Monitoring Of Surface Deformation And Modelling Of Terrestrial Water Storage In Dali Of Yunnan Province By Using SBAS-InSAR Technology

Terrestrial water storage(TWS)change is the result of evapotranspiration,rainfall,runoff,groundwater exploitation,and other natural and human factors,and has a positive response to global or regional climate evolution.Accurate acquisition of long-term TWS changes is of great significance to the study of the regional water cycle,regional climate change,rational allocation of water resources,guidance of agricultural production,and early warning of drought and flood disasters.However,the traditional TWS acquisition method using a variety of ground-based sensors and manual measurement has some problems such as the small coverage range of the single station,heavy workload,limited coverage range of network space,and unequal distribution.The hydrological model using atmospheric and hydrological observations to estimate TWS changes can effectively reflect the hydrological cycle process,but there are many uncertainties in the physical model itself and model parameters,and there are great differences between the inversion results of different models.The Gravity Recovery and Climate Experiment(GRACE)provides an unprecedented opportunity to probe temporal and spatial variations in terrestrial water stocks(TWS)over a wide range of areas.However,the low temporal resolution(month)of the GRACE system and the discontinuous data loss during operation have been plagued by TWS research.Data Assimilation(DA)not only provides a conditional estimate but also takes into account the uncertainty of the model and the measurement value,it provides the potential to effectively reduce the measurement scale in space and time,which is unique in TWS inversion The advantages.Using the DA to process the vertical deformation derived from the elastic response of the Earth’s surface is another approach to estimate the TWS.The Small Baseline Subset Interferometric Synthetic Aperture Radar(SBAS-InSAR)establishes a short baseline SAR image set,extracts permanent scatterers as monitoring points,and obtains the time series deformation of monitoring points.It has unparalleled advantages in large-scale surface time series deformation monitoring.The purpose of this study was to demonstrate whether the time-series deformation obtained by the SBAS-InSAR and DA processing can estimate the TWS.For validation purposes,we conducted a DA experiment in Dali Prefecture,which is a draught-prone area in the southwestern part of Yunnan Province.The TWS estimates were validated by using the GRACE inversion results.Excessive exploitation of groundwater for a long time has resulted in a sharp drop in groundwater level,causing irreversible damage to the natural environment and man-made structures,such as uneven ground subsidence and ground subsidence.The surface deformation caused by overexploitation of groundwater is not caused by the change in surface water quality.To explore the impact of vertical surface deformation caused by the inelastic response on TWS estimation,it is necessary to monitor the surface deformation in the overexploitation area of groundwater.In addition,the uneven deformation in the influence area of groundwater overexploitation threatens the operation safety of the high-speed railway.Strengthening the monitoring of surface deformation in groundwater mining areas is an effective way to rationally utilize resources and prevent and control geological disasters.Aiming at the problem that DInSAR technology is susceptible to atmospheric effect and time decorrelation in large-scale settlement funnel detection,this paper uses the Sentinel-1unwrapped interferogram published on the Li CSAR website and uses the NSBAS method to process 448 interferometric images to obtain the rapid acquisition.The temporal subsidence results of 0.001°(90 m)resolution in Dali Prefecture from July 3,2015,to February 25,2021,were found,and two subsidence funnels,which were not mentioned in the literature before,were found,respectively,Xiangyun County and Binchuan County.Although Li CSAR can quickly obtain large-scale surface deformation information,due to the low resolution of Li CSAR data,it is impossible to accurately analyze the cause of subsidence and the impact of subsidence on surrounding structures.Given the problem that the resolution of Li CSAR data is low and detailed deformation information cannot be obtained,this paper uses Gamma and Mint Py to process the Sentinel-1A data of 102 scenes through the range of the sedimentation funnel obtained by Li CSAR and obtains a higher resolution of the sedimentation funnel area.Based on the time series deformation results of the surface,the dynamic changes of the subsidence in this area and the reasons for its formation are analyzed.The results show that:(1)The subsidence of Binchuan County is relatively serious,the subsidence range is large(about 18 square kilometers),and the maximum annual subsidence rate reaches-60mm/year;the subsidence range of Xiangyun County is relatively small(about 13 square kilometers),the maximum sedimentation rate reaches-55mm/year.In addition,the chronological subsidence of Xiangyun County and Binchuan County has obvious seasonal changes.(2)The Guangda railway passes through the edge of the subsidence area in Xiangyun County,and the accumulation of large gradients threatens the safety of railway operations.Therefore,it is necessary to monitor the subsidence funnel in Xiangyun County for a long time.In this paper,the data assimilation(DA)method was employed to integrate the vertical deformation obtained from the small baseline subset(SBAS)InSAR processing into the NASA Catchment Land Surface Model(CLSM),which improved the estimation of the TWS.Firstly,I used a one-dimensional Ensemble Kalman Filter for DA research to estimate the TWS in Dali Prefecture,southwestern China.Results revealed that the numerical difference between the estimated TWS and the GRACE TWS retrievals was significantly decreased by the SBAS-InSAR DA method than the OL method.In addition,the temporal resolution of the SBAS-InSAR DA-based TWS was improved to 12 days compared with GRACE-based TWS.Furthermore,we recovered the discontinuous deletion and blank of GRACE-based TWS from2015 to 2018 by the SBAS-InSAR DA method.To verify the accuracy of TWS estimation by SBAS-InSAR DA,the TWS obtained from SBAS-InSAR DA and OL were evaluated using GRACE TWS.For the whole study area,the average TWS changes obtained by SBAS-InSAR DA and OL demonstrate the superiority of the SBAS-InSAR DA method.In particular,the SBAS-InSAR DA improved ub RMSD and reduced the average TWS ub RMSD in Dali Prefecture from 61 mm to 30 mm.However,for R and ub RMSD of a single pixel,there are some unsatisfactory results.In some pixels,the value of R is lower after data assimilation than before.The ub RMSD values of the two methods are both too high in some areas,which may be caused by the changes in surface water reserves(such as lakes and rivers)are not fully reflected in the CLSM.The results show that it is effective to integrate the TWS variation information contained in the SBAS-InSAR vertical temporal deformation into the land surface model through DA.