The Role of Citrus Groves in Rainfall-Triggered Landslide Hazards in Uwajima, Japan

Abstract

Landslides often cause deaths and severe economic losses. In general, forests play an important role in reducing landslide probability because of the stabilizing effect of the tree roots. Although fruit groves consist of trees, which are similar to forests, practical land management, such as the frequent trampling of fields by laborers and compression of the terrain, may cause such land to become prone to landslides compared with forests. Fruit groves are widely distributed in hilly regions, but few studies have examined their role in landslide initiation. This study aims at filling this gap evaluating the predisposing and triggering conditions for rainfall-triggering landslides in part of Uwajima City, Japan. A large number of landslides occurred due to a heavy rainfall event in July 2018, where citrus groves occupied about 50% of the study area. In this study, we combined geodata with a regression model to assess the landslide hazard of fruit groves in hilly regions. We developed maps for five conditioning factors: slope gradient, slope aspect, normalized difference vegetation index (NDVI), land use, and geology. Based on these five maps and a landslide inventory map, we found that the landslide area density in citrus groves was larger than in forests for the categories of slope gradient, slope aspect, NDVI, and geology. Ten logistic regression models along with different rainfall indices (i.e., 1-h, 3-h, 12-h, 24-h maximum rainfall and total rainfall) and different land use (forests or citrus groves) in addition to the other four conditioning factors were produced. The result revealed that “citrus grove” was a significant factor with a positive coefficient for all models, whereas “forest” was a negative coefficient. These results suggest that citrus groves have a higher probability of landslide initiation than forests in this study area. Similar studies targeting different sites with various types of fruit groves and several rainfall events are crucial to generalize the analysis of landslide hazard in fruit groves.

Post-Landslide Liquefaction Analysis: A Case Study in the Kupang Regency Area, Indonesia

“…Shabbir et al [40] investigated the impact of environmental changes on landslides, revealing seasonal patterns in fatal landslides and the influence of environmental factors on their occurrence (the study examined the role of citrus groves in exacerbating rainfall-induced landslide hazards, highlighting vegetation's impact on landslide events) [41].…”

Land Cover Trajectories and Their Impacts on Rainfall-Triggered Landslide Occurrence in a Cultivated Mountainous Region of Western Japan

“…Therefore, fruit trees in orchards may have only a limited slope stabilising effect due to their small size and low planting density. Lusiana and Shinohara [19] analysed the spatial distribution and causal factors of landslide occurrences during the July 2018 storm event in a hilly area of western Japan (ca. 110 km southwest of our study area); they showed that the landslide density became higher in citrus orchards than in surrounding forests.…”

“…Numerous studies have examined how anthropogenic land cover changes have affected landslide occurrence. These studies demonstrated that, particularly in steep mountainous terrains, the occurrences of shallow landslides due to rainfall events have been markedly accelerated by deforestation, such as harvesting in plantation forests [5][6][7][8][9][10][11], shifting (slash-and-burn) cultivation [3,12], and forest conversion to pasture [13][14][15][16] or farmland [17][18][19][20]. Studies focusing on the role of tree roots in slope stabilisation have revealed that the effectiveness of root systems for soil layer reinforcement is highly spatially heterogeneous and does not remain constant over time.…”

“…Although landslide occurrences are expected to be closely related to the predisposition and rainfall amount at each location [3], few studies have considered both effects in characterising landslide distribution in a single storm event. Recent advances in meteorological radar observation networks allowed us to analyse the spatial relationship between rainfall events and landslides, even in remote mountainous regions without dense ground observatories, e.g., [19]. We used radar/rain gauge-analysed precipitation (RRAP), which is generated by correcting radar-estimated rainfall using rainfall records at ground observatories; it is therefore more reliable and accurate than the original radar estimates, e.g., [30][31][32][33], although the spatial and temporal resolution is not very high (1-h precipitation data with spatial resolution ≥ 1 km).…”