Publications
Publications found: 2022
On the assimilation set-up of ASCAT soil moisture data for improving streamflow catchment simulation
Loizu, J., Massari, C., Álvarez-Mozos, J., Tarpanelli, A., Brocca, L., Casalí, J., 2017, On the assimilation set-up of ASCAT soil moisture data for improving streamflow catchment simulation,
Advances in water resources (2017). doi_10.1016/j.advwatres.2017.10.034,
DOI: 10.1016%2Fj.advwatres.2017.10.034
Abstract
Assimilation of remotely sensed surface soil moisture (SSM) data into hydrological catchment models has been ...
Assimilation of remotely sensed surface soil moisture (SSM) data into hydrological catchment models has been identified as a means to improve streamflow simulations, but reported results vary markedly depending on the particular model, catchment and assimilation procedure used. In this study, the influence of key aspects, such as the type of model, re-scaling technique and SSM observation error considered, were evaluated. For this aim, Advanced SCATterometer ASCAT-SSM observations were assimilated through the ensemble Kalman filter into two hydrological models of different complexity (namely MISDc and TOPLATS) run on two Mediterranean catchments of similar size (750 km2). Three different re-scaling techniques were evaluated (linear re-scaling, variance matching and cumulative distribution function matching), and SSM observation error values ranging from 0.01% to 20% were considered. Four different efficiency measures were used for evaluating the results. Increases in Nash-Sutcliffe efficiency (0.03-0.15) and efficiency indices (10-45%) were obtained, especially when linear re-scaling and observation errors within 4-6% were considered. This study found out that there is a potential to improve streamflow prediction through data assimilation of remotely sensed SSM in catchments of different characteristics and with hydrological models of different conceptualizations schemes, but for that, a careful evaluation of the observation error and re-scaling technique set-up utilized is required.
SM2RAIN-CCI: A new global long-term rainfall data set derived from ESA CCI soil moisture
Ciabatta, L., Massari, C., Brocca, L., Gruber, A., Reimer, C., Hahn, S., Paulik, C., Dorigo, W., Kidd, R., Wagner, W., 2017, SM2RAIN-CCI: A new global long-term rainfall data set derived from ESA CCI soil moisture,
Earth system science data. Papers in open discussion (2017). doi_10.5194/essd-2017-86,
Abstract
Accurate and long-term rainfall estimates are the main inputs for several applications, spanning from crop ...
Accurate and long-term rainfall estimates are the main inputs for several applications, spanning from crop modeling to climate analysis. In this study, we present a new rainfall data set (SM2RAIN-CCI) obtained from the inversion of the satellite soil moisture (SM) observations derived from the ESA Climate Change Initiative (CCI) via SM2RAIN (Brocca et al., 2014). Daily rainfall estimates are generated for an 18-year long period (1998-2015), with a spatial sampling of 0.25° on a global scale and are based on the integration of the ACTIVE and the PASSIVE ESA CCI SM data sets.
The quality of the SM2RAIN-CCI rainfall data set is evaluated by comparing it with two stateof-art rainfall satellite products, i.e. the Tropical Measurement Mission Multi-satellite Precipitation Analysis 3B42 real-time product (TMPA 3B42RT) and the Climate Prediction Center Morphing Technique (CMORPH), and one modelled data set (ERA-Interim). The assessment is carried out on a global scale at 1° of spatial sampling and 5-day of temporal sampling by comparing these products with the gauge-based Global Precipitation Climatology Centre Full Data Daily (GPCC-FDD) product. SM2RAIN-CCI shows relatively good results in terms of correlation coefficient (median value > 0.56), Root Mean Square Difference (RMSD, median value < 10.34 mm) and BIAS (median value < -14.44 %) during the evaluation period. The validation has been also carried out at original resolution (0.25°) over Europe, Australia and other 5 areas worldwide to test the capabilities of the data set to correctly identify rainfall events under different climate and precipitation regimes.
The CCI-SM derived rainfall data set is freely available at http_//www.esa-soilmoisture-cci.org at https_//doi.org/10.5281/zenodo.846259.
Global-scale evaluation of 22 precipitation datasets using gauge observations and hydrological modeling
Beck, H.E., Vergopolan, N., Pan, M., Levizzani, V., van Dijk, A.I.J.M., Weedon, G., Brocca, L., Pappenberger, F., Huffman, G.J., Wood, E.F., 2017, Global-scale evaluation of 22 precipitation datasets using gauge observations and hydrological modeling,
Hydrology and earth system sciences (Online) 21 (2017): 6201–6217. doi_10.5194/hess-21-6201-2017,
DOI: 10.5194%2Fhess-21-6201-2017
Abstract
We undertook a comprehensive evaluation of 23 gridded (quasi-)global (sub-)daily precipitation (P) datasets for the ...
We undertook a comprehensive evaluation of 23 gridded (quasi-)global (sub-)daily precipitation (P) datasets for the period 2000-2016. Thirteen non-gauge-corrected P datasets were evaluated using daily P gauge observations from 76 086 gauges worldwide. Another ten gauge-corrected datasets were evaluated using hydrological modeling, by calibrating the conceptual model HBV against streamflow records for each of 9053 small to medium-sized (< 50 000 km2) catchments worldwide, and comparing the resulting performance. Marked differences in spatio-temporal patterns and accuracy were found among the datasets. Among the uncorrected P datasets, the satellite- and reanalysis-based MSWEP-ng V1.2 and V2.0 datasets generally showed the best temporal correlations with the gauge observations, followed by the reanalyses (ERA-Interim, JRA-55, and NCEP-CFSR) and the the satellite- and reanalysis-based CHIRP V2.0 dataset, the estimates based primarily on passive microwave remote sensing of rainfall (CMORPH V1.0, GSMaP V5/6, and TMPA 3B42RT V7) or near-surface soil moisture (SM2RAIN-ASCAT), and finally, estimates based primarily on thermal infrared imagery (GridSat V1.0, PERSIANN, and PERSIANN-CCS). Two of the three reanalyses (ERA-Interim and JRA-55) unexpectedly obtained lower trend errors than the satellite datasets. Among the corrected P datasets, the ones directly incorporating daily gauge data (CPC Unified and MSWEP V1.2 and V2.0) generally provided the best calibration scores, although the good performance of the fully gaugebased CPC Unified is unlikely to translate to sparsely or ungauged regions. Next best results were obtained with P estimates directly incorporating temporally coarser gauge data (CHIRPS V2.0, GPCP-1DD V1.2, TMPA 3B42 V7, and WFDEI-CRU), which in turn outperformed those indirectly incorporating gauge data through other multi-source datasets (PERSIANN-CDR V1R1 and PGF). Our results highlight large differences in estimation accuracy, and hence, the importance of P dataset selection in both research and operational applications. The good performance of MSWEP emphasizes that careful data merging can exploit the complementary strengths of gauge-, satellite- and reanalysis-based P estimates.
Correcting satellite-based precipitation products through SMOS soil moisture data assimilation in two land-surface models of different complexity_ API and SURFEX
Román-Cascón, Carlos; Pellarin, Thierry; Gibon, François; Brocca, Luca; Cosme, Emmanuel; Crow, Wade; Fernández-Prieto, Diego; Kerr, Yann H.; Massari, Christian, 2017, Correcting satellite-based precipitation products through SMOS soil moisture data assimilation in two land-surface models of different complexity_ API and SURFEX,
Remote sensing of environment 200 (2017): 295–310. doi_10.1016/j.rse.2017.08.022,
DOI: 10.1016%2Fj.rse.2017.08.022
Abstract
Global rainfall information is useful for many applications. However, real-time versions of satellite-based rainfall products ...
Global rainfall information is useful for many applications. However, real-time versions of satellite-based rainfall products are known to contain errors. Recent studies have demonstrated how the information about rainfall intrinsically contained in soil moisture data can be utilised for improving rainfall estimates. That is, soil moisture dynamics are impacted for several days by the accumulated amount of rainfall following within a particular event. In this context, soil moisture data from the Soil Moisture Ocean Salinity (SMOS) satellite is used in this study to correct rainfall accumulation estimates provided by satellite-based real-time precipitation products such as CMORPH, TRMM-3B42RT or PERSIANN. An algorithm based on the SMOS measurements data assimilation is tested in two land-surface models of different complexity_ a simple hydrological model (Antecedent Precipitation Index (API)) and a more sophisticated state-of-the-art land-surface model (SURFEX (Surface Externalisée)). We show how the assimilation technique, based on a particle filter method, generally leads to a significant improvement in rainfall estimates, with slightly better results for the simpler (and less computationally demanding) API model. This methodology has been evaluated for six years at ten sites around the world with different land use and climatological features. The results also show the limitations of the methodology in regions highly affected by mountainous terrain, forest or intense radio-frequency interference (RFI), which can notably affect the quality of the retrievals. The satisfactory results shown here invite the future operational application of the methodology in near-real time on a global scale.
Exploiting a constellation of satellite soil moisture sensors for accurate rainfall estimation
Tarpanelli, A.; Massari, C.; Ciabatta, L.; Filippucci, P.; Amarnath, G.; Brocca, L., 2017, Exploiting a constellation of satellite soil moisture sensors for accurate rainfall estimation,
Advances in water resources 108 (2017): 249–255. doi_10.1016/j.advwatres.2017.08.010,
DOI: 10.1016%2Fj.advwatres.2017.08.010
Abstract
A merging procedure is applied to five daily rainfall estimates achieved via SM2RAIN applied to ...
A merging procedure is applied to five daily rainfall estimates achieved via SM2RAIN applied to the soil moisture products obtained by the Advanced SCATterometer, the Advanced Microwave Scanning Radiometer 2, the Soil Moisture Active and Passive mission, the Soil Moisture and Ocean Salinity mission and backscattering observations of RapidScat. The precipitation estimates are evaluated against dense ground networks in the period ranging from April to December, 2015, in India and in Italy, at 0.25°/daily spatial/temporal resolution. The merged product derived by combining the different SM2RAIN rainfall products shows better results in term of statistical and categorical metrics with respect to the use of the single products. A good agreement with reference to ground observations is obtained, with median correlations equal to 0.65 and 0.77 in India and in Italy, respectively. The merged dataset is found to slightly outperform those of the IMERG product of the Global Precipitation Measurement mission underlying the large potential of the proposed approach.
An assessment of the performance of global rainfall estimates without ground-based observations
Massari, Christian; Crow, Wade; Brocca, Luca, 2017, An assessment of the performance of global rainfall estimates without ground-based observations,
Hydrology and earth system sciences 21 (2017): 4347–4361. doi_10.5194/hess-21-4347-2017,
DOI: 10.5194%2Fhess-21-4347-2017
Abstract
Satellite-based rainfall estimates over land have great potential for a wide range of applications, but ...
Satellite-based rainfall estimates over land have great potential for a wide range of applications, but their validation is challenging due to the scarcity of ground-based observations of rainfall in many areas of the planet. Recent studies have suggested the use of triple collocation (TC) to characterize uncertainties associated with rainfall estimates by using three collocated rainfall products. However, TC requires the simultaneous availability of three products with mutually uncorrelated errors, a requirement which is difficult to satisfy with current global precipitation data sets.
In this study, a recently developed method for rainfall estimation from soil moisture observations, SM2RAIN, is demonstrated to facilitate the accurate application of TC within triplets containing two state-of-the-art satellite rainfall estimates and a reanalysis product. The validity of different TC assumptions are indirectly tested via a high-quality ground rainfall product over the contiguous United States (CONUS), showing that SM2RAIN can provide a truly independent source of rainfall accumulation information which uniquely satisfies the assumptions underlying TC. On this basis, TC is applied with SM2RAIN on a global scale in an optimal configuration to calculate, for the first time, reliable global correlations (vs. an unknown truth) of the aforementioned products without using a ground benchmark data set.
The analysis is carried out during the period 2007-2012 using daily rainfall accumulation products obtained at 1° × 1° spatial resolution. Results convey the relatively high performance of the satellite rainfall estimates in eastern North and South America, southern Africa, southern and eastern Asia, eastern Australia, and southern Europe, as well as complementary performances between the reanalysis product and SM2RAIN, with the first performing reasonably well in the Northern Hemisphere and the second providing very good performance in the Southern Hemisphere.
The methodology presented in this study can be used to identify the best rainfall product for hydrologic models with sparsely gauged areas and provide the basis for an optimal integration among different rainfall products.
In this study, a recently developed method for rainfall estimation from soil moisture observations, SM2RAIN, is demonstrated to facilitate the accurate application of TC within triplets containing two state-of-the-art satellite rainfall estimates and a reanalysis product. The validity of different TC assumptions are indirectly tested via a high-quality ground rainfall product over the contiguous United States (CONUS), showing that SM2RAIN can provide a truly independent source of rainfall accumulation information which uniquely satisfies the assumptions underlying TC. On this basis, TC is applied with SM2RAIN on a global scale in an optimal configuration to calculate, for the first time, reliable global correlations (vs. an unknown truth) of the aforementioned products without using a ground benchmark data set.
The analysis is carried out during the period 2007-2012 using daily rainfall accumulation products obtained at 1° × 1° spatial resolution. Results convey the relatively high performance of the satellite rainfall estimates in eastern North and South America, southern Africa, southern and eastern Asia, eastern Australia, and southern Europe, as well as complementary performances between the reanalysis product and SM2RAIN, with the first performing reasonably well in the Northern Hemisphere and the second providing very good performance in the Southern Hemisphere.
The methodology presented in this study can be used to identify the best rainfall product for hydrologic models with sparsely gauged areas and provide the basis for an optimal integration among different rainfall products.
Automatic mapping of event landslides at basin scale in Taiwan using a Montecarlo approach and synthetic land cover fingerprints
Mondini, Alessandro C.; Chang, Kang-Tsung; Chiang, Shou-Hao; Schlogel, Romy; Notarnicola, Claudia; Saito, Hitoshi, 2017, Automatic mapping of event landslides at basin scale in Taiwan using a Montecarlo approach and synthetic land cover fingerprints,
International journal of applied earth observation and geoinformation 63 (2017): 112–121. doi_10.1016/j.jag.2017.07.016,
DOI: 10.1016%2Fj.jag.2017.07.016
Abstract
We propose a framework to systematically generate event landslide inventory maps from satellite images in ...
We propose a framework to systematically generate event landslide inventory maps from satellite images in southern Taiwan, where landslides are frequent and abundant. The spectral information is used to assess the pixel land cover class membership probability through a Maximum Likelihood classifier trained with randomly generated synthetic land cover spectral fingerprints, which are obtained from an independent training images dataset. Pixels are classified as landslides when the calculated landslide class membership probability, weighted by a susceptibility model, is higher than membership probabilities of other classes. We generated synthetic fingerprints from two FORMOSAT-2 images acquired in 2009 and tested the procedure on two other images, one in 2005 and the other in 2009. We also obtained two landslide maps through manual interpretation. The agreement between the two sets of inventories is given by the Cohen's k coefficients of 0.62 and 0.64, respectively. This procedure can now classify a new FORMOSAT-2 image automatically facilitating the production of landslide inventory maps.
Soil variability and biogeochemical fluxes_ Toward a better understanding of soil processes at the land surface
Martinez, G.; Brocca, L.; Gerke, H. H.; Pachepsky, Y. A., 2017, Soil variability and biogeochemical fluxes_ Toward a better understanding of soil processes at the land surface,
Vadose zone journal 16 (2017). doi_10.2136/vzj2017.07.0145,
DOI: 10.2136%2Fvzj2017.07.0145
Abstract
Soil biogeochemical fluxes in the vadose zone are characterized by a large degree of variability ...
Soil biogeochemical fluxes in the vadose zone are characterized by a large degree of variability in space and time. This fact leads to the need for the development and application of appropriate methodologies to better understand the high nonlinearity and complex feedback mechanisms responsible for such fluxes. In this sense, there still exists a lack of knowledge in topics such as the scale dependence of the spatial and temporal variability of the controls on soil moisture and biodegradation rates and the dynamic behavior of flow and transport model parameter, and its association with the presence of roots. Knowledge of the variability of biogeochemical fluxes is needed for assorted applications ranging from natural hazards and environmental pollution risk assessment to agricultural production and water resources management. The contributions to this special section epitomize the ongoing effort toward the characterization, quantification, modeling, and understanding of biogeochemical fluxes in the vadose zone at several spatial and temporal scales. The main progress has been the identification of different controls on soil moisture and biodegradation rates depending on the scale of the study as well as the important dependence of the spatial and temporal variability of biogeochemical fluxes on dynamic properties such as vegetation and weather variables.
Gender, age and circumstances analysis of flood and landslide fatalities in Italy.
Salvati, Paola; Petrucci, Olga; Rossi, Mauro; Bianchi, Cinzia; Pasqua, Aurora A; Guzzetti, Fausto, 2017, Gender, age and circumstances analysis of flood and landslide fatalities in Italy.,
Science of the total environment 610-611 (2017): 867–879. doi_10.1016/j.scitotenv.2017.08.064,
DOI: 10.1016%2Fj.scitotenv.2017.08.064
Abstract
Floods and landslides are frequent and destructive geo-hydrological hazards that cause harm to people every ...
Floods and landslides are frequent and destructive geo-hydrological hazards that cause harm to people every year. We analysed data on 1292 landslide and 771 flood fatalities that occurred in Italy in the 50-year period 1965-2014, to determine the dependence of the fatalities on gender and age and the circumstances of death by type of hazard. The multinomial probability mass function of the expected fatalities by gender and age, as reported by national census data, were estimated and compared with the observed landslide and flood fatalities. We identified the age categories over or under represented when the observed fatalities were respectively higher or lower than the modelled expected deaths. We found that in Italy males are more vulnerable to floods and landslides for most of the age categories. Apart from children, males are over-represented up to the age of 89 for floods and up to 79 for landslides, whereas females are under-represented up to the age of 59 for floods and landslides, and over-represented above 70 for floods and between 60 and 79 for landslides. To consider the demographic and socio-cultural changes over time, we performed a temporal analysis splitting the record into two non-overlapping subsets of 25year each. The analysis demonstrated that the over-representation of males compared to the females, both for landslide and flood is statistically significant and does not vary in time, indicating a different propensity towards the risk taking and a different degree of exposure between males and females. Analysis of the data allowed to identify the common circumstances of death. Landslides fatalities occurred frequently indoor, whereas the majority of the flood fatalities occurred outdoor, outlining the different dynamics of the hazards. Floods killed numerous people along roads and drivers or passengers travelling in vehicles. We expect that the results of this work will be helpful to design recommendations for self-protecting actions, and proactive policies that can contribute to reduce the human toll of floods and landslides in Italy, and elsewhere.
Hydrological Risk_ Landslide
Nicola Casagli, Fausto Guzzetti, Michel Jaboyedoff, Farrokh Nadim, David Petley, 2017, Hydrological Risk_ Landslide,
, 2017,
Abstract
Hydrological Risk_ Landslide ...
Hydrological Risk_ Landslide
La conoscenza dei pericoli naturali come supporto ai processi decisionali di governo del territorio
L. Fondacci(1), M. Alvioli(2), F. Fiorucci(2), 2017, La conoscenza dei pericoli naturali come supporto ai processi decisionali di governo del territorio,
Urbanistica informazioni (Testo stamp.) 271 (2017): 68–69.,
Abstract
La natura, ciò che concerne l'uomo prima che egli inizi a manipolare e trasformare , ...
La natura, ciò che concerne l'uomo prima che egli inizi a manipolare e trasformare , è stata arricchita o impoverita da attività a crescente specializzazione. Gli insediamenti umani che ne sono derivati non simboleggiano più le sollecitazioni dinamiche che ci incalzano nell'assegnare la nostra idea di futuro alle sostanze terrestri , ma sono la causa della più potente pressione antropica e dei più distruttivi eventi atmosferici . Nello scritto, frutto dell'incontro di discipline diverse , si sostiene che l'approccio scientifico alla gestione dei rischi naturali può diventare parte della pianificazione urbana e ambientale , e aiutare i decisori ad intraprendere tutte le azioni necessarie a prevenire o ridurre significativamente i rischi per la popolazione e le infrastrutture, in base a metodi oggettivi e replicabili.
Characterization and quantification of path dependency in landslide susceptibility
Samia J.; Temme A.; Bregt A.; Wallinga J.; Guzzetti F.; Ardizzone F.; Rossi M., 2017, Characterization and quantification of path dependency in landslide susceptibility,
Geomorphology (Amst.) 292 (2017): 16–24. doi_10.1016/j.geomorph.2017.04.039,
DOI: 10.1016%2Fj.geomorph.2017.04.039
Abstract
Landslides cause major environmental damage, economic losses and casualties. Although susceptibility to landsliding is usually ...
Landslides cause major environmental damage, economic losses and casualties. Although susceptibility to landsliding is usually considered an exclusively location-specific phenomenon, indications exist that landslide history co-determines susceptibility to future landslides. In this contribution, we quantified the role of landslide path dependency (the effect of landslides on landslides) using a multi-temporal landslide inventory from Italy. The fraction of landslides following earlier landslides in the same location exhibited an exponential decay, with susceptibility increasing 15-fold right after an initial landslide, and returning to pre-landslide values after about 25 years. We investigated the role of the geometry and location of a previous landslide for the occurrence of follow-up landslides. Larger landslides are more likely to cause follow-up landslides. Also landslide shape, topographic wetness index, the vertical distance to the nearest channel network, the absolute profile curvature and relative slope position of an earlier landslide, however, are important in predicting whether a follow-up landslide occurs. Combined in a binary logistic model, these attributes correctly predict 60% of times whether a landslide will be followed-up. These findings open the way for time-variant mapping of susceptibility to landslides, by including the effect of the spatio-temporal history of landsliding on susceptibility.
Impact of rainfall spatial aggregation on the identification of debris flow occurrence thresholds
Francesco Marra (1), Elisa Destro (2), Efthymios I. Nikolopoulos (3), Davide Zoccatelli (1,2), Jean Dominique Creutin (4), Fausto Guzzetti (5), and Marco Borga (2), 2017, Impact of rainfall spatial aggregation on the identification of debris flow occurrence thresholds,
Hydrology and earth system sciences (Online) 21 (2017): 4525–4532. doi_10.5194/hess-21-4525-2017,
DOI: 10.5194%2Fhess-21-4525-2017
Abstract
The systematic underestimation observed in de- bris flow early warning thresholds has been associated with ...
The systematic underestimation observed in de- bris flow early warning thresholds has been associated with the use of sparse rain gauge networks to represent highly non-stationary rainfall fields. Remote sensing products per- mit concurrent estimates of debris-flow-triggering rainfall for areas poorly covered by rain gauges, but the impact of using coarse spatial resolutions to represent such rainfall fields is still to be assessed. This study uses fine-resolution radar data for ~ 100 debris flows in the eastern Italian Alps to (i) quan- tify the effect of spatial aggregation (1-20 km grid size) on the estimation of debris-flow-triggering rainfall and on the identification of early warning thresholds and (ii) compare thresholds derived from aggregated estimates and rain gauge networks of different densities. The impact of spatial aggre-gation is influenced by the spatial organization of rainfall and by its dependence on the severity of the triggering rainfall. Thresholds from aggregated estimates show 8-21 % varia- tion in the parameters whereas 10-25 % systematic variation results from the use of rain gauge networks, even for densi- ties as high as 1/10 km-2.
Soil electrical resistivity for spatial sampling design, prediction and uncertainty modelling of soil moisture
Calamita, G.1, Perrone, A.1, Brocca, L.2, Straface, S.1,3., 2017, Soil electrical resistivity for spatial sampling design, prediction and uncertainty modelling of soil moisture,
Vadose zone journal 16 (2017). doi_10.2136/vzj2017.01.0022,
DOI: 10.2136%2Fvzj2017.01.0022
Abstract
Geophysics constitutes a possible approach to estimate soil moisture with cost-competitive and minimally invasive measurements ...
Geophysics constitutes a possible approach to estimate soil moisture with cost-competitive and minimally invasive measurements carrying information about various soil physical properties. In this study, a geostatistical-based methodology for the integration of easily obtainable shallow soil electrical resistivity with soil moisture measurements was developed. Simultaneous and co-located surface measurements of soil moisture and electrical resistivity were performed during two field surveys in a test site located in central Italy. After an accurate characterization of the spatial auto-and cross-semivariance of soil moisture and electrical resistivity, an approach to design a soil moisture sampling strategy was set up. Soil moisture point predictions and uncertainties were estimated by ordinary co-kriging (OCK) interpolation and co-kriging simulation (CS), respectively. Results showed that at least 17 spatially regular soil moisture samples integrated with relatively denser soil electrical resistivity data via OCK are necessary to obtain a sufficiently accurate (RMSE <= 0.05) reconstruction of the average soil moisture at the test field. A comparison with the ordinary kriging interpolator, which takes into account only soil moisture samples, showed an improvement for OCK point prediction accuracy (RMSE from 0.049 to 0.039 and explained variance from 27 to 50%). The spatial uncertainty modeling empirically confirmed that geostatistical simulations furnish spatial uncertainty patterns more realistic and less dependent on the sampling scheme than interpolation approaches. Compared with sequential Gaussian simulations, which take into account only soil moisture data, the CS provided a model of local uncertainty with narrower probability intervals and lower prediction uncertainty.
ESA CCI Soil Moisture for improved Earth system understanding_ state-of-the art and future directions
Dorigo, W.,Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, D., Hamer, P. Hirschi, M., Ikonen, J., de Jeu, R., Kidd, R., Lahoz, W., Liu, Y.Y., Miralles, D., Mistelbauer, T., Nicolai-Shaw, N., Parinussa, R., Pratola, C., Reimer, C., van der Schalie, R., Seneviratne, S.I., Smolander, T., Lecomte, P., 2017, ESA CCI Soil Moisture for improved Earth system understanding_ state-of-the art and future directions,
Remote sensing of environment 203 (2017): 185–215. doi_10.1016/j.rse.2017.07.001,
DOI: 10.1016%2Fj.rse.2017.07.001
Abstract
Climate Data Records of soil moisture are fundamental for improving our understanding of long-term dynamics ...
Climate Data Records of soil moisture are fundamental for improving our understanding of long-term dynamics in the coupled water, energy, and carbon cycles over land. To respond to this need, in 2012 the European Space Agency (ESA) released the first multi-decadal, global satellite-observed soil moisture (SM) dataset as part of its Climate Change Initiative (CCI) program. This product, named ESA CCI SM, combines various single-sensor active and passive microwave soil moisture products into three harmonised products_ a merged ACTIVE, a merged PASSIVE, and a COMBINED active + passive microwave product. Compared to the first product release, the latest version of ESA CCI SM includes a large number of enhancements, incorporates various new satellite sensors, and extends its temporal coverage to the period 1978-2015. In this study, we first provide a comprehensive overview of the characteristics, evolution, and performance of the ESA CCI SM products. Based on original research and a review of existing literature we show that the product quality has steadily increased with each successive release and that the merged products generally outperform the single-sensor input products. Although ESA CCI SM generally agrees well with the spatial and temporal patterns estimated by land surface models and observed in-situ, we identify surface conditions (e.g., dense vegetation, organic soils) for which it still has large uncertainties. Second, capitalising on the results of > 100 research studies that made use of the ESA CCI SM data we provide a synopsis of how it has contributed to improved process understanding in the following Earth system domains_ climate variability and change, land-atmosphere interactions, global biogeochemical cycles and ecology, hydrological and land surface modelling, drought applications, and meteorology. While in some disciplines the use of ESA CCI SM is already widespread (e.g. in the evaluation of model soil moisture states) in others (e.g. in numerical weather prediction or flood forecasting) it is still in its infancy. The latter is partly related to current shortcomings of the product, e.g., the lack of near-real-time availability and data gaps in time and space. This study discloses the discrepancies between current ESA CCI SM product characteristics and the preferred characteristics of long-term satellite soil moisture products as outlined by the Global Climate Observing System (GCOS), and provides important directions for future ESA CCI SM product improvements to bridge these gaps.
Validation practices for satellite based earth observation data across communities
Loew, A., Bell, W., Brocca, L., Bulgin, C., Burdanowitz, J., Calbet, X., Donner, R., Ghent, D., Gruber, A., Kaminski, T., Kinzel, J., Klepp, C., Lambert, J.C., Schaepman-Strub, G., Schröder, M., Verhoelst, T., 2017, Validation practices for satellite based earth observation data across communities,
Reviews of geophysics (1985) (2017). doi_10.1002/2017rg000562,
Abstract
Assessing the inherent uncertainties in satellite data products is a challenging task. Different technical approaches ...
Assessing the inherent uncertainties in satellite data products is a challenging task. Different technical approaches have been developed in the Earth Observation (EO) communities to address the validation problem which results in a large variety of methods as well as terminology.
This paper reviews state-of-the-art methods of satellite validation and documents their similarities and differences. First the overall validation objectives and terminologies are specified, followed by a generic mathematical formulation of the validation problem. Metrics currently used as well as more advanced EO validation approaches are introduced thereafter. An outlook on the applicability and requirements of current EO validation approaches and targets is given.
The multi temporal
Barbetta, Silvia; Coccia, Gabriele; Moramarco, Tommaso; Brocca, Luca; Todini, Ezio, 2017, The multi temporal,
Journal of hydrology (Amst.) 551 (2017): 555–576. doi_10.1016/j.jhydrol.2017.06.030,
DOI: 10.1016%2Fj.jhydrol.2017.06.030
Abstract
This work extends the multi-temporal approach of the Model Conditional Processor (MCP-MT) to the multi-model ...
This work extends the multi-temporal approach of the Model Conditional Processor (MCP-MT) to the multi-model case and to the four Truncated Normal Distributions (TNDs) approach, demonstrating the improvement on the single-temporal one. The study is framed in the context of probabilistic Bayesian decision-making that is appropriate to take rational decisions on uncertain future outcomes. As opposed to the direct use of deterministic forecasts, the probabilistic forecast identifies a predictive probability density function that represents a fundamental knowledge on future occurrences. The added value of MCP-MT is the identification of the probability that a critical situation will happen within the forecast lead-time and when, more likely, it will occur. MCP-MT is thoroughly tested for both single-model and multi-model configurations at a gauged site on the Tiber River, central Italy. The stages forecasted by two operative deterministic models, STAFOM-RCM and MISDc, are considered for the study. The dataset used for the analysis consists of hourly data from 34 flood events selected on a time series of six years. MCP-MT improves over the original models' forecasts_ the peak overestimation and the rising limb delayed forecast, characterizing MISDc and STAFOM-RCM respectively, are significantly mitigated, with a reduced mean error on peak stage from 45 to 5 cm and an increased coefficient of persistence from 0.53 up to 0.75. The results show that MCP-MT outperforms the single-temporal approach and is potentially useful for supporting decision-making because the exceedance probability of hydrometric thresholds within a forecast horizon and the most probable flooding time can be estimated.
Modeling the water budget of the Upper Blue Nile basin using the JGrass-NewAge model system and satellite data
Abera, Wuletawu; Abera, Wuletawu; Formetta, Giuseppe; Brocca, Luca; Rigon, Riccardo, 2017, Modeling the water budget of the Upper Blue Nile basin using the JGrass-NewAge model system and satellite data,
Hydrology and earth system sciences 21 (2017): 3145–3165. doi_10.5194/hess-21-3145-2017,
DOI: 10.5194%2Fhess-21-3145-2017
Abstract
The Upper Blue Nile basin is one of the most datascarce regions in developing countries, ...
The Upper Blue Nile basin is one of the most datascarce regions in developing countries, and hence the hydrological information required for informed decision making in water resource management is limited. The hydrological complexity of the basin, tied with the lack of hydrometeorological data, means that most hydrological studies in the region are either restricted to small subbasins where there are relatively better hydrometeorological data available, or on the whole-basin scale but at very coarse timescales and spatial resolutions. In this study we develop a methodology that can improve the state of the art by using available, but sparse, hydrometeorological data and satellite products to obtain the estimates of all the components of the hydrological cycle (precipitation, evapotranspiration, discharge, and storage). To obtain the water-budget closure, we use the JGrass-NewAge system and various remote sensing products. The satellite product SM2R-CCI is used for obtaining the rainfall inputs, SAF EUMETSAT for cloud cover fraction for proper net radiation estimation, GLEAM for comparison with NewAge-estimated evapotranspiration, and GRACE gravimetry data for comparison of the total water storage amounts available in the whole basin. Results are obtained at daily time steps for the period 1994-2009 (16 years), and they can be used as a reference for any water resource development activities in the region. The overall water-budget analysis shows that precipitation of the basin is 1360-230mm per year. Evapotranspiration accounts for 56% of the annual water budget, runoff is 33 %, storage varies from 10 to C17% of the water budget.
Discharge estimation and forecasting by MODIS and altimetry data in Niger-Benue River
Tarpanelli, Angelica; Amarnath, Giriraj; Brocca, Luca; Massari, Christian; Moramarco, Tommaso, 2017, Discharge estimation and forecasting by MODIS and altimetry data in Niger-Benue River,
Remote sensing of environment 195 (2017): 96–106. doi_10.1016/j.rse.2017.04.015,
DOI: 10.1016%2Fj.rse.2017.04.015
Abstract
Flooding is one of the most devastating natural hazards in the world and its forecast ...
Flooding is one of the most devastating natural hazards in the world and its forecast is essential in flood risk reduction and disaster response decision. The lack of adequate monitoring networks, especially in developing countries prevents near real-time flood prediction that could help to reduce the loss of lives and economic damages. In the last few years, increasing availability of multi-satellite sensors induced to develop new techniques for retrieving river discharge and especially in supporting discharge nowcasting and forecasting activities. Recently, the potential of radar altimetry to estimate water levels and discharge in ungauged river sites with good accuracy has been demonstrated. However, the considerable benefit derived from this technique is attenuated by the low revisit time of the satellite (10 or 35 days, depending on the satellite mission) causing delays on the predicting operations. For this reason, sensors with a higher temporal resolution such as the MODerate resolution Imaging Spectroradiometer (MODIS), working in visible/Infra-Red bands, can support flood forecasting.
In this study, we performed the forecast of river discharge by using MODIS and we compared it with the radar altimetry and in-situ data along the Niger-Benue River in Nigeria to develop an operational flood forecasting scheme that could help in rapid emergency response and decision making processes. In the first step, four MODIS products (daily and, 8-day from the TERRA and AQUA satellites) at two gauged sites were used for discharge estimation. Secondly, the capability of remote sensing sensors to forecast discharge a few days (~ 4 days) in advance at a downstream section using MODIS is analyzed and also compared with the one obtained by the use of radar altimetry by ENVISAT and Jason-2.
The results confirmed the capability of the MODIS data to estimate river discharge with performance indices > 0.97 and 0.95 in terms of coefficient of correlation and Nash Sutcliffe efficiency. In particular, RMSE does not exceed 1300 m3/s and the fractional RMSE ranges between 0.15 and 0.23. For the forecasting exercise, both altimetry and MODIS provide satisfactory results with positive coefficient of persistence considering 4 days of lead time (> 0.34). Although altimetry was found to be more accurate in the forecasting of river discharge (RMSE ~ 350 m3/s), the much higher temporal resolution of MODIS guarantees a continuity that is more suitable to address operational activities.
A Review of the Applications of ASCAT Soil Moisture Products
Brocca, Luca; Crow, Wade T.; Ciabatta, Luca; Ciabatta, Luca; Massari, Christian; De Rosnay, Patricia; Enenkel, Markus; Hahn, Sebastian; Amarnath, Giriraj; Camici, Stefania; Tarpanelli, Angelica; Wagner, Wolfgang, 2017, A Review of the Applications of ASCAT Soil Moisture Products,
IEEE journal of selected topics in applied earth observations and remote sensing (Print) 10 (2017): 2285–2306. doi_10.1109/JSTARS.2017.2651140,
DOI: 10.1109%2FJSTARS.2017.2651140
Abstract
Remote sensing of soil moisture has reached a level of good maturity and accuracy for ...
Remote sensing of soil moisture has reached a level of good maturity and accuracy for which the retrieved products are ready to use in real-world applications. Due to the importance of soil moisture in the partitioning of the water and energy fluxes between the land surface and the atmosphere, a wide range of applications can benefit from the availability of satellite soil moisture products. Specifically, the Advanced SCATterometer (ASCAT) on board the series of Meteorological Operational (Metop) satellites is providing a near real time (and long-term, 9+ years starting from January 2007) soil moisture product, with a nearly daily (sub-daily after the launch of Metop-B) revisit time and a spatial sampling of 12.5 and 25 km. This study first performs a review of the climatic, meteorological, and hydrological studies that use satellite soil moisture products for a better understanding of the water and energy cycle. Specifically, applications that consider satellite soil moisture product for improving their predictions are analyzed and discussed. Moreover, four real examples are shown in which ASCAT soil moisture observations have been successfully applied toward_ 1) numerical weather prediction, 2) rainfall estimation, 3) flood forecasting, and 4) drought monitoring and prediction. Finally, the strengths and limitations of ASCAT soil moisture products and the way forward for fully exploiting these data in real-world applications are discussed.
Accuracy versus variability of climate projections for flood assessment in central Italy
Camici, S.; Brocca, L.; Moramarco, T., 2017, Accuracy versus variability of climate projections for flood assessment in central Italy,
Climatic change 141 (2017): 273–286. doi_10.1007/s10584-016-1876-x,
DOI: 10.1007%2Fs10584-016-1876-x
Abstract
Climatic extremes are changing and decision-makers express a strong need for reliable information on future ...
Climatic extremes are changing and decision-makers express a strong need for reliable information on future changes over the coming decades as a basis for adaption strategies. In the hydrological-hydraulic context, to estimate changes on floods, a modeling chain composed by general circulation models (GCMs), bias correction (BC) methods, and hydrological modeling is generally applied. It is well-known that each step of the modeling chain introduces uncertainties, resulting in a reduction of the reliability of future climate projections. The main goal of this study is the assessment of the accuracy and variability (i.e., model accuracy, climate intermodel variability, and natural variability) on climate projections related to the present period. By using six different GCMs and two BC methods, the "climate intermodel variability" is evaluated. "Natural variability" is estimated through random realizations of stochastic weather generators. By comparing observed and simulated extreme discharge values, obtained through a continuous rainfall-runoff model, "model accuracy" is computed. The Tiber River basin in central Italy is used as a case study. Results show that in climate projections, model accuracy and climate intermodel variability components have to be clearly distinguished. For accuracy, the hydrological model is found to be the largest source of error; for variability, natural variability contributes for more than 75% to the total variability while GCM and BC have a much lower influence. Moreover, accuracy and variability components vary significantly, and not consistently, between catchments with different permeability characteristics.
Editorial: River basin hydrology and natural hazards_ Monitoring, prediction and prevention
Biondi, Daniela; Brocca, Luca; Castellarin, Attilio, 2017, Editorial: River basin hydrology and natural hazards_ Monitoring, prediction and prevention,
Hydrology research (Print) 48 (2017): 613–615. doi_10.2166/nh.2017.000,
Abstract
The 5th edition of the 'Hydrology Days' of the Italian Hydrological Society was held in ...
The 5th edition of the 'Hydrology Days' of the Italian Hydrological Society was held in Perugia, Italy, 6-8 October 2015, to provide a joint forum of hydrologists and a broad range of stakeholders for commenting and discussing on 'River basin hydrology and natural hazards_ monitoring, prediction and prevention'. A total of 58 abstracts were presented at the workshop. The 2½-day conference was organized by the 'Hydrology Group' of the Research Institute for Geo-Hydrological Protection (National Research Council of Italy) in collaboration with the Italian Hydrological Society, the Tiber River Basin Authority and the professional association of Engineers of Perugia. Specifically, the Italian Hydrological Society (SII-IHS) was founded in 2009 to foster progress, enhancement and dissemination of hydrological sciences in Italy, including all aspects related to water resources systems management and possible interaction with human activity. In this perspective, one of the main objectives of the Association is to stimulate interdisciplinary collaboration among academia, research institutes, institutional stakeholders and private operators.
Soil moisture for hydrological applications_ Open questions and new opportunities
Brocca, Luca; Ciabatta, Luca; Massari, Christian; Camici, Stefania; Tarpanelli, Angelica, 2017, Soil moisture for hydrological applications_ Open questions and new opportunities,
Water (Basel) 9 (2017). doi_10.3390/w9020140,
DOI: 10.3390%2Fw9020140
Abstract
Soil moisture is widely recognized as a key parameter in the mass and energy balance ...
Soil moisture is widely recognized as a key parameter in the mass and energy balance between the land surface and the atmosphere and, hence, the potential societal benefits of an accurate estimation of soil moisture are immense. Recently, scientific community is making great effort for addressing the estimation of soil moisture over large areas through in situ sensors, remote sensing and modelling approaches. The different techniques used for addressing the monitoring of soil moisture for hydrological applications are briefly reviewed here. Moreover, some examples in which in situ and satellite soil moisture data are successfully employed for improving hydrological monitoring and predictions (e.g., floods, landslides, precipitation and irrigation) are presented. Finally, the emerging applications, the open issues and the future opportunities given by the increased availability of soil moisture measurements are outlined.
Near real time de-noising of satellite-based soil moisture retrievals_ An intercomparison among three different techniques
Massari, Christian; Su, Chun Hsu; Brocca, Luca; Sang, Yan Fang; Ciabatta, Luca; Ryu, Dongryeol; Wagner, Wolfgang, 2017, Near real time de-noising of satellite-based soil moisture retrievals_ An intercomparison among three different techniques,
Remote sensing of environment 198 (2017): 17–29. doi_10.1016/j.rse.2017.05.037,
DOI: 10.1016%2Fj.rse.2017.05.037
Abstract
Real-time de-noising of satellite-derived soil moisture observations presents opportunities to deliver more accurate and timely ...
Real-time de-noising of satellite-derived soil moisture observations presents opportunities to deliver more accurate and timely satellite data for direct satellite users. So far, the most commonly used techniques for reducing the impact of noise in the retrieved satellite soil moisture observations have been based on moving average filters and Fourier based methods. This paper introduces a new alternative wavelet based approach called Wiener-Wavelet-Based Filter (WiW), which uses an entropy based de-noising method to design a causal version of the filter. WiW is used as a post-retrieval processing tool to enhance the quality of observations derived from one active (the Advanced Scatterometer, ASCAT) and one passive (the Advanced Microwave Scanning Radiometer for Earth Observing System, AMSRE) satellite sensors. The filter is then compared with two candidate de-noising techniques, namely_ i) a Wiener causal filter introduced by Su et al. (2013) and ii) a conventional moving average filter. The validation is carried out globally at 173 (for AMSRE) and 243 (for ASCAT) soil moisture stations. Results show that all the three de-noising techniques can increase the agreement between satellite and in situ measurements in terms of correlation and signal-to-noise ratio. The Wiener-based methods show least signal distortion and demonstrate to be conservative in retaining the signal information in de-noised data. Importantly, the Wiener filters can be calibrated with the data at hand, without the need for auxiliary data.
Hazard and population vulnerability analysis_ a step towards landslide risk assessment
Franny G. Murillo-García (1), Mauro Rossi (2), Francesca Ardizzone (2), Federica Fiorucci (2), Irasema Alcántara-Ayala (3), 2017, Hazard and population vulnerability analysis_ a step towards landslide risk assessment,
Journal of mountain science (Online) 14 (2017). doi_10.1007/s11629-016-4179-9,
DOI: 10.1007%2Fs11629-016-4179-9
Abstract
In this paper, an attempt to analyse
landslide hazard and vulnerability in the municipality
of ...
In this paper, an attempt to analyse
landslide hazard and vulnerability in the municipality
of Pahuatlán, Puebla, Mexico, is presented. In order
to estimate landslide hazard, the susceptibility,
magnitude (area-velocity ratio) and landslide
frequency of the area of interest were produced based
on information derived from a geomorphological
landslide inventory; the latter was generated by using
very high resolution satellite stereo pairs along with
information derived from other sources (Google Earth,
aerial photographs and historical information).
Estimations of landslide susceptibility were
determined by combining four statistical techniques_
(i) logistic regression, (ii) quadratic discriminant
analysis, (iii) linear discriminant analysis, and (iv)
neuronal networks. A Digital Elevation Model (DEM)
of 10 m spatial resolution was used to extract the
slope angle, aspect, curvature, elevation and relief.
These factors, in addition to land cover, lithology and
distance to faults, were used as explanatory variables
for the susceptibility models. Additionally, a Poisson
model was used to estimate landslide temporal
frequency, at the same time as landslide magnitude
was obtained by using the relationship between
landslide area and the velocity of movements. Then,
due to the complexity of evaluating it, vulnerability of
population was analysed by applying the Spatial
Approach to Vulnerability Assessment (SAVE) model
which considered levels of exposure, sensitivity and
lack of resilience. Results were expressed on maps on
which different spatial patterns of levels of landslide
hazard and vulnerability were found for the inhabited
areas. It is noteworthy that the lack of optimal
methodologies to estimate and quantify vulnerability
is more notorious than that of hazard assessments.
Consequently, levels of uncertainty linked to landslide
risk assessment remain a challenge to be addressed.
The Differential Slow Moving Dynamic of a Complex Landslide_ Multi-sensor Monitoring
Gerardo Herrera, Juan Carlos Garci?a Lo?pez-Davalillo,
Jose Antonio Ferna?ndez-Merodo, Marta Be?jar-Pizarro,
Paolo Allasia, Piernicola Lollino, Giorgio Lollino, Fausto Guzzetti, Maria Inmaculada A?lvarez-Ferna?ndez, Andrea Manconi, Javier Duro, Ciscu Sa?nchez, and Rube?n Iglesias, 2017, The Differential Slow Moving Dynamic of a Complex Landslide_ Multi-sensor Monitoring,
4th World Landslide Forum, pp. 219–225, Lubiana, 2017,
Abstract
Monitoring is essential to understand the mechanics of landslides, and predict their behavior in time ...
Monitoring is essential to understand the mechanics of landslides, and predict their behavior in time and space. In this work we discuss the performance of multi-sensor monitoring techniques applied to measure the kinematics and the landslide hydrology of Portalet landslide complex, which is located in the SW-facing slopes of Petrasos peak at the border between Spain and France. In the summer 2004, the excavation of a parking lot at the foot of the slides triggered a secondary failure in the lower part of the slope, accelerating the dynamic of the landslide complex. The deployed hydro-meteorological network has been useful to understand that the greatest infiltration in the moving mass is produced in spring due to the combination of snow melt and seasonal rainfall. Landslide surface kinematics measured with differential GPS (D-GPS) were useful to measure the slower (<10 cm/year) and faster (20-30 cm/year) dynamic of the landslide complex. Advanced DInSAR was useful to monitor the slower ground displacements from long datasets of SAR images, providing a wider spatial coverage and measurement point density than the D-GPS. In addition, the NL-InSAR processing strategy was applied to monitor the faster motion using short datasets of TerraSAR-X images excluding the snow cover period.
Landslide Dynamics_ ISDR-ICL Landslide Interactive Teaching Tools (LITT)
Kyoji Sassa, Fausto Guzzetti, Hiromitsu Yamagishi, Z?eljko Arbanas, Nicola Casagli, Binod Tiwari, Ko-Fei Liu, Alexander Strom, Mauri McSaveney, Eileen McSaveney, Khang Dang, and Hendy Setiawan, 2017, Landslide Dynamics_ ISDR-ICL Landslide Interactive Teaching Tools (LITT),
4th World Landslide Forum, pp. 193–218, Lubiana, 2017,
Abstract
K. Sassa (&)
International Consortium on Landslides (ICL), Kyoto, Japan e-mail: sassa@iclhq.org
F. Guzzetti
Istituto di Ricerca per ...
K. Sassa (&)
International Consortium on Landslides (ICL), Kyoto, Japan e-mail: sassa@iclhq.org
F. Guzzetti
Istituto di Ricerca per la Protezione Idrogeologica, Consiglio Nazionale delle Ricerche, via Madonna Alta 126, 06128 Perugia, Italy
e-mail: Fausto.Guzzetti@irpi.cnr.it
H. Yamagishi
Asian Institute of Spatial Information, Shiroishi-Ku, Hongodori 2chome Kita 3-10, Sapporo, 003-0025, Japan
e-mail: hiromitsuyamagishi88@gmail.com
Z?. Arbanas
Faculty of Civil Engineering, University of Rijeka, Radmile Matejc?ic? 3 Rijeka 51000, Rijeka, Croatia
e-mail: zeljko.arbanas@gradri.uniri.hr
N. Casagli
Department of Earth Sciences, University of Firenze, Via La Pira 4, 50212 Florence, Italy
e-mail: nicola.casagli@unifi.it
B. Tiwari
Civil & Environmental Engineering Department, California State University, Fullerton, 800 N State College Blvd., E-419, Fullerton, CA 92831, USA
e-mail: btiwari@fullerton.edu
© The Author(s) 2017
K. Sassa et al. (eds.), Advancing Culture of Living with Landslides, DOI 10.1007/978-3-319-59469-9_17
K. Liu
National Taiwan University, No.1, Roosevelt Road, Chinese Taipei, 10617, Taiwan, Republic of China
e-mail: kfliu@ntu.edu.tw
M. McSaveney E. McSaveney
GNS Science, PO Box 30368, Lower Hutt, 5040, New Zealand e-mail: m.mcsaveney@gns.cri.nz
E. McSaveney
e-mail: e.mcsaveney@gns.cri.nz
H. Setiawan
Disaster Prevention Research Institute, Kyoto University, Uji, 611-0011, Japan
e-mail: hendy@flood.dpri.kyoto-u.ac.jp
A. Strom
Geodynamics Research Centre--branch of JSC "Hydroproject Institute", Volokolamsk Highway 2, Moscow, 125993, Russia e-mail: strom.alexandr@yandex.ru
K. Dang
International Consortium on Landslides, Kyoto, Japan e-mail: khangdq@gmail.com
K. Dang
VNU University of Science, Hanoi, Vietnam
How Many Rainfall-Induced Landslides Are Detectable by a Regional Seismic Monitoring Network?
Andrea Manconi (1), Stefano Luigi Gariano (2), Velio Coviello (3), and Fausto Guzzetti (2), 2017, How Many Rainfall-Induced Landslides Are Detectable by a Regional Seismic Monitoring Network?,
4th World Landslide Forum, pp. 161–168, Lubiana, 2017,
Abstract
Mass wasting events occurring on the Earth's surface may induce seismic signals, which can be ...
Mass wasting events occurring on the Earth's surface may induce seismic signals, which can be recorded also at tens of kilometers from the source area. The waveforms relevant to mass wasting differ from those caused by earthquakes, because they are usually characterized by a cigar shaped waveform, duration of several tens of seconds, and low frequencies (1-10 Hz). In literature, no studies have performed a systematic analysis on comprehensive catalogues of rainfall induced landslide records at regional scale. In this work, we analyze the seismic waveforms of 1058 landslides induced by rainfall in Italy, spanning the period between 2000 and 2014. Seismic data are gathered by several European research infrastructures and collected in the European Integrated Data Archive of the Observatories and Research Facilities for European Seismology. We present preliminary results obtained from this large effort, as well as some first statistical considerations on the rainfall-triggered landslides identified within seismic records. Such analyses may provide important insights for the development and calibration of automatic landslide identification algorithms, which might be then used to verify the validity of landslide forecasting procedures based on rainfall thresholds, as well as to enhance the catalogues completeness by exploiting quantitative measures and relying not only chronicle information.
Measures of Spatial Autocorrelation Changes in Multitemporal SAR Images for Event Landslides Detection
Alessandro C. Mondini, 2017, Measures of Spatial Autocorrelation Changes in Multitemporal SAR Images for Event Landslides Detection,
Remote sensing (Basel) (2017). doi_10.3390/rs9060554,
DOI: 10.3390%2Frs9060554
Abstract
Landslides cause damages and affect victims worldwide, but landslide information is
lacking. Even large events may ...
Landslides cause damages and affect victims worldwide, but landslide information is
lacking. Even large events may not leave records when they happen in remote areas or simply
do not impact with vulnerable elements. This paper proposes a procedure to measure spatial
autocorrelation changes induced by event landslides in a multi-temporal series of synthetic aperture
radar (SAR) intensity Sentinel-1 images. The procedure first measures pixel-based changes between
consecutive couples of SAR intensity images using the Log-Ratio index, then it follows the temporal
evolution of the spatial autocorrelation inside the Log-Ratio layers using the Moran's I index and the
semivariance. When an event occurs, the Moran's I index and the semivariance increase compared
to the values measured before and after the event. The spatial autocorrelation growth is due to the
local homogenization of the soil response caused by the event landslide. The emerging clusters of
autocorrelated pixels generated by the event are localized by a process of optimal segmentation of
the log-ratio layers. The procedure was used to intercept an event that occurred in August 2015
in Myanmar, Tozang area, when strong rainfall precipitations triggered a number of landslides.
A prognostic use of the method promises to increase the availability of information about the number
of events at the regional scale, and to facilitate the production of inventory maps, yielding useful
results to study the phenomenon for model tuning, landslide forecast model validation, and the
relationship between triggering factors and number of occurred events.
Detection of rainfall-induced landslides on regional seismic networks
Andrea Manconi (1), Velio Coviello (2), Stefano Luigi Gariano (3,4), and Matteo Picozzi (5), 2017, Detection of rainfall-induced landslides on regional seismic networks,
European Geosciences Union General Assembly 2017, pp. EGU2017-7248–EGU2017-7248, Vienna, 23-28/04/2017,
Abstract
Seismic techniques are increasingly adopted to detect signals induced by mass movements and to quantitatively ...
Seismic techniques are increasingly adopted to detect signals induced by mass movements and to quantitatively evaluate geo-hydrological hazards at different spatial and temporal scales. By analyzing landslide-induced seismicity, it is possible obtaining significant information on the source of the mass wasting, as well as on its dynamics. However, currently only few studies have performed a systematic back analysis on comprehensive catalogues of events to evaluate the performance of proposed algorithms. In this work, we analyze a catalogue of 1058 landslides induced by rainfall in Italy. Among these phenomena, there are 234 rock falls, 55 debris flows, 54 mud flows, and 715 unspecified shallow landslides. This is a subset of a larger catalogue collected by the Italian research institute for geo-hydrological protection (CNR IRPI) during the period 2000-2014 (Brunetti et al., 2015). For each record, the following information are available_ the type of landslide; the geographical location of the landslide (coordinates, site, municipality, province, and 3 classes of geographic accuracy); the temporal information on the landslide occurrence (day, month, year, time, date, and 3 classes of temporal accuracy); the rainfall conditions (rainfall duration and cumulated event rainfall) that have resulted in the landslide. We consider here only rainfall-induced landslides for which exact date and time were known from chronicle information. The analysis of coeval seismic data acquired by regional seismic networks show clear signals in at least 3 stations for 64 events (6% of the total dataset). Among them, 20 are associated to local earthquakes and 2 to teleseisms; 10 are anomalous signals characterized by irregular and impulsive waveforms in both time and frequency domains; 33 signals are likely associated to the landslide occurrence, as they have a cigar-shaped waveform characterized by emerging onsets, duration of several tens of seconds, and low frequencies (1-10 Hz). For this last category of events, we have applied the approach proposed in Manconi et al. (2016), in order to evaluate the performance of automatic identification, location and first order classification of landslide events trough seismic data only. Our analysis may provide important insights for the development and calibration of landslide identification algorithms,
which might be used to enhance the completeness of landslide catalogues by relying on quantitative data.
Design of a reliable and operational landslide early warning system at regional scale
Michele Calvello (1), Luca Piciullo (2), Stefano Luigi Gariano (3), Massimo Melillo (4), Maria Teresa Brunetti (5), Silvia Peruccacci (6), and Fausto Guzzetti (7), 2017, Design of a reliable and operational landslide early warning system at regional scale,
European Geosciences Union General Assembly 2017, pp. EGU2017-4070–EGU2017-4070, Vienna, 23-28/04/2017,
Abstract
Landslide early warning systems at regional scale are used to warn authorities, civil protection personnel ...
Landslide early warning systems at regional scale are used to warn authorities, civil protection personnel and the population about the occurrence of rainfall-induced landslides over wide areas, typically through the prediction and measurement of meteorological variables. A warning model for these systems must include a regional correlation law and a decision algorithm. A regional correlation law can be defined as a functional relationship between rainfall and landslides; it is typically based on thresholds of rainfall indicators (e.g., cumulated rainfall, rainfall duration) related to different exceedance probabilities of landslide occurrence. A decision algorithm can be defined as a set of assumptions and procedures linking rainfall thresholds to warning levels. The design and the employment of an operational and reliable early warning system for rainfall-induced landslides at regional scale depend on the identification of a reliable correlation law as well as on the definition of a suitable decision algorithm. Herein, a five-step process chain addressing both issues and based on rainfall thresholds is proposed; the procedure is tested in a landslide-prone area of the Campania region in southern Italy. To this purpose, a database of 96 shallow landslides triggered by rainfall in the period 2003-2010 and rainfall data gathered from 58 rain gauges are used. First, a set of rainfall thresholds are defined applying a frequentist method to reconstructed rainfall conditions triggering landslides in the test area. In the second step, several thresholds at different exceedance probabilities are evaluated, and different percentile combinations are selected for the activation of three warning levels. Subsequently, within steps three and four, the issuing of warning levels is based on the comparison, over time and for each combination, between the measured rainfall and the pre-defined warning level thresholds. Finally, the optimal percentile combination to be employed in the regional early warning system is selected evaluating the model performance in terms of success and error indicators by means of the " event, duration matrix, performance " (EDuMaP) method.
Evaluating the impact of climate change on landslide occurrence, hazard, and risk_ from global to regional scale.
Stefano Luigi Gariano (1,2) and Fausto Guzzetti (1), 2017, Evaluating the impact of climate change on landslide occurrence, hazard, and risk_ from global to regional scale.,
European Geosciences Union General Assembly 2017, pp. EGU2017-503–EGU2017-503, Vienna, 23-28/04/2017,
Abstract
According to the fifth report of the Intergovernmental Panel on Climate Change, "warming of the ...
According to the fifth report of the Intergovernmental Panel on Climate Change, "warming of the climate system is unequivocal". The influence of climate changes on slope stability and landslides is also undisputable. Nevertheless, the quantitative evaluation of the impact of global warming, and the related changes in climate, on landslides remains a complex question to be solved. The evidence that climate and landslides act at only partially overlapping spatial and temporal scales complicates the evaluation. Different research fields, including e.g., climatology, physics, hydrology, geology, hydrogeology, geotechnics, soil science, environmental science, and social science, must be considered. Climatic, environmental, demographic, and economic changes are strictly correlated, with complex feedbacks, to landslide occurrence and variation. Thus, a holistic, multidisciplinary approach is necessary.
We reviewed the literature on landslide-climate studies, and found a bias in their geographical distribution, with several studies centered in Europe and North America, and large parts of the world not investigated. We examined advantages and drawbacks of the approaches adopted to evaluate the effects of climate variations on landslides, including prospective modelling and retrospective methods that use landslide and climate records, and paleoenvironmental information. We found that the results of landslide-climate studies depend more on the emission scenarios, the global circulation models, the regional climate models, and the methods to downscale the climate variables, than on the description of the variables controlling slope processes. Using ensembles of projections based on a range of emissions scenarios would reduce (or at least quantify) the uncertainties in the obtained results.
We performed a preliminary global assessment of the future landslide impact, presenting a global distribution of the projected impact of climate change on landslide activity and abundance. Where global warming is expected to increase, the frequency and intensity of severe rainfall events, a primary trigger of shallow, rapid-moving landslides that cause many landslide fatalities, an increase in the number of people exposed to landslide risk is to be expected.
Furthermore, we defined a group of objective and reproducible methods for the quantitative evaluation of the past and future (expected) variations in landslide occurrence and distribution, and in the impact and risk to the population, as a result of changes in climatic and environmental factors (particularly, land use changes), at regional scale. The methods were tested in a southern Italian region, but they can easily applied in other physiographic and climatic regions, where adequate information is available.
Combating Desertification and Land Degradation – Spatial Strategies Using Vegetation. Chapter 5_ Synthesis and Application of Spatial Strategies for Use of Vegetation to Minimise Connectivity.
Hooke J., Sandercock P., Barberá G., Castillo V., Cammeraat L.H., De Baets, Poesen J., Torri D., van Wesemael B., 2017., 2017, Combating Desertification and Land Degradation – Spatial Strategies Using Vegetation. Chapter 5_ Synthesis and Application of Spatial Strategies for Use of Vegetation to Minimise Connectivity.,
Combating Deserti cation and Land Degradation - Spatial Strategies Using Vegetation, edited by Hooke J., Sandercock P., pp. 105–124. Basel_ Springer Basel, 2017,
Abstract
The knowledge that has been acquired in the project RECONDES on critical conditions necessary for ...
The knowledge that has been acquired in the project RECONDES on critical conditions necessary for plants and on the occurrence of such conditions in the landscape is used in combination with the analysis of processes to develop strategies that could be applied at critical points and locations, identi ed by the con- nectivity mapping, to produce greatest effectiveness of the vegetation measures. This is achieved at the plot and land unit scale based on measurements of plant conditions, and at the catchment scale with the analysis of vegetation cover and conditions, both scales involving identi cation of erosion hotspots from connectiv- ity mapping and modelling. These results have provided the framework for recom- mendations on spatial strategies and targeting of revegetation and restoration. The analysis of the effectiveness of different types of plants and species is used to select appropriate plants for different locations in the landscape. This has informed the development of practical guidelines produced for use by land managers and advi- sors. The research was developed in a Mediterranean environment but has wider applicability to drylands prone to erosion by water.
Combating Desertification and Land Degradation – Spatial Strategies Using Vegetation, Chapter 1, Introduction.
Hooke J., Barberá G., Cammeraat L.H., Poesen J., Torri D., and van Wesemael B., 2017, Combating Desertification and Land Degradation – Spatial Strategies Using Vegetation, Chapter 1, Introduction.,
Combating Desertification and Land Degradation - Spatial Strategies Using Vegetation, edited by Hooke J. and Sandercock P., pp. 1–12, 2017,
Abstract
This book explains the methods and results of a major research project, RECONDES, that was ...
This book explains the methods and results of a major research project, RECONDES, that was undertaken to develop strategies of effective use of vegetation to combat desertification and land degradation by water. The research approach combined understanding of the processes of erosion and land degradation with identification of suitable and effective plants and types of vegetation that could be used to decrease the intensity of soil erosion. The project uses the relatively new concept of physical connectivity of water and sediment in the landscape. The premise of the approach is that sediment connectivity can be reduced through the development of vegetation in the flow pathways, and that this approach is more sustainable than the use of physical structures. It required research into the locations and characteristics of these pathways and into properties of suitable plants and species at a range of scales and land units. These components are combined to produce a spatial strategy of use of suitable plants at the most strategic points in the landscape, designed for restoration or mitigation of land degradation. Additional bene ts of use of vegetation as a strategy of sustainable management are outlined. The methods and restoration strategy were developed in relation to the dryland environments of the Mediterranean region of southern Europe, involving field measurements, monitoring and modelling in the study area in Southeast Spain, the driest and most vulnerable region in Europe to desertification.
Landslides, floods and sinkholes in a karst environment_ the 1-6 September 2014 Gargano event, southern Italy
Maria Elena Martinotti1, Luca Pisano2,6, Ivan Marchesini1, Mauro Rossi1, Silvia Peruccacci1,
Maria Teresa Brunetti1, Massimo Melillo1, Giuseppe Amoruso3, Pierluigi Loiacono3, Carmela Vennari2,4, Giovanna Vessia2,5, Maria Trabace3, Mario Parise2,a, and Fausto Guzzetti1, 2017, Landslides, floods and sinkholes in a karst environment_ the 1-6 September 2014 Gargano event, southern Italy,
Natural hazards and earth system sciences (Online) 17 (2017): 467–480. doi_10.5194/nhess-17-467-2017,
DOI: 10.5194%2Fnhess-17-467-2017
Abstract
In karst environments, heavy rainfall is known to cause multiple geohydrological hazards, including inundations, flash ...
In karst environments, heavy rainfall is known to cause multiple geohydrological hazards, including inundations, flash floods, landslides and sinkholes. We studied a period of intense rainfall from 1 to 6 September 2014 in the Gargano Promontory, a karst area in Puglia, southern Italy. In the period, a sequence of torrential rainfall events caused severe damage and claimed two fatalities. The amount and accuracy of the geographical and temporal information varied for the different hazards. The temporal information was most accurate for the inundation caused by a major river, less accurate for flash floods caused by minor torrents and even less accurate for landslides. For sinkholes, only generic information on the period of occurrence of the failures was avail- able. Our analysis revealed that in the promontory, rainfall- driven hazards occurred in response to extreme meteorological conditions and that the karst landscape responded to the torrential rainfall with a threshold behaviour. We exploited the rainfall and the landslide information to design the new ensemble-non-exceedance probability (E-NEP) algorithm for the quantitative evaluation of the possible occurrence of rainfall-induced landslides and of related geo- hydrological hazards. The ensemble of the metrics produced
by the E-NEP algorithm provided better diagnostics than the single metrics often used for landslide forecasting, including rainfall duration, cumulated rainfall and rainfall intensity. We expect that the E-NEP algorithm will be useful for landslide early warning in karst areas and in other similar environments. We acknowledge that further tests are needed to evaluate the algorithm in different meteorological, geological and physiographical settings.
Mapping color fluctuations in the photon in ultraperipheral heavy ion collisions at the Large Hadron Collider
Alvioli M.(1); Frankfurt L.(2); Guzey V.(3); Strikman M.(4); Zhalov M.(3), 2017, Mapping color fluctuations in the photon in ultraperipheral heavy ion collisions at the Large Hadron Collider,
Physics letters. B (Print) 767 (2017): 450–457. doi_10.1016/j.physletb.2017.02.034,
DOI: 10.1016%2Fj.physletb.2017.02.034
Abstract
We model effects of color fluctuations (CFs) in the light-cone photon wave function and for ...
We model effects of color fluctuations (CFs) in the light-cone photon wave function and for the first time
make predictions for the distribution over the number of wounded nucleons ? in the inelastic photon-
nucleus scattering. We show that CFs lead to a dramatic enhancement of this distribution at ? = 1 and
large ? > 10. We also study the implications of different scales and CFs in the photon wave function on
the total transverse energy sum E_T and other observables in inelastic ? A scattering with different triggers.
Our predictions can be tested in proton-nucleus and nucleus-nucleus ultraperipheral collisions at the
LHC and will help to map CFs, whose first indications have already been observed at the LHC.
Dealing with heterogeneous landslide information for landslide susceptibility assessment_ comparing a pixel-based and slope unit-based approach
Liesbet Jacobs (1,2), Matthieu Kervyn (2), Jean Poesen (3), Paola Reichenbach (4), Mauro Rossi (4), Ivan
Marchesini (4), Massimiliano Alvioli (4), Olivier Dewitte (1), 2017, Dealing with heterogeneous landslide information for landslide susceptibility assessment_ comparing a pixel-based and slope unit-based approach,
European Geosciences Union General Assembly 2017, pp. 1–1, Vienna, 23-28/04/2017,
Abstract
In the Rwenzori Mountains, various multi-disciplinary data collection initiatives have resulted in a heterogeneous
database counting ...
In the Rwenzori Mountains, various multi-disciplinary data collection initiatives have resulted in a heterogeneous
database counting 247 fully characterized landslides with known size and shape (polygon dataset) and 307 land-
slides represented as single points taken at an unknown location within the landslide body (point dataset). While
the polygon dataset covers only 9% of the inhabited highlands, the point dataset extends the total inventoried area
to 18% of the entire inhabited highland region. A regional susceptibility model for the total area should therefore
include both information from polygon- as well as point datasets. This involves two distinct methodological chal-
lenges with regard to the use of points and polygons respectively. Firstly, the point dataset, where the location of
the point within the landslide body is unknown, may not be fully representative for the spatial conditions under
which the landslides occurred. Here we aim to identify a robust approach, to limit this uncertainty and maximize
the point location representativeness. For this purpose, a pixel-based approach is tested and compared to a slope
unit-based approach. To mimic the uncertainty related to the localization of the points, 50 random samplings of
single points within each landslide were performed and then fed into a logistic regression model. The model was
thus run 50 times using both the slope unit-based and the pixel-based approach. The results show that the slope
unit-based alternative has an overall better performance than the pixel-based with comparable stability over the
runs. Based on these results, the slope unit seems a more appropriate mapping unit for a susceptibility model based
on point-data. A second significant methodological issue, when using polygon-based models, concerns the decision
on when a slope unit is considered to be landslide-prone. A threshold representing the fraction of the slope unit
affected by landslides above which a slope unit is assigned to be landslide-prone is often used for this purpose. The
selection of this threshold is a trade-off: the larger the threshold, the more slope units also containing landslides are
considered safe, while a small threshold will give more weight to mapping errors of landslide polygons exceeding
slope unit boundaries. Here, five different thresholds ranging from 0.0005 to 0.05 are compared with the repeated
random sampling described above. A threshold of 0.001 was found to provide the best model performances, while
the random sampling approach performed better than the models based on thresholds larger than 0.001. This shows
that a threshold approach can produce the best model performances only if an optimal threshold selection is per-
formed. Based on these findings, a regional slope unit-based model was (i) calibrated using landslide polygon data
and performing an optimal threshold selection and (ii) validated using the point-data achieving an AUCROC of 0.69.
This experiment shows that although pixel-based susceptibility mapping is by far the most common statis-
tical approach, slope unit-based modelling can represent a more powerful approach especially when dealing with
landslide point-data or a heterogeneous combination of point- and polygon data.
Daily precipitation estimation through different microwave sensors_ Verification study over Italy
Ciabatta L.; Marra A.C.; Panegrossi G.; Casella D.; Sano P.; Dietrich S.; Massari C.; Brocca L., 2017, Daily precipitation estimation through different microwave sensors_ Verification study over Italy,
Journal of hydrology (Amst.) 545 (2017): 436–450. doi_10.1016/j.jhydrol.2016.12.057,
DOI: 10.1016%2Fj.jhydrol.2016.12.057
Abstract
The accurate estimation of rainfall from remote sensing is of paramount importance for many applications ...
The accurate estimation of rainfall from remote sensing is of paramount importance for many applications as, for instance, the mitigation of natural hazards like floods, droughts, and landslides. Traditionally, microwave observations in the frequency between 10 and 183 GHz are used for estimating rainfall based on the direct interaction of radiation with the hydrometeors within precipitating clouds in a so-called top-down approach. Recently, a bottom-up approach was proposed that uses satellite soil moisture products derived from microwave observations (<10 GHz) for the estimation of accumulated rainfall amounts. The integration of the bottom-up and top-down approaches has large potential for providing high accurate rainfall estimates exploiting their different and complementary nature. In this study, we perform a long-term (3 years) assessment of different satellite rainfall products exploiting the full range of microwave frequencies over Italy. Specifically, the integration of two top-down algorithms (CDRD, Cloud Dynamics and Radiation Database, and PNPR, Passive microwave Neural network Precipitation Retrieval) for estimating rainfall from conically and cross-track scanning radiometers, and one bottom-up algorithm (SM2RAIN) applied to the Advanced SCATterometer soil moisture product is carried out. The performances of the products, individually and merged together, are assessed at daily time scale. The integration of top-down and bottom-up approaches provides the highest performance both in terms of continuous and categorical scores (i.e., median correlation coefficient and root mean square error values equal to 0.71 and 6.62 mm, respectively). In such a combination, the limitations of the two approaches are compensated allowing a better estimation of ground accumulated rainfall through SM2RAIN while, overcoming the limitations of rainfall estimation for intense events during wet conditions through CDRD-PNPR product. The accuracy and the reliability of the merged product open new possibilities for their testing in hydrological applications, such as the monitoring and prediction of floods and droughts over large areas, including regions where ground-based measurements are sparse or not available.
Long-term patterns of change in a vanishing cultural landscape_ a GIS-based assessment.
Amici V., Maccherini S., Santi E., Torri D., Vergari F., Del Monte M.,, 2017, Long-term patterns of change in a vanishing cultural landscape_ a GIS-based assessment.,
Ecological informatics (Print) 37 (2017): 38–51. doi_10.1016/j.ecoinf.2016.11.008,
DOI: 10.1016%2Fj.ecoinf.2016.11.008
Abstract
The specific patterns of land use change that can be observed in many economically developed ...
The specific patterns of land use change that can be observed in many economically developed countries have fundamental implications on landscape structure and geomorphological processes. Areas characterized by widespread erosion such as badlands are often sensitive to anthropic modifications and of large interest in the analysis of the topographic determinants of land use change. This work aims to analyse the land use and landscape structure changes occurred in a Mediterranean landscape by analysing historical maps and infer the underlying processes that contribute to the pattern of change. First we carried out a comparative examination of three historical image datasets (1820, 1954, 2005) through overlay image processing and cross- classification analysis. Then we analysed the relationships between the detected land-use transformations and topographic parameters. Finally we determined the landscape structure change patterns through the use of GIS-based landscape metrics. The results showed how the study areas have experienced significant land use changes, mainly due to the abandonment of traditional rural systems. We found semi-natural areas distribution to be closely connected with terrain-shaping processes. The processes that underlie the multi-temporal landscape structure change have produced an overall increase of the landscape complexity. The work is one of the first attempts to use historical cartographic data to quantitatively assess changes in land use and landscape structure in the Mediterranean area. The proposed integrated methodology can support decision-making landscape planning and may represent a useful tool to define effective strategies for biodiversity conservation.
Exploring the effects of seismicity on landslides and catchment sediment yield_ An Italian case study
Vanmaercke M.; Ardizzone F.; Rossi M.; Guzzetti F., 2017, Exploring the effects of seismicity on landslides and catchment sediment yield_ An Italian case study,
Geomorphology (Amst.) 278 (2017): 171–183. doi_10.1016/j.geomorph.2016.11.010,
DOI: 10.1016%2Fj.geomorph.2016.11.010
Abstract
Recent studies showed that contemporary average catchment sediment yields (SY, [t km- 2 y- 1]) ...
Recent studies showed that contemporary average catchment sediment yields (SY, [t km- 2 y- 1]) at regional and continental scales are often strongly correlated to spatial patterns of seismic activity. Nonetheless, we currently have little insights into the mechanisms that explain these correlations. We investigated how spatial patterns of SY in Italy are linked to patterns of seismic activity. For a dataset of 103 Italian catchments with average SY measured over a period of years to decades, we extracted tectonic and none-tectonic variables that potentially explain observed differences in SY. These include proxies for vertical uplift rates and cumulative seismic moments (CSM) associated with historic earthquakes of different ranges of magnitude. Results showed that also across Italy, SY is significantly correlated to seismicity. However, SY showed much stronger correlations with proxies of seismicity relating to small but frequent earthquakes (2 <= Mw b 4) than with proxies relating to tectonic uplift or large, potentially landslide-triggering earthquakes (Mw >= 4). Analyses of a dataset of about 500,000 landslides across Italy showed very comparable trends_ spatial patterns of landslides within similar lithological units gener- ally show a significant positive correlation with CSM of weak but frequent seismicity and generally not with CSM of large earthquakes. These results suggest that, on a decadal time scale and at a regional/continental spatial scale, frequent but relatively weak seismicity may exert a more important geomorphic impact than large earthquake events or tectonic uplift.
A reliable rainfall-runoff model for flood forecasting_ review and application to a semiurbanized watershed at high flood risk in Italy
Masseroni, D., Cislaghi, A., Camici, S., Massari, C., Brocca, L., 2017, A reliable rainfall-runoff model for flood forecasting_ review and application to a semiurbanized watershed at high flood risk in Italy,
Hydrology research (Online) (2017): 726–740. doi_10.2166/nh.2016.037,
Abstract
Many rainfall-runoff (RR) models are available in the scientific literature. Selecting the best structure and ...
Many rainfall-runoff (RR) models are available in the scientific literature. Selecting the best structure and parameterization for a model is not straightforward and depends on a broad number of factors, including climatic conditions, catchment characteristics, temporal/spatial resolution and model objectives. In this study, the RR model 'Modello Idrologico Semi-Distribuito in continuo' (MISDc), mainly developed for flood simulation in Mediterranean basins, was tested on the Seveso basin, which is stressed several times a year by flooding events mainly caused by excessive urbanization. The work summarizes a compendium of the MISDc applications over a wide range of catchments in European countries and then it analyses the performances over the Seveso basin. The results show a good fit behaviour during both the calibration and the validation periods with a Nash-Sutcliffe coefficient index larger than 0.9. Moreover, the median volume and peak discharge errors calculated on several flood events were less than 25%. In conclusion, we can be assured that the reliability and computational speed could make the MISDc model suitable for flood estimation in many catchments of different geographical contexts and land use characteristics. Moreover, MISDc will also be useful for future support of real-time decision-making for flood risk management in the Seveso basin.
Large-area landslide susceptibility with optimized slope-units
Massimiliano Alvioli, Ivan Marchesini, Paola Reichenbach, Mauro Rossi, Francesca Ardizzone, Federica
Fiorucci, Fausto Guzzetti, 2017, Large-area landslide susceptibility with optimized slope-units,
European Geosciences Union General Assembly 2017, pp. 1–1, Vienna, 23-28/04/2017,
Abstract
A Slope-Unit (SU) is a type of morphological terrain unit bounded by drainage and divide ...
A Slope-Unit (SU) is a type of morphological terrain unit bounded by drainage and divide lines that maximize the
within-unit homogeneity and the between-unit heterogeneity across distinct physical and geographical boundaries
[1]. Compared to other terrain subdivisions, SU are morphological terrain unit well related to the natural (i.e.,
geological, geomorphological, hydrological) processes that shape and characterize natural slopes. This makes SU
easily recognizable in the field or in topographic base maps, and well suited for environmental and geomorpholog-
ical analysis, in particular for landslide susceptibility (LS) modelling.
An optimal subdivision of an area into a set of SU depends on multiple factors_ size and complexity of the study
area, quality and resolution of the available terrain elevation data, purpose of the terrain subdivision, scale and
resolution of the phenomena for which SU are delineated.
We use the recently developed r.slopeunits software [2,3] for the automatic, parametric delineation of SU within
the open source GRASS GIS based on terrain elevation data and a small number of user-defined parameters.
The software provides subdivisions consisting of SU with different shapes and sizes, as a function of the input
parameters.
In this work, we describe a procedure for the optimal selection of the user parameters through the production of
a large number of realizations of the LS model. We tested the software and the optimization procedure in a 2,000
km2 area in Umbria, Central Italy.
For LS zonation we adopt a logistic regression model implemented in an well-known software [4,5], using about
50 independent variables. To select the optimal SU partition for LS zonation, we want to define a metric which
is able to quantify simultaneously_ (i) slope-unit internal homogeneity (ii) slope-unit external heterogeneity (iii)
landslide susceptibility model performance. To this end, we define a comprehensive objective function S, as the
product of three normalized objective functions dealing with the points (i)-(ii)-(iii) independently. We use an intra-
segment variance function V, the Moran's autocorrelation index I and the AUCROC function R arising from the
application of the logistic regression model. Maximization of the objective function S = f(I,V,R) as a function
of the r.slopeunits input parameters provides an objective and reproducible way to select the optimal parameter
combination for a proper SU subdivision for LS modelling.
We further perform an analysis of the statistical significance of the LS models as a function of the r.slopeunits
input parameters, focusing on the degree of coarseness of each subdivision. We find that the LRM, when applied
to subdivisions with large average SU size, has a very poor statistical significance, resulting in only few (5%,
typically lithological) variables being used in the regression due to the large heterogeneity of all variables within
each unit, while up to 35% of the variables are used when SU are very small. This behavior was largely expected
and provides further evidence that an objective method to select SU size is highly desirable.
[1] Guzzetti, F. et al., Geomorphology 31, (1999) 181-216
[2] Alvioli, M. et al., Geoscientific Model Development 9 (2016), 3975-3991
[3] http_//geomorphology.irpi.cnr.it/tools/slope-units
[4] Rossi, M. et al., Geomorphology 114, (2010) 129-142
[5] Rossi, M. and Reichenbach, P., Geoscientific Model Development 9 (2016), 3533-3543
A reappraisal of bridge piers scour vulnerability_ a case study in the Upper Tiber River basin (central Italy)
S. Barbetta, S. Camici and T. Moramarco, 2017, A reappraisal of bridge piers scour vulnerability_ a case study in the Upper Tiber River basin (central Italy),
Journal of flood risk management (2017). doi_10.1111/jfr3.12130,
DOI: 10.1111%2Fjfr3.12130
Abstract
The issue of bridge piers vulnerability to scour is addressed by comparing two
procedures. The first ...
The issue of bridge piers vulnerability to scour is addressed by comparing two
procedures. The first method quantifies the Scour Vulnerability Index (SVI)
considering the combined effects of local and contraction scour. The method
requires that a scale factor, for taking account of the scour depth overestimation
provided by empirical formulae, is quantified for the selected case study through
inspection campaigns. The second approach identifies a vulnerability index to
vertical instability depending on several indicators. The study is carried out for
a sample of 46 bridges in the Tiber River basin, central Italy, and shows that the
two methods identify the same number of piers affected by 'high' vulnerability.
Results are supplemented by outcomes of inspections that identified, through
the scale factor, a high correlation between measured scour depth and SVI value.
SVI, simpler and most practical, seems useful for an expeditious estimate of
scour vulnerability in large areas and can be adopted by decision makers to
identify the structures requiring attention in terms of maintenance and control.
The presented results do not provide a general rule for a correct estimate of
scour. They refer to solely the investigated case study and need to be verified in
other rivers context.
Sm2Rain-Cci (1 Jan 1998 – 31 December 2015) Global Daily Rainfall Dataset
Ciabatta, Luca, Massari, Christian, Brocca, Luca, Gruber, Alexander, Reimer, Christoph, Hahn, Sebastian, Paulik, Christoph, Dorigo, Wouter, Kidd, Richard, Wagner, Wolfgang, 2017, Sm2Rain-Cci (1 Jan 1998 – 31 December 2015) Global Daily Rainfall Dataset,
2017,
Abstract
A NEW GLOBAL SCALE RAINFALL PRODUCT obtained from satellite soil moisture data through the SM2RAIN ...
A NEW GLOBAL SCALE RAINFALL PRODUCT obtained from satellite soil moisture data through the SM2RAIN algorithm (Brocca et al., 2014), at 0.25 degree/daily spatial-temporal resolution, has been delivered (Ciabatta et al., 2018). The SM2RAIN method was applied to the ESA CCI soil moisture Active and Passive products (Liu et al., 2011, 2012; Wagner et al., 2012) for the period from January 1998 to December 2015 (18 years).
The CCI-derived rainfall datasets (in mm/day) is gridded over a 0.25-degree grid on a global scale. The number of dates is 6574 (1998/01/01 - 2015/12/31). The product represents the cumulated rainfall between the 00_00 and the 23_59 UTC of the indicated day. A climatological correction has been applied to the data at monthly scale.
The rainfall dataset is provided in netCDF format. A total of 18 netCDF files, one per year, are provided.
The rainfall dataset is obtained by applying the SM2RAIN algorithm to the ESA CCI soil moisture Active and Passive products at version 03.1 separately. Then, an integration procedure based on a weighted average is applied in order to obtain the rainfall estimate. The algorithm has been calibrated during three different periods (1998-2001, 2002-2006 and 2007-2013) against the Global Precipitation Climatology Centre Full-Data daily dataset (GPCC-FDD, Schamm et al., 2015). The quality flag provided within the raw soil moisture observations has been used to mask out low quality data, as well as the areas characterized by high topographic complexity, high frozen soil and snow probability and presence of tropical forests.
SISMA 2016 – Relazione di sopralluogo nel comune di Mogliano, parcheggio camper
Francesca Ardizzone, Michele Santangelo, 2016, SISMA 2016 – Relazione di sopralluogo nel comune di Mogliano, parcheggio camper,
13 dicembre 2016, pp.1–6, 2016,
Abstract
Provincia: MACERATA
Comune_ Mogliano
Indirizzo/Località Parcheggio Camper. Vedi Figura 1 e figura 2.
Coordinate geografiche (WGS 84 lon/lat ...
Provincia: MACERATA
Comune_ Mogliano
Indirizzo/Località Parcheggio Camper. Vedi Figura 1 e figura 2.
Coordinate geografiche (WGS 84 lon/lat in formato sessagesimale):
13°28'52.5"/E43°11'06.7"N
SISMA 2016 – Relazione di sopralluogo nel comune di Mogliano, campo sportivo
Francesca Ardizzone, Michele Santangelo, 2016, SISMA 2016 – Relazione di sopralluogo nel comune di Mogliano, campo sportivo,
13 dicembre 2016, pp.1–5, 2016,
Abstract
Provincia: MACERATA
Comune_ Mogliano
Indirizzo/Località Campo sportivo. Vedi figura 1 e figura 2.
Coordinate geografiche (WGS 84 lon/lat ...
Provincia: MACERATA
Comune_ Mogliano
Indirizzo/Località Campo sportivo. Vedi figura 1 e figura 2.
Coordinate geografiche (WGS 84 lon/lat in formato sessagesimale):
13°29'06.46"/E 43°10'17.38"N
SISMA 2016 – Relazione di sopralluogo nel territorio del comune di Mogliano – campo sportivo ex seminario
Francesca Ardizzone, Michele Santangelo, 2016, SISMA 2016 – Relazione di sopralluogo nel territorio del comune di Mogliano – campo sportivo ex seminario,
13 dicembre 2016, pp.1–5, 2016,
Abstract
Provincia: MACERATA
Comune_ Mogliano
Indirizzo/Località Campo sportivo ex-seminario. Vedi figura 1 e figura 2.
Coordinate geografiche (WGS 84 ...
Provincia: MACERATA
Comune_ Mogliano
Indirizzo/Località Campo sportivo ex-seminario. Vedi figura 1 e figura 2.
Coordinate geografiche (WGS 84 lon/lat in formato sessagesimale):
13°28'25.25"/E 43°11'0.30"N
SISMA 2016 – Relazione di sopralluogo nel Comune di Monte San Martino
Francesca Ardizzone, Michele Santangelo, 2016, SISMA 2016 – Relazione di sopralluogo nel Comune di Monte San Martino,
13 dicembre 2016, pp.1–7, 2016,
Abstract
Provincia: MACERATA
Comune_ Monte San Martino
Indirizzo/Località Campo sportivo. Vedi figura 1 e figura 2.
Coordinate geografiche (WGS ...
Provincia: MACERATA
Comune_ Monte San Martino
Indirizzo/Località Campo sportivo. Vedi figura 1 e figura 2.
Coordinate geografiche (WGS 84 lon/lat in formato sessagesimale):
13°27'16.32"/E 43°01'31.38"N
SISMA 2016 – Relazione di sopralluogo nel comune di Muccia
Paola Salvati, Michele Santangelo, 2016, SISMA 2016 – Relazione di sopralluogo nel comune di Muccia,
24 novembre 2016, pp.1–8, 2016,
Abstract
Provincia: MACERATA
Comune_ Muccia
Indirizzo/Località: Muccia, via delle piane (Figura 1).
Coordinate geografiche (WGS 84 lon/lat in formato ...
Provincia: MACERATA
Comune_ Muccia
Indirizzo/Località: Muccia, via delle piane (Figura 1).
Coordinate geografiche (WGS 84 lon/lat in formato sessagesimale):
43°04'47"N - 13°02'48"E
SISMA 2016 – Relazione di sopralluogo in località Vallicelle, comune di Camerino
Paola Salvati, Michele Santangelo, 2016, SISMA 2016 – Relazione di sopralluogo in località Vallicelle, comune di Camerino,
24 novembre 2016, pp.1–6, 2016,
Abstract
Provincia: MACERATA
Comune_ Camerino
Indirizzo/Località: Camerino, Vallicelle (Figura 1).
Coordinate geografiche (WGS 84 lat/lon in formato sessagesimale):
43°07'47"N - ...
Provincia: MACERATA
Comune_ Camerino
Indirizzo/Località: Camerino, Vallicelle (Figura 1).
Coordinate geografiche (WGS 84 lat/lon in formato sessagesimale):
43°07'47"N - 13°04'11"E
Data from https://intranet.cnr.it/people/
