Fausto Marincioni

Catastrophic flood and forest cover change in the Huong river basin, central Viet Nam: A gap between common perceptions and facts

Recent catastrophic floods in Viet Nam have been increasingly linked to land use and forest cover change in the uplands. Despite the doubts that many scientists have expressed on such nexus, this common view prompted both positive forest protection/reforestation programs and often-unwarranted blame on upland communities for their forest management practices. This study discusses the disparity between public perceptions and scientific evidences relating the causes of catastrophic floods. The former was drawn on the results of a questionnaire and focus groups discussions with key informants of different mountainous communities, whereas the latter was based on GIS and remote sensing analysis of land cover change, including a statistical analysis of hydro-meteorological data of the Huong river basin in Viet Nam. Results indicate that there is a gap between the common beliefs and the actual relationship between the forest cover change and catastrophic floods. Undeniably, the studied areas showed significant changes in land cover over the period 1989-2008, yet, 71% of the variance of catastrophic flood level in the downstream areas appeared related to variance in rainfall. Evidences from this study showed that the overall increasing trends of catastrophic flooding in the Huong river basin was mainly due to climate variability and to the development of main roads and dyke infrastructures in the lowlands. Forest management policies and programs, shaped on the common assumption that forest degradation in the upland is the main cause of catastrophic flood in the downstream areas, should be reassessed to avoid unnecessary strain on upland people.

Application of a process-based shallow landslide hazard model over a broad area in Central Italy

Process-based models are widely used for rainfall-induced shallow landslide forecasting. Previous studies have successfully applied the U.S. Geological Survey’s Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability (TRIGRS) model (Baum et al. 2002) to compute infiltration-driven changes in the hillslopes’ factor of safety on small scales (i.e., tens of square kilometers). Soil data input for such models are difficult to obtain across larger regions. This work describes a novel methodology for the application of TRIGRS over broad areas with relatively uniform hydrogeological properties. The study area is a 550-km2 region in Central Italy covered by post-orogenic Quaternary sediments. Due to the lack of field data, we assigned mechanical and hydrological property values through a statistical analysis based on literature review of soils matching the local lithologies. We calibrated the model using rainfall data from 25 historical rainfall events that triggered landslides. We compared the variation of pressure head and factor of safety with the landslide occurrence to identify the best fitting input conditions. Using calibrated inputs and a soil depth model, we ran TRIGRS for the study area. Receiver operating characteristic (ROC) analysis, comparing the model’s output with a shallow landslide inventory, shows that TRIGRS effectively simulated the instability conditions in the post-orogenic complex during historical rainfall scenarios. The implication of this work is that rainfall-induced landslides over large regions may be predicted by a deterministic model, even where data on geotechnical and hydraulic properties as well as temporal changes in topography or subsurface conditions are not available.

Rainfall Threshold and Landslides in the Post-orogenic Complex of the Esino River Basin, Central Italy

Hydrogeological hazards are widespread and recurrent in Italy, requiring constant monitoring, prevention and mitigation activities. This paper contributes to the landslide forecast debate, analysing the relationship between rainfall and landslides in the eastward section of the Esino river basin located in the Marche region (central Italy). This area of similar hydrogeological properties is characterized by post-orogenic quaternary sediments prone to rainfall-induced shallow landslides. The preliminary investigation revealed the occurrence of 232 landslides, most of all shallow and small-sized, from 1953 to 2011. Rainfall data from neighbouring rain gauges were compared with the historical series of landslides both on annual and monthly basis. Moreover, the intensity-duration empirical model is applied to describe a new empirical triggering threshold valid for the study area. Threshold rainfall conditions are described by the equation: \( I = 1.61 \times D^{ - 0.21} \) where I = mean rainfall intensity (mm/h) and D = rainfall duration (h). Such equation represents the conditions that in the past decades activated 90 % of all landslides occurred within the area. This rainfall threshold could be used to forecast landslides occurrence in the post-orogenic complex of the Esino river basin.

A baseline assessment of emergency planning and preparedness in Italian universities.

Besides offering teaching and research services, schools and universities also must provide for the safety and security of their employees, students, and visitors. This paper describes emergency preparedness in a sample of Italian universities. In particular it examines risk perception within a specific professional category (university safety and security officers) in a specific cultural context (Italy). In addition, it discusses the transposition and implementation in a European Union (EU) member state of EU Council Directive 89/391/EEC of 12 June 1989, on the introduction of measures to encourage improvements in the safety and health of workers. The findings highlight heterogeneous and fragmented emergency management models within the Italian university system, underlining the need for a stricter framework of standardised safety protocols and emergency management guidelines. The study also points out that enhancing emergency planning and preparedness in Italian universities entails increasing safety leadership, employee engagement and individual responsibility for safety and security; essentially, it necessitates improving the culture of risk prevention.

Sustainability assessment of traditional fisheries in Cau Hai lagoon (South China Sea).

Overfishing and progressive environmental degradation of the Vietnamese Cau Hai coastal lagoon appear to be threatening the ecological integrity and water quality of the largest estuarine complex of Southeast Asia. This study assessed the relationships between the density of traditional fisheries and organic matter sedimentary contents in Cau Hai lagoon. Data revealed that the density of stake traps (the most common fishing gear used in this lagoon), decreasing hydrodynamic energy in shallow water, causes the accumulation of a large fraction of organic matter refractory to degradation. The relationship between biopolymeric carbon (a proxy of availability of organic matter) and stake traps density fits a S-shape curve. The logistic equation calculated a stake traps density of 90 m of net per hectare, as the threshold over which maximum accumulation of organic matter occurs in Cau Hai. With such level of stake trap density, and assuming a theoretical stationary status of the lagoon, the time necessary for the system to reach hypoxic conditions has been calculated to be circa three weeks. We recommend that this density threshold should not be exceeded in the Cau Hai lagoon and that further analyses of organic loads in the sediment should be conducted to monitor the trophic conditions of this highly eutrophicated lagoon.

A rapid method for flood susceptibility mapping in two districts of Phatthalung Province (Thailand): present and projected conditions for 2050

This study discusses the application of a multiple logistic regression analysis in Khao Chai Son and Mueang Phatthalung districts (Phatthalung Province in southern Thailand), which were the two worst flooded districts in the 2011 inundation. The aim is to test an easy, rapid, and cost-effective method to asses flood susceptibility in a data-poor country. Climatic, topographic, and geological data have been overlaid with those of the flood events occurred in the study area from 2007 to 2011. Results showed a positive spatial correlation between the northeast monsoon precipitation and flooding. Moreover, using the rainfall projection of the U.S. National Center for Atmospheric Research the proposed model forecasts a sharp increase of flood susceptibility in the study area by the year 2050. Given the versatility of such model, local governments could easily use it to define the areas in their territories most exposed to flood hazard and timely implement risk reduction policies and practices.

Linking Vegetation Patterns and Landslide Occurrence: An Empirical Method

We propose an approach for identifying the possible links between vegetation patterns and landscape portions interested by landslides. The chosen study area is the Marche Region (central Italy), and within this, the Esino River Valley was selected as a smaller focus area for multitemporal analysis. The land cover data for this area was available for the period 1990–2006. With these data we performed a change detection, and a Morphological Spatial Pattern Analysis (MSPA) of land covers. The findings of these two analysis, were then integrated with: (a) the Italian national landslides database, also called AVI (considering only on the 646 landslides documented over the Marche region up to the year 1990), and (b) the local landslides database of the Esino Watershed (considering 421 landslides occurred over the 1990–2006 period). Results of the land covers change detection showed that in the study area many mixed cultivated patches were transformed into crops over the period 2000 and 2006. Results of the landslides pattern analysis showed high occurrence: (i) in structures that represent a transition between different covers (edge, branch, bridge) over the more vegetated areas, and (ii) in core areas of crops. Further studies are suggested in order to conclude a causal association between the vegetation patterns and landslide occurrence, repeating the described procedure in different study areas, with different climatic and geological settings.

Reducing the Gap Between Science, Policy and Practice: The Role of Civil Protection

Climate change confronts human society with a variety of new challenges. Among the various hazards in prospective scenarios, there is an increasing pressure on soil due to climatic variations, effects and impacts. This paper offers a perspective in the debate about science-policy-practice interface, about climate change and emerging hazards, analyzing a 50 years’ time-series of the Marche Region’s (central Italy) meteorological data and perception data. The analysis of meteorological data highlights a significant increasing trend in temperature both annually and seasonally, and a significant decreasing trend in daily precipitation in all seasons except autumn, which are causing a reduction in soil water availability. Moreover an historical analysis on the number of the regional landslides shows an increasing trend in the number of shallow landslides in the last 30 years. The perception data where obtained through the analysis of approximately 800 questionnaires carried out in the Marche Region in May–June 2011 to residents, policy makers and emergency managers. The analysis of questionnaires revealed a high awareness of climate change and apprehension about it causes and possible effects. Moreover the analysis highlights a differentiated concern about the increase in the number of landslides and their socio-economic impacts among the three groups. This could be due to an ineffective information exchange among scientific community, public administration, emergency managers and citizens. Therefore, we suggest that the “brokerage” role of the Civil Protection Agency in the information exchange process should be increased.

Correction to: A historical geomorphological approach to flood hazard management along the shore of an alpine lake (northern Italy)

This correction stands to correct mistakes presented in the original article due to a lag in the e-proofing system and the correction handling for this article. The original article has been corrected.

Impact of climate change on landslides frequency: the Esino river basin case study (Central Italy)

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).