04 Jan 2022
04 Jan 2022
Status: this preprint is currently under review for the journal NHESS.

Process-based flood damage modelling relying on expert knowledge: a methodological contribution applied to agricultural sector

Pauline Brémond1, Anne-Laurence Agenais1, Frédéric Grelot1, and Claire Richert2 Pauline Brémond et al.
  • 1INRAE, G-EAU, Univ Montpellier, AgroParisTech, BRGM, CIRAD, IRD, INRAE, Institut Agro, Montpellier, France
  • 2ITK, Clapiers, France

Abstract. Flood damage assessment is crucial for evaluating flood management policies. In particular, properly assessing damage to the agricultural assets is important because they may have greater exposure and are complex economic systems. The modelling approaches used to assess flood damage are of several types and can be fed by damage data collected post-flood, from experiments or based on expert knowledge. The process-based models fed by expert knowledge are subject of research and also widely used in an operational way. Although identified as potentially transferable, they are in reality often case-specific and difficult to reuse in time (updatbililty) and space (transferability). In this paper, we argue that process-based models are not doomed to be context specific as far as the modelling process is rigorous. We propose a methodological framework aiming at verifying the conditions necessary to develop these models in a spirit of capitalisation by relying on four axes which are: i/ the explicitation of assumptions, ii/ the validation, iii/ the updatability, iv/ the transferability. The methodological framework is then applied to the model we have developed in France to produce national damage functions for the agricultural sector. We show in this paper that the proposed methodological framework allows an explicit description of the modelling assumptions and data used, which is necessary to consider a reuse in time or a transfer to another geographical area. We also highlight that despite the lack of feedback data on post-flood damages, the proposed methodological framework is a solid basis to consider the validation, transfer, comparison and capitalisation of data collected around process-based models relying on expert knowledge. In conclusion, we identify research tracks to be implemented to pursue this improvement in a spirit of capitalisation and international cooperation.

Pauline Brémond et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on nhess-2021-398', Anonymous Referee #1, 26 Jan 2022
    • AC1: 'Reply on RC1', Pauline Bremond, 28 Mar 2022
  • RC2: 'Comment on nhess-2021-398', Anonymous Referee #2, 03 Feb 2022
    • AC2: 'Reply on RC2', Pauline Bremond, 28 Mar 2022

Pauline Brémond et al.

Pauline Brémond et al.


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Short summary
It is impossible to protect all issues against flood risk. To prioritise protection, economic analyses are conducted. The French Ministry of the Environment wanted to make available damage functions that we have developed for several sectors. On this basis, we propose a methodological framework and apply it to the model we have developed to assess damage to agriculture. This improves the description, validation, transferability and updatability of models based on expert knowledge.