Search Results

You are looking at 1 - 10 of 474 items for :

  • Risk assessment x
  • Journal of Hydrometeorology x
  • All content x
Clear All
Chandra Rupa Rajulapati, Simon Michael Papalexiou, Martyn P. Clark, Saman Razavi, Guoqiang Tang, and John W. Pomeroy

events, and quantifies the likelihood of extremes to occur. More frequent and larger extremes with respect to the average precipitation occur when a heavy tail is observed in a particular region. Therefore, assessment of a tail’s heaviness is useful to understand the likelihood of extremes and thus guide risk management strategies. The tail function F ¯ X ⁡ ( x ) of random variable X is the complimentary cumulative distribution function of X . Several classifications of tail functions exist, yet

Restricted access
Catherine Champagne, Andrew Davidson, Patrick Cherneski, Jessika L’Heureux, and Trevor Hadwen

1. Introduction Agricultural risk assessment is a key tool for determining potential and actual losses in food production that result from climatic extremes such as deficits and excesses of moisture in the soil and at the surface. Soil moisture is a key determinant of crop production, impacting field accessibility for seeding, harvest, and field management; sustaining productive crop growth; and often determining vulnerability of crops to disease and pests. Characterizing soil moisture and soil

Full access
Juliette Blanchet and Victor Mélèse

of the region. This result emphasizes the merit of using high-resolution radar data rather than a sparser rain gauge network. Despite a significant progress brought in the area of rainfall severity assessment, a limitation of the present study is that the considered spatial scales of aggregation, which are squared, do not coincide with the hydrological risk that depends on the shape of watershed over which rainfall accumulates. An improvement of this study will be to consider the severity over

Free access
Dazhi Xi, Ning Lin, and James Smith

2003 ; Liu et al. 2017 , 2020 ). Several approaches have been employed to simulate TC rainfall. High-resolution climate models enable the explicit simulation of TCs and have been used to study the future changes of TC rainfall climatology ( Liu et al. 2018 ; Bacmeister et al. 2018 ; Vecchi et al. 2019 ). However, it is computationally expensive to generate a large number of possible TC scenarios for risk assessment by running high-resolution climate models. To overcome this challenge, TC

Open access
Danielle C. Verdon-Kidd and Anthony S. Kiem

the first step in any drought (or flood, bushfire, or any other climate-driven extreme) risk assessment should be to understand the climate mechanisms that drive periods of elevated risk. For example, numerous studies [refer to Diaz and Markgraf (2000) and references therein] have shown that strong relationships exist between eastern Australian rainfall and streamflow, and the global-scale ocean–atmospheric circulation process known as the El Niño–Southern Oscillation (ENSO). ENSO refers to the

Full access
Clement Guilloteau, Marielle Gosset, Cecile Vignolles, Matias Alcoba, Yves M. Tourre, and Jean-Pierre Lacaux

RVF vector risk assessment can be improved. Section 2 presents the dataset used for this study. It includes satellite rainfall products and a dense rain gauge network in Niger. In section 3 , a newly developed model is presented. Section 4 quantifies the sensitivity of the model to rainfall variability within 45 km × 45 km. It investigates high-resolution satellite rainfall as a forcing field and compares it with using a single rain gauge. Finally, the model-estimated water bodies are

Full access
Cristián Chadwick, Jorge Gironás, Sebastián Vicuña, Francisco Meza, and James McPhee

; Datta and Burges 1984 ; Datta and Houck 1984 ). But decision-making should no longer rely completely on the assumption of stationarity ( Milly et al. 2008 , 2015 ), as global change in general, and climate change in particular, are altering the behavior of hydroclimatic variables. A widely used approach to cope with uncertainty in water resources management under stationarity has been probabilistic risk assessment, in which exceedance probabilities are given to different possible outcomes. Risk

Full access
M. A. Ben Alaya, F. Zwiers, and X. Zhang

) is commonly used to estimate a possible magnitude of an extreme having a very high return period that is judged to have a negligible risk of exceedance. The World Meteorological Organization (WMO; WMO 1986 ), defines PMP as “the greatest depth of precipitation for a given duration meteorologically possible for a design watershed or a given storm area at a particular location at a particular time of year, with no allowance made for long-term climatic trends.” PMP is commonly used for estimating

Open access
Thomas Engel, Andreas H. Fink, Peter Knippertz, Gregor Pante, and Jan Bliefernicht

case showing 1200 UTC 26 Aug 2012. The yellow star shows the location of Dakar. 5. Statistical analysis Using the two cases discussed in section 4 as illustration, here we examine the capability of SRFE to reproduce observed rain rates and their applicability for a flood risk assessment for the African continent. For this, the satellite data will be directly compared to the surface measurements to highlight systematic differences between these two sources of rainfall information. a. Comparison of

Open access
Lu Gao, Jie Huang, Xingwei Chen, Ying Chen, and Meibing Liu

numerous studies (e.g., Alexander et al. 2006 ; Coumou and Rahmstorf 2012 ; Ingram 2016 ; IPCC 2013 ). Many previous studies have shown that extreme precipitation is increasing significantly in northwestern and southeastern China, especially during the rainy season from April to September (e.g., Fu et al. 2013 ; Ning and Qian 2009 ; Wang and Zhou 2005 ; Xu et al. 2011 ; You et al. 2011 ; Zhai et al. 2005 ; Zhang et al. 2009 , 2008 ). Therefore, quantitative assessment of extreme

Full access