GIS-based estimation of the winter storm damage probability in forests: a case study from Baden-Wuerttemberg (Southwest Germany)

Abstract

Data on storm damage attributed to the two high-impact winter storms 'Wiebke' (28 February 1990) and 'Lothar' (26 December 1999) were used for GIS-based estimation and mapping (in a 50 × 50 m resolution grid) of the winter storm damage probability (P(DAM)) for the forests of the German federal state of Baden-Wuerttemberg (Southwest Germany). The P(DAM)-calculation was based on weights of evidence (WofE) methodology. A combination of information on forest type, geology, soil type, soil moisture regime, and topographic exposure, as well as maximum gust wind speed field was used to compute P(DAM) across the entire study area. Given the condition that maximum gust wind speed during the two storm events exceeded 35 m s(-1), the highest P(DAM) values computed were primarily where coniferous forest grows in severely exposed areas on temporarily moist soils on bunter sandstone formations. Such areas are found mainly in the mountainous ranges of the northern Black Forest, the eastern Forest of Odes, in the Virngrund area, and in the southwestern Alpine Foothills.

The Role of Highly-Resolved Gust Speed in Simulations of Storm Damage in Forests at the Landscape Scale: A Case Study from Southwest Germany

“…A predictor variable nearly equally important for RF-model accuracy as GS stat,Dec was FOR (PI = 18.3) which is in good agreement with findings reported for the study area in previous investigations [17,19]. Also important for the RF-modeling performance was MOIST (PI = 11.9).…”

“…Results from ROC-curve evaluation of the OOB-samples of PCmod,j (PCOOB,j) show that the cross-validated AUC-value for PCOOB,1, which represents the damage probability class "no damage", is higher (AUC = 0.86) than in previous studies [12,17,19,49] (Figure 9). The AUC-values that are …”

“…In moist soils, root development is often hampered [42,43] and root anchorage is lower as compared with drier soils [44,45]. In this study, all other predictor variables that have been shown to be of importance for storm damage occurrence like soil type [17,19] or soil acidification [46] are of minor importance (PI < 10) for classification of storm damage probability.…”

“…The strong variations of GS stat,Dec on a small spatial scale, especially in the Black Forest, are due to the complex orography in the study area. The spatial resolution of all predictor variables is 50 mˆ50 m. Further descriptions of the predictor variables are given in [19] and [27].…”

“…In our opinion, this is mainly because the spatial resolution of the available gust speed fields (50 mˆ50 m) is far more detailed than the gust speed data available in previous studies [12,[17][18][19]. The high-resolution gust speed models incorporate roughness and topographic features, which had to be neglected or considered separately in earlier investigations.…”