COSMOS-Europe: a European network of cosmic-ray neutron soil moisture sensors

[EN] Climate change increases the occurrence and severity of droughts due to increasing temperatures, altered circulation patterns, and reduced snow occurrence. While Europe has suffered from drought events in the last decade unlike ever seen since the beginning of weather recordings, harmonized long-term datasets across the continent are needed to monitor change and support predictions. Here we present soil moisture data from 66 cosmic-ray neutron sensors (CRNSs) in Europe (COSMOS-Europe for short) covering recent drought events. The CRNS sites are distributed across Europe and cover all major land use types and climate zones in Europe. The raw neutron count data from the CRNS stations were provided by 24 research institutions and processed using state-of-the-art methods. The harmonized processing included correction of the raw neutron counts and a harmonized methodology for the conversion into soil moisture based on available in situ information. In addition, the uncertainty estimate is provided with the dataset, information that is particularly useful for remote sensing and modeling applications. This paper presents the current spatiotemporal coverage of CRNS stations in Europe and describes the protocols for data processing from raw measurements to consistent soil moisture products. The data of the presented COSMOS-Europe network open up a manifold of potential applications for environmental research, such as remote sensing data validation, trend analysis, or model assimilation The dataset could be of particular importance for the analysis of extreme climatic events at the continental scale. Due its timely relevance in the scope of climate change in the recent years, we demonstrate this potential application with a brief analysis on the spatiotemporal soil moisture variability. The dataset, entitled "Dataset of COSMOS-Europe: A European network of Cosmic-Ray Neutron Soil Moisture Sensors", is shared via Forschungszentrum Julich: https://doi.org/10.34731/x9s3-kr48 (Bogena and Ney, 2021).We thank TERENO (Terrestrial Environmental Observatories), funded by the Helmholtz-Gemeinschaft for the financing and maintenance of CRNS stations. We acknowledge financial support by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) of the research unit FOR 2694 Cosmic Sense (grant no. 357874777) and by the German Federal Ministry of Education of the Research BiookonomieREVIER, Digitales Geosystem -Rheinisches Revier project (grant no. 031B0918A). COSMOS-UK has been supported financially by the UK's Natural Environment Research Council (grant no. NE/R016429/1). The Olocau experimental watershed is partially supported by the Spanish Ministry of Science and Innovation through the research project TETISCHANGE (grant no. RTI2018-093717-BI00). The Calderona experimental site is partially supported by the Spanish Ministry of Science and Innovation through the research projects CEHYRFO-MED (grant no. CGL2017-86839C3-2-R) and SILVADAPT.NET (grant no. RED2018-102719-T) and the LIFE project RESILIENT FORESTS (grant no. LIFE17 CCA/ES/000063). The University of Bristol's Sheepdrove sites have been supported by the UK's Natural Environment Research Council through a number of projects (grant nos. NE/M003086/1, NE/R004897/1, and NE/T005645/1) and by the International Atomic Energy Agency of the United Nations (grant no. CRP D12014).Bogena, HR.; Schrön, M.; Jakobi, J.; Ney, P.; Zacharias, S.; Andreasen, M.; Baatz, R.... (2022). COSMOS-Europe: a European network of cosmic-ray neutron soil moisture sensors. Earth System Science Data. 14(3):1125-1151. https://doi.org/10.5194/essd-14-1125-20221125115114

COSMOS-Europe : a European network of cosmic-ray neutron soil moisture sensors

We thank TERENO (Terrestrial Environmental Observatories), funded by the Helmholtz-Gemeinschaft for the financing and maintenance of CRNS stations. We acknowledge financial support by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) of the research unit FOR 2694 Cosmic Sense (grant no. 357874777) and by the German Federal Ministry of Education of the Research BioökonomieREVIER, Digitales Geosystem – Rheinisches Revier project (grant no. 031B0918A). COSMOS-UK has been supported financially by the UK’s Natural Environment Research Council (grant no. NE/R016429/1). The Olocau experimental watershed is partially supported by the Spanish Ministry of Science and Innovation through the research project TETISCHANGE (grant no. RTI2018-093717-BI00). The Calderona experimental site is partially supported by the Spanish Ministry of Science and Innovation through the research projects CEHYRFO-MED (grant no. CGL2017-86839- C3-2-R) and SILVADAPT.NET (grant no. RED2018-102719-T) and the LIFE project RESILIENT FORESTS (grant no. LIFE17 CCA/ES/000063). The University of Bristol’s Sheepdrove sites have been supported by the UK’s Natural Environment Research Council through a number of projects (grant nos. NE/M003086/1, NE/R004897/1, and NE/T005645/1) and by the International Atomic Energy Agency of the United Nations (grant no. CRP D12014). Acknowledgements. We thank Peter Strauss and Gerhab Rab from the Institute for Land and Water Management Research, Federal Agency for Water Management Austria, Petzenkirchen, Austria. We thank Trenton Franz from the School of Natural Resources, University of Nebraska–Lincoln, Lincoln, NE, United States. We also thank Carmen Zengerle, Mandy Kasner, Felix Pohl, and Solveig Landmark, UFZ Leipzig, for supporting field calibration, lab analysis, and data processing. We furthermore thank Daniel Dolfus, Marius Schmidt, Ansgar Weuthen, and Bernd Schilling, Forschungszentrum Jülich, Germany. The COSMOS-UK project team is thanked for making its data available to COSMOS-Europe. Luca Stevanato is thanked for the technical details about the Finapp sensor. The stations at Cunnersdorf, Lindenberg, and Harzgerode have been supported by Falk Böttcher, Frank Beyrich, and Petra Fude, German Weather Service (DWD). The Zerbst site has been supported by Getec Green Energy GmbH and Jörg Kachelmann (Meteologix AG). The CESBIO sites have been supported by the CNES TOSCA program. The ERA5-Land data are provided by ECMWF (Muñoz Sabater, 2021). The Jena dataset was retrieved at the site of The Jena Experiment, operated by DFG research unit FOR 1451.Peer reviewedPublisher PD

Beton ağırlık barajlarının sismik davranışlarının tahmin edilmesi için yer hareketlerinin ölçeklendirilmesi.

Designing dams for seismic safety gains importance as the number of dams are increasing as a result of increasing need in water storage and hydropower. To define a structure’s seismic safety, scaling of accelerograms should be considered as one of the most crucial elements. Appropriate scaling of ground motion records is required to better estimate the linear and nonlinear structural response of a structure. Although, in literature, there exist numerous methods dealing with this issue, it is required to determine the most suitable ones for designing concrete gravity dams. In this study, in order to compare the effectiveness of different ground motion scaling procedures, four different ground motion scaling procedures were used. The scaling methods used in this thesis are namely, non-stationary spectral matching, scaling for ASCE-7-10, scaling of records to arithmetic mean of maximum incremental velocity and Modal Pushover Based Scaling. The two dimensional Concrete Gravity Dam models are analyzed by utilizing non-linear dynamic analyses for the selected and scaled records.M.S. - Master of Scienc

Yağış-akış modellemesi için kozmik ışın nötron algılaması ile elde edilen toprak nemininin kullanılmasındaki fırsatlar ve zorluklar

Retrieving or estimating soil moisture is one of the most important elements of hydrology, since most of the hydrological studies consider the absence (drought) or excessiveness (flood) of water stored in the soil. Water stored in a basin has a very strong relation with the amount of soil moisture thus knowing the soil moisture significantly facilitates the estimation of other parameters of the hydrological cycle. For agricultural decision making systems, it is also vital to know whether the plants receive the amount of water necessary for their growth, which can be indicated by the amount of soil moisture. There are various ways of measuring soil moisture, where each technique has its own advantages and disadvantages. Some of these methods can provide very accurate measurements with very high costs or they may have very high temporal resolutions with limited spatial coverages. Among different methods, soil moisture measurement from recently invented Cosmic Ray Neutron Probes (CRNPs) has a good potential to be used in hydrological studies due to its larger spatial coverage, low cost and high temporal resolution. It is also possible to use this product together with satellite soil moisture products to obtain reliable soil moisture information with even more spatial coverage. The aim of this study is to assess the effectiveness of CRNPs in determination of soil moisture at basin scale, to validate satellite soil moisture products and to use the soil moisture information derived from CRNP and satellite products for improving hydrological modeling. For this study, the first CRNP of Turkey has been installed in Çakıt Basin, south of Turkey, and the neutron counts obtained from the CRNP have been converted into soil moisture values after a series of correction and conversion processes. The CRNP based soil moisture data have been used in the validation of different soil moisture satellite products to test the effectiveness of CRNPs in satellite product validation and assess the potential of using CRNPs in conjunction with satellite soil moisture products for studies covering relatively larger areas. The relation between soil moisture and evaporation is also investigated through CRNP soil moisture values. Finally, CRNP based soil moisture data have been introduced into the calibration of a conceptual hydrological model and it has been found that introducing CRNP soil moisture data into NAM conceptual model improves the model statistics of Çakıt Basin (421 km²) and one of its sub basins, Darboğaz sub-basin (121 km²). Using CRNP based soil moisture data to calibrate the NAM model increased the Kling-Gupta Efficiency score for the discharge data of Çakıt Basin from 0.56 (Calibration) and 0.42 (Validation) to 0.81 (Calibration) and 0.64 (Validation). Similar improvements were noted for most of the statistical measures for both Çakıt Basin and Darboğaz sub-basin.Toprak nemini ölçmek veya tahmin etmek, hidrolojinin en önemli unsurlarından olup hidrolojik çalışmaların çoğu toprakta depolanan suyun yokluğunu (kuraklık) veya fazlalığını (taşkın) dikkate alır. Bir havzada depolanan suyun toprak nemi miktarı ile çok güçlü bir ilişkisi vardır, bu nedenle toprak nemini bilmek hidrolojik döngünün diğer parametrelerinin tahminini önemli ölçüde kolaylaştırır. Tarımsal karar verme sistemlerinde, bitkilerin büyümeleri için gerekli olan miktarda su alıp almadıklarını bilmek de hayati önem taşımakla birlikte bu bilgi toprak nem miktarı ile oldukça ilişkilidir. Her teknik kendi avantaj ve dezavantajlarına sahip olmakla birlikte, toprak nemini ölçmenin çeşitli yolları vardır. Bu yöntemlerden bazıları çok yüksek maliyetlerle çok doğru ölçümler sağlayabilir veya sınırlı mekansal kapsama alanıyla çok yüksek zamansal çözünürlüklere sahip olabilir. Farklı yöntemler arasında, yakın zamanda icat edilen Kozmik Işın Nötron Sayaçlarından (CRNP'ler) toprak nemi ölçümleri, daha geniş mekansal kapsamı, düşük maliyeti ve yüksek zamansal çözünürlüğü nedeniyle hidrolojik çalışmalarda kullanılmak için iyi bir potansiyele sahiptir. Bu ürünü uydu toprak nemi ürünleri ile birlikte kullanarak daha fazla mekansal kapsama ile güvenilir toprak nemi bilgisi elde etmek de mümkündür. Bu çalışmanın amacı, havza ölçeğinde toprak nemi tayininde CRNP'lerin etkinliğini değerlendirmek, uydu toprak nemi ürünlerini doğrulamak ve CRNP ile uydu ürünlerinden elde edilen toprak nemi bilgilerini hidrolojik modellemeyi geliştirmek için kullanmaktır. Bu çalışma için Türkiye'nin ilk CRNP'si Türkiye'nin güneyindeki Çakıt Havzası'na kurulmuş ve CRNP'den elde edilen nötron sayıları bir dizi düzeltme ve dönüştürme işleminden sonra toprak nem değerlerine dönüştürülmüştür. CRNP'ye dayalı toprak nemi verileri, uydu doğrulamasında CRNP'lerin etkinliğini test etmek ve nispeten daha geniş alanları kapsayan çalışmalar için uydu toprak nemi ürünleri ile birlikte CRNP'leri kullanma potansiyelini değerlendirmek için farklı toprak nemi uydu ürünlerinin doğrulamasında kullanılmıştır. Toprak nemi ile buharlaşma arasındaki ilişki de CRNP toprak nemi değerleri üzerinden araştırılmıştır. Son olarak, kavramsal bir hidrolojik modelin kalibrasyonuna CRNP bazlı toprak nemi verileri dahil edilmiş ve CRNP toprak nemi verilerinin NAM kavramsal modeline dahil edilmesinin Çakıt Havzası'nda (421 km²) ve alt havzalarından biri olan Darboğaz alt havzası'nda (121 km²) model istatistiklerini geliştirdiği sonucuna ulaşılmıştır. NAM modelini kalibre etmek için CRNP bazlı toprak nemi verilerinin kullanılması, Çakıt Havzası debi verileri için Kling-Gupta Verimlilik skorunu 0,56 (Kalibrasyon) ve 0,42 (Doğrulama)'dan 0,81 (Kalibrasyon) ve 0,64 (Doğrulama)'ya yükseltmiştir. Hem Çakıt Havzası hem de Darboğaz Alt Havzası için istatistiksel ölçütlerin çoğunda benzer gelişmeler kaydedilmiştir.Ph.D. - Doctoral Progra

Potential use of Cosmic Ray Neutron Sensor in estimating state variables in hydrological models

Knowing state variables-fluxes and storages of water and energy- that are propagated in time by the model physics is crucial in hydrological modeling. Soil moisture and snow water equivalent are the most important state variables of water storage. Measurement of soil moisture is possible via several methods including: Laboratory tests and time domain reflectometers (having high accuracies but smaller measurement footprints), ground penetrating radar and remote sensing methods (having large measurement footprints but lower accuracies and resolutions). Typical methods for measuring SWE include point measurements (snow tubes) and large-scale measurements (remote sensing). In this study we want to present the potential use of the cosmic-ray neutron sensor (CRNS) to monitor soil moisture and SWE. The CRNS measures above-ground moderated neutron intensity within a radius of approximately 300 m. It was installed at elevation of 1459 m in the south part of Turkey and an ML3 ThetaProbe (CS 616) soil moisture sensor was established at 5cm depth to get continuous soil moisture values. There is a path eddy covariance system with energy balance sensors installed at 100 m north to the cosmic ray probe and daily snow depth has been measured at this location for the water year 2017. Neutron count measurements were corrected for the changes in atmospheric pressure, atmospheric water vapor and intensity of incoming neutron flux. The calibration of the volumetric soil moisture was performed, from the laboratory analysis, the bulk density in the foot print of CRNS varies between 1.56(g/cm3) -1.25 (g/cm3), and the dominant soil texture is silty clay loam and silt loam. The water content reflectometer was calibrated for soil-specific conditions and soil moisture estimates were also corrected with respect to soil temperature. An average of 35% difference is observed between the daily volumetric soil moisture obtained from CRNS and CS616. Both sensors show consistent changes in soil moisture due to the storm events. Although CS 616 measurements are 30% larger than the CRP measurements, both sensors showed 4.5% increase in volumetric soil moisture due to the storm of 15.5 mm. Satellite soil moisture products obtained from the Soil Moisture and Ocean Salinity (SMOS) and the METOP-A/B Advanced Scatterometer (ASCAT) were compared with the measurements of the CRNS. The snow depth values were converted to SWE values by using the snow density values. The SWE values were negatively correlated with the CRNS-measured moderated neutron intensity, giving Pearson correlation coefficients of 0.92 (2016/2017). A linear regression performed on the calculated SWE values from measured snow depths and moderated neutron intensity counts for 2016/2017 yielded an R2 of 0.84. The results indicate high potential of CRNS to close the gap between point-scale measurements, hydrological models, and remote sensing of the cryosphere

Using cosmic-ray neutron probes in validating satellite soil moisture products and land surface models

Soil moisture content is one of the most important parameters of hydrological studies. Cosmic-ray neutron sensing is a promising proximal soil moisture sensing technique at intermediate scale and high temporal resolution. In this study, we validate satellite soil moisture products for the period of March 2015 and December 2018 by using several existing Cosmic Ray Neutron Probe (CRNP) stations of the COSMOS database and a CRNP station that was installed in the south part of Turkey in October 2016. Soil moisture values, which were inferred from the CRNP station in Turkey, are also validated using a time domain reflectometer (TDR) installed at the same location and soil water content values obtained from a land surface model (Noah LSM) at various depths (0.1 m, 0.3 m, 0.6 m and 1.0 m). The CRNP has a very good correlation with TDR where both measurements show consistent changes in soil moisture due to storm events. Satellite soil moisture products obtained from the Soil Moisture and Ocean Salinity (SMOS), the METOP-A/B Advanced Scatterometer (ASCAT), Soil Moisture Active Passive (SMAP), Advanced Microwave Scanning Radiometer 2 (AMSR2), Climate Change Initiative (CCI) and a global land surface model Global Land Data Assimilation System (GLDAS) are compared with the soil moisture values obtained from CRNP stations. Coefficient of determination (r 2 ) and unbiased root mean square error (ubRMSE) are used as the statistical measures. Triple Collocation (TC) was also performed by considering soil moisture values obtained from different soil moisture products and the CRNPs. The validation results are mainly influenced by the location of the sensor and the soil moisture retrieval algorithm of satellite products. The SMAP surface product produces the highest correlations and lowest errors especially in semi-arid areas whereas the ASCAT product provides better results in vegetated areas. Both global and local land surface models’ outputs are highly compatible with the CRNP soil moisture values