sensing

Ph.D. in Physics

Ph.D. in Applied Mathematics

Outils

MATLAB

Python

Description du poste

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CRSA - Postdoctoral position on high-resolution root zone soil moisture estimation by assimilation of microwave-derived surface soil moisture

Mohammed VI Polytechnic University is an institution oriented towards applied research and innovation with a focus on Africa.

Located at the heart of the future Green City of Benguerir, Mohammed VI Polytechnic University (UM6P), a higher education institution with international standards, is established to contribute to the development of Morocco and the African continent. Its vision is honed around research and innovation at the service of education and development. This unique nascent university, with its state-of-the-art campus and infrastructure, has woven a sound academic and research network, and its recruitment process is seeking high quality academics and professionals in order to boost its quality-oriented research environment in the metropolitan area of Marrakech.

About CRSA:

CRSA is a transversal structure across several UM6P Programs. Research within the center is organized around several major areas that aim to ensure the challenging Food and Water security goal in Africa, with a special focus on developing methods/tools that use multi-source remotely sensed data. The research aims to improve our understanding of the integrated functioning of continental surfaces and their interaction with climate and humans, with emphasis on sustainable management of natural resources (soil, land, water, agriculture) in the context of Climate Change. One of the center’s goals is to provide a set of services and operational products to users (local, national and international) that aid in the decision support of water and food systems.

Job Description:

Root zone soil moisture is an essential climate variable (ECV) that is crucial for characterizing the Earth’s climate. It is a key variable in hydrology, meteorology, and agronomy, regulating the exchange of water, energy, and carbon between the land surface and the atmosphere. For agriculture, soil moisture in the root zone controls vegetation health, development, transpiration, biomass production, and nutrient absorption. Its estimation is essential for monitoring vegetation’s health and water status, and making decisions on irrigation scheduling and optimal application rates to ensure crop hydration, promote healthy root development, facilitate nutrient uptake, and maximize yields. It also enables efficient irrigation by applying only the needed amounts at the right time, avoiding nutrient leaching, soil degradation, and water wastage.

In contrast to in situ measurements, remote sensing data provide frequent, large-scale measurements that can be used to estimate surface variables of interest. Radar data can now be used to obtain high-resolution maps of surface soil moisture, suitable for plot-scale applications. Surface soil moisture can be used to estimate root zone soil moisture via land surface models and surface models that link surface and root zone processes.

Combining radar-derived surface soil moisture maps with land surface models using data assimilation can produce daily root zone soil moisture estimates while improving accuracy and reducing errors. The position’s objective is to develop an approach combining an appropriate land surface model with radar-derived surface soil moisture using sequential data assimilation for high-resolution mapping.

Key Responsibilities:

• Assess different land surface models for root zone soil moisture estimation
• Combine a land surface model with a sequential data assimilation technique
• Participate in field data collection and analysis
• Publish research findings in peer-reviewed journals and present at conferences and workshops
• Contribute to supervision of Master’s and PhD students

Qualifications:

• Ph.D. in Earth Sciences, Remote Sensing, Physics, Applied Mathematics, or related field
• Strong background in land surface modeling, remote sensing data analysis, image processing, and geospatial analysis
• Experience with satellite imagery (e.g., Sentinel-1, Landsat, Sentinel-2) and other remote sensing data sources
• Proficiency in MATLAB and Python for data analysis and algorithm development
• Knowledge of data assimilation techniques is an advantage
• Excellent communication skills and ability to work effectively in a collaborative research environment