Geospatial Tools for Irrigation Water Management

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Description

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• Develop stakeholder-centric, demand-driven geospatial applications based on the WaPOR land and water productivity datasets to map irrigated water use hotspots, conduct water productivity assessments, and assess irrigation scheme performance.
• Develop custom applications using machine learning, multi-criteria, or other relevant methods to enhance water management across large spatial scales.
• Contribute to the scientific advancement and methodological developments of IWMI’s digital water innovation toolsets.
• Develop technical guidance and training materials for the custom geospatial applications.
• Prepare high-quality research reports and journal articles.
• Collaborate with a multidisciplinary team to implement innovative, remote sensing-based approaches for improved water management in the regions where IWMI operates.
• Provide technical support to researchers for complex geospatial analysis in various research and management projects at IWMI headquarters.
• Assist in training and capacity-building activities related to the tools developed within the Water Productivity/Water Accounting group.
• Perform other related assignments as required.

• PhD in Remote sensing, geospatial analytics, hydro-informatics, water resources, spatial hydrology, machine learning, or a related discipline.
• Experience in applying remote sensing and spatial analysis in the field of agriculture and water management.
• Prior experience in using supervised and unsupervised algorithms, including machine learning methods (e.g., ecological niche modeling) on large spatial datasets in Python, R, or any other programming language.
• Demonstrated experience in using Python to handle large spatial and non-spatial datasets.
• Experience in using Google Earth Engine or other cloud-based earth observation data processing environments for geospatial tool developments.
• Experience designing and implementing approaches for data-scarce environments.

• Experience in wastewater estimation, reuse, and loss estimation modeling.
• Experience in the Middle East and North Africa (MENA) countries.
• Prior experience in modeling emissions from agriculture and wastewater sectors.

• Strong understanding of irrigation and hydrological issues in Egypt and/or MENA region, with proven experience in applying hydrological modeling and earth observation data for solving real-world problems (such as irrigation scheduling).
• Proficiency in Python, R, or other programming languages with experience in numeric and geospatial Python packages like Numpy, Scikit-learn, GDAL, or similar packages.
• Strong analytical, numerical, and data visualization skills, with the ability to process large temporal and spatial datasets in Python.
• Ability to use advanced spatial analysis and geospatial tools for multi-scale assessments of agricultural water use.
• Positive attitude, solid work ethic, and a demonstrated capacity and interest in learning new technologies and taking on additional responsibilities over time.
• Self-motivated, enthusiastic, and able to work independently and as part of a multidisciplinary team.
• Fluent in both spoken and written English and Arabic.
• Good interpersonal skills and the ability to establish and maintain effective working relationships with people in a multicultural and multidisciplinary environment, with sensitivity and respect for diversity.

• Demonstrated abilities in applying machine learning approaches, segmentation models, computer vision, or deep learning methods on remote sensing data to develop use cases in water management and agriculture will be an added advantage.
• Working proficiency in French will be an added advantage.

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