Normalization of the crop water stress index to assess the within-field spatial variability of water stress sensitivity

  • PDF / 2,657,972 Bytes
  • 20 Pages / 439.37 x 666.142 pts Page_size
  • 27 Downloads / 225 Views

DOWNLOAD

REPORT


Normalization of the crop water stress index to assess the within‑field spatial variability of water stress sensitivity Victoria Gonzalez‑Dugo1   · Pablo J. Zarco‑Tejada1,2 · Diego S. Intrigliolo3 · Juan‑Miguel Ramírez‑Cuesta3 Accepted: 20 October 2020 © Springer Science+Business Media, LLC, part of Springer Nature 2020

Abstract This paper presents a novel methodology for identifying homogeneous areas within highfrequency drip-irrigated orchards and for defining the most sensitive and resistant areas of the field to water stress. The methodology proposed here is based on the assessment of water status at the tree level during mild water stress using remote sensing derived indicators which provide valuable information about the spatial distribution of the response to water stress within an orchard. The areas more resistant to water stress will maintain a good water status, while those prone to water stress will develop initial symptoms of water deficit. The study was performed over three different peach orchards that were evaluated from 2 to 3 years. Water status was monitored using high-resolution thermal imagery acquired before and after the onset of water stress. The Thermal Sensitivity Index (TSI), derived from the difference of the CWSI and the cumulated reference evapotranspiration between the two dates, demonstrated to be well related to the increase of stem water potential. The spatial distribution of TSI enables the identification of sensitive areas within a peach orchard, a first step for establishing precision drip irrigation programs. Keywords  CWSI · High-resolution remote sensing · Thermal · Management zone · Sensitive areas · Peach orchard

* Victoria Gonzalez‑Dugo [email protected] 1

Instituto de Agricultura Sostenible (IAS), Consejo Superior de Investigaciones Científicas (CSIC), Alameda del Obispo s/n, 14004 Cordoba, Spain

2

Department of Infrastructure Engineering, Faculty of Veterinary and Agricultural Sciences (FVAS), School of Agriculture and Food, Melbourne School of Engineering (MSE), University of Melbourne, Melbourne, VIC 3010, Australia

3

Dpto. Riego, Centro de Edafología y Biología Aplicada del Segura (CEBAS-CSIC), P.O. Box 164, 30100 Murcia, Spain





13

Vol.:(0123456789)



Precision Agriculture

Introduction Agricultural fields are naturally heterogeneous and this variability is often related to soil properties, mainly variations in slope, texture, depth and mineral composition (Camp and Sadler 1998). These factors are static or relatively stable from year to year, and have been used in the past to delineate management zones, or at least, to identify homogeneous areas within fields (Schepers et al. 2004; Bazzi et al. 2019). The identification of these management units is particularly relevant for the optimized use of external inputs and for irrigation purposes. Considering the current situation of water availability and future climate change scenarios, it is essential to identify strategies to save water while maintaining crop productivity by the efficient use of