Agricultural Water Management (Dec 2024)
Assessment of irrigation water use for dry beans in center pivots using ERA5 Land climate variables and Sentinel 2 NDVI time series in the Brazilian Cerrado
Abstract
The Brazilian Cerrado is a vital agricultural region, yet its expansion often overlooks the high climate risks posed by the prolonged dry season, particularly from June to September when water demand surges, causing low-flow conditions. Recent studies highlight significant water deficits between May and October, making irrigation water use (IWU) crucial for policymakers and managers. This study estimates IWU for dry beans grown under center pivots during the dry season in the state of Mato Grosso, Brazil, a leading agricultural producer with 309,372 km² of agricultural land. Mato Grosso relies heavily on irrigation from April to October for bean cultivation. We used NDVI time series from Sentinel-2A data from 2019 to 2023 to classify dry beans areas based on t-SNE and k-means cluster classification. The individual NDVI time series for the dry season for each pivot was divided based on the peak NDVI values to analyze phenological parameters- such as duration, start and end of the season- to assess water needs from April to September. ERA-5 Land climate data provided daily reference evapotranspiration (ETo) and precipitation (P), which were used to compute the crop’s water requirement. Irrigation depth (D) was estimated using a water balance equation incorporating crop coefficients (Kc) and daily irrigation needs adjusted for efficiency. The analysis shows that dry-season irrigation in the Cerrado primarily replenishes soil moisture, often leading to inefficient water use. From 2019–2023, IWU increased significantly, with the model showing a strong correlation (R² = 0.92) to reported accumulated irrigation depth for center pivot during the dry season. However, the model underestimated needs from May to July and overestimated in August, with a bias of −21.88 mm. The North subregion, benefiting from favorable conditions, accounted for 43 % of the state's IWU. The study provides valuable insights into IWU trends, supporting strategic decisions and resource allocation, while offering a cost-effective method for real-time IWU estimation.
