The OPTIMISTE team (Optimization of the Piloting and Technologies of Irrigation, Minimization of the InputS, Transfers in the Environment) of INRAE Montpellier (France) has joined MAGO to promote and facilitate the collaborative, operational use of its Optirrig model for the generation, analysis and optimization of irrigation scenarios.

 

Specifications, functionalities and final needs for the Optirrig model in MAGO (WP2, led by Claire Wittling from INRAE Montpellier).  


Optirrig takes its inputs from contextual data (climate forcings, soil properties, crop description) including basic financial elements (expected selling price, fixed and variable costs linked to water and energy consumption) and from site management data (sowing date and agricultural operations) with a focus on irrigation equipment or method (sprinkler irrigation, surface or subsurface drip irrigation, irrigation by submersion). 

This is the piece of information needed to run the model. However, additional information always proves useful to constrain model behaviour and predictions (e.g. probes in the soil profile) especially in poorly-gauged contexts (e.g. surface moisture, Leaf Area Index or water stress estimations from satellite data) but also from direct observations, typically by taking great advantage of routine observations made by the farmers (e.g. number of leaves, phenological stages, grain or fruit humidity or aspect – to be converted into quantitative values of some of the model's variables).

Then Optirrig delivers a large series of daily variables (e.g. soil water content, crop growth and biomass production, stress level) related to the dynamics of the physical processes at play, and a few seasonal variables to be regarded as performance indicators over the season (total irrigation, crop yield, financial income, evaluations of irrigation efficiency, productivity and relevance – any user-defined evaluation may be included).

Optirrig offers various functionalities, starting with pre-treatments to help the user handle the required input data, as a format conversion is often necessary to switch from the original data type and structure to the formats required by Optirrig. Then several actions are possible, dispatched into three categories, (i) prospective studies, e.g. irrigation scenarios under climate change and lower resource availability hypothesis, (ii) ex-post analyses, e.g. re-evaluation and improvement of past, well documented irrigation strategies, testing and comparing the effects of alternative decision rules and different ways of thinking the irrigation issue, and (iii) the use of the model as a real-time decision-support system, in which decisions are taken from the current state of the soil-plant system but also from its modelled evolution in the short term, relying on weather forecasts.

All this applies to several possible model versions, depending on the hydro-agronomic calculations of interest for a given project. Here, MAGO deals with water, nitrogen and salinity management, but evaluations of irrigation efficiency and productivity also are primary scopes (not forgetting that methodologies for the evaluation of the energetic and financial efficiency of irrigation are currently under discussion – thanks to recent works here at Montpellier and to the visit of INRGREF colleagues of Tunisia this week). Emphasis will be placed on conservation agriculture practices with respect to the previous elements but conventional practices will not be disregarded. Crop species to be included are cereals, vegetables (tomatoes and potatoes) and fruit trees (citrus trees).

Finally, the challenge we* are most often facing with Optirrig is to use less than a given irrigation quota to obtain more than a target crop yield, reaching the maximum possible financial income. Solutions are sought in examination and improvement of the irrigation decision rules, changing the interplay (maths people say the implicit function) between total irrigation, crop yield and financial income. Agronomists say that doing so we are travelling along the production curve. Hopefully for the best and for wider horizons…

All the best from Montpellier, and waiting to meet the other participants in Barcelona soon.
Bruno

* My young colleague Madiop Lo will be with us for a 1-year contract on MAGO, to handle Optirrig developments.