雅礱江上游積雪面積變化與徑流關(guān)系研究
發(fā)布時(shí)間：2019-03-22 20:15
【摘要】：雅礱江是長(zhǎng)江上游金沙江最大的一級(jí)河流,是中國(guó)水能資源最富集的河流之一,也是我國(guó)水電規(guī)劃建設(shè)的十三大水電基地之一。甘孜以上地區(qū)作為雅礱江的河源,其河川徑流特征變化將會(huì)從長(zhǎng)期和短期兩方面影響雅礱江中下游水資源的開(kāi)發(fā)和利用情況。分析和預(yù)測(cè)甘孜段徑流的變化規(guī)律,不僅有助于深入了解雅礱江流域的水資源特性,為流域內(nèi)水資源合理開(kāi)發(fā)利用提供依據(jù),也有助于雅礱江流域梯級(jí)水電站調(diào)度的徑流預(yù)報(bào)提供參考。本文將雅礱江流域甘孜以上地區(qū)作為研究區(qū),以2009-2014年HJ數(shù)據(jù)和2000-2014年MODIS積雪產(chǎn)品、甘孜水文站徑流數(shù)據(jù)、研究區(qū)內(nèi)的清水河、石渠和甘孜氣象站的逐日降水和氣溫?cái)?shù)據(jù)作為數(shù)據(jù)資料。首先,對(duì)比研究已有HJ數(shù)據(jù)的積雪識(shí)別方法的優(yōu)缺點(diǎn),提出了改進(jìn)的HJ數(shù)據(jù)積雪識(shí)別方法,采用GF數(shù)據(jù)對(duì)其進(jìn)行精度評(píng)價(jià),并作為參考值對(duì)MODIS積雪產(chǎn)品進(jìn)行精度評(píng)估;其次,在獲取積雪面積數(shù)據(jù)的基礎(chǔ)上,分析了研究區(qū)徑流、積雪覆蓋面積、氣溫和降水的不同階段的年內(nèi)、年際變化特征;再次,利用相關(guān)分析和多元回歸分析法分析了各階段徑流及其影響因素的相關(guān)方向和相關(guān)程度,探討了枯水期和融雪影響期徑流變化對(duì)積雪、氣溫和降水變化的響應(yīng)程度,并對(duì)徑流進(jìn)行了預(yù)測(cè)分析;最后,實(shí)現(xiàn)研究區(qū)HBV水文模型的模擬,并根據(jù)相關(guān)分析結(jié)果,增加積雪覆蓋面積的輸入改進(jìn)水文模型,提高徑流的模擬預(yù)測(cè)精度。結(jié)果表明,經(jīng)同時(shí)相的GF數(shù)據(jù)精度驗(yàn)證,本文提出的僅用環(huán)境星CCD數(shù)據(jù)作為數(shù)據(jù)源的積雪識(shí)別算法分類精度在90%以上,可以快速、有效地提取研究區(qū)積雪面積。雅礱江甘孜以上地區(qū)徑流曲線呈“單峰型”,屬于雨水、融雪水混合補(bǔ)給類型的河流,2000-2014年間融雪影響期和汛期徑流均表現(xiàn)為顯著增加趨勢(shì)。研究區(qū)積雪累積和融化幅度較大,平均每年融化43332.33 km2的新雪,枯水期平均積雪面積年際波動(dòng)較大,無(wú)明顯的變化規(guī)律,融雪影響期和汛期積雪面積均呈現(xiàn)微弱的上升趨勢(shì)。枯水期降水有微弱的增加趨勢(shì),高海拔地區(qū)的氣溫增加趨勢(shì)顯著,整體氣溫的增加隨海拔的降低而稍有減緩;融雪影響期的降水除甘孜附近無(wú)明顯變化趨勢(shì),研究區(qū)其他地區(qū)均有顯著增加;汛期氣溫相對(duì)穩(wěn)定,降水呈微弱的上升趨勢(shì)。研究區(qū)枯水期徑流主要通過(guò)地下水補(bǔ)給,與氣溫呈中度正相關(guān),與降水和積雪面積無(wú)顯著相關(guān)性;融雪影響期徑流與降水和氣溫表現(xiàn)為顯著正相關(guān),與積雪覆蓋面積表現(xiàn)為顯著負(fù)相關(guān),降水、氣溫和積雪面積的彈力系數(shù)分別為0.289、0.779、0.004,且均通過(guò)90%置信度的檢驗(yàn),其中,降水增加對(duì)徑流變化的影響程度為58.11%,冬季積雪覆蓋面積和氣溫對(duì)徑流的影響程度和為30.85%;汛期徑流與降水表現(xiàn)為中度正相關(guān),降水的彈力系數(shù)為0.219,對(duì)徑流的影響程度為89.07%。融雪影響期徑流與冬季積雪面積、上月均氣溫和上月均降水的回歸結(jié)果以及枯水期徑流與上月徑流的回歸結(jié)果在95%的置信度下通過(guò)了回歸方程的五種檢驗(yàn),且擬合度R2均在0.80以上,可用于預(yù)估枯水期和融雪影響期的月均徑流。將2005~2007年作為率定期,2010~2013年作為驗(yàn)證期,應(yīng)用HBV水文模型對(duì)甘孜站日、月徑流進(jìn)行模擬,驗(yàn)證期模型效率系數(shù)為0.8153和0.8702,RE為-8.399和-8.4105,說(shuō)明HBV水文模型總體上可較好地模擬徑流變化。改進(jìn)后的水文模型效率系數(shù)為0.8726和0.9250,RE為-4.3313和-4.3725,模型效率系數(shù)和誤差范圍均有所改善,可以更好預(yù)測(cè)和模擬研究區(qū)徑流。
[Abstract]:The Yamen River is the largest river in the Jinsha River in the upper reaches of the Yangtze River. It is one of the most abundant rivers in China's hydropower resources. It is also one of the ten major hydropower bases in China's hydropower planning and construction. As the river source of the Yamen River, the change of the river runoff characteristics will influence the development and utilization of the water resources in the middle and lower reaches of the Yamen River from the long-term and the short-term. The analysis and prediction of the change law of the runoff in the river basin can not only help to understand the characteristics of the water resources in the Yalanjiang river basin, provide the basis for the rational development and utilization of the water resources in the basin, and also help to provide the reference for the runoff prediction of the cascade hydropower station in the Yabjiang river basin. As a research area, the daily precipitation and air temperature data of Qingshuihe, Shiqu and Ganzi meteorological station in the study area are used as data for the study area of the area of Ganzi and above in the Yalanjiang river basin. The daily precipitation and air temperature data of the Clear Water River, the stone canal and the Ganzi meteorological station in the study area are taken as data by the HJ data in 2009-2014 and the MODIS snow-covered products of 2000-2014 and the runoff data of the Ganzi hydrological station. First of all, the advantages and disadvantages of the snow cover recognition method of HJ data are compared, the improved HJ data snow-snow identification method is proposed, the precision evaluation is carried out by using the GF data, and the MODIS snow product is evaluated with the reference value as a reference value, and secondly, on the basis of acquiring the snow area data, The annual and interannual variation of runoff, snow cover area, air temperature and precipitation in the study area were analyzed, and the correlation direction and degree of the runoff and its influencing factors were analyzed by correlation analysis and multiple regression analysis. In this paper, the response degree of the runoff change on the change of snow, air temperature and precipitation during the dry season and the snow-melting period is discussed, and the runoff is predicted and analyzed. Finally, the simulation of the HBV hydrological model in the study area is realized, and the input and improved hydrological model of the snow cover area is increased according to the relevant analysis results. And the simulation prediction precision of the runoff is improved. The results show that, with the verification of the data accuracy of GF data at the same time, the classification accuracy of the snow-snow recognition algorithm only with the environmental star CCD data as the data source is above 90%, and the area of the snow in the study area can be effectively and effectively extracted. The runoff curve of the area above the Ganzi River in the Yafangjiang River is a "unimodal", which belongs to the mixed recharge type of the rainwater and the snow-melting water. In the period 2000-2014, the snow-melting-effect period and the flood-season runoff show a significant increase in the trend. The accumulated and melting range of the snow in the study area is larger, the average annual melting of the new snow is 43332.33km2, and the average snow cover area in the dry season is relatively large, there is no obvious change law, and the snow-melting effect period and the snow cover area in the flood season show a weak upward trend. There is a slight increase in the precipitation in the dry season, the increase of the temperature in the high-altitude area is significant, the increase of the whole air temperature is slightly slower with the decrease of the altitude, and the precipitation of the snow-melting-effect period has no obvious change trend in the vicinity of the Ganzi, and there is a significant increase in the other parts of the study area; The temperature of the flood season is relatively stable and the precipitation is in a weak upward trend. The runoff in the dry season of the study area is mainly supplied through the groundwater, which is moderately positive with the temperature, and has no significant correlation with the precipitation and the area of the snow. The runoff and the precipitation and the air temperature show a significant positive correlation with the snow-melting effect, and the rainfall is negatively correlated with the snow cover area. The elastic coefficient of the air temperature and the snow cover area is 0.289, 0.779, and 0.004, and all passes the test of 90% confidence, among which, the effect of the precipitation increase on the runoff change is 58.11%, and the influence degree of the snow cover area and the air temperature on the runoff is 30.85%; The runoff and precipitation in the flood season are moderate and positive, the elastic coefficient of the precipitation is 0.219, and the effect on the runoff is 89.07%. The regression results of the annual runoff and the winter snow cover area, the upper monthly temperature and the last monthly precipitation, and the regression results of the runoff in the dry season and the last-month runoff have passed the five tests of the regression equation with 95% confidence, and the fitting degree R2 is more than 0.80, Can be used for estimating the monthly average runoff of the dry season and the snow-melting influence period. During the period from 2005 to 2007, as the period of verification, the period of 2010 to 2013 was used as the verification period, and the day and monthly runoff of the Ganzi station were simulated by using the HBV hydrological model. The efficiency coefficient of the model was 0.8153 and 0.8702, and RE was-8.399 and-8.4105, which indicated that the hydrological model of the HBV could well simulate the runoff change. The improved hydrological model efficiency coefficient is 0.8726 and 0.9250, RE is-4.3313 and-4.3725, the model efficiency coefficient and the error range are all improved, and the study area run-off can be better predicted and simulated.
【學(xué)位授予單位】：蘭州交通大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類號(hào)】：P426.635;P333.1
本文編號(hào)：2445882
[Abstract]:The Yamen River is the largest river in the Jinsha River in the upper reaches of the Yangtze River. It is one of the most abundant rivers in China's hydropower resources. It is also one of the ten major hydropower bases in China's hydropower planning and construction. As the river source of the Yamen River, the change of the river runoff characteristics will influence the development and utilization of the water resources in the middle and lower reaches of the Yamen River from the long-term and the short-term. The analysis and prediction of the change law of the runoff in the river basin can not only help to understand the characteristics of the water resources in the Yalanjiang river basin, provide the basis for the rational development and utilization of the water resources in the basin, and also help to provide the reference for the runoff prediction of the cascade hydropower station in the Yabjiang river basin. As a research area, the daily precipitation and air temperature data of Qingshuihe, Shiqu and Ganzi meteorological station in the study area are used as data for the study area of the area of Ganzi and above in the Yalanjiang river basin. The daily precipitation and air temperature data of the Clear Water River, the stone canal and the Ganzi meteorological station in the study area are taken as data by the HJ data in 2009-2014 and the MODIS snow-covered products of 2000-2014 and the runoff data of the Ganzi hydrological station. First of all, the advantages and disadvantages of the snow cover recognition method of HJ data are compared, the improved HJ data snow-snow identification method is proposed, the precision evaluation is carried out by using the GF data, and the MODIS snow product is evaluated with the reference value as a reference value, and secondly, on the basis of acquiring the snow area data, The annual and interannual variation of runoff, snow cover area, air temperature and precipitation in the study area were analyzed, and the correlation direction and degree of the runoff and its influencing factors were analyzed by correlation analysis and multiple regression analysis. In this paper, the response degree of the runoff change on the change of snow, air temperature and precipitation during the dry season and the snow-melting period is discussed, and the runoff is predicted and analyzed. Finally, the simulation of the HBV hydrological model in the study area is realized, and the input and improved hydrological model of the snow cover area is increased according to the relevant analysis results. And the simulation prediction precision of the runoff is improved. The results show that, with the verification of the data accuracy of GF data at the same time, the classification accuracy of the snow-snow recognition algorithm only with the environmental star CCD data as the data source is above 90%, and the area of the snow in the study area can be effectively and effectively extracted. The runoff curve of the area above the Ganzi River in the Yafangjiang River is a "unimodal", which belongs to the mixed recharge type of the rainwater and the snow-melting water. In the period 2000-2014, the snow-melting-effect period and the flood-season runoff show a significant increase in the trend. The accumulated and melting range of the snow in the study area is larger, the average annual melting of the new snow is 43332.33km2, and the average snow cover area in the dry season is relatively large, there is no obvious change law, and the snow-melting effect period and the snow cover area in the flood season show a weak upward trend. There is a slight increase in the precipitation in the dry season, the increase of the temperature in the high-altitude area is significant, the increase of the whole air temperature is slightly slower with the decrease of the altitude, and the precipitation of the snow-melting-effect period has no obvious change trend in the vicinity of the Ganzi, and there is a significant increase in the other parts of the study area; The temperature of the flood season is relatively stable and the precipitation is in a weak upward trend. The runoff in the dry season of the study area is mainly supplied through the groundwater, which is moderately positive with the temperature, and has no significant correlation with the precipitation and the area of the snow. The runoff and the precipitation and the air temperature show a significant positive correlation with the snow-melting effect, and the rainfall is negatively correlated with the snow cover area. The elastic coefficient of the air temperature and the snow cover area is 0.289, 0.779, and 0.004, and all passes the test of 90% confidence, among which, the effect of the precipitation increase on the runoff change is 58.11%, and the influence degree of the snow cover area and the air temperature on the runoff is 30.85%; The runoff and precipitation in the flood season are moderate and positive, the elastic coefficient of the precipitation is 0.219, and the effect on the runoff is 89.07%. The regression results of the annual runoff and the winter snow cover area, the upper monthly temperature and the last monthly precipitation, and the regression results of the runoff in the dry season and the last-month runoff have passed the five tests of the regression equation with 95% confidence, and the fitting degree R2 is more than 0.80, Can be used for estimating the monthly average runoff of the dry season and the snow-melting influence period. During the period from 2005 to 2007, as the period of verification, the period of 2010 to 2013 was used as the verification period, and the day and monthly runoff of the Ganzi station were simulated by using the HBV hydrological model. The efficiency coefficient of the model was 0.8153 and 0.8702, and RE was-8.399 and-8.4105, which indicated that the hydrological model of the HBV could well simulate the runoff change. The improved hydrological model efficiency coefficient is 0.8726 and 0.9250, RE is-4.3313 and-4.3725, the model efficiency coefficient and the error range are all improved, and the study area run-off can be better predicted and simulated.
【學(xué)位授予單位】：蘭州交通大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類號(hào)】：P426.635;P333.1
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