Evolution of the Soil Wetness Index (SWI) in France: Analysis with Google Earth Engine

Authors: Guillaume Attard & Julien Bardonnet

Spring (left) and summer (right) SWI gain/loss between 1970–2021.

In France, about 10 millions of houses are exposed to the shrinkage and swelling of clay soils [1] and between 1989 and 2021, the cost of damages related to this phenomenon represented more than 15 billion euros [2]. This phenomenon mostly occurs after severe draught events, that can be identified by low values of the soil wetness index (SWI).

The SWI represents the state of the soil water reserve (2 meters deep) in relation to the available water at the field capacity (water available for plant feeding). For more details, see the mathematical definition in appendix 1. This index is a key component of the national compensation progam: when damages are caused by the shrinkage and swelling of clay soils, the official recognition of “natural disaster” relies on the SWI [3]. If the return period of the SWI value is higher than 25 years, then municipalities can be recognized and supported by the national natural disasters compensation program.

In the current context of climate change, the following questions arise:

• How did the SWI evolve in France since the beginning of its calculation at a national scale in 1969?
• Is there eventually some locations more impacted than others in terms of soil wetness evolution?

Dataset availability and description

We explore the evolution of the uniform SWI (see appendix 1) in France between 1970 to 2021. Uniform SWI values are provided by Meteo-France on a monthly basis since 1969 with a spatial resolution of 8 km. Each monthly value integrates the moisture status of the current month and of the two previous months. The dataset is available on the website of Meteo-France.

Google Earth Engine Analysis

We first ingested this dataset in Google Earth Engine as an Image Collection. This Earth Engine asset has been made publicly available.

Then, the dataset has been reduced and resampled regarding the four seasons of interest to eventually differentiate spring, summer, autumn, or winter soil wetness evolutions over the period 1970–2021.

The uniform SWI image collection ingested in Earth Engine is composed by 624 images (1 image by month from January 1970 to December 2021). For each year, and for each season, a composite image has been create with the mean SWI values of the season.

Then, a linear fit reduction has been applied to each seasonal collection in order to get the general trend. This process computes the least squares estimate of a linear function of the seasonal uniform SWI variable.

Finally, the resulting national trend image is reduced at the scale of French departments. It allows for estimating the averaged SWI gain/loss over the period of interest.

Results

The result of the analysis is illustrated on the figure below. On this figure, the absolute SWI gain/loss between 1970–2021 is mapped. The quantitative table associated with these results is provided in appendix 2, where the averaged SWI gain/loss by department and by season is given.

These results can be summarized as follow:

• The 5 most impacted departments in terms of SWI loss are Gers, Cantal, Haute-Garonne, Lozère and Loire.
• The spring is the season where the most severe and generalized SWI loss is observed. The most severe spring SWI loss is observed in Ardèche (absolute loss of 0.29 over the period 1970–2021).
• In 78 departments (over 96), the SWI trend between 1970–2021 is negative, and in 33 departments the trend is particularly severe. In these departments, the absolute SWI loss is higher than 0.1 (all seasons averaged).

Complementary notes — contact

This article and the code has been elaborated with the support of Ageoce. Ageoce builds digital solutions and services focusing on geodata intelligence and geosciences.

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Appendix 1 : mathematical definition of the SWI

The calculation of the SWI reads as follow:

SWI = (θfc ​− θwi) / (​θ − θwi)​​

with:

• θ: water content in the soil,
• θwi: water content in the soil at the wilting point. The wilting point represents the point below what water cannot be extracted by plant roots,
• θfc water content in the soil at the field capacity. The field capacity represents the point after which water cannot be stored by soil any more. After that point, gravitational forces become too high and water starts to infiltrate the lower levels.

Additionally, for a month m, the uniformized SWI is given as follow:

USWI = (SWIm ​+ SWIm−1​ + SWIm−2) / 3​​

Appendix 2: Table of SWI evolution by department

Averaged SWI gain/loss (1970–2021) by department and by season.

Bibliography

[1] SDES (2021) Nouveau zonage d’exposition au retrait-gonflement des argiles : plus de 10,4 millions de maisons individuelles potentiellement très exposées. Article web du ministère en charge de l’écologie en France.

[2] France Assureurs (2022) Le risque sécheresse et son impact sur les habitations. Web article.

[3] Ministère de l’intérieur (2019) Circulaire INTE1911312C relative à la procédure de reconnaissance de l’état de catastrophe naturelle — Révision des critères permettant de caractériser l’intensité des épisodes de sécheresse-réhydratation des sols à l’origine de mouvements de terrains différentiels.