دانلود رایگان مقاله انگلیسی تاثیر تغییرات اقلیمی بر فرکانس رانش زمین: مطالعه موردی حوضه ی Esino - اشپرینگر 2018

Abstract

Researchers have long attempted to determine the amount of rainfall needed to trigger slope failures, yet relatively little progress has been reported on the effects of climate change on landslide initiation. Indeed, some relationships between landslides and climate change have been highlighted, but sign and magnitude of this correlation remain uncertain and influenced by the spatial and temporal horizon considered. This work makes use of statistically adjusted high-resolution regional climate model simulations, to study the expected changes of landslides frequency in the eastern Esino river basin (Central Italy). Simulated rainfall was used in comparison with rainfall thresholds for landslide occurrence derived by two observation-based statistical models (1) the cumulative event rainfall–rainfall duration model, and (2) the Bayesian probabilistic model. Results show an overall increase in projected landslide occurrence over the twenty-first century. This is especially confirmed in the high-emission scenario representative concentration pathway 8.5, where according to the first model, the events above rainfall thresholds frequency shift from * 0.025 to * 0.05 in the mountainous sector of the study area. Moreover, Bayesian analysis revealed the possible occurrence of landslide-triggering rainfall with a magnitude never occurred over the historical period. Landslides frequency change signal presents also considerable seasonal patterns, with summer displaying the steepest positive trend coupled to the highest inter-model spread. The methodological chain here proposed aims at representing a flexible tool for future landslide-hazard assessment, applicable over different areas and time horizons (e.g., short-term climate projections or seasonal forecasts).

5 Conclusions

In this study, statistically adjusted simulated rainfall was used to assess future landslide trends in the Esino river basin, Central Italy, through the end of the twenty-first century. We investigated possible changes in landslide-triggering rainfall patterns by means of three RCM simulations driven by two different emission scenarios (RCP 4.5 and RCP 8.5), in coastal, hilly and mountainous sites (Ancona, Jesi, and Apiro, respectively). Then, we performed landslide occurrence analysis using two statistical models run on four rainfall proxies. The first model couples cumulative event rainfall and rainfall duration proxies (EARTh analysis) to determine the projected temporal evolution of rainfall events exceeding three chosen landslide-triggering thresholds (10p, 50p, and 95p). The considered time interval was 1971–2099. The second model calculated the percentage variation in landslide probability between the historical (1971–2000) and a future (2070–2099) time periods. The model used four thresholds (low, medium, high, and NA) providing specific intervals of the daily rainfall and 5-day antecedent rainfall proxies (Bayesian analysis).

Both analyses projected an overall increase in landslides occurrence in the Esino river basin throughout the twenty-first century. This result was particularly marked for the RCP 8.5 scenario. The EARTh analysis showed that all the significant trends are positive, even if the sensitivity to the different RCPs varied significantly according to the RCMs considered. Moreover, the Bayesian analysis displayed positive median and maximum values of LVCs, thus indicating an overall increment of the rainfall events among all the LPCs.

On an annual basis, both statistical models revealed discrepancies among RCPs and RCMs in correspondence of the higher thresholds, thus shedding uncertainty over future landslides trends. However, all analyses indicated a larger increasing number of landslides in the mountain site in respect to the hill and coast sites. Finally, while the Bayesian investigation showed higher data scattering in the coastal site, the EARTh analysis did not present substantial differences in the inter-model spread across the studied sites.