bluuebunny/crossref_metadata_2025 huggingface dataset:
A combinatorial method for improving hourly precipitation interpolation based on singular value decomposition
Authors: Sheng Sheng , Chen Hua , Xu Chong-Yu , Zhang Wen , Li Zhishuai , Guo Shenglian
Published: March 2020

Reliable estimation of grid precipitation dataset from gauge observations is crucial for hydrological modelling and water balance studies. Datasets developed by common precipitation interpolation methods are mainly derived from the spatial relationship of gauges while neglecting the trend contained in the antecedent precipitation. Precipitation data can be viewed as an intrinsically related matrix, with columns representing temporal relationships and rows representing spatial relationships. A method, called combinatorial point spatiotemporal interpolation based on singular value decomposition (CPST-SVD) that combines traditional interpolators and matrix factorization and considers the spatiotemporal correlation of precipitation, is proposed to improve estimation. Two widely used approaches including the inverse distance weighting (IDW) and universal kriging (UK) were combined to the new method respectively to interpolate precipitation data. Hourly precipitation data from several flood events were selected to verify the performance of the new method in the time period between 2012 and 2018 under different meteorological conditions in Hanjiang Basin, China. The Funk SVD algorithm and the stochastic gradient descent (SGD) algorithm were introduced for matrix factorization and optimization. The performances of all methods in the leave-one-out cross-validation were assessed and compared by five statistical indicators. The results show that CPST-SVD combined with IDW has the highest accuracy, followed by CPST-SVD combined with UK, IDW and UK in descending order. Through combination, estimation errors in precipitation interpolation can be greatly reduced, especially for the situation that the distribution of surrounding gauges is not so uniform or the precipitation in the target gauge is non-zero. In addition, the larger the amount of precipitation event, the greater the improvement of error. Therefore, this study provides a more accurate method for interpolating precipitation based on the assessment of both temporal and spatial information.
Molecular ecological network complexity drives stand resilience of soil bacteria to mining disturbances among typical damaged ecosystems in China
Authors: Ma Jing , Chen Fu
Published: March 2020

Understanding the interactions among different soil microbial species and how they responded to disturbances are essential to ecological restoration and resilience in the damaged mining areas. This information, however, remains unclear and poorly understood. In this study, we investigated the bacterial distribution in disturbed mining areas across three provinces of China, and constructed molecular ecological networks to reveal the interactions among soil bacterial communities. Furthermore, we examined the relationship between the microbial network topology and environmental factors to show if there is a correlation between the resilience of bacterial community and external pressure. Bacterial community composition differed dramatically among the different disturbed mining areas, and bacterial diversity decreased as microbial networks became more complex. Additionally, based on the network topology, we distinguished key microbial populations among the different mining areas, such as Proteobacteria, Acidobacteria, Actinobacteria, and Chloroflexi. Moreover, the network structure was significantly correlated with soil properties (e.g., pH value, electrical conductivity value, and available phosphorus value), which suggested that microbial network interactions might change the soil resilience, then affect soil ecosystem functions. Overall, our findings provided insight into the ways in which microorganisms responded to mining activities and change the resilience by regulating their interactions in different ecosystems.
Iterative P-wave velocity inversion using Markov chain Monte Carlo method
Authors: Jun Hyunggu , Jou Hyeong-Tae , Kim Han-Joon , Lee Sang Hoon
Published: March 2020

Imaging the subsurface structure through seismic data needs various information and one of the most important information is the subsurface P-wave velocity. The P-wave velocity structure mainly influences on the location of the reflectors during the subsurface imaging, thus many algorithms has been developed to invert the accurate P-wave velocity such as conventional velocity analysis, traveltime tomography, migration velocity analysis (MVA) and full waveform inversion (FWI). Among those methods, conventional velocity analysis and MVA can be widely applied to the seismic data but generate the velocity with low resolution. On the other hands, the traveltime tomography and FWI can invert relatively accurate velocity structure, but they essentially need long offset seismic data containing sufficiently low frequency components. Recently, the stochastic method such as Markov chain Monte Carlo (McMC) inversion was applied to invert the accurate P-wave velocity with the seismic data without long offset or low frequency components. This method uses global optimization instead of local optimization and poststack seismic data instead of prestack seismic data. Therefore, it can avoid the problem of the local minima and limitation of the offset. However, the accuracy of the poststack seismic section directly affects the McMC inversion result. In this study, we tried to overcome the dependency of the McMC inversion on the poststack seismic section and iterative workflow was applied to the McMC inversion to invert the accurate P-wave velocity from the simple background velocity and inaccurate poststack seismic section. The numerical test showed that the suggested method could successfully invert the subsurface P-wave velocity.
Catchment scale estimation of current and future water balance in the Chernobyl Exclusion Zone in Ukraine
Authors: Igarashi Yasunori , Zheleznyak Mark , Lisovyi Hlib , Wakiyama Yoshifumi , Onda Yuichi , Nanba Kenji , Konoplev Alexei , Laptev Gennady , Damiyanovich Volodyill , Samoilov Dmitry , Serhii Kirieiev Serhii
Published: March 2020

Changes in the catchment scale water balance have important social implications for usable water now and in the future. Stream discharge is also directly related to radionuclides flux in the river water system. The aim of this study was to clarify the water balance in the Chernobyl Exclusion Zone (CEZ) under current and future climate conditions. A catchment scale hydrological model was used with long-term discharge data to project the future trend of radionuclides wash-off from the contaminated catchment at the CEZ in Ukraine. The Sakhan river catchment in the CEZ (51.41°N, 30.00°E) in Ukraine is one of the Pripyat river systems, and has a total surface area of 186.9 km2. We found that under the current climate, 84% of annual input (sum of rainfall and snowmelt) was consumed as evapotranspiration, and discharge was estimated to be 16%. In future climates, annual precipitation is expected to increase. However, a projected increase in the vapor pressure deficit led the consumption of precipitation as evapotranspiration and no significant increase in discharge. The study found that warmer winter and spring temperatures will decrease the snowfall, and increase the rainfall, but it was not enough to increase evapotranspiration. As a result, the peak of discharge shifted from April to March. The increase of future average discharge during the winter and spring came from a combination of (1) increasing rainfall in the winter and spring, and (2) relatively small levels of evapotranspiration, which enhanced the catchment scale water recharge in soil moisture and gave rise to greater discharge during winter and spring. The reduction of extreme river discharge from the hydrological projections could reduce the probability of high radionuclides concentration in the river water system in the future, owing to the reduction of surface runoff water from the contaminated surface soil and/or top layer of floodplain soils in the CEZ.
How biotic and abiotic factors affect stemflow production? Insights from both local and global scales
Authors: Zhang Yafeng , Wang Xinping , Pan Yanxia , Hu Rui
Published: March 2020

Stemflow production has been reported to be influenced by a suite of biotic and abiotic factors, and those factors would be quite different considering local and global scales. Although the number of published stemflow studies showed a steady increasing trend in recent years, the relative contributions of biotic and abiotic factors to stemflow production were still largely unclear due to the large number of influencing factors and the complex interactions among those factors. Here we present stemflow results conducted from both from local scale and global scale: (1) stemflow of nine xerophytic shrubs of Caragana korshinskii were measured in nearly nine growing seasons from 2010 to 2018 within a desert area of northern China, accompanying with observing on six biotic variables (shrub morphological attributes) and ten abiotic variables (meteorological conditions); (2) a global synthesis of stemflow production results (stemflow percentage was reported) derived from Web of Science for more than 200 peer-reviewed papers published in the last 50 years (1970-2019), and ten most reported biotic factors (vegetation life form, phenology, leaf form, bark form, community density, community age, vegetation height, diameter at breast height, leaf area index, stemflow measuring scale) and four abiotic factors (climate types, mean annual precipitation, elevation, mean annual temperature) were considered. We performed a machine learning method (boosted regression trees) to evaluate the relative contribution of each biotic and abiotic factor to stemflow percentage, and partial dependence plots were presented to visualize the effects of individual explanatory variables on stemflow percentage, respectively.
Variation of bacterial communities in Muztagh ice core from 1869 to 2000
Authors: Liu Yongqin , Yao Tandong , Xu Baiqing
Published: March 2020

Many studies focusing on the physical and chemical indicators of the ice core reflected the climate changes. However, only few biological indicators indicated the past climate changes which are mainly focused in biomass rather than diversity. How the biodiversity response to the climate change during the past hundred years is still unknow. Glaciers in Mt. Muztagh Ata region are inﬂuenced by the year-round westerly circulation. We firstly disclosed annual variations of bacterial community compositions in ice core over the past 130 years from Muztagh Glacier, the western Tibetan Plateau. Temporal variation in bacterial abundance was strongly controlled by DOC, TN, δ18O, Ca2+, SO42−, NH4+ and NO3−. Proteobacteria, Actinobacteria and Firmicutes were the three most abundant bacterial phyla, accounting for 49.3%, 21.3% and 11.0% of the total community, respectively. The abundances of Firmicutes and Bacteroidetes pronouncedly increased over time throughout the entire ice core. UPGMA cluster analysis of the bacterial community composition separated the all ice core samples into two main clusters along the temporal variation. The first cluster consisted of samples from 1951 to 2000 and the second cluster contained main samples during the period of 1869-1950. The stage 1 and stage 2 bacterial community dissimilarities increased linearly with time on the basis of the Bray-Curtis distance, indicating a similar temporal–decay relationship between the stage 1 and stage 2 bacterial communities. Of all the environmental variables examined, only DOC and NH4+ exhibited very strong negative correlations with bacterial Chao1-richness. 18O was another important variable in shaping the ice core bacterial community composition and contributed 1.6% of the total variation. Moreover, DistLM analysis indicated that the environmental variables explained more variation in the stage 1 community (20.1%) than that of the stage 2 community (19.9%).
Applying Conditional Nonlinear Optimal Perturbation (CNOP) in the ensemble ENSO forecast system
Authors: Zhou Qian , Zhang Yunfei , Hu Junya , Duan Wansuo
Published: March 2020

      Considering the effects of initial uncertainty on the ENSO forecast, ensemble forecasts method is applied in the latest version of ENSO forecast system in National Marine Environmental Forecasting Center (NMEFC, China). The currently operational ENSO forecasts system of NMEFC is established based on the CESM model, with initialization and data assimilation.

      First, leading five Singular Vectors (SV) are obtained using the climatological SST empirical singular vector method, and a SV based ensemble forecasts system is . However, the SVs can only present the initial errors that have the fasted error growth rates in a linear assumption, while ENSO and its forecasting system both are nonlinear. So, Conditional Nonlinear Optimal Perturbations (CNOP), which is has the largest error growth at the prediction time in a nonlinear scenario, is used to replace the leading SV, while other 4 SVs are kept to construct a CNOP-SV based ensemble forecast system. The hindcasts of ENSO from 1982 to 2017 shows that, the ENSO prediction skills of both SV based and CNOP-SV based ENSO ensemble forecasts are improved when compared with the old forecasting system, moreover, the CNOP-SV based ensemble forecast system has a much larger spread, showing higher prediction skills.
Weighted total least squares problems with inequality constraints solved by standard least squares theory
Authors: Jian Xie , Sichun Long
Published: March 2020

The errors-in-variables (EIV) model is applied to surveying and mapping fields such as empirical coordinate transformation, line/plane fitting and rigorous modelling of point clouds and so on as it takes the errors both in coefficient matrix and observation vector into account. In many cases, not all of the elements in coefficient matrix are random or some of the elements are functionally dependent. The partial EIV (PEIV) model is more suitable in dealing with such structured coefficient matrix. Furthermore, when some reliable prior information expressed by inequality constraints is considered, the adjustment result of inequality constrained PEIV (ICPEIV) model is expected to be improved. There are two kinds of algorithms to solve the ICPEIV model under the weighted total least squares (WTLS) criterion currently. On the one hand, one can linearize the PEIV model and transform it into a sequence of quadratic programming (QP) sub-problems. On the other hand, one can directly solve the nonlinear target function by common used programming algorithms.All the QP algorithms and nonlinear programming methods are complicated and not familiar to the geodesists, so the ICPEIV model is not widely used in geodesy.   

In this contribution, an algorithm based on standard least squares is proposed. First, the estimation of model parameters and random variables in coefficient matrix are separated according to the Karush-Kuhn-Tucker (KKT) conditions of the minimization problem. The model parameters are obtained by solving the QP sub-problems while the variables are determined by the functional relationship between them. Then the QP problem is transformed to a system of linear equations with nonnegative Lagrange multipliers which is solved by an improved Jacobi iterative algorithm. It is similar to the equality-constrained least squares problem. The algorithm is simple because the linearization process is not required and it has the same form of classical least squares adjustment. Finally, two empirical examples are presented. The linear approximation algorithm, the sequential quadratic programming algorithm and the standard least squares algorithm are used. The examples show that the new method is efficient in computation and easy to implement, so it is a beneficial extension of classical least squares theory.
Optimal Error Analysis of MJO Prediction Associated with Uncertainties in Sea Surface Temperature over Indian Ocean
Authors: Li Xiaojing , Tang Youmin
Published: March 2020

In this study, the predictability of the Madden-Julian Oscillation (MJO) is investigated using the coupled Community Earth System Model (CESM) and the climatically relevant singular vector (CSV) method. The CSV method is an ensemble-based strategy to calculate the optimal growth of the initial error on the climate scale. We focus on the CSV analysis of MJO initialized at phase II, facilitating the investigation of the effect of the initial errors of the sea surface temperature (SST) in the Indian Ocean on it. Six different MJO events are chosen as the study cases to ensure the robustness of the results.

The results indicate that for all the study cases, the optimal perturbation structure of the SST, denoted by the leading mode of the singular vectors (SVs), is a meridional dipole-like pattern between the Bay of Bengal and the southern central Indian Ocean. The MJO signal tends to be more converged and significant in the Eastern Hemisphere while the model is perturbed by leading SV. The moist static energy analysis results indicate that the eastward propagation is much more evident in the terms of vertical advection and radiation flux than others. Therefore, the SV perturbation can strengthen and converge the MJO signal mostly by increasing the vertical advection of the moist static energy.

Further, the sensitivity studies indicate that the structure of the leading SV is not sensitive to the initial states, which suggests that we might not need to calculate SVs for each initial time in constructing the ensemble prediction, significantly saving computational time in the operational forecast systems.
Comparison between Laser Ranging Interferometer and K/Ka band Ranging instruments.
Authors: Allgeyer Sebastien , McQueen Herbert , Tregoning Paul
Published: March 2020

The GRACE Follow-On mission is the first twin-satellite mission equipped with a laser ranging interferometer (LRI) to measure the inter-satellite distance between the pair of satellites. The LRI operates independently of the K/Ka-band interferometer (KBR) and uses wavelengths 104 times shorter than the K-band system.  Released at the end of July 2019, the LRI range data is therefore expected to be of higher accuracy than the KBR and offers the possibility of a better spatial resolution. We compare the LRI and KBR observations of the GRACE-FO mission, from launch to December 2019, to assess the quality of the new LRI system. Spectral analysis of the level1B data shows that the noise level of the LRI is 3 orders of magnitude smaller than the KBR and that the gravity signal can be detected in the spectral band up to 30mHz in the LRI data compared to 20mHz in the KBR data.  We compare gravity fields estimated using LRI and KBR and show which parts of the spherical harmonic spectrum are affected by the improved accuracy of the LRI observations.
Impacts of soil hydrologial modeling on long-term terrestrial carbon cycle inferred from CCDAS (Carbon Cycle Data Assimilation System)
Authors: Wu Mousong , Scholze Marko , Jiang Fei , Wang Hengmao , Zhang Wenxin , Lu Zhengyao , He Wei , Wang Songhan , Kaminski Thomas , Vossbeck Michael , Wang Jun , Ju Weimin
Published: March 2020

The terrestrial carbon cycle is an important part of the global carbon budget due to its large gross exchange fluxes with the atmosphere and their sensitivity to climate change. Terrestrial biosphere models show large uncertainties in estimating carbon fluxes, which impacts global carbon budget assessments. The land surface carbon cycle is tightly controlled by soil moisture through plant physiological processes. In this context, accurate soil moisture data will improve the modeling of carbon fluxes in a model-data fusion framework. We employ the Carbon Cycle Data Assimilation System (CCDAS) to assimilate 36 years (1980-2015) of surface soil moisture data as provided by the ESA CCI in combination with atmospheric CO2 concentration observations at global scale. We will present the methods used for assimilating long-term remotely sensed soil moisture into the terrestrial biosphere model, and demonstrate the importance of soil moisture in modeling ecosystem carbon cycle processes. We will also investigate the impacts of soil moisture on the terrestrial carbon cycle during climate extremes at various scales.
Climatic response of tree-ring densitometric records in a semiarid site of China
Authors: Song Huiming , Liu Yu
Published: March 2020

The tree-ring densitometric studies conducted in the semiarid regions are rare, among them, minimum earlywood density (MND) records the strongest climate signals than other density parameters. In contrast, maximum density of latewood (MXD) in cold and humid regions usually shows the most significant association with summer temperatures. Density parameters of Purplecone Spruce (Picea purpurea Mast.) in Mt. Shouyang, northwestern China, a typical semiarid region were obtained to test the density-climate relationships. It is showed that MXD has strong positive correlations with temperatures and a negative correlation with precipitation in the late growing season from July to September. MND is significantly positively correlated with temperature and positively correlated with precipitation during the early growing season. During early growing season, spring droughts always occur due to low precipitation. A narrow ring is built under moisture stress, since tree growth is inhibited by decreasing cell division and cell enlargement. With the intensification of monsoon, more precipitation is available, which can basically meet the needs of tree growth. During strong monsoon season with humid conditions, trees are less affected by moisture stress. In this case, high temperature could increase cell wall thickness in the latewood which strongly affects the tree-ring maximum density. It could explain why there is a significant positive correlation between MXD and summer-fall temperature.
The Pacific Decadal Oscillation less predictable under greenhouse warming
Authors: Li Shujun
Published: March 2020

The Pacific Decadal Oscillation (PDO) is the most prominent form of decadal variability over the North Pacific, characterized by its horseshoe-like sea surface temperature (SST) anomaly pattern. The PDO exerts a substantial influence on marine ecosystems, fisheries, and agriculture. Through modulating global mean temperature, the phase shift of the PDO at the end of the 20th century is suggested to be an influential factor in the recent surface warming hiatus. Therefore, determining the predictability of the PDO in a warming climate is of great importance. By analyzing future climate under different emission scenarios simulated by the Coupled Model Intercomparison Project phase 5 (CMIP5), we show that the prediction lead time and the associated amplitude of the PDO decreases sharply under greenhouse warming conditions. This decrease is largely attributable to a warming-induced intensification of oceanic stratification, which accelerates propagation of Rossby waves, shortening the PDO lifespan and suppressing its amplitude by limiting its growth time. Our results suggest that greenhouse warming will make prediction of the PDO more challenging, with far-reaching ramifications.  
Chronology of Tectonic Movement of Cratonic Basin: Insight from New Evidences from Ordos Basin, North China
Authors: He Dengfa
Published: March 2020

Craton is the stable unit of the lithosphere. The cratonic basin is thus the sedimentary basin developed upon craton. It has long been recognized as a kind of basin characterized by minor tectonic deformation and stable architecture. With the increasing evidences in the recent years, it is noticed that it has much more mobility, and is controlled not only by the lithospheric plate movements but also by the deep mantle activation. To explore the mobile behaviour of cratonic basin is an important window to address the intra-continental deformation mechanism. Taking the Ordos basin as an example, based on the new deep boreholes, the high-resolution seismic reflection profiles, cores, and the outcrops around the basin, the paper establishes the chronology of tectonic movement around the Ordos basin utilizing the integrated method of the isotopic dating, the bio-stratigraphy, and the sequence stratigraphy. It shows that, the basin developed the ten regional unconformities, underwent multi-period volcanic activities during the Middle Proterozoic, the late Early Paleozoic, the Late Triassic, and the Early Cretaceous. It was subjected to multi-stage compression, such as the Late Ordovician to Devonian, the Late Triassic, the Late Jurassic to Early Cretaceous, and the Neogene to Quaternary. Upon the crystalline basement of the Archaean and the Lower Proterozoic, the basin underwent five distinct extension-compression cycles, such as the extension in middle Proterozoic and compression in late Proterozoic, the extension in Cambrian to early Ordovician and compression in late Ordovician to Devonian, the extension in Carboniferous to middle Triassic and compression in late Triassic, the extension in early to middle Triassic and compression in late Jurassic to Cretaceous, and the extension in Paleogene and compression in Neogene to Quaternary, with a charter of a much longer period of the earlier cycle and a shorter period of the later cycle, and a longer period of extension and a shorter period of contraction in each cycle. The extension-compression cycle controlled the formation and evolution of the Ordos oil and gas super basin.
Application of artificial neural network model for regional frequency analysis at Han River basin, South Korea
Authors: Lee Joohyung , Kim Hanbeen , Kim Taereem , Heo Jun-Haeng
Published: March 2020

Regional frequency analysis (RFA) is used to improve the accuracy of quantiles at sites where the observed data is insufficient. Due to the development of technologies, complex computation of huge data set is possible with a prevalent personal computer. Therefore, machine learning methods have been widely applied in many disciplines, including hydrology. There are also many previous studies that apply the machine learning methods to RFA. The main purpose of this study is to apply the artificial neural network (ANN) model for RFA. For this purpose, performance of RFA based on the ANN model is measured. For the homogeneous region in Han River basin, rainfall gauging sites are divided into training and testing groups. The training group consists of sites where the record length of data is more than 30 years. The testing group contains sites where the record length of data is spanned from 10 to 30 years. Various hydro-meteorological variables are used as an input layer and parameters of generalized extreme value (GEV) distribution for annual maximum rainfall data are used as an output layer of the ANN model. Then, the root mean square error (RMSE) values between the predicted and observed quantiles are calculated. To evaluate the model performance, the RMSEs of quantile estimated by the ANN model are compared to those of the index flood model.
Sedimentary Dispersal and Accumulation in the oceanic basin, South China Sea, revealed by Sediment Budget
Authors: Wang Fei , Ding Weiwei
Published: March 2020

South China Sea (SCS) is not only the crucial pathway for transporting terrigenous materials from Eurasia to the Western Pacific Ocean since the early Oligocene, but also the dominant accumulation and preservation place as a result of limited material exchange between the semi-closed oceanic basin and the open ocean since the middle Miocene. Diverse factors, including global climate changes, eustatic sea level change, regional and local tectonic events, et al., controlled the sedimentary dispersal and accumulational patterns in the oceanic basin of the SCS, which can be revealed by the calculation of sediment budget at different geological times, as the sediment budget can illustrate directly the sediment influx, storage, loss in a basin system (Hapke et.al, 2010).

By interpreting the multichannel seismic profiles covering the whole oceanic basin with constraints from International Ocean Discovery Program (IODP) Expeditions 349, 367 and 368, we reconstructed the sequence stratigraphy framework of the study area, and then calculated the sedimentary budget at different geological time. This work aims to quantitate the sedimentary dispersal and accumulation in the oceanic basin for the first time.

Until now we have completed the sequence boundary identification and dating, as well as the division of sedimentary units of all multichannel seismic profiles. The grid data of different sequence boundaries have been obtained and posted on the bathymetric map, and by the time-depth conversion with appropriate function in different region referred from the drilling results of IODP expeditions, we have figured out the thickness of each sedimentary unit. In the following we will do the decompaction correction before calculating the sedimentary budget of the whole oceanic basin at different times. This work could increase our understandings on the major controlling factors and possible material sources of the deposition process.

 
Methane and carbon dioxide dynamics affected by water-level fluctuations in a shallow lake: Implications for wetland restoration
Authors: Yuan Xiaomin , Liu Qiang
Published: March 2020

Shallow lake was characterized by distinct hydrology, biochemistry and ecology that influence the carbon balance. This study explored methane and carbon emission responses to water level fluctuation in shallow lake, and also addressed its legacy for wetland restoration. This study used the process-based biogeochemical model, denitrification-decomposition (DNDC) model to simulate the alteration of methane and carbon emission with water level fluctuation in the Baiyangdian Lake (BYD Lake). The results showed: (i) compared with the observed carbon flux, the DNDC model can presented a suitable results in capturing the dynamics of methane and carbon dioxide, and the daily rate of carbon dioxide and methane emission showed sensitive to water fluctuation when it ranged from -10 cm to 10 cm; (ii) for the carbon dioxide, the annual flux showed a decline trend when the duration prolonged from 10 days to 40 days, and then an increasing trend while the duration prolonged to 90 days furtherly, with a lowest flux when the duration is 40 days, while for the methane, annual emission increased with inundation lasting time and the flux changing from -2.27 kg C/ha/y to 1.57 kg C/ha/y; and (iii) The flux of carbon dioxide and methane increased when water level fluctuation frequency increased, for a certain water level fluctuation frequency, carbon dioxide flux is lowest in January and February, and methane flux is negative from December to March of the following year. All of these results indicated that water level fluctuation (e.g., magnitude, duration and frequency) affected the carbon dioxide and methane flux, which will help to reduce the emission of carbon dioxide and methane by regulating ecological water transfer.

Keywords: shallow lake, carbon emission; DNDC; water level fluctuation

Acknowledgments

This study was supported by the National Key R&D Program of China (No. 2018ZX07110001, No. 2017YFC0404505) and the National Natural Science Foundation of China (No. 51579008).
Assessment of glacier lakes development in Central Caucasus
Authors: Lavrentiev Ivan , Petrakov Dmitry , Kutuzov Stanislav , Smirnov Andrey
Published: March 2020

Glacier mass loss and consequent termini retreat lead to formation and growth of glacier lakes. In the Mt. Elbrus region, outbursts of lakes formed in recent decades have led to human casualties and significant damage. Building codes of Russian Federation on engineering surveys do not regulate the possibility of glacier lake formation in front of retreating glaciers, which can lead to errors in the future engineering design. Using ground based and airborne GPR data, as well as global ice thickness models, we have identified areas of potential lake formation on glacier bed for a number of glaciers in the Mt. Elbrus region. The method was tested by retrospective modeling for Bolshoy Azau and Djikiugankez glaciers bed topography on the base of 1957 topographic map. In the areas where glaciers disappeared by 2017, out of 13 simulated closed bed depressions 7 existing lakes were predicted by the hydraulic potential. 6 closed depressions on Djikiugankez glacier bed as of 1957 are currently absent, which might be related to the model uncertainties and the original DEMs errors, as well as to possible filling of lakes by sediments. Retrospective modeling of the Bashkara glacier bed topography based on SRTM DEM (2000) showed significant growth potential of the lake Lapa. Retrospective modeling of the Kaayarty glacier bed topography has not provided a clear answer about the possibility if subglacial lake outburst flood was a trigger for catastrophic debris flow formation during the summer of 2000.

In case of total disappearance of Bolshoy Azau, Djikiugankez and Bashkara glaciers at least 11 new lakes with total area of about 1.7 km2 and an average depth of 8 m will form. While the deepest lake will appear in ablation zone of Bolshoy Azau glacier (at elevation 3100-3400 m a.s.l.) the largest in area (1 km2) glacial lake will be formed at the Djikiugankez snout with maximum depth of 40 m and mean depth of 7.2 m. The simulation also showed that in the present conditions, glacier bed lakes of different number and size may also exist under studied glaciers. Our estimates may contain uncertainties due to low resolution of airborne GPR data and the lack of GPR data for Kaayarty glacier, DEM and ice thickness model errors. Detailed ground-based radar survey planned for the summer 2020 will enable the assessment of the size and volume of the potential lakes under Bolshoy Azau glacier.

This work was funded by RFBR grant No. 18-05-00520.
A study on turbulence flow and pressure due to hydraulic jump
Authors: Choi Seo Hye , Kim Hyung Suk , Park Moonhyung
Published: March 2020

The hydraulic jump occurs depending on conditions of upstream and downstream and makes large vortexes in itself of which flow is complex and fluctuates. Recently, the abnormal climate and gain of the impervious area increase the variation in river discharge. It can result in exerting the pressure that is over the acceptable load at the bottom in the downstream of a weir and increasing the fluctuation of the pressure due to the hydraulic jump. Those can provoke damages because of negative pressure, erosion of materials, local scour, and excess of the design load. Thus, this study aims at making use of the design in river-bed maintenance structures such as riprap and an apron considering by the pressure fluctuations. We simulated the hydraulic jump phenomenon through a hydraulic model experiment and examined the relationship between hydraulic factors and the pressure in the range of the hydraulic jump. Specifically, the hydraulic jump is generated by installing a weir upstream in the channel and measured the velocity of the flow by using particle image velocimetry (PIV) and bubble image velocimetry (BIV) to identify the characteristics of turbulence in the section of the hydraulic jump. Also, this study measured the pressure at the bottom along to the flow. As a result, the main factors of the pressure fluctuations are derived by statistical analysis such as determining the correlation between the pressure and the factors. In the subsequent study, it will be suggested to expect the pressure fluctuations at the bottom by using surrounding hydraulic factors in hydraulic jump through an elaborate analysis.

 

Acknowledgement

"This work is supported by the Korea Agency for Infrastructure Technology Advancement (KAIA) grant funded by the Ministry of Land, Infrastructure and Transport (Grant 20AWMP-C140010-03)."
Space-Time Landslide Predictive Modelling
Authors: Lombardo Luigi , Opitz Thomas , Ardizzone Francesca , Huser Raphaël , Guzzetti Fausto
Published: March 2020

Landslides are nearly ubiquitous phenomena and pose severe threats to people, properties, and the environment. Investigators have for long attempted to estimate landslide hazard to determine where, when, and how destructive landslides are expected to be in an area. This information is useful to design landslide mitigation strategies, and to reduce landslide risk and societal and economic losses. In the geomorphology literature, most attempts at predicting the occurrence of populations of landslides rely on the observation that landslides are the result of multiple interacting, conditioning and triggering factors. Here, we propose a novel Bayesian modelling framework for the prediction of space-time landslide occurrences of the slide type caused by weather triggers. We consider log-Gaussian cox processes, assuming that individual landslides stem from a point process described by an unknown intensity function. We tested our prediction framework in the Collazzone area, Umbria, Central Italy, for which a detailed multi-temporal landslide inventory spanning 1941-2014 is available together with lithological and bedding data. We tested five models of increasing complexity. Our most complex model includes fixed effects and latent spatio-temporal effects, thus largely fulfilling the common definition of landslide hazard in the literature. We quantified the spatio-temporal predictive skill of our model and found that it performed better than simpler alternatives. We then developed a novel classification strategy and prepared an intensity-susceptibility landslide map, providing more information than traditional susceptibility zonations for land planning and management. We expect our novel approach to lead to better projections of future landslides, and to improve our collective understanding of the evolution of landscapes dominated by mass-wasting processes under geophysical and weather triggers.
Two aspects of decadal ENSO variability modulating the long-term global carbon cycle
Authors: Park So-won , Kim Jin-Soo , Kug Jong-Seong , Stuecker Malte F. , Kim In-Won , Williams Mathew
Published: March 2020

El Niño-Southern Oscillation (ENSO) is the primary cause of interannual variations in the global carbon cycle because ENSO-driven extensive teleconnection over continents affects the terrestrial ecosystem process. ENSO is an interannual phenomenon, but it also has decadal variability. The ENSO-like SST pattern and ENSO characteristic, e.g. ENSO amplitude, change on decadal timescales. However, the influence of decadal ENSO variability on global carbon cycle has not yet been fully examined. Here we examined the impacts of decadal ENSO variability on decadal variation of terrestrial carbon flux by analyzing fully coupled pre-industrial control simulation of the Community Earth System Model 1 large ensemble (CESM1-LE). Considerable decadal variability of atmosphere-to-land carbon flux exists and this terrestiral carbon flux is mainly modulated by the tropical biosphere on decadal timescales as well as on interannual timescales. We found that there are two different pathways, which can explain about 36% of the decadal variations in terrestrial carbon flux. First, long-term climate change over tropics induced by decadal tropical Pacific SST variability regulates the terrestrial productivity and hence atmospheric CO2 on decadal time scale. Second, decadal changes in asymmetric terrestrial ecosystem’s response to ENSO events, resulted from decadal modulation of ENSO amplitude, generate decadal variability of terrestrial carbon flux.

Key words: Global Carbon Cycle, El Niño-Southern Oscillation (ENSO), Pacific Decadal Variability, ENSO asymmetry, Decadal NBP variability
Can reclaimed land be converted to arable land? –Positive: Evidences of soil microbial activity from a laboratory experiment
Authors: Chen Ruirui , Zhang Jianwei , Feng Youzhi
Published: March 2020

Agriculture is a drive for land reclamation. Reclaiming coastal saline soils is increasingly undertaken as water and heat resources are normally plentiful in coastal land. However, growth of both crops and soil microorganisms is limited due to high cation content and osmotic stress, making saline soils unproductive when converted to arable land. For crops, great efforts have to be made to screen salt-tolerant species suitable for land reclamation. For soil microorganisms in saline soils, will the same separation and domestication of salt-tolerant species be necessary to improve microbial activity as done with crops?

To improve such understandings, we studied coastal saline soils covering non-, mild-, and severe-salinity. Their bacterial diversities were characterized by high throughput sequencing, and microbial metabolic activities analyzed with substrate-induced heat release curves. Abundant and diverse bacterial communities were detected in the severe-salinity soils. While we did not observe soil salinity significantly affected the microbial richness, it did shift soil bacterial community composition. However, the severe-salinity soil was not dominant with salt-tolerant microbial species. With thermodynamic analysis, we discovered glucose amendment efficiently promoted microbial metabolic activity regardless of their community composition. Severe salinity did not inhibit potential metabolic activity of soil microbial community. A further 2-month incubation experiment supported that microbial metabolic kinetics of the severe-salinity soil amended with maize straw recovered and moved toward to the non-salinity soil.

Therefore, our study supported that salt-tolerant species are not indispensable in land reclamation. An addition of labile organic amendments can help to rapidly multiply microbial growth and recover soil microbial functions.
Oxygen and Carbon Isotopes of Cold-water Corals——Reconstructing Paleotemperature changes and Calcification Mechanism
Authors: Kong Le
Published: March 2020

         Cold-water corals represent an intriguing paleoceanographic archive with a great potential to reconstruct high-resolution paleoenvironmental changes. Compared to those of shallow-water corals, proxies derived from cold-water corals have been complicated by biologically mediated vital effects. The oxygen and carbon stable isotope compositions of cold-water coral skeletons are more depleted than the expected carbonate-seawater equilibrium values by ~4–6‰ and ~10‰, respectively. Therefore, it is necessary to correct for the vital effect before using δ18O as a temperature proxy. δ18O and δ13C of cold-water corals exhibit strong linear correlations after adjusting for ambient seawater δ18O and δ13C values. The δ18O intercepts of this linear regression were found to be correlated with water temperatures. This so-called ‘intercept method’ can therefore be used to reconstruct temperatures variations of intermediate and deep oceans. Moreover, sampling along the growing bands of cold-water corals can provide samples to generate temperature sequences. After that, three geochemical models have been proposed to explain the δ18O and δ13C depletion of cold-water corals. However, none of them can explain the behavior of all geochemical parameters. In future, more analyses and experiments at micro-scales are required to adjust these geochemical models or propose new ones.
Evaluation of Measurement Errors of Tipping Bucket Rain Gauges
Authors: Jiang Guangxu , Liu Jiufu , Li Xuegang , Liu Hongwei , Liao Aimin
Published: March 2020

The observation accuracy of rainfall processes affects every aspects of the meteorological and hydrological affairs, which is widely monitored by various types of tipping bucket rain gauges（TBRs）because of the simple structure and reliable performance. The study of the measurement errors of TBRs is quite valuable and necessary for improving the rainfall data quality and evaluating the uncertainty of the research based on the dataset.

In this study, an artificial rainfall and monitor experiment system is designed with peristaltic pump, balances, recorder and controller for the accurate rainfall and the TBRs instrumental values record, based on which the error distribution and instrument stability were analyzed. Eight types of TBRs are chose for the error evaluation experiment, including five single-layer TBRs, three double-layer TBRs. For each TBRs, we observe its performance under 6 rain intensity (0.1-4mm/min) in turn. With regard to each rain intensity, when the simulated total rainfall reaches 10 mm, the experiment stops and records the data, then repeats the same experiment 6 times.

The result shows that the single-layer TBRs have a good linear relationship between the rainfall and the measurement error, and the double-layer TBRs has a significant regulating effect on the continuous heavy rain intensity, which can make the rain flow steadily down to the lower tipping bucket (metering tipping bucket) with a stable rain intensity to avoid the rain intensity variation influence on the measurement error. However, due to its high resolution of 0.1mm, it is greatly affected by the residual water volume of the tipper bucket.

According to the results, the single-layer TBRs can correct the actual rainfall measurement process according to the error ~ rainfall intensity curve. The double-layer TBRs can play an important role in the rainy day record, but the randomness of the residual in the tipping bucket needs to be further estimated. Because the proportion of the light rainfall intensity in most of the rainfall events are quite high according to the statistics, it is necessary to have lower measurement error under the light rainfall in the TBRs chosen and calibration process. It's a good idea to choose a combination of rain gauges(0.1mm&0.5mm) to improve the accuracy of rainfall and rainy day.
Chemical variations in hydrothermal systems recorded by epidote in altered oceanic crust of South China Sea
Authors: Tian Liyan , Hu Si-Yu , Wang Xuan-Ce
Published: March 2020

The circulation of seawater within the oceanic crust promotes the extensive chemical variations of the lithosphere prior to its entering subduction zones as well as the development of the biosphere. A good understanding of the chemical variations during hydrothermal circulation is essential to further decipher the biological activities in such extreme environments. Epidote is a common byproduct, but a good indicator for hydrothermal activities during the hydrothermal alteration of oceanic crust.

This study presents the petrographic and geochemical features of epidote from depth of 850-910 m (below the surface) in the northern South China Sea margin to provide insights into the possible chemical variations in hydrothermal systems in subsurface. Eight samples with obvious epidote veins were chosen from the altered basalts in Hole 1502B of IODP Expedition 368. They cover a range with different depth and occurrences, including epidote veins, composite epidote-calcite veins, and composite epidote-silica veins. Sulfide mineralization is widespread and dominated with pyrite, chalcopyrite and sphalerite. Scanning Electron Microscopy images show that the epidote-calcite vein samples display obvious zonation structure in epidote, and the others not. The major element concentrations of Fe also show variations with epidote zonation. We further carried out in situ trace element concentration measurement on epidote minerals by Laser Ablation-Induced Coupled Plasma-Mass Spectrometry. In Chondrite-normalized diagrams, all epidote mineral samples show flat patterns with significant positive Eu anomalies, which may relate to highly oxidized conditions maximising Eu3+ incorporation. We therefore propose that the zonation of epidote may reflect the pulse of hydrothermal activities, one of which is likely to be associated with the precipitation of chalcopyrite and sphalerite.