We focus on the complex characteristics of groundwater level data, including nonlinear trends, seasonal fluctuations, and random disturbances, and introduce the Prophet time series prediction model developed by Facebook. The aim is to use its nonlinear trend capture, seasonal fluctuation analysis, and flexible response ability to outliers and data missing to significantly improve the accuracy of groundwater level anomaly identification. Through observation data from Beilin district seismic station in Suihua city, Heilongjiang province, it is shown that the Prophet model performs well in capturing dynamic characteristics of time series data and can effectively identify anomalies. The high fitting accuracy and predictive ability of adjusted model have been confirmed, with low prediction error and high determination coefficient. In addition, the model identifies water level anomalies related to earthquakes in earthquake prediction, providing a new perspective for earthquake precursor research. This study demonstrates the effectiveness of Prophet model in processing complex time series data, providing a new tool for earthquake prediction.

GNSS technology is widely used in landslide monitoring, but it is difficult to install monitoring equipment in complex high-risk landslide environment. UAV-dropped is expected to realize unmanned deployment of monitoring equipment. In view of the problems of UAV-dropped endurance and terrain threat in complex environment, the path planning of UAV-dropped is particularly critical as the basic mission. In this paper, the path planning problem of UAV-dropped in complex mountainous area is studied in three aspects: 3D real map construction of geological disaster area, cost function design and flight path planning algorithm. In addition, whale optimization algorithm based on adaptive weight and Levy flight strategy is applied to the flight path planning of UAV-dropped. Taking Hongyanzi landslide in Hanyuan county, Sichuan province as the study area, the path planning of UAV-dropped GNSS monitoring equipment was realized.

We focus on the apparent resistivity method in earthquake precursor observation, develop a detection device suitable for its observation system, and conduct theoretical simulation and on-site testing on the device. First, we analyze the apparent resistivity measurement system, and point out the shortcomings of existing detection systems. Second, according to the demand analysis of observation system, the corresponding detection index and circuit are designed, and the detection accuracy of instrument is designed to 0.001 level to improve the performance. Finally, the developed device is theoretically simulated using Simulink, and the impact of interference on observation results is compared and studied. Random earthquake observation stations in Gansu region are selected for on-site testing. The results show that the developed device can not only visually display the working status of apparent resistivity measurement system, but also accurately evaluate the real-time superiority and inferiority of apparent resistivity observation system, and fill the gap in detection device of apparent resistivity observation system and provide great convenience for frontline earthquake workers.

Aiming the issue of reduced accuracy in sea surface height inversion using global navigation satellite system interferometric reflectometry (GNSS-IR) due to elevation angle deviation, a correction method for elevation angle deviation based on the ionospheric region is proposed. To verify the reliability of the correction method for elevation angle deviation, a comparison is made between the inversion results before and after applying the correction to the elevation angle deviation. The results indicate that the inversion results, after correction for elevation angle deviation, exhibit higher accuracy. The method for correcting elevation angle deviation can effectively rectify the deviation caused by the ionosphere.

Current robust fitting algorithms are prone to failure in point cloud data with a high contamination rate. To solve this problem, we introduce a weight matrix in the plane fitting method based on eigenvalue decomposition, where the initial weight is determined based on the normal vector information of point cloud, thus reducing the influence of outliers. We further use the scale-adaptive method to enhance the robustness. The scale factor of this method gradually decreases as the number of iterations increases, effectively solving the problem of low breakdown ration of traditional M estimation. The experimental results show that the breakdown ratio of the proposed algorithm is higher than that of existing robust point cloud fitting methods, and it can accurately estimate plane parameters in the point cloud data with a high outlier ratio.

To objectively evaluate the accuracy of TPXO series ocean tide models for the eastern China sea(ECS), we use the latest FES2014b and EOT20 as reference models. The assessment is performed by computing the root mean square error(RMSE) of the M₂ vertical ocean tide loading(OTL) displacements and the root sum square(RSS) of the 8 principal tidal constituents based on the GPS-observed M₂ vertical OTL displacements and tide gauge observations from the evenly selected 22 GPS sites and 65 tide gauges in the coastal areas, respectively. The results show that: 1) In the whole ECS, EOT20 is the most accurate model with RMSE of 0.41 mm and RSS of 11.1 cm, while the accuracy of FES2014b is slightly lower with RMSE of 0.43 mm and RSS of 11.4 cm. 2) Along the coast of eastern China and the western Korean Peninsula, there are large differences between TPXO models and FES2014b, and the RSS with tide gauge observations are 2-6 times as much as that of FES2014b and EOT20. 3) Both TPXO9_Atlas and TPXO8_Atlas agree better than other models with the M₂ vertical OTL observations in the Ryukyu Islands, and the two models are suggested for the local correction of OTL displacements.

Using the BIC_tp noise model identification criterion, we analyzed the temporal noise characteristics of sea surface height (SSH) and their influencing factors at 350 virtual coastal satellite altimetry stations worldwide. Furthermore, we explored the impact of environmental loads on SSH time series and the characteristics of sea level changes across different time spans. The results indicate that the assumptions of FN+WN, FN+RW+WN, and PL+WN noise models can lead to errors in estimating the velocity parameters of SSH time series. Furthermore, there is a diversity of SSH time series noise models, and the velocity uncertainties under different noise models vary significantly. Identifying their noise characteristics is crucial for accurately obtaining sea level change parameters. The average global sea level rise rates for the different time spans of 1993 to 2006, 2007 to 2020, and 1993 to 2020 are 2.59 mm/a, 4.41 mm/a, and 3.08 mm/a, respectively, indicating that sea level is accelerating its rise. The optimal noise models and velocity changes for the SSH time series before and after environmental loading correction are not significant, indicating that the load effect has a relatively minor impact on the characteristics of SSH time series.

We successfully estimate ice shelf thickness products for Antarctic ice shelves among 2003 and 2022 from the ICESat, CryoSat-2, and ICESat-2 altimetry satellites. The results reveal a rapid thinning trend in the Antarctic ice shelves overall. The Amundsen region is experiencing rapid thinning, and the Amery region is thinning most slowly.

In response to the problems of premature convergence and easily falling into local optima when using traditional global optimization algorithms such as particle swarm optimization and simulated annealing for dispersion curve inversion, we introduce the bald eagle search (BES) algorithm into the study of dispersion curve inversion. Through inversion analysis of multiple typical geological theoretical models and measured data from the Wyoming region of the United States, the results show that the BES algorithm has strong applicability, stability, and noise resistance in the inversion of Rayleigh wave dispersion curves.

We use the ESPAC method to detect the geological structure below the Mogao Grottoes of Dunhuang using observed data obtained by linear array. The detection results show that the layers determined by microtremor survey method are clearly visible, with significant fluctuations of each layer on the two-dimensional microtremor apparent S-wave velocity profile. The covering layer is thick at both ends and thin in the middle. There is a bedrock intrusion in the middle of profile, and there is a solitary stone with a width of 30 m×40 m. Using geological survey data calibration of the relevant region, we show that the thickness of Quaternary cover layer represented by mixed backfill, fine sand, and gravel sand is about 8 m, and the burial depth of complete bedrock surface is about 30 m. The research results can provide geophysical basis for the protection of cultural relics in the Mogao Grottoes.