Evaluating the Differences of Gridding Techniques for Digital Elevation Models Generation and Their Influence on the Modeling of Stony Debris Flows Routing: A Case Study From Rovina di Cancia Basin (North-Eastern Italian Alps)

Debris \ufb02ows are among the most hazardous phenomena in mountain areas. To cope with debris \ufb02ow hazard, it is common to delineate the risk-prone areas through routing models. The most important input to debris \ufb02ow routing models are the topographic data, usually in the form of Digital Elevation Models (DEMs). The quality of DEMs depends on the accuracy, density, and spatial distribution of the sampled points; on the characteristics of the surface; and on the applied gridding methodology. Therefore, the choice of the interpolation method affects the realistic representation of the channel and fan morphology, and thus potentially the debris \ufb02ow routing modeling outcomes. In this paper, we initially investigate the performance of common interpolation methods (i.e., linear triangulation, natural neighbor, nearest neighbor, Inverse Distance to a Power, ANUDEM, Radial Basis Functions, and ordinary kriging) in building DEMs with the complex topography of a debris \ufb02ow channel located in the Venetian Dolomites (North-eastern Italian Alps), by using small footprint full- waveform Light Detection And Ranging (LiDAR) data. The investigation is carried out through a combination of statistical analysis of vertical accuracy, algorithm robustness, and spatial clustering of vertical errors, and multi-criteria shape reliability assessment. After that, we examine the in\ufb02uence of the tested interpolation algorithms on the performance of a Geographic Information System (GIS)-based cell model for simulating stony debris \ufb02ows routing. In detail, we investigate both the correlation between the DEMs heights uncertainty resulting from the gridding procedure and that on the corresponding simulated erosion/deposition depths, both the effect of interpolation algorithms on simulated areas, erosion and deposition volumes, solid-liquid discharges, and channel morphology after the event. The comparison among the tested interpolation methods highlights that the ANUDEM and ordinary kriging algorithms are not suitable for building DEMs with complex topography. Conversely, the linear triangulation, the natural neighbor algorithm, and the thin-plate spline plus tension and completely regularized spline functions ensure the best trade-off among accuracy and shape reliability. Anyway, the evaluation of the effects of gridding techniques on debris \ufb02ow routing modeling reveals that the choice of the interpolation algorithm does not signi\ufb01cantly affect the model outcomes

Soil erosion in the Alps : causes and risk assessment

The issue of soil erosion in the Alps has long been neglected due to the low economic value of the agricultural land. However, soil stability is a key parameter which affects ecosystem services like slope stability, water budgets (drinking water reservoirs as well as flood prevention), vegetation productivity, ecosystem biodiversity and nutrient production. In alpine regions, spatial estimates on soil erosion are difficult to derive because the highly heterogeneous biogeophysical structure impedes measurement of soil erosion and the applicability of soil erosion models. However, remote sensing and geographic information system (GIS) methods allow for spatial estimation of soil erosion by direct detection of erosion features and supply of input data for soil erosion models. Thus, the main objective of this work is to address the problem of soil erosion risk assessment in the Alps on catchment scale with remote sensing and GIS tools. Regarding soil erosion processes the focus is on soil erosion by water (here sheet erosion) and gravity (here landslides). For these two processes we address i) the monitoring and mapping of the erosion features and related causal factors ii) soil erosion risk assessment with special emphasis on iii) the validation of existing models for alpine areas. All investigations were accomplished in the Urseren Valley (Central Swiss Alps) where the valley slopes are dramatically affected by sheet erosion and landslides. For landslides, a natural susceptibility of the catchment has been indicated by bivariate and multivariate statistical analysis. Geology, slope and stream density are the most significant static landslide causal factors. Static factors are here defined as factors that do not change their attributes during the considered time span of the study (45 years), e.g. geology, stream network. The occurrence of landslides might be significantly increased by the combined effects of global climate and land use change. Thus, our hypothesis is that more recent changes in land use and climate affected the spatial and temporal occurrence of landslides. The increase of the landslide area of 92% within 45 years in the study site confirmed our hypothesis. In order to identify the cause for the trend in landslide occurrence time-series of landslide causal factors were analysed. The analysis revealed increasing trends in the frequency and intensity of extreme rainfall events and stocking of pasture animals. These developments presumably enhanced landslide hazard. Moreover, changes in land-cover and land use were shown to have affected landslide occurrence. For instance, abandoned areas and areas with recently emerging shrub vegetation show very low landslide densities. Detailed spatial analysis of the land use with GIS and interviews with farmers confirmed the strong influence of the land use management practises on slope stability. The definite identification and quantification of the impact of these non-stationary landslide causal factors (dynamic factors) on the landslide trend was not possible due to the simultaneous change of several factors. The consideration of dynamic factors in statistical landslide susceptibility assessments is still unsolved. The latter may lead to erroneous model predictions, especially in times of dramatic environmental change. Thus, we evaluated the effect of dynamic landslide causal factors on the validity of landslide susceptibility maps for spatial and temporal predictions. For this purpose, a logistic regression model based on data of the year 2000 was set up. The resulting landslide susceptibility map was valid for spatial predictions. However, the model failed to predict the landslides that occurred in a subsequent event. In order to handle this weakness of statistic landslide modelling a multitemporal approach was developed. It is based on establishing logistic regression models for two points in time (here 1959 and 2000). Both models could correctly classify >70% of the independent spatial validation dataset. By subtracting the 1959 susceptibility map from the 2000 susceptibility map a deviation susceptibility map was obtained. Our interpretation was that these susceptibility deviations indicate the effect of dynamic causal factors on the landslide probability. The deviation map explained 85% of new independent landslides occurring after 2000. Thus, we believe it to be a suitable tool to add a time element to a susceptibility map pointing to areas with changing susceptibility due to recently changing environmental conditions or human interactions. In contrast to landslides that are a direct threat to buildings and infrastructure, sheet erosion attracts less attention because it is often an unseen process. Nonetheless, sheet erosion may account for a major proportion of soil loss. Soil loss by sheet erosion is related to high spatial variability, however, in contrast to arable fields for alpine grasslands erosion damages are long lasting and visible over longer time periods. A crucial erosion triggering parameter that can be derived from satellite imagery is fractional vegetation cover (FVC). Measurements of the radiogenic isotope Cs-137, which is a common tracer for soil erosion, confirm the importance of FVC for soil erosion yield in alpine areas. Linear spectral unmixing (LSU), mixture tuned matched filtering (MTMF) and the spectral index NDVI are applied for estimating fractional abundance of vegetation and bare soil. To account for the small scale heterogeneity of the alpine landscape very high resolved multispectral QuickBird imagery is used. The performance of LSU and MTMF for estimating percent vegetation cover is good (r²=0.85, r²=0.71 respectively). A poorer performance is achieved for bare soil (r²=0.28, r²=0.39 respectively) because compared to vegetation, bare soil has a less characteristic spectral signature in the wavelength domain detected by the QuickBird sensor. Apart from monitoring erosion controlling factors, quantification of soil erosion by applying soil erosion risk models is done. The performance of the two established models Universal Soil Loss Equation (USLE) and Pan-European Soil Erosion Risk Assessment (PESERA) for their suitability to model erosion for mountain environments is tested. Cs-137 is used to verify the resulting erosion rates from USLE and PESERA. PESERA yields no correlation to measured Cs-137 long term erosion rates and shows lower sensitivity to FVC. Thus, USLE is used to model the entire study site. The LSU-derived FVC map is used to adapt the C factor of the USLE. Compared to the low erosion rates computed with the former available low resolution dataset (1:25000) the satellite supported USLE map shows “hotspots” of soil erosion of up to 16 t ha-1 a-1. In general, Cs-137 in combination with the USLE is a very suitable method to assess soil erosion for larger areas, as both give estimates on long-term soil erosion. Especially for inaccessible alpine areas, GIS and remote sensing proved to be powerful tools that can be used for repetitive measurements of erosion features and causal factors. In times of global change it is of crucial importance to account for temporal developments. However, the evaluation of the applied soil erosion risk models revealed that the implementation of temporal aspects, such as varying climate, land use and vegetation cover is still insufficient. Thus, the proposed validation strategies (spatial, temporal and via Cs-137) are essential. Further case studies in alpine regions are needed to test the methods elaborated for the Urseren Valley. However, the presented approaches are promising with respect to improve the monitoring and identification of soil erosion risk areas in alpine regions

DEM Spatial Resolution Impact On Hillslope Erosion and Deposition Modeling, an Application On Lebanese Watersheds

Geographic Information Systems analysis based on Digital Elevation Models (DEMs) vary with spatial resolution and datasets production method. DEMs with different spatial resolutions can lead to several analysis results. This study investigates the effects of DEMs on predicting soil erosion and deposition modeling on Lebanese river basins. Two DEMs at different spatial resolutions from two sources were used to calculate topographic and hydrological parameters for the prediction of the Sediment Transport Index (STI), the erosion-deposition based on Unit Stream Power Erosion and the Deposition Model (USPED) taking into account only the topography factors expressed in DEMs. This paper analyzes hillslope erosion and deposition rates in a GIS to estimate patterns sheet and rill erosion in 13 Lebanese river basins. A correlation analysis applied to test the degree of similarity between the datasets and the effect of erosion deposition with spatial resolution.Results indicate that rill erosion and deposition have an influence on high spatial resolution DEMs, due to the good terrain representation especially the concave forms of deposition.This result shows the increased rill erosivity of channel ?ow in the downstream, and sediment deposition in concave areas

Comparison of landscape approaches to define spatial patterns of hillslope-scale sediment delivery ratio

A sediment delivery ratio (SDR) is that fraction of gross erosion that is transported from a given catchment in a given time interval. In essence, a SDR is a scaling factor that relates sediment availability and deposition at different spatial scales. In this paper, we focus on hillslope-scale SDR, i.e. the ratio of sediment produced from hillslopes to that delivered to the stream network. Factors that affect hillslope water movement, and thus entrainment or deposition of sediments, ultimately affecting the SDR, include upslope area, climate, topography, and soil cover. In erosion models, SDR is usually treated as a constant parameter. However, the use of spatially variable SDRs could improve the spatial prediction of the critical sources of sediment, i.e. identification of those areas directly affecting stream water quality. Such information would improve prioritisation of natural resource management effort and investment. Recent literature has described several landscape approaches to represent SDR variability in space, some of which account only for topography, whilst others consider topography and soil cover characteristics. The aim of this study was to evaluate four landscape approaches for their ability to depict spatial patterns of SDR in the Avon-Richardson catchment in the semi-arid Wimmera region (Victoria, South-east Australia). Erosion was assessed using a semi-distributed model (CatchMODS) with disaggregation based in subcatchments of around 40 km2 area. Hillslope gross erosion was assessed with a RUSLE approach. By applying the four landscape approaches using DEM and estimates of land use cover, four landscape index subcatchment distributions were calculated. These were normalised into standard distributions. Then, a sigmoid function was used to transform the standardised indices into SDR-index distributions ranging from zero to one. Finally, subcatchment SDRs were estimated as the product of the SDR-index by a whole-of-catchment SDR value that was estimated by calibration against sediment loads measured at five gauging stations of the study area. The major sources of hillslope erosion were modelled to be located in the southern hilly areas of the catchment. However, a topographic convergence approach predicted as well important contribution of hillslope-erosion sediment loads coming from the eastern flatter cropping land. The introduction of landscape-variable SDRs improved the overall goodness-of-fit of modelled versus observed sediment loads at five gauging stations located in the catchment for only the topographic convergence approach. However, the limited number of observations (11), the location of some gauging stations downstream of active gully erosion, and the lack of gauging stations monitoring the north-eastern part of the catchment hindered the assessment of which spatial distribution of hillslope erosion best represented the real catchment conditions. Further research is needed to define the relationship between landscape indices and SDR; and to evaluate the spatial distribution of erosion against more complete field evidence

Numerical modelling and economics of agricultural land degradation in the Maltese Islands

The study applies a new GIS-based numerical modelling approach to calculate the economic burden agricultural land owners suff er through soil erosion land degradation. Numerically modelled soil erosion volumes in Maltese agricultural areas were estimated at 766 278 m3/yr costing 7.98M€/yr to replace. The model calculates that the average owner incurs 1170€/0.01km2/yr on soil replacement and soil improvement requirements. With average yearly economic revenue of 1720€/0.01km2/yr, this cost benefi t imbalance may force agricultural land owners to not replace eroded soils. Over time, as a result of soil erosion, an increasingly large proportion of agricultural land may no longer suitable for agricultural purposes. Over 50 years, 1.53km2 (0.5% of Maltese area) of agricultural land may be depleted of soil, incurring an average national agricultural revenue loss of 0.26M€ per year. Soil erosion rates, and associated economic implications, may be mitigated with cost e ffective management practices. Two such practices include conservation tillage, which o ffers various economic advantages to farmers, and the restoration of breaches in slope-facing rubble walls in areas subject to soil erosion. The latter may require an investment of 11.94M€ at the National scale or €1,600 by the average agricultural land owner. Both measures contribute towards the sustainable use of Maltese agricultural areas and maintaining key associated ecosystems services.peer-reviewe

Contemporary geomorphological activity throughout the proglacial area of an alpine catchment

Quantification of contemporary geomorphological activity is a fundamental prerequisite for predicting the effects of future earth surface process and landscape development changes. However, there is a lack of high-resolution spatial and temporal data on geomorphological activity within alpine catchments, which are especially sensitive to climate change, human impacts and which are amongst the most dynamic landscapes on Earth. This study used data from repeated laser scanning to identify and quantify the distribution of contemporary sediment sources and the intensity of geomorphological activity within the lower part of a glaciated alpine catchment; Ödenwinkelkees, central Austria. Spatially, geomorphological activity was discriminated by substrate class. Activity decreased in both areal extent and intensity with distance from the glacier, becoming progressively more restricted to the fluvially-dominated valley floor. Temporally, geomorphological activity was identified on annual, seasonal, weekly and daily timescales. Activity became more extensive with increasing study duration but more intense over shorter timescales, thereby demonstrating the importance of temporary storage of sediment within the catchment. The mean volume of material moved within the proglacial zone was 4400m.yr, which suggests a net surface lowering of 34mm.yr in this part of the catchment. We extrapolate a minimum of 4.8mm.yr net surface lowering across the whole catchment. These surface lowering values are approximately twice those calculated elsewhere from contemporary measurements of suspended sediment flux, and of rates calculated from the geological record, perhaps because we measure total geomorphological activity within the catchment rather than overall efflux of material. Repeated geomorphological surveying therefore appears to mitigate the problems of hydrological studies underestimating sediment fluxes on decadal-annual time-scales. Further development of the approach outlined in this study will enable the quantification of geomorphological activity, alpine terrain stability and persistence of landforms

The debris flow occurred at ru secco creek, venetian dolomites, on 4 august 2015: Analysis of the phenomenon, its characteristics and reproduction by models

On 4 August 2015, a very high intensity storm, 31.5 mm in 20 min (94.5 mm/h), hit the massif of Mount Antelao on the Venetian Dolomites triggering three stony debris \ufb02ows characterized by high magnitude. Two of them occurred in the historical sites of Rovina di Cancia and Rudan Creek and were stopped by the retaining works upstream the inhabited areas, while the third routed along the Ru Secco Creek and progressively reached the resort area and the village of San Vito di Cadore, causing fatalities and damages. The main triggering factor of the Ru Secco debris \ufb02ow was a large rock collapse on the northern cliffs of Mount Antelao occurred the previous autumn. The fallen debris material deposited on the Vallon d\u2019Antrimoia inclined plateau at the base of the collapsed cliffs and, below it, on the Ru Salvela Creek, covering it from the head to the con\ufb02uence with the Ru Secco Creek. The abundant runoff, caused by the high intensity rainfall on 4 August 2015, entrained about 52,500 m3 of the debris material laying on the Vallon d\u2019Antrimoia forming a debris \ufb02ow surge that hit and eroded the debris deposit covering the downstream Ru Salvela Creek, increasing its volume, about 110,000 m3 of mobilized sediments. This debris \ufb02ow routed downstream the con\ufb02uence, \ufb02ooding the parking of a resort area where three people died, and reached the village downstream damaging some buildings. A geomorphological analysis was initially carried out after surveying the whole basin. All liquid and solid-liquid contributions to the phenomenon were recognized together with the areas subjected to erosion and deposition. The elaboration of pre and post-event topographical surveys provided the map of deposition-erosion depths. Using the rainfall estimated by weather radar and corrected by the nearest rain gauge, about 0.8 km far, we estimated runoff by using a rainfall-runoff model designed for the headwater rocky basins of Dolomites. A triggering model provided the debris \ufb02ow hydrographs in the initiation areas, after using the simulated runoff. The initial solid-liquid surge hydrographs were, then, routed downstream by means of a cell model. The comparison between the simulated and estimated deposition-erosion pattern resulted satisfactory. The results of the simulation captured, in fact, the main features of the occurred phenomenon