Effect of Sea Level Variation on Tidal Characteristic Values for the East China Sea

Tidal waves in the East China Sea are simulated numerically with POM(Princeton Ocean Model) model for normal mean sea level, 30 cm higher, 60 cm higher, and 100 cm higher, respectively, and the simulated result is compared with the harmonic analysis result of hourly sea level data from 19 tide gauges for more than 19 years. It is indicated that the long-term mean sea level variation affects notably tidal waves in this region. Generally, the tidal amplitude increases when the mean sea level rises, but this relationship may be inverse for some sea areas. The maximal variation of tidal amplitude takes place in the zones near the Fujian coast and the Zhejiang coast, rather than the shallowest Bohai Sea. The maximum increase of M2 amplitude can exceed about 15 cm corresponding to the 60 cm rise of the mean sea level along the Fujian coast. The other regions with large variations of tidal amplitude are those along the Jiangsu coast, the south-east coast of Shandong, and the south-east coast of Dalian. The propagation of tidal waves is also related to mean sea level variation, and the tidal phase-lag decreases generally when the mean sea level rises. Almost all the regions where the tidal phase-lag increases with rising mean sea level are close to amphidromic points, meanwhile the spatial area of such regions is very small. Because the influence of mean sea level variation upon tidal waves is spatially marked, such spatial effect should be considered in calculation of the tidal characteristic value and engineering water level. In the region where the amplitudes of the major tidal constituents increase, the probable maximum high water level becomes higher, the probable maximum low water level becomes lower, and both design water level andcheck water level increase obviously. For example, the design water level at Xiamen increases by 13.5 cm due to the variation of tidal waves when the mean sea level rises 60 cm, the total increase of design water level being 73.5 cm.

Effect of Sea Level Variation on Calculation of Design Water Level

The long-term variation and seasonal variation of sea level have a notable effect on the calculation of engineering water level. Stich an effect is first analyzed in this paper. The maximal amplitude of inter-annual anomaly of monthly mean sea level along the China coast is larger than 60 cm. Both the storm surge disaster and cold wave disaster are seasonal disasters in various regions, so the water level corresponding to the 1% of the cumulative frequency in the cumulative frequency curve of hourly water level data for different seasons in various sea areas is different from design water level., for example, the difference between them reaches maximum in June, July and August for northern sea area, and maximum in September, October and November for Southern China Sea, The hourly water level data of 19 gauge stations along the China coast are analyzed. Firstly, the annual mean sea level for every station is obtained; secondly, linear changing rates of annual mean sea level are obtained with the stochastic dynamic method; thirdly, the astronomical tide and storm surge tide are obtained by subtracting the linear fitting part from the original hourly data, finally, two distributions corresponding to the astronomical tide and wind tide are obtain ed according to whether the astronomical tide and storm tide are correlative or not. So the two check water levels are obtained with the joint probability method, The maximal difference between the two water levels of 100 years' recurrence is more than 30 cm. Both of the two check water levels have disadvantages in the use of observation data, so the mean value is suggested to be taken as the final check water level. A comparison between the two check-water levels indicates that the effect of sea level variation upon design water level and check water level is larger than 80 cm at some stations.

INCIDENCE MATRIX APPROACH FOR CALCULATING READINESS LEVELS

Contemporary system maturity assessment approaches have failed to provide robust quantitative system evaluations resulting in increased program costs and developmental risks.Standard assessment metrics,such as Technology Readiness Levels（TRL）,do not sufficiently evaluate increasingly complex systems.The System Readiness Level（SRL）is a newly developed system development metric that is a mathematical function of TRL and Integration Readiness Level（IRL） values for the components and connections of a particular system.SRL acceptance has been hindered because of concerns over SRL mathematical operations that may lead to inaccurate system readiness assessments.These inaccurate system readiness assessments are called readiness reversals.A new SRL calculation method using incidence matrices is proposed to alleviate these mathematical concerns.The presence of SRL readiness reversal is modeled for four SRL calculation methods across several system configurations.Logistic regression analysis demonstrates that the proposed Incidence Matrix SRL（IMSRL）method has a decreased presence of readiness reversal than other approaches suggested in the literature.Viable SRL methods will foster greater SRL adoption by systems engineering professionals and will support system development risk reduction goals.