AGRIDE-c, a conceptual model for the estimation of flood damage to crops: development and implementation

Abstract

Abstract. This paper presents AGRIDE-c, a conceptual model for the assessment of flood damage to crops, in favour of more comprehensive flood damage assessments. Available knowledge on damage mechanisms triggered by inundation phenomena is systematised in a usable and consistent tool, with the main strength represented by the integration of physical damage assessment into the evaluation of its economic consequences on the income of the farmers. This allows AGRIDE-c to be used to guide the flood damage assessment process in different geographical and economic contexts, as demonstrated by the example provided in this study for the Po Plain (north of Italy). The development and implementation of the model highlighted that a thorough understanding and modelling of mechanisms causing damage to crops is a powerful tool to support more effective damage mitigation strategies, both at public and at private (i.e. farmers) levels.

Cost–benefit analysis of flood mitigation measures: a case study employing high-performance hydraulic and damage modelling

“…However, future researches should be focussed on a better evaluation of the effect of the distribution of damage across the year (depending on the time of occurrence of the flood and the corresponding vegetative stage of the plants) on the estimation of the yearly expected damage and, on turn, on risk. Given the importance of the time of the year, risk estimates should not be based only on annual probabilities, but also on seasonal probabilities; this would imply changing the present conceptualization of flood return periods (Molinari et al 2019). Nonetheless, in this paper, only damage to crops has been considered, while future assessment should be extended to other damageable components of a farm (i.e.…”

“…These items are difficult to be evaluated due to the complexity of phenomena and (inter)linkages leading to damage and the lack of standardized modelling tools (Merz et al 2010;Meyer et al 2013). To cover this gap, the collection and the share of ex-post damage data, in a unique and consistent manner, should be encouraged, leading to an improvement of damage models calibration and validation (Molinari et al 2019). The creation of a common database (such as the European Union spatial data infrastructure, proposed by the EU INSPIRE Directive) containing the aforementioned elements, will ease the identification of required data and results.…”

“…Monetary damage to agriculture was estimated by means of the AGRIDE-c model for the Po plain (Molinari et al 2019). The model furnishes, for different kinds of crops (namely, grain maize, wheat, barley and grassland), the damage suffered by an individual farmer.…”

“…This choice derives from the analysis of the hydrometric levels in Lodi, from the second half of 1998 until June of 2018, showing that November is the month when high water stages in the river have been registered more frequently (2002 flood event included). Finally, as regards the permanence of water on the field, considering the crop types present in November and their life stages, it can be assumed that the duration of the flood does not influence the potential damage in this period of the year (see also Molinari et al 2019). Indeed, grain maize and soy are absent and the damage is associated with the bare soil only.…”

“…month), flood intensities (i.e. water depth and flood duration) and damage alleviation strategies ("c" = continuation; "r" = reseeding; "a" = abandoning)(Molinari et al 2019)…”