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- MakaleAçık Erişim2024Scopus SJRQ1Monitoring Surface Deformations in a Fossil Landslide Zone and Identifying Potential Failure Mechanisms: A Case Study of Gümüşhane State Hospital
Alemdag, Selçuk; Yalvaç, Sefa; Bjelotomić Oršulić, Olga; Kara, Osman; Zeybek, Halil İbrahim; Bostanci, Hasan Tahsin; Markovinović, Danko
The escalating occurrence of landslides has drawn increasing attention from the scientific community, primarily driven by a combination of natural phenomena such as unpredictable seismic events, intensified precipitation, and rapid snowmelt attributable to climate fluctuations, compounded by inadequacies in engineering practices during site selection. Within the scope of this investigation, contemporary geodetic techniques using the GNSS were employed to monitor structural and surface deformations in and around a hospital edifice situated within an ancient fossil landslide region. Additionally, inclinometer measurements facilitated the determination of slip circle parameters. A subsequent analysis integrated these datasets to scrutinize both the hospital structure and its surrounding slopes. In addition to the finite element method, four different limit equilibrium methods (Bishop, GLE–Morgenstern–Price, Spencer, and Janbu) were used in the evaluation of stability. Since the safety number determined in all analyses was <1, it was determined that the slope containing the hospital building was unstable. The movement has occurred again due to the additional load created by the hospital building built on the currently stable slope, the effect of surface and groundwater, and the improperly designed road route. As a result of geodetic monitoring, it was determined that the sliding speed on the surface was in the N-E direction and was approximately 3 cm, and this situation almost coincided with inclinometer measurements.
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İncele - MakaleYalnız künye2023Scopus SJRQ1Excessive groundwater withdrawal and resultant land subsidence in the Küçük Menderes River Basin, Turkey as estimated from InSAR-SBAS and GNSS measurements
Yalvaç, Sefa; Alemdağ, Selçuk; Zeybek, Halil İbrahim; Yalvaç, Murat
Küçük Menderes River Basin (KMRB) is located in the western part of Turkey in the city of İzmir. The basin hosts about half a million people and 90% of the population makes their living from farming and animal husbandry. Most of the water needs for agricultural irrigation, animal husbandry, and drinking are met from groundwater resources in the basin. Since the water pumped from the aquifers cannot be naturally recharged by surface waters and precipitation, the groundwater level is rapidly receding and a decrease of up to 150 meters has been observed in the historical groundwater level time series since the 1990s. For this reason, land subsidence occurred in the basin and as a result of this, crustal surface cracks have formed and infrastructure and superstructure facilities have been endangered. To prevent loss of life and property that may occur in the future, it has become necessary to estimate the magnitude and the expansion zone of the land subsidence by carrying out geodetic monitoring studies in the region. In this study, the analyzes performed by Interferometric Synthetic Aperture Radar-Small Baseline Subset (InSAR-SBAS) and Global Navigation Satellite System (GNSS) methods to monitor land subsidence in the KMRB are presented. For this purpose, monthly 74 SAR images from 2017 to the end of 2022 were evaluated according to the SBAS procedure in the GMTSAR academic analysis software. In order to, both validate the InSAR-SBAS results and convert the deformation rate in the Line of Sight (LOS) to the ellipsoid normal direction, 3 periods of GNSS campaign were performed between 2021 and 2023 in 5 different GNSS stations and evaluated with the GAMIT/GLOBK software. According to the analyses, the land subsidence rate of up to −165 mm/year has been estimated in the KMRB, especially in the district centers of Bayındır and Ödemiş. In addition, unlike many studies, different rates and propagation of subsidence were determined in different parts of the basin depending on the aquifer type and precipitation. Monthly time series of the deformations were created and the behavior of the deformations and its relationship with the groundwater withdrawal and the lithological structure in the region was scrutinized. Thus, the spatio-temporal behaviour of the land subsidence and the associated geological factors were revealed.
AtıfScopus13WoS11OpenAlex11İncele - MakaleYalnız künye2020Scopus SJRQ2Validating InSAR-SBAS results by means of different GNSS analysis techniques in medium- and high-grade deformation areas
Yalvac, Sefa
This study aimed to validate the interferometric synthetic aperture radar (InSAR) method by using relative and absolute Global Navigation Satellite System (GNSS) techniques. In this context, two land subsidence areas, one high (Mexico City) and one medium (Aguascalientes), were monitored between 2014 and 2018 by using Sentinel 1A satellite data. The monitoring was carried out with the Small Baseline Subset (SBAS) technique using 46 images for Mexico City and 18 images for Aguascalientes. Concordantly, the GNSS Continuously Operating Reference Station (CORS) data in the regions were analyzed with relative and Precise Point Positioning (PPP) GNSS analysis techniques. The time series obtained from three different analyses were compared and the results were evaluated in light of statistical criteria. According to the results, it is determined that the InSAR-SBAS technique can vary up to ± 20 mm from the displacement values obtained from GNSS due to various noise sources. Such deviations were limited to a few samples, and in general the differentiations were reasonable in the range of 7–8 mm. The difference between the deformation velocity estimation results obtained from the three different methods varied between 3 and 10 mm/year. In this context, these findings suggest that the InSAR-SBAS technique is an effective method for monitoring land deformation with the accuracy of sub-centimeter decided. In addition, PPP which has become an increasingly popular technique showed fast and reliable results in the range of 5–10 mm for InSAR verification. Moreover, with this study, most current results for Mexico City, which is the world’s fastest subsiding metropole, were achieved. In the central region of the city, the detected 300 mm/year of subsidence rate was updated as 370 mm/year. In addition, Aguascalientes was monitored by using the Sentinel 1A satellite mission for the first time in this study. The 60 mm/year subsidence rate obtained for Aguascalientes in previous studies was updated and it was estimated that there are zones where this rate reaches up to − 115 mm/year levels. In this regard, it was concluded that the deformation rate has increased for both regions since the previous monitoring studies.
AtıfScopus60WoS53OpenAlex62İncele - MakaleYalnız künye2018Scopus SJRQ1Galileo satellite data contribution to GNSS solutions for short and long baselines
Yalvac, S.; Berber, M.
GALILEO (Europe's Global Navigation Satellite System) is going full speed ahead to achieve full constellation by 2020. Since GALILEO is currently an emerging system, the contribution of these satellites to GNSS (Global Navigation Satellite System) solutions needs to be investigated. For this purpose, GNSS data collected at three IGS (International GNSS Service) MGEX (Multi GNSS Experiment) stations are analyzed. For the analyses, GPS (Global Positioning System) only, GLONASS (Russia's Global Navigation Satellite System) only, GALILEO-only and combined solutions are tested and also effect of baseline length is examined. The results indicate that compared to GPS, GLONASS and ALL (GPS + GLONASS + GALILEO) solutions, GALILEO results vary greatly. When GALILEO observations are combined with other observations, the precision goes down. That is to say, for short baseline solution, GALILEO results fluctuate around 1 cm in the horizontal plane and in the vertical plane variations are mostly within 3–5 cm. For long baseline solution, GALILEO results are going up and down in the horizontal between 2 and 3 cm and in the vertical roughly 10 cm. In terms of accuracy, for short baseline solution, GALILEO-only solution is close to GPS-only solution; yet, we cannot say the same thing for long baseline solution.
AtıfScopus13WoS11OpenAlex12İncele - BildiriYalnız künye2017Detecting and removing repetitive errors from PPP time series by means of adaptive filter
Yalvaci, Sefa; Ustun, Aydin; Berber, Mike Mustafa
PPP (Precise Point Positioning) is a relatively new GNSS (Global Navigation Satellite System) method that enables position determinations using a single receiver. Being able to survey with a single receiver makes this approach more attractive and affordable than other GNSS positioning techniques. Since a single receiver is used, a drawback of this technique is propagation of errors such as orbit and clock uncertainties, atmospheric disturbances etc. Due to these errors, precision of point positioning may reach up to decimeter levels. Fortunately, some of these error sources such as orbital errors, multipath etc. are repetitive errors and therefore can be detected by using digital filters. Adaptive noise canceling filters are used to detect the correlated part of the time series. These filters optimize themselves using the Least Mean Square (LMS) algorithm which is a powerful tool for Geosciences and are also used for many engineering applications. In this study, it is aimed to detect repetitive errors on coordinate time series by using adaptive noise canceling filter. For the application, four stations have been selected from NGS CORS (National Geodetic Survey Continuously Operating Reference Station) network. Two of these stations are highly affected by multipath error and the other two are not. The coordinate time series of the GNSS sites have been obtained using PPP technique on kinematic mode (epoch by epoch) for several consecutive days. The cross-correlation analysis has been performed and up to 92% correlation has been detected between the daily time series. The correlated part of the data set has been captured by means of adaptive noise canceling filter and removed from the data set. After the filtration process, up to 50% precision improvement has been achieved on coordinate time series, especially for the stations affected by multipath.
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