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Statistic inversion of multi-zone transition probability models for aquifer characterization in alluvial fans

Understanding the heterogeneity arising from the complex architecture of sedimentary sequences in alluvial fans is challenging. This paper develops a statistical inverse framework in a multi-zone transition probability approach for characterizing the heterogeneity in alluvial fans. An analytical solution of the transition probability matrix is used to define the statistical relationships among different hydrofacies and their mean lengths, integral scales, and volumetric proportions. A statistical inversion is conducted to identify the multi-zone transition probability models and estimate the optimal statistical parameters using the modified Gauss-Newton-Levenberg-Marquardt method. The Jacobian matrix is computed by the sensitivity equation method, which results in an accurate inverse solution with quantification of parameter uncertainty. We use the Chaobai River alluvial fan in the Beijing Plain, China, as an example for elucidating the methodology of alluvial fan characterization. The alluvial fan is divided into three sediment zones. In each zone, the explicit mathematical formulations of the transition probability models are constructed with optimized different integral scales and volumetric proportions. The hydrofacies distributions in the three zones are simulated sequentially by the multi-zone transition probability-based indicator simulations. The result of this study provides the heterogeneous structure of the alluvial fan for further study of flow and transport simulations.Comment: 29 pages, 7 figures, and 3 table

Modeling 3-D permeability distribution in alluvial fans using facies architecture and geophysical acquisitions

Alluvial fans are highly heterogeneous in hydraulic properties due to complex depositional processes, which make it difficult to characterize the spatial distribution of the hydraulic conductivity (K). An original methodology is developed to identify the spatial statistical parameters (mean, variance, correlation range) of the hydraulic conductivity in a three-dimensional (3-D) setting by using geological and geophysical data. More specifically, a large number of inexpensive vertical electric soundings are integrated with a facies model developed from borehole lithologic data to simulate the log10(K) continuous distributions in multiplezone heterogeneous alluvial megafans. The Chaobai River alluvial fan in the Beijing Plain, China, is used as an example to test the proposed approach. Due to the non-stationary property of the K distribution in the alluvial fan, a multiplezone parameterization approach is applied to analyze the conductivity statistical properties of different hydrofacies in the various zones. The composite variance in each zone is computed to describe the evolution of the conductivity along the flow direction. Consistently with the scales of the sedimentary transport energy, the results show that conductivity variances of fine sand, medium-coarse sand, and gravel decrease from the upper (zone 1) to the lower (zone 3) portion along the flow direction. In zone 1, sediments were moved by higher-energy flooding, which induces poor sorting and larger conductivity variances. The composite variance confirms this feature with statistically different facies from zone 1 to zone 3. The results of this study provide insights to improve our understanding on conductivity heterogeneity and a method for characterizing the spatial distribution of K in alluvial fans

Spatiotemporal Evolution of Land Subsidence in the Beijing Plain 2003–2015 Using Persistent Scatterer Interferometry (PSI) with Multi-Source SAR Data

Land subsidence is one of the most important geological hazards in Beijing, China, and its scope and magnitude have been growing rapidly over the past few decades, mainly due to long-term groundwater withdrawal. Interferometric Synthetic Aperture Radar (InSAR) has been used to monitor the deformation in Beijing, but there is a lack of analysis of the long-term spatiotemporal evolution of land subsidence. This study focused on detecting and characterizing spatiotemporal changes in subsidence in the Beijing Plain by using Persistent Scatterer Interferometry (PSI) and geographic spatial analysis. Land subsidence during 2003–2015 was monitored by using ENVISAT ASAR (2003–2010), RADARSAT-2 (2011–2015) and TerraSAR-X (2010–2015) images, with results that are consistent with independent leveling measurements. The radar-based deformation velocity ranged from −136.9 to +15.2 mm/year during 2003–2010, and −149.4 to +8.9 mm/year during 2011–2015 relative to the reference point. The main subsidence areas include Chaoyang, Tongzhou, Shunyi and Changping districts, where seven subsidence bowls were observed between 2003 and 2015. Equal Fan Analysis Method (EFAM) shows that the maximum extensive direction was eastward, with a growing speed of 11.30 km2/year. Areas of differential subsidence were mostly located at the boundaries of the seven subsidence bowls, as indicated by the subsidence rate slope. Notably, the area of greatest subsidence was generally consistent with the patterns of groundwater decline in the Beijing Plain

Imaging Land Subsidence Induced by Groundwater Extraction in Beijing (China) Using Satellite Radar Interferometry

Beijing is one of the most water-stressed cities in the world. Due to over-exploitation of groundwater, the Beijing region has been suffering from land subsidence since 1935. In this study, the Small Baseline InSAR technique has been employed to process Envisat ASAR images acquired between 2003 and 2010 and TerraSAR-X stripmap images collected from 2010 to 2011 to investigate land subsidence in the Beijing region. The maximum subsidence is seen in the eastern part of Beijing with a rate greater than 100 mm/year. Comparisons between InSAR and GPS derived subsidence rates show an RMS difference of 2.94 mm/year with a mean of 2.41 ± 1.84 mm/year. In addition, a high correlation was observed between InSAR subsidence rate maps derived from two different datasets (i.e., Envisat and TerraSAR-X). These demonstrate once again that InSAR is a powerful tool for monitoring land subsidence. InSAR derived subsidence rate maps have allowed for a comprehensive spatio-temporal analysis to identify the main triggering factors of land subsidence. Some interesting relationships in terms of land subsidence were found with groundwater level, active faults, accumulated soft soil thickness and different aquifer types. Furthermore, a relationship with the distances to pumping wells was also recognized in this work.This work was supported by the National Natural Science Foundation of China under Grant 41201419 and a China Scholarship Council (CSC) scholarship to Mi Chen. Roberto Tomás was supported by the Ministry of Education, Culture and Sport through the project PRX14/00100. Part of this work is also supported by the Spanish Ministry of Economy and Competitiveness and EU FEDER funds under projects TIN2014-55413-C2-2-P, by the UK Natural Environmental Research Council (NERC) through the LICS and IRNHiC projects (ref. NE/K010794/1 and NE/N012151/1, respectively), the ESA-MOST DRAGON-3 projects (ref. 10607 and 10665) and the Open Fund from the Key Laboratory of Earth Fissures Geological Disaster, Ministry of Land and Resources (Geological Survey of Jiangsu Province)

Genetic Diagnostic Evaluation of Trio-Based Whole Exome Sequencing Among Children With Diagnosed or Suspected Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a group of clinically and genetically heterogeneous neurodevelopmental disorders. Recent tremendous advances in the whole exome sequencing (WES) enable rapid identification of variants associated with ASD including single nucleotide variations (SNVs) and indels. To further explore genetic etiology of ASD in Chinese children with negative findings of copy number variants (CNVs), we applied WES in 80 simplex families with a single affected offspring with ASD or suspected ASD, and validated variations predicted to be damaging by Sanger sequencing. The results showed that an overall diagnostic yield of 8.8% (9.2% in the group of ASD and 6.7% in the group of suspected ASD) was observed in our cohort. Among patients with diagnosed ASD, developmental delay or intellectual disability (DD/ID) was the most common comorbidity with a diagnostic yield of 13.3%, followed by seizures (50.0%) and craniofacial anomalies (40.0%). All of identified de novo SNVs and indels among patients with ASD were loss of function (LOF) variations and were slightly more frequent among female (male vs. female: 7.3% vs. 8.5%). A total of seven presumed causative genes (CHD8, AFF2, ADNP, POGZ, SHANK3, IL1RAPL1, and PTEN) were identified in this study. In conclusion, WES is an efficient diagnostic tool for diagnosed ASD especially those with negative findings of CNVs and other neurological disorders in clinical practice, enabling early identification of disease related genes and contributing to precision and personalized medicine

Genetic Evaluation of 114 Chinese Short Stature Children in the Next Generation Era: a Single Center Study

Background/Aims: The genetics of human height is a frequently studied and complex issue. However, there is limited genetic research of short stature. To uncover the subgroup of patients to have higher yield and to propose a simplified diagnostic algorithm in the next generation era. Methods: This study included 114 Chinese children with height SDS ≤ -2.5 and unknown etiology from 2014 to 2015. Target/whole exome sequencing (referred as NGS) and chromosomal microarray analysis (CMA) were performed on the enrolled patients sequentially to identify potential genetic etiologies. The samples solved by NGS and CMA were retrospectively studied to evaluate the clinical pathway of the patients following a standard diagnostic algorithm. Results: In total, a potential genetic etiology was identified in 41 (36%) patients: 38 by NGS (33.3%), two by CMA (1.8%), and an additional one by both (0.9%). There were 46 different variants in 29 genes and 2 pathogenic CNVs identified. The diagnostic yield was significantly higher in patients with facial dysmorphism or skeletal abnormalities than those without the corresponding phenotype (P=0.006 and P=0.009, respectively, Pearson’s χ2 test). Retrospectively study the cohort indicate 83.3% patients eventually would be evaluated by NGS/CMA. Conclusion: This study confirms the utility of high-throughput molecular detection techniques for the etiological diagnosis of undiagnosed short stature and suggests that NGS could be used as a primary diagnostic strategy. Patients with facial dysmorphism and/or skeletal abnormalities are more likely to have a known genetic etiology. Moving NGS forward would simplified the diagnostic algorithm