Lake Water Storage Changes Over The Qinghai-Tibetan Plateau From Multi-mission Satellite Data And Its Influencing Factors Analysis

The highest and largest number lake group on earth is distributed in the Qinghai-Tibetan plateau(QTP),which is also the region with the most lakes in China.The QTP is the source of major rivers in China.The lakes in this area play a crucial role in water regulation for these rivers.It is of great significance to effectively measure the change of lake storage in the region for the utilization of water resources and the sustainable development of the country.The multi-satellite data was applied for calculating the lake storage variations in this region in this thesis.The main contents of this dissertain include the study of waveform retracker in the land and water junction;the research on multi-source data fusion method of inland lakes;the automated processing of satellite altimetry;the lake storage variations estimated by altimetry and remote sensing data;the lake storage balance analysis by GRACE observations;and study on the response of the lake storage to climate change.The main work and achievements of this thesis are as follows:(1)The retracked water levels are seriously degraded due to land contamination in altimeter waveforms,while the satellite passes through the land-water junction.A waveform decontamination technique is proposed to reducing the noise caused by land contamination,and then the threshold retracker is applied to dealing with the decontaminated waveform.The accuracy of the SSHs derived by the decontaminated technique is respectively 15cm and 20cm,which evaluated by the geoid and tide gauge data.Incidentally,most available data are remained(97%)in this method.Considering the narrow area of inland lakes,we propose an improved waveform decontamination technique.The accuracy of each algorithm was evaluated with the hydrometer measurements of four lakes in the QTP;the result shows that the accuracy is improved by 2.5cm than threshold retracker,which indicates that the water level of inland lakes could be effectively improved by the waveform decontamination technology.(2)We mainly study the method of multi-source altimetry data fusion for inland lakes.The different altimetry data was unified into the same time system and coordinate system,the system deviation between multi-satellites was eliminated by adjustment method and the precision of water level was improved accordingly.The feasibility of the method was verified by an example.A robust method of rejecting outliers in altimeter data was studied and the clear water level time series has been obtained.An automated program for altimetry data was developed to achieve batch extraction of altimetry measurements from lakes in the QTP and the automatic generation of water level time series.The efficiency of estimating the water level has been improved significantly.(3)The variations of lake level in QTP are estimated by four types of altimetry data in different periods.The lakes were observed using T/P-family and ERS-family altimetry data.The results showed that the average water level change trend was+17.2 cm/yr during the period from 1992 to 2017.The water level changes of 181 lakes were observed by integrated data from Icesat and Cryosat-2 satellite.The results showed that the average change rate of lake level over the QTP was +14.6 cm/yr during the period from 2003 to 2017.For the lake distributed over the entire plateau,it is found that the lake level in the north of QTP shows a rising rate,while the lake level over the Brahmaputra river basin and Indus river basin show a decreasing trend.By using the multi-source altimetry data,it was found that the water level of a large count of lakes turned from falling to rising in 1997,and turned from rising to decreasing in 2012.(4)The NDWI index was applied for extract the lake boundary.The remote sensing data demonstrates the expansion rate of the Qinghai-Tibet Plateau lake area was +452.45km2/yr from 1992 to 2015,while the rapid expansion(+444.6 km2/yr)of lakes in Inner plateau is the main contributer.Moreover,the lake area change rate derived by remote sensing and the lake level change rate derived by altimetry data is quite consistent with each other.We discuss the method of estimating lake storage combined altimetry and remote sensing observations.The calculated results show that the lake storage increased +5.86Gt/yr over the QTP from 1992 to 2015.Whereas the lake with the fastest rising is Siling Tso(+1.22Gt/yr),which accounted for about 21%of the overall increase,and the lake with the fastest falling is the Yambdrok(-0.11Gt/yr).(5)The change of Terrestrial Water Storage(?TWS)over QTP was calculated by GRACE monthly gravity field models,the results showed that the ?TWS was quite consistent with the changes of lake storage(?LWS)in the regional distribution.The TWS of Brahmaputra river basin in the south continues decreasing,the TWS of Qaidam basin in the north continues increasing,and the TWS of Inner basin and Yellow river basin in the middle of plateau turned from increase to decrease in 2012.It is found that the ?LWS is the main contributer to the ?TWS in the inner plateau,and the dominate factor in both ?LWS and ?TWS is the net precipitation.(6)Since the amount of glacial meltwater cannot be estimated accurately,the glacial coefficient is applied to qualitatively analyzing the relationship between the glacial and the variations of lake level in this study.The statistical results represent that there are no significant differences of the water level change rate between glacial-fed lakes and the non-glacial lakes from 2003 to 2009;the average rate of change of the glacial-fed lakes was 20cm/yr,which was similar to the average rate of changes of 22 cm/yr for the non-glacial-fed lakes.Nevertheless,the water level change rate of glacial-fed lakes during 2010-2017 is higher than that of non-glacial lakes(respectively 8cm/yr and 3cm/yr).The water level change rate was analyzed between the lakes in permafrost zone and the ones in non permafrost zone,the results show that the water level change rate of lakes in permafrost areas is more quickly than that in non-frozen areas in all periods.In summary,since the reduction of precipitation in 2012,the contribution of glacial and permafrost meltwater to lake storage has been strengthened,this partly reduces the decline rate of lake level.The method of using precipitation and evaporation data to simulate the ? LWS in closed lakes was proposed,and the contribution of non-net precipitation factors was separated from the? LWS.The sudden water level rise of many lakes over the north of QTP was monitored by Cryosat-2 and Landsat satellite,as well as the outburst flood event of Zhuonai Lake in the near area.This example raises the potential of an operational use of radar altimetry,which could deliver near-real time lake level heights to assess the risk of a glacial lake outburst flood(GLOF)and provide warnings.The relationship between air temperature changes and lake level changes was analyzed.The change of water level was positively correlated with the air temperature change in autumn and negatively correlated in winter.