Defining irrigation thresholds in remote sensing-based decision support systems: a review of crop models mechanistic descriptions of crop water stress
Authors: Tolomio Massimo , Casa Raffaele 
Published: March 2020

&lt;p&gt;Irrigation management decision support systems based on remote sensing and hydrological models need to find a balance between simplicity and accuracy in the definition of crop water stress thresholds when irrigation should be triggered. Among the most widely used crop models, which synthesize current mechanistic knowledge of crop water stress processes, there is a wide range of complexity that is worth exploring in order to improve the formalisms of current hydrological models.&lt;/p&gt;&lt;p&gt;In the present work, some of the most widely used crop models (chosen among those freely available and well documented) were examined in their description of crop water stress processes and irrigation thresholds definition. They are: APSIM, AQUACROP, CROPSYST, CROPWAT, DAISY, DSSAT, EPIC, STICS and WOFOST. Model manuals and scientific papers were reviewed to identify differences and similarities in the water stress functions related to crop growth.&lt;/p&gt;&lt;p&gt;A strict categorization of the model features is inappropriate, since the functions utilized are always at least slightly different and the models may focus on different features of the agroecosystem. Nevertheless, major similarities and differences among the models were found:&lt;/p&gt;&lt;ol&gt;&lt;li&gt;&lt;em&gt;The function of biomass growth.&lt;/em&gt; AQUACROP and CROPWAT (both developed by FAO) are water-driven models (growth is directly related to transpiration). DAISY, DSSAT, EPIC, STICS and WOFOST are radiation-driven models (growth is related to radiation). APSIM and CROPSYST calculate both water- and radiation-driven biomass and keep the most limiting of these.&lt;/li&gt;
&lt;li&gt;&lt;em&gt;The main variable used to calculate water stress indices.&lt;/em&gt; AQUACROP, CROPWAT and WOFOST use stress coefficients that depend directly on the depletion status of plant available water (difference between field capacity and wilting point). CROPSYST, DAISY, DSSAT and EPIC calculate water stress on the ratio between actual transpiration (limited by roots and soil characteristics) and potential transpiration (weather-dependent). APSIM uses both approaches, depending on the specific crop and growth process targeted. STICS expresses the transpiration rate as a function of the available water content (in m&lt;sup&gt;3&lt;/sup&gt;/m&lt;sup&gt;3&lt;/sup&gt; above wilting point), and from this it calculates water stress indices.&lt;/li&gt;
&lt;li&gt;&lt;em&gt;The influence of water stress indices on vegetative growth.&lt;/em&gt; Water stress in CROPWAT, DAISY and WOFOST affects biomass growth, whereas in APSIM, AQUACROP, CROPSYST, DSSAT, EPIC and STICS multiple indices affect biomass growth and leaf expansion in different ways. The rationale behind the last approach is that as soil water uptake becomes more difficult, water stress slows down cells division and expansion (reducing the leaf expansion rate) before photosynthesis is reduced by stomatal closure.&lt;/li&gt;
&lt;/ol&gt;&lt;p&gt;The models were then calibrated for the maize and tomato crops using field and remote sensing data on crop yield, soil moisture, evapotranspiration (ET) and leaf area index (LAI), for two locations, respectively in Northern and Southern Italy (Calcinato and Capitanata). Simulations were then carried out and compared in terms of the optimal irrigation amounts calculated by the different models and predicted yields.&lt;/p&gt;