Articles | Volume 20, issue 1
https://doi.org/10.5194/nhess-20-21-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-20-21-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
03 Jan 2020
Research article |
| 03 Jan 2020
| 03 Jan 2020
Evaluation of a combined drought indicator and its potential for agricultural drought prediction in southern Spain
María del Pilar Jiménez-Donaire
CORRESPONDING AUTHOR
Department of Agronomy, University of Córdoba, Córdoba, 14071, Spain
Ana Tarquis
CEIGRAM, Universidad Politécnica de Madrid, Madrid, 28040, Spain
Grupo de Sistemas Complejos, Universidad Politécnica de Madrid, Madrid, 28040, Spain
Juan Vicente Giráldez
Department of Agronomy, University of Córdoba, Córdoba, 14071, Spain
Institute for Sustainable Agriculture, CSIC, Cordova,
14071, Spain
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Juan J. Martin-Sotoca, Ernesto Sanz, Antonio Saa-Requejo, Rubén Moratiel, Andrés F. Almeida-Ñauñay, and Ana M. Tarquis
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2023-145, https://doi.org/10.5194/nhess-2023-145, 2023
Preprint under review for NHESS
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This work includes vegetation (VCI) and water content index (WCI) series from two semiarid rangeland areas in Spain. Based on then, a Z-score for both was calculated to use it as an anomaly index. In this way, we associated negative anomalies with drought episodes. Then, we study the relations of these negative anomalies to see if it is possible to use WCI as an alarm of agronomic drought (VCI negative anomaly). The description of the behaviour of both areas and their comparison are made.
Jonathan Rizzi, Ana M. Tarquis, Anne Gobin, Mikhail Semenov, Wenwu Zhao, and Paolo Tarolli
Nat. Hazards Earth Syst. Sci., 21, 3873–3877, https://doi.org/10.5194/nhess-21-3873-2021, https://doi.org/10.5194/nhess-21-3873-2021, 2021
Panagiotis T. Nastos, Nicolas R. Dalezios, Ioannis N. Faraslis, Kostas Mitrakopoulos, Anna Blanta, Marios Spiliotopoulos, Stavros Sakellariou, Pantelis Sidiropoulos, and Ana M. Tarquis
Nat. Hazards Earth Syst. Sci., 21, 1935–1954, https://doi.org/10.5194/nhess-21-1935-2021, https://doi.org/10.5194/nhess-21-1935-2021, 2021
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Risk assessment consists of three steps: identification, estimation and evaluation. Nevertheless, the risk management framework also includes a fourth step, the need for feedback on all the risk assessment undertakings. However, there is a lack of such feedback, which constitutes a serious deficiency in the reduction of environmental hazards at the present time. The objective of this review paper consists of addressing meteorological hazards and extremes within the risk management framework.
Rubén Moratiel, Raquel Bravo, Antonio Saa, Ana M. Tarquis, and Javier Almorox
Nat. Hazards Earth Syst. Sci., 20, 859–875, https://doi.org/10.5194/nhess-20-859-2020, https://doi.org/10.5194/nhess-20-859-2020, 2020
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The estimation of ETo using temperature is particularly attractive in places where air humidity, wind speed and solar radiation data are not readily available. In this study we used, for the estimation of ETo, seven models against Penman–Monteith FAO 56 with temporal (annual and seasonal) and spatial perspective over Duero basin (Spain). The results of the tested models can be useful for adopting appropriate measures for efficient water management under the limitation of agrometeorological data.
Irene Blanco-Gutiérrez, Rhys Manners, Consuelo Varela-Ortega, Ana M. Tarquis, Lucieta G. Martorano, and Marisol Toledo
Nat. Hazards Earth Syst. Sci., 20, 797–813, https://doi.org/10.5194/nhess-20-797-2020, https://doi.org/10.5194/nhess-20-797-2020, 2020
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The Amazon rainforest is being destroyed, resulting in negative ecological and social impacts. We explore how stakeholders perceive the causes of the Amazon's degradation in Bolivia and Brazil and develop a series of scenarios to help strengthen the balance between human development and environmental conservation. The results suggest that the application of governance and well-integrated technical and social reform strategies encourages positive regional changes even under climate change.
Omar Roberto Valverde-Arias, Paloma Esteve, Ana María Tarquis, and Alberto Garrido
Nat. Hazards Earth Syst. Sci., 20, 345–362, https://doi.org/10.5194/nhess-20-345-2020, https://doi.org/10.5194/nhess-20-345-2020, 2020
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We designed an index-based insurance (IBI) for drought and flood in rice crops in Babahoyo (Ecuador). We assessed Babahoyo's soil, climatic and topographic variability, finding two homogeneous zones inside this area. We set differentiated insurance premiums according to the particular risk status of each zone. Results demonstrate that this IBI is an efficient risk transfer tool for policyholders. This insurance design could contribute to stabilizing farmers' incomes and rice production.
Juan José Martín-Sotoca, Antonio Saa-Requejo, Rubén Moratiel, Nicolas Dalezios, Ioannis Faraslis, and Ana María Tarquis
Nat. Hazards Earth Syst. Sci., 19, 1685–1702, https://doi.org/10.5194/nhess-19-1685-2019, https://doi.org/10.5194/nhess-19-1685-2019, 2019
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Vegetation indices based on satellite images, such as the normalized difference vegetation index (NDVI), have been used for damaged pasture insurance. The occurrence of damage is usually defined by NDVI thresholds mainly based on normal statistics. In this work a pasture area in Spain was delimited by MODIS images. A statistical analysis of NDVI was applied to search for alternative distributions. Results show that generalized extreme value distributions present a better fit than normal ones.
Carmelo Alonso, Ana M. Tarquis, Ignacio Zúñiga, and Rosa M. Benito
Nonlin. Processes Geophys., 24, 141–155, https://doi.org/10.5194/npg-24-141-2017, https://doi.org/10.5194/npg-24-141-2017, 2017
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NDVI and EVI vegetation indexes, estimated from satellite images, can been used to estimate root zone soil moisture. However, depending on the spatial and radiometric resolution of the sensors used, estimations could change. In this work, images taken by satellites IKONOS-2 and LANDSAT-7 of the same location are compared on the four bands involved in these vegetation indexes. The results show that spatial resolution has a similar scaling effect in the four bands, but not radiometric resolution.
Ana M. Tarquis, María Teresa Castellanos, Maria Carmen Cartagena, Augusto Arce, Francisco Ribas, María Jesús Cabello, Juan López de Herrera, and Nigel R. A. Bird
Nonlin. Processes Geophys., 24, 77–87, https://doi.org/10.5194/npg-24-77-2017, https://doi.org/10.5194/npg-24-77-2017, 2017
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Melon crop got different levels of N that constituted a contribution to the variation of soil N at mainly larger scales. During its development a proportion of the N was taken up, adding a second factor of variability at smaller scales. After the melon harvest, the wheat was sown across the plots and harvested at the end of the season. Wheat was used as a N sink crop and allowed us to evaluate the soil N residual. Multiscale and relative entropy were applied to study N scale dependencies.
Antonio Hayas, Tom Vanwalleghem, Ana Laguna, Adolfo Peña, and Juan V. Giráldez
Hydrol. Earth Syst. Sci., 21, 235–249, https://doi.org/10.5194/hess-21-235-2017, https://doi.org/10.5194/hess-21-235-2017, 2017
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Gully erosion is one of the most important erosion processes. In this study, we provide new data on gully dynamics over long timescales with an unprecedented temporal resolution. We apply a new Monte Carlo based method for calculating gully volumes based on orthophotos and, especially, for constraining uncertainties of these estimations. Our results show that gully erosion rates are highly variable from year to year and significantly higher than other erosion processes.
N. R. Dalezios, A. Blanta, N. V. Spyropoulos, and A. M. Tarquis
Nat. Hazards Earth Syst. Sci., 14, 2435–2448, https://doi.org/10.5194/nhess-14-2435-2014, https://doi.org/10.5194/nhess-14-2435-2014, 2014
P. Cely, A. M. Tarquis, J. Paz-Ferreiro, A. Méndez, and G. Gascó
Solid Earth, 5, 585–594, https://doi.org/10.5194/se-5-585-2014, https://doi.org/10.5194/se-5-585-2014, 2014
A. Matulka, P. López, J. M. Redondo, and A. Tarquis
Nonlin. Processes Geophys., 21, 269–278, https://doi.org/10.5194/npg-21-269-2014, https://doi.org/10.5194/npg-21-269-2014, 2014
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Diego Guenzi, Danilo Godone, Paolo Allasia, Nunzio Luciano Fazio, Michele Perrotti, and Piernicola Lollino
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Natalie Brožová, Tommaso Baggio, Vincenzo D'Agostino, Yves Bühler, and Peter Bebi
Nat. Hazards Earth Syst. Sci., 21, 3539–3562, https://doi.org/10.5194/nhess-21-3539-2021, https://doi.org/10.5194/nhess-21-3539-2021, 2021
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Hugues Brenot, Nicolas Theys, Lieven Clarisse, Jeroen van Gent, Daniel R. Hurtmans, Sophie Vandenbussche, Nikolaos Papagiannopoulos, Lucia Mona, Timo Virtanen, Andreas Uppstu, Mikhail Sofiev, Luca Bugliaro, Margarita Vázquez-Navarro, Pascal Hedelt, Michelle Maree Parks, Sara Barsotti, Mauro Coltelli, William Moreland, Simona Scollo, Giuseppe Salerno, Delia Arnold-Arias, Marcus Hirtl, Tuomas Peltonen, Juhani Lahtinen, Klaus Sievers, Florian Lipok, Rolf Rüfenacht, Alexander Haefele, Maxime Hervo, Saskia Wagenaar, Wim Som de Cerff, Jos de Laat, Arnoud Apituley, Piet Stammes, Quentin Laffineur, Andy Delcloo, Robertson Lennart, Carl-Herbert Rokitansky, Arturo Vargas, Markus Kerschbaum, Christian Resch, Raimund Zopp, Matthieu Plu, Vincent-Henri Peuch, Michel Van Roozendael, and Gerhard Wotawa
Nat. Hazards Earth Syst. Sci., 21, 3367–3405, https://doi.org/10.5194/nhess-21-3367-2021, https://doi.org/10.5194/nhess-21-3367-2021, 2021
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Johnny Douvinet, Anna Serra-Llobet, Esteban Bopp, and G. Mathias Kondolf
Nat. Hazards Earth Syst. Sci., 21, 2899–2920, https://doi.org/10.5194/nhess-21-2899-2021, https://doi.org/10.5194/nhess-21-2899-2021, 2021
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Fabio Brighenti, Francesco Carnemolla, Danilo Messina, and Giorgio De Guidi
Nat. Hazards Earth Syst. Sci., 21, 2881–2898, https://doi.org/10.5194/nhess-21-2881-2021, https://doi.org/10.5194/nhess-21-2881-2021, 2021
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In this paper we propose a methodology to mitigate hazard in a natural environment in an urbanized context. The deformation of the ground is a precursor of paroxysms in mud volcanoes. Therefore, through the analysis of the deformation supported by a statistical approach, this methodology was tested to reduce the hazard around the mud volcano. In the future, the goal is that this dangerous area will become both a naturalistic heritage and a source of development for the community of the area.
Doris Hermle, Markus Keuschnig, Ingo Hartmeyer, Robert Delleske, and Michael Krautblatter
Nat. Hazards Earth Syst. Sci., 21, 2753–2772, https://doi.org/10.5194/nhess-21-2753-2021, https://doi.org/10.5194/nhess-21-2753-2021, 2021
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Multispectral remote sensing imagery enables landslide detection and monitoring, but its applicability to time-critical early warning is rarely studied. We present a concept to operationalise its use for landslide early warning, aiming to extend lead time. We tested PlanetScope and unmanned aerial system images on a complex mass movement and compared processing times to historic benchmarks. Acquired data are within the forecasting window, indicating the feasibility for landslide early warning.
Michal Bíl, Pavel Raška, Lukáš Dolák, and Jan Kubeček
Nat. Hazards Earth Syst. Sci., 21, 2581–2596, https://doi.org/10.5194/nhess-21-2581-2021, https://doi.org/10.5194/nhess-21-2581-2021, 2021
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The online landslide database CHILDA (Czech Historical Landslide Database) summarises information about landslides which occurred in the area of Czechia (the Czech Republic). The database is freely accessible via the https://childa.cz/ website. It includes 699 records (spanning the period of 1132–1989). Overall, 55 % of all recorded landslide events occurred only within 15 years of the extreme landslide incidence.
Anna Kruspe, Jens Kersten, and Friederike Klan
Nat. Hazards Earth Syst. Sci., 21, 1825–1845, https://doi.org/10.5194/nhess-21-1825-2021, https://doi.org/10.5194/nhess-21-1825-2021, 2021
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Messages on social media can be an important source of information during crisis situations. This article reviews approaches for the reliable detection of informative messages in a flood of data. We demonstrate the varying goals of these approaches and present existing data sets. We then compare approaches based (1) on keyword and location filtering, (2) on crowdsourcing, and (3) on machine learning. We also point out challenges and suggest future research.
Enrique Guillermo Cordaro, Patricio Venegas-Aravena, and David Laroze
Nat. Hazards Earth Syst. Sci., 21, 1785–1806, https://doi.org/10.5194/nhess-21-1785-2021, https://doi.org/10.5194/nhess-21-1785-2021, 2021
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We developed a methodology that generates free externally disturbed magnetic variations in ground magnetometers close to the Chilean convergent margin. Spectral analysis (~ mHz) and magnetic anomalies increased prior to large Chilean earthquakes (Maule 2010, Mw 8.8; Iquique 2014, Mw 8.2; Illapel 2015, Mw 8.3). These findings relate to microcracks within the lithosphere due to stress state changes. This physical evidence should be thought of as a last stage of the earthquake preparation process.
Corey M. Scheip and Karl W. Wegmann
Nat. Hazards Earth Syst. Sci., 21, 1495–1511, https://doi.org/10.5194/nhess-21-1495-2021, https://doi.org/10.5194/nhess-21-1495-2021, 2021
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For many decades, natural disasters have been monitored by trained analysts using multiple satellite images to observe landscape change. This approach is incredibly useful, but our new tool, HazMapper, offers researchers and the scientifically curious public a web-accessible
cloud-based tool to perform similar analysis. We intend for the tool to both be used in scientific research and provide rapid response to global natural disasters like landslides, wildfires, and volcanic eruptions.
Matti Wiegmann, Jens Kersten, Hansi Senaratne, Martin Potthast, Friederike Klan, and Benno Stein
Nat. Hazards Earth Syst. Sci., 21, 1431–1444, https://doi.org/10.5194/nhess-21-1431-2021, https://doi.org/10.5194/nhess-21-1431-2021, 2021
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In this paper, we study when social media is an adequate source to find metadata about incidents that cannot be acquired by traditional means. We identify six major use cases: impact assessment and verification of model predictions, narrative generation, recruiting citizen volunteers, supporting weakly institutionalized areas, narrowing surveillance areas, and reporting triggers for periodical surveillance.
Hui Liu, Ya Hao, Wenhao Zhang, Hanyue Zhang, Fei Gao, and Jinping Tong
Nat. Hazards Earth Syst. Sci., 21, 1179–1194, https://doi.org/10.5194/nhess-21-1179-2021, https://doi.org/10.5194/nhess-21-1179-2021, 2021
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We trained a recurrent neural network model to classify microblogging posts related to urban waterlogging and establish an online monitoring system of urban waterlogging caused by flood disasters. We manually curated more than 4400 waterlogging posts to train the RNN model so that it can precisely identify waterlogging-related posts of Sina Weibo to timely determine urban waterlogging.
Roope Tervo, Ilona Láng, Alexander Jung, and Antti Mäkelä
Nat. Hazards Earth Syst. Sci., 21, 607–627, https://doi.org/10.5194/nhess-21-607-2021, https://doi.org/10.5194/nhess-21-607-2021, 2021
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Predicting the number of power outages caused by extratropical storms is a key challenge for power grid operators. We introduce a novel method to predict the storm severity for the power grid employing ERA5 reanalysis data combined with a forest inventory. The storms are first identified from the data and then classified using several machine-learning methods. While there is plenty of room to improve, the results are already usable, with support vector classifier providing the best performance.
Michaela Wenner, Clément Hibert, Alec van Herwijnen, Lorenz Meier, and Fabian Walter
Nat. Hazards Earth Syst. Sci., 21, 339–361, https://doi.org/10.5194/nhess-21-339-2021, https://doi.org/10.5194/nhess-21-339-2021, 2021
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Mass movements constitute a risk to property and human life. In this study we use machine learning to automatically detect and classify slope failure events using ground vibrations. We explore the influence of non-ideal though commonly encountered conditions: poor network coverage, small number of events, and low signal-to-noise ratios. Our approach enables us to detect the occurrence of rare events of high interest in a large data set of more than a million windowed seismic signals.
Luiz Felipe Galizia, Thomas Curt, Renaud Barbero, and Marcos Rodrigues
Nat. Hazards Earth Syst. Sci., 21, 73–86, https://doi.org/10.5194/nhess-21-73-2021, https://doi.org/10.5194/nhess-21-73-2021, 2021
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This paper aims to provide a quantitative evaluation of three remotely sensed fire datasets which have recently emerged as an important resource to improve our understanding of fire regimes. Our findings suggest that remotely sensed fire datasets can be used to proxy variations in fire activity on monthly and annual timescales; however, caution is advised when drawing information from smaller fires (< 100 ha) across the Mediterranean region.
Philippe Weyrich, Anna Scolobig, Florian Walther, and Anthony Patt
Nat. Hazards Earth Syst. Sci., 20, 2811–2821, https://doi.org/10.5194/nhess-20-2811-2020, https://doi.org/10.5194/nhess-20-2811-2020, 2020
Patric Kellermann, Kai Schröter, Annegret H. Thieken, Sören-Nils Haubrock, and Heidi Kreibich
Nat. Hazards Earth Syst. Sci., 20, 2503–2519, https://doi.org/10.5194/nhess-20-2503-2020, https://doi.org/10.5194/nhess-20-2503-2020, 2020
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The flood damage database HOWAS 21 contains object-specific flood damage data resulting from fluvial, pluvial and groundwater flooding. The datasets incorporate various variables of flood hazard, exposure, vulnerability and direct tangible damage at properties from several economic sectors. This paper presents HOWAS 21 and highlights exemplary analyses to demonstrate the use of HOWAS 21 flood damage data.
Giuseppe Esposito, Ivan Marchesini, Alessandro Cesare Mondini, Paola Reichenbach, Mauro Rossi, and Simone Sterlacchini
Nat. Hazards Earth Syst. Sci., 20, 2379–2395, https://doi.org/10.5194/nhess-20-2379-2020, https://doi.org/10.5194/nhess-20-2379-2020, 2020
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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.
Mohammad Malakootian and Majid Nozari
Nat. Hazards Earth Syst. Sci., 20, 2351–2363, https://doi.org/10.5194/nhess-20-2351-2020, https://doi.org/10.5194/nhess-20-2351-2020, 2020
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The present study estimated the Kerman–Baghin aquifer vulnerability using DRASTIC and composite DRASTIC (CDRASTIC) indices with the aid of geographic information system (GIS) techniques. The aquifer vulnerability maps indicated very similar results, identifying the north-west parts of the aquifer as areas with high to very high vulnerability. According to the results, parts of the studied aquifer have a high vulnerability and require protective measures.
Diana Contreras, Alondra Chamorro, and Sean Wilkinson
Nat. Hazards Earth Syst. Sci., 20, 1663–1687, https://doi.org/10.5194/nhess-20-1663-2020, https://doi.org/10.5194/nhess-20-1663-2020, 2020
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The socio-economic condition of the population determines their vulnerability to earthquakes, tsunamis, volcanic eruptions, landslides, soil erosion and land degradation. This condition is estimated mainly from population censuses. The lack to access to basic services, proximity to hazard zones, poverty and population density highly influence the vulnerability of communities. Mapping the location of this vulnerable population makes it possible to prevent and mitigate their risk.
Simona Colombelli, Francesco Carotenuto, Luca Elia, and Aldo Zollo
Nat. Hazards Earth Syst. Sci., 20, 921–931, https://doi.org/10.5194/nhess-20-921-2020, https://doi.org/10.5194/nhess-20-921-2020, 2020
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We developed a mobile app for Android devices which receives the alerts generated by a network-based early warning system, predicts the expected ground-shaking intensity and the available lead time at the user position, and provides customized messages to inform the user about the proper reaction to the alert. The app represents a powerful tool for informing in real time a wide audience of end users and stakeholders about the potential damaging shaking in the occurrence of an earthquake.
Richard Styron, Julio García-Pelaez, and Marco Pagani
Nat. Hazards Earth Syst. Sci., 20, 831–857, https://doi.org/10.5194/nhess-20-831-2020, https://doi.org/10.5194/nhess-20-831-2020, 2020
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The Caribbean and Central American region is both tectonically active and densely populated, leading to a large population that is exposed to earthquake hazards. Until now, no comprehensive fault data covering the region have been available. We present a new public fault database for Central America and the Caribbean that synthesizes published studies with new mapping from remote sensing to provide fault sources for the CCARA seismic hazard and risk analysis project and to aid future research.
Quancai Xie, Qiang Ma, Jingfa Zhang, and Haiying Yu
Nat. Hazards Earth Syst. Sci., 19, 2827–2839, https://doi.org/10.5194/nhess-19-2827-2019, https://doi.org/10.5194/nhess-19-2827-2019, 2019
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This paper evaluates a new method for modeling the site amplification factor. Through implementing this method and making simulations for different cases, we find that this method shows better performance than the previous method and JMA report. We better understand the advantages and disadvantages of this method, although there are some problems that need to be considered carefully and solved; it shows good potential to be used in future earthquake early warning systems.
David A. Bonneau, D. Jean Hutchinson, Paul-Mark DiFrancesco, Melanie Coombs, and Zac Sala
Nat. Hazards Earth Syst. Sci., 19, 2745–2765, https://doi.org/10.5194/nhess-19-2745-2019, https://doi.org/10.5194/nhess-19-2745-2019, 2019
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In mountainous regions around the world rockfalls pose a hazard to infrastructure and society. To aid in our understanding and management of these complex hazards, an inventory can be compiled. Three-dimensional remote sensing data can be used to locate the source zones of these events and generate models of areas which detached. We address the way in which the shape of a rockfall object can be measured. The shape of a rockfall has implications for forward modelling of potential runout zones.
Kwonmin Lee, Hye-Sil Kim, and Yong-Sang Choi
Nat. Hazards Earth Syst. Sci., 19, 2241–2248, https://doi.org/10.5194/nhess-19-2241-2019, https://doi.org/10.5194/nhess-19-2241-2019, 2019
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This study examined the advances in the predictability of thunderstorms using geostationary satellite imageries. Our present results show that by using the latest geostationary satellite data (with a resolution of 2 km and 10 min), thunderstorms can be predicted 90–180 min ahead of their mature state. These data can capture the rapidly growing cloud tops before the cloud moisture falls as precipitation and enable prompt preparation and the mitigation of hazards.
Qingyun Zhang, Yongsheng Li, Jingfa Zhang, and Yi Luo
Nat. Hazards Earth Syst. Sci., 19, 2229–2240, https://doi.org/10.5194/nhess-19-2229-2019, https://doi.org/10.5194/nhess-19-2229-2019, 2019
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Before the opening of the railway, the deformation of the Qinghai–Tibet Railway was very small and considered stable. After opening, the overall stability of the railway section was good. The main deformation areas are concentrated in the areas where railway lines turn and geological disasters are concentrated. In order to ensure the safety of railway operation, it is necessary to carry out long-term time series observation along the Qinghai–Tibet Railway.
Xiao Huang, Cuizhen Wang, and Junyu Lu
Nat. Hazards Earth Syst. Sci., 19, 2141–2155, https://doi.org/10.5194/nhess-19-2141-2019, https://doi.org/10.5194/nhess-19-2141-2019, 2019
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This study examined the spatiotemporal dynamics of nighttime satellite-derived human settlement in response to different levels of hurricane proneness in a period from 1992 to 2013. It confirms the
Snow Belt-to-Sun BeltUS population shift trend. The results also suggest that hurricane-exposed human settlement has grown in extent and area, as more hurricane exposure has experienced a larger increase rate in settlement intensity.
Maja Kucharczyk and Chris H. Hugenholtz
Nat. Hazards Earth Syst. Sci., 19, 2039–2051, https://doi.org/10.5194/nhess-19-2039-2019, https://doi.org/10.5194/nhess-19-2039-2019, 2019
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We performed pre-disaster 3-D mapping with a drone in downtown Victoria, BC, Canada. This was the first drone mapping mission over a Canadian city approved by Canada’s aviation authority. We were legally constrained to using a specific drone. The goal was to assess the quality of the 3-D map. Results indicate that the spatial accuracies achieved with this drone would allow for sub-meter building collapse detection, but the non-tilting camera was insufficient for mapping buildings in 3-D.
Reza Hassanzadeh, Mehdi Honarmand, Mahdieh Hossienjani Zadeh, and Farzin Naseri
Nat. Hazards Earth Syst. Sci., 19, 1989–2009, https://doi.org/10.5194/nhess-19-1989-2019, https://doi.org/10.5194/nhess-19-1989-2019, 2019
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This paper proposes a new model for evaluating local seismic amplification susceptibility by considering direct characteristics of influencing criteria and dealing with uncertainty of modelling through production of fuzzy membership functions and GIS. This model helps planners and decision makers easily produce local seismic amplification susceptibility to be incorporated in designing development plans of urban areas and to evaluate safety measures of existing infrastructure.
Salvador Gil-Guirado, Alfredo Pérez-Morales, and Francisco Lopez-Martinez
Nat. Hazards Earth Syst. Sci., 19, 1955–1971, https://doi.org/10.5194/nhess-19-1955-2019, https://doi.org/10.5194/nhess-19-1955-2019, 2019
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In this study the SMC-Flood database for the municipalities of the Mediterranean coast of mainland Spain is presented. This database has enabled the reconstruction of 3008 cases of flooding on a municipal scale between 1960 and 2015. The data analysis reveals a growing trend in the frequency and area affected by flood cases. The main novelty lies in the fact that we have detected a clear latitudinal gradient of growing intensity and severity of flood cases with a north–south direction.
Juan José Martín-Sotoca, Antonio Saa-Requejo, Rubén Moratiel, Nicolas Dalezios, Ioannis Faraslis, and Ana María Tarquis
Nat. Hazards Earth Syst. Sci., 19, 1685–1702, https://doi.org/10.5194/nhess-19-1685-2019, https://doi.org/10.5194/nhess-19-1685-2019, 2019
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Vegetation indices based on satellite images, such as the normalized difference vegetation index (NDVI), have been used for damaged pasture insurance. The occurrence of damage is usually defined by NDVI thresholds mainly based on normal statistics. In this work a pasture area in Spain was delimited by MODIS images. A statistical analysis of NDVI was applied to search for alternative distributions. Results show that generalized extreme value distributions present a better fit than normal ones.
Hongyan Chen, Gengxing Zhao, Yuhuan Li, Danyang Wang, and Ying Ma
Nat. Hazards Earth Syst. Sci., 19, 1499–1508, https://doi.org/10.5194/nhess-19-1499-2019, https://doi.org/10.5194/nhess-19-1499-2019, 2019
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Using Landsat data, the inversion model of soil salt content (SSC) for different seasons was determined in the Kenli District in the Yellow River Delta region of China. The SSC exhibited a gradual increasing trend from the southwest to northeast. The SSC accumulated in spring, decreased in summer, increased in autumn and reached its peak at the the end of winter. The results can provide data for the control of soil salt hazards and utilization of saline–alkali soil.
Cited articles
Allen, R. G., Pereira, L .S., Raes, D., and Smith, M.: Crop
evapotranspiration: guidelines for computing crop water requirements, FAO
irrigation and drainage paper. Food and Agriculture Organization of the
United Nations, Rome, Italy, 1998.
Andreadis, K. M., Clark, E. A., Wood, A. W., Hamlet, A. F., and Lettenmaier, D. P.: Twentieth-Century Drought in the Conterminous United States, J. Hydrometeorol., 6, 985–1001, https://doi.org/10.1175/JHM450.1, 2005.
Azmi, M., Rüdiger, C., and Walker, J. P.: A data fusion-based drought index,
Water Resour. Res., 52, 2222–2239,
https://doi.org/10.1002/2015WR017834, 2016.
Brocca, L., Melone, F., and Moramarco, T.: On the estimation of antecedent
wetness conditions in rainfall–runoff modelling, Hydrol. Process., 22,
629–642, 2008.
Brooks, R. H. and Corey, A. T.: Properties of Porous Media Affecting Fluid
Flow, J. Irrig. Drain. E.-ASCE, 92, 61–90, 1966.
Bussay, A., Szinell, C., and Szentimery, T.: Investigation and Measurements
of Droughts in Hungary, Hungarian Meteorological Service, New York, 1999.
Cammalleri, C., Micale, F., and Vogt, J.: A novel soil moisture-based
drought severity index (DSI) combining water deficit magnitude and
frequency, Hydrol. Proc., 30, 289–301, https://doi.org/10.1002/hyp.10578, 2016.
Cancelliere, A.: Drought length properties for periodic-stochastic
hydrologic data, Water Resour. Res., 40, W02503, https://doi.org/10.1029/2002WR001750, 2004.
Carrão, H., Russo,
S., Sepulcre-Canto, G., and Barbosa, P.: An empirical standardized soil
moisture index for agricultural drought assessment from remotely sensed
data, Int. J. Appl. Earth Obs., 48, 74–84, 2016.
Censo Agrario: National Institute for Statistics, available at:
https://www.ine.es/dyngs/INEbase/es (last acess: 15 March 2019), 2009.
Cook, E. R., Seager, R., Kushnir, Y., et al.: Old World megadroughts and pluvials during the Common
Era, Sci. Adv., 1, e1500561, https://doi.org/10.1126/sciadv.1500561, 2015.
Cook, B. I., Anchukaitis, K. J., Touchan, R., Meko, D. M., and Cook, E. R.:
Spatiotemporal drought variability in the Mediterranean over the last 900
years, J. Geophys. Res.-Atmos., 121, 2060–2074, https://doi.org/10.1002/2015JD023929, 2016.
Dalezios, N., Loukas, A., Vasiliades, L., and Liakopoulos, E.:
Severity-duration-frequency analysis of droughts and wet periods in Greece,
Hydrolog. Sci. J., 45, 751–769, https://doi.org/10.1080/02626660009492375, 2000.
Gao, B.: NDWI – A Normalized Difference Water Index for RemoteSensing of
Vegetation Liquid Water From Space, Remote
Sens. Environ., 58, 257–266, 1996.
Georgakakos, K. P.: A generalized stochastic hydrometeorological model for
flood and flash-flood forecasting. 1:
Formulation, Water Resour. Res., 22, 2083–2095, 1986.
Gouveia, C., Trigo, R. M., and DaCamara, C. C.: Drought and vegetation stress monitoring in Portugal using satellite data, Nat. Hazards Earth Syst. Sci., 9, 185–195, https://doi.org/10.5194/nhess-9-185-2009, 2009.
Gulácsi, A. and Kovács, F.: Drought monitoring with spectral indices
calculated from MODIS satellite images in Hungary, J.
Environ. Geogr., 8, 11–20, 2015.
Guttman, N. B.: Accepting the Standardized Precipitation Index: a calculation
algorithm, J. Am. Water Resour. As., 34, 113–121, 1999.
Hao, Z. and AghaKouchak, A.: Multivariate Standardized Drought Index: A
parametric multi-index model, Adv. Water Resour., 57, 12–18, 2013.
Hao, Z., Yuan, X., Xia, Y., Hao, F., and Singh, V. P.: An overview of drought
monitoring and prediction systems at regional and global scales, B. Am.
Meteorol. Soc., 98, 1879–1896, 2017.
Herrera-Estrada, J. E., Satoh, Y., and Sheffield, J.: Spatiotemporal dynamics
of global drought, Geophys. Res. Lett., 44, 2254–2263, https://doi.org/10.1002/2016GL071768, 2017.
Hobbins, M. T., Wood, A., McEvoy, D. J., Huntington, J. L., Morton, C.,
Anderson, M., and Hain, C.: The evaporative demand drought index. Part I:
linking drought evolution to variations in evaporative demand, J.
Hydrometeorol., 17, 1745–1761, 2016.
Hunt, E. D., Hubbard, K. G., Wilhite, D. A., Arkebauer, T. J., and Dutcher, A.
L.: The development and evaluation of a soil moisture index, Int. J.
Climatol., 29, 747–759, 2009.
Ji, L. and
Peters, A. J.: Assessing vegetation response to drought in the northern Great
Plains using vegetation and drought indices, Remote Sens. Environ.,
87, 85–98, https://doi.org/10.1016/S0034-4257(03)00174-3, 2003.
Kao, S.-C. and Govindaraju, R. S.: A copula-based joint deficit index for
droughts, J. Hydrol., 380, 121–134,
https://doi.org/10.1016/j.jhydrol.2009.10.029, 2010.
Kędzior, M. and Zawadzki, J.: SMOS data as a source of the agricultural
drought information: Case study of the Vistula catchment, Poland, Geoderma,
306, 167–182, https://doi.org/10.1016/j.geoderma.2017.07.018, 2017.
Keyantash, J. A. and Dracup, J. A.: The quantification of drought indices,
B. Am. Meteorol. Soc., 83, 1167–1180, 2002.
Khare, Y. P., Martinez, C. J.,
and Muñoz-Carpena, R.: Parameter variability and drought models; a study
using the agricultural reference index for drought (ARID), Agron. J.,
105, 1417–1432, 2013.
Kogan, F. N.: Droughts of the Late 1980s in the United States as Derived from
NOAA Polar-Orbiting Satellite Data, B. Am. Meteorol. Soc., 76, 655–668,
1995.
Krueger, E. S., Ochsner, T. E., Quiring, S. M., Engle, D. M., Carlson, J. D.,
Twidwell, D., and Fuhlendorf, S. D.: Measured Soil
Moisture is a Better Predictor of Large Growing-Season Wildfires than the
Keetch–Byram Drought Index, Soil Sci. Soc.
Am. J., 81, 490–502, https://doi.org/10.2136/sssaj2017.01.0003, 2017.
Lloyd-Hughes, B. and Saunders, M. A.: A drought climatology for Europe, Int.
J. Climatol., 22, 1571–1592, 2002.
Martínez-Fernández, J., González-Zamora, A., Sánchez, N.,
and Gumuzzio, A.: A soil water based index as a suitable agricultural
drought indicator, J. Hydrol., 522, 265–273,
https://doi.org/10.1016/j.jhydrol.2014.12.051, 2015.
McEvoy, D. J., Huntington, J. L., Hobbins, M. T., Wood, A., Morton, C.,
Anderson, M., and Hain, C.: The evaporative demand drought index. Part
II:CONUS-wide assessment against common drought indicators, J.
Hydrometeorol., 17, 1763–1779, 2016.
McKee, T. B., Doesken, N. J., and Kleist, J.: The relationship of drought
frequency and duration to time scales, in: Proceedings of the 8th Conference
on Applied Climatology, American Meteorological Society Boston, MA,
179–183, 1993.
Orth, R., Staudinger, M., Seneviratne, S. I., Seibert, J., and Zappa, M.:
Does model performance improve with complexity? A case study with three
hydrological models, J. Hydrol., 523, 147–159, 2015.
Peel, M. C., Finlayson, B. L., and McMahon, T. A.: Updated world map of the Köppen-Geiger climate classification, Hydrol. Earth Syst. Sci., 11, 1633–1644, https://doi.org/10.5194/hess-11-1633-2007, 2007.
Perrin, C., Michel, C., and Andréassian, V.: Does a large number of
parameters enhance model performance? Comparative assessment of common
catchment model structures on 429 catchments, J. Hydrol., 242,
275–301, https://doi.org/10.1016/S0022-1694(00)00393-0, 2001.
Quiring, S. M. and Ganesh, S.: Evaluating the utility of the Vegetation
Condition Index (VCI) for monitoring meteorological drought in Texas, Agr.
Forest Meteorol., 150, 330–339, 2010.
Rawls, W. J., Brakensiek, D. L., and Soni, B.: Agricultural Management Effects
on Soil Water Processes Part I: Soil Water Retention and Green and Ampt
Infiltration Parameters, T. ASAE, 26, 1747–1752, 1983.
Rawls, W. J., Gimenez, D., and Grossman, R.: Use of soil texture, bulk
density, and slope of the water retention curve to predict saturated
hydraulic conductivity, T. ASAE, 41, 983–988, 1998.
Rossi, S. and Niemeyer, S.: Drought Monitoring with estimates of the
Fraction of Absorbed Photosynthetically-active
Radiation (fAPAR) derived from MERIS, in: Remote Sensing for Drought: Innovative Monitoring
Approaches, edited by: Wardlow, B. D., Anderson, M. C., and
Verdin, J. P., CRC Press Boca Raton, FL, USA, 95–120, 2012.
Sepulcre-Canto, G., Horion, S., Singleton, A., Carrao, H., and Vogt, J.: Development of a Combined Drought Indicator to detect agricultural drought in Europe, Nat. Hazards Earth Syst. Sci., 12, 3519–3531, https://doi.org/10.5194/nhess-12-3519-2012, 2012.
Sienz, F., Bothe, O., and Fraedrich, K.: Monitoring and quantifying future climate projections of dryness and wetness extremes: SPI bias, Hydrol. Earth Syst. Sci., 16, 2143–2157, https://doi.org/10.5194/hess-16-2143-2012, 2012.
Sohrabi, M. M., Ryu, J. H., Abatzoglou, J., and Tracy, J.: Development of soil
moisture drought index to characterize droughts, J. Hydrol. Eng., 20, 04015025,
https://doi.org/10.1061/(ASCE)HE.1943-5584.0001213, 2015.
Stagge, J. H., Kingston, D. G., Tallaksen, L. M., and Hannah, D. M.: Observed
drought indices show increased divergence across Europe, Sci. Rep.-UK, 7, 14045,
https://doi.org/10.1038/s41598-017-14283-2, 2017.
Szalai, S. and Szinell, C.: Comparison of two drought indices for drought
monitoring in Hungary – a case study, in:
Drought and Drought Mitigation in Europe, edited by: Somma, F. and Vogt, J. V., Springer, Berlin, 161–166,
2000.
Tannehill, I. R.: Drought: its causes and effects, Princeton Univ. Press,
Princeton, N.J., 1947.
Ting, M., Seager, R., Li, C., Liu, H., and Henderson, N.: Mechanism of
Future Spring Drying in the Southwestern United States in CMIP5 Models, J.
Climate, 31, 4265–4279, https://doi.org/10.1175/JCLI-D-17-0574.1, 2018.
Vanderlinden, K.: Análisis de procesos hidrológicos a diferentes
escalas espacio-temporales, PhD Diss., University of Córdoba, Dept. of
Agronomy, Córdoba, Spain, 2001 (in Spanish).
Van Loon, A. F. and Van Lanen, H. A. J.: A process-based typology of hydrological drought, Hydrol. Earth Syst. Sci., 16, 1915–1946, https://doi.org/10.5194/hess-16-1915-2012, 2012.
Van Loon, A. F. and Laaha, G.: Hydrological drought severity explained by
climate and catchment characteristics, J. Hydrol., 526, 3–14, 2015.
Wang, L. and Yuan, X.: Two types of flash drought and their connections with
seasonal drought, Adv. Atmos. Sci., 35, 1478–1490, 2018.
Wilhite, D. A. and Glantz, M. H. Understanding the drought phenomenon: the
role of definitions, Water Int., 10, 111–120, 1985.
Wilhite, D. A., Hayes, M. J., Kinutson, C., and Smith, K. H.: Planning for
drought: moving from crisis to risk management, J. Am. Water Resour. As.,
36, 697–710, 2000.
Yang, T., Ding, J., Liu, D., Wang, X., and Wang, T.: Combined use of
multiple drought indices for global assessment of dry gets drier and wet
gets wetter paradigm, J. Climate, 32, 737–748, 2019.
Zarch, M. A. A., Sivakumar, B., and Sharma, A.: Droughts in a warming climate:
A global assessment of Standardized precipitation index (SPI) and
Reconnaisance drought index (RDI), J. Hydrol., 526, 183–195, 2015.
Short summary
A new combined drought indicator (CDI) is proposed that integrates rainfall, soil moisture and vegetation dynamics. The performance of this indicator was evaluated against crop damage data from agricultural insurance schemes in five different areas in SW Spain. Results show that this indicator was able to predict important droughts in 2004–2005 and 2011–2012, marked by crop damage of between 70 % and 95 % of the total insured area. This opens important applications for improving insurance schemes.
A new combined drought indicator (CDI) is proposed that integrates rainfall, soil moisture and...
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