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Movement of lateral hyporheic flow between stream and groundwater

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Science China Earth Sciences 2017年第11期60卷 2033-2040页

作者： ZHANG Yu WANG JianLi YANG PingHeng XIE ShiYou School of Geographical Sciences Southwest UniversityChongqing Key Laboratory of Karst EnvironmentKey Laboratory of Eco-environments in Three Gorges ReservoirMinistry of EducationChongqing 400715China Field Scientific Observation&research base ofkarst eco-environments at nanchuan in chongqing Ministry of Land and ResourcesChongqing 408435China Key Laboratory of Shale Gas and Geoengineering Institute of Geology and GeophysicsChinese Academy of SciencesBeijing 100029China

The hyporbeic zone plays an important role in groundwater and stream water quality protection. To investigate the stream-groundwater interaction mechanisms in the lateral hyporheic zone, this study examined Ma＇an Creek in chongqing during the dry season from December 2015 to April 2016. The water level, water temperature, pH and CF concentration in the hyporheic zone and groundwater were monitored in situ. The sediment permeability coefficient, stable isotopes of hydrogen and oxygen and concentration of DOC were analyzed. The results show that the water level changes of hyporheic zone and the movement of hyporheic flow were influenced significantly by the permeability coefficient of sediment. The hyporheic flow approximately 10 cm from the stream bank was clearly affected by precipitation infiltration and evapotranspiration. During the study period, the groundwater recharged the stream, and the impact of groundwater on the hyporheic flow gradually decreased with the flow path. The hyporheic flow approximately 30 cm from the stream bank was still mainly affected by groundwater. Approximately 10-30 cm from the stream bank, the mixing of groundwater with precipitation and stream water intensified. Due to the sediment properties, moisture accumulated approximately 10 cm from the stream bank and drained into the stream via hyporheic flow, with potential impacts on stream water quality.

关键词： Hyporheic zone Lateral hyporheic flow Permeability coefficient Hydrogen and oxygen isotopes Ma'an Creek

Comparing the performances of WRF QPF and PERSIANN-CCS QPEs in karst flood simulation and forecasting by coupling the karst-Liuxihe model

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Frontiers of Earth Science 2022年第2期16卷 381-400页

作者： Ji LI Daoxian YUAN Yuchuan SUN Jianhong LI chongqing Jinfo Mountain karst ecosystem National Observation and research Station School of Geographical SciencesSouthwest UniversityChongqing 400715China Key Laboratory of karst Dynamics(MNR&Guangxi)Institute of karst Geology CAGSGuilin 541004China

Long-term rainfall data are crucial for flood simulations and forecasting in karst ***,in karst areas,there is often a lack of suitable precipitation data available to build distributed hydrological models to forecast karst *** precipitation forecasts(QPFs)and estimates(QPEs)could provide rational methods to acquire the available precipitation data for karst ***,coupling a physically based hydrological model with QPFs and QPEs could greatly enhance the performance and extend the lead time of flood forecasting in karst *** study served two main *** purpose was to compare the performance of the Weather research and Forecasting(WRF)QPFs with that of the Precipitation Estimations through Remotely Sensed Information based on the Artificial Neural Network-Cloud Classification System(PERSIANN-CCS)QPEs in rainfall forecasting in karst river *** other purpose was to test the feasibility and effective application of karst flood simulation and forecasting by coupling the WRF and PERSIANN models with the karst-Liuxihe *** rainfall forecasting results showed that the precipitation distributions of the 2 weather models were very similar to the observed rainfall ***,the precipitation amounts forecasted by WRF QPF were larger than those measured by the rain gauges,while the quantities forecasted by the PERSIANN-CCS QPEs were smaller.A postprocessing algorithm was proposed in this paper to correct the rainfall estimates produced by the two weather *** flood simulations achieved based on the postprocessed WRF QPF and PERSIANN-CCS QPEs coupled with the karst-Liuxihe model were much improved over previous *** particular,coupling the postprocessed WRF QPF with the karst-Liuxihe model could greatly extend the lead time of flood forecasting,and a maximum lead time of 96 h is adequate for flood warnings and emergency responses,which is extremely important in flood simulations and forecasting.

关键词： WRF QPF PERSIANN-CCS QPEs the karst-Liuxihe model flood simulation and forecasting karst river basin

The uncertainty analysis of the MODIS GPP product in global maize croplands

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Frontiers of Earth Science 2018年第4期12卷 739-749页

作者： Xiaojuan HUANG Mingguo MA Xufeng WANG Xuguang TANG Hong YANG chongqing Engineering research Center for Remote Sensing Big Data Application Southwest UniversityChongqing 400715China research base of karst eco-environments at nanchuan in chongqing Ministry of Natural ResourcesSchool of Geographical SciencesSouthwest UniversityChongqing 400715China Northwest Institute of eco-environment and Resources Chinese Academy of SciencesLanzhou 730000China Department of Geography and Environmental Science University of ReadingReading RG66ABUK

Gross primary productivity (GPP) is very important in the global carbon cycle. Currently, the newly released estimates of 8-day GPP at 500 m spatial resolution (Collection 6) are provided by the Moderate Resolution Imaging Spectroradiometer (MODIS) Land Science Team for the global land surface via the improved light use efficiency (LUE) model. However, few studies have evaluated its performance. In this study, the MODIS GPP products (GPPMOD) were compared with the observed GPP (GPPEC) values from site-level eddy covariance measurements over seven maize flux sites in different areas around the world. The results indicate that the annual GPPMOD was underestimated by 6%‒58% across sites. Nevertheless, after incorporating the parameters of the calibrated LUE, the measurements of meteorological variables and the reconstructed Fractional Photosynthetic Active Radiation (FPAR) into the GPPMOD algorithm in steps, the accuracies of GPPMOD estimates were improved greatly, albeit to varying degrees. The differences between the GPPMOD and the GPPEC were primarily due to the magnitude of LUE and FPAR. The underestimate of maize cropland LUE was a widespread problem which exerted the largest impact on the GPPMOD algorithm. In American and European sites, the performance of the FPAR exhibited distinct differences in capturing vegetation GPP during the growing season due to the canopy heterogeneity. In addition, at the DE-Kli site, the GPPMOD abruptly produced extreme low values during the growing season because of the contaminated FPAR from a continuous rainy season. After correcting the noise of the FPAR, the accuracy of the GPPMOD was improved by approximately 14%. Therefore, it is crucial to further improve the accuracy of global GPPMOD, especially for the maize crop ecosystem, to maintain food security and better understand global carbon cycle.

关键词： MODIS GPP eddy covariance maize cropland validation improvement

Future variation of land surface temperature in the Yangtze River Basinbasedon CMIP6 model

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International Journal of Digital Earth 2023年第1期16卷 2776-2796页

作者： Jinlian Liu Hanya Tang Fengqin Yan Shiwei Liu Xuguang Tang Zhi Ding Pujia Yu chongqing Jinfo Mountain karst ecosystem National Observation and research Station School of Geographical SciencesSouthwest UniversityChongqingPeople’s Republic of China State Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijingPeople’s Republic of China chongqing Key Laboratory of karst Environment School of Geographical SciencesSouthwest UniversityChongqingPeople’s Republic of China

In recent years,past changes in global and regional land surface temperatures(LST)have been well studied,however,future LST changes have been largely ignored owing to data *** this study,three climate variables of CMIP6,namely air temperature(AT),precipitation(Pre),and leaf area index(LAl),were spatially corrected using the Delta downscaling *** this basis,by combining MODIS LST,elevation,slope and aspect,a random forest(RF)model was built to calculate the LST from 2022 to *** absolute variability(AV)and Mann-Kendall(M-K)tests were used to quantitatively detect interannual and seasonal LST changes in different Shared Socioeconomic Pathways(SSPs)*** results showed that the AV value increased successively from SSP1-2.6 to SSP2-4.5 and then to *** with the base period(2003-2021),the increment in interannual,spring,summer and autumn LST during 2022-2100 was mainly between 1 and 2°℃under *** interannual and seasonal LST were spatially characterized by significant warming over large areas,and the increasing was the fastest under *** results indicate that,in the future,LST will increase further over large areas,especially in winter.

关键词： Temporal and spatial changes Delta downscaling Random forest Global warming

Multi-disciplinary approaches to water systems:introduction to the special column

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Frontiers of Earth Science 2020年第2期14卷 251-255页

作者： Steven RFASSNACHT Mingguo MA ESS-Watershed Science Colorado State UniversityFort CollinsCO 80523-1476USA Cooperative Institute for research in the Atmosphere Fort CollinsCO 80523-1375USA Natural Resources ecology Laboratory Fort CollinsCO 80523-1499USA research base of karst eco-environments at nanchuan in chongqing Ministry of Nature ResourcesSchool of Geographical SciencesSouthwest UniversityChongqing 400715China

1 Introduction As the human population grows,the livelihoods and well-being of a significant portion of humanity will depend even more on the ability of freshwater ecosystems to provide essential services(Vörösmarty et al.,2010),which will require the maintenance of biodiversity in these freshwater systems(Dudgeon et al.,2006).There are many competing demands on the available water resources,such as potable water,fish and wildlife habitat,agriculture,industrial use,and recreation,that are driven by different sectors;even within a specific sector there can be diverging *** example,water management of the Upper Arkansas River in Colorado has been mandated by the 1949 Arkansas River Compact between the US states of Colorado and Kansas which has led to stream-aquifer issues(Taylor and Luckey,1974),water transfers from agriculture to urban(Howe et al.,1990),and competing recreational uses(Wollmuth et al.,1985;Arkansas Basin Roundtable,2017).The recent Upper Arkansas Voluntary Flow Management Program tries to balance many users,including recreation by kayakers and rafters who want to maintain streamflow(at the Wellsville gauge)at or greater than 20 m3/s as well as anglers who want lower flows in the range of 7 to 11 m3/s to maintain fish habitat(Arkansas Basin Roundtable,2017).

关键词： Upper habitat maintain

Heterogeneous sea-level rises along coastal zones and small islands

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Science Bulletin 2019年第11期64卷 748-755页

作者： Guoshuai Li Xin Li Tandong Yao Tao Che Hong Yang Mingguo Ma Haipeng Zhao Xiaoduo Pan Institute of Tibetan Plateau research Chinese Academy of SciencesBeijing 100101China Center for Excellence in Tibetan Plateau Earth Sciences Chinese Academy of SciencesBeijing 100101China Northwest Institute of eco-Environment and Resources Chinese Academy of SciencesLanzhou 730000China Dapartment of Geography and Environmental Science University of ReadingWhiteknightsReading RC6 6ABUK research base of karst eco-environments at nanchuan in chongqing Ministry of Natural ResourcesSchool of Geographical SciencesSouthwest UniversityChongqing 400715China Department of Earth and Environmental Systems Indiana State UniversityTerre HauteIN 47809USA

Coastal zones and many small islands are highly susceptible to sea-level rise(SLR). Coastal zones have a large exposed population and integrated high-value assets, and islands provide diverse ecosystem services to millions of people worldwide. The coastal zones and small islands affected by SLR are likely to suffer from submergence, flooding and erosion in the future. However, very few studies have addressed the heterogeneity in SLR changes and the potential risk to coastal zones and small islands. Here we used the mean sea level(MSL) derived from satellite altimetry data to analyse the trends and accelerations of SLRs along global coastal zones and small islands. We found that except for the Antarctic coastal zone, the annual MSL within 50 km of the coasts presented an increasing trend of 3.09 ± 0.13 mm a^-1 but a decreasing acceleration of -0.02 ± 0.02 mm a^-2 from 1993 to 2017. The highest coastal MSL trend of3.85 ± 0.60 mm a^-1 appeared in Oceania, and the lowest trend of 2.32 ± 0.37 mm a^-1 occured in North America. Africa, North America and South America showed acceleration trends, and Eurasia, Australia and Oceania had deceleration trends. Further, MSLs around global small islands reflected an increasing trend with a rate of 3.01 ± 0.16 mm a^-1 but a negative acceleration of -0.02 ± 0.02 mm a^-2. Regional heterogeneity in the trends and accelerations of MSLs along the coasts and small islands suggests that stakeholders should take discriminating precautions to cope with future disadvantageous impacts of the SLR.

关键词： Sea-level rise Coastal zones Small islands Heterogeneity

Uncertainty in water resources:introduction to the specia column

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Frontiers of Earth Science 2018年第4期12卷 649-652页

作者： S.R.FASSNACHT R.W.WEBB M.MA ESS-Watershed Science Colorado State UniversityFort CollinsCO 80523-1476USA Cooperative Institute for research in the Atmosphere Fort CollinsCO 80523-1375USA Natural Resources ecology Laboratory Fort CollinsCO 80523-1499USA Institute of Arctic and Alpine research University of Colorado BoulderBoulderCO 80309-0450USA now with Department of Civil Constructionand Environmental EngineeringUniversity of New MexicoAlbuquerqueNM 87131USA research base of karst eco-environments at Nanehuan in chongqing Ministry of Nature ResourcesSchool of Geographical SciencesSouthwest UniversityChongqing 400715China

Uncertainty is a defining problem in the understanding of earth systems, especially for water resources (Guillaume et al., 2017). The word “uncertainty” can have a variety of meanings (Montanari, 2007; Beven, 2016). Typically, we only understand processes in the confines of laboratory experiments, on a very fine scale in the field, or in vague generalities. This is often the case because the processes are not well understood, or there is not enough data at the appropriate resolution or over a sufficient extent. Scaling issues occur at both spatial and temporal resolution leaving the scientist with imperfect knowledge of a system and poorly defined errors when evaluating it.

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Internet of Things to network smart devices for ecosystem monitoring

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Science Bulletin 2019年第17期64卷 1234-1245页

作者： Xin Li Ning Zhao Rui Jin Shaomin Liu Xiaomin Sun Xuefa Wen Dongxiu Wu Yan Zhou Jianwen Guo Shiping Chen Ziwei Xu Mingguo Ma Tianming Wang Yonghua Qu Xinwei Wang Fangming Wu Yuke Zhou Institute of Tibetan Plateau research Chinese Academy of Sciences Beijing 100101 China State Key Laboratory of Remote Sensing Science Faculty of Geographical Science Beijing Normal University Beijing 100875 China State Key Laboratory of Remote Sensing Science Institute of Remote Sensing and Digital Earth Chinese Academy o f Sciences Beijing 100101 China Center for Excellence in Tibetan Plateau Earth Sciences Chinese Academy o f Sciences Beijing 100101 China Key Laboratory of Remote Sensing of Gansu Province Heihe Remote Sensing Experimental Research Station Cold and Arid Regions Environmental and Engineering Research Institute Chinese Academy of Sciences Lanzhou 730000 China State Key Laboratory of Earth Surface Processes and Resource ecology Faculty o f Geographical Science Beijing Normal University Beijing 100875 China Key Laboratory of ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing 100101 China State Key Laboratory of Vegetation and Environmental Change Institute of Botany Chinese Academy of Sciences Beijing 100093 China Optoelectronics System Laboratory Institute of Semiconductors Chinese Academy of Sciences Beijing 100083 China research base of karst eco-environments at nanchuan in chongqing Ministry of Nature Resources School of Geographical Sciences Southwest University Chongqing 400715 China Ministry of Education Key Laboratory for Biodiversity Science and Engineering Monitoring and Research Center for Amur Tigers and Amur Leopards National Forestry and Grassland Administration & College of Life Sciences Beijing Normal University Beijing 100875 China

Smart, real-time, low-cost, and distributed ecosystem monitoring is essential for understanding and managing rapidly changing ecosystems. However, new techniques in the big data era have rarely been introduced into operational ecosystem monitoring, particularly for fragile ecosystems in remote *** introduce the Internet of Things(IoT) techniques to establish a prototype ecosystem monitoring system by developing innovative smart devices and using IoT technologies for ecosystem monitoring in isolated environments. The developed smart devices include four categories: large-scale and nonintrusive instruments to measure evapotranspiration and soil moisture, in situ observing systems for CO2 and d13 C associated with soil respiration, portable and distributed devices for monitoring vegetation variables, and Bi-CMOS cameras and pressure trigger sensors for terrestrial vertebrate monitoring. These new devices outperform conventional devices and are connected to each other via wireless communication networks. The breakthroughs in the ecosystem monitoring IoT include new data loggers and longdistance wireless sensor network technology that supports the rapid transmission of data from devices to wireless networks. The applicability of this ecosystem monitoring IoT is verified in three fragile ecosystems, including a karst rocky desertification area, the National Park for Amur Tigers, and the oasis-desert ecotone in China. By integrating these devices and technologies with an ecosystem monitoring information system, a seamless data acquisition, transmission, processing, and application IoT is created. The establishment of this ecosystem monitoring IoT will serve as a new paradigm for ecosystem monitoring and therefore provide a platform for ecosystem management and decision making in the era of big data.

关键词： ecosystem monitoring Fragile ecosystem Internet of Things Wireless sensor network Smart device

Human activity and climate change triggered the expansion of rocky desertification in the karst areas of Southwestern China

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Science China Earth Sciences 2021年第10期64卷 1761-1773页

作者： Chaojun CHEN Daoxian YUAN Hai CHENG Tsailuen YU Chuanchou SHEN RLawrence EDWARDS Yao WU Siya XIAO Jian ZHANG Tao WANG Ran HUANG Ziqi LIU Tingyong LI Junyun LI chongqing Key Laboratory of karst Environment School of Geographical SciencesSouthwest UniversityChongqing 400715China Key Laboratory of karst Dynamics MNRGuangxiInstitute of Karst GeologyChinese Academy of Geological SciencesGuilin 541004China Yunnan Key Laboratory of Plateau Geographical Processes&Environmental Changes Faculty of GeographyYunnan Normal UniversityKunming 650500China Institute of Global Environmental Change Xi’an Jiaotong UniversityXi’an 710049China High-precision Mass Spectrometry and Environment Change Laboratory(HISPEC) Department of GeosciencesTaiwan UniversityTaipei 10617China research Center for Future Earth Taiwan UniversityTaipei 10617China Global Change research Center Taiwan UniversityTaipei 10617China Department of Earth Sciences University of MinnesotaMinneapolisMN 55455USA Environnements et Paléoenvironnements Océaniques et Continentaux(EPOC) UMR CNRS 5805Universitéde BordeauxPessac 33600France School of karst Science Guizhou Normal UniversityGuiyang 550001China

It is conducive to the sustainable development of human beings in karst regions to research the mechanism of karst rocky desertification(KRD)*** the large-scale KRD in southwestern China is caused by climate change or human activities is still *** this study,the evolution of the KRD in southwestern China over the past 2000 years was reconstructed through the high-precisionδ^(13)C record of stalagmites from Shijiangjun(SJJ)Cave,Guizhou Province,***δ^(13)C of the stalagmites from SJJ Cave exhibited heavy values from the Medieval Warm Period(MWP)to the Little Ice Age(LIA).Furthermore,theδ^(13)C records of other stalagmites and tufa from southwestern China also showed the same significant heavy *** the stalagmiteδ^(13)C could record the change of ecological environment,it indicated that the consistent change of the stalagmitesδ^(13)C may record the process of KRD expansion in the karst regions of southwestern *** the MWP,the stronger Asian summer monsoon and the northward movement of the rain belt led to a dry period in southwestern China and a wet period in northern *** contrast,it was wet in southwestern China and dry in northern China during the *** addition,after the Jing-Kang event(JK event,AD1127)occurred at the end of the Northern Song dynasty,the political and economic center of China migrated to southern China for the first time,which changed the population distribution pattern of larger population in the north and smaller population in the ***,the expansion of KRD in southwestern China was exacerbated in the MWP due to the change of climate in southwestern China,the migration of a large number of people,wars,the large-scale reclamation of arable land,and the cultivation of large areas of crops.

关键词： karst rocky desertification Jing-Kang event Stalagmiteδ13C record Medieval Warm Period Little Ice Age