A perfect prognosis approach for daily precipitation series in consideration of space–time correlation structure     

Malika?KhaliliEmail authorView author&#;s OrcID profile  Van-Thanh-Van?Nguyen 《Stochastic Environmental Research and Risk Assessment (SERRA)》2018,32(12):3333-3364

Downscaling techniques are the required tools to link the global climate model outputs provided at a coarse grid resolution to finer scale surface variables appropriate for climate change impact studies. Besides the at-site temporal persistence, the downscaled variables have to satisfy the spatial dependence naturally observed between the climate variables at different locations. Furthermore, the precipitation spatial intermittency should be fulfilled. Because of the complexity in describing these properties, they are often ignored, which can affect the effectiveness of the hydrologic process modeling. This study is a continuation of the work by Khalili and Nguyen (Clim Dyn 49(7–8):2261–2278.  https://doi.org/10.1007/s00382-016-3443-6, 2017) regarding the multi-site statistical downscaling of daily precipitation series. Different approach of multi-site statistical downscaling based on the concept of the spatial autocorrelation is presented in this paper. This approach has proven to give effective results for multi-site multivariate statistical downscaling of daily extreme temperature time series (Khalili et al. in Int J Climatol 33:15–32.  https://doi.org/10.1002/joc.3402, 2013). However, more challenges are presented by the precipitation variable because of the high spatio-temporal variability and intermittency. The proposed approach consists of logistic and multiple regression models, linking the global climate predictors to the precipitation occurrences and amounts respectively, and using the spatial autocorrelation concept to reproduce the spatial dependence observed between the precipitation series at different sites. An empirical technique has also been involved in this approach in order to fulfill the precipitation intermittency property. The proposed approach was performed using observed daily precipitation data from ten weather stations located in the southwest region of Quebec and southeast region of Ontario in Canada, and climate predictors from the NCEP/NCAR (National Centers for Environmental Prediction/National Centre for Atmospheric Research) reanalysis dataset. The results have proven the ability of the proposed approach to adequately reproduce the observed precipitation occurrence and amount characteristics, temporal and spatial dependence, spatial intermittency and temporal variability.  相似文献   

A stochastic rough-approximation water management model for supporting sustainable water-environment strategies in an irrigation district of arid region     

X.?T.?Zeng  G.?H.?HuangEmail author  J.?L.?Zhang  Y.?P.?Li  L.?You  Y?Chen  P.?P.?Hao 《Stochastic Environmental Research and Risk Assessment (SERRA)》2017,31(9):2183-2200

In this study, a stochastic rough-approximation water management model (SRAWM) associated with optimistic and pessimistic options is proposed for supporting regional sustainability in an irrigation system (IS) of an arid region with uncertain information. SRAWM can not only handle conventional stochastic variations in objective functions or constraints, but also tackle objective and subjective (i.e., risk performance of the decision maker) fuzziness through rough-approximation model based on measure Me. The developed model would be applied to a real case study of an irrigation district (ID) in Kaidu-kongque River Basin, China, which is encountering challenges in economic development and a serious environmental crisis (e.g., drought, water deficit, land deterioration, stalinization, soil erosion and water pollution) synchronously. Simulation technical (i.e., support vector regression) is put into SRAWM framework to reflect dynamic prediction of water demand in the future. Results of optimized irrigation area, water allocation, water deficit, pollution reduction, water and soil erosion and system benefit under various water-environmental policies (corresponding to various ecological effects) are obtained. Tradeoffs between ecological and irrigative water usages can facilitate the local decision makers rectifying the current irrigation patterns and ecological protection polices. Moreover, compromises between systemic benefit and failure risk can help policymakers to generate a robust risk-control plan under uncertainties. These detections are beneficial to achieve conjunctive goals of socio-economic development and eco-environmental sustainability in such an arid IS.  相似文献   

Producing forest fire susceptibility map via multi-criteria decision analysis and frequency ratio methods     

Arca  Deniz  Hacısalihoğlu  Mercan  Kutoğlu  Ş. Hakan 《Natural Hazards》2020,104(1):73-89

Natural Hazards - Located in the Mediterranean basin, one of the world’s leading places in terms of forest fires, Turkey is one of the countries where forest fires are experienced very often...  相似文献