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  本文關(guān)鍵詞：流域水文分析與水文預(yù)報方法研究　出處：《華中科技大學(xué)》2016年博士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 多變量趨勢分析 多目標(biāo)參數(shù)率定 流量歷時曲線 信息熵 LUBE區(qū)間預(yù)報 偏互信息 遙相關(guān)氣候因子 數(shù)據(jù)驅(qū)動模型

【摘要】：流域水文分析和水文預(yù)報是水文學(xué)領(lǐng)域的兩個主要研究方向,是水利工程規(guī)劃建設(shè)、水資源優(yōu)化配置及安全高效可持續(xù)利用的重要支撐。由于我國特殊的地理位置和氣候條件,導(dǎo)致水資源在時空分布上極度不均,此外受氣候變化與人類活動的強烈影響,流域水循環(huán)過程和水資源時空分布規(guī)律發(fā)生了深遠(yuǎn)變化,加劇了流域水文特性的復(fù)雜程度和水資源的不安全性,尤其是大型水利工程、跨流域調(diào)水工程等人類活動對水文系統(tǒng)產(chǎn)生了重要影響,水利工程脅迫下流域自然徑流破碎化導(dǎo)致水文系統(tǒng)偏離自然條件下的演變規(guī)律,使得流域水資源系統(tǒng)的時空變異規(guī)律更加復(fù)雜,對流域水文分析和水文預(yù)報研究提出了更高要求。本文圍繞變化環(huán)境下流域水資源演變及高效利用中面臨的關(guān)鍵科學(xué)問題和技術(shù)難題,以長江上游為主要研究對象,研究流域水文分析和水文預(yù)報的先進(jìn)理論方法與技術(shù)手段,研究工作對于減輕早澇災(zāi)害損失及實現(xiàn)水資源可持續(xù)利用具有重要的理論指導(dǎo)意義和工程實用價值。相關(guān)研究成果可供流域管理機構(gòu)參考和借鑒,應(yīng)用前景廣闊。本文的主要研究內(nèi)容和創(chuàng)新性成果包括：(1)為克服單變量趨勢分析方法無法檢驗出整體水文事件是否存在顯著變化趨勢的局限,本文引入多變量Mann-Kendal趨勢分析方法,分別對長江上游干支流水文控制站的年最大洪峰、年最大7d洪量和年最低月平均徑流、年最低3個月平均徑流的單變量與聯(lián)合變量進(jìn)行變化趨勢分析。實例研究表明,長江上游洪水過程整體呈現(xiàn)減小趨勢,而低徑流過程則整體呈增大趨勢。在整體水文事件趨勢分析方面,多變量Mann-Kendal趨勢分析方法展現(xiàn)出明顯優(yōu)勢,能夠檢驗多個相互關(guān)聯(lián)的水文變量是否具有顯著變化趨勢,而單變量Mann-Kendal趨勢分析方法僅能單獨檢驗?zāi)骋凰淖兞糠窬哂酗@著變化趨勢。因此,對包含多個相互關(guān)聯(lián)變量的水文事件進(jìn)行趨勢分析時,需要同時進(jìn)行單變量和多變量趨勢分析才能全面掌握水文事件中單個水文變量變化趨勢和整體變化趨勢。(2)在水文模型參數(shù)率定中,基于殘差的整體性評價指標(biāo)能夠定量評價模型模擬結(jié)果和實測水文資料的差別,因而被廣泛選作目標(biāo)函數(shù)來指導(dǎo)水文模型的參數(shù)率定。然而,基于整體性評價指標(biāo)的參數(shù)率定方法僅能保障水文模擬結(jié)果和實測水文資料的殘差盡可能小,無法滿足水文模擬結(jié)果和實測水文資料有較高的水文一致程度。因此,本文將能夠量化流域水文特征的水文特性簽名及整體性評價指標(biāo)一起作為參數(shù)率定的目標(biāo)函數(shù),極大提高了徑流預(yù)報的水文一致程度,尤其是提出的流量信息熵差指標(biāo)能夠度量模擬和實測徑流的靜態(tài)統(tǒng)計信息差異,從而提高了預(yù)報徑流擬合流量歷時曲線的能力。同時,針對目標(biāo)函數(shù)個數(shù)過多而出現(xiàn)的支配保留現(xiàn)象,研究工作對水文特性簽名目標(biāo)函數(shù)進(jìn)行離散化,既有效緩解了支配保留效應(yīng),又能兼顧目標(biāo)函數(shù)的區(qū)分性能,提高了水文模型參數(shù)率定可包含的目標(biāo)函數(shù)個數(shù)。(3)針對確定性預(yù)報僅給出變量在未來時刻的一個單點預(yù)報值,沒有提供與預(yù)報相關(guān)的內(nèi)在不確定程度,本文通過建立區(qū)間預(yù)報來度量洪水預(yù)報的不確定性。然而,傳統(tǒng)區(qū)間預(yù)報建立方法需要對水文數(shù)據(jù)或預(yù)報誤差的概率分布進(jìn)行人為假設(shè),而且建立區(qū)間預(yù)報的計算量較大,阻礙了區(qū)間預(yù)報的實際應(yīng)用。因此,本文提出兩種改進(jìn)LUBE區(qū)間預(yù)報方法,第一種較大程度地改進(jìn)了原始單目標(biāo)LUBE區(qū)間預(yù)報方法存在的問題,第二種則是擴(kuò)展單目標(biāo)LUBE區(qū)間預(yù)報方法到多目標(biāo)框架。長江上游洪水區(qū)間預(yù)報的研究結(jié)果表明,兩種方法均明顯提高了區(qū)間預(yù)報效果,在相似的區(qū)間預(yù)報覆蓋率下,利用本文所提方法產(chǎn)生的區(qū)間預(yù)報寬度更窄。同時,本文采用區(qū)間預(yù)報平均相對寬度指標(biāo)計算區(qū)間預(yù)報的相對寬度,提高了高流量時段的洪水預(yù)報效果。此外,多目標(biāo)LUBE區(qū)間預(yù)報方法能夠幫助研究人員根據(jù)需要選擇覆蓋率和寬度合適的區(qū)間預(yù)報,極大地減少了單目標(biāo)LUBE方法中CWC目標(biāo)函數(shù)參數(shù)選擇帶來的工作量。(4)為提高中長期徑流預(yù)報精度,本文研究偏互信息輸入因子選擇方法,從前期實測降水、徑流和遙相關(guān)氣候因子中選擇合適的輸入,通過增加與流域徑流相關(guān)性高的遙相關(guān)氣候因子作為數(shù)據(jù)驅(qū)動模型的輸入,實現(xiàn)了流域中長期徑流高精度預(yù)報。偏互信息輸入因子選擇方法能夠度量輸入變量和輸出變量的線性與非線性相關(guān)關(guān)系,且可以避免冗余輸入變量的選入,函數(shù)測試結(jié)果表明,偏互信息方法對時間序列模型和非線性模型均十分有效,能夠準(zhǔn)確按照與輸出變量相關(guān)程度順序挑選出相關(guān)變量。同時,金沙江流域?qū)嵗芯拷Y(jié)果也表明偏互信息方法適用于水文氣象變量的輸入因子選擇,基于偏互信息方法的預(yù)報結(jié)果優(yōu)于線性相關(guān)系數(shù)法。
[Abstract]:Watershed hydrological analysis and hydrological prediction are two main research directions in the field of hydrology. They are important support for water conservancy project planning and construction, optimal allocation of water resources, and safe, efficient and sustainable utilization. Due to China's special geographical location and climatic conditions, the water resources is extremely uneven distribution in space and time, is strongly affected by the climate change and human activities, a profound change occurred in the water cycle process and the spatial and temporal distribution of water resources law, heightened the safety complexity of watershed hydrologic characteristics and water resources. Especially the large water conservancy project, inter basin water diversion project and other human activities have an important impact on the hydrological system, water conservancy project stress natural runoff basin fragmentation lead to deviations from the evolution of natural conditions makes the hydrological system, spatial and temporal variability of watershed water resources system is more complex, put forward higher requirements on watershed hydrologic analysis and forecast research. The key scientific and technical problems in the evolution of basin water resources around the changing environment and efficient utilization of this paper, in the upper reaches of the Yangtze River as the main research object, research on watershed hydrologic analysis and prediction of the advanced theoretical methods and technical means, research work to alleviate the drought and flood disaster losses and has important theoretical significance and practical value to realize the sustainable utilization of water resources. The relevant research results can be used for reference and reference for river basin management institutions, and the application prospects are wide. The main research contents and innovative results are as follows: (1) in order to overcome the single variable trend analysis method to test the overall hydrological events if there is a significant trend of limitations, this paper introduces the multi variable Mann-Kendal trend analysis method, analysis the change trend of single variable and joint variable respectively on the upper reaches of the Yangtze River Hydrological control station of the annual maximum the annual maximum flood volume and flood peak, 7d years minimum monthly runoff and annual minimum 3 months of average runoff. The case study shows that the flood process in the upper reaches of the Yangtze River tends to decrease, while the low runoff process is increasing. In the overall trend of hydrological event analysis, multivariate Mann-Kendal trend analysis method shows obvious advantages, to test whether the multiple interrelated hydrological variables have significant changes in trend, while the single variable Mann-Kendal trend analysis method can only test a single variable has significant change. Therefore, trend analysis of hydrological events involving multiple interrelated variables requires simultaneous univariate and multivariate trend analysis to fully grasp the trend and overall trend of single hydrological variables in hydrological events. (2) in the calibration of hydrological model parameters, the holistic evaluation index based on residuals can quantitatively evaluate the difference between the simulated results and the observed hydrologic data. Therefore, it is widely selected as the objective function to guide the parameter calibration of hydrological models. However, the method of parameter calibration based on holistic evaluation index can only ensure that the residual of hydrological simulation results and measured hydrologic data is as small as possible, which can not meet the high hydrological consistency of hydrological simulation results and measured hydrological data. Therefore, this paper will be able to sign the hydrological characteristics and overall evaluation index quantification of watershed hydrological characteristics as objective function parameters set, which greatly improves the consistency of hydrological runoff forecasting, especially the static statistical information flow difference information entropy the index can measure the simulated and measured runoff, thus improving the ability to predict runoff flow duration curve fitting. At the same time, according to the objective function of a large number of emerging dominant retention phenomenon, the discretization of the hydrological characteristics of the objective function signature research, can effectively alleviate the dominant reserve effects, and can also distinguish the performance objective function, the objective function improves a number of hydrological model parameters calibration can be contained. (3) for a deterministic prediction, we only give a single point prediction value of variables in the future time, and do not provide the intrinsic uncertainty related to prediction. In this paper, we set up interval prediction to measure the uncertainty of flood forecasting. However, the traditional interval prediction method needs artificial hypothesis for the probability distribution of hydrological data or forecast error, and the computation of interval prediction is large, which hinders the practical application of interval prediction. Therefore, two improved LUBE interval prediction methods are proposed in this paper. The first one improves the existing problems of the original single target LUBE interval prediction method, and the second one is to extend the single target LUBE interval prediction method to the multi-objective framework. The results of flood interval prediction in the upper reaches of Yangtze River indicate that the two methods can obviously improve the effect of interval prediction. Under the similar interval prediction coverage, the interval prediction produced by the proposed method is narrower. At the same time, in this paper, the relative width of interval prediction average relative width is used to calculate the relative width of the interval forecast, which improves the effect of flood forecast in high flow time period. In addition, multi-objective LUBE interval prediction method can help researchers choose interval prediction with appropriate coverage and width according to needs, which greatly reduces the workload of parameter selection of CWC target function in single target LUBE method. (4) in order to improve the long-term runoff forecast accuracy, this paper studies partial mutual information input factor selection method, selecting the appropriate input from the measured rainfall, runoff and teleconnection climate factor, the increase in runoff and watershed high correlation teleconnection climate factors as data driven model input, to achieve the long-term runoff high basin the accuracy of prediction. Partial mutual information input factor selection method can measure the linear and nonlinear correlation between input variables and output variables, and avoid redundant input variables selection. The result of function test shows that partial mutual information method is very good for time series models and nonlinear models.
【學(xué)位授予單位】：華中科技大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2016
【分類號】：P333;P338

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