Consultant - Computational Hydrologist
International Water Management Institute, United States

The International Water Management Institute (IWMI) is a leading global research organization dedicated to sustainable water and land resources management. Our mission is to improve the productivity, profitability, and resilience of water and land resources in support of food security, livelihoods, and environmental sustainability. Our teams are lead by researchers and scientists, and our projects are often materialized through prototypes that are engineered with our in-house expertise, upon which production-ready platforms must be designed so that they can be implemented for real world application in the field, through the engagement of technological partners for the implementation of such projects.

The Limpopo River Basin (LRB) is a region of immense environmental, socio-economic significance, extending across Botswana, South Africa, Zimbabwe, and Mozambique. It encompasses a diverse range of ecosystems, including forests, wetlands, and savannahs, supporting a rich variety of flora and fauna. The river and its tributaries provide essential water resources for agriculture, livestock, and fisheries, supporting millions of livelihoods. Despite these invaluable resources, the LRB faces challenges such as hydro-climatic extremes, land degradation, poor water quality, urbanization, and population growth, which threaten biodiversity and weaken local communities' resilience to climate change. The basin also faces increasing competition for access to limited water resources and arable land, with women and youth disproportionately affected.

To address these pressing challenges, IWMI’s new project aims to create a comprehensive Digital Twin of the Limpopo River Basin. The LRB Digital Twin will serve as a virtual representation of the basin's socio-ecological system, bridging the physical and digital worlds. This advanced approach combines environmental data, modelling, and analysis tools with digital technology to enable sustainable and inclusive water management.

This is an internationally/globally hired consultancy; therefore, individuals with relevant abilities from diverse locations around the world are encouraged to apply.The work arrangement for this consultancy is remote.

The primary objective of this role is to contribute to the creation of a comprehensive Digital Twin of the Limpopo River Basin (LRB) by utilizing the Soil and Water Assessment Tool (SWAT) model to forecast water availability and support sustainable water management practices.

Responsibilities,

• Data Preprocessing: Gather, preprocess, and integrate input data from remote sensing and suitable stations for utilization in the SWAT model.
• Model Calibration: Calibrate the SWAT model using local weather station and stream flow data to ensure accuracy and reliability.
• Operationalization: Operationalize the SWAT model to generate consistent and reliable forecasts.
• Cloud Deployment: Deploy the SWAT model in an AWS environment for enhanced accessibility and scalability.
• Post-Processing and Integration: Incorporate post-processing of SWAT output for potential integration into the User Interface (UI) model.

• Preprocessing Scripts for input amp; output data for the SWAT Model.
• Automation Script for the Seasonal Forecast.
• Best Calibrated SWAT Model with new observed data.
• Provide 2024 water availability forecast.
• Deploy the Operational SWAT Model on AWS Cloud.
• Improvement amp; Validation.
• Documentation.
• Final Report / Peer review paper.

Requirements

• Masters or PhD in hydrological modeling, environmental modeling. computational modeling or in a related discipline.
• At least 05 years of hands on experience in hydrological modeling, computational modeling.
• Proven experience in calibrating hydrological models (especially SWAT model) using local weather and stream flow data to ensure accuracy and reliability.

• Expertise in Hydrology: Profound understanding and practical experience in hydrological modeling and analysis, specifically with the SWAT model.
• Remote Sensing and Data Integration: Capability to preprocess and integrate diverse datasets, particularly from remote sensing sources, for input into hydrological models.
• Cloud Computing: Proficiency in deploying models in cloud environments, specifically AWS, for enhanced accessibility and scalability.
• Problem-Solving Skills: Ability to troubleshoot model-related issues and propose innovative solutions.
• Team Collaboration: Strong communication skills to collaborate effectively with multidisciplinary teams of researchers

Job Rewards and Benefits