The Study Of Risk Estimation Model Of River Health By Incomplete Information

The problem of river health endangers badly national security and social stability in the lastest years. Systematic risk and crisis of river health system in the Yellow River basin with many tributaries, are very outstanding, especially on the flood, water quality, water ecology and water environment.This paper mainly researches systematic risk,runoff condition, runoff risk and crisis estimation of river health system, in which the concept of river health system risk is re-definited by deeply understanding the concepts of risk and uncertainties, and analyzing the relation among each influence factor and the comprehensive effect of those influence factors. Furthermore the quantitative analysis to some factors is made, and Combined the characteristics of river health risk analysis, those are studied on the theories and methods of information clouding diffusion, definition method of river health runoff condition and estimation method of risic-endangement degree. In the end, the theories and methods applied to risk analysis of the Yellow River health, which has made some innovation achievements.(1) For a long time, the Statistical Analysis Method of Datum has been widely applied in Hydrology to confirm hydrological risk, which purpose is to estimate the exceedance probability of hydrological variables. Long sequence data acquirement is very important to estimate hydrological risk. In fact, it is too complicated to collect long sequence feature extreme data because most of samples are small samples. Even if"long sequence"data has been acquired, data integrity still can not be ensured. As the result of this, the accuracy of risk estimation can not be ensured. In this paper, in allusion to the finiteness ("small sample") and incompleteness of hydrological feature extreme data, information diffusion method for small sample data was improved and spread window-width multi-objective colligation optimization method was presented. By application of this method, the diffusivity of different observations was sufficiently considered, and the accuracy of probability density estimation was further improved, and objective basis was supplied for risk estimation.(2) The informations collected are non-perfect, those informations not only supply fuzzy information but also stochastic information. Aim at the the characteristic of fuzzy and stochastic of non-perfect sample space, combined the cloud theory to extension the information diffusion principle and method, information clouding diffusion principle and method is put forward, and the fact that information clouding diffusion is the precedent of information diffusion. The test indicates that the extension is reasonable and effective, the fuzzy and random information of non-perfect knowledge is used fully, the accuracy of the probability density estimation was improved, the risk analysis element of hydrology and water resource model is anundanced.(3) parameter estimation method is used in risk evaluation, first, a statistical model is supposed to adapt samples ,the one extremum event was estimated. model uncertainty and parameter uncertainty are existed in the method. To hydrological system, the samples of the hydrological factors are not sufficient, and the infection factors that formated is complex, the suppose of the probability distribution function that accord with the practical condition then undergo parameters estimation are impossible. The risk analysis model that based on information clouding diffusion principle is put forward. The result indicates that the analysis based on the model is more validity, more accuracy, more fast, and more convenience.(5) By definition of ecological velocity and water-depth, the ecological water depth & flow velocity method that considered wetted perimeter, rough rate, hydraulic gradient of channel and (considered) the water needed that to keep some ecological function simultaneity. The facts indicates that the computation result accord with the facts , can satisfy the basic need of river ecosystem health to ecological flux , can fit the dynamic changes of different annual precipitation and erent period of time of channel morphology perfectly.(6) The estimtation of rivers health status is one of the main research contents of water security risk management and crisis management. Because of the complexity, dynamic, openness, nonlinearity of river system, it brings many difficulties to the estimation. The core problem is the set of the prediction index and the ascertainment of the predication method. To improve better the estimation method of river health, the risk & endangement degree estimation model was put forward, and was used in the flood and storage risk & endangement estimation of Yellow River health. The results indicates that the practicality and effectiveness of the method is positive, as an effictive method to the estimitation of rivers health status.