Satellite Data Rendered Irrigation Using Penman-Monteith and SEBAL (Github)

A scalable and easy-to-apply framework to empower the canal water managers
A water-provider-centric irrigation advisory system designed to manage surface water resources and allocate water efficiently to areas in need, thereby promoting sustainable irrigation practices in the context of a changing climate. The system utilizes satellite remote sensing based SEBAL (Surface Energy Balance Algorithm for Land) and Penman-Monteith evapotranspiration models to estimate crop water use. By integrating the responses from the previous irrigation cycle, current precipitation, forecasted precipitation, evapotranspiration-based water needs and percolation, the framework calculates the net water requirements for command areas within irrigation canal networks. Operating on a weekly basis, the system generates advisories that enable the irrigation water provider to make informed, science-based decisions about water allocation. These advisories quantify the net water requirement, giving water providers the flexibility to dispatch water to areas of higher need based on their on-ground judgment. Additionally, the proposed framework when running locally can simulate future cropping patterns by assuming potential policy changes or net reduction in water supply in the main canal due to climate change or increased transboundary withdrawal. The advisory system is developed and implemented on the Teesta River Irrigation System located in Northern Bangladesh, demonstrating its effectiveness. However, its application is not limited to Bangladesh, as it is scalable to other regions with similar water management challenges.