PAR(<Emphasis Type="Bold">p</Emphasis>)-vine copula based model for stochastic streamflow scenario generation     

Guilherme?PereiraEmail author  álvaro?Veiga 《Stochastic Environmental Research and Risk Assessment (SERRA)》2018,32(3):833-842

Synthetic streamflow data is vital for the energy sector, as it feeds stochastic optimisation models that determine operational policies. Considered scenarios should differ from each other, but be the same from a statistical point of view, i.e., the scenarios must preserve features of the original time series such as the mean, variance, and temporal dependence structures. Traditionally, linear models are applied for this task. Recently, the advent of copulas has led to the emergence of an alternative that overcomes the drawbacks of linear models. In this context, we propose a methodology based on vine copulas for the stochastic simulation of periodic streamflow scenarios. Copula-based models that focus on single-site inflow simulation only consider lag-one time dependence. Therefore, we suggest an approach that incorporates lags that are greater than one. Furthermore, the proposed model deals with the strong periodicity that is commonly present in monthly streamflow time series. The resulting model is a non-linear periodic autoregressive model. Our results indicate that this model successfully simulates scenarios, preserving features that are observed in historical data.  相似文献   

Multi-objective optimal design for flood risk management with resilience objectives   总被引：1，自引：1，他引：0  

Hsin-Ting?Su  Sai?Hung?CheungEmail author  Edmond?Yat-Man?Lo 《Stochastic Environmental Research and Risk Assessment (SERRA)》2018,32(4):1147-1162

In flood risk management, the divergent concept of resilience of a flood defense system cannot be fully defined quantitatively by one indicator and multiple indicators need to be considered simultaneously. In this paper, a multi-objective optimization (MOO) design framework is developed to determine the optimal protection level of a levee system based on different resilience indicators that depend on the probabilistic features of the flood damage cost arising under the uncertain nature of rainfalls. An evolutionary-based MOO algorithm is used to find a set of non-dominated solutions, known as Pareto optimal solutions for the optimal protection level. The objective functions, specifically resilience indicators of severity, variability and graduality, that account for the uncertainty of rainfall can be evaluated by stochastic sampling of rainfall amount together with the model simulations of incurred flood damage estimation for the levee system. However, these model simulations which usually require detailed flood inundation simulation are computationally demanding. This hinders the wide application of MOO in flood risk management and is circumvented here via a surrogate flood damage modeling technique that is integrated into the MOO algorithm. The proposed optimal design framework is applied to a levee system in a central basin of flood-prone Jakarta, Indonesia. The results suggest that the proposed framework enables the application of MOO with resilience objectives for flood defense system design under uncertainty and solves the decision making problems efficiently by drastically reducing the required computational time.  相似文献   

Three-dimensional analysis of ozone and PM<Subscript>2.5</Subscript> distributions obtained by observations of tethered balloon and unmanned aerial vehicle in Shanghai,China     

Xiao-Bing?Li  Dongfang?Wang  Qing-Chang?Lu  Zhong-Ren?PengEmail author  Qingyan?Fu  Xiao-Ming?Hu  Juntao?Huo  Guangli?Xiu  Bai?Li  Chao?Li  Dong-Sheng?Wang  Hanyu?Wang 《Stochastic Environmental Research and Risk Assessment (SERRA)》2018,32(5):1189-1203

A lightweight unmanned aerial vehicle (UAV) and a tethered balloon platform were jointly used to investigate three-dimensional distributions of ozone and PM_2.5 concentrations within the lower troposphere (1000 m) at a localized coastal area in Shanghai, China. Eight tethered balloon soundings and three UAV flights were conducted on May 25, 2016. Generalized additive models (GAMs) were used to quantitatively describe the relationships between air pollutants and other obtained parameters. Field observations showed that large variations were captured both in the vertical and horizontal distributions of ozone and PM_2.5 concentrations. Significant stratified layers of ozone and PM_2.5 concentrations as well as wind directions were observed throughout the day. Estimated bulk Richardson numbers indicate that the vertical mixing of air masses within the lower troposphere were heavily suppressed throughout the day, leading to much higher concentrations of ozone and PM_2.5 in the planetary boundary layer (PBL). The NO and NO₂ concentrations in the experimental field were much lower than that in the urban area of Shanghai and demonstrated totally different vertical distribution patterns from that of ozone and PM_2.5. This indicates that aged air masses of different sources were transported to the experimental field at different heights. Results derived from the GAMs showed that the aggregate impact of the selected variables for the vertical variations can explain 94.3% of the variance in ozone and 94.5% in PM_2.5. Air temperature, relative humidity and atmospheric pressure had the strongest effects on the variations of ozone and PM_2.5. As for the horizontal variations, the GAMs can explain 56.3% of the variance in ozone and 57.6% in PM_2.5. The strongest effect on ozone was related to air temperature, while PM_2.5 was related to relative humidity. The output of GAMs also implied that fine aerosol particles were in the stage of growth in the experimental field, which is different from ozone (aged air parcels of ozone). Geographical parameters influenced the horizontal variations of ozone and PM_2.5 concentrations by changing underlying surface types. The differences of thermodynamic properties between land and sea resulted in quick changes of PBL height, air temperature and dew point over the coastal area, which was linked to the extent of vertical mixing at different locations. The results of GAMs can be used to analyze the sources and formation mechanisms of ozone and PM_2.5 pollutions at a localized area.  相似文献   

Delineation of flooding risk hotspots based on digital elevation model,calculated and historical flooding extents: the case of Ouagadougou     

Raffaele?De RisiEmail author  Fatemeh?Jalayer  Francesco?De Paola  Sarah?Lindley 《Stochastic Environmental Research and Risk Assessment (SERRA)》2018,32(6):1545-1559

Delineation of flood risk hotspots can be considered as one of the first steps in an integrated methodology for urban flood risk management and mitigation. This paper presents a step-by-step methodology in a GIS-based framework for identifying flooding risk hotspots for residential buildings. This is done by overlaying a map of potentially flood-prone areas [estimated through the topographic wetness index (TWI)], a map of residential areas [extracted from a city-wide assessment of urban morphology types (UMT)], and a geo-spatial census dataset. The novelty of this paper consists in the fact that the flood-prone areas (the TWI thresholds) are identified through a maximum likelihood method (MLE) based both on inundation profiles calculated for a specific return period (T_R), and on information about the extent of historical flooding in the area of interest. Furthermore, Bayesian parameter updating is employed in order to estimate the TWI threshold by employing the historical extent as prior information and the inundation map for calculating the likelihood function. For different statistics of the TWI threshold, the map of potentially flood-prone areas is overlaid with the map of residential urban morphology units in order to delineate the residential flooding risk urban hotspots. Overlaying the delineated urban hotspots with geo-spatial census datasets, the number of people affected by flooding is estimated. These kind of screening procedures are particularly useful for locations where there is a lack of detailed data or where it is difficult to perform accurate flood risk assessment. In fact, an application of the proposed procedure is demonstrated for the identification of urban flooding risk hotspots in the city of Ouagadougou, capital of Burkina Faso, a city for which the observed spatial extent of a major flood event in 2009 and a calculated inundation map for a return period of 300 years are both available.  相似文献   

The 2014 Earthquake Model of the Middle East: seismogenic sources     

Laurentiu Danciu  Karin Şeşetyan  Mine Demircioglu  Levent Gülen  Mehdi Zare  Roberto Basili  Ata Elias  Shota Adamia  Nino Tsereteli  Hilal Yalçın  Murat Utkucu  Muhammad Asif Khan  Mohammad Sayab  Khaled Hessami  Andrea N. Rovida  Massimiliano Stucchi  Jean-Pierre Burg  Arkady Karakhanian  Hektor Babayan  Mher Avanesyan  Tahir Mammadli  Mahmood Al-Qaryouti  Doğan Kalafat  Otar Varazanashvili  Mustafa Erdik  Domenico Giardini 《Bulletin of Earthquake Engineering》2018,16(8):3465-3496

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On approximation for fractional stochastic partial differential equations on the sphere     

Vo?V.?Anh  Philip?Broadbridge  Andriy?Olenko  Yu?Guang?WangEmail authorView author&#;s OrcID profile 《Stochastic Environmental Research and Risk Assessment (SERRA)》2018,32(9):2585-2603

This paper gives the exact solution in terms of the Karhunen–Loève expansion to a fractional stochastic partial differential equation on the unit sphere \({\mathbb {S}}^{2} \subset {\mathbb {R}}^{3}\) with fractional Brownian motion as driving noise and with random initial condition given by a fractional stochastic Cauchy problem. A numerical approximation to the solution is given by truncating the Karhunen–Loève expansion. We show the convergence rates of the truncation errors in degree and the mean square approximation errors in time. Numerical examples using an isotropic Gaussian random field as initial condition and simulations of evolution of cosmic microwave background are given to illustrate the theoretical results.  相似文献   

Data assimilation of soil water flow by considering multiple uncertainty sources and spatial–temporal features: a field-scale real case study     

Xiaomeng?Li  Liangsheng?ShiEmail author  Yuanyuan?Zha  Yakun?Wang  Shun?Hu 《Stochastic Environmental Research and Risk Assessment (SERRA)》2018,32(9):2477-2493

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An environmental indicator: particulate characteristics on pedestrian pathway along integrated urban thoroughfare in Metropolis     

Wei?Pan  Hong-Di?He  Yu?Xue  Wei-Zhen?LuEmail author 《Stochastic Environmental Research and Risk Assessment (SERRA)》2018,32(9):2527-2536

Particulate matter (PM) originated by road transport constitutes an urgent task for megacities and pedestrians are supposed to be the first batch of innocent victims that exposed to and inhaled the polluted air. Footbridges have become a promising resolution to land tension, the location and design of them should be more considered in order to provide a more desirable walking system to pedestrians. In this study, three groups of PM [i.e., 0.3–0.9 μm (sub-fine), 0.9–2.5 μm (fine) and 2.5–10 μm (coarse)] were measured at different traffic scenario related footbridges (i.e., upstream of the on-ramp, downstream of the on-ramp, and signalized intersection) along an urban artery in Hong Kong, and their traffic volume composition, multifractality and cross-correlation behavior were investigated thereafter. Multifractal detrended fluctuation analysis and multifractal detrended fluctuation cross-correlation analysis were used simultaneously to quantify the persistency of different PM groups and interaction between them. The results indicate that although the particle concentration at intersection above footbridges presents the lowest, it has the highest emission rate and the strongest multifractality and cross-correlation behavior, especially the finer ones. Hence, it is suggest that the nature ventilation style of footbridges should avoid to be built above the signalized intersection due to the long persistency of particles and active interaction between different particle groups.  相似文献   

Bayesian maximum entropy approach and its applications: a review     

Junyu?He  Alexander?KolovosEmail author 《Stochastic Environmental Research and Risk Assessment (SERRA)》2018,32(4):859-877

The present paper reviews the conceptual framework and development of the Bayesian Maximum Entropy (BME) approach. BME has been considered as a significant breakthrough and contribution to applied stochastics by introducing an improved, knowledge-based modeling framework for spatial and spatiotemporal information. In this work, one objective is the overview of distinct BME features. By offering a foundation free of restrictive assumptions that limit comparable techniques, an ability to integrate a variety of prior knowledge bases, and rigorous accounting for both exact and uncertain data, the BME approach was coined as introducing modern spatiotemporal geostatistics. A second objective is to illustrate BME applications and adoption within numerous different scientific disciplines. We summarize examples and real-world studies that encompass the perspective of science of the total environment, including atmosphere, lithosphere, hydrosphere, and ecosphere, while also noting applications that extend beyond these fields. The broad-ranging application track suggests BME as an established, valuable tool for predictive spatial and space–time analysis and mapping. This review concludes with the present status of BME, and tentative paths for future methodological research, enhancements, and extensions.  相似文献   

Reducing uncertainty in stochastic streamflow generation and reservoir sizing by combining observed,reconstructed and projected streamflow     

Jason?PatskoskiEmail authorView author&#;s OrcID profile  A.?Sankarasubramanian 《Stochastic Environmental Research and Risk Assessment (SERRA)》2018,32(4):1065-1083

Reservoir sizing is one of the most important aspects of water resources engineering as the storage in a reservoir must be sufficient to supply water during extended droughts. Typically, observed streamflow is used to stochastically generate multiple realizations of streamflow to estimate the required storage based on the Sequent Peak Algorithm (SQP). The main limitation in this approach is that the parameters of the stochastic model are purely derived from the observed record (limited to less than 80 years of data) which does not have information related to prehistoric droughts. Further, reservoir sizing is typically estimated to meet future increase in water demand, and there is no guarantee that future streamflow over the planning period will be representative of past streamflow records. In this context, reconstructed streamflow records, usually estimated based on tree ring chronologies, provide better estimates of prehistoric droughts, and future streamflow records over the planning period could be obtained from general circulation models (GCMs) which provide 30 year near-term climate change projections. In this study, we developed paleo streamflow records and future streamflow records for 30 years are obtained by forcing the projected precipitation and temperature from the GCMs over a lumped watershed model. We propose combining observed, reconstructed and projected streamflows to generate synthetic streamflow records using a Bayesian framework that provides the posterior distribution of reservoir storage estimates. The performance of the Bayesian framework is compared to a traditional stochastic streamflow generation approach. Findings based on the split-sample validation show that the Bayesian approach yielded generated streamflow traces more representative of future streamflow conditions than the traditional stochastic approach thereby, reducing uncertainty on storage estimates corresponding to higher reliabilities. Potential strategies for improving future streamflow projections and its utility in reservoir sizing and capacity expansion projects are also discussed.  相似文献