Hydrological modeling,leveraging mathematical formulations to represent the hydrological cycle,is a pivotal tool in representing the spatiotemporal dynamics and distribution patterns inherent in hydrology.These models...Hydrological modeling,leveraging mathematical formulations to represent the hydrological cycle,is a pivotal tool in representing the spatiotemporal dynamics and distribution patterns inherent in hydrology.These models serve a dual purpose:they validate theoretical robustness and applicability via observational data and project future trends,thereby bridging the understanding and prediction of natural processes.In rapid advancements in computational methodologies and the continuous evolution of observational and experimental techniques,the development of numerical hydrological models based on physicallybased surface-subsurface process coupling have accelerated.Anchored in micro-scale conservation principles and physical equations,these models employ numerical techniques to integrate surface and subsurface hydrodynamics,thus replicating the macro-scale hydrological responses of watersheds.Numerical hydrological models have emerged as a leading and predominant trend in hydrological modeling due to their explicit representation of physical processes,heightened by their spatiotemporal resolution and reliance on interdisciplinary integration.This article focuses on the theoretical foundation of surface-subsurface numerical hydrological models.It includes a comparative and analytical discussion of leading numerical hydrological models,encompassing model architecture,numerical solution strategies,spatial representation,and coupling algorithms.Additionally,this paper contrasts these models with traditional hydrological models,thereby delineating the relative merits,drawbacks,and future directions of numerical hydrological modeling.展开更多
Accurate quantification of soil moisture is essential to understand the land surface processes.Soil hydraulic properties influence water transport in soil and thus affect the estimation of soil moisture.However,some s...Accurate quantification of soil moisture is essential to understand the land surface processes.Soil hydraulic properties influence water transport in soil and thus affect the estimation of soil moisture.However,some soil hydraulic properties are only observable at a few field sites.In this study,the effects of soil hydraulic properties on soil moisture estimation are investigated by using the one-dimensional(1-D)Richards equation at ELBARA,which is part of the Maqu monitoring network over the Tibetan Plateau(TP),China.Soil moisture assimilation experiments are then conducted with the unscented weighted ensemble Kalman filter(UWEnKF).The results show that the soil hydraulic properties significantly affect soil moisture simulation.Saturated soil hydraulic conductivity(Ksat)is optimized based on its observations in each soil layer with a genetic algorithm(GA,a widely used optimization method in hydrology),and the 1-D Richards equation performs well using the optimized values.If the range of Ksat for a complete soil profile is known for a particular soil texture(rather than for arbitrary layers within the horizon),optimized Ksat for each soil layer can be obtained by increasing the number of generations in GA,although this increases the computational cost of optimization.UWEnKF performs well with optimized Ksat,and improves the accuracy of soil moisture simulation more than that with calculated Ksat.Sometimes,better soil moisture estimation can be obtained by using optimized saturated volumetric soil moisture content Ksat.In summary,an accurate soil profile can be obtained by using soil moisture assimilation with optimized soil hydraulic properties.展开更多
The utilization of big Earth data has provided insights into the planet we inhabit in unprecedented dimensions and scales.Unraveling the concealed causal connections within intricate data holds paramount importance fo...The utilization of big Earth data has provided insights into the planet we inhabit in unprecedented dimensions and scales.Unraveling the concealed causal connections within intricate data holds paramount importance for attaining a profound comprehension of the Earth system.Statistical methods founded on correlation have predominated in Earth system science(ESS)for a long time.Nevertheless,correlation does not imply causation,especially when confronted with spurious correlations resulting from big data.Consequently,traditional correlation and regression methods are inadequate for addressing causation related problems in the Earth system.In recent years,propelled by advancements in causal theory and inference methods,particularly the maturity of causal discovery and causal graphical models,causal inference has demonstrated vigorous vitality in various research directions in the Earth system,such as regularities revealing,processes understanding,hypothesis testing,and physical models improving.This paper commences by delving into the origins,connotations,and development of causality,subsequently outlining the principal frameworks of causal inference and the commonly used methods in ESS.Additionally,it reviews the applications of causal inference in the main branches of the Earth system and summarizes the challenges and development directions of causal inference in ESS.In the big Earth data era,as an important method of big data analysis,causal inference,along with physical model and machine learning,can assist the paradigm transformation of ESS from a model-driven paradigm to a paradigm of integration of both mechanism and data.Looking forward,the establishment of a meticulously structured and normalized causal theory can act as a foundational cornerstone for fostering causal cognition in ESS and propel the leap from fragmented research towards a comprehensive understanding of the Earth system.展开更多
Soil moisture is an essential climate variable(ECV) concerned widely. Due to its high spatial variability, it is costly to measure soil moisture at tens of kilometers scale. In this study, a ten-year(2002–2011) daily...Soil moisture is an essential climate variable(ECV) concerned widely. Due to its high spatial variability, it is costly to measure soil moisture at tens of kilometers scale. In this study, a ten-year(2002–2011) daily soil moisture dataset at 0.25° spatial resolution for Chinese mainland was produced through assimilating the Advanced Microwave Scanning Radiometer for Earth Observing System(AMSR-E) brightness temperature(TB) data into a land surface model(LSM). The obtained soil moisture data was evaluated against soil moisture-measuring networks deployed in two wet areas and one dry area of the Tibetan Plateau.The results show that for the wet areas the accuracy of the soil moisture product obtained from the assimilation is considerably higher than that of both AMSR-E official soil moisture products and land surface simulation results, and for the dry area their accuracy is comparable to each other. The spatial pattern of the soil moisture from the new product is consistent with that of soil porosity from an independent survey-based dataset, further confirming the credibility of the new product. According to this product, the transition regions in China show stronger seasonal variation of soil moisture than dry and wet regions, and drier regions have stronger inter-annual variability of soil moisture than wetter regions, particularly during transitional seasons(spring and autumn). The soil moisture product is accessible at the National Tibetan Plateau Data Center.展开更多
The information revolution has been one of the driving forces to the innovation in geography. However, environmental remote sensing, geographic information science and technology, and geocomputing, which once resided ...The information revolution has been one of the driving forces to the innovation in geography. However, environmental remote sensing, geographic information science and technology, and geocomputing, which once resided within the family of geography, are gradually moving close to information science but are alienated from geography. Therefore, it is necessary to reexamine the interactive convergence of geography and information science, and advance the disciplinary system of geographic science to accommodate the researches with information as subjects and methods. In this paper, we propose to reformulate the relationship between geographic science and information science with a new discipline, i.e., information geography, which not only refers to the geography of information but also a methodological system for studying geography using information science.This paper summarizes the background of information geography’s emergence, its definition, and the difference and similarities with other disciplinary concepts. The impact of information geography on geographic paradigm shift is also investigated from the ontological, epistemological, and methodological perspectives.展开更多
Ice avalanches are one of the most devastating mountain hazards,and can pose a great risk to the security of the surrounding area.Although ice avalanches have been widely observed in mountainous regions around the wor...Ice avalanches are one of the most devastating mountain hazards,and can pose a great risk to the security of the surrounding area.Although ice avalanches have been widely observed in mountainous regions around the world,only a few ice avalanche events have been studied comprehensively,due to the lack of available data.In this study,in response to the recent catastrophic rock-ice avalanche(7 February 2021)at Chamoli in the India Himalaya,we used high-resolution satellite images and found that this event was actually a glacier-rock landslide,where the collapse of the rock-ice body was caused by the sliding of the bedrock beneath the glacier,for which the source area and volume loss were about 2.89×10^(5) m^(2) and 2.46×10^(7) m^(3),respectively,corresponding to an average elevation change of about−85 m.Furthermore,visual analysis of the dense time-series satellite images shows that the overall downward sliding of the collapsed rock-ice body initiated around the summer of 2017,and thereafter exhibited clear seasonality(mainly in summer).Meteorological analysis reveals a strong rainfall anomaly in the initiation period of the sliding and a remarkable winter warming anomaly in the 40 days before the collapse.Comparisons of multi-temporal digital elevation models(DEMs)further suggest that the glacier geometry in the collapsed areas was likely changing(i.e.,accelerated surface thinning in the lower part of the glaciers and insignificant change in the upper part),which is consistent with the region-wide climate warming.Finally,by combining the above findings and a geomorphic analysis,we conclude that the rock-ice avalanche event was mainly caused by the joint effects of climate and weather changes acting on a steeply sloping and fracture-prone geological condition.The findings of this study provide new and valuable evidence for the study of slope/glacier instability at high altitudes.This study also highlights that,for the Himalaya and other high mountain ranges,there is an urgent need to identify the glaciers that have a high risk of ice avalanches.展开更多
Alpine grassland is the main ecosystem of the Tibetan Plateau(TP),thus accurate simulation of water and heat exchange in the grassland will significantly enhance the understanding of the land-atmosphere interaction pr...Alpine grassland is the main ecosystem of the Tibetan Plateau(TP),thus accurate simulation of water and heat exchange in the grassland will significantly enhance the understanding of the land-atmosphere interaction process on the TP.In this study,we assessed and improved the ensemble numerical simulations of the community Noah land surface model with multiparameterization options(Noah-MP)by using observations collected from four alpine grassland observation sites.The four observation sites belong to the upper Heihe River Basin Integrated Observatory Network located in the northeastern part of the TP.First,an ensemble of 1008 numerical simulation experiments,based on multiparameterization options of seven physical processes/variables in the Noah-MP,was carried out for the vegetation growing season.The Taylor skill score was then used to assess the model performance and select the optimal combination of parameterization options for a more exact simulation of the water and heat exchange in alpine grassland.The accuracy of Noah-MP simulation was further improved by introducing new parameterizations of thermal roughness length,soil hydraulic properties,and vertical root distribution.It was found that:(1)Simulation of water and heat exchange over alpine grassland in the growing season was mainly affected by the parameterizations of dynamic vegetation,canopy stomatal resistance,runoff and groundwater dynamics,and surface exchange coefficient for heat transfer.Selection of different parameterization options for these four physical processes/variables led to large differences in the simulation of water and heat fluxes.(2)The optimal combination of parameterization options selected in the current Noah-MP framework suffered from significant overestimation of sensible heat flux(H)and underestimation of soil moisture(θ)at all observation sites.(3)The overestimation of H was significantly improved by introducing a new parameterization of thermal roughness length.Furthermore,the underestimation ofθwas resolved by introducing a new parameterization of soil hydraulic properties that considered the organic matter effect and a new vertical distribution function for the vegetation root system.The results of this study provide an important reference for further improving the simulation of water and heat exchange by using the land surface model in alpine grassland.展开更多
Plate-like Fe-rich intermetallic phases directly influence the mechanical properties of recycled Al alloys;thus, many attempts have been made to modify the morphology of these phases. Through synchrotron X-ray imaging...Plate-like Fe-rich intermetallic phases directly influence the mechanical properties of recycled Al alloys;thus, many attempts have been made to modify the morphology of these phases. Through synchrotron X-ray imaging and electron microscopy, the underlying nucleation and growth mechanisms of Fe-rich phases during the solidification of Al-5 Ti-1 B-modified Al-2 Fe alloys were revealed in this study. The results showed that the Al-5 Ti-1 B grain refiner as well as the applied pressure both resulted in reduction of the size and number of primary Al_(3)Fe phases and promoted the formation of eutectic Al_(6)Fe phases.The tomography results demonstrated that Al-5 Ti-1 B changed the three-dimensional(3 D) morphology of primary Fe-rich phases from rod-like to branched plate-like, while a reduction in their thickness and size was also observed. This was attributed to the fact that Ti-containing solutes in the melts inhibit the diffusion of Fe atoms and the Al_(3)Fe twins produce re-entrant corner on the twin boundaries along the growth direction. Moreover, the TiB_(2) provides possible nucleation sites for Al_6Fe phases. The nucleation mechanism of Fe-rich phases is discussed in terms of experimental observations and crystallography calculations. The decrease in the lattice mismatch between TiB_(2) and Al_(6)Fe phases was suggested, which promoted the transformation of Al_(3)Fe to Al_(6)Fe phases.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.41930759,42325502)the West Light Foundation of the Chinese Academy of Sciences(Grant No.xbzg-zdsys-202215)+2 种基金the Chinese Academy Sciences Talents Program,National Cryosphere Desert Data Centerthe Qinghai Key Laboratory of Disaster Prevention(Grant No.QFZ-2021-Z02)2023 First Batch of Science and Technology Plan Projects of Lanzhou City(Grant No.2023-1-49)。
文摘Hydrological modeling,leveraging mathematical formulations to represent the hydrological cycle,is a pivotal tool in representing the spatiotemporal dynamics and distribution patterns inherent in hydrology.These models serve a dual purpose:they validate theoretical robustness and applicability via observational data and project future trends,thereby bridging the understanding and prediction of natural processes.In rapid advancements in computational methodologies and the continuous evolution of observational and experimental techniques,the development of numerical hydrological models based on physicallybased surface-subsurface process coupling have accelerated.Anchored in micro-scale conservation principles and physical equations,these models employ numerical techniques to integrate surface and subsurface hydrodynamics,thus replicating the macro-scale hydrological responses of watersheds.Numerical hydrological models have emerged as a leading and predominant trend in hydrological modeling due to their explicit representation of physical processes,heightened by their spatiotemporal resolution and reliance on interdisciplinary integration.This article focuses on the theoretical foundation of surface-subsurface numerical hydrological models.It includes a comparative and analytical discussion of leading numerical hydrological models,encompassing model architecture,numerical solution strategies,spatial representation,and coupling algorithms.Additionally,this paper contrasts these models with traditional hydrological models,thereby delineating the relative merits,drawbacks,and future directions of numerical hydrological modeling.
基金Supported by the National Natural Science Foundation of China(52109036,51709046,51539003,41761134090,41830752,and 42071033)Belt and Road Special Foundation of the State Key Laboratory of Hydrology–Water Resources and Hydraulic Engineering of Hohai University(2021490611)+1 种基金Open Foundation of Key Laboratory of Hydrometeorological Disaster Mechanism and Warning of Ministry of Water Resources(HYMED202203,HYMED202210)Lanzhou Institute of Arid Meteorology(IAM202119).
文摘Accurate quantification of soil moisture is essential to understand the land surface processes.Soil hydraulic properties influence water transport in soil and thus affect the estimation of soil moisture.However,some soil hydraulic properties are only observable at a few field sites.In this study,the effects of soil hydraulic properties on soil moisture estimation are investigated by using the one-dimensional(1-D)Richards equation at ELBARA,which is part of the Maqu monitoring network over the Tibetan Plateau(TP),China.Soil moisture assimilation experiments are then conducted with the unscented weighted ensemble Kalman filter(UWEnKF).The results show that the soil hydraulic properties significantly affect soil moisture simulation.Saturated soil hydraulic conductivity(Ksat)is optimized based on its observations in each soil layer with a genetic algorithm(GA,a widely used optimization method in hydrology),and the 1-D Richards equation performs well using the optimized values.If the range of Ksat for a complete soil profile is known for a particular soil texture(rather than for arbitrary layers within the horizon),optimized Ksat for each soil layer can be obtained by increasing the number of generations in GA,although this increases the computational cost of optimization.UWEnKF performs well with optimized Ksat,and improves the accuracy of soil moisture simulation more than that with calculated Ksat.Sometimes,better soil moisture estimation can be obtained by using optimized saturated volumetric soil moisture content Ksat.In summary,an accurate soil profile can be obtained by using soil moisture assimilation with optimized soil hydraulic properties.
基金supported by the Basic Science Center for Tibetan Plateau Earth System(BCTPES,NSFC project Grant Nos.41988101)the National Natural Science Foundation of China(Grant No.42101397)。
文摘The utilization of big Earth data has provided insights into the planet we inhabit in unprecedented dimensions and scales.Unraveling the concealed causal connections within intricate data holds paramount importance for attaining a profound comprehension of the Earth system.Statistical methods founded on correlation have predominated in Earth system science(ESS)for a long time.Nevertheless,correlation does not imply causation,especially when confronted with spurious correlations resulting from big data.Consequently,traditional correlation and regression methods are inadequate for addressing causation related problems in the Earth system.In recent years,propelled by advancements in causal theory and inference methods,particularly the maturity of causal discovery and causal graphical models,causal inference has demonstrated vigorous vitality in various research directions in the Earth system,such as regularities revealing,processes understanding,hypothesis testing,and physical models improving.This paper commences by delving into the origins,connotations,and development of causality,subsequently outlining the principal frameworks of causal inference and the commonly used methods in ESS.Additionally,it reviews the applications of causal inference in the main branches of the Earth system and summarizes the challenges and development directions of causal inference in ESS.In the big Earth data era,as an important method of big data analysis,causal inference,along with physical model and machine learning,can assist the paradigm transformation of ESS from a model-driven paradigm to a paradigm of integration of both mechanism and data.Looking forward,the establishment of a meticulously structured and normalized causal theory can act as a foundational cornerstone for fostering causal cognition in ESS and propel the leap from fragmented research towards a comprehensive understanding of the Earth system.
基金supported by the National Key Research and Development Program of China (Grant No. 2018YFA0605400)the Frontier Science Project of Chinese Academy of Sciences (Grant No. QYZDY-SSW-DQC011-03)+1 种基金the National Natural Science Foundation of China (Grant No. 91537210)the 13th Five-year Informatization Plan of Chinese Academy of Sciences (Grant No. XXH13505-06)。
文摘Soil moisture is an essential climate variable(ECV) concerned widely. Due to its high spatial variability, it is costly to measure soil moisture at tens of kilometers scale. In this study, a ten-year(2002–2011) daily soil moisture dataset at 0.25° spatial resolution for Chinese mainland was produced through assimilating the Advanced Microwave Scanning Radiometer for Earth Observing System(AMSR-E) brightness temperature(TB) data into a land surface model(LSM). The obtained soil moisture data was evaluated against soil moisture-measuring networks deployed in two wet areas and one dry area of the Tibetan Plateau.The results show that for the wet areas the accuracy of the soil moisture product obtained from the assimilation is considerably higher than that of both AMSR-E official soil moisture products and land surface simulation results, and for the dry area their accuracy is comparable to each other. The spatial pattern of the soil moisture from the new product is consistent with that of soil porosity from an independent survey-based dataset, further confirming the credibility of the new product. According to this product, the transition regions in China show stronger seasonal variation of soil moisture than dry and wet regions, and drier regions have stronger inter-annual variability of soil moisture than wetter regions, particularly during transitional seasons(spring and autumn). The soil moisture product is accessible at the National Tibetan Plateau Data Center.
文摘The information revolution has been one of the driving forces to the innovation in geography. However, environmental remote sensing, geographic information science and technology, and geocomputing, which once resided within the family of geography, are gradually moving close to information science but are alienated from geography. Therefore, it is necessary to reexamine the interactive convergence of geography and information science, and advance the disciplinary system of geographic science to accommodate the researches with information as subjects and methods. In this paper, we propose to reformulate the relationship between geographic science and information science with a new discipline, i.e., information geography, which not only refers to the geography of information but also a methodological system for studying geography using information science.This paper summarizes the background of information geography’s emergence, its definition, and the difference and similarities with other disciplinary concepts. The impact of information geography on geographic paradigm shift is also investigated from the ontological, epistemological, and methodological perspectives.
基金This work was supported by the National Natural Science Foundation of China(Grant Nos.41988101&42001381)the China Post-Doctoral Program for Innovative Talents(Grant No.BX20200343)+1 种基金the China Post-Doctoral Science Foundation(Grant No.2020M670480)The TanDEM-X data were provided as part of a science data project conducted by the German Aerospace Center(Grant No.NTI_BIST7136).
文摘Ice avalanches are one of the most devastating mountain hazards,and can pose a great risk to the security of the surrounding area.Although ice avalanches have been widely observed in mountainous regions around the world,only a few ice avalanche events have been studied comprehensively,due to the lack of available data.In this study,in response to the recent catastrophic rock-ice avalanche(7 February 2021)at Chamoli in the India Himalaya,we used high-resolution satellite images and found that this event was actually a glacier-rock landslide,where the collapse of the rock-ice body was caused by the sliding of the bedrock beneath the glacier,for which the source area and volume loss were about 2.89×10^(5) m^(2) and 2.46×10^(7) m^(3),respectively,corresponding to an average elevation change of about−85 m.Furthermore,visual analysis of the dense time-series satellite images shows that the overall downward sliding of the collapsed rock-ice body initiated around the summer of 2017,and thereafter exhibited clear seasonality(mainly in summer).Meteorological analysis reveals a strong rainfall anomaly in the initiation period of the sliding and a remarkable winter warming anomaly in the 40 days before the collapse.Comparisons of multi-temporal digital elevation models(DEMs)further suggest that the glacier geometry in the collapsed areas was likely changing(i.e.,accelerated surface thinning in the lower part of the glaciers and insignificant change in the upper part),which is consistent with the region-wide climate warming.Finally,by combining the above findings and a geomorphic analysis,we conclude that the rock-ice avalanche event was mainly caused by the joint effects of climate and weather changes acting on a steeply sloping and fracture-prone geological condition.The findings of this study provide new and valuable evidence for the study of slope/glacier instability at high altitudes.This study also highlights that,for the Himalaya and other high mountain ranges,there is an urgent need to identify the glaciers that have a high risk of ice avalanches.
基金supported by the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant Nos.XDA20100101,XDA20100103)。
文摘Alpine grassland is the main ecosystem of the Tibetan Plateau(TP),thus accurate simulation of water and heat exchange in the grassland will significantly enhance the understanding of the land-atmosphere interaction process on the TP.In this study,we assessed and improved the ensemble numerical simulations of the community Noah land surface model with multiparameterization options(Noah-MP)by using observations collected from four alpine grassland observation sites.The four observation sites belong to the upper Heihe River Basin Integrated Observatory Network located in the northeastern part of the TP.First,an ensemble of 1008 numerical simulation experiments,based on multiparameterization options of seven physical processes/variables in the Noah-MP,was carried out for the vegetation growing season.The Taylor skill score was then used to assess the model performance and select the optimal combination of parameterization options for a more exact simulation of the water and heat exchange in alpine grassland.The accuracy of Noah-MP simulation was further improved by introducing new parameterizations of thermal roughness length,soil hydraulic properties,and vertical root distribution.It was found that:(1)Simulation of water and heat exchange over alpine grassland in the growing season was mainly affected by the parameterizations of dynamic vegetation,canopy stomatal resistance,runoff and groundwater dynamics,and surface exchange coefficient for heat transfer.Selection of different parameterization options for these four physical processes/variables led to large differences in the simulation of water and heat fluxes.(2)The optimal combination of parameterization options selected in the current Noah-MP framework suffered from significant overestimation of sensible heat flux(H)and underestimation of soil moisture(θ)at all observation sites.(3)The overestimation of H was significantly improved by introducing a new parameterization of thermal roughness length.Furthermore,the underestimation ofθwas resolved by introducing a new parameterization of soil hydraulic properties that considered the organic matter effect and a new vertical distribution function for the vegetation root system.The results of this study provide an important reference for further improving the simulation of water and heat exchange by using the land surface model in alpine grassland.
基金supported by the Team Project Natural Science Foundation of Guangdong Province(2015A030312003)Basic and Applied Basic Foundation of Guangdong Province(2019A1515110270)+2 种基金Research start-up funds of DGUT(GC300501138)Scientific Research Foundation of Advanced Talents(Innovation Team)DGUT(No.KCYCXPT2016004 and No.TDQN2019005)Natural Science Foundation of China(52074131)。
文摘Plate-like Fe-rich intermetallic phases directly influence the mechanical properties of recycled Al alloys;thus, many attempts have been made to modify the morphology of these phases. Through synchrotron X-ray imaging and electron microscopy, the underlying nucleation and growth mechanisms of Fe-rich phases during the solidification of Al-5 Ti-1 B-modified Al-2 Fe alloys were revealed in this study. The results showed that the Al-5 Ti-1 B grain refiner as well as the applied pressure both resulted in reduction of the size and number of primary Al_(3)Fe phases and promoted the formation of eutectic Al_(6)Fe phases.The tomography results demonstrated that Al-5 Ti-1 B changed the three-dimensional(3 D) morphology of primary Fe-rich phases from rod-like to branched plate-like, while a reduction in their thickness and size was also observed. This was attributed to the fact that Ti-containing solutes in the melts inhibit the diffusion of Fe atoms and the Al_(3)Fe twins produce re-entrant corner on the twin boundaries along the growth direction. Moreover, the TiB_(2) provides possible nucleation sites for Al_6Fe phases. The nucleation mechanism of Fe-rich phases is discussed in terms of experimental observations and crystallography calculations. The decrease in the lattice mismatch between TiB_(2) and Al_(6)Fe phases was suggested, which promoted the transformation of Al_(3)Fe to Al_(6)Fe phases.