检索结果-南通市图书馆

Artificial intelligence for geoscience:Progress,challenges,and perspectives

在线全文

学校读者我要写书评

暂无评论

The Innovation 2024年第5期5卷 136-160,135页

作者： Tianjie Zhao Sheng Wang Chaojun Ouyang Min chen chenying Liu Jin Zhang Long Yu Fei Wang Yong Xie jun Li Fang Wang Sabine Grunwald Bryan MWong Fan Zhang Zhen Qian Yongjun Xu chengqing Yu Wei Han Tao Sun Zezhi Shao Tangwen Qian Zhao chen Jiangyuan Zeng Huai Zhang Husi Letu Bing Zhang Li Wang Lei Luo Chong Shi Hongjun Su Hongsheng Zhang Shuai Yin Ni Huang Wei Zhao Nan Li Chaolei Zheng Yang Zhou Changping Huang Defeng Feng Qingsong Xu Yan Wu Danfeng Hong Zhenyu Wang Yinyi Lin Tangtang Zhang Prashant Kumar Antonio Plaza Jocelyn Chanussot Jiabao Zhang Jiancheng Shi Lizhe Wang Aerospace Information research institute Chinese Academy of SciencesBeijing 100094China School of Computer Science China University of GeosciencesWuhan 430078China State Key Laboratory of Mountain Hazards and Engineering Resilience Institute of Mountain Hazards and EnvironmentChinese Academy of SciencesChengdu 610299China Key Laboratory of Virtual geographic Environment(Ministry of Education of PRC) Nanjing Normal UniversityNanjing 210023China Data Science in Earth Observation Technical University of Munich80333 MunichGermany The National Key Laboratory of Water Disaster Prevention Yangtze Institute for Conservation and DevelopmentHohai UniversityNanjing 210098China institute of Computing Technology Chinese Academy of SciencesBeijing 100190China School of geographical sciences Nanjing University of Information Science and TechnologyNanjing 210044China State Key Laboratory of Soil and Sustainable Agriculture Institute of Soil ScienceChinese Academy of SciencesNanjing 210008China Soil Water and Ecosystem Sciences DepartmentUniversity of FloridaPO Box 110290GainesvilleFLUSA Materials Science Engineering Program Cooperating Faculty Member in the Department of Chemistry and Department of Physics Astronomy University of CaliforniaCaliforniaRiversideCA 92521USA institute of Remote Sensing and geographical Information System School of Earth and Space SciencesPeking UniversityBeijing 100871China Key Laboratory of Computational Geodynamics University of Chinese Academy of SciencesBeijing 100049China International research Center of Big Data for Sustainable Development Goals Beijing 100094China College of Geography and Remote Sensing Hohai UniversityNanjing 211100China Department of Geography The University of Hong KongHong Kong 999077SARChina Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control Nanjing 210044China School of Environmental Science and Engineering Nanjing University of Information Science&TechnologyNanjing 210044China Collaborative Inno

This paper explores the evolution of geoscientific inquiry,tracing the progression from traditional physics-based models to modern data-driven approaches facilitated by significant advancements in artificial intelligence(AI)and data collection *** models,which are grounded in physical and numerical frameworks,provide robust explanations by explicitly reconstructing underlying physical ***,their limitations in comprehensively capturing Earth’s complexities and uncertainties pose challenges in optimization and real-world *** contrast,contemporary data-driven models,particularly those utilizing machine learning(ML)and deep learning(DL),leverage extensive geoscience data to glean insights without requiring exhaustive theoretical *** techniques have shown promise in addressing Earth science-related ***,challenges such as data scarcity,computational demands,data privacy concerns,and the“black-box”nature of AI models hinder their seamless integration into *** integration of physics-based and data-driven methodologies into hybrid models presents an alternative *** models,which incorporate domain knowledge to guide AI methodologies,demonstrate enhanced efficiency and performance with reduced training data *** review provides a comprehensive overview of geoscientific research paradigms,emphasizing untapped opportunities at the intersection of advanced AI techniques and *** examines major methodologies,showcases advances in large-scale models,and discusses the challenges and prospects that will shape the future landscape of AI in *** paper outlines a dynamic field ripe with possibilities,poised to unlock new understandings of Earth’s complexities and further advance geoscience exploration.

关键词： Earth utilizing landscape

Hydrologic and water quality performance of a laboratory scale bioretention unit

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Frontiers of Environmental Science & Engineering 2018年第1期12卷 159-167页

作者： jun xia Hongping Wang Richard L. Stanford Guoyan Pant Shaw L. Yus State Key Laboratory of Water resources ＆ Hydropower Engineering sciences Wuhan University Wuhan 430072 China Key Laboratory of Water Cycle ＆ Related Land Surface Processes Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing 100101 China Department of Environmental Engineering School of Resources and Environmental Science Wuhan University Wuhan 430079 China ATR Associates Inc. Strasburg VA 22657 USA Department of Civil and Environmental Engineering University of Virginia Charlottesville VA 22903 USA

A bioretention unit （BRU） or cell is a green infrastructure practice that is widely used as a low impact development （LID） technique for urban stormwater management. Bioretention is considered a good fit for use in china＇s sponge cit.y construction,projects. However, studies on biooretention design, whichincorporates site-specific environmental and social-economic conditions in china are still very much needed. In this study, an experimental BRU, consisted of two cells planted with Turf grass and Buxus shfica,was tested with eighteen synthesized storm events. Three levels （high, median, low） of flows and concentrations of pollutants （TN, TP and COD） were fed to the BRU and the performance of which was examined. The results showed that the BRU not only delayed and lowered the peak flowsbut also removed TN, TP and COD in various ways and to different extents. Under the high, medium and low inflow rate conditions, the outflow peaks were delayed for at least 13 minutes and lowered at least 52.. The two cells stored a maximum of 2.1 mm and 2.5 mm for turf grass and Buxus sinica, respectively. For both cells the total depth available for storage was 1,2.0 mm, including a maximum 110 mm deep ponding area. The largest infiltrate rate was 2.6 mrn/h for both cells with different plants. For the eighteen events, TP and COD were removed at least 60% and 42. by mean concentration, and 65% and 49% by total load, respectively. In the reservoir layer, the efficiency ratio of removal of TN, TP and COD were 52., 8% and 38%, respectively, within 5 days after runoff events stopped. Furthermore, the engineering implication of the hydrological and water quality performances in sponge city construction projects is discussed.

关键词： Bioretention unitSponge cityStormwater runoffPeak reductionPollutant removal

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

三江源区典型植被蒸散及水量平衡分析

华北水利水电大学学报（自然科学版） 2024年第3期45卷 42-50页

作者：屈柳燕贾绍凤李润杰温军周秉荣权晨青海师范大学青海省自然地理与环境过程重点实验室青海西宁810008 中国科学院地理科学与资源研究所陆地水循环及地表过程重点实验室北京100101 青海省水利水电科学研究院有限公司流域水循环与生态重点实验室青海西宁810001 青海省气象科学研究所青海西宁810001

植被蒸散对生态系统的能量转换和水量平衡有直接影响。为探讨三江源区不同植被蒸散时程分配及其水量平衡特征,以灌丛(金露梅、置疑小檗、鬼箭锦鸡儿、乌柳)、草地(星星草、针茅、早熟禾、垂穗披碱草、芨芨草、冰草、丛生薹草、高山蒿草... 详细信息

植被蒸散对生态系统的能量转换和水量平衡有直接影响。为探讨三江源区不同植被蒸散时程分配及其水量平衡特征,以灌丛(金露梅、置疑小檗、鬼箭锦鸡儿、乌柳)、草地(星星草、针茅、早熟禾、垂穗披碱草、芨芨草、冰草、丛生薹草、高山蒿草)为研究对象,于2.19年11月—2.2.年10月采用蒸渗仪法对其实际蒸散进行测量,应用Angstrom太阳经验公式与Penman-Monteith公式估算凝结水,研究了其蒸散量及时程分配规律,探讨了不同植被下垫面的水量平衡特征。结果表明:(1)三江源区凝结水普遍存在且全年都在发生,各地年凝结水量的变化范围为2..47~56.88 mm,凝结水日发生概率为75.68%~95.90%。(2.植被年蒸散量空间分布不均,年蒸散量的变化范围为396.2.~707.69 mm,夏季(6—8月)蒸散量占全年蒸散量的41.69%~70.74%。(3)水量平衡特征空间异质性明显,金露梅与置疑小檗、鬼箭锦鸡儿与乌柳的水量平衡特征基本一致,不同牧草间水量平衡特征不一致。整体来看,植被蒸散量高于降水量与凝结水量之和,各植被类型对土壤水均有不同程度的消耗(8.04~67.68 mm)。

关键词：三江源蒸散凝结水水量平衡

中国1960—2.19年体感温度的时空变化及其风险分析

在线全文

学校读者我要写书评

暂无评论

气候变化研究进展 2024年第3期20卷 265-277页

作者：陈婷婷余文君李艳忠白鹏星寅聪黄曼捷邵伟南京信息工程大学水文与水资源工程学院南京210044 水利部水文气象灾害机理与预警重点实验室南京210044 中国科学院地理科学与资源研究所/中国科学院陆地水循环及地表过程重点实验室北京100101

体感温度(Apparent Temperature,AP)描述了人体实际感受到的温度。文中基于我国1960—2.19年的空气温度、相对湿度和风速等气象要素数据,估算并分析了4个典型气候区(湿润区、过渡区、干旱区和青藏高原)AP的时空变化格局及其高温风险。... 详细信息

体感温度(Apparent Temperature,AP)描述了人体实际感受到的温度。文中基于我国1960—2.19年的空气温度、相对湿度和风速等气象要素数据,估算并分析了4个典型气候区(湿润区、过渡区、干旱区和青藏高原)AP的时空变化格局及其高温风险。结果发现:(1)在空间分布上,AP由东南沿海向西北内陆递减,平均AP值由湿润区(约为17.0℃)逐渐向干旱区(约为7.0℃)和青藏高原区(约为0.6℃)递减;(2.全国AP呈现显著上升的趋势,4个典型气候区的上升速率分别为0.2.℃/(10 a)、0.2.℃/(10 a)、0.15℃/(10 a)和0.13℃/(10 a);(3)气温变化对AP的贡献率最高,约为92.4%,其次是风速及相对湿度,约为5.6%和2.0%;(4)典型气候区的高温风险天数变化呈现空间异质性,湿润区和青藏高原大部分地区均呈现显著增长趋势。

关键词：体感温度(AP) 时空变化中国气候区归因分析风险分析

S1PR1 serves as a viable drug target against pulmonary fibrosis by increasing the integrity of the endothelial barrier of the lung

在线全文

学校读者我要写书评

暂无评论

Acta Pharmaceutica Sinica B 2023年第3期13卷 1110-1127页

作者： Mengyao Hao Rong Fu jun Tai Zhenhuan Tian xia Yuan Yang {2. Mingjin Wang Huimin Jiang Ming Ji Fangfang Lai Nina Xue Liping Bai Yizhun Zhu xiaoxi Lv xiaoguang {2. Jing Jin State Key Laboratory of Bioactive Substances and Functions of natural Medicines Institute of Materia MedicaChinese Academy of Medical SciencesPeking Union Medical CollegeBeijing 100050China Department of Otolaryngology Head and Neck SurgeryChildren's Hospital Capital Institute of PediatricsBeijing 100020China Department of Thoracic Surgery Peking Union Medical College HospitalPeking Union Medical CollegeDong Cheng DistrictBeijing 100730China State Key Laboratory of natural and Biomimetic Drugs School of Pharmaceutical SciencesPeking UniversityBeijing 100191China Department of Pharmacology School of PharmaceuticalGuangzhou University of Chinese MedicineGuangzhou 510000China State Key Laboratory of Quality research in chinese Medicine Macao Institute for Applied Research in Medicine and HealthMacao University of Science and TechnologyTaipaMacao SAR 999078China

Idiopathic pulmonary fibrosis(IPF)is a progressive lung disease with unclear etiology and limited treatment *** median survival time for IPF patients is approximately 2.3 years and there is no effective intervention to treat IPF other than lung *** important components of lung tissue,endothelial cells(ECs)are associated with pulmonary ***,the role of endothelial dysfunction in pulmonary fibrosis(PF)is incompletely ***-1-phosphate receptor 1(S1PR1)is a G protein-coupled receptor highly expressed in lung *** expression is markedly reduced in patients with ***,we generated an endothelial-conditional S1pr1 knockout mouse model which exhibited inflammation and fibrosis with or without bleomycin(BLM)*** activation of S1PR1 with an S1PR1 agonist,IMMH002.exerted a potent therapeutic effect in mice with bleomycin-induced fibrosis by protecting the integrity of the endothelial *** results suggest that S1PR1 might be a promising drug target for IPF therapy.

关键词： Idiopathic pulmonary fibrosis Endothelial barrier Tight junction Sphingosine-1-phosphate receptor 1 Sphingosine-1-phosphate receptor 1 agonist FTY72. IMMH002 Protein stability

Impacts of Climate Change on the Hydrological Cycle in the Haihe Basin

在线全文

学校读者我要写书评

暂无评论

Impacts of Climate Change on the Hydrological Cycle in the H...

2.11 International Symposium on Water Resource and Environmental Protection(ISWREP 2.11)

作者： Zeng Sidong Zhang Liping xia jun State Key Laboratory of Water resources and Hydropower Engineering sciences Wuhan University Key Laboratory of Water Cycle & Related Processes The institute of geographic sciences and natural resources research Chinese Academy of Sciences

ISBN: (纸本)9781612843377

Climate change will lead to a significant alteration in regional hydrological *** this paper,the impacts of climate change on the hydrological cycle were analyzed for the Haihe ***,the linear regression and Mann-Kendall non-parametric test methods were used to analyze the change characteristics of the hydrological and meteorological *** results show a significant increase for temperature,while precipitation decreases slightly,and runoff decreases drastically during the past 50 *** the applicability of SWAT （Soil and Water Assessment Tool） model based on the DEM （Digital Elevation Model）,land use and soil type was verified in the *** the precipitation,temperature,runoff and evaporation response processes based on the IPCC AR4 multi-mode climate models under different GHG emission scenarios （SRES-A2.A1B and B1） in the 2.st century were discussed in three time periods:2.2.s （2.11-2.40）,2.50s （2.41-2.70）,2.80s （2.71-2.99）.The results show that there are systematic positive trends for precipitation and temperature while the trends for runoff and evaporation will differ with *** with the reference period （1961-1990）,the future runoff in the Haihe basin decreases in the previous period while increases in the subsequent period during which the increasing trend are more pronounced in the south than in the *** future evaporation in the basin shows an increase with a positive trend in the northern part and a negative trend in the southern part.

关键词： The Haihe basin Climate Change Water Cycle SWAT

来源： cnki会议评论

在线全文

cnki会议

学校读者我要写书评

暂无评论

平原M5.5地震土壤气地球化学特征及成因

地震地质 2024年第2期46卷 433-448页

作者：苏淑娟陈其峰孙豪刘军冯梁乐徐继龙杨彦明雒昆利山东省地震局济南250000 中国科学院地理科学与资源研究所北京100101 内蒙古自治区地震局呼和浩特010010 中国地震局地质研究所地震动力学国家重点实验室北京100029

2.2.年8月6日2.33分,山东省德州市平原县发生M5.5地震。文中跨震中布设4条长30km的勘测线,现场测量了土壤气Rn、CO_(2.和Hg浓度。结果表明:1)土壤气浓度表现出明显的空间差异,震中区与4条测线的东、西两端气体浓度相对较高。2.土壤气... 详细信息

2.2.年8月6日2.33分,山东省德州市平原县发生M5.5地震。文中跨震中布设4条长30km的勘测线,现场测量了土壤气Rn、CO_(2.和Hg浓度。结果表明:1)土壤气浓度表现出明显的空间差异,震中区与4条测线的东、西两端气体浓度相对较高。2.土壤气浓度的空间分布特征在震中及其东部地区相似,但在震中西部差异较大,在西部旧城断裂(F_(3))附近,Rn和CO_(2.的浓度高于震中区,推测应与地震活动和F_(3)控制的鼻状构造有关。3)Rn、CO_(2.和Hg的浓度在陵县-冠县断裂(F_(1))和F_(3)附近出现高值异常,余震自F_(1)向F_(3)发展,结合地质与地球物理研究资料推断,平原M5.5地震应与F_(1)和F_(3)共同作用有关。以上结果表明,气体地球化学方法能较好地指示隐伏断层的位置与展布方向。

关键词：平原M5.5地震断层土壤气浓度陵县-冠县断裂旧城断裂构造地球化学

维普期刊数据库博看期刊

Multi-object approach and its appfication to adaptive water management under climate change

在线全文

学校读者我要写书评

暂无评论

Journal of geographical sciences 2017年第3期27卷 259-274页

作者： HONG Si xia jun {2. junxu WAN Long NING Like SHI Wei Key Laboratory of Water Cycle and Related Land Surface Processes Institute of Geographic Sciences and Natural Resources Research CAS Beijing 100101 China State Key Laboratory of Water resources and Hydropower Engineering Science Wuhan University Wuhan 430072 China University of chinese academy of sciences Beijing 100049 China School of Resource Environment and Earth Science Yunnan University Kunming 650091 China

This paper addresses issues on adaptive water management under the impact of climate change. Based on a set of comprehensive indicators of water system, a decision making approach of multi-objects is developed and applied to quantify water adaptive man- agement for the demands of water sustainable use, water environmental protection and eco-water requirement under the climate change. For this study in china, two key indicators are proposed, namely （1） the water resources vulnerability （V） that was represented by inte- grated sensitivity （S） and resilience （C） of climate change impact on water resources, and （2. the sustainability of socio-economy and water environment, marked by DD, that is integrated scaler of socio-economic development （EG） based on the amount of GDP and the water en- vironment and relative eco-system quality （LI）. To find a reasonable solution for adaptive water management, a multi-objective decision making model of adaptive water management is further developed and the multi-objective model was transformed into an integrated single optimization model through developing an integrated measure function, called as VDD=DD/V. This approach has been applied to adaptive water resources planning and management for case study of china with new policy, called as the strict management of water resources based on three red line controls, i.e., the control of total water use by the total water re- sources allocation, the control of lower water use efficiency by the water demand manage- ment and the control of the total waste water load by water quality management in the East- ern china Monsoon Region that covers major eight big river basins including Yangtze River, Yellow River, Haihe River and Huaihe River. It is shown that the synthetic representation of water resource vulnerability and socio-economic sustainability by the integrated objective function （VDD） and integrated decision making model are workable and practicable. Adaptive management effect of the

关键词： adaptive water management climate change multi-object vulnerability sustainability VDD

耦合统计方法、机器学习模型和聚类算法的滑坡易发性评价方法

在线全文

学校读者我要写书评

暂无评论

地球信息科学学报 2024年第3期26卷 620-637页

作者：王启盛熊俊楠程维明崔兴洁庞全刘俊陈文杰唐浩然宋南霄西南石油大学土木工程与测绘学院成都610500 中国科学院地理科学与资源研究所资源与环境信息系统国家重点实验室北京100101 中山大学地理科学与规划学院广州510275 四川省安全科学技术研究院成都610046 四川安信科创有限公司成都610041

我国西部山区滑坡灾害频发,精确评估滑坡易发性对地质灾害防治至关重要。结合统计方法与机器学习模型的集成模型已广泛的应用于滑坡易发性评价,然而对其结果的进一步优化仍值得考虑。本文提出一种耦合统计方法、机器学习模型以及聚类算... 详细信息

我国西部山区滑坡灾害频发,精确评估滑坡易发性对地质灾害防治至关重要。结合统计方法与机器学习模型的集成模型已广泛的应用于滑坡易发性评价,然而对其结果的进一步优化仍值得考虑。本文提出一种耦合统计方法、机器学习模型以及聚类算法的综合评价方法,以宁南县为例,研究其对滑坡易发性评价精度的提升效应。该方法首先将信息量法(Information Value, IV)、确定系数法(Certainty Factor, CF)和频率比法(Frequency Ratio, FR)分别与随机森林模型(Random Forest, RF)结合,得到三种集成模型(IV-RF、CF-RF、FR-RF)。此后,引入ISO聚类算法对三种集成模型的结果进行分级,得到三种耦合模型(IV-RF-ISO、CF-RF-ISO、FR-RF-ISO)。AUC值(Area Under the Curve)、准确率、F1分数和种子单元面积指数(Seed Cell Area Indexes,SCAI)被用于评估模型的精度。结果显示,集成模型性能均优于单一模型,其准确率和F1分数均大于0.85,AUC值均大于0.9。其中FR-RF模型表现最优,准确率(0.911)、F1分数(0.912.和AUC值(0.965)较FR模型分别提升了0.095、0.096和0.074。与自然断点法和Kmeans聚类法相比,引入ISO算法的耦合模型FR-RF-ISO分级效果最优,其高低易发区SCAI值的差异更为显著。本研究成果表明,耦合统计方法、机器学习与聚类算法的综合评价方法具有较高精度,为提高滑坡易发性评价精度提供思路。

关键词：滑坡易发性信息量确定系数频率比随机森林聚类算法宁南县