Developing Tools
A theme of SatWIN-ALERT is to further develop and use frameworks like TAMSAT-ALERT*, a monitoring and decision support tool that combines information from various data streams to support the management of agricultural and meteorological drought. For subsistence farmers and the insurance partners that support them, deciding what crops to grow, when to plant, or when to apply fertilizer is of the utmost importance. The answers to these questions are not straightforward and are affected by weather and other environmental factors; but with improved drought information about expected conditions from TAMSAT-ALERT, users can make more-informed decisions.
In the past, people have tried to assess drought just using rainfall statistics. However, weather-related hazards are often complicated, and other factors such as the soil type can influence the impact of low rainfall. TAMSAT-ALERT is an open-source framework, developed by the University of Reading, that can generate soil moisture, crop yield, and other metrics using current and historical weather, land surface properties, and optionally weather forecasts. Given the current state of these metrics and historical weather data (with each year of historical data representing one possible weather future), TAMSAT-ALERT can then be used to provide early warning of weather-related hazard to a range of decision makers to mitigate their exposure to risk.
Currently, TAMSAT-ALERT supports a variety of metrics, including soil moisture and rainfall. And the tool is highly flexible, so it’s possible for risk assessments to be generated using other metrics based on meteorological data. We’re also currently working on integrating vegetation indices (EVI and NDVI, for example). TAMSAT-ALERT can also be updated throughout the season and as regularly as every single day.
Beyond basis risk and agricultural forecasting support, TAMSAT-ALERT is also being developed as a tool to support humanitarian aid. Integrating vegetation indices into TAMSAT-ALERT will allow the tool to better forecast the possible implications of a season on livestock or crop production. These predictions could be used to move aid into areas of food security risk before conditions worsen.
TAMSAT-ALERT can support decision-making by quantifying the risk of adverse weather-related conditions and aims to complement tools and strategies already in place. Users are encouraged to run TAMSAT-ALERT in parallel for different metrics, including rainfall statistics, soil moisture, modelled crop yield or potential insurance pay-outs. This allows the user to compare the differing outputs which can give a better understanding of the complete picture. TAMSAT-ALERT is also a lightweight tool that does not require large amounts of processing power, allowing it to be run on a standard computer. Additionally, the entire project is rooted in an open science model, with all publications in open access journals and all the code freely available on GitHub in Python.
*TAMSAT-AgricuLtural dEcision suppoRT