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Murcia’s Agrometeorological Data: Irrigation & Crop Planning

by Dr. Michael Lee – Health Editor

Murcia‘s SIAM‌ Network Empowers ​Farmers with Real-Time Climate Data

The Region of⁤ Murcia is ​leveraging a ⁣network of 55 agrometeorological stations to provide⁤ farmers with crucial data for informed decision-making regarding irrigation, fertilization, pest and ⁢disease control,⁣ and overall crop planning.Managed by the Murcian Institute​ for Agricultural⁣ and Environmental Research and Progress (IMIDA), the⁣ network includes stations operated by the Ministry of Agriculture (15), the City of Mazarrón (1), and the Polytechnic University of Cartagena (UPCT) (1), strategically positioned throughout the region’s irrigated areas.

These stations continuously monitor key atmospheric variables including temperature, relative humidity, ⁤wind speed and direction, solar radiation, and rainfall.⁤ This data‌ is freely ⁤accessible to farmers and othre interested parties through the Agrarian Details ⁤System of ​Murcia (SIAM) website (http://siam.imida.es/apex/f?p=101:1:2197402189847629) ⁢and via the ‘Agroclima Carm’ mobile submission.

According to‍ the⁣ Minister⁣ of ⁢Water,⁤ Agriculture, Livestock and Fisheries, ‌Sara Rubira, the system allows‌ farmers to proactively address‍ potential challenges. “Farmers⁢ can now know the needs of‌ their crops from their mobile devices, even predict and anticipate climate events requiring measures like irrigation or⁢ frost mitigation,” she stated.

The SIAM platform allows users to customize data​ reception based on specific crop needs and desired parameters, and also provides historical data reports⁣ for⁣ comparative‍ analysis. Specific stations, like those in Salmerón (Moratalla) and Broken and the Plain⁤ of ‌the Olivers (Calasparra), are particularly valuable to producers within ⁢the DOP Calasparra​ rice-growing‌ region, providing localized data on variations ⁢in humidity, temperature, and wind.​

Ultimately, the network‍ aims to promote more efficient and sustainable agricultural practices by optimizing resource use based on real-time needs.

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