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Water is arguably our most precious resource, which is related to the hydrological cycle, climate change, regional drought events, and water resource management. In Turkey, besides traditional hydrological studies, Terrestrial Water Storage (TWS) is poorly investigated at a continental scale, with limited and sparse observations. Moreover, TWS is a key parameter for studying drought events through the analysis of its variation. In this paper, TWS variation, and thus drought analysis, spatial mass distribution, long-term mass change, and impact on TWS variation from the parameter scale (e.g., precipitation, rainfall rate, evapotranspiration, soil moisture) to the climatic change perspective are investigated. GRACE (Gravity Recovery and Climate Experiment) Level 3 (Release05-RL05) monthly land mass data of the Centre for Space Research (CSR) processing center covering the period from April 2002 to January 2016, Global Land Data Assimilation System (GLDAS: Mosaic (MOS), NOAH, Variable Infiltration Capacity (VIC)), and Tropical Rainfall Measuring Mission (TRMM-3B43) models and drought indices such as self-calibrating Palmer Drought Severity (SCPDSI), El Niño–Southern Oscillation (ENSO), and North Atlantic Oscillation (NAO) are used for this purpose. Turkey experienced serious drought events interpreted with a significant decrease in the TWS signal during the studied time period. GRACE can help to better predict the possible drought nine months before in terms of a decreasing trend compared to previous studies, which do not take satellite gravity data into account. Moreover, the GRACE signal is more sensitive to agricultural and hydrological drought compared to meteorological drought. Precipitation is an important parameter affecting the spatial pattern of the mass distribution and also the spatial change by inducing an acceleration signal from the eastern side to the western side. In Turkey, the La Nina effect probably has an important role in the meteorological drought turning into agricultural and hydrological drought.

A global gravity model (GGM) is a mathematical function describing the gravity field of the Earth. The assessment of GGMs involves identifying the best-fitting model to local gravity field for geodetic and geophysical applications. Thus, highly accurate independent datasets are required to obtain the appropriate model. In general, GPS/levelling data have been used for this purpose. If these measurements are not performed simultaneously, they may not be reliable due to vertical deformations especially in seismically active countries. Therefore, we used highly precise absolute and vertical gravity gradient measurements obtained by the Scientific and Technological Research Council of Turkey’s (TUBITAK) National Metrology Institute and General Directorate of Mapping within the frame of Turkish Height System Modernization and Gravity Recovery Project over the period of 2016–2018 from Turkey to choose the best GGM for the whole of Turkey among the 19 latest tested satellite-only and combined GGMs (2004–2018). Our results showed that vertical gravity gradient measurements could also be used for the regional validation of GGMs as an independent in situ dataset. The GOCE based XGM2016 combined model and GO_CONS_GCF_2_TIM_R5 satellite-based model were found to be the best-fitting models. The results also showed improvements over the widely used EGM2008 up to the spherical degree 270 for Turkey. The improvements of the GOCE models over the EGM2008 model are mostly seen in mountainous areas such as the Black sea, Aegean Sea, some parts of the Mediterranean, and South-eastern Anatolia regions with maximum improvements in the coastal areas of the Eastern Black Sea. The best-fitting GGMs to local gravity field identified with these measurements could be used for further geodetic and geophysical purposes in Turkey.

<p>For the quasi-geoid determination by 3-D Least Squares Collocation (LSC) in the context of Molodensky’s approach, there is no need to measured or modelled vertical gravity gradient (VGG) as the 3-D LSC takes the varying heights of the gravity observation points into account. However, the use of measured or modelled VGG instead of the thereotical value is expected to improve the quasigeoid-geoid separation term particularly in mountainous areas. The VGG measurements are found to be different from the theoretical value in the range of - % 25 and + % 39 in western Turkey. Previously there has been no study using modelled VGGs for gravimetric geoid modelling in Turkey. VGGs are modelled by 3-D Least Squares Collocation (LSC) in remove-restore approach and validated by terrestrial VGG measurements in western Turkey. The effect of using modelled VGG instead of the theoretical one in quasigeoid-to-geoid separation term is found to be significant. The quasi-geoid computed by 3-D LSC in western Turkey is converted to geoids using theoretical or modelled VGG values and compared with GPS/levelling geoid-undulations.</p><p> </p>

ÖzÜlkemiz gibi deprem kuşağında olan bir coğrafya için deprem araştırmaları ve olası erken uyarı sistemlerine dair olan yeni yaklaşımlar, son zamanlarda meydana gelen depremleri de göz önünde bulunduracak olursak (ör. İzmir, 2020), artan bir önem ve ihtiyaç teşkil etmektedir. Özellikle uyku halinde iken yakalanılan depremler, bilindiği üzere, çok daha vahim sonuçlar doğurmaktadır. Bu çalışmada, mevcut çalışmalardan farklı olarak, ilk tasarımı yapılan deprem erken uyarı sistemi yaklaşımı, uyku halinde iken, içinde bulunan sensörler aracılığı ile ivmeölçer'e dönüştürülen akıllı telefonlar sayesinde, ReQuakenition ismini verdiğimiz bir telefon uygulaması arayüzü ile acil durumlarda olası bir depremin haber verilmesi amaçlandı. Afet ve Acil Durum Yönetimi Başkanlığı (AFAD) web sayfasından indirilen gerçek deprem verilerinden yararlanarak Uzun kısa süreli belleğe sahip (Long-Short Term Memory: LSTM) tekrarlayan sinir ağı mimarisi (Recurrent Neural Network: RNN) derin öğrenme algoritmaları ile eğitilen verilerden elde edilen sonuçlarda %82'nin üzerinde duyarlılık gözlemlendi. Elde edilen bu ilk sonuçlar, son derece yaygın olarak kullanılan akıllı telefonların, deprem erken uyarı sistemlerinde kullanılmak üzere, jeodezik ve sismik ağların yanı sıra çok daha yoğun ve homojen bir ivmeölçer ağı gibi çalışabilmesi adına ümit vericidir.

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