Publications
Publications found: 2022
Calibration of a Distributed Hydrological Model (VIC-3L) Based on Global Water Resources Reanalysis Datasets
Koohi, Sakine; Azizian, Asghar; Brocca, Luca, 2022, Calibration of a Distributed Hydrological Model (VIC-3L) Based on Global Water Resources Reanalysis Datasets,
Water resources management 36 (2022): 1287–1306. doi_10.1007/s11269-022-03081-9,
DOI: 10.1007%2Fs11269-022-03081-9
Abstract
The lack of observed streamflow datasets for calibration of rainfall-runoff models imposes substantial problems for ...
The lack of observed streamflow datasets for calibration of rainfall-runoff models imposes substantial problems for their applicability, especially in poorly gauged or ungauged river basins. Developing satellite technologies and increasing computational powers over the past decades, have provided an environment for researchers to simulate several water balance components globally using these datasets and assimilation techniques. Due to importance of accurate hydrologic modeling, this study aims to investigate the applicability of global water resources reanalysis (GWRR) datasets including surface soil moisture (SSM), evapotranspiration (ET), and surface runoff (SR) components for calibration of the macro-scale hydrological model (VIC-3L) over the SefidRood basin (SRB) in Iran at different calibration scenarios. Results show that in the case of using SSM datasets, the model's performance in the simulation of streamflow hydrograph, with the NSE value higher than 0.65, is better than using other datasets. Among different datasets, the SSM based on LISFLOOD and HBV are the best ones for calibration of VIC-3L model over SRB. In contrast, using ET datasets aren't so reliable for hydrological calibration in the study area. Furthermore, in the cases of using SSM and surface runoff datasets, the model tends to overestimation of low-flows, while, ET datasets are more reliable for simulation of such these flows. Also, findings displayed that the combination of ET and SSM datasets for hydrological calibration performed better than using only one dataset. In conclusion, this research gives useful and applied insights in the applicability of GWRR data sources for hydrological modeling and water resources studies, especially in data limited regions.
Double-scale analysis on the detectability of irrigation signals from remote sensing soil moisture over an area with complex topography in central Italy
Dari, Jacopo; Brocca, Luca; Quintana-Seguí, Pere; Casadei, Stefano; Escorihuela, María José; Stefan, Vivien; Morbidelli, Renato, 2022, Double-scale analysis on the detectability of irrigation signals from remote sensing soil moisture over an area with complex topography in central Italy,
Advances in water resources 161 (2022). doi_10.1016/j.advwatres.2022.104130,
DOI: 10.1016%2Fj.advwatres.2022.104130
Abstract
Despite a detailed knowledge of the spatial-temporal dynamics of irrigation being necessary to optimize the ...
Despite a detailed knowledge of the spatial-temporal dynamics of irrigation being necessary to optimize the agricultural production without exacerbating the pressure exercised on the water resource, such information is still often lacking worldwide. In this study, a double-scale analysis on the detectability of the irrigation occurrence over an area in central Italy through remote sensing soil moisture is proposed; the period of interest is a 3-year time span from 2017 to 2019. The detectability of district- or sub-district-scale irrigation signals through remotely sensed soil moisture data is investigated at two different spatial resolutions_ 1 km and plot scale. Three soil moisture products sampled at 1 km resolution are evaluated_ a DISPATCH (DISaggregation based on Physical And Theoretical scale CHange) downscaled version of SMAP (Soil Moisture Active Passive) and two Sentinel-1-derived products, namely the 1 km version delivered by Copernicus and a plot-scale-born version developed by THEIA and aggregated at 1 km. The THEIA Sentinel-1 product aggregated at 100 m is used in the plot-scale analysis. Over the study area, the irrigation extent is determined by the fragmentation of the agricultural fields and the complex topography, making the adoption of plot-scale data necessary. Satisfactory results are obtained by comparing maps of irrigated areas at 100 m spatial resolution produced through the k-means clustering algorithm with ground-truth data, since the method fails only once out of seven in properly reproducing the irrigated or non-irrigated conditions occurred over four pilot agricultural fields.
Irrigation estimates from space_ Implementation of different approaches to model the evapotranspiration contribution within a soil-moisture-based inversion algorithm
Dari, Jacopo; Quintana-Seguí, Pere; Morbidelli, Renato; Saltalippi, Carla; Flammini, Alessia; Giugliarelli, Elena; Escorihuela, María José; Stefan, Vivien; Brocca, Luca, 2022, Irrigation estimates from space_ Implementation of different approaches to model the evapotranspiration contribution within a soil-moisture-based inversion algorithm,
Agricultural water management (Print) 265 (2022). doi_10.1016/j.agwat.2022.107537,
DOI: 10.1016%2Fj.agwat.2022.107537
Abstract
Irrigation is the most impacting and uncertain human intervention on the water resource. The possibility ...
Irrigation is the most impacting and uncertain human intervention on the water resource. The possibility of retrieving information on irrigation practices through remote sensing technology opens unprecedented perspectives on the monitoring of anthropized basins. This study is aimed at assessing the impact of different approaches to model the contribution of the evapotranspiration in retrieving the amounts of water applied for irrigation through a soil-moisture-based (SM-based) inversion algorithm; such a contribution is conclusive especially over semi-arid regions. Three modeling approaches relying on both calculated and remotely sensed actual and potential evapotranspiration (ET and PET) data sets were implemented to represent the evapotranspiration rate within the SM-based inversion method, which allows backward estimation of irrigation through the soil water balance inversion. By combining the different evapotranspiration data sources and modeling approaches, seven experiments aimed at inverting DISPATCH (DISaggregation based on Physical And Theoretical scale CHange) downscaled SMAP (Soil Moisture Active Passive) soil moisture at 1 km to estimate irrigation over four heavily irrigated agricultural districts located in Spain (Aragon and Catalonia) were compared. The results highlighted that the application of the FAO56 guidelines parametrization relying on the use of optical data as proposed by the authors in a previous study remains the most reliable configuration. In fact, the implementation of a simplified approach not considering the transpiration component of the specific crop led to irrigation underestimates. Finally, it is interesting to note that the application of the method with remotely sensed ET from MODIS (MODerate-resolution Imaging Spectroradiometer) produced reliable district-aggregated irrigation estimates, thus opening the perspective of an algorithm configuration forced with remote sensing data only.
Irrigation Mapping on Two Contrasted Climatic Contexts Using Sentinel-1 and Sentinel-2 Data
Elwan, Ehsan; Le Page, Michel; Jarlan, Lionel; Baghdadi, Nicolas; Brocca, Luca; Modanesi, Sara; Dari, Jacopo; Quintana Segui, Pere; Zribi, Mehrez, 2022, Irrigation Mapping on Two Contrasted Climatic Contexts Using Sentinel-1 and Sentinel-2 Data,
Water (Basel) 14 (2022). doi_10.3390/w14050804,
DOI: 10.3390%2Fw14050804
Abstract
This study aims to propose an operational approach to map irrigated areas based on the ...
This study aims to propose an operational approach to map irrigated areas based on the synergy of Sentinel-1 (S1) and Sentinel-2 (S2) data. An application is proposed at two study sites in Europe-in Spain and in Italy-with two climatic contexts (semiarid and humid, respectively), with the objective of proving the essential role of multi-site training for a robust application of the proposed methodologies. Several classifiers are proposed to separate irrigated and rainfed areas. They are based on statistical variables from Sentinel-1 and Sentinel-2 time series data at the agricultural field scale, as well as on the contrasted behavior between the field scale and the 5 km surroundings. The support vector machine (SVM) classification approach was tested with different options to evaluate the robustness of the proposed methodologies. The optimal number of metrics found is five. These metrics illustrate the importance of optical/radar synergy and the consideration of multi-scale spatial information. The highest accuracy of the classifications, approximately equal to 85%, is based on training dataset with mixed reference fields from the two study sites. In addition, the accuracy is consistent at the two study sites. These results confirm the potential of the proposed approaches towards the most general use on sites with different climatic and agricultural contexts.
Broadening and Deepening the Rainfall-Induced Landslide Detection_ Practices and Perspectives at a Global Scale
Guoqiang Jia, Qiuhong Tang, Stefano Luigi Gariano, Massimo Melillo, Ximeng Xu, Guoyong Leng, Xu Li, 2022, Broadening and Deepening the Rainfall-Induced Landslide Detection_ Practices and Perspectives at a Global Scale,
Climate Risk and Sustainable Water Management, edited by Q. Tang & G. Leng, pp. 267–288. Cambridge_ Cambridge university press, 2022,
Abstract
A better detection of landslide occurrence is critical for disaster prevention and mitigation. Over the ...
A better detection of landslide occurrence is critical for disaster prevention and mitigation. Over the past four decades, great achievements have been made, ranging from inventories to mapping, susceptibility analysis to triggering threshold identification. Here, we proposed a model to establish global distributed rainfall thresholds, by linking triggering rainfall with geo-environmental causes related to landslide events. The model was based on multiple linear regression method, to define rainfall thresholds as a function of diverse geo-environmental variables, fitted and validated by a combined and relatively accurate landslide dataset. Results show primarily feasible performances for training and testing datasets, with low mean absolute error (0.22 log(mm)) and a high coefficient of determination (0.67) totally. We further prepared global distributed threshold maps for sub- and multi-daily rainfall durations. They share similar spatial distributions in line with previous research. The normalized rainfall index, defined as the ratio of precipitation amount over distributed rainfall thresholds, can be an index of possible landslide occurrence, that is, regions with a normalized index over 1.0 correspond to high probability. We argue that distributed rainfall threshold models are an improvement of empirical threshold models and susceptibility assessments by considering the interaction between triggering rainfall and geo-environmental causes, and promising for better hazard assessment.
A systematic review of scientific literature on earthquake-induced landslides
Luca Schilirò 1, Mauro Rossi 2, Federica Polpetta 1, Federica Fiorucci 2, Carolina Fortunato 1, Paola Reichenbach 2, 2022, A systematic review of scientific literature on earthquake-induced landslides,
EGU General Assembly 2022, Vienna, 23-27/05/2022,
Landslide susceptibility maps of Italy_ lesson learnt from dealing with multiple landslide classes and the uneven spatial distribution of the national inventory
Marco Loche (1), Massimiliano Alvioli (2), Ivan Marchesini (2), Haakon Bakka (3), Luigi Lombardo(4), 2022, Landslide susceptibility maps of Italy_ lesson learnt from dealing with multiple landslide classes and the uneven spatial distribution of the national inventory,
Earth-science reviews 232 (2022): 104125. doi_10.1016/j.earscirev.2022.104125,
DOI: 10.1016%2Fj.earscirev.2022.104125
Abstract
Landslide susceptibility corresponds to the probability of landslide occurrence across a given geographic space. This ...
Landslide susceptibility corresponds to the probability of landslide occurrence across a given geographic space. This probability is usually estimated by using a
binary classifier which is informed of landslide presence/absence data and associated landscape characteristics. Here, we consider the Italian national landslide inventory to prepare slope-unit based landslide susceptibility maps. These maps are prepared for the eight types of mass movements existing in the inventory, (Complex, Deep Seated Gravitational Slope Deformation, Diffused Fall, Fall, Rapid Flow, Shallow, Slow Flow, Translational) and build one susceptibility map for each type. The analysis - carried out by using a Bayeian version of a Generalized Additive Model with a multiple intercept for each Italian region - revealed that the inventory may have been compiled with different levels of detail. This would be consistent with the datases being assembled from twenty sub-inventories, each prepared by different administrations of the Italian regions. As a result, this spatial inhonomegenity may lead to a biased national-scale susceptibility maps. On the basis of these considerations, we further analyzed the national database to confirm or reject the varying quality hypothesis suggested by the multiple intercepts results. For each landslide type, we then tried to build unbiased
susceptibility models by removing regions with a poor landslide inventory from the calibration stage, and used them only as a prediction target of a simulation routine.
We analyzed the resulting eight maps finding out a congruent dominant pattern in the Alpine and Apennine sectors. The whole procedure is implemented in R-INLA. This allowed to examine fixed (linear) and random (nonlinear) effects from an interpretative standpoint and produced a full prediction equipped with an estimated uncertainty.
We propose this overall modeling pipeline for any landslide datasets where a significant mapping bias may influence the susceptibility pattern over space.
Geomorphological slope units of the Himalayas
M. Alvioli (a), I. Marchesini (a), B. Pokharel (b), K. Gnyawali (c), S. Lim (b), 2022, Geomorphological slope units of the Himalayas,
2022,
Abstract
Terrain classification based on slope units (SU). Colors match the figures below and correspond to ...
Terrain classification based on slope units (SU). Colors match the figures below and correspond to ten classes (clusters), obtained by k-means clustering with slope unit aggregation level. Clustering was applied using mean and standard deviation of morphometric variables calculated within each slope unit polygon_ elevation is the dominant contribution. The inset shows the location of the study area (blue polygon), mostly in Nepal. Maps in EPSG_4326. © Journal of Maps, 2022
Geomorphological slope units of the Himalayas
M. Alvioli (a), I. Marchesini (a), B. Pokharel (b), K. Gnyawali (c), S. Lim (b), 2022, Geomorphological slope units of the Himalayas,
Journal of maps (2022). doi_10.1080/17445647.2022.2052768,
DOI: 10.1080%2F17445647.2022.2052768
Abstract
Slope units represent surface slopes by means of polygons delimited by drainage and divide lines ...
Slope units represent surface slopes by means of polygons delimited by drainage and divide lines obtained on a digital topography. Objective slope unit delineation for a given digital elevation model is still an open issue and, often, a limitation that may dictate the use of a more traditional pixel-based approach for spatial analysis. Availability of slope unit maps facilitates many kinds of studies, and allows scholars to focus on specific scientific issues rather than on preparing sound mapping units from scratch for their research. Here, we present a slope unit map of a large portion of the Himalayas. The map is prepared following a widely tested, parameter-free optimization algorithm. The area encompassed by the map is relevant to studies of the well-known 2015 Gorkha earthquake and monsoons, which makes it relevant to a vast portion of the scientific community working in natural hazards including, but not limited to, landslide scientists and practitioners. The map contains 112,674 polygons with average area of 0.38 km2, and is published in vector form. The map is accompanied by a selection of data including morphometric and thematic quantities. In addition to describing the rationale behind delineation of the polygonal map and selected data, we describe an application devoted to unsupervised terrain classification. We applied a
k-means clustering procedure with two strategies_ one at (coarser) basin scale, and one at (finer) slope unit scale. We show similarities and differences between the two classification strategies, highlighting the role of the slope unit subdivision in the two cases.
The role of morphology on the spatial distribution of short-duration rainfall extremes in Italy
P. Mazzoglio(1), I. Butera(1), M. Alvioli(2), P. Claps(1), 2022, The role of morphology on the spatial distribution of short-duration rainfall extremes in Italy,
Hydrology and earth system sciences (Online) 26 (2022): 1659–1672. doi_10.5194/hess-26-1659-2022,
DOI: 10.5194%2Fhess-26-1659-2022
Abstract
The dependence of rainfall on elevation has frequently been documented in the scientific literature and ...
The dependence of rainfall on elevation has frequently been documented in the scientific literature and may be relevant in Italy, due to the high degree of geographical and morphological heterogeneity of the country. However, a detailed analysis of the spatial variability of short-duration rainfall extremes and their connection to the landforms does not exist. Using a new, comprehensive and position-corrected rainfall extreme dataset (I2-RED), we present a systematic study of the relationship between geomorphological forms and the average of rainfall extremes (index rainfall) across the whole of Italy. We first investigated the dependence of sub-daily rainfall depths on elevation and other landscape indices through univariate and multivariate linear regressions. After analyzing the results, we repeated the analysis on geomorphological subdivisions of Italy. The results of the national-scale regression analysis did not confirm the assumption of elevation being the sole driver of the variability of rainfall extremes. The longitude, latitude, distance from the coastline, morphological obstructions and mean annual rainfall resulted to be significantly related to the index rainfall, and to play different roles for different durations (1- to 24-hours). However, when comparing the results of the best multivariate regression models with univariate regressions for morphological subdivisions, we found that "local" rainfall-topography relationships within the geomorphological subdivisions outperformed the country-wide multiple regressions and offered a reasonable representation of the effect of morphology on rainfall extremes.
A first attempt to evaluate the impact of agricultural practices on slope stability
Evelina Volpe 1, Stefano Luigi Gariano 1, Francesca Ardizzone 1, Federica Fiorucci 1, and Diana Salciarini 2, 2022, A first attempt to evaluate the impact of agricultural practices on slope stability,
EGU22 European Geosciences Union General Assembly 2022, Vienna, Austria, 23-17/05/2022,
Abstract
Shallow landslides induced by rainfall are very common movements that occur in hilly and mountainous ...
Shallow landslides induced by rainfall are very common movements that occur in hilly and mountainous areas causing losses of human life, ecological and environmental impacts and considerable economical costs. The predisposing factors for shallow landslides are represented by morphology, lithology, soil type, land cover, and land use, and their changes. Land use is constantly evolving because it is linked to human activities; the increase of population pressure and economic development forced more people to use all areas available. A lot of scientific contributions analyzed the positive effects of vegetation cover on slope stability, focusing on the mechanical effects of vegetation (both vegetation cover and roots) in terms of providing additional mechanical root reinforcement. Conversely, the effects of agricultural practices on slope stability conditions are poorly investigated. Indeed, while agriculture contributes positively to the landscape, biodiversity, climate and fires, on the other hand, improper agricultural practices and soil uses can modify the mechanical properties of the involved soils leading to a possible increase of instability phenomena.
To evaluate the effect of agricultural practices on the slope stability conditions, we present an application of a probabilistic, physically-based model for the triggering of rainfall-induced landslides (PG_TRIGRS - a probabilistic, geostatistic-based extension of the TRIGRS model) to the Collazzone area, a cultivated area located in Umbria, central Italy, characterized by a high susceptibility to landslides, which is studied and periodically monitored through systematic image analysis and on-site surveys.
The method applied in this research included the comparison between landslides observed in situ and the spatial distribution of the probability of failure derived from the application of PG_TRIGRS model, which models the study area in a GIS grid and treats each cell as an infinite slope. More in detail, a heuristic approach was adopted_ after a first run of the model with unbiased parameters, the slope stability analysis has been carried out assuming several percentages of reduction of the effective soil cohesion (c') to mimic an increasing impact of agricultural practices on the strength conditions.
A back-analysis methodology, with the support of sensitivity indices, was adopted to provide a preliminary quantitative evaluation of the effect induced by agricultural practices on the mechanical properties of the soil. To test the reliability of the method, standard contingency matrix and skill scores were adopted and the best compromise between correct and incorrect model outcomes was obtained considering a reduction of c' between 20% and 30%. In conclusion, we could estimate that in the analyzed area the agricultural practices can cause a 20 to 30% reduction in soil.
DEWS: a QGIS tool pack for the automatic selection of reference rain gauges for landslide-triggering rainfall thresholds
Omar F. Althuwaynee 1, Massimo Melillo 1, Stefano Luigi Gariano 1, Luigi Lombardo 2, Hyuck-Jin Park 3, Sang-Wan Kim 3, Paulo Hader 4, Meriame Mohajane 5, Renata Pacheco Quevedo 6, Filippo Catani 7, and Ali Aydda 8, 2022, DEWS: a QGIS tool pack for the automatic selection of reference rain gauges for landslide-triggering rainfall thresholds,
EGU2022 European Geosciences Union General Assembly 2022, Vienna, Austria, 23-27/05/2022,
Abstract
Several territorial landslide early warning systems in different parts of the world are based on ...
Several territorial landslide early warning systems in different parts of the world are based on empirical rainfall thresholds for landslide triggering. The calculation of such thresholds, using rainfall measurements gathered from rain gauges, has been examined frequently, especially considering uncertainties, modeling complexity, spatial assumptions, and analytical tools. Installed rain gauge networks that are spatially clustered in crowded areas have different spatial and attribute settings based on landslide occurrence conditions, such as rainfall record accessibility, processing, and usability, as well as specific locational, morphological, and hydrological settings.
In this research work, we introduce an automatic tool called DEWS (Distance, Elevation, Watershed, and Slope unit) for rainfall-induced landslide spatial reference rain gauge selection. DEWS can be considered supplementary and complementary to the CTRL-T tool (Calculation of Thresholds for Rainfall-induced Landslides Tool) developed earlier, and works on a macro-to-micro scale of the spatial components of CTRL-T rain gauge selections. The output information, i.e. the list of selected reference rain gauges, can be used as input for CTRL-T to calculate frequentist rainfall thresholds at different non-exceedance probabilities. The DEWS tool fills the gap of the current literature, where the selection of reference rain gauges is mostly based on the nearest distance location and on statistical or manual procedures, without considering the morphological and hydrological settings of the area in which landslides occurred.
The tool allows extracting rain gauges referring to landslide locations by employing four spatial filters_ F1 (Distance), F2 (Elevation), F3 (Watershed), F4 (Slope unit), needing only a DEM, the coordinates of landslide and rain gauge locations and the parameters of the filter's algorithms as inputs. More in detail, F1 selects rain gauges within a specified buffer distance from the landslide locations using the setting parameters and the coordinates of the landslides and rain gauges. Then, F2 uses the DEM to extract the elevation of the rain gauges and the landslides and then calculates the differences within each buffer circle; therefore, the filter keeps only the rain gauge with closest elevation values to each landslide (within F1 results) using the recommended/preferred/ or allowable elevation difference defined by the parameter's settings. In F3, the rain gauges falling in the watershed that contains the landslide locations are extracted (within F1 and F2 results). F4, which is the smallest and most focused filter, uses a previously developed tool pack (within F1, F2, and F3 results) to extract the slope units associated with each landslide. Consequently, only the rain gauges falling within these slope units are selected.
DEWS was implemented in a free tool pack in QGIS software, with default parameter values for non-expert users. The tool pack is divided into three main blocks following the filter structure (F1 and F2 are kept together). The reliability of DEWS was tested at a territorial scale in South Korea, using 223 landslides and 328 rain gauges. As a second step, frequentist rainfall thresholds were calculated in the study area.
A data-driven approach to establish prediction surfaces for rainfallinduced shallow landslides in South Tyrol, Italy
Stefan Steger1, Robin Kohrs1, Alice Crespi1, Mateo Moreno1,2, Peter James Zellner1, Jason Goetz3, Volkmar Mair4, Stefano Luigi Gariano5, Maria Teresa Brunetti5, Massimo Melillo5, Silvia Peruccacci5, and Massimiliano Pittore1, 2022, A data-driven approach to establish prediction surfaces for rainfallinduced shallow landslides in South Tyrol, Italy,
EGU2022 European Geosciences Union General Assembly 2022, Vienna, 23-27/05/2022,
Abstract
The occurrence of rainfall-induced shallow landslides is frequently caused by an interplay of predisposing environmental ...
The occurrence of rainfall-induced shallow landslides is frequently caused by an interplay of predisposing environmental factors and dynamic preparatory and triggering conditions. For large-area assessments and for regional early warning, event-based landslide inventories are often employed to establish critical rainfall thresholds using statistical procedures (e.g., non-exceedance probability curves). These approaches typically put the spotlight on rainfall conditions associated with known landslide occurrences. Not accounting for rainfall conditions that did not induce slope instability comes along with a variety of criticalities, such as the impossibility to discriminate landslide from non-landslide rainfall conditions or the difficulty to validate the results.
This contribution proposes a data-driven approach based on Generalized Additive Mixed Models (GAMM) to identify season-dependent shallow landslide rainfall conditions for the province of South Tyrol, Italy. The work builds upon high resolution gridded daily rainfall data and landslide observations for the period from 2000 to 2020. The workflow comprised an initial filtering of rainfall-induced landslides (presence data) and a rule-based stratified random sampling procedure to select non-landslide rainy days at the same locations (absence data). The time periods (time windows in days) to describe preparatory and triggering cumulative rainfall conditions were determined using an optimization procedure based on cross validation. In addition to modelling a yearly effect, a circular day-of-the-year variable was included in the model to consider additional seasonal influences. The underlying nested data structure (i.e., repeated measurements at each landslide location) was accounted for via a location-dependent random intercept. The resulting probability scores for the analysed variables were validated using space-time cross validation, visualized in the form of probability surface plots and complemented with quantitative thresholds (e.g., curves that optimally separate landslide presences and absences).
Validation of the model showed a high capability to distinguish the two groups (presence vs. absence observations). The results further indicate that the temporal prediction of shallow landslides in South Tyrol can be improved by accounting for systematic seasonal effects other than triggering and preparatory rainfall variables. This novel approach is flexible and will further be extended to derive space-time predictions. Strengths and limitations for regional landslide early warning will be discussed.
The research leading to these results are related to the Proslide project that received funding from the research program Research Südtirol/Alto Adige 2019 of the Autonomous Province of Bozen/Bolzano - Südtirol/Alto Adige.
Performance of satellite rainfall products for landslide prediction in India
M.T. Brunetti, M. Melillo, S.L. Gariano, L. Ciabatta, L. Brocca, Giriraj Amarnath, S. Peruccacci, 2022, Performance of satellite rainfall products for landslide prediction in India,
European Geophysical Union (EGU) 2022, Vienna, 23-27/05/2022,
Abstract
Landslides are among the most dangerous natural hazards, especially in developing countries. In these areas, ...
Landslides are among the most dangerous natural hazards, especially in developing countries. In these areas, where rain gauge networks are scarce, satellite rainfall products can be a viable alternative for landslide prediction. To date, only a few studies have investigated the capability and effectiveness of these products in regional-scale landslide prediction. We performed a comparative study on the reliability of ground-based rainfall products and satellite rainfall products for landslide prediction in India. We used a catalog of 197 rainfall-induced landslides over the 13-year period between April 2007 and October 2019. We calculated frequentist rainfall thresholds using GPM, SM2RAIN-ASCAT satellite products, and their merging, at daily and hourly temporal resolution, and ground-based data from the rainfall network of the Indian Meteorological Department (IMD) at daily resolution. The results indicate that satellite rainfall products outperform ground-based observations in the prediction of landslides due to their improved spatial (0.1° vs. 0.25°/pixel) and temporal (hourly vs. daily) resolutions. The best performance is achieved through the merging of GPM and SM2RAIN-ASCAT. These results open up the possibility for using satellite rainfall products in landslide early warning systems, particularly in poorly gauged areas.
Rainfall and landslide initiation
Fausto Guzzetti (1), Stefano Luigi Gariano (2), Silvia Peruccacci (2), Maria Teresa Brunetti (2), Massimo Melillo (2), 2022, Rainfall and landslide initiation,
, pp. 427–450. New York_ Elsevier, 2022,
Abstract
Capitolo sulle interazioni tra piogge e frane con specifici riferimenti ai modelli di previsione dell'innesco ...
Capitolo sulle interazioni tra piogge e frane con specifici riferimenti ai modelli di previsione dell'innesco delle frane, sia fisicamente basati che statistici. Particolari paragrafi dedicati alle soglie pluviometriche
Earthquake-triggered landslides susceptibility assessment by critical acceleration_ grid cells vs. slope units vs. ground-motion
Kaushal Gnyawali (1,2), Season Maharjan (2), Chong Xu (3), and Massimiliano Alvioli (4), 2022, Earthquake-triggered landslides susceptibility assessment by critical acceleration_ grid cells vs. slope units vs. ground-motion,
ICOSSAR 2021-2022,13th International Conference on Structural Safety & Reliability, Tongji University, Shanghai, Cina, 13-17 settembre 2022,
Abstract
Earthquake ground motion is the primary driver of earthquake-triggered landslides; however, their predictability is poor. ...
Earthquake ground motion is the primary driver of earthquake-triggered landslides; however, their predictability is poor. We use Newmark's critical acceleration method to map landslides triggered by the 2015 Gorkha earthquake in central Nepal. In this method, we compare the critical acceleration of a block (landslide pixel or slope unit) with the peak ground acceleration (PGA) to assess landslide susceptibility. We analyse earthquake-triggered landslide occurrence on each grid cell and each slope unit using two different sources of peak ground acceleration (from USGS ShakeMap and KTP seismic station). A total of four susceptibility maps were developed, which were compared with the existing landslide inventory of the 2015 Gorkha earthquake and validated using the Matthews correlation coefficient. Results from this study showed that the slope unit-based mapping using ShakeMap's PGA yields the best results. The landslide susceptibility map generated using this technique resembles well with the landslide inventory map and can be used for prioritizing rapid earthquake response, detailed investigations and planning.
Mass-Movements and Climate Change
Stefano Luigi Gariano (1), Fausto Guzzetti (1,2), 2022, Mass-Movements and Climate Change,
Treatise on Geomorphology, edited by John (Jack) F. Shroder, pp. 1–13. Amsterdam_ Elsevier, 2022,
Abstract
Although mass-movements can be caused by a variety of natural phenomena and human actions, in ...
Although mass-movements can be caused by a variety of natural phenomena and human actions, in most areas of the world rainfall is their primary trigger. An often-neglected complication of the operational forecasting of rainfall-induced landslides is global warming, in particular the related ongoing and expected changes in rainfall and temperature. The evaluation of the effects of the current and the projected climate change on the stability/instability conditions of natural and engineered slopes remains complicated.
In this chapter, we address the main questions related to the assessment of the impact of climate change on mass-movements. Starting from the results of a review of studies on the topic, we analyze and discuss how climate factors (and their changes) influence slope stability conditions and landslide hazard. This is not trivial, due to multiple reasons, including the fact that (i) the temporal and the geographical scales of climate and landslides are very different; (ii) different climate variables affect landslides; (iii) landslides are complex and diversified phenomena that respond differently to changes in climate.
Moreover, we outline the main research needs and we provide general and specific recommendations for the operational forecasting of rainfall-induced landslides considering the current and the expected changes in climate. In particular, a holistic approach is needed to understand and measure how climate variables and their variability affect mass-movements, and to provide useful projections that will allow effective short- and long-term actions to reduce landslide risk.
The International Soil Moisture Network_ Serving Earth system science for over a decade
Dorigo, Wouter; Himmelbauer, Irene; Aberer, Daniel; Schremmer, Lukas; Petrakovic, Ivana; Zappa, Luca; Preimesberger, Wolfgang; Xaver, Angelika; Annor, Frank; Ardö, Jonas; Baldocchi, Dennis; Bitelli, Marco; Blöschl, Günter; Bogena, Heye; Brocca, Luca; Calvet, Jean Christophe; Camarero, J. Julio; Capello, Giorgio; Choi, Minha; Cosh, Michael C.; Van De Giesen, Nick; Hajdu, Istvan; Ikonen, Jaakko; Jensen, Karsten H.; Kanniah, Kasturi Devi; De Kat, Ileen; Kirchengast, Gottfried; Kumar Rai, Pankaj; Kyrouac, Jenni; Larson, Kristine; Liu, Suxia; Loew, Alexander; Moghaddam, Mahta; Martínez Fernández, José; Mattar Bader, Cristian; Morbidelli, Renato; Musial, Jan P.; Osenga, Elise; Palecki, Michael A.; Pellarin, Thierry; Petropoulos, George P.; Pfeil, Isabella; Powers, Jarrett; Robock, Alan; Rüdiger, Christoph; Rummel, Udo; Strobel, Michael; Su, Zhongbo; Sullivan, Ryan; Tagesson, Torbern; Varlagin, Andrej; Vreugdenhil, Mariette; Walker, Jeffrey; Wen, Jun; Wenger, Fred; Wigneron, Jean Pierre; Woods, Mel; Yang, Kun; Zeng, Yijian; Zhang, Xiang; Zreda, Marek; DIetrich, Stephan; Gruber, Alexander; Van Oevelen, Peter; Wagner, Wolfgang; Scipal, Klaus; Drusch, Matthias; Sabia, Roberto, 2021, The International Soil Moisture Network_ Serving Earth system science for over a decade,
Hydrology and earth system sciences 25 (2021): 5749–5804. doi_10.5194/hess-25-5749-2021,
DOI: 10.5194%2Fhess-25-5749-2021
Abstract
In 2009, the International Soil Moisture Network (ISMN) was initiated as a community effort, funded ...
In 2009, the International Soil Moisture Network (ISMN) was initiated as a community effort, funded by the European Space Agency, to serve as a centralised data hosting facility for globally available in situ soil moisture measurements . The ISMN brings together in situ soil moisture measurements collected and freely shared by a multitude of organisations, harmonises them in terms of units and sampling rates, applies advanced quality control, and stores them in a database. Users can freely retrieve the data from this database through an online web portal (https://ismn.earth/en/, last access_ 28 October 2021). Meanwhile, the ISMN has evolved into the primary in situ soil moisture reference database worldwide, as evidenced by more than 3000 active users and over 1000 scientific publications referencing the data sets provided by the network. As of July 2021, the ISMN now contains the data of 71 networks and 2842 stations located all over the globe, with a time period spanning from 1952 to the present. The number of networks and stations covered by the ISMN is still growing, and approximately 70 % of the data sets contained in the database continue to be updated on a regular or irregular basis. The main scope of this paper is to inform readers about the evolution of the ISMN over the past decade, including a description of network and data set updates and quality control procedures. A comprehensive review of the existing literature making use of ISMN data is also provided in order to identify current limitations in functionality and data usage and to shape priorities for the next decade of operations of this unique community-based data repository.
A Review of Irrigation Information Retrievals from Space and Their Utility for Users
Massari, Christian; Modanesi, Sara; Dari, Jacopo; Gruber, Alexander; De Lannoy, Gabrielle J. M.; Girotto, Manuela; Quintana-Segui, Pere; Le Page, Michel; Jarlan, Lionel; Zribi, Mehrez; Ouaadi, Nadia; Vreugdenhil, Mariette; Zappa, Luca; Dorigo, Wouter; Wagner, Wolfgang; Brombacher, Joost; Pelgrum, Henk; Jaquot, Pauline; Freeman, Vahid; Volden, Espen; Prieto, Diego Fernandez; Tarpanelli, Angelica; Barbetta, Silvia; Brocca, Luca, 2021, A Review of Irrigation Information Retrievals from Space and Their Utility for Users,
Remote sensing (Basel) 13 (2021). doi_10.3390/rs13204112,
DOI: 10.3390%2Frs13204112
Abstract
Irrigation represents one of the most impactful human interventions in the terrestrial water cycle. Knowing ...
Irrigation represents one of the most impactful human interventions in the terrestrial water cycle. Knowing the distribution and extent of irrigated areas as well as the amount of water used for irrigation plays a central role in modeling irrigation water requirements and quantifying the impact of irrigation on regional climate, river discharge, and groundwater depletion. Obtaining high-quality global information about irrigation is challenging, especially in terms of quantification of the water actually used for irrigation. Here, we review existing Earth observation datasets, models, and algorithms used for irrigation mapping and quantification from the field to the global scale. The current observation capacities are confronted with the results of a survey on user requirements on satellite-observed irrigation for agricultural water resources' management. Based on this information, we identify current shortcomings of irrigation monitoring capabilities from space and phrase guidelines for potential future satellite missions and observation strategies.
The 63-year changes in annual streamflow volumes across Europe with a focus on the Mediterranean basin
Masseroni, Daniele; Camici, Stefania; Cislaghi, Alessio; Vacchiano, Giorgio; Massari, Christian; Brocca, Luca, 2021, The 63-year changes in annual streamflow volumes across Europe with a focus on the Mediterranean basin,
Hydrology and earth system sciences 25 (2021): 5589–5601. doi_10.5194/hess-25-5589-2021,
DOI: 10.5194%2Fhess-25-5589-2021
Abstract
Determining the spatiotemporal variability in the annual streamflow volume plays a relevant role in hydrology ...
Determining the spatiotemporal variability in the annual streamflow volume plays a relevant role in hydrology with regard to improving and implementing sustainable and resilient policies and practices of water resource management. This study investigates annual streamflow volume trends in a newly assembled, consolidated, and validated data set of daily mean river flow records from more than 3000 stations which cover near-natural basins in more than 40 countries across Europe. Although the data set contains streamflow time series from 1900 to 2013 in some stations, the statistical analyses were carried out by including observations from 1950 to 2013 in order to have a consistent and reliable data set over the continent. Trends were detected by calculating the slope of the Theil-Sen line over the annual anomalies of streamflow volume.
Closing the Water Cycle from Observations across Scales_ Where Do We Stand?
Dorigo, Wouter; Dietrich, Stephan; Aires, Filipe; Brocca, Luca; Carter, Sarah; Cretaux, Jean-Francois; Dunkerley, David; Enomoto, Hiroyuki; Forsberg, Rene; Guntner, Andreas; Hegglin, Michaela, I; Hollmann, Rainer; Hurst, Dale F.; Johannessen, Johnny A.; Kummerow, Christian; Lee, Tong; Luojus, Kari; Looser, Ulrich; Miralles, Diego G.; Pellet, Victor; Recknagel, Thomas; Vargas, Claudia Ruz; Schneider, Udo; Schoeneich, Philippe; Schroeder, Marc; Tapper, Nigel; Vuglinsky, Valery; Wagner, Wolfgang; Yu, Lisan; Zappa, Luca; Zemp, Michael; Aich, Valentin, 2021, Closing the Water Cycle from Observations across Scales_ Where Do We Stand?,
Bulletin of the American Meteorological Society 102 (2021): E1897–E1935. doi_10.1175/BAMS-D-19-0316.1,
DOI: 10.1175%2FBAMS-D-19-0316.1
Abstract
Life on Earth vitally depends on the availability of water. Human pressure on freshwater resources ...
Life on Earth vitally depends on the availability of water. Human pressure on freshwater resources is increasing, as is human exposure to weather-related extremes (droughts, storms, floods) caused by climate change. Understanding these changes is pivotal for developing mitigation and adaptation strategies. The Global Climate Observing System (GCOS) defines a suite of essential climate variables (ECVs), many related to the water cycle, required to systematically monitor Earth's climate system. Since long-term observations of these ECVs are derived from different observation techniques, platforms, instruments, and retrieval algorithms, they often lack the accuracy, completeness, and resolution, to consistently characterize water cycle variability at multiple spatial and temporal scales. Here, we review the capability of ground-based and remotely sensed observations of water cycle ECVs to consistently observe the hydrological cycle. We evaluate the relevant land, atmosphere, and ocean water storages and the fluxes between them, including anthropogenic water use. Particularly, we assess how well they close on multiple temporal and spatial scales. On this basis, we discuss gaps in observation systems and formulate guidelines for future water cycle observation strategies. We conclude that, while long-term water cycle monitoring has greatly advanced in the past, many observational gaps still need to be overcome to close the water budget and enable a comprehensive and consistent assessment across scales. Trends in water cycle components can only be observed with great uncertainty, mainly due to insufficient length and homogeneity. An advanced closure of the water cycle requires improved model-data synthesis capabilities, particularly at regional to local scales.
Landslide Hazard and Risk Assessment for Civil Protection Early Response
Giuseppe Esposito, Olga Petrucci, 2021, Landslide Hazard and Risk Assessment for Civil Protection Early Response,
Understanding and Reducing Landslide Disaster Risk, edited by Sassa Kyoji, Miko? Matja?, Sassa Shinji, Bobrowsky Peter T. , Takara Kaoru, Dang Khang, pp. 513–518. CH-6330 Cham (ZG): Springer International Publishing, 2021,
Abstract
This paper presents a series of severe landslide disasters occurred in Italy, during which the ...
This paper presents a series of severe landslide disasters occurred in Italy, during which the local scientific community supported civil protection authorities in the management of the emergency responses. Depending on the event characteristics, scientific support focused on landslide mapping, damage assessment, monitoring, early warning, and designing of countermeasures. Relevant studies, published after the disasters and describing these activities, highlight that, in case of major events, the scientific community can provide a significant support in decision-making processes and intervention strategies, by means of multi-disciplinary skills, experience and resources. The Italian example of cooperation between the scientific community and civil protection authorities here described highlights as a knowledge transfer from theoretical frameworks to practical applications can optimize the disaster response operations. Even if this study focuses on the Italian situation, it may represents a starting point to evaluate the real contribution provided by landslide experts in disaster responses worldwide, for understanding weaknesses and strengths. In many countries, in fact, local authorities are not able to provide timely and effective responses also because of a lacking or insufficient support of scientists.
A data-driven method for assessing the probability for terrain grid cells of initiating rockfalls on a large area
Massimiliano Alvioli, Michele Santangelo, Federica Fiorucci, Mauro Cardinali, Ivan Marchesini, Paola Reichenbach and Mauro Rossi, 2021, A data-driven method for assessing the probability for terrain grid cells of initiating rockfalls on a large area,
Geomorphometry 2021, Perugia, 13-17 settembre 2021,
Abstract
Rockfalls are one harmful kind of landslide, due to their
rapidity, destructive potential and high probability ...
Rockfalls are one harmful kind of landslide, due to their
rapidity, destructive potential and high probability of occurrence on
steep topographies, often found along transportation corridors.
Various factors can trigger rockfalls, including intense rainfall and
seismic activity, and diverse phenomena affect their occurrence, like
rock weathering and fracturing. Existing approaches for the
assessment of rockfall susceptibility range from purely
phenomenological to purely deterministic, physically based methods.
A common requirement for many approaches is the need to locate
the potential point locations of source areas, often located uphill on
cliffs. Application of a physically based model, in particular, allows
the calculation of material runout stemming from rockfalls
originating from such point locations. In this work, we propose a
method for the location of rockfall source points, on a digital
elevation model, suitable for large areas. We deem the method as
data-driven, because it relies on expert delineation of potential
source areas from Google Earth images in few sample locations,
representative of the study area at large. We measure the slope
distribution of grid cells encompassed by expert-mapped source
areas, and generalize the distribution of sources to the whole of the
study area. We apply the method to a corridor of about 17,000 km in
length and varying width, containing the entire Italian railway
network. The map of source areas represents the main input for a
physically based simulation of rockfall trajectories with the model
STONE, and likely of other similar physically based or
phenomenological models for rockfall runout assessment.
Physically based simulations of seismically induced rockfalls
M. Alvioli, 2021, Physically based simulations of seismically induced rockfalls,
Italy-Japan joint workshop on landslide monitoring systems and related topics, Perugia, 4-5 novembre 2021,
Abstract
Three-dimensional model for rockfalls
Assumes point-like boulders
Simulates trajectories from
user-defined starting points
Trajectories ...
Three-dimensional model for rockfalls
Assumes point-like boulders
Simulates trajectories from
user-defined starting points
Trajectories are a sequence of falling, bouncing, rolling states
Boulders stop when kinetic energy is exhausted by friction
Input_ digital elevation model (here, 10 m national DEM, 300,000 km2)
Ancillary data_ terrain geological/lithological information
=> terrain parameters (friction coefficient, normal & tangential restitution)
Rockfall susceptibility and seismically induced rockfall susceptibility at regional and national scale
Massimiliano Alvioli+, F. Mori §, A. Mendicelli §, M. Rossi +, M. Moscatelli §, I. Marchesini +, P. Reichenbach +, 2021, Rockfall susceptibility and seismically induced rockfall susceptibility at regional and national scale,
Il contributo del CNR IRPI al sistema paese per la mitigazione dei rischi geo idrologici, Roma, 25-26 novembre 2021,
Abstract
Three-dimensional model for rockfalls
Assumes point-like boulders
Simulates trajectories from user-defined starting points
Simulated trajectories_ ...
Three-dimensional model for rockfalls
Assumes point-like boulders
Simulates trajectories from user-defined starting points
Simulated trajectories_ falling, bouncing, rolling
Boulders stop when kinetic energy is exhausted by friction
Input_ digital elevation model
(here, 10 m national DEM, 300,000 km2)
Ancillary data_ terrain geological/lithological information
=> terrain parameters (friction, restitution coefficients)
=> Usually applied at slope/catchment scale with static sources (susceptibility maps)
=> We run STONE at national scale, and select sources dynamically (specific trigger)
Exploring event landslide mapping using Sentinel-1 SAR backscatter products
Michele Santangelo, Mauro Cardinali, Francesco Bucci, Federica Fiorucci, Alessandro Cesare Mondini, 2021, Exploring event landslide mapping using Sentinel-1 SAR backscatter products,
Geomorphology (Amst.) (2021). doi_10.1016/j.geomorph.2021.108021,
DOI: 10.1016%2Fj.geomorph.2021.108021
Abstract
Landslides triggered by meteorological phenomena occur worldwide and cause extensive and severe damages to properties, ...
Landslides triggered by meteorological phenomena occur worldwide and cause extensive and severe damages to properties, and life loss. Detailed maps of event landslides can sensibly shorten emergency response time, possibly resulting in reduced death tolls. In most cases, however, optical post-event images are not always available right after the event, due to dense cloud cover. Since Synthetic Aperture Radar (SAR) sensors overcome the limitation of cloud cover, in this work we explore the use of C-band Sentinel-1 SAR amplitude images to map event landslides. A team of four expert photo-interpreters first defined interpretation criteria of SAR amplitude post-event images of the backscatter coefficient (??) and of the derived images of change. The same team mapped two large event landslides occurred in Villa Santa Lucia (Chile) and Tonzang (Myanmar). Maps were prepared on a total of 72 images for the Chile test case and 54 for the Myanmar test case. Images included VV (vertical transmit, vertical receive) and VH (vertical transmit, horizontal receive) polarisation, ascending and descending orbits, multilook processing, adaptive and moving window filters, post-event images and images of change. In the first case, interpreters were asked to map the event landslide on an optical post-event image before mapping on SAR images, whereas in Myanmar it was done in the end. Results were quantitatively compared to the maps prepared on post-event optical images, assumed as benchmark. Results revealed a good agreement between the SAR-derived maps and the benchmark. Locally, errors can be due to geometrical distortions, and speckling-like effects. Also polarisation plays an important role, as opposed to filtering. Despite the preliminary nature of this study, it proved that SAR amplitude derived products are suitable to prepare accurate maps of large event landslides, and that they should be further tested to prepare event inventories.
Capability of remote sensing images to distinguish the urban surface materials_ A case study of venice city
Rosa Maria Cavalli, 2021, Capability of remote sensing images to distinguish the urban surface materials_ A case study of venice city,
Remote sensing (Basel) 13 (2021): 1–29. doi_10.3390/rs13193959,
DOI: 10.3390%2Frs13193959
Abstract
Many countries share an effort to understand the impact of growing urban areas on the ...
Many countries share an effort to understand the impact of growing urban areas on the environment. Spatial, spectral, and temporal resolutions of remote sensing images offer unique access to this information. Nevertheless, their use is limited because urban surface materials exhibit a great diversity of types and are not well spatially and spectrally distinguishable. This work aims to quantify the effect of these spatial and spectral characteristics of urban surface materials on their retrieval from images. To avoid other sources of error, synthetic images of the historical center of Venice were analyzed. A hyperspectral library, which characterizes the main materials of Venice city and knowledge of the city, allowed to create a starting image at a spatial resolution of 30 cm and spectral resolution of 3 nm and with a spectral range of 365-2500 nm, which was spatially and spectrally resampled to match the characteristics of most remote sensing sensors. Linear spectral mixture analysis was applied to every resampled image to evaluate and compare their capabilities to distinguish urban surface materials. In short, the capability depends mainly on spatial resolution, secondarily on spectral range and mixed pixel percentage, and lastly on spectral resolution; impervious surfaces are more distinguishable than pervious surfaces. This analysis of capability behavior is very important to select more suitable remote sensing images and/or to decide the complementarity use of different data.
Evaluating three non-gauge-corrected satellite precipitation estimates by a regional gauge interpolated dataset over Iran
Eini, Mohammad Reza; Olyaei, Mohammad Ali; Kamyab, Taraneh; Teymoori, Javad; Brocca, Luca; Piniewski, Miko?aj, 2021, Evaluating three non-gauge-corrected satellite precipitation estimates by a regional gauge interpolated dataset over Iran,
Journal of Hydrology_ Regional Studies 38 (2021). doi_10.1016/j.ejrh.2021.100942,
DOI: 10.1016%2Fj.ejrh.2021.100942
Abstract
Study region_ Iran has about 1.648 million km, is placed between 44° and 64° E ...
Study region_ Iran has about 1.648 million km, is placed between 44° and 64° E and 25-40° N in the southwest of the Middle East and North Africa. It is characterized by a tough precipitation gradient with a mean annual precipitation of 250 mm, concentrating primarily during the wet months (January to April). Study focus_ In this study, we evaluated the performance of three non-gauge-corrected satellite precipitation estimates and a linear combination of these products (SPC) versus the Asfezari (Iran national reanalysis dataset) using four continuous statistics (R, NSE, RMSE, and BIAS) and three categorical metrics (POD, FAR, and CSI). New hydrological insights for the region_ The foremost issue for hydrologists in Iran, and many other developing countries, is off-line rainfall data without near real-time availability. For this reason, researchers are using satellite products. These gridded datasets have their benefits and drawbacks with regard to their resolution, time span, time steps, and accuracy. Therefore, testing the quality of gridded datasets is the primary step of using them in hydrological assessments. Current research compares the satellite products with a national gridded dataset (Asfezari) over Iran for the first time. Overall, the SPC dataset had better accuracy than other datasets. Then SM2RAIN-ASCAT showed better accuracy than PERSIANN-CCS and CMORPH in both statistical accuracy and detection.
Assessment of bottom-up satellite rainfall products on estimating river discharge and hydrologic signatures in Brazilian catchments
Almagro, André; Oliveira, Paulo Tarso Sanches; Brocca, Luca, 2021, Assessment of bottom-up satellite rainfall products on estimating river discharge and hydrologic signatures in Brazilian catchments,
Journal of hydrology (Amst.) 603 (2021). doi_10.1016/j.jhydrol.2021.126897,
DOI: 10.1016%2Fj.jhydrol.2021.126897
Abstract
Satellite rainfall products are one of the most valuable tools for water resources monitoring in ...
Satellite rainfall products are one of the most valuable tools for water resources monitoring in data-scarce regions, due to their low latency and quasi-global range. However, there are still uncertainties associated with rainfall products performance used to estimate hydrologic signatures in several regions, such as Brazil. Here, we investigate the performance of three rainfall products in estimating daily precipitation, daily river discharge, and hydrologic signatures over Brazil_ the SM2RAIN-ASCAT and the GPM+SM2RAIN satellite products, and the ERA5 reanalysis product. We used a subset of 520 catchments from the Catchments Attributes for Brazil (CABra) dataset and the hydrologic modeling was carried out using the MISDc hydrologic model. Satellite-based products performed better than ERA5 for most Brazilian biomes in estimating daily precipitation when compared with ground observations used as reference. Daily river discharge was also better modeled with SM2RAIN-ASCAT and GPM+SM2RAIN. Hydrologic modeling presented low values of bias and >80% of catchments with KGE > 0.5 in calibration. Lastly, hydrologic signatures were well estimated by SM2RAIN-ASCAT and GPM+SM2RAIN, and for some biomes (Atlantic Forest, Cerrado, and Caatinga) they are better predictors than ground-based observations. We showed that there is a significant added value when using SM2RAIN-ASCAT and GPM+SM2RAIN products in tropical catchments, allowing a high-quality continuous water resources monitoring even in data-scarce regions. Besides, our findings pave the way for a better understanding of hydrologic extremes (droughts and floods) using these satellite rainfall products on multiple spatial and temporal scales.
Toward a self-calibrated and independent SM2RAIN rainfall product
Filippucci, Paolo; Brocca, Luca; Massari, Christian; Saltalippi, Carla; Wagner, Wolfgang; Tarpanelli, Angelica, 2021, Toward a self-calibrated and independent SM2RAIN rainfall product,
Journal of hydrology (Amst.) 603 (2021). doi_10.1016/j.jhydrol.2021.126837,
DOI: 10.1016%2Fj.jhydrol.2021.126837
Abstract
Rainfall monitoring is fundamental in many hydrological applications such as flood and landslide forecasting and ...
Rainfall monitoring is fundamental in many hydrological applications such as flood and landslide forecasting and water resources management. In-situ measurements are the traditional data source of rainfall, but the worldwide declining number of stations, their low spatial representativeness and the data access problem limit their use. Satellite products are being widely used as an alternative data source. Among them, SM2RAIN-based products, which exploit the inversion of the water balance equation to derive rainfall from soil moisture observations, have shown relatively good skills for hydrological applications. However, the need of calibrating the SM2RAIN parameter values against a reference represents one important limitation, particularly over data scarce regions. In this study, we explore the possibility to self-calibrate SM2RAIN and thus to obtain rainfall estimates from the Advanced SCATterometer (ASCAT) soil moisture independently from any reference rainfall dataset. Four parametric relationships relating SM2RAIN parameter values to static descriptors (average rainfall, topography, soil moisture noise) are developed. To develop such relationships, a sample of 1009 points uniformly distributed over the areas covered by rain gauges in Australia, India, Italy and the United States is selected. A global validation of the methodology is conducted by comparing the performances of the parameterized product with the classical product in which the parameter values are estimated by calibration against a reference rainfall dataset. The Final Run of the Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (IMERG) precipitation dataset is used for performance assessment, together with the triple collocation techniques by using the Gauge-based Global Precipitation Climatology Center (GPCC) product and the Late Run of IMERG. The aim of the analysis is to obtain an uncalibrated SM2RAIN methodology to retrieve rainfall whose performance are similar to those obtained with calibration. The results at 1009 points show that the performances of the parameterized SM2RAIN product are in line with those of the calibrated one, with an increased capability in the detection of intense rainfall events and an acceptable reduction of the performance according to both Pearson Correlation and Root Mean Square Error indexes. The application of triple collocation confirms these findings on a global scale, showing that the SM2RAIN product outperforms both GPCC and IMERG -- Late run estimations in areas characterized by low density of rain gauges and good quality of ASCAT soil moisture retrievals (i.e., Africa and South America).
Performance evaluation of long ndvi timeseries from avhrr, modis and landsat sensors over landslide-prone locations in qinghai-tibetan plateau
Sajadi, Payam; Sang, Yan Fang; Gholamnia, Mehdi; Bonafoni, Stefania; Brocca, Luca; Pradhan, Biswajeet; Singh, Amit, 2021, Performance evaluation of long ndvi timeseries from avhrr, modis and landsat sensors over landslide-prone locations in qinghai-tibetan plateau,
Remote sensing (Basel) 13 (2021). doi_10.3390/rs13163172,
DOI: 10.3390%2Frs13163172
Abstract
The existence of several NDVI products in Qinghai-Tibetan Plateau (QTP) makes it challenging to identify ...
The existence of several NDVI products in Qinghai-Tibetan Plateau (QTP) makes it challenging to identify the ideal sensor for vegetation monitoring as an important factor for landslide detection studies. A pixel-based analysis of the NDVI time series was carried out to compare the performances of five NDVI products, including ETM+, OLI, MODIS Series, and AVHRR sensors in QTP. Harmonic analysis of time series and wavelet threshold denoising were used for reconstruction and denoising of the five NDVI datasets. Each sensor performance was assessed based on the behavioral similarity between the original and denoised NDVI time series, considering the preservation of the original shape and time series values by computing correlation coefficient (CC), mean absolute error (MAE), root mean square error (RMSE), and signal to noise ratio (SNR). Results indicated that the OLI slightly outperformed the other sensors in all performance metrics, especially in mosaic natural vegetation, grassland, and cropland, providing 0.973, 0.015, 0.022, and 27.220 in CC, MAE, RMSE, and SNR, respectively. AVHRR showed similar results to OLI, with the best results in the predominant type of land covers (needle-leaved, evergreen, closed to open). The MODIS series performs lower across all vegetation classes than the other sensors, which might be related to the higher number of artifacts observed in the original data. In addition to the satellite sensor comparison, the proposed analysis demonstrated the effectiveness and reliability of the implemented methodology for reconstructing and denoising different NDVI time series, indicating its suitability for long-term trend analysis of different natural land cover classes, vegetation monitoring, and change detection.
The impact of probability density functions assessment on model performance for slope stability analysis
Volpe, Evelina; Ciabatta, Luca; Salciarini, Diana; Camici, Stefania; Cattoni, Elisabetta; Brocca, Luca, 2021, The impact of probability density functions assessment on model performance for slope stability analysis,
Geosciences (Basel) 11 (2021). doi_10.3390/geosciences11080322,
DOI: 10.3390%2Fgeosciences11080322
Abstract
The development of forecasting models for the evaluation of potential slope instability after rainfall events ...
The development of forecasting models for the evaluation of potential slope instability after rainfall events represents an important issue for the scientific community. This topic has received considerable impetus due to the climate change effect on territories, as several studies demonstrate that an increase in global warming can significantly influence the landslide activity and stability conditions of natural and artificial slopes. A consolidated approach in evaluating rainfall-induced landslide hazard is based on the integration of rainfall forecasts and physically based (PB) predictive models through deterministic laws. However, considering the complex nature of the processes and the high variability of the random quantities involved, probabilistic approaches are recommended in order to obtain reliable predictions. A crucial aspect of the stochastic approach is represented by the definition of appropriate probability density functions (pdfs) to model the uncertainty of the input variables as this may have an important effect on the evaluation of the probability of failure (PoF). The role of the pdf definition on reliability analysis is discussed through a comparison of PoF maps generated using Monte Carlo (MC) simulations performed over a study area located in the Umbria region of central Italy. The study revealed that the use of uniform pdfs for the random input variables, often considered when a detailed geotechnical characterization for the soil is not available, could be inappropriate.
Assimilation of satellite soil moisture products for river flow prediction_ An extensive experiment in over 700 catchments throughout europe
De Santis, D.; Biondi, D.; Crow, W. T.; Camici, S.; Modanesi, S.; Brocca, L.; Massari, C., 2021, Assimilation of satellite soil moisture products for river flow prediction_ An extensive experiment in over 700 catchments throughout europe,
Water resources research 57 (2021). doi_10.1029/2021WR029643,
Abstract
In this study, we perform a data assimilation (DA) experiment on a very large number ...
In this study, we perform a data assimilation (DA) experiment on a very large number (>700) of small-and medium-scale (150-10,000 km) European catchments to assess the impact of satellite soil moisture (SM) DA on streamflow simulations for different climatic and hydrologic conditions. In the experiment, Climate Change Initiative SM active, passive and combined products are assimilated over a time period 2003-2016 via an Ensemble Kalman Filter (EnKF). The results show that, on average, the assimilation of the three products provides relatively small improvements as compared to analogous open loop (OL) results (i.e., with an increase on median Kling-Gupta Efficiency equal to 0.0048, 0.0033, and 0.0022 [-] for the active, the passive, and the combined products, respectively). OL performance itself is found to be a significant driver of the assimilation results_ greater improvements are observed in catchments with poor OL streamflow predictions and inaccurate precipitation estimates. The remotely sensed product accuracy also emerges as relevant for assimilation efficiency, while factors affecting SM retrievals such as vegetation density, topographic complexity and basin area are found to have only a limited impact on the spatial pattern of performance. Small and detrimental effects of SM assimilation are observed over fully humid catchments and at high latitudes where pre-storm soil moisture has reduced control on runoff generation as well as in basins where the hydrological model contains structural limitations.
Assessment of earthquake-induced landslide inventories and susceptibility maps using slope unit-based logistic regression and geospatial statistics
B. Pokharel(1), M. Alvioli(2), S. Lim(1), 2021, Assessment of earthquake-induced landslide inventories and susceptibility maps using slope unit-based logistic regression and geospatial statistics,
Scientific reports (Nature Publishing Group) (2021). doi_10.1038/s41598-021-00780-y,
DOI: 10.1038%2Fs41598-021-00780-y
Abstract
Inventories of seismically induced landslides provide essential information about the extent and severity of ground ...
Inventories of seismically induced landslides provide essential information about the extent and severity of ground effects after an earthquake. Rigorous assessment of the completeness of a landslide inventory and the quality of a landslide susceptibility map derived from the inventory is of paramount importance for disaster management applications. Methods and materials applied while preparing inventories influence their quality, but the criteria for generating an inventory are not standardized. This study considered five landslide inventories prepared by different authors after the 2015 Gorkha earthquake, to assess their differences, understand the implications of their use in producing landslide susceptibility maps in conjunction with standard landslide predisposing factors and logistic regression. We adopted three assessment criteria_ 1) an error index to identify the mutual mismatches between the inventories; 2) statistical analysis, to study the inconsistency in predisposing factors and performance of susceptibility maps; and 3) geospatial analysis, to assess differences between the inventories and the corresponding susceptibility maps. Results show that substantial discrepancies exist among the mapped landslides. Although there is no distinct variation in the significance of landslide causative factors and the performance of susceptibility maps, a hot spot analysis and cluster/outlier analysis of the maps revealed notable differences in spatial patterns. The percentages of landslide-prone hot spots and clustered areas are directly proportional to the size of the landslide inventory. The proposed geospatial approaches provide a new perspective to the investigators for the quantitative comparisons of earthquake-triggered landslide inventories and susceptibility maps.
Aggiornamento della validazione delle previsioni del SARF Sardegna
Stefano Luigi Gariano, Massimo Melillo, Maria Teresa Brunetti, Silvia Peruccacci, Mauro Rossi, Ivan Marchesini, Cinzia Bianchi, Barbara Denti, 2021, Aggiornamento della validazione delle previsioni del SARF Sardegna,
2021,
Abstract
Il presente documento contiene la definizione delle procedure per la validazione del sistema SARF Sardegna. ...
Il presente documento contiene la definizione delle procedure per la validazione del sistema SARF Sardegna. Le attività qui riportate sono state realizzate nell'ambito delle Modifiche all'Estensione dell'Accordo di Collaborazione tra la Direzione Generale della Protezione Civile della Regione Autonoma della Sardegna servizio previsione rischi e dei sistemi informativi, infrastrutture e reti e il Consiglio Nazionale delle Ricerche, Istituto di Ricerca per la Protezione Idrogeologica (CNR IRPI) per la "Sperimentazione, validazione e sviluppo del Sistema di Allertamento Regionale per la previsione di Frane pluvio-indotte in Sardegna (SARF Sardegna)".
Il rapporto rappresenta la prima valutazione delle prestazioni del SARF Sardegna per la previsione di frane pluvio-indotte sul territorio regionale da aprile 2020 a febbraio 2021. Tale attività ha riguardato la raccolta e l'uso di informazioni sull'occorrenza di frane pluvio-indotte sul territorio regionale e l'implementazione di procedure per il confronto delle previsioni del SARF Sardegna con l'occorrenza di frane nei giorni successivi, nel periodo di validità delle previsioni stesse.
Il presente documento è suddiviso in quattro capitoli. Il Capitolo 1 contiene un'introduzione ai contenuti del documento. Nel Capitolo 2 sono descritti i dati utilizzati nella procedura di validazione del SARF Sardegna, mentre nel Capitolo 3 è descritta la procedura di validazione stessa. Il Capitolo 4 riporta le schede di validazione e un'analisi complessiva della capacità predittiva del sistema sulla base dei risultati della validazione.
Advances in Geomorphometry
M. Alvioli(1), I. Marchesini(1), L.Melelli(2), P. Guth(3), 2021, Advances in Geomorphometry,
Transactions in GIS (Online) 25 (2021): 1–5. doi_10.1111/tgis.12859,
DOI: 10.1111%2Ftgis.12859
Description of a complex, rainfall-induced landslide within a multi-stage three-dimensional model
T.V. Tran(1), M. Alvioli(2), V.H. Hong(1), 2021, Description of a complex, rainfall-induced landslide within a multi-stage three-dimensional model,
Natural hazards (Dordr.) 110 (2021): 1953–1968. doi_10.1007/s11069-021-05020-0,
DOI: 10.1007%2Fs11069-021-05020-0
Abstract
The mechanical processes involved in movements of earth or rock masses under the effect of ...
The mechanical processes involved in movements of earth or rock masses under the effect of gravity - a landslide - may include several phases where the failure of one portion of terrain can lead to the instability of the surrounding parts. An earlier landslide might have follow-up landslides until the landscape finds the equilibrium state. Soon thereafter, recurring landslides are often recorded in landslide inventories but are seldom exploited in physical landslide modeling. Here, we study the landslide mechanism using Scoops3D - a three-dimensional, physically based landslide model. The program employs the three-dimensional column limit equilibrium and a digital elevation model to perform a slope stability analysis. Scoops3D evaluates the stability of rotational, spherical slip surfaces encompassing many grid cells, producing the least-stable sliding surface throughout the entire digital landscape. The program creates two important outputs, namely a factor of safety map and a terrain map showing the new topographical conditions of the site with unstable areas removed. To define the final predicted landslide boundary, we have run Scoops3D repeatedly to assess the site's stability using a newly produced terrain profile until the model predicts as stable all of the grid cells within the entire landscape. We compared the method's prediction with the actual sliding scar that took place on August 05th, 2019, following a historical rainstorm in Sapa - Vietnam. Results for modified success rate, a performance metric, show that with reliable input data, the approach can predict the evolution of landslides with improved results compared to the traditional method using Scoops3D.
Rockfall susceptibility and network-ranked susceptibility along the Italian railway
Alvioli M.; Santangelo M.; Fiorucci F.; Cardinali M.; Marchesini I.; Reichenbach P.; Rossi M.; Guzzetti F.; Peruccacci S., 2021, Rockfall susceptibility and network-ranked susceptibility along the Italian railway,
Engineering geology 293 (2021): 106301–106301. doi_10.1016/j.enggeo.2021.106301,
DOI: 10.1016%2Fj.enggeo.2021.106301
Abstract
Rockfalls pose a substantial threat to ground transportation, due to their rapidity, destructive potential and ...
Rockfalls pose a substantial threat to ground transportation, due to their rapidity, destructive potential and high probability of occurrence on steep topographies, often found along roads and railway routes. Approaches for the assessment of rockfall susceptibility range from purely phenomenological methods and statistical methods, suitable for modeling large areas, to purely deterministic ones, usually easier to use in local analyses. A common requirement is the need to locate potential detachment points, often found uphill on cliffs, and the subsequent assessment of the runout areas of rockfalls stemming from such points. Here, we apply a physically based model for the calculation of rockfall trajectories along the whole Italian railway network, within a corridor of total length of about 17,000 km and varying width. We propose a data-driven method for the location of rockfall source points based on expert mapping of potential source areas on sample representative locations. Using empirical distributions of gridded slope angle values in source areas mapped by experts, we derived probabilistic maps of rockfall sources in the proximity of the railway network, regardless of a particular trigger. Source areas act as starting points of simulated trajectories within the three-dimensional model STONE. The program provides a pixel-by-pixel trajectory count, covering 24,500 km and representing the largest homogeneous application of the model to date. We classified the raster map into a vector susceptibility map, analyzing the railway track as a collection of segments, for which we provide segment-wise rockfall susceptibility. Eventually, we considered an equivalent graph representation of the network, which helps classifying the segments both on the basis of rockfall susceptibility and the role of each segment in the network, resulting in a network-ranked susceptibility. Both maps are useful for subsequent hazard assessment, and to prioritize safety improvements along the railway, at national scale.
The response of calcareous plankton to the Sapropel S1 interval in North Ionian Sea
Antonio Cascella a,*, Sergio Bonomo a, b, Fabrizio Lirer c, Giulia Margaritelli d, Helena Checa e, Isabel Cacho e, Leopoldo D. Pena e, Jaime Frigola e, 2021, The response of calcareous plankton to the Sapropel S1 interval in North Ionian Sea,
Global and planetary change (Print) (2021). doi_10.1016/j.gloplacha.2021.103599,
DOI: 10.1016%2Fj.gloplacha.2021.103599
Abstract
A high resolution study of calcareous nannofossils has been performed on samples from the Sapropel ...
A high resolution study of calcareous nannofossils has been performed on samples from the Sapropel S1interval deposited in the North Ionian Sea, with the aim to assess the paleoenvironmental changes in the photic zone during this crucial interval in Mediterranean circulation. Calcareous nannofossil data have been integrated with planktonic foraminiferal data recently published in Checa et al. (2020) from which the paleoclimatic curve has been constructed.
Placoliths (namely Emiliania huxleyi) and Florisphaera profunda distributions, along with that of planktonic foraminifer Globigerinoides ruber white, evidence that, after a progressive weakening of surface water mixing, a deep chlorophyll maximum developed just prior to the sapropel deposition. We suggest that these changes took place as a response to enhanced precipitation conditions and riverine discharge as testified by increasing trend of reworked coccoliths and the occurrence of lower salinity taxon Braarudosphaera bigelowii. Calcareous nannofossils also point out that the oceanographic (water column stratification, reduced bottom water ventilation) and biogeochemical (increased primary production) processes that occurred during the S1 formation were particularly dominant during the earliest part of the older S1 warm phase (S1a). Our results support than some re-ventilation events of the shallow depth of studied site (665 m) occurred to some extent, particularly during the final phases of S1a.
The distribution of holococcoliths, more abundant during the cold interruption phase Si, seems confirm that the preservation of these tiny coccoliths, highly susceptible to dissolution, is enhanced under seafloor re-ventilation conditions.
Finally, we tentatively suggest that preservation also plays a significant role in the distribution of the warm upper photic zone taxa, particularly during the warm S1b interval.
The Joint IPWG
R. Roca, Z.S. Haddad, F.F. Akimoto, L. Alexander, A. Behrangi, G. Huffman, S. Kato, C. Kidd, P.E. Kirstetter, T. Kubota, C. Kummerow, T.S. L'Ecuyer, V. Levizzani, V. Maggioni, C. Massari, H. Masunaga, M. Schröder, F.J. Tapiador, F.J. Turk, N. Utsumi, 2021, The Joint IPWG,
2021,
Abstract
This report is a result of an interesting journey that originated in discussions between Rémy ...
This report is a result of an interesting journey that originated in discussions between Rémy Roca, chair of Global Energy and Water Exchanges (GEWEX) Data and Analysis Panel (GDAP), and Ziad Haddad, chair of International Precipitation Working Group (IPWG), during visits to Toulouse and to Pasadena as well as during many of the various workshops and conferences dedicated to precipitation. It culminated in the present report built from contributions by more than 20 scientists from all over the world. The first written draft was completed immediately following an open meeting for interested contributors that took place on a Saturday morning in a public library in the heights of San Diego (Haddad and Roca, 21 October 2017). From this initial plan, many objectives were successfully achieved without modification, while a few required maturation before we were able to include them in the completed assessment, all of this in spite of the ongoing pandemic. The current report completes the GEWEX assessment portfolio and follows the previous IPWG assessment by 10+ years (Gruber and Levizzani, 2008). Hopefully it is the first of a more frequent and regular series of precipitation assessments.
Assessing two methods to define rainfall intensity and duration thresholds for shallow landslides in data-scarce catchments of the Colombian Andean Mountains
Roberto J. Marin(a,b), María Fernanda Velásquez (a,b), Edwin F. García (b), Massimiliano Alvioli (c), Edier Aristizábal (d), 2021, Assessing two methods to define rainfall intensity and duration thresholds for shallow landslides in data-scarce catchments of the Colombian Andean Mountains,
Catena (Cremling.) 206 (2021): 105563. doi_10.1016/j.catena.2021.105563,
DOI: 10.1016%2Fj.catena.2021.105563
Abstract
Rainfall thresholds are intensity-duration relations supposedly able to distinguish precipitation events that may or may ...
Rainfall thresholds are intensity-duration relations supposedly able to distinguish precipitation events that may or may not trigger landslides. The most common method for defining rainfall thresholds relies on observed landslides and the corresponding values of rainfall intensity and duration that caused each failure. Alternative methods to define rainfall thresholds, using physically-based models, recently gained importance, as they may provide complementary information to other methods. Still, their applicability in most of the world's regions, including the Colombian Andes' mountainous basins, has not been demonstrated or validated. In this study, we evaluated the applicability of the physically-based model TRIGRS to define rainfall intensity and duration thresholds in individual basins from the Colombian Andes. We obtained rainfall thresholds using two different methods and compared them with landslide-triggering rainfall events in two distinct basins, namely La Arenosa and La Liboriana. Furthermore, we used a (presumably incomplete) landslide database from Medellín to rebuild the rainfall events associated with individual landslides and compared them with the physically-based thresholds. The rainfall thresholds calculated in the three study areas and the applicability of the methods in data-scarce environments were assessed. Results showed that both methods for defining rainfall intensity and duration thresholds have merits and represent potential tools to improve or complement landslide early warning systems, especially in data-scarce regions.
Satellite rainfall products outperform ground observations for landslide prediction in India
Maria Teresa Brunetti1, Massimo Melillo1, Stefano Luigi Gariano1, Luca Ciabatta1, Luca Brocca1, Giriraj Amarnath2, and Silvia Peruccacci1, 2021, Satellite rainfall products outperform ground observations for landslide prediction in India,
Hydrology and earth system sciences 25 (2021): 3267–3279. doi_10.5194/hess-25-3267-2021,
DOI: 10.5194%2Fhess-25-3267-2021
Abstract
Landslides are among the most dangerous natural hazards, particularly in developing countries, where ground observations ...
Landslides are among the most dangerous natural hazards, particularly in developing countries, where ground observations for operative early warning systems are lacking. In these areas, remote sensing can represent an important detection and monitoring process to predict landslide occurrence in space and time, particularly satellite rainfall products that have improved in terms of accuracy and resolution in recent times. Surprisingly, only a few studies have investigated the capability and effectiveness of these products in landslide prediction in reducing the impact of this hazard on the population.
We have performed a comparative study of ground- and satellite-based rainfall products for landslide prediction in India by using empirical rainfall thresholds derived from the analysis of historical landslide events. Specifically, we have tested Global Precipitation Measurement (GPM) and SM2RAIN-ASCAT satellite rainfall products, and their merging, at daily and hourly temporal resolution, and Indian Meteorological Department (IMD) daily rain gauge observations. A catalogue of 197 rainfall-induced landslides that occurred throughout India in the 13-year period between April 2007 and October 2019 has been used.
Results indicate that satellite rainfall products outperform ground observations thanks to their better spatial (0.1? vs. 0.25?) and temporal (hourly vs. daily) resolutions. The better performance is obtained through the merged GPM and SM2RAIN-ASCAT products, even though improvements in reproducing the daily rainfall (e.g. overestimation of the number of rainy days) are likely needed. These findings open a new avenue for using such satellite products in landslide early warning systems, particularly in poorly gauged areas.
Using satellite rainfall products to assess the triggering conditions for hydro-morphological processes in different geomorphological settings in China
Nan Wang (a,b), Luigi Lombardo (c), Stefano Luigi Gariano (d), Weiming Cheng (a,b,e,f), Changjun Liu (g), Junnan Xiong (a,h), Ruibo Wang (a), 2021, Using satellite rainfall products to assess the triggering conditions for hydro-morphological processes in different geomorphological settings in China,
International journal of applied earth observation and geoinformation (Online) 102 (2021). doi_10.1016/j.jag.2021.102350,
DOI: 10.1016%2Fj.jag.2021.102350
Abstract
Hydro-morphological processes (HMP, i.e. all processes contained within the spectrum defined between debris flows and ...
Hydro-morphological processes (HMP, i.e. all processes contained within the spectrum defined between debris flows and flash floods) initiate in response to intense rainfall events. Efficient HMP hazard assessment over large regions is often hindered because of limited rainfall observations over mountainous areas. Real-time and easily accessible satellite rainfall products offer new opportunities to address the observational coverage problem in ungauged catchments. In this work, two satellite rainfall products, Global Precipitation Measurement (GPM) and Climate Hazards Group Infrared Precipitation with Station Data (CHIRPS), are investigated by taking the ground measurements as a reference. Based on a close agreement between GPM and rain gauge data, daily rainfall together with a series of antecedent rainfall values were calculated to investigate the spatio-temporal distribution of HMP occurred from 2001 to 2015 across the whole Chinese territory. Ultimately, rainfall thresholds for HMP initiation within different geomorphological settings in China were obtained by_ (1) building antecedent rainfall sequences consisting of HMP and non-HMP via 100 nonparametric bootstrapped replicates; (2) testing several percentiles of the rainfall distribution as thresholds for HMP occurrence; (3) optimizing rainfall thresholds for six geomorphological macro-regions in China. This study confirmed the ability of satellite data in defining the rainfall conditions for the triggering of HMP, acknowledging the potential underestimation and/or bias that characterize any satellite rainfall products. Our findings provides new insight on rainfall conditions responsible for HMP initiation at the Chinese national scale.
Integrazione delle informazioni contenute in LAND-deFeND nell’interfaccia del SARF Sardegna
Ivan Marchesini1, Maria Teresa Brunetti1, Silvia Peruccacci1, Stefano Luigi Gariano1, Barbara Denti1, Mauro Rossi1, Massimo Melillo1, 2021, Integrazione delle informazioni contenute in LAND-deFeND nell’interfaccia del SARF Sardegna,
pp.1–16, 2021,
Abstract
Il presente documento illustra le attività realizzate nell'ambito delle Modifiche all'Estensione dell'Accordo di collaborazione tra ...
Il presente documento illustra le attività realizzate nell'ambito delle Modifiche all'Estensione dell'Accordo di collaborazione tra la Direzione Generale della Protezione Civile della Regione Autonoma della Sardegna servizio previsione rischi e dei sistemi informativi, infrastrutture e reti e il Consiglio Nazionale delle Ricerche, Istituto di Ricerca per la Protezione Idrogeologica (CNR IRPI) per la "Sperimentazione, validazione e sviluppo del Sistema di Allertamento Regionale per la previsione di Frane pluvio-indotte in Sardegna (SARF Sardegna)". In particolare, le attività previste riguardavano_
ol'integrazione di LAND-deFeND nell'interfaccia del SARF Sardegna;
ola stesura di un apposito rapporto;
ola manutenzione e il potenziamento operativo del SARF-Sardegna, con l'aggiornamento dell'interfaccia del sistema.
Il presente documento è suddiviso in due capitoli e la bibliografia di riferimento. Il primo capitolo introduce le attività svolte, mentre il secondo le descrive, suddividendole in due sotto-sezioni relative all'integrazione del LAND-deFeND nel SARF Sardegna e alla manutenzione e al potenziamento operativo del sistema.
Catalogo e soglie pluviometriche Sardegna
Massimo Melillo1, Stefano Luigi Gariano1, Barbara Denti1, Maria Teresa Brunetti1, Silvia Peruccacci1, Mauro Rossi1, Ivan Marchesini1, Cinzia Bianchi1, Domenico Caracciolo2, 2021, Catalogo e soglie pluviometriche Sardegna,
pp.1–35, 2021,
Abstract
Il presente documento illustra le attività realizzate nell'ambito delle Modifiche all'Estensione dell'Accordo di Collaborazione tra ...
Il presente documento illustra le attività realizzate nell'ambito delle Modifiche all'Estensione dell'Accordo di Collaborazione tra la Direzione Generale della Protezione Civile della Regione Autonoma della Sardegna servizio previsione rischi e dei sistemi informativi, infrastrutture e reti e il Consiglio Nazionale delle Ricerche, Istituto di Ricerca per la Protezione Idrogeologica (CNR IRPI) per la "Sperimentazione, validazione e sviluppo del Sistema di Allertamento Regionale per la previsione di Frane pluvio-indotte in Sardegna (SARF Sardegna)".
Tale documento riporta dati e informazioni relativi alla consegna di due prodotti previsti_
oanalisi della banca dati esistente e raccolta, organizzazione ed elaborazione di informazioni meteorologiche e geomorfologiche su movimenti franosi indotti da piogge in Sardegna;
oaggiornamento delle soglie pluviometriche empiriche per la previsione del possibile innesco di fenomeni franosi in Sardegna.
Il presente documento riporta le soglie pluviometriche empiriche di tipo cumulata - durata (CD) per il possibile innesco di fenomeni franosi in Sardegna da implementare nel Sistema di Allertamento Regionale per la previsione del possibile innesco di fenomeni franosi indotti da piogge SARF Sardegna. Le soglie sono calcolate utilizzando i dati del catalogo di eventi di pioggia con frane in Sardegna costruito dal CNR-IRPI. Sono state definite soglie pluviometriche oggettive e riproducibili, per percentuali di non superamento scelte e che includono l'incertezza nei parametri che definiscono le soglie.
A Global Landslide Non-Susceptibility Map
Guoqiang Jia(a,b), Massimiliano Alvioli(c), Stefano Luigi Gariano(c), Ivan Marchesini(c) , Fausto Guzzetti(d), Qiuhong Tang(a,b), 2021, A Global Landslide Non-Susceptibility Map,
Geomorphology (Amst.) 389 (2021): 107804. doi_10.1016/j.geomorph.2021.107804,
DOI: 10.1016%2Fj.geomorph.2021.107804
Abstract
At variance with conventional landslide susceptibility assessment, non-susceptibility analysis aims at selecting locations in which ...
At variance with conventional landslide susceptibility assessment, non-susceptibility analysis aims at selecting locations in which the likelihood of landslide occurrence is null or negligible. The advantage of this approach is that it does not require estimating different degrees of likelihood outside of the locations of negligible susceptibility. Thus, it entails the use of simplified classification methods. In this work, we tested and validated the existing non-susceptibility model with 18 global and regional landslide datasets, as a prior for the global application. The existing model was applied previously in Italy and the Mediterranean region, and defined by a non-linear relief vs. slope threshold curve, below which landslide susceptibility is negligible. Then, we applied a similar analysis, and proposed a global map, using relief and slope obtained from global elevation data at about 90-m resolution. The global map classifies 82.9% of the landmasses with negligible landslide susceptibility. The non-susceptible areas are broadly consistent with the "very-low" susceptibility class in existing global and continental landslide susceptibility maps and a national non-susceptibility map in the conterminous United States. Quantitative analyses revealed that population and settlements are denser within non-susceptible area than elsewhere, which makes the map of potential interest for non-exposure analysis, land planning and disaster responses at a global scale.
Combining Satellite InSAR, Slope Units and Finite Element Modeling for Stability Analysis in Mining Waste Disposal Areas
J. López-Vinielles(1,2,3), J.A. Fernández-Merodo(1,4), P. Ezquerro(1,2), J.C. García-Davalillo(1), R. Sarro(1), C. Reyes-Carmona(1), A. Barra(5), J.A. Navarro(5), V. Krishnakumar(5), M. Alvioli(6), G. Herrera(1,7), 2021, Combining Satellite InSAR, Slope Units and Finite Element Modeling for Stability Analysis in Mining Waste Disposal Areas,
Remote sensing (Basel) 13 (2021): 1–24. doi_10.3390/rs13102008,
DOI: 10.3390%2Frs13102008
Abstract
Slope failures pose a substantial threat to mining activity due to their destructive potential and ...
Slope failures pose a substantial threat to mining activity due to their destructive potential and high probability of occurrence on steep slopes close to limit equilibrium conditions, which are often found both in open pits and in waste and tailing disposal facilities. The development of slope monitoring and modeling programs usually entails the exploitation of in situ and remote sensing data, together with the application of numerical modeling, and it plays an important role in the definition of prevention and mitigation measures aimed at minimizing the impact of slope failures in mining areas. In this paper, a new methodology is presented; one that combines satellite radar interferometry and 2D finite element modeling for slope stability analysis at a regional scale, and applied within slope unit polygons. Although the literature includes many studies applying radar interferometry and modeling for slope stability analysis, the addition of slope units as input data for radar interferometry and modeling purposes has, to our knowledge, not previously been reported. A former mining area in southeast Spain was studied, and the method proved useful for detecting and characterizing a large number of unstable slopes. Out of the 1959 slope units used for the spatial analysis of the radar interferometry data, 43 were unstable, with varying values of safety factor and landslide size. Out of the 43 active slope units, 21 exhibited line of sight velocities greater than the maximum error obtained through validation analysis (2.5 cm/year). Finally, this work discusses the possibility of using the results of the proposed approach to devise a proxy for landslide hazard. The proposed methodology can help to provide non-expert final users with intelligible, clear, and easily comparable information to analyze slope instabilities in different settings, and not limited to mining areas.
Landslide failures detection and mapping using Synthetic Aperture Radar_ Past, present and future
Alessandro Cesare Mondini Fausto Guzzetti Kang-Tsung Chang Oriol Monserrat Tapas Ranjan Martha Andrea Manconi, 2021, Landslide failures detection and mapping using Synthetic Aperture Radar_ Past, present and future,
Earth Science Review (2021). doi_10.1016/j.earscirev.2021.103574,
DOI: 10.1016%2Fj.earscirev.2021.103574
Abstract
Landslides are geomorphological processes that shape the landscapes of all continents, dismantling mountains and contributing ...
Landslides are geomorphological processes that shape the landscapes of all continents, dismantling mountains and contributing sediments to the river networks. Caused by geophysical and meteorological triggers, including intense or prolonged rainfall, seismic shaking, volcanic activity, and rapid snow melting, landslides pose a serious threat to people, property, and the environment in many areas. Given their abundance and relevance, investigators have long experimented with techniques and tools for landslide detection and mapping using primarily aerial and satellite optical imagery interpreted visually, or processed by semi-automatic or automatic procedures or algorithms. Optical (passive) sensors have known limitations due to their inability to capture Earth surface images through the clouds and to work in the absence of daylight. The alternatives are active, "all-weather" and "day-and-night", microwave radar sensors capable of seeing through the clouds and working in presence and absence of daylight. We review the literature on the use of Synthetic Aperture Radar (SAR) imagery to detect and map landslide failures - i.e., the single most significant movement episodes in the history of a landslide - and of landslide failure events - i.e., populations of landslides in areas ranging from a few to several thousand square kilometres caused by a single trigger. We examine 54 articles published in representative journals presenting 147 case studies in 32 nations, in all continents, except Antarctica. Analysis of the geographical location of 70 study areas shows that SAR imagery was used to detect and map landslides in most morphological, geological, seismic, meteorological, climate, and land cover settings. The time history of the case studies reveals the increasing interest of the investigators in the use of SAR imagery for landslide detection and mapping, with less than one article per year from 1995 to 2011, rising to about 5 articles per year between 2012 and 2020, and an average period of about 4.2 years between the launch of a satellite and the publication of an article using imagery taken by the satellite. To detect and map landslides, investigators use a common framework that exploits the phase and the amplitude of the electromagnetic return signal recorded in the SAR images, to measure terrain surface properties and their changes. To discriminate landslides from the surrounding stable terrain, a classification of the ground properties is executed by expert visual (heuristic) interpretation, or through numerical (statistical) modelling approaches. Despite undisputed progress over the last 26 years, challenges remain to be faced for the effective use of SAR imagery for landslide detection and mapping. In the article, we examine the theoretical, research, and operational frameworks for the exploitation of SAR images for landslide detection and mapping, and we provide a perspective for future applications considering the existing and the planned SAR satellite missions.
New approach to computing mean velocity and discharge
Abdolvandi A.F.; Ziaei A.N.; Moramarco T.; Singh V.P., 2021, New approach to computing mean velocity and discharge,
Hydrological sciences journal (2021). doi_10.1080/02626667.2020.1859115,
DOI: 10.1080%2F02626667.2020.1859115
Abstract
Estimation of discharge hydrograph may be needed at river gauging stations where discharge is computed ...
Estimation of discharge hydrograph may be needed at river gauging stations where discharge is computed by converting water stage using a stage-discharge relation (a rating curve) or multiplying mean velocity by flow cross-sectional area. The mean velocity is computed by converting the measured maximum velocity to mean velocity using a conversion factor. Estimating the velocity conversion factor at stations where measured discharge data are insufficient remains a challenge. This study develops a novel method for determining the conversion factor by combining the entropy velocity profile, a data-driven technique, and a one-dimensional (1-D) flood routing model, and thus develops a method to determine discharge at the weak gauging sites. The method was used with two different assumptions_ constant velocity factor and velocity factor depending on the aspect ratio. Results showed that this method optimally estimated the conversion factor.
Design Flood and Flood-Prone Areas under Rating Curve Uncertainty_ Area of Vieux-Ténès, Algeria
Kastali A.; Zeroual A.; Remaoun M.; Serrano-Notivoli R.; Moramarco T., 2021, Design Flood and Flood-Prone Areas under Rating Curve Uncertainty_ Area of Vieux-Ténès, Algeria,
Journal of hydrologic engineering 26 (2021). doi_10.1061/(ASCE)HE.1943-5584.0002049,
DOI: 10.1061%2F(ASCE)HE.1943-5584.0002049
Abstract
The accuracy of flood control models depends on the set of annual maximum discharge used ...
The accuracy of flood control models depends on the set of annual maximum discharge used to estimate design flood via statistical flood frequency analysis (FFA). The uncertainties associated with the discharge time series from stage records are often ignored. Indeed, the uncertainty associated with discharge estimation is not addressed in many of the previous hydraulic risk analyses. In this study, we provide a quantitative approach to rigorously explore the effect that the rating curve uncertainty has on the design flood estimation and the flood hazard mapping. The town of Vieux-Ténès, Algeria, located near the mouth of the Allala River, was used as a case study. Despite the presence of concrete flood protection walls, several floods caused severe damage over the last decades in the town. Multisegment Bayesian rating curve, based on the Bayesian rating curve (BaRatin) method, was used to compute the rating curve uncertainty of the Allala hydrometric station, allowing for the creation of a new time series of annual maximum discharge for the 1973-2017 time period and the estimation of the design flood for different return periods by FFA. The Hydrologic Engineering Center's river analysis system (HEC-RAS) was used to model the water levels for different locations based on steady flow analysis, using them to define flood-prone areas and an effective protection system. We found that estimations of the flooded area varied between -18% and 15% when assessing rating curve uncertainties. Results highlighted that the existing flood control system is not sufficient to protect the inner city against flood risks, especially in the lower-lying areas of the flooded area.
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