Quantifying rates of climate change in mountain regions is of considerable interest, not least because mountains are viewed as climate “hotspots” where change can anticipate or amplify what is ...occurring elsewhere. Accelerating mountain climate change has extensive environmental impacts, including depletion of snow/ice reserves, critical for the world's water supply. Whilst the concept of elevation‐dependent warming (EDW), whereby warming rates are stratified by elevation, is widely accepted, no consistent EDW profile at the global scale has been identified. Past assessments have also neglected elevation‐dependent changes in precipitation. In this comprehensive analysis, both in situ station temperature and precipitation data from mountain regions, and global gridded data sets (observations, reanalyses, and model hindcasts) are employed to examine the elevation dependency of temperature and precipitation changes since 1900. In situ observations in paired studies (using adjacent stations) show a tendency toward enhanced warming at higher elevations. However, when all mountain/lowland studies are pooled into two groups, no systematic difference in high versus low elevation group warming rates is found. Precipitation changes based on station data are inconsistent with no systematic contrast between mountain and lowland precipitation trends. Gridded data sets (CRU, GISTEMP, GPCC, ERA5, and CMIP5) show increased warming rates at higher elevations in some regions, but on a global scale there is no universal amplification of warming in mountains. Increases in mountain precipitation are weaker than for low elevations worldwide, meaning reduced elevation‐dependency of precipitation, especially in midlatitudes. Agreement on elevation‐dependent changes between gridded data sets is weak for temperature but stronger for precipitation.
Plain Language SummaryMountains cover a large part of the Earth's surface and harbor distinct ecosystems, hold most of snow and ice outside the polar regions, and provide water for billions of people. This research looks at recent climate changes in mountains and compares them with simultaneous changes in lowland regions using weather station data, large global data sets, and climate models. We examine changes since 1900, but also concentrate on the last 40 years since this is when many changes have started to accelerate. Nearly all regions of the globe are getting warmer. When we make local comparisons, mountain sites are usually warming faster than lower areas nearby. However, when we average data from all global mountains and compare them with those from all lowland areas, there is no significant difference. Rainfall/snowfall on the other hand is decreasing in some areas, and increasing in others. In nearly all cases the strongest increase is occurring in the lowland areas, with increases in the mountains being more subdued (if at all). One consequence of our findings is that stores of mountain snow and ice may decline even faster than previously assumed due to the combination of enhanced mountain warming and reduced elevation dependency of rainfall/snowfall.
Key PointsUsing station and gridded data sets, we compare global precipitation and temperature trends by elevationLocal comparisons of paired stations and regional comparisons using gridded data often show faster mountain than lowland warmingPrecipitation differences between mountains and adjacent lowlands are reducing, often driven by stronger precipitation increase in lowlands
The choice of the proper resolution in landslide susceptibility mapping is a worth considering issue. If, on the one hand, a coarse spatial resolution may describe the terrain morphologic properties ...with low accuracy, on the other hand, at very fine resolutions, some of the DEM-derived morphometric factors may hold an excess of details. Moreover, the landslide inventory maps are represented throughout geospatial vector data structure, therefore a conversion procedure vector-to-raster is required.
This work investigates the effects of raster resolution on the susceptibility mapping in conjunction with the use of different algorithms of vector-raster conversion. The Artificial Neural Network technique is used to carry out such analyses on two Sicilian basins. Seven resolutions and three conversion algorithms are investigated. Results indicate that the finest resolutions do not lead to the highest model performances, whereas the algorithm of conversion data may significantly affect the ANN training procedure at coarse resolutions.
•Landslide susceptibility maps using ANN.•Effects of raster resolution and vector-to-raster conversion algorithms.•The finest resolutions do not necessarily lead to the highest model performances.•The algorithm of conversion data may significantly affect the ANN training.
This study proposes a new methodology for estimating the additional shear strength (or cohesion) exerted by vegetation roots on slope stability analysis within a coupled hydrological‐stability model. ...The mechanical root cohesion is estimated within a Fiber Bundle Model framework that allows for the evaluation of the root strength as a function of stress‐strain relationships of populations of fibers. The use of such model requires the knowledge of the root architecture. A branching topology model based on Leonardo's rule is developed, providing an estimation of the amount of roots and the distribution of diameters with depth. The proposed methodology has been implemented into an existing distributed hydrological‐stability model able to simulate the dynamics of factor of safety as a function of soil moisture dynamics. The model also accounts for the hydrological effects of vegetation, which reduces soil water content via root water uptake, thus increasing the stability. The entire methodology has been tested in a synthetic hillslope with two configurations of vegetation type, i.e., trees and shrubs, which have been compared to a configuration without vegetation. The vegetation has been characterized using roots data of two mediterranean plant species. The results demonstrate the capabilities of the topological model in accurately reproducing the observed root structure of the analyzed species. For the environmental setting modeled, the effects of root uptake might be more significant than the mechanical reinforcement; the additional resistance depends strictly on the vegetation root depth. Finally, for the simulated climatic environment, landslides are seasonal, in agreement with past observations.
Key Points:
Root cohesion estimated using a FBM and branching topology model
Assessment of hydrological and mechanical stability effects of roots for shrubs and trees
The effects of root uptake can be more significant than the mechanical reinforcement
•Hydrological processes are recurrently affected by land-use and climate changes.•Synthetic experiments with advanced models can explain some feedback mechanisms.•Alterations in the hydrological ...response depends on the basins’ spatial scale.•Urbanization and its spatial evolution affect the runoff components partitioning.•Urbanization could either smooth or exacerbate climate change effects on runoff.
This paper proposes a modeling framework able to analyze the alterations in watershed hydrology induced by two recurrent drivers for hydrological changes: climate change and urbanization. The procedure is based on the coupling of a stochastic weather generator with a land use change model for the generation of some hypothetical scenarios. The generated scenarios are successively used to force a physically-based and spatial distributed hydrological model to reconstruct the basin response under different conditions. Several potential climate alterations are simulated by imposing negative and positive variations in the mean annual precipitation and a simultaneous temperature increase. Urbanization is conceptualized by an increase in the impervious fraction of the basin. The procedure is applied to a large basin and a much smaller sub-basin; the results show how climate and land use changes may interact and affect the fundamental hydrological dynamics and how the processes governing basin hydrological response may change with spatial scale.
This study proposes a methodology for the drought assessment based on the seasonal forecasts. These are climate predictions of atmospheric variables, such as precipitation, temperature, wind speed, ...for upcoming season, up to 7 months. In regions particularly vulnerable to droughts and to changes in climate, such as the Mediterranean areas, predictions of precipitation with months in advance are crucial for understanding the possible shifts, for example, in water resource availability. Over Europe, practical applications of seasonal forecasts are still rare, because of the uncertainties of their skills; however, the predictability varies depending on the season and area of application. In this study, we describe a methodology which integrates, through a statistical approach, seasonal forecast and reanalysis data to assess the climate state, i.e. drought or not, of a region for predefined periods in the next future, at monthly scale. Additionally, the skill of the forecasts and the reliability of the released climate state assessment are estimated in terms of the false rate, i.e. the probability of missing alerts or false alarms. The methodology has been first built for a case study in Zakynthos (Greece) and then validated for a case study in Sicily (Italy). The selected locations represent two areas of the Mediterranean region often suffering from drought and water shortage situations. Results showed promising findings, with satisfying matching between predictions and observations, and false rates ranging from 1 to 50%, depending on the selected forecast period.
Tidal measurements from the Italian city of Venice, available since 1872 and constituting the longest sea-level record in the Mediterranean area, indicate that local flooding statistics have ...dramatically worsened during the last decades. Individual flooding episodes are associated with adverse meteorological conditions, and their increased frequency is mainly attributed to the rise of the average local Relative Sea Level (RSL). However, the role of interannual-to-multidecadal modes of average RSL variability in shaping the evolution of Venice flooding is highly significant and can cause sharp increases in the flood frequency episodes. Here, we use local tidal measurements in Venice covering 1872–2020 to deeply inspect the contribution and predictability of the different components characterizing the observed average RSL variability, including a long-term trend and four quasi-periodic modes. Our results demonstrate that the observed increase in flooding frequency is not only due to the average RSL rise but also due to a progressive widening of tidal anomalies around the average RSL, revealed by opposite trends in mean tidal maxima and minima. Moreover, interannual and decadal periodicities are not negligible in modulating the timing of annual mean RSL and flood frequency extremes. This study demonstrates that the last decades experienced an unprecedented sharp increase in sea level, which significantly affected the decadal predictability of RSL with statistical methods. Our work contributes to a deeper understanding of the sources of uncertainty in decadal sea-level variability and predictability in the Venice lagoon.
Landslides are a serious threat to life and property throughout the world. The causes of landslides are various since multiple dynamic processes are involved in driving slope failures. One of these ...causes is prolonged rainfall, which affects slope stability in different ways. Water infiltrating in a hillslope may cause a rise of the piezometric surface, which, in turn, involves an increase of the pore water pressure and a decrease of the soil shear resistance. For this reason, knowledge of spatio-temporal dynamics of soil water content, infiltration processes and groundwater dynamics, is of considerable importance in the understanding and prediction of landslides dynamics.
In this paper a spatially distributed and physically based approach is presented, which embeds a slope failure method in a hydrological model. The hydrological model here used is the tRIBS model (Triangulated Irregular Network Real-Time Integrated Basin Simulator) that allows simulation of most of spatial-temporal hydrologic processes (infiltration, evapotranspiration, groundwater dynamics and soil moisture conditions) that can influence landsliding. Slope stability is assessed by implementing the infinite slope model in tRIBS. The model, based on geotechnical and geomorphological characteristics, classifies each computational cell as unconditionally stable or conditionally stable. Soil moisture conditions resulting from precipitation can trigger landslides at conditionally stable locations. When a landslide occurs, the model also computes the amount of detached soil and its possible path downslope.
Model performance has been initially tested on a small catchment with very steep slopes, located in the northern part of Sicily (Italy), after a sensitivity analysis concerning some model parameters.
Leonardo's rule (Lrule) applied to below-ground systems defines a simple topological scheme that describes how the branches of root architectures develop within the soil. The approach does not ...consider the soil-climate-root interactions. From another hand, eco-hydrological approaches exploit physically-based formulations to derive the dynamic evolution of root profile based on soil and climate characteristics. In homogenous soil and simplified hydrological conditions, analytical solutions can be derived, as demonstrated by Laio's model, who proposed a simple exponential formulation to derive the Root Area (AR) profile. Apart from Laio's model, more generalized functions, i.e. derived by two and three parameters gamma distribution or others, can be efficiently used to derive the AR profile.
This communication proposes a combination of the Lrule and eco-hydrological approaches to derive the AR profile, at given soil and climate conditions, allowing to identify a physical and theoretical meaning of the Lrule's parameters. A comprehensive root dataset from field measurements carried out in the region of Tuscany (Italy) is used. Results demonstrate that values of Lrule's parameters derived throughout the proposed mathematical relationships tend to constant values in case of exponential function, which is valid for homogenous soils. Moreover, in a realistic vegetated soil, where top-soil is different than deep-soil, functions derived from a two and three parameters gamma distribution may reproduce better root data observations.
•Root architecture description throughout topological model.•Analyzing Leonardo's rule parameters meaning.•Comparison between topological and eco-hydrological approaches.•Root biomass distribution controlled by soil and climate characteristics.
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