[Defended thesis] Ivana Aleksovska: Improve short- and medium-term predictions of agronomic models by better taking into account the uncertainty of weather forecasts

Ivana Aleksovska is one of the #DigitAg co-funded PhDs

She defended her thesis on 8th December 2020.

Watch the video of Ivana’s thesis defence

Improve short- and medium-term predictions of agronomic models by better taking into account the uncertainty of weather forecasts

  • Start Date: November 2017
  • University: Université Toulouse III Paul Sabatier
  • PhD School: SDU2E (Toulouse)
  • Field(s): Mathematics
  • Doctoral Thesis Advisor: Laure Raynaud, Météo France, Robert Faivre, Miat, Inrae
  • Co-supervisors : François Brun, Acta
  • Funding: #DigitAg – Acta-les instituts techniques
  • #DigitAg: Cofunded PhD – Challenge 1

Abstract: Meteorological conditions: the crop cycle, irrigation management, crop protection and fertilization. This sector is strongly demanding decision support systems to better assess these constraints. A range of services is developing to meet this need such as Météus proposed by Isagri or Taméo built by Météo-France and Arvalis – Institut du végétal.

Atmospheric flow is a chaotic phenomenon and the development of quality weather forecasts is a scientific challenge, as there are many uncertainties: estimation of the initial conditions over the globe, representation of the physical processes in numerical weather prediction systems. To cope with this problem, the meteorological centers, including Météo-France, have implemented ensemble prediction systems that provide an estimate of the uncertainty of the predicted meteorological conditions.

The objective of this thesis is to define methods to exploit these ensemble meteorological forecasts for agronomic applications. To this end, the partner organizations (ACTA, Arvalis, IFV, Inrae and Météo-France) of this project have identified contrasted case studies for which they have agronomic models. The doctoral student will work successively on the definition of the junction between the different ensemble of forecasts covering different timeframes, on the evaluation of the resulting uncertainties, and the development of representations of the results to make them easily usable by agricultural users.

Contact:  ivana.aleksovska [AT] inrae.fr​ – Tél : 07 83 71 41 68

Papers & scientific communications

I Aleksovska (2018) Effet de la météo sur un modèle de ravageurs de la vigne et analyse des incertitudes de prévision. Rencontres du Réseau Mexico (Inria, Irstea, Inra, Labex COTE), Bordeaux (FRA), 12-13 novembre 2018

I Aleksovska, Laure Raynaud, Robert Faivre, François Brun and Marc Raynal (2020) Design and evaluation of calibrated and seamless ensemble weather forecasts for crop protection applications, AMS

Conference papers

Présentation des travaux de thèse Ivana Aleksovska “Effet de la météo sur un modèle de ravageurs de la vigne et analyse des incertitudes de prévision” @ACTA_asso @meteofrance @Inra_Tlse @Arvalisofficiel @vignevinfrance @DigitAgLab aux rencontres Mexico à @Inria Bordeaux 12-13nov pic.twitter.com/50DiXRKl5F— François Brun – ACTA (@fbrunACTA) 15 novembre 2018

I. Aleksovska, F. Brun, L. Raynaud, R. Faivre, M. Raynal, O. Deudon (2018), Prendre en compte de l’incertitude des previsions meteorologiques dans les OAD utilisees pour gérer les maladies et ravageurs des cultures,  Végéphyl – 12e Conférence Internationale sur les Maladies des Plantes, 10, 11 et 12 Décembre 2018, Tours

I Aleksovska, L. Raynaud, R.Faivre, F. Brun, M. Raynal, O. Deudon, F. Souverain (2019), Accounting for the uncertainty of weather forecasts in decision support systems used for crop management,  12th EFITA International Conference, 27-29 June, 2019, Rhodes island, Greece