Articles | Volume 7, issue 2
Development and technical paper 25 Mar 2014
Development and technical paper | 25 Mar 2014
Improving predictive power of physically based rainfall-induced shallow landslide models: a probabilistic approach
S. Raia et al.
No articles found.
Nat. Hazards Earth Syst. Sci., 21, 1467–1471,Short summary
This is a perspective based on personal experience on whether a large number of landslides caused by a single trigger (e.g. an earthquake, an intense rainfall, a rapid snowmelt event) or by multiple triggers in a period can be predicted, in space and time, considering the consequences of slope failures.
Giuseppe Esposito, Ivan Marchesini, Alessandro Cesare Mondini, Paola Reichenbach, Mauro Rossi, and Simone Sterlacchini
Nat. Hazards Earth Syst. Sci., 20, 2379–2395,Short summary
In this article, we present an automatic processing chain aimed to support the detection of landslides that induce sharp land cover changes. The chain exploits free software and spaceborne SAR data, allowing the systematic monitoring of wide mountainous regions exposed to mass movements. In the test site, we verified a general accordance between the spatial distribution of seismically induced landslides and the detected land cover changes, demonstrating its potential use in emergency management.
Jalal Samia, Arnaud Temme, Arnold Bregt, Jakob Wallinga, Fausto Guzzetti, and Francesca Ardizzone
Nat. Hazards Earth Syst. Sci., 20, 271–285,Short summary
For the Collazzone study area in Italy, we quantified how much landslides follow others using Ripley's K function, finding that susceptibility is increased within 60 m and 17 years after a previous landslide. We then calculated the increased susceptibility for every pixel and for the 17-time-slice landslide inventory. We used these as additional explanatory variables in susceptibility modelling. Model performance increased substantially with this landslide history component included.
Michele Santangelo, Massimiliano Alvioli, Marco Baldo, Mauro Cardinali, Daniele Giordan, Fausto Guzzetti, Ivan Marchesini, and Paola Reichenbach
Nat. Hazards Earth Syst. Sci., 19, 325–335,Short summary
The paper discusses the use of rockfall modelling software and photogrammetry applied to images acquired by RPAS to provide support to civil protection agencies during emergency response. The paper focuses on a procedure that was applied to define the residual rockfall risk for a road that was hit by an earthquake-triggered rockfall that occurred during the seismic sequence that hit central Italy on 24 August 2016. Road reopening conditions were decided based on the results of this study.
Txomin Bornaetxea, Mauro Rossi, Ivan Marchesini, and Massimiliano Alvioli
Nat. Hazards Earth Syst. Sci., 18, 2455–2469,Short summary
While producing a landslide susceptibility map using a fieldwork-based landslide inventory and a logistic regression model, two crucial questions came to our minds. (i) Shall we consider unsurveyed regions of the study area, for which landslide absence is typically assumed? (ii) Which reference mapping unit should be used in our model? So we compared four maps and found that rejecting unsurveyed regions together with slope units as reference mapping unit should be the best option.
Anna Roccati, Francesco Faccini, Fabio Luino, Laura Turconi, and Fausto Guzzetti
Nat. Hazards Earth Syst. Sci., 18, 2367–2386,Short summary
Natural instability processes are very common. Almost every year, landslides, mud flows and debris flows in the Alpine and Apennine areas and flooding in the Po flood plain cause severe damage to structures and infrastructure and often claim human lives. Geology researchers collect thousands of rain data and process them to try the most precise prediction about the triggering of superficial landslides in order to mitigate the risk and safeguard human goods and lives.
Federica Fiorucci, Daniele Giordan, Michele Santangelo, Furio Dutto, Mauro Rossi, and Fausto Guzzetti
Nat. Hazards Earth Syst. Sci., 18, 405–417,Short summary
This paper describes the criteria for the optimal selection of remote sensing images to map event landslides, discussing the ability of monoscopic and stereoscopic VHR satellite images and ultra-high-resolution UAV images to resolve the landslide photographical and morphological signatures. The findings can be useful to decide on the optimal imagery and technique to be used when planning the production of a landslide inventory map.
Liesbet Jacobs, Olivier Dewitte, Jean Poesen, John Sekajugo, Adriano Nobile, Mauro Rossi, Wim Thiery, and Matthieu Kervyn
Nat. Hazards Earth Syst. Sci., 18, 105–124,Short summary
While country-specific, continental and global susceptibility maps are increasingly available, local and regional susceptibility studies remain rare in remote and data-poor settings. Here, we provide a landslide susceptibility assessment for the inhabited region of the Rwenzori Mountains. We find that higher spatial resolutions do not necessarily lead to better models and that models built for local case studies perform better than aggregated susceptibility assessments on the regional scale.
Francesco Marra, Elisa Destro, Efthymios I. Nikolopoulos, Davide Zoccatelli, Jean Dominique Creutin, Fausto Guzzetti, and Marco Borga
Hydrol. Earth Syst. Sci., 21, 4525–4532,Short summary
Previous studies have reported a systematic underestimation of debris flow occurrence thresholds, due to the use of sparse networks in non-stationary rain fields. We analysed high-resolution radar data to show that spatially aggregated estimates (e.g. satellite data) largely reduce this issue, in light of a reduced estimation variance. Our findings are transferable to other situations in which lower envelope curves are used to predict point-like events in the presence of non-stationary fields.
Maria Elena Martinotti, Luca Pisano, Ivan Marchesini, Mauro Rossi, Silvia Peruccacci, Maria Teresa Brunetti, Massimo Melillo, Giuseppe Amoruso, Pierluigi Loiacono, Carmela Vennari, Giovanna Vessia, Maria Trabace, Mario Parise, and Fausto Guzzetti
Nat. Hazards Earth Syst. Sci., 17, 467–480,Short summary
We studied a period of torrential rain between 1 and 6 September 2014 in the Gargano Promontory, Puglia, southern Italy, which caused a variety of geohydrological hazards, including landslides, flash floods, inundations and sinkholes. We used the rainfall and the landslide information available to us to design and test the new ensemble – non-exceedance probability (E-NEP) algorithm for the quantitative evaluation of the probability of the occurrence of rainfall-induced landslides.
Massimiliano Alvioli, Ivan Marchesini, Paola Reichenbach, Mauro Rossi, Francesca Ardizzone, Federica Fiorucci, and Fausto Guzzetti
Geosci. Model Dev., 9, 3975–3991,Short summary
Slope units are morphological mapping units bounded by drainage and divide lines that maximize within-unit homogeneity and between-unit heterogeneity. We use r.slopeunits, a software for the automatic delination of slope units. We outline an objective procedure to optimize the software input parameters for landslide susceptibility (LS) zonation. Optimization is achieved by maximizing an objective function that simultaneously evaluates terrain aspect segmentation quality and LS model performance.
Mauro Rossi and Paola Reichenbach
Geosci. Model Dev., 9, 3533–3543,Short summary
Landslide susceptibility maps show places where landslides may occur in the future. These maps are prepared using different approaches, information on past landslides distribution and a variety of geo-environmental data. The paper describes LAND-SE (LANDslide Susceptibility Evaluation), an open-source software coded in R for statistically based susceptibility zonation that provides estimates of model performances and uncertainty. A user guide and example data are distributed with the software.
Roberta Paranunzio, Francesco Laio, Marta Chiarle, Guido Nigrelli, and Fausto Guzzetti
Nat. Hazards Earth Syst. Sci., 16, 2085–2106,Short summary
We provide the results of the joint analysis of the main climate variables and spatiotemporal distribution of 41 rockfalls that occurred in the Italian Alps between 1997 and 2013 in the absence of an evident trigger. We compared the meteorological conditions preceding the failures with the historical datasets, to determine if rockfall initiation was associated with some climatic anomaly. We found out that temperature anomalies were associated with rockfall occurrence in 83 % of our case studies.
Paola Salvati, Umberto Pernice, Cinzia Bianchi, Ivan Marchesini, Federica Fiorucci, and Fausto Guzzetti
Nat. Hazards Earth Syst. Sci., 16, 1487–1497,Short summary
We designed the POLARIS website to communicate to a broader audience information on geohydrological (landslide and flood) hazards with potential consequences to the population. POLARIS publishes periodic reports, analyses of specific damaging events and blog posts. POLARIS can help multiple audiences understand how risks can be reduced through appropriate measures and behaviours, contributing to increasing the resilience of the population to geohydrological risk.
S. L. Gariano, O. Petrucci, and F. Guzzetti
Nat. Hazards Earth Syst. Sci., 15, 2313–2330,Short summary
We study temporal and geographical variations in the occurrence of 1466 rainfall-induced landslides in Calabria, southern Italy, in the period 1921–2010. To evaluate the impact on the population, we compare the number of rainfall-induced landslides with the size of population in the 409 municipalities in Calabria. We find variations in yearly and geographical distribution of rainfall-induced landslides, variations in rainfall triggering conditions, and changes in the impact on the population.
M. Santangelo, I. Marchesini, F. Bucci, M. Cardinali, F. Fiorucci, and F. Guzzetti
Nat. Hazards Earth Syst. Sci., 15, 2111–2126,Short summary
In this work, we present a new semi-automatic procedure to prepare landslide inventory maps that uses GIS applications and tools for the digitization of photo-interpreted data. Results show that the new semi-automatic procedure proves more efficient for the production of landslide inventories and results in the production of more accurate maps, compared to the manual procedure. The presented work has potential consequences for multiple applications of landslide studies.
M. Mergili, I. Marchesini, M. Alvioli, M. Metz, B. Schneider-Muntau, M. Rossi, and F. Guzzetti
Geosci. Model Dev., 7, 2969–2982,Short summary
The article deals with strategies to (i) reduce computation time and to (ii) appropriately account for uncertain input parameters when applying an open source GIS sliding surface model to estimate landslide susceptibility for a 90km² study area in central Italy. For (i), the area is split into a large number of tiles, enabling the exploitation of multi-processor computing environments. For (ii), the model is run with various parameter combinations to compute the slope failure probability.
P. Salvati, C. Bianchi, F. Fiorucci, P. Giostrella, I. Marchesini, and F. Guzzetti
Nat. Hazards Earth Syst. Sci., 14, 2589–2603,
G. Vessia, M. Parise, M. T. Brunetti, S. Peruccacci, M. Rossi, C. Vennari, and F. Guzzetti
Nat. Hazards Earth Syst. Sci., 14, 2399–2408,
I. Marchesini, F. Ardizzone, M. Alvioli, M. Rossi, and F. Guzzetti
Nat. Hazards Earth Syst. Sci., 14, 2215–2231,
B. Merz, J. Aerts, K. Arnbjerg-Nielsen, M. Baldi, A. Becker, A. Bichet, G. Blöschl, L. M. Bouwer, A. Brauer, F. Cioffi, J. M. Delgado, M. Gocht, F. Guzzetti, S. Harrigan, K. Hirschboeck, C. Kilsby, W. Kron, H.-H. Kwon, U. Lall, R. Merz, K. Nissen, P. Salvatti, T. Swierczynski, U. Ulbrich, A. Viglione, P. J. Ward, M. Weiler, B. Wilhelm, and M. Nied
Nat. Hazards Earth Syst. Sci., 14, 1921–1942,
A. Manconi, F. Casu, F. Ardizzone, M. Bonano, M. Cardinali, C. De Luca, E. Gueguen, I. Marchesini, M. Parise, C. Vennari, R. Lanari, and F. Guzzetti
Nat. Hazards Earth Syst. Sci., 14, 1835–1841,
A. C. Mondini, A. Viero, M. Cavalli, L. Marchi, G. Herrera, and F. Guzzetti
Nat. Hazards Earth Syst. Sci., 14, 1749–1759,
C. Vennari, S. L. Gariano, L. Antronico, M. T. Brunetti, G. Iovine, S. Peruccacci, O. Terranova, and F. Guzzetti
Nat. Hazards Earth Syst. Sci., 14, 317–330,
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Lele Shu, Paul A. Ullrich, and Christopher J. Duffy
Geosci. Model Dev., 13, 2743–2762,Short summary
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Harsh Beria, Joshua R. Larsen, Anthony Michelon, Natalie C. Ceperley, and Bettina Schaefli
Geosci. Model Dev., 13, 2433–2450,Short summary
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Andrew J. Newman and Martyn P. Clark
Geosci. Model Dev., 13, 1827–1843,Short summary
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Zhen Yin, Sebastien Strebelle, and Jef Caers
Geosci. Model Dev., 13, 651–672,Short summary
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Thomas Bueche, Marko Wenk, Benjamin Poschlod, Filippo Giadrossich, Mario Pirastru, and Mark Vetter
Geosci. Model Dev., 13, 565–580,Short summary
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Christopher B. Marsh, John W. Pomeroy, and Howard S. Wheater
Geosci. Model Dev., 13, 225–247,Short summary
The Canadian Hydrological Model (CHM) is a next-generation distributed model. Although designed to be applied generally, it has a focus for application where cold-region processes, such as snowpacks, play a role in hydrology. A key feature is that it uses a multi-scale surface representation, increasing efficiency. It also enables algorithm comparisons in a flexible structure. Model philosophy, design, and several cold-region-specific examples are described.
Ganquan Mao and Junguo Liu
Geosci. Model Dev., 12, 5267–5289,
Mattia Zaramella, Marco Borga, Davide Zoccatelli, and Luca Carturan
Geosci. Model Dev., 12, 5251–5265,Short summary
This paper presents TOPMELT, a parsimonious snowpack simulation model integrated into a basin-scale hydrological model. TOPMELT implements the full spatial distribution of clear-sky potential solar radiation by means of a statistical representation: this approach reduces computational burden, which is a key potential advantage when parameter sensitivity and uncertainty estimation procedures are carried out. The model is assessed by examining different resolutions of its domain.
Rui Wu, Lei Yang, Chao Chen, Sajjad Ahmad, Sergiu M. Dascalu, and Frederick C. Harris Jr.
Geosci. Model Dev., 12, 4115–4131,Short summary
The paper mainly has two contributions. First, a post-processor framework is proposed to improve hydrologic model accuracy. The key is to characterize possible connections between model inputs and errors. Based on results, it is also possible to replace the time-consuming model calibration step using our post-processor framework. Second, a window selection method is proposed to handle nonstationary data. A window size is chosen containing stable data using a measure named
DSproposed by us.
Geosci. Model Dev., 12, 4061–4073,Short summary
This paper presents a new model code that can be used to date the flow of hot fluids in the crust and the age of hot springs. It does so by modelling the thermal effects of fluid flow in the subsurface and by comparing the results with low-temperature thermochronology, which is a widely used method to quantify the temperature history of minerals and rocks. The model also demonstrates the effects of the depth and angle of permeable faults on temperatures of hot springs.
Jiali Wang, Cheng Wang, Vishwas Rao, Andrew Orr, Eugene Yan, and Rao Kotamarthi
Geosci. Model Dev., 12, 3523–3539,Short summary
WRF-Hydro needs to be calibrated to optimize its output with respect to observations. However, when applied to a relatively large domain, both WRF-Hydro simulations and calibrations require intensive computing resources and are best performed in parallel. This study ported an independent calibration tool (parameter estimation tool – PEST) to high-performance computing clusters and adapted it to work with WRF-Hydro. The results show significant speedup for model calibration.
Brendan Alexander Harmon, Helena Mitasova, Anna Petrasova, and Vaclav Petras
Geosci. Model Dev., 12, 2837–2854,Short summary
The numerical model, r.sim.terrain, simulates how overland flows of water and sediment shape topography over short periods of time. We tested the model by comparing runs of the simulation against a time series of airborne lidar surveys for our study landscape. Through these tests, we demonstrated that the model can simulate gully evolution including processes such as channel incision, channel widening, and the development of scour pits, rills, and depositional ridges.
Elena Shevnina and Andrey Silaev
Geosci. Model Dev., 12, 2767–2780,Short summary
The paper provides a theory and assumptions behind an advance of frequency analysis (AFA) approach in long-term hydrological forecasting. In this paper, a new core of the probabilistic hydrological model MARkov Chain System (MARCSHYDRO) was introduced, together with the code and an example of a climate-scale prediction of an exceedance probability curve of river runoff with low computational costs.
Ting Sun and Sue Grimmond
Geosci. Model Dev., 12, 2781–2795,Short summary
A Python-enhanced urban land surface model, SuPy (SUEWS in Python), is presented with its development (the SUEWS interface modification, F2PY configuration and Python frontend implementation), cross-platform deployment (PyPI, Python Package Index) and demonstration (online tutorials in Jupyter notebooks for users of different levels). SuPy represents a significant enhancement that supports existing and new model applications, reproducibility and enhanced functionality.
Stephan Thober, Matthias Cuntz, Matthias Kelbling, Rohini Kumar, Juliane Mai, and Luis Samaniego
Geosci. Model Dev., 12, 2501–2521,Short summary
We present a model that aggregates simulated runoff along a river (i.e. a routing model). The unique feature of the model is that it can be run at multiple resolutions without any modifications to the input data. The model internally (dis-)aggregates all input data to the resolution given by the user. The model performance does not depend on the chosen resolution. This allows efficient model calibration at coarse resolution and subsequent model application at fine resolution.
Wouter J. M. Knoben, Jim E. Freer, Keirnan J. A. Fowler, Murray C. Peel, and Ross A. Woods
Geosci. Model Dev., 12, 2463–2480,Short summary
Computer models are used to predict river flows. A good model should represent the river basin to which it is applied so that flow predictions are as realistic as possible. However, many different computer models exist, and selecting the most appropriate model for a given river basin is not always easy. This study combines computer code for 46 different hydrological models into a single coding framework so that models can be compared in an objective way and we can learn about model differences.
Robert Reinecke, Laura Foglia, Steffen Mehl, Tim Trautmann, Denise Cáceres, and Petra Döll
Geosci. Model Dev., 12, 2401–2418,Short summary
G³M is a new global groundwater model (http://globalgroundwatermodel.org) that simulates lateral and vertical flows as well as exchanges with surface water bodies like rivers, lakes, and wetlands for the whole globe except Antarctica and Greenland. The newly developed model framework enables an efficient integration into established global hydrological models. This paper presents the G³M concept and specific model design decisions together with first results under a naturalized equilibrium.
Gemma Coxon, Jim Freer, Rosanna Lane, Toby Dunne, Wouter J. M. Knoben, Nicholas J. K. Howden, Niall Quinn, Thorsten Wagener, and Ross Woods
Geosci. Model Dev., 12, 2285–2306,Short summary
DECIPHeR (Dynamic fluxEs and ConnectIvity for Predictions of Hydrology) is a new modelling framework that can be applied from small catchment to continental scales for complex river basins. This paper describes the modelling framework and its key components and demonstrates the model’s ability to be applied across a large model domain. This work highlights the potential for catchment- to continental-scale predictions of streamflow to support robust environmental management and policy decisions.
Katherine R. Barnhart, Rachel C. Glade, Charles M. Shobe, and Gregory E. Tucker
Geosci. Model Dev., 12, 1267–1297,Short summary
Terrainbento 1.0 is a Python package for modeling the evolution of the surface of the Earth over geologic time (e.g., thousands to millions of years). Despite many decades of effort by the geomorphology community, there is no one established governing equation for the evolution of topography. Terrainbento 1.0 thus provides 28 alternative models that support hypothesis testing and multi-model analysis in landscape evolution.
Taesam Lee and Vijay P. Singh
Geosci. Model Dev., 12, 1189–1207,Short summary
A simple novel technique for simulating multisite occurrence of precipitation is proposed. The proposed technique employs the nonparametric approaches k-nearest neighbor and genetic algorithms. We tested this technique in various ways and proved that this simple technique can be useful and comparable to the existing one.
Alberto Martínez-de la Torre, Eleanor M. Blyth, and Graham P. Weedon
Geosci. Model Dev., 12, 765–784,Short summary
Land–surface interactions with the atmosphere are key for weather and climate modelling studies, both in research and in the operational systems that provide scientific tools for decision makers. Regional assessments will be influenced by the characteristics of the land. We improved the representation of river flows in Great Britain by including a dependency on the terrain slope. This development will be reflected not only in river flows, but in the whole water cycle represented by the model.
Matthew R. Hipsey, Louise C. Bruce, Casper Boon, Brendan Busch, Cayelan C. Carey, David P. Hamilton, Paul C. Hanson, Jordan S. Read, Eduardo de Sousa, Michael Weber, and Luke A. Winslow
Geosci. Model Dev., 12, 473–523,Short summary
The General Lake Model (GLM) has been developed to undertake simulation of a diverse range of wetlands, lakes, and reservoirs. The model supports the science needs of the Global Lake Ecological Observatory Network (GLEON), a network of lake sensors and researchers attempting to understand lake functioning and address questions about how lakes around the world vary in response to climate and land use change. The paper describes the science basis and application of the model.
Fanny Sarrazin, Andreas Hartmann, Francesca Pianosi, Rafael Rosolem, and Thorsten Wagener
Geosci. Model Dev., 11, 4933–4964,Short summary
We propose the first large-scale vegetation–recharge model for karst regions (V2Karst), which enables the analysis of the impact of changes in climate and land cover on karst groundwater recharge. We demonstrate the plausibility of V2Karst simulations against observations at FLUXNET sites and of controlling modelled processes using sensitivity analysis. We perform virtual experiments to further test the model and gain insight into its sensitivity to precipitation pattern and vegetation cover.
G.-H. Crystal Ng, Andrew D. Wickert, Lauren D. Somers, Leila Saberi, Collin Cronkite-Ratcliff, Richard G. Niswonger, and Jeffrey M. McKenzie
Geosci. Model Dev., 11, 4755–4777,Short summary
The profound importance of water has led to the development of increasingly complex hydrological models. However, implementing these models is usually time-consuming and requires specialized expertise, stymieing their widespread use to support science-driven decision-making. In response, we have developed GSFLOW–GRASS, a robust and comprehensive set of software tools that can be readily used to set up and execute GSFLOW, the U.S. Geological Survey's coupled groundwater–surface-water flow model.
Xenia Stavropulos-Laffaille, Katia Chancibault, Jean-Marc Brun, Aude Lemonsu, Valéry Masson, Aaron Boone, and Hervé Andrieu
Geosci. Model Dev., 11, 4175–4194,Short summary
Integrating vegetation in urban planning is promoted to counter steer potential impacts of climate and demographic changes. Assessing the multiple benefits of such strategies on the urban microclimate requires a detailed coupling of both the water and energy transfers in numerical tools. In this respect, the representation of water-related processes in the urban subsoil of the existing model TEB-Veg has been improved. The new model thus allows a better evaluation of urban adaptation strategies.
Michael Bliss Singer, Katerina Michaelides, and Daniel E. J. Hobley
Geosci. Model Dev., 11, 3713–3726,Short summary
For various applications, a regional or local characterization of rainfall is required, particularly at the watershed scale, where there is spatial heterogeneity. Furthermore, simple models are needed that can simulate various scenarios of climate change including changes in seasonal wetness and rainstorm intensity. To this end, we have developed the STOchastic Rainstorm Model (STORM). We explain its developments and data requirements, and illustrate how it simulates rainstorms over a basin.
Kristi R. Arsenault, Sujay V. Kumar, James V. Geiger, Shugong Wang, Eric Kemp, David M. Mocko, Hiroko Kato Beaudoing, Augusto Getirana, Mahdi Navari, Bailing Li, Jossy Jacob, Jerry Wegiel, and Christa D. Peters-Lidard
Geosci. Model Dev., 11, 3605–3621,Short summary
The Earth’s land surface hydrology and physics can be represented in highly sophisticated models known as land surface models. The Land surface Data Toolkit (LDT) software was developed to meet these models’ input processing needs. LDT supports a variety of land surface and hydrology models and prepares the inputs (e.g., meteorological data, satellite observations to be assimilated into a model), which can be used for inter-model studies and to initialize weather and climate forecasts.
Joseph J. Hamman, Bart Nijssen, Theodore J. Bohn, Diana R. Gergel, and Yixin Mao
Geosci. Model Dev., 11, 3481–3496,Short summary
Variable Infiltration Capacity (VIC) is a widely used hydrologic model. This paper documents the development of VIC version 5, which includes a reconfiguration of the model source code to support a wider range of modeling applications. It also represents a significant step forward for the VIC user community in terms of support for a range of modeling applications, reproducibility, and scientific robustness.
Rebecca Emerton, Ervin Zsoter, Louise Arnal, Hannah L. Cloke, Davide Muraro, Christel Prudhomme, Elisabeth M. Stephens, Peter Salamon, and Florian Pappenberger
Geosci. Model Dev., 11, 3327–3346,Short summary
Global overviews of upcoming flood and drought events are key for many applications from agriculture to disaster risk reduction. Seasonal forecasts are designed to provide early indications of such events weeks or even months in advance. This paper introduces GloFAS-Seasonal, the first operational global-scale seasonal hydro-meteorological forecasting system producing openly available forecasts of high and low river flow out to 4 months ahead.
Sylvain Kuppel, Doerthe Tetzlaff, Marco P. Maneta, and Chris Soulsby
Geosci. Model Dev., 11, 3045–3069,Short summary
This paper presents a novel ecohydrological model in which both the fluxes of water and the relative concentration in stable isotopes (2H and 18O) can be simulated. Spatial heterogeneity, lateral transfers and plant-driven water use are incorporated. A thorough evaluation shows encouraging results using a wide range of in situ measurements from a Scottish catchment. The same modelling principles are then used to simulate how (and where) precipitation ages as water transits in the catchment.
Ping Shen, Limin Zhang, Hongxin Chen, and Ruilin Fan
Geosci. Model Dev., 11, 2841–2856,Short summary
A rainstorm can trigger numerous debris flows. A difficult task in debris flow risk assessment is to identify debris flow initiation locations and volumes. This paper presents a new model to solve this problem by physically simulating the initiation of debris flows by hillslope bed erosion and transformation from slope failures. The sediment from these two initiation mechanisms joins the flow mixture, and the volume of the flow mixture increases along the flow path due to additional bed erosion.
Aleotti, P.: A warning system for rainfall-induced shallow failures, Eng. Geol., 73, 247–265, 2004.
Alvioli, M., Guzzetti, F., and Rossi, M.: Scaling properties of rainfall-induced shallow landslides predicted by a physically based model, Geomorphology, online first, https://doi.org/10.1016/j.geomorph.2013.12.039, 2014.
Baum, R., Harp, E., and Hultman, W.: Map showing recent and historic landslide activity on coastal bluffs of Puget Sound between Shilshole Bay and Everett, US Geological Survey Miscellaneous Field Studies Map MF-2346, scale 1 : 24 000, 2000.
Baum, R., Savage, W., and Godt, J.: TRIGRS – a fortran program for transient rainfall infiltration and grid-based regional slope-stability analysis, US Geological Survey Open-file Report, Vol. 424, 61 pp., 2002.
Baum, R., McKenna, J., Godt, J., Harp, E., and McMulle, S.: Hydrologic monitoring of landslide-prone coastal bluffs near Edmonds and Everett, Washington, US Geological Survey Open-file Report, 42 pp., 2005.
Baum, R., Savage, W., and Godt, J.: TRIGRS – a fortran program for transient rainfall infiltration and grid-based regional slope-stability analysis, version 2.0, US Geological Survey Open-file Report, Vol. 1159, 75 pp., 2008.
Baum, R., Godt, J., and Savage, W.: Estimating the timing and location of shallow rainfall-induced landslides using a model for transient, unsaturated infiltration, J. Geophys. Res., 115, F03013, https://doi.org/10.1029/2009JF001321, 2010.
Brabb, E. and Harrod, B.: Landslides: Extent and Economic Significance, A. A. Balkema Publisher, Rotterdam, 385 pp., 1989.
Cardinali, M., Ardizzone, F., Galli, M., Guzzetti, F., and Reichenbach, P.: Landslides triggered by rapid snow melting: the December 1996–January 1997 event in central Italy, in: Proceedings of the EGS Plinius Conference held at Maratea, 439–448, 2000.
Church, P.: Some precipitation characteristics of Seattle, Weatherwise, December, 244–251, 1974.
Crosta, G.: Regionalization of rainfall thresholds: an aid to landslide hazard evaluation, Environ. Geol., 35, 131–145, 1998.
Crosta, G. B. and Frattini, P.: Distributed modelling of shallow landslides triggered by intense rainfall, Nat. Hazards Earth Syst. Sci., 3, 81–93, https://doi.org/10.5194/nhess-3-81-2003, 2003.
DeRose, R.: Relationships between slope morphology, regolith depth, and the incidence of shallow landslides in eastern Taranaki Hill Country, Z. Geomorphol. Supp., 105, 49–60, 1996.
Fawcett, T.: An introduction to ROC analysis, Pattern Recogn. Lett., 27, 861–874, 2006.
Feda, J., Bohác, J., and Herle, I.: Shear resistance of fissured Neogene clays, Eng. Geol., 39, 171–184, 1995.
Fiorucci, F., Cardinali, M., Carlà, R., Rossi, M., Mondini, A. C., Santurri, L., Ardizzone, F., and Guzzeti, F.: Seasonal landslide mapping and estimation of landslide mobilization rates using aerial and satellite images, Geomorphology, 129, 59–70, 2011.
Frattini, P., Crosta, G., and Sosio, R.: Approaches for defining thresholds and return periods for rainfall-triggered shallow landslides, Hydrol. Process., 23, 1444–1460, 2009.
Freeze, A., and Cherry, J.: Groundwater, Hemel Hempstead: Prentice-Hall International, xviii + 604 pp., 1979.
Galster, R. and Laprade, W.: Geology of Seattle, Washington, United States of America, Bulletin of the Association of Engineering Geologistst, 18, 235–302, 1991.
Gardner, W.: Some steady-state solutions of the unsaturated moisture flow equation with application to evaporation from a water table, Soil Sci. 85, 228–232, Rotterdam, 1958.
Godt, J., Baum, R., and Chleborad, A.: Rainfall characteristics for shallow landsliding in Seattle, Washington, USA, Earth Surf. Proc. Land., 31, 97–110, 2006.
Godt, J., Baum, R., Savage, W., Salciarini, D., Schulz, W., and Harp, E.: Transient deterministic shallow landslide modeling: requirements for susceptibility and hazard assessments in a GIS framework, Eng. Geol., 102, 214–226, 2008.
Gorsevski, P., Gessler, P., Boll, J., Elliot, W., and Foltz, R.: Spatially and temporally distributed modeling of landslide susceptibility, Geomorphology, 80, 178–198, 2006.
Guzzetti, F., Carrara, A., Cardinali, M., and Reichenbach, P.: Landslide hazard evaluation: a review of current techniques and their application in a multi-scale study, central Italy, Geomorphology, 31, 181–216, 1999.
Guzzetti, F., Reichenbach, P., Cardinali, M., Galli, M., and Ardizzone, F.: Probabilistic landslide hazard assessment at the basin scale, Geomorphology, 72, 272–299, 2005.
Guzzetti, F., Galli, M., Reichenbach, P., Ardizzone, F., and Cardinali, M.: Landslide hazard assessment in the Collazzone area, Umbria, Central Italy, Nat. Hazards Earth Syst. Sci., 6, 115–131, https://doi.org/10.5194/nhess-6-115-2006, 2006a.
Guzzetti, F., Reichenbach, P., Ardizzone, F., Cardinali, M., and Galli, M.: Estimating the quality of landslide susceptibility models, Geomorphology, 81, 166–184, 2006b.
Guzzetti, F., Peruccacci, S., Rossi, M., and Stark, C.: Rainfall thresholds for the initiation of landslides in central and southern europe, Meteorol. Atmos. Phys., 98, 239–267, 2007.
Guzzetti, F., Peruccacci, S., Rossi, M., and Stark, C.: The rainfall intensity-duration control of shallow landslides and debris flows: an update, Landslides, 5, 3–17, 2008.
Guzzetti, F., Ardizzone, F., Cardinali, M., Rossi, M., and Valigi, D.: Landslide volumes and landslide mobilization rates in Umbria, central Italy, Earth Planet. Sc. Lett., 279, 222–229, 2009.
Hammond, C., Hall, D., Miller, S., and Swetik, P.: Level I Stability Analysis (LISA) Documentation for Version 2.0: Ogden, Utah, U.S. Forest Service Intermountain Research Station, General Technical Report INT-285, 190 pp., 1992.
Haneberg, W. C.: A rational probabilistic method for spatially distributed landslide hazard assessment, Environ. Eng. Geosci., 10, 27–43, 2004.
Haugerud, R., Harding, D., Johnson, S., Harless, J., Weaver, C., and Sherrod, B.: High-resolution lidar topography of the Puget Lowland, Washington, GSA Today, 13, 4–10, 2003.
Hillel, D.: Introduction to Soil Physics, Academic, San Diego, 1982.
Iverson, R.: Landslide triggering by rain infiltration, Water Resour. Res., 36, 1897–1910, 2000.
Kevorkian, J.: Partial differential equation: analytical solution techniques, Vol. 35, 2nd Edn., Text in applied Mathematics, Springer, 1991.
Lade, P. V.: The mechanics of surficial failure in soil slopes Eng. Geol. 114, 57–64, 2010.
Lu, N., Wayllace, A., Carrera, J., and Likos, W.: Constant flow method for concurrently measuring soil-water characteristic curve and hydraulic conductivity function, Geotech. Test. J., 29, 230–241, 2006.
Minard, J. P.: Distribution and description of geologic units in the Mukilteo quadrangle, Washington, US Geological Survey Miscellaneous Field Studies Map MF-1438, scale 1 : 24 000, 2000.
Montgomery, D. and Dietrich, W.: A physically based model for the topographic control of shallow landsliding, Water Resour. Res., 30, 1153–1171, 1994.
Pack, R. T., Tarboton, D. G., and Goodwin, C. N.: Terrain Stability Mapping with SINMAP, technical description and users guide for version 1.00. Report Number 4114-0, Terratech Consulting Ltd., Salmon Arm, B.C., Canada, 1998.
Partnership for reducing landslide risk: Assessment of the National Landslide Hazards Mitigation Strategy, edited by The National Academies Press, Washington, D.C., 2004.
Richards, L.: Capillary conduction of liquids through porous mediums, Physics, 1, 318–333, https://doi.org/10.1063/1.1745010, 1931.
Rodriguez-Iturbe, I., Vogel, G., Rigon, R., Entekhabi, D., Castelli, F., and Rinaldo, A.: On the spatial organization of soil moisture fields, Geophys. Res. Lett., 22, 2752–2760, 1999.
Rossi, M., Guzzetti, F., Reichenbach, P., Mondini, A., and Peruccacci, S.: Optimal landslide susceptibility zonation based on multiple forecasts, Geomorphology, 114, 129–142, 2010.
Salciarini, D., Godt, J., Savage, W., Conversini, R., Baum, R., and Michael. J.: Modeling regional initiation of rainfall-induced shallow landslides in the eastern Umbria region of central Italy, Landslides, 3, 181–194, 2006.
Savage, W., Godt, J., and Baum, R.: A model for spatially and temporally distributed shallow landslide initiation by rainfall infiltration, in: Debrisflow Hazards Mitigation-Mechanics, edited by: Rickenmann, D. and Chen, C., prediction and assessment: Millpress, Rotterdam, 179–187, 2003.
Savage, W., Godt, J., and Baum, R.: Modeling time-dependent aerial slope stability, in: Landslides-Evaluation and Stabilization, Proceedings of the 9th International Symposium on Landslides, edited by: Lacerda, W. A., Erlich, M., Fontoura, S. A. B., and Sayao, A. S. F., A. A. Balkema Publishers, London, 1, 23–36, 2004.
Schulz, W.: Landslide susceptibility revealed by lidar imagery and historical records, Seattle, Washington, Eng. Geol., 89, 67–87, 2007.
Shafiee, A.: Permeability of compacted granule-clay mixtures Eng. Geol., 97, 199–208, 2008.
Simoni, S., Zanotti, F., Bertoldi, G., and Rigon, R.: Modeling the probability of occurrence of shallow landslides and channelized debris flows using GEOtop-FS, Hydrol. Process., 22, 532–545, 2008.
Sirangelo, B., Versace, P., and Capparelli, G.: Forewarning model for landslides triggered by rainfall based on the analysis of historical data file, in: Hydrology of the Mediterranean and Semiarid Regions, Proceedings International Symposium held at Montpellier, 1Al IS Publ., 278, 298–304, 2003.
Soeters, R. and Van Westen, C.: Slope instability recognition, analysis and zonation, in: Landslides. Investigation and Mitigation, edited by: Turner, A. K. and Schuster, R. L., National Academy Press, Transportation Research Board, Special Report 247, Washington, DC, 129–177, 1996.
Srivastava, R. and Yeh, T.-C. J.: Analytical solutions for one-dimensional, transient infiltration toward the water table in homogeneous and layered soils, Water Resour. Res., 27, 753–762, 1991.
Tarolli, P., Sofia, G., and Dalla Fontana, G.: Geomorphic features extraction from high-resolution topography: landslide crowns and bank erosion, Nat. Hazards, 61, 65–83, 2012.
Taylor, D.: Fundamentals of Soil Mechanics, New York, Wiley, 1948.
Terlien, M.: The determination of statistical and deterministic hydrological landslide-triggering thresholds, Environ. Geol., 35, 124–130, 1998.
Uchida, T., Akiyama, K., and Tamura, K.: The role of grid cell size, flow routing and spatial variability of soil depth of shallow landslide prediction, Italian Journal of Engineering Geology-Book, 149–157, 2011.
van Westen, C., Castellanos-Abella, E., and Kuriakose, S.: Spatial data for landslide susceptibility, hazard, and vulnerability assessment: an overview, Eng. Geol., 102, 112–131, 2008.
Vieira, B. C., Fernandes, N. F., and Filho, O. A.: Shallow landslide prediction in the Serra do Mar, São Paulo, Brazil, Nat. Hazards Earth Syst. Sci., 10, 1829–1837, https://doi.org/10.5194/nhess-10-1829-2010, 2010.
Western, A., Zhou, S., Grayson, R., Mcmahon, T., Bloschl, G., and Wilson, D.: Spatial correlation of soil moisture in small catchments and its relationship to dominant spatial hydrological processes, J. Hydrol., 286, 113–134, 2004.
Wu, W. and Sidle, R. C.: A distributed slope stability model for steep forested basins, Water Resour. Res., 31, 2097–2110, 1995.
Wyllie, D. C. and Mah, C. W.: Rock Slope Engineering: Civil and Mining, Spon, London, 2004.