European air transport network(EATN)and Chinese air transport network(CATN),as two important air transport systems in the world,are facing increasingly spatial hazards,such as extreme weathers and natural disasters. I...European air transport network(EATN)and Chinese air transport network(CATN),as two important air transport systems in the world,are facing increasingly spatial hazards,such as extreme weathers and natural disasters. In order to reflect and compare impact of spatial hazards on the two networks in a practical way,a new spatial vulnerability model(SVM)is proposed in this paper,which analyzes vulnerability of a network system under spatial hazards from the perspectives of network topology and characteristics of hazards. Before introduction of the SVM,two abstract networks for EATN and CATN are established with a simple topological analysis by traditional vulnerability method. Then,the process to study vulnerability of an air transport network under spatial hazards by SVM is presented. Based on it,a comparative case study on EATN and CATN under two representative spatial hazard scenarios,one with an even spatial distribution,named as spatially uniform hazard,and the other with an uneven spatial distribution that takes rainstorm hazard as an example,is conducted. The simulation results show that both of EATN and CATN are robust to spatially uniform hazard,but vulnerable to rainstorm hazard. In the comparison of the results of the two networks that only stands from the points of network topology and characteristics of hazard without considering certain unequal factors,including airspace openness and flight safety importance in Europe and China,EATN is more vulnerable than CATN under rainstorm hazard. This suggests that when the two networks grow to a similar developed level in future,EATN needs to pay more attention to the impact of rainstorm hazard.展开更多
This study assesses vulnerability of agriculture to drought, using WINISAREG model and seasonal SPI2-index for eight climate regions （1951-2004）. Results relative to Plovdiv show that in soils of large TAW （total a...This study assesses vulnerability of agriculture to drought, using WINISAREG model and seasonal SPI2-index for eight climate regions （1951-2004）. Results relative to Plovdiv show that in soils of large TAW （total available water） net irrigation requirements NIRs range from 0 to 380 mm. In soils of small TAW, NIRs reach 440 mm in the very dry year. NIRs in Sofia/Silistra are about 100 mm smaller than in Plovdiv while in Sandanski they are 30-110 mm larger. Rainfed maize is associated with great yield variability （29% 〈 Cv 〈 72%）. Considering an economical RYD （relative yield decrease） threshold, 32% of years are risky when TA Wis large in Plovdiv that is double than in Sofia and half than in Sandanski. In North Bulgaria the risky years are 10% in Pleven/Silistra that is half than in Lom. In Plovdiv region reliable relationships （R2 〉 91%） were found relating the SPI2 ＂July-Aug.＂ with simulated RYD of rainfed maize while remaining relationships were less accurate （73% 〈 R2 〈 86%）. Economical losses are produced when High Peak Season SPI2 〈 ＋ 0.20 in Sandanski, SPI2 〈 - 0.50 in Plovdiv and SPI2 〈 - 0.90 in Sofia. In North Bulgaria the SPI2 threshold ranges from - 0.75 to - 1.50. Derived reliable relationships and SPl-thresholds are used for drought vulnerability mapping.展开更多
基金This work was supported in part by the National Key Research and Development Program of China(No.2018YFC0823706-02)the Fundamental Research Funds for the Central Universities of China(No.3122019057).
文摘European air transport network(EATN)and Chinese air transport network(CATN),as two important air transport systems in the world,are facing increasingly spatial hazards,such as extreme weathers and natural disasters. In order to reflect and compare impact of spatial hazards on the two networks in a practical way,a new spatial vulnerability model(SVM)is proposed in this paper,which analyzes vulnerability of a network system under spatial hazards from the perspectives of network topology and characteristics of hazards. Before introduction of the SVM,two abstract networks for EATN and CATN are established with a simple topological analysis by traditional vulnerability method. Then,the process to study vulnerability of an air transport network under spatial hazards by SVM is presented. Based on it,a comparative case study on EATN and CATN under two representative spatial hazard scenarios,one with an even spatial distribution,named as spatially uniform hazard,and the other with an uneven spatial distribution that takes rainstorm hazard as an example,is conducted. The simulation results show that both of EATN and CATN are robust to spatially uniform hazard,but vulnerable to rainstorm hazard. In the comparison of the results of the two networks that only stands from the points of network topology and characteristics of hazard without considering certain unequal factors,including airspace openness and flight safety importance in Europe and China,EATN is more vulnerable than CATN under rainstorm hazard. This suggests that when the two networks grow to a similar developed level in future,EATN needs to pay more attention to the impact of rainstorm hazard.
文摘This study assesses vulnerability of agriculture to drought, using WINISAREG model and seasonal SPI2-index for eight climate regions （1951-2004）. Results relative to Plovdiv show that in soils of large TAW （total available water） net irrigation requirements NIRs range from 0 to 380 mm. In soils of small TAW, NIRs reach 440 mm in the very dry year. NIRs in Sofia/Silistra are about 100 mm smaller than in Plovdiv while in Sandanski they are 30-110 mm larger. Rainfed maize is associated with great yield variability （29% 〈 Cv 〈 72%）. Considering an economical RYD （relative yield decrease） threshold, 32% of years are risky when TA Wis large in Plovdiv that is double than in Sofia and half than in Sandanski. In North Bulgaria the risky years are 10% in Pleven/Silistra that is half than in Lom. In Plovdiv region reliable relationships （R2 〉 91%） were found relating the SPI2 ＂July-Aug.＂ with simulated RYD of rainfed maize while remaining relationships were less accurate （73% 〈 R2 〈 86%）. Economical losses are produced when High Peak Season SPI2 〈 ＋ 0.20 in Sandanski, SPI2 〈 - 0.50 in Plovdiv and SPI2 〈 - 0.90 in Sofia. In North Bulgaria the SPI2 threshold ranges from - 0.75 to - 1.50. Derived reliable relationships and SPl-thresholds are used for drought vulnerability mapping.
