From the perspective of achieving sustainable development in the world and building a community with a shared future for humankind in the "Anthropocene", and considering the complexity of the Earth's surface system, various disasters facing humanity, and future challenges of resource shortages and environmental risks, we proposed the development of "geographical synergy"—the mechanism, process and dynamics of the Earth's surface system and regional sustainability—in order to realize the transformation of geographical research from the explanation of human-environment relationship to the design of human-environment synergy. We discussed the scientific and technological questions of modern geography from the perspectives of integrating natural and social units, natural resources and natural disasters, achievements and faults of humans, and coupling of dynamic and non-dynamic processes and systems. We proposed the metrics of "consilience degree" as a measure of the complexity of integrated disaster reduction system based on the understanding of disaster system and the mechanism, process and dynamics of hazard and disaster formation. Using the principles of synergetic tolerance, synergetic constraint, synergetic amplification and synergetic diversification, we proposed to build an integrated disaster risk governance consilience model under the leadership of governments and with enterprises as the main body and the full participation of communities, with multiple optimization objectives of social consent maximization, cost minimization, welfare maximization, and risk minimization. Finally, we elaborated on the synergy of human and nature through "changing nature appropriately", with a case study on the Dujiangyan irrigation system, which enabled the win-win pattern of disaster reduction and benefit making.

本文从地球进入“人类世”（Anthropocene）之后,实现世界可持续发展、建设人类命运共同体的角度出发,就地表系统的复杂性、人类面临的各种灾难以及将要面临的各种资源短缺和环境风险等问题,提出发展“地理协同论”,即：地球表层系统与区域可持续性机理、过程与动力学,以实现地理学研究从理解“人—地关系”到设计“人—地协同”的转变。着眼于“人类世”时代地球表层系统由多尺度、多过程等组成的复杂性,回顾了区域论、综合论、系统论等经典地理学理论,从自然单元与社会单元的结合、自然资源利用与自然灾害防御、人类功与过的评价、自然地图与行政地图间的关系、动力学与非动力学的耦合等主题入手,深入讨论了现代地理科学与技术问题。通过理解灾害系统及其致灾成害机理、过程和动力学,构建凝聚度指标,量化综合减灾系统的复杂性。利用协同宽容、约束、放大和分散原理,以灾害风险防范共识最高、成本最低、福利最大、风险最小化为目标,构建以政府为主导、企业为主体和社区全面参与的综合灾害风险防范凝聚力模式。在分析都江堰工程如何实现除害与兴利并举的基础上,综合阐释了“人类世”时代“适度改造自然”,以实现人与自然的协同。

Since the 20th century, geography came into being with distinctive disciplinary characteristics by sustained effort of geographers. This paper puts forward predicament from cognitive and thought in the new era, and depicts new geographic characteristics from five aspects: new technology, new orders, new data, new approaches and new driving factors. According to new content of geo-regionality and new approaches of geo-comprehensiveness, the paper proposes that complexity research would be a successful new path in geography, and the complexity would be the third characteristic of geography. Then, the paper details some complex spatial patterns, complex time processes and complex spatio-temporal mechanisms in geography research. Based on the concept of a geographic complex system, this paper presents core issues and corresponding complex research tools. Finally, the paper puts forward new challenges and new requirements for geography in the new era.

20世纪以来,经地理学者不断探索和努力,地理学已经形成了其特有的学科特征。首先从认知方法和思维角度,阐述了新时代地理学所面临的困境;从新技术、新秩序、新数据、新方法以及新动因等方面,诠释了地理学的新时代特征。其次,针对地理区域性的新内涵和地理综合性研究所需的新方法,提出了复杂性研究是地理学成功的新路径,并认为复杂性是地理学研究的第三特征。再次,重点讨论了地理研究存在的空间复杂格局、时间复杂过程和时空复杂机制,进而解释了地理复杂系统的基本概念,并就地理复杂系统的核心问题提供了相应的研究方法。最后,提出了新时代地理学面临的新挑战和新要求。

Physical geography is the cornerstone of comprehensive study in geography. On the basis of reviewing the main research progress of physical geography, this article discussed the new research directions of physical geography. Driven by global environmental changes, physical geography and its branches have achieved significant progress. Recent progress in physical geography mainly includes research on the synthesis of physical geographic processes, land surface system integration, land-sea interaction, and physical geography application for regional ecological or environmental management. Physical geography needs to face the global climate change and human needs, explore new methods of technology application, carry out integrated multi-factor and multi-process research, develop geographical models, model future environmental dynamics and sustainable development, and serve the national priorities. In the process of physical geography development, we should pay more attention to the following frontier areas and directions: (1) geomorphology needs to focus on the study of geomorphology and global environmental change, and geomorphology and human activities; (2) biogeography needs to focus on the exploration of frontier fields such as attribute geography, global change biogeography, and to connect spatial distribution in biogeography and human needs under the background of change; (3) hydrology needs to integrate the multi-factor, multi-process, and multi-scale research, and to promote the development of ecological hydrology, social hydrology, and hydrological morphology; (4) physical geography needs to play a key role in the research of climate change, and serve major international research projects in climate change; (5) comprehensive physical geography research needs to meet national priority demands, focusing on the coupling of human-land system, resource and environment carrying capacity assessment, ecological security pattern, and ecological civilization construction; (6) physical geography needs to merge the natural and human elements and processes, develop complex system simulation models, and analyze the coupling mechanism of natural and human factors and the dynamic change of land surface system.

自然地理学是地理学的基础学科,也是地理学综合研究的基石。本文在梳理自然地理学主要研究进展的基础上,思考了新时代自然地理学的发展方向。在全球环境变化驱动下,自然地理学及其分支学科在传承中得到新的发展。自然地理学近年来的研究进展主要表现为自然地理过程综合与深化、陆地表层系统集成、陆海相互作用和区域生态环境管理应用等方面。自然地理学及其分支学科的发展需要面向全球环境变化和人类需求,探索应用新技术新方法,开展多要素多过程集成研究,发展并完善地理模型,模拟和预测环境变化与可持续发展,服务于国家重大需求和政府决策。在发展过程中,亟待关注以下前沿领域与方向：①地貌学需要重点加强地貌学与全球环境变化及人类活动关系研究;②生物地理学有待深化属性地理学、全球变化生物地理学等前沿领域的探索,连接变化背景下的生物地理空间分布与人类需求;③水文学需要开展多要素、多过程、多尺度的综合集成研究,发展生态水文学、社会水文学、水文形态学等新兴学科领域;④自然地理学有待全方位介入气候变化研究,在气候变化国际重大研究计划、气候变化框架公约等方面发挥更加积极的支撑功能;⑤综合自然地理需要面向国家重大需求,聚焦人地系统耦合研究,在资源环境承载力评估、生态安全格局与生态文明建设等领域作出积极贡献;⑥自然地理学需深化耦合自然与人文要素及过程研究,建立发展复杂系统模拟模型,分析和模拟变化环境下的自然、人文要素耦合机制和陆地表层系统动态变化规律。

The modern international and domestic science advancements have brought forward new opportunities as well as higher requirements to the development of geographic science in China. In planning the disciplinary structure of geographic science in the "Development Strategy of Discipline and Frontier Research in China (2021-2035)", we propose a modified disciplinary structure for the geographic science in the new era. The geographic science in China can be categorized into four secondary disciplines, i.e., integrated geography, physical geography, human geography, and information geography, considering the current situation and development outlook of geographic science. The tertiary disciplines under each secondary discipline are nearly fully developed, and a few quaternary disciplines under tertiary disciplines have already been widely accepted and used. We hope this new disciplinary structure can play a breakthrough role for improving the branches of geographic science, promoting the development of emerging disciplines under the framework of geographic science, and better serving the international and domestic development needs in the new era.

新的国际和国内形势为地理科学带了新的发展机遇,同时也提出了更高的要求。以《中国学科及前沿领域发展战略研究（2021—2035）》地理科学的学科规划为契机,本文系统梳理了新时期地理科学的学科体系。根据地理科学现状和发展趋势,中国地理科学可划分为综合地理学、自然地理学、人文地理学和信息地理学4个二级学科,各二级学科下的三级学科也基本成熟,有些三级学科下的四级学科名称也在普遍使用。我们希望以这一新的学科体系为支点,完善地理科学的学科分支,推动地理科学框架下新兴学科的发展,更好地服务于新时期国际及国家的战略需求。

Since 2010, big data has played a significant role in various fields of science, engineering and society. The paper introduces the concepts of geographic big-data, the fourth paradigm and nonlinear complex geographic system, and discusses interactive relationships of these concepts. It is proposed that geographic big-data and the fourth paradigm would become a new opportunity to research on geography complexity. Then the paper discusses how to use the methods of geographic big-data and complexity science to examine geography complexity. For example, based on big-data, a series of indicators of statistical physics fields could be constructed to describe the complex nonlinear characteristics of the real geographic world. Deep learning, complex network and multi-agent methods can be used to model and simulate the complex nonlinear geographic systems. These methods are important for a better understanding of the complexity of geographic phenomena and processes, as well as the analysis, simulation, inversion and prediction of complex geographic systems. Finally, the paper highlights that the combination of geographic big-data and complexity science would be the mainstream scientific method of geography in the 21st century.

大数据之风自2010年席卷全球,已在科学、工程和社会等领域产生深远影响。本文首先从地理大数据、第四范式以及非线性复杂地理系统3组基本概念出发,剖析上述3组概念之间的科学联系与相互支撑作用,提出大数据和第四范式为地理复杂性研究提供新机遇。其后,探讨如何利用大数据和复杂性科学的理论方法开展地理复杂性研究。基于地理大数据,可以通过统计物理学的系列指标描述现实地理世界的复杂非线性特征,同时,还可利用深度学习、复杂网络、多智能体等方法,实现复杂非线性地理系统的推演和模拟。上述方法对认知地理现象和过程的复杂性,对复杂地理系统的分析、模拟、反演与预测有重要作用。最后,提出地理大数据和复杂性科学相互支撑可能成为21世纪地理学的主流科学方法。

“一带一路”沿线为自然灾害高发地区,且多为经济欠发达、抗灾能力弱的发展中国家。灾害发生时,挖掘和分析相关推特数据有助于开展应急救援、灾情评估、减灾防灾等工作,为中国国际救援与救助工作提供重要支撑。主题模型能在没有经验语料库的情况下,从海量灾害相关推文中快速聚合出对灾害救援、评估有价值的信息。本文采用BTM模型和LDA模型,对2013年海燕台风相关推文进行细粒度的主题聚类,分析2个模型的精度并测试它们对近似灾害主题的区分能力,并基于“需求相关”主题类的推文,通过地名匹配,分析了海燕台风发生过程中菲律宾物资、医疗等需求程度的空间分布。结果表明： ① 在区分主题近似的短文本时,BTM总体精度为0.598,LDA的总体精度仅为0.321,说明在海燕台风灾害推文的主题识别中,BTM模型的精度高于LDA模型;② BTM能够较好识别出“灾害地点相关”、“祈福相关”等较为精细的灾害主题;③ 经初步验证,基于“需求相关”主题文本生成的物资、医疗等需求的需求程度空间分布与实际需求情况基本相符。

Kinship networks are a fundamental social unit in human societies, and like social networks in general, provide social support in times of need. Here, we investigate the impact of sudden environmental shock, the M 7.0 2013 Ya'an earthquake, on the mobile communications patterns of local families, which we operationalize using anonymized individual-level mobile telecommunications metadata from family plan subscribers of a major carrier (N = 35,565 people). We demonstrate that families' communications dynamics after the earthquake depended on their triadic embeddedness structure, a structural metric we propose that reflects the number of dyads in a family triad that share social ties. We find that individuals in more embedded family structures were more likely to first call other family plan members and slower in calling non-family ties immediately after the earthquake; these tendencies were stronger at higher earthquake intensity. In the weeks after the event, individuals in more embedded family structures had more reciprocal communications and contacted more social ties in their broader social network. Overall, families that are structurally more embedded displayed higher levels of intra-family coordination and mobilization of non-family social connections.© 2021. The Author(s).

Video supervision equipment, which is readily available in most cities, can record the processes of urban floods in video form. Ubiquitous reference objects, which often appear in videos, can be used to indicate urban waterlogging depths. This makes video images a valuable data source for obtaining waterlogging depths. However, the urban waterlogging information contained in video images has not been effectively mined and utilized. In this paper, we present a method to automatically estimate urban waterlogging depths from video images based on ubiquitous reference objects. First, reference objects from video images are detected during the flooding and non-flooding periods using an object detection model with a convolutional neural network (CNN). Then, waterlogging depths are estimated using the height differences between the detected reference objects in these two periods. A case study is used to evaluate the proposed method. The results show that our proposed method could effectively mine and utilize urban waterlogging depth information from video images. This method has the advantages of low economic cost, acceptable accuracy, high spatiotemporal resolution, and wide coverage. It is feasible to promote this proposed method within cities to monitor urban floods.

We introduce physics-informed neural networks - neural networks that are trained to solve supervised learning tasks while respecting any given laws of physics described by general nonlinear partial differential equations. In this work, we present our developments in the context of solving two main classes of problems: data-driven solution and data-driven discovery of partial differential equations. Depending on the nature and arrangement of the available data, we devise two distinct types of algorithms, namely continuous time and discrete time models. The first type of models forms a new family of data-efficient spatio-temporal function approximators, while the latter type allows the use of arbitrarily accurate implicit Runge-Kutta time stepping schemes with unlimited number of stages. The effectiveness of the proposed framework is demonstrated through a collection of classical problems in fluids, quantum mechanics, reaction-diffusion systems, and the propagation of nonlinear shallow-water waves. (C) 2018 Elsevier Inc.

. By coordinating the design and distribution of global climate model simulations of the past, current, and future climate, the Coupled Model Intercomparison Project (CMIP) has become one of the foundational elements of climate science. However, the need to address an ever-expanding range of scientific questions arising from more and more research communities has made it necessary to revise the organization of CMIP. After a long and wide community consultation, a new and more federated structure has been put in place. It consists of three major elements: (1) a handful of common experiments, the DECK (Diagnostic, Evaluation and Characterization of Klima) and CMIP historical simulations (1850–near present) that will maintain continuity and help document basic characteristics of models across different phases of CMIP; (2) common standards, coordination, infrastructure, and documentation that will facilitate the distribution of model outputs and the characterization of the model ensemble; and (3) an ensemble of CMIP-Endorsed Model Intercomparison Projects (MIPs) that will be specific to a particular phase of CMIP (now CMIP6) and that will build on the DECK and CMIP historical simulations to address a large range of specific questions and fill the scientific gaps of the previous CMIP phases. The DECK and CMIP historical simulations, together with the use of CMIP data standards, will be the entry cards for models participating in CMIP. Participation in CMIP6-Endorsed MIPs by individual modelling groups will be at their own discretion and will depend on their scientific interests and priorities. With the Grand Science Challenges of the World Climate Research Programme (WCRP) as its scientific backdrop, CMIP6 will address three broad questions: – How does the Earth system respond to forcing? – What are the origins and consequences of systematic model biases? – How can we assess future climate changes given internal climate variability, predictability, and uncertainties in scenarios? This CMIP6 overview paper presents the background and rationale for the new structure of CMIP, provides a detailed description of the DECK and CMIP6 historical simulations, and includes a brief introduction to the 21 CMIP6-Endorsed MIPs.\n

. Cropland greatly impacts food security, energy supply,\nbiodiversity, biogeochemical cycling, and climate change. Accurately and\nsystematically understanding the effects of agricultural activities requires\ncropland spatial information with high resolution and a long time span. In\nthis study, the first 1 km resolution global cropland proportion dataset for\n10 000 BCE–2100 CE was produced. With the cropland map initialized in 2010 CE, we first harmonized the cropland demands extracted from the History\nDatabase of the Global Environment 3.2 (HYDE 3.2) and the Land-Use\nHarmonization 2 (LUH2) datasets and then spatially allocated the demands\nbased on the combination of cropland suitability, kernel density, and other\nconstraints. According to our maps, cropland originated from several\nindependent centers and gradually spread to other regions, influenced by\nsome important historical events. The spatial patterns of future cropland\nchange differ in various scenarios due to the different socioeconomic\npathways and mitigation levels. The global cropland area generally shows an\nincreasing trend over the past years, from 0×106 km2 in 10 000 BCE\nto 2.8×106 km2 in 1500 CE, 6.2×106 km2 in 1850 CE,\nand 16.4×106 km2 in 2010 CE. It then follows diverse trajectories\nunder future scenarios, with the growth rate ranging from 16.4 % to\n82.4 % between 2010 CE and 2100 CE. There are large area disparities among\ndifferent geographical regions. The mapping result coincides well with\nwidely used datasets at present in both distribution pattern and total\namount. With improved spatial resolution, our maps can better capture the\ncropland distribution details and spatial heterogeneity. The\nspatiotemporally continuous and conceptually consistent global cropland\ndataset serves as a more comprehensive alternative for long-term earth\nsystem simulations and other precise analyses. The flexible and efficient\nharmonization and downscaling framework can be applied to specific regions\nor extended to other land use and cover types through the adjustable parameters\nand open model structure. The 1 km global cropland maps are available at\nhttps://doi.org/10.5281/zenodo.5105689 (Cao et al., 2021a).\n

Young generations are severely threatened by climate change

Increasing Earth's surface air temperature yields an intensification of its hydrological cycle(1). As a consequence, the risk of river floods will increase regionally within the next two decades due to the atmospheric warming caused by past anthropogenic greenhouse gas emissions(2-4). The direct economic losses(5,6) caused by these floods can yield regionally heterogeneous losses and gains by propagation within the global trade and supply network(7). Here we show that, in the absence of large-scale structural adaptation, the total economic losses due to fluvial floods will increase in the next 20 years globally by 17% despite partial compensation through market adjustment within the global trade network. China will suffer the strongest direct losses, with an increase of 82%. The United States is mostly affected indirectly through its trade relations. By contrast to the United States, recent intensification of the trade relations with China leaves the European Union better prepared for the import of production losses in the future.