Sea Level Monitoring Research Articles

Data-driven optimization of coastal sea level monitoring: Leveraging known patterns for enhanced reconstruction

Efficiently configuring sea level monitoring stations is crucial for obtaining accurate spatiotemporal data while managing operational and maintenance costs and addressing the challenges posed by missing data. This study focuses on optimizing the selection of stations within Turkey's coastal sea level monitoring network by leveraging the inherent lower dimensionality in data. The network consists of 18 stations distributed along Turkey's coastline. To identify dominant patterns in historical sea level data, Empirical Orthogonal Function (EOF) analysis was employed, followed by the application of the QR decomposition with column pivoting algorithm. Model performance is assessed using the Nash-Sutcliffe coefficient of efficiency (CE) and root mean square error (RMSE). Remarkably, the results demonstrated that reconstructing the entire dataset, encompassing all 18 stations was possible with a CE of 0.94 and an RMSE of 0.06. Even utilizing data from two or three stations alone achieves acceptable reconstruction accuracy. The effectiveness of EOF analysis combined with QR with column pivoting algorithm suggests promising applications in various scientific fields.

The IoT-Based Early Warning System for Detecting High Tide Floods (ROB-EWS) in Tambak Lorok, Semarang Indonesia

Background and Objectives: The Tambaklorok fishing village area, located on the northern coast of Semarang City, Indonesia, is susceptible to sea level fluctuations, which often lead to tidal flooding and seawater encroaching into residential areas. Consequently, a seawater flood detector (rob) is needed for effective disaster mitigation for affected communities. This study aims to implement a disaster mitigation system by installing an IoT-based Seawater Flood (Rob) Early Warning System to reduce disaster risks and their impacts on the community. Methods: The IoT-based Early Warning System is designed to detect floods by monitoring sea level height parameters. Results: IoT-based devices measure sea level using ultrasonic sensors, with the readings processed by a microprocessor. The data is then periodically analyzed and transmitted to an application in real-time. This technology allows for real-time information dissemination through web applications and alerts in the form of sirens. These warnings enable residents to evacuate and move to safer areas. The siren alerts are categorized into two levels: Alert 1 indicates that seawater is approaching the land boundary, while Alert 2 signals that water has begun to enter residential areas. Additionally, designated evacuation zones will guide affected communities to safer areas. Conclusion: The installation of an IoT-based Early Warning System delivers real-time information to help mitigate the impact of rising sea levels (rob) in the Tambak Lorok fishing village community.

Datum Alignment Between GNSS-IR Sea Level Estimations and Tide Gauges in Türkiye: A Vertical Local Tie Approach

Connecting Asia and Europe, Türkiye is vital for maritime transit, which requires continuous and precise sea level monitoring. Traditional tide gauges (TGs), while valuable, often have data gaps. GNSS-IR provides an alternative, though aligning it with TG measurements is challenging. This study introduces a method to estimate Vertical Local Tie (VLT) between the TG zero and the GNSS antenna phase centre, allowing GNSS-IR sea level estimates to be aligned with TG measurements. In disruptions, GNSS-IR can consistently supplement TG data. We validated this approach by evaluating a 1-year data from four GNSS stations namely, ARSZ, GADA, TRBZ, and YLVA involving in the Türkiye National Sea Level Monitoring System (TUDES) network. These stations are located on the coasts of the Mediterranean, Aegean, Black, and Marmara Seas, respectively. Compared with the TG measurements, ARSZ achieved the highest epoch-based correlation as 87.00%. For daily averages, the GADA and TRBZ showed a correlation of over 96% with TG data. Notably, TRBZ recorded the lowest daily average RMSE at 2.2 cm using the VLT-median approach. The results demonstrate that when VLT is utilized, well-configured GNSS stations, ensuring uninterrupted transmissions and appropriate data intervals, provide a reliable alternative or complement to TGs for sea level monitoring.

Potential Sunda Strait tsunami hazard due to the current deformation of Anak Krakatau

Abstract The tsunami Sunda Strait event at 2018 is a prove that volcanic activity may trigger a devastating and unpredictable tsunami. Several findings indicate that this catasrophe generated by flank collapse caused by the instability of Gunung Anak Krakatau (AK). Other processes of volcanic activity that cause tsunamis include pyroclastic flows, subaerial and submarine landslides, underwater explosions, blasts, and caldera collapse. In the 1883, Krakatau Mount produced the largest tsunami event, and it is apparent that AK is one of threats in Sunda Strait that may potentially produce tsunami in the future since it is still active until now. Some latest research shows there are two submarine landslide threats near Gunung Anak Krakatau; in the northeast part of AK and an elliptical landslide source in the west part of AK with the estimated landslide volume about 0.014 km3 and 0.6 km3, respectively. Those threats will be simulated by shallow water equation model to obtain the tsunami wave height near the source and at crucial areas along Sunda Strait as well as its tsunami time arrival. The first scenario is sourced from a new deposit from the 2018 eruption, and the latter is a change of slopes bathymetry due to volcanic or seismic activity. It is observed that the highest elevation of tsunami from the first scenario reached only 2.5 cm at Tanjung Lesung, Banten and 80 cm at the nearest island, Panjang Island. The second scenario has the height of 50 cm at Labuan, Banten and 70 cm at Panjang Island. The tsunami time travel at the surrounding islands is ranging between 0.6 - 5.8 minutes (scenario 1) and 0.7-4.9 minutes (scenario 2). Both scenario reached the inexpensive device of sea level monitoring at the east side of Rakata after 5 minutes and the height is 30 cm and 1.6 cm respectively for scenario 1 and 2.

Sea Surface Height Measurements Based on Multi-Antenna GNSS Buoys.

Sea level monitoring is an essential foundational project for studying global climate change and the rise in sea levels. Satellite radar altimeters, which can sometimes provide inaccurate sea surface height data near the coast, are affected by both the instrument itself and geophysical factors. Buoys equipped with GNSS receivers offer a relatively flexible deployment at sea, allowing for long-term, high-precision measurements of sea surface heights. When operating at sea, GNSS buoys undergo complex movements with multiple degrees of freedom. Attitude measurements are a crucial source of information for understanding the motion state of the buoy at sea, which is related to the buoy's stability and reliability during its development. In this study, we designed and deployed a four-antenna GNSS buoy with both position and attitude measurement capabilities near Jimiya Wharf in Qingdao, China, to conduct offshore sea surface monitoring activities. The GNSS data were processed using the Precise Point Positioning (PPK) method to obtain a time series of sea surface heights, and the accuracy was evaluated using synchronous observation data from a small sea surface height radar. The difference between the GNSS buoy and the full-time radar was calculated, resulting in a root-mean-square error (RMSE) of 1.15 cm. Concurrently, the attitude of the GNSS buoy was calculated using multi-antenna technology, and the vertical elevation of the GNSS buoy antenna was corrected using the obtained attitude data. The RMSE between the corrected GNSS buoy data and the high ground radar was 1.12 cm, indicating that the four-antenna GNSS buoy can not only acquire high-precision coastal sea level data but also achieve synchronous measurement of the buoy's attitude. Furthermore, the data accuracy was also improved after the sea level attitude correction.

Assessing Tidal Models in the Ryukyu Islands Region Using the ENOPF Method

Abstract Satellite remote sensing can monitor sea level changes at temporal and spatial scales, plays an important role in the study of tides, and is widely used in numerical tidal models. However, these tidal models are usually computationally expensive. The equidistant nodes orthogonal polynomial fitting (ENOPF) method may overcome that drawback. This study evaluates the accuracy of the ENOPF method in fitting the major tidal constituents in the region near the Ryukyu Islands, where the water depth on either side of the islands varies significantly. The results show that the ENOPF method can accurately fit the major tidal constituents in the presence of complex topography. Furthermore, this approach can also be used to generate reasonable cotidal charts and provide valuable tidal information for hydrodynamic model simulations in the East China Sea. For the high-resolution hydrodynamic model of the East China Sea in particular, reasonable open boundary conditions can be provided by the ENOPF method.

Unifying the Nepal height system and China height system based on gravity frequency shift approach

Highly accurate international height reference frames with long-term stability, global consistency, and homogeneity are crucial for monitoring sea level variations, understanding climate change, managing disasters, and supporting other applications that benefit scientific research and societal well-being. Currently, there are over 100 local height reference systems worldwide. Unifying these systems is a pivotal step toward constructing international height reference frames. The method introduced in this study—the gravity frequency shift via Satellite Frequency Signal Transfer (SFST)—represents a groundbreaking relativistic geodetic approach, demonstrating its potential to surpass the constraints of conventional techniques. The advent of high-precision optical atomic clocks (OAC) with an accuracy level of 1×10−18 has facilitated this method's implementation. The International Association of Geodesy (IAG) has established the International Height Reference System (IHRS) and its practical realization, the International Height Reference Frame (IHRF). Our study focuses on two neighbouring height systems: the China Height System (CHS) and the Nepal Height System (NHS), separated by the Himalayas and the Tibetan plateau. We aim to unify these two systems by determining the geopotential and orthometric height differences between their respective height datum stations: the Qingdao Height Datum Station (QHDS) and the Madar Height Datum Station (MHDS) using a simulation experiment with the method mentioned above. Using an OAC with an accuracy of 1×10−18, we identified a geopotential difference of −8.348±0.464m2s−2 and an orthometric height difference of 0.786±0.047 m between QHDS and MHDS. These results suggest that the introduced method could unify any two height systems with few-centimeter-level precision, emphasizing its significance in contributing to the construction of the IHRS/IHRF with today's required precision. In summary, the SFST technique is a novel geodetic method that offers an alternative for height system unification, delivering centimeter-level precision, surpassing traditional methods, and supporting the development of the IHRF.

Comparison between Microwave Radar Gauge and Pressure Gauge in Monitoring Sea Level Surface at Alexandria Naval Port

Comparison between Microwave Radar Gauge and Pressure Gauge in Monitoring Sea Level Surface at Alexandria Naval Port

Does Sea Level Change in The Strait of Istanbul, Türkiye?

Bosphorus is a narrow water passage connecting the Marmara Sea and the Black Sea through a sea level balance current flow. In this study, change points in mean and in variance and trend analysis are performed to reveal whether sea level is changing or not. Moreover, the simple linear regression is calculated to explain the relationships among sea level data in the three stations located in the Black Sea, the Marmara Sea and Bosphorus. The Turkish National Sea Level Monitoring System (TUDES) measures sea water level at each 15-minute periods in three stations in order to minimize the effect of turbulence. The sea level in the coastal area of Istanbul city is most populous region with its highly economic importance. The most important reason for this is the serious decrease in the amount of water discharged into the Black Sea due to dams and excessive water usage. The three sea level stations have no change points on the average of the whole data. The change points in variance are depicted especially in gap data years and especially around year 2018. While the difference in the sea level of the Istanbul and Sile stations contain seasonality, the difference between the other stations has a sinusoidal component. While this study lights on understanding the sea level characteristics of the Bosphorus, it also emphasizes the importance of accuracy, completeness and long-term measurement data requirement.

IoT Sea Level Monitoring Development and Field Testing Study

The measurement of sea level is essential to oceanography because it provides vital information about the ocean environment, such as tides, currents, and water temperature. This research aimed to develop an Internet of Things (IoT)-based sea level monitoring device that can precisely measure sea level and transmit data in real time. An ESP32 microcontroller, a GSM module, an MS5803-14BA sensor, and a battery constituted the device. To protect the electronics from the ocean environment, the components were assembled on a PCB board and placed within a waterproof box. The field test was conducted for 17 hours at the Class 1 Navigation Office Port in Tanjungpinang, and the Ubidots platform was used to monitor the data. The device accurately measured sea level with an RMSE of 0.69 cm and an accuracy rate of 99.47%, according to the results. However, the field test also revealed problems with data transmission, with 18.81% of the data not being transmitted to the server. This low data transmission rate may have been caused by low RSSI levels and signal quality issues with the operator. To understand the causes of these data losses and improve the device's overall performance, additional research is required. This study demonstrated the viability of utilizing an Internet of Things-based sea level monitoring device to precisely measure sea level and transmit data in real time. It provides valuable information for the improvement and further development of sea level monitoring systems.

Accuracy investigation of GNSS-reflectometry for sea level monitoring on Horseshoe Island, Antarctica: preliminary results of the Turkish permanent GNSS station (TUR1)

Accuracy investigation of GNSS-reflectometry for sea level monitoring on Horseshoe Island, Antarctica: preliminary results of the Turkish permanent GNSS station (TUR1)

Numerical Modeling of Tidal Phenomena of the Penzhinskaya Bay

In this study, the Delft3D-Flow hydrodynamic model was used to determine the characteristics of the main tidal waves and currents in the Penzhina Bay (Sea of Okhotsk, Russia). The initial and boundary conditions are set according to the TPXO9 model data, the salinity and water temperature for each model layer are set based on the reanalysis data of the HYCOM ocean general circulation model, with a time step of 3 h. E-uropean Center for Medium-Range Weather Forecasts ECMWF (European Center for Medium-Range Weather Forecasts) reanalysis ERA-5 was used as meteoforcing. Modeling was performed for the ice-free period from May to September 2005. Maps of cotidal lines, tidal ellipses, and reversibility coefficient for the main tide waves: semidiurnal wave M2 and diurnal wave K1 were constructed. The model was verified by comparing the published and calculated harmonic components for 9 sea level monitoring points located in the Penzhina Bay. Conformance evaluation generally shows a high degree of consistency between model and reference data. The values of the coefficient of determination R2 between the series formed by the model and published harmonic components are in the range of 0.96–0.99. According to the magnitude of relative errors, the simulation results are divided into two consistency categories – high (1.48–2.14%) and satisfactory (2.93–4.27%). Spatial patterns of distribution for the values of relative errors were not found. A certain inconsistency in the results is presumably due to the time discretization of the observation time support and the short sea level monitoring data series used to calculate the published harmonic components at the Penzhina Bay.

Combined Coastal Sea Level Estimation Considering Astronomical Tide and Storm Surge Effects: Model Development and Its Application in Thermaikos Gulf, Greece

Tide gauge recordings furnish the longest and almost the most continuous data source of sea level monitoring. Traditionally, they are collected using tide gauge instrumentation fixed at seaport locations to provide a time series of sea level estimates relative to a local geodetic benchmark. Sea level tidal observables are distinguished in the astronomical tide component originating from the attraction of the Earth–Moon–Sun gravitational system, and the storm surges ought to have meteorological effects due to wind and atmospheric air pressure variation. This study provides a comprehensive methodological approach and software to compute sea level considering astronomical tides enhanced by storm surge effects. The model is realized and assessed using a long-standing set of 21 consecutive years of tidal and meteorological measurements originating from Thermaikos Gulf, Greece. Analyses show model verification and conclusions about the tidal behavior of the test area, suggesting a satisfactory agreement (86% Willmott Skill factor, 9 cm standard deviation) between predicted and observed sea level estimates, accounting for amplitude and the time shift of skew surges.

Coastal Waveform Retracking for Synthetic Aperture Altimeters Using a Multiple Optimization Parabolic Cylinder Algorithm

The importance of monitoring sea level in coastal zones becomes more and more obvious in the era of global climate change, because, in coastal zones, although satellite altimetry is an ideal tool in measuring sea level over open ocean, but its accuracy often decreases significantly at coast due to land contamination. Although the accuracy of waveform processing algorithms for synthetic aperture altimeters has been improved in the last decade, the computational speed is still not fast enough to meet the requirements of real-time processing, and the accuracy cannot meet the needs of nearshore areas within 1 km from the coast. To improve the efficiency and accuracy in the coastal zone, this study proposed an innovative waveform retracking scheme for the coastal zone based on a multiple optimization parabolic cylinder algorithm (MOPCA) integrated with machine learning algorithms such as recurrent neural network and Bayesian estimation. The algorithm was validated using 153-pass repeat cycle data from Sentinel-6 over Qianliyan Island and Hong Kong–Wanshan Archipelago. The computational speed of the proposed algorithm was four to five times faster than the current operational synthetic aperture radar (SAR) retracking algorithm, and its accuracy within 0–20 km from the island was comparable to the most popular SAMOSA+ algorithm, better than the official data product provided by Sentinel-6. Especially, the proposed algorithm demonstrates remarkable stability in the sense of proceeding speed. It maintains consistent performance, even when dealing with intricate wave patterns within a proximity of 1 km from the coast. The results showed that the proposed scheme greatly improved the quality of coastal altimetry waveform retracking.

Insights on the Extreme Storm Surge Event of the 22 November 2022 in the Venice Lagoon

The Italian Institute for Environmental Protection and Research (ISPRA) manages the national sea state real time monitoring system for Italy, which consists of the National Sea Level Network (RMN), the North Adriatic and Venice Lagoon Sea Level Network (RMLV), the National Wave Networks (RON), and a marine weather forecasting system. These systems are particularly deployed to monitor and predict storm surges that affect the northern part of the Adriatic Sea and the Venice Lagoon, usually causing damages and morphological impacts over the highly anthropized coastal areas. On 22 November 2022, an extreme storm surge event occurred in the northern Adriatic Sea, producing severe damages on its coastline. Venice and the surrounding urban settlements have been protected from flooding thanks to the operation of the Mo.S.E. (Modulo Sperimentale Elettromeccanico) system, a set of artificial barriers built to isolate the lagoon from the sea in case of extreme high tides. Coastal flooding prevention measures, such as storm-surge barriers, are indeed being widely adopted globally because of the accelerating rise in sea levels. An analysis of this extreme event is presented here to highlight the functionality and the usefulness of the ISPRA sea state monitoring system. In particular, the analysis of the as-if scenario reproducing the natural tide propagation within the lagoon, neglecting the operation of the Mo.S.E. system, can only be pursued by using hydrodynamic models forced using extensive observed data. Results highlight that the “not-regulated” sea level would have exceeded 200 cm above the reference datum at Chioggia, a threshold never recorded in the Venice Lagoon since sea level monitoring systems have been operational.

Assessment and exploitation of coastal low resolution mode sea level data from CryoSat-2 on the entrance to the Gulf of California

The CryoSat-2 mission (CS2), initially conceived for sea ice measurements, is also useful for sea level monitoring in oceanic and coastal areas. Only specific regions have two high resolution modes (SAR Delay/Doppler and SAR-Interferometric modes), while the rest of the areas are measured in low-resolution mode (LRM). The entrance to the Gulf of California presents this mode of operation. Sea Level Anomalies (SLA) obtained from CS2 are compared with tide gauges at three locations, Cabo San Lucas (CSL) south of the Baja California peninsula, Mazatlán (MZ) and San Blas (SB) on the continental margin. The comparison shows good agreement between SLAs in CSL and MZ, with standard deviations of the differences (SDD) lower than 0.09 m and Pearson’s correlations higher than 0.7 (95% of confidence level). San Blas is in a complex location and with less data, presenting an SDD greater than 0.13 m and a correlation below 0.55. We present the cross-shore seasonal and interannual variability in CSL and MZ using the CS2 SLA time series from 2011 to 2020. The variability shows the presence of events such as El Niño (2015 to early 2016), La Niña (2011) and the warm event of 2014 (nicknamed “the Blob”). Additionally, the residual time series of CS2 obtained after extracting the annual, semi-annual and monthly components, shows the East side (at MZ) is more affected by El Niño/La Niña variability while the West side (at CSL) is more influenced by the Blob/El Niño. Estimated long-term SLA trend at both locations are around 3.1 mm/yr, supporting similar findings by previous studies.

Sea-Level Estimation from GNSS-IR under Loose Constraints Based on Local Mean Decomposition.

The global navigation satellite system-interferometric reflectometry (GNSS-IR) technique has emerged as an effective coastal sea-level monitoring solution. However, the accuracy and stability of GNSS-IR sea-level estimation based on quadratic fitting are limited by the retrieval range of reflector height (RH range) and satellite-elevation range, reducing the flexibility of this technology. This study introduces a new GNSS-IR sea-level estimation model that combines local mean decomposition (LMD) and Lomb-Scargle periodogram (LSP). LMD can decompose the signal-to-noise ratio (SNR) arc into a series of signal components with different frequencies. The signal components containing information from the sea surface are selected to construct the oscillation term, and its frequency is extracted by LSP. To this end, observational data from SC02 sites in the United States are used to evaluate the accuracy level of the model. Then, the performance of LMD and the influence of noise on retrieval results are analyzed from two aspects: RH ranges and satellite-elevation ranges. Finally, the sea-level variation for one consecutive year is estimated to verify the stability of the model in long-term monitoring. The results show that the oscillation term obtained by LMD has a lower noise level than other signal separation methods, effectively improving the accuracy of retrieval results and avoiding abnormal values. Moreover, it still performs well under loose constraints (a wide RH range and a high-elevation range). In one consecutive year of retrieval results, the new model based on LMD has a significant improvement effect over quadratic fitting, and the root mean square error and mean absolute error of retrieval results obtained in each month on average are improved by 8.34% and 8.87%, respectively.

The Rise and Fall of Alaska and Yukon Glaciers Detected by TOPEX/Poseidon and Jason‐2 Altimeters Using a Novel Glacier‐Threshold Method

AbstractRadar altimetry has been used to monitor sea level changes and ice sheet elevation changes for decades. Over mountain glaciers, radar altimetry has limited applications due to contaminated waveforms caused by complex glacier surfaces and steep terrains. In this study, we develop a glacier‐threshold method (GTM) to determine glacier elevation changes in Alaska and Yukon. The GTM retracks waveforms, reduces terrain effect and detects invalid elevation observations from the TOPEX/Poseidon (T/P) and Jason‐2 (J2) altimeters, resulting in an average usable rate of 35% from original altimeter‐measured heights. The selected measurements are used to construct time series of glacier elevation changes over 1993–2002 (T/P) and 2008–2016 (J2) at 47 sites. A crossover analysis, validation by airborne laser altimetry observations, and comparisons with recent studies confirm the estimated glacier elevation changes. Our findings suggest that the thinning of glaciers in Alaska and Yukon has been ubiquitous in recent years. The site near Walsh Glacier has the highest thinning rate of −5.71 ± 0.09 m/yr, followed by Chitina Glacier at −4.51 ± 0.21 m/yr. Only 17% of sites show glacier thickening due to surges and mass accumulations. Using a sophisticated data processing algorithm like the GTM, we show that altimeter data from the repeat TOPEX‐Jason missions can be used to monitor long‐term glacier elevation changes at inaccessible spots, creating an additional value for altimeter missions originally purposed for monitoring long‐term sea level change.

Multi-GNSS Combination Multipath Reflectometry Based on IVMD Method for Sea Level Retrieval

Sea level monitoring is particularly important in coastal areas that are vulnerable to marine disasters. It was recently demonstrated that the global navigation satellite system multipath reflectometry (GNSS-MR) technique, which uses multipath signals reflected from the sea, can be applied to determine the sea level. However, this approach does not provide sufficient accuracy or equally spaced sampling to meet the actual sea level monitoring requirements for certain stations. To solve the deficiency of the traditional GNSS-MR technique, the least squares method, which is based on sliding time windows, was applied. Using the sliding windows to combine the quad-constellation multi-GNSS retrieval can effectively improve the accuracy and time resolution of sea level retrieval, but insufficient data or a lack of data in some time ranges and missing overflights in some timeframes can lead to the calculation of faults in these time windows, causing the estimated loss of corresponding sampling points. In this study, we used a robust regression solution strategy based on multi-GNSS sea level retrieval and an improved variational mode decomposition (IVMD) algorithm to process sea level retrieval after robust regression. BRST and HKQT stations are located on the western coast of France and the northern coast of Hong Kong. The two stations can both receive satellite observation data from the four satellite systems. Through the experiment, using data retrieved from the BRST and HKQT stations, the results of this study demonstrate that the IVMD method based on multi-GNSS sea level retrieval can further improve the accuracy to <10 cm and can achieve 10 min equal interval sampling. This is significant for using GNSS-MR technology to detect sea level height and monitor sea level change and could be applied to other sites.

Seabed morphology characterization for Indonesian cable-based tsunameter route in Cilacap Segment, Indonesia

The Indonesian government has initiated a program for Ina Tsunami Early Warning System by the development of sea level monitoring systems including a Cable-Based Tsunameter. Seabed feature characterization is a critical part of the engineering design process as well as for the understanding of environmental impacts. This study aims to characterize the seabed morphology along the cable route plan at the Cilacap segment by analyzing the seafloor mapping and identifying of any existing hazards. A series of marine surveys for the data acquisition hydro-acoustic and geophysics was conducted by RV Baruna Jaya IV, in December 2020. The analysis and interpretation of seabed geomorphology were conducted using qualitative methods on four Blocks. Results indicate anthropogenic objects (debris, wreck, and scars), while the features of ripples, and pockmarks. Furthermore, sediment layers which are interpreted into four units from the top to bottom shows fine grained sediment towards the top. Finally, the hazard assessment denotes that there are three hazard categories (low, medium, and high), of which the highest category is located in the pockmark cluster (Block 4). The existing CBT cable route place is faced with geomorphological obstacles and environmental threats, so it’s recommended to change the route as far as 50meters.