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Water shortage is one of the issues people are facing globally nowadays especially in arid and semi-arid regions. In these regions the increase in air temperature with slightly changing rates of precipitation cause frequent droughts. This determines the necessity for the usage of irrigation in agriculture that, in turn, makes it the most water consuming sector of economy.The detection of water stress using different approaches is crucial for irrigation scheduling and precise calculation of the volume of water that covers the gap needed for plants’ normal development.It is known that the Photochemical Reflectance Index (PRI) is highly sensitive to the photosynthetic activity of plants. Especially that can be observed for forests and orchards due to the high heterogeneity of canopy structure. In previous studies it was found that PRI can be used as an indicator for monitoring water stress in plants. However, at present, no full answer is given about the limitations of PRI usability and no clear algorithm is formulated for its use in order to detect water stress of plants.In this regard, we concentrate on studying the response of PRI to the water stress of olive trees rain-fed conditions for the case of semi-arid climate (Tunisia). We performed the analysis of data sets for 2021 and 2022, which are, respectively, a dry year and a year of normal water availability. The data sets included meteorological data, PRI measurements made every five minutes, sap flow measurements, soil moisture content values, and dendrometer measurements.On the first stage of our study we processed PRI data sets in order to find an analytic function that best describes daily dynamics of the index. As the result, a new modeling function is constructed to describe an increase in PRI in the middle of the day when minimal PRI values are reached several hours after sunrise and before sunset. Such PRI behavior was mainly observed in sunny days of the dry year.Further, we looked for the correlations of the characteristics of PRI daily dynamics, particularly minimal of PRI, with the values of sap flow that is a main measurable indicator in the class of transpiration and water stress models (see, e.g., https://doi.org/10.1016/j.agwat.2020.106343 ). In this context, the behavior of PRI was different for 2021 and 2022, which, in our opinion, related with weather conditions. For the dry year of 2021 we found a strong correlation between the minimum of PRI and sap flow in morning hours (R2= 0,68) during the summer season. For the normal year 2022 the same results are not obvious.In the perspective of our study it is planned to compare the results for the rain-fed site with the measurements obtained under irrigated conditions. The final goal of the research we want to achieve is to propose a reliable approach for separation of physically meaningful part of PRI signal from the noises created by the canopy structure. This will lead us to the reliable algorithm of PRI usage for the detection of plants’ water stress condition.