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An accurate and robust method for the extraction of glacial lakes is critical to effective management of these natural water resources. Conventional methods often have limitations in terms of low spectral contrast and heterogeneous backgrounds in an image. This study presents a robust and automated method for the yearly mapping of glacial lake over a large scale, which took advantage of the complementarity between the modified normalized difference water index (MNDWI) and the nonlocal active contour model, required only local homogeneity in reflectance features of lake. The cloud computing approach with the Google Earth Engine (GEE) platform was used to process the intensive amount of Landsat 8 images from 2015 (344 path\u002Frows and approximately 7504 scenes). The experimental results were validated by very high resolution images from Chinese GaoFen-1 (GF-1) panchromatic multi-spectral (PMS) and appeared a general good agreement. This is the first time that information regarding the spatial distribution of glacial lakes over the HMA has been derived automatically within quite a short period of time. By integrating it with the relevant indices, it can also be applied to detect other land cover types such as snow or vegetation with improved accuracy.",{"EN":198,"VI":199},"An automated method for glacial lake mapping in High Mountain Asia using Landsat 8 imagery","Phương pháp tự động lập bản đồ hồ băng tại vùng núi cao châu Á bằng ảnh viễn thám Landsat 8",{"VOID":201},"Arendt A, Bolch T, Cogley JG, et al. (2015) Randolph Glacier Inventory–A dataset of global glacier outlines: Version 5.0. GLIMS Technical Report. pp 3–25. (https:\u002F\u002Fwww.glims.org\u002FRGI\u002F00_rgi50_TechnicalNote.pdf, accessed on 2015-07)\nBhardwaj A, Singh MK, Joshi PK, et al. (2015) A lake detection algorithm (LDA) using Landsat 8 data: A comparative approach in glacial environment. International Journal of Applied Earth Observation & Geoinformation 38: 150–163. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.jag.2015.01.004\nDong JW, Xiao X, Kou W, et al. (2015) Tracking the dynamics of paddy rice planting area in 1986–2010 through time series Landsat images and phenology-based algorithms. Remote Sensing of Environment 160(160): 99–113. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.rse.2015.01.004\nFeyisa GL, Meilby H, Fensholt R, et al. (2014) Automated Water Extraction Index: A new technique for surface water mapping using Landsat imagery. Remote Sensing of Environment 140(1): 23–35. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.rse.2013.08.029\nFisher A, Flood N, Danaher T (2016) Comparing Landsat water index methods for automated water classification in eastern Australia. Remote Sensing of Environment 175: 167–182. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.rse.2015.12.055\nFujita K, Sakai A, Nuimura T, et al. (2009) Recent changes in Imja Glacial Lake and its damming moraine in the Nepal Himalaya revealed by in situ surveys and multi-temporal ASTER imagery. Environmental Research Letters 4(4): 940–941. https:\u002F\u002Fdoi.org\u002F10.1088\u002F1748-9326\u002F4\u002F4\u002F045205\nGorelick N, Hancher M, Dixon M, et al. (2017) Google Earth Engine: Planetary-scale geospatial analysis for everyone. Remote Sensing of Environment 202: 18–27. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.rse.2017.06.031\nJi L, Zhang L, Wylie B (2009) Analysis of dynamic thresholds for the normalized difference water index. Photogrammetric Engineering & Remote Sensing 75(11): 1307–1317. https:\u002F\u002Fdoi.org\u002F10.14358\u002Fpers.75.11.1307\nJiang H, Feng M, Zhu Y, et al. (2014) An automated method for extracting rivers and lakes from Landsat imagery. Remote Sensing 6(6): 5067–5089. https:\u002F\u002Fdoi.org\u002F10.3390\u002Frs6065067\nJung M, Peyré G, Cohen LD (2012) Non-local active contours. SIAM Journal on Imaging Sciences 5(3): 255–266. https:\u002F\u002Fdoi.org\u002F10.1007\u002F978-3-642-24785-9_22\nKlein I, Dietz AJ, Gessner U, et al. (2014) Evaluation of seasonal water body extents in Central Asia over the past 27 years derived from medium-resolution remote sensing data. International Journal of Applied Earth Observation & Geoinformation 26(2): 335–349. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.jag.2013.08.004\nLankton S, Tannenbaum A (2008) Localizing region-based active contours. IEEE Transactions on Image Processing 17(11): 2029–2039. https:\u002F\u002Fdoi.org\u002F10.1109\u002Ftip.2008.2004611\nLi C, Kao CY, Gore JC, et al. (2008) Minimization of region-scalable fitting energy for image segmentation. IEEE Transactions on Image Processing 17(10): 1940–1949. https:\u002F\u002Fdoi.org\u002F10.1109\u002Ftip.2008.2002304\nLi J, Sheng YW (2012) An automated scheme for glacial lake dynamics mapping using Landsat imagery and digital elevation models: A case study in the Himalayas. International Journal of Remote Sensing 33(16): 5194–5213. https:\u002F\u002Fdoi.org\u002F10.1080\u002F01431161.2012.657370\nMcfeeters SK (1996) The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features. International Journal of Remote Sensing 17(7): 1425–1432. https:\u002F\u002Fdoi.org\u002F10.1080\u002F01431169608948714\nMergili M, Müller JP, Schneider JF (2013) Spatio-temporal development of high-mountain lakes in the headwaters of the Amu Darya River (Central Asia). Global & Planetary Change 107(5): 13–24. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.gloplacha.2013.04.001\nMaiersperger TK, Scaramuzza PL, Leigh L, et al. (2013) Characterizing LEDAPS surface reflectance products by comparisons with AERONET, field spectrometer, and MODIS data. Remote Sensing of Environment 136:1–13. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.rse.2013.04.007\nMasek JG, Vermote EF, Saleous NE, et al. (2006) A Landsat surface reflectance dataset for North America, 1990-2000. IEEE Geoscience & Remote Sensing Letters 3(1):68–72. https:\u002F\u002Fdoi.org\u002F10.1109\u002Flgrs.2005.857030\nHansen MC, Potapov PV, Moore R, et al. (2014) High-resolution global maps of 21st-century forest cover change. Science 342(6160): 850–853. https:\u002F\u002Fdoi.org\u002F10.1126\u002Fscience.1244693\nNie Y, Sheng YW, Liu Q, et al. (2017) A regional-scale assessment of Himalayan glacial lake changes using satellite observations from 1990 to 2015. Remote Sensing of Environment 189: 1–13. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.rse.2016.11.008\nNASA (2016) Landsat 7 science data users handbook. pp 9-17. (http:\u002F\u002Flandsathandbook.gsfc.nasa.gov\u002Forbit_coverage\u002Fprog_sect 5_2.html, accessed on 2016-11-16)\nPatel NN, Angiuli E, Gamba P, et al. (2015) Multitemporal settlement and population mapping from Landsat using Google Earth Engine. International Journal of Applied Earth Observation & Geoinformation 35 (Part B):199–208. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.jag.2014.09.005\nPekel JF, Cottam A, Gorelick N, et al. (2016) High-resolution mapping of global surface water and its long-term changes. Nature 540(7633): 418–422. https:\u002F\u002Fdoi.org\u002F10.1038\u002Fnature20584\nQiu J (2008) China: The third pole. Nature 454(7203): 393–396. https:\u002F\u002Fdoi.org\u002F10.1038\u002F454393a\nRodríguez E, Morris CS, Belz JE (2006) A global assessment of the SRTM performance. Photogrammetric Engineering & Remote Sensing 72(3): 249–260. https:\u002F\u002Fdoi.org\u002F10.14358\u002Fpers.72.3.249\nRoy DP, Wulder MA, Loveland TR, et al. (2014) Landsat-8: Science and product vision for terrestrial global change research. Remote Sensing of Environment 145: 154–172. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.rse.2014.02.001\nRyu JH, Won JS, Min KD (2002) Waterline extraction from Landsat TM data in a tidal flat: A case study in Gomso Bay, Korea. Remote Sensing of Environment 83(3): 442–456. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fs0034-4257(02)00059-7\nSalerno F, Thakuri S, Agata CD, et al. (2012) Glacial lake distribution in the Mount Everest region: Uncertainty of measurement and conditions of formation. Global & Planetary Changes 92-93(1): 30–39. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.gloplacha.2012.04.001\nTian BS, Li Z, Zhang MM, et al. (2017) Mapping thermokarst lakes on the Qinghai–Tibet Plateau using nonlocal active contours in Chinese GaoFen-2 multispectral imagery. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 10(5): 1687–1700. https:\u002F\u002Fdoi.org\u002F10.1109\u002Fjstars.2017.2666787\nTulbure MG, Broich M (2013) Spatiotemporal dynamic of surface water bodies using Landsat time-series data from 1999 to 2011. ISPRS Journal of Photogrammetry & Remote Sensing 79(330): 44–52. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.isprsjprs.2013.01.010\nWang W, Xiang Y, Gao Y, et al. (2015) Rapid expansion of glacial lakes caused by climate and glacier retreat in the Central Himalayas. Hydrological Processes 29(6): 859–874. https:\u002F\u002Fdoi.org\u002F10.1002\u002Fhyp.10199\nWang X, Ding Y, Liu S, et al. (2013) Changes of glacial lakes and implications in Tian Shan, central Asia, based on remote sensing data from 1990 to 2010. Environmental Research Letters 8(4): 575–591. https:\u002F\u002Fdoi.org\u002F10.1088\u002F1748-9326\u002F8\u002F4\u002F044052\nWang X, Chai KG, Liu SY, et al. 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(2012) Different glacier status with atmospheric circulations in Tibetan Plateau and surroundings. Nature Climate Change 2(9): 663–667. https:\u002F\u002Fdoi.org\u002F10.1038\u002Fnclimate1580\nZhang GQ, Yao TD, Xie H, et al. (2015) An inventory of glacial lakes in the Third Pole region and their changes in response to global warming. Global & Planetary Change 131: 148–157. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.gloplacha.2015.05.013\nZhang GQ, Li JL, Zheng GX (2017) Lake-area mapping in the Tibetan Plateau: an evaluation of data and methods. International Journal of Remote Sensing 38 (3):742–772. https:\u002F\u002Fdoi.org\u002F10.1080\u002F01431161.2016.1271478\nZhang K, Song H, Zhang L (2010) Active contours driven by local image fitting energy. Pattern Recognition 43(4): 1199–1206. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.patcog.2009.10.010\nZhu Z, Wang S, Woodcock CE (2015) Improvement and expansion of the Fmask algorithm: cloud, cloud shadow, and snow detection for Landsats 4-7, 8, and Sentinel 2 images. Remote Sensing of Environment 159: 269–277. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.rse.2014.12.014\nZhu Z, Woodcock CE (2012) Object-based cloud and cloud shadow detection in Landsat imagery. Remote Sensing of Environment 118 (6):83–94. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.rse.2011.10.028",{"VOID":203},"10.1007\u002Fs11629-017-4518-5","PUBLICATION","VERIFIED","2024-12-10T13:46:01.872+00:00","Auto Verify",[209],"VI","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs11629-017-4518-5",[212,228,260],{"id":213,"sortIndex":23,"researcher":22,"roles":214,"affiliations":216,"properties":225,"displayName":227,"givenName":22,"familyName":22},"ac2eb70b-6890-4220-a468-3273b34dc200",[215],"AUTHOR",[217],{"id":218,"sortIndex":23,"affiliation":219,"properties":22},"7e33845e-76cd-4de0-99a0-ee2260f9f8f8",{"id":218,"createTime":22,"updateTime":22,"relativeEntities":220,"slug":22,"properties":221,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":224,"statistic":22},[],{"title":222},{"VI":223},"Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, China",[],{"title":226},{"VI":227},"Mei-mei 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the first impoundment of the Three Gorges Reservoir (TGR) in China in 2003, more than 5000 landslides including potential landslides were identified. In this paper, a deep-seated active landslide in TGR area was analyzed. Fourteen years’ monitoring data and field investigations from 2006 to 2020 were used to analyze the deformation characteristics, influencing factors, and meteohydrological thresholds. The landslide showed a none-overall periodic movement pattern featuring acceleration during long-duration rainfall and rapid transition to constant creep after rainfall events. Two secondary sliding masses, No. 1 and No. 2, were defined via field investigation. The reservoir has no impact on the deformation whereas long-duration-low-intensity rainfall is the main factor. At present, the cumulative displacements of the main sliding mass range from 0.9 to 3.2 m, and the deformation during the rainy season is gradually increasing. The boundary of this landslide was formed, and the boundary of No. 2 sliding mass became obvious. The probability of the failure of sliding mass No. 2 is very high under the conditions of continuous rainfall. The 15-day antecedent rainfall combined with 4-day cumulative rainfall could be the rainfall threshold which could be associated with the groundwater level S1 of 294 m above sea level for forecasting large deformation of Tanjiawan landslide.",{"EN":347},"Deformation characteristics and thresholds of the Tanjiawan landslide in the Three Gorges Reservoir Area, China",{"VOID":349},"[\"367812313250877602\"]",{"VOID":351},"Brunetti MT, Peruccacci S, Rossi M, et al. (2010) Rainfall thresholds for the possible occurrence of landslides in Italy. Nat Hazards Earth Syst Sci 10(3): 447–458. https:\u002F\u002Fdoi.org\u002F10.5194\u002Fnhess-10-447-2010\nCaracciolo D, Arnone E, Conti FL, et al. (2017) Exploiting historical rainfall and landslide data in a spatial database for the derivation of critical rainfall thresholds. Environ Earth Sci 76(5): 222. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs12665-017-6545-5\nChleborad AF, Baum RL, Godt JW, et al. 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(2014) Economic benefit assessment of the geo-hazard monitoring and warning engineering system in the Three Gorges Reservoir area: a case study of the landslide in Zigui. Nat Hazards 75(2): 219–231. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs11069-014-1112-9\nZangerl C, Eberhardt E, Perzlmaier S (2010) Kinematic behaviour and velocity characteristics of a complex deep-seated crystalline rockslide system in relation to its interaction with a dam reservoir. Eng Geol 112(1):53–67. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.enggeo.2010.01.001\nZhang FL, Deng ML, Zhou Jian, et al. (2021) Basic deformation characteristics and mechanism of Tanjiawan landslide in the Three Gorges Reservoir Area. J Yangtze River Sci Res Inst 38(1): 78–83. (In Chinese). https:\u002F\u002Fdoi.org\u002F10.11988\u002Fckyyb.20191255\nZhang S, Xu Q Hu ZM et al. (2016) Effects of rainwater softening on red mudstone of deep-seated landslide, Southwest China. Eng Geol 204: 1–13. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.enggeo.2016.01.013",{"VOID":353},"10.1007\u002Fs11629-021-6979-9","2024-06-25T11:15:57.260+00:00","https:\u002F\u002Flink.springer.com\u002F10.1007\u002Fs11629-021-6979-9",[357,390,410,430,451,467,488],{"id":358,"sortIndex":23,"researcher":22,"roles":359,"affiliations":360,"properties":385,"displayName":387,"givenName":22,"familyName":22},"3b1e4a3b-11f6-4a6e-862c-d865f00d3432",[215],[361,369,377],{"id":362,"sortIndex":23,"affiliation":363,"properties":22},"c491452c-9e40-4892-9f88-9b32d3f0ef35",{"id":362,"createTime":22,"updateTime":22,"relativeEntities":364,"slug":22,"properties":365,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":368,"statistic":22},[],{"title":366},{"VI":367},"Hubei Geological Disaster Prevention and Control Engineering Technology Research Center, China Three Gorges University, Yichang, 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technologies have been necessary for improving fruit quality and productivity of citrus, labor-saving and orchard conservation on steep slope lands since aging of growers and decrease in the number of successors is remarkable in mountain areas of southwestern Japan. The purpose of this paper is to introduce new technologies for improving citrus production that have been developed in recent years. A new fruit quality control system using drip irrigation and liquid fertilization technique combined with year-round plastic mulching was developed, and it enables high quality and stable citrus fruit production. Water and\u002For nutrient solution is automatically supplied through drip tubes that are laid under the mulching sheets to give adequate water stress, so as to improve sugar and acid content of fruit. A new transportation system for steep sloping citrus orchards, which is a combination of the monorail system and contour narrow paths, was suggested. A small walking cultivator was developed to explain the procedure of narrow path excavation. After introducing the narrow path, working hours for fertilizer and chemical herbicide application were reduced. Disaster prevention mapping of citrus orchards on slope lands was developed based on computer-aided seepage estimation and topographic data. The mapping can show zones of both ascending flow and descending flow of underground water during heavy rains in citrus orchards. The mapping is considered to be effective for the management of orchards and prevention of erosion on slope lands.",{"EN":574},"New technologies and systems for high quality citrus fruit production, labor-saving and orchard construction in mountain areas of Japan",{"VOID":576},"[\"13633877567404726801\"]",{"VOID":578},"Kawamoto, O., Shimazaki, S., Yoshisako, H. and Yoshimura, A. 2003. Disaster prevention mapping system and high functional farm path to conserve slope orchards. In: Technical documents on citrus orchards conservation on slope land. National Agricultural Research Center for Western Region (Zentsuji, Kagawa) 13–19\nMorinaga, K., Yoshikawa, H., Nakao, S. and Muramatsu, N. 2002. Standard amounts of fertilizer and water, and some problems in the drip irrigation and fertilizing system with year round plastic mulching in Satsuma mandarin. Journal of Japan Society of Horticulture Science 71: 105\nMorinaga, K., Yoshikawa, H., Nakao, S., Muramatsu, N. and Hasegawa, Y. 2004a. Novel system for high quality and stable fruit production of Satsuma mandarin using drip irrigation and liquid fertilization system with year round plastic mulching. Horticulture Research in Japan 3 (1): 45–49\nMorinaga, K., Yoshikawa, H., Nakao, S., Sekino, K., Muramatsu, N. and Hasegawa, Y. 2004b. Effects of drip irrigation and liquid fertilization system with year round plastic mulching on fruit production of Satsuma mandarin. Horticulture Research in Japan 3 (1) 33–37\nSumikawa, O., Tanaka, H., Nakao, S., Inooku, K. and Miyazaki, M. 2000. Development of computer aided farm path designing system for sloping citrus orchards. Proceedings of 14 th Memorial CIGR (Commission Internationale du Genie Rural) Congress (Tsukuba, Japan). pp:1086–1096\nSumikawa, O., Miyazaki, M., Inooku, K., Okado, A. and Tanaka, H. 2002. Improvement of farm work environment of steep sloping orchard — Narrow paths excavation by a walking tractor. In: ISMAB (International Symposium on Machinery and Mechatronics for Agriculture and Bio-systems Engineering) 2002, Taiwan. pp: 337–343\nYoshikawa-Yamanishi, H., Nakao, S. and Hasegawa, Y. 2000a. Year round plastic sheet mulching of Satsuma mandarin cultured in open field for the production of high quality fruits. Journal of Japan Society of Horticulture Science 69(2): 279\nYoshikawa-Yamanishi, H., Nakao, S. and Hasegawa, Y. 2000b. Drip irrigation system under year-round plastic sheet mulch to improve the quality of Satsuma mandarin (Citrus unshiu Marc.) fruits. International Citrus Congress in USA. Pp: 278.\nYoshikawa-Yamanishi, H., Nakao, S., Hasegawa, Y. and Morinaga, K. 2001. Effect of low precipitation during summer season on the quality of Satsuma mandarin fruit cultured by fertigation method with drip irrigation under year round plastic sheet mulching. 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in the 1930s, two relatively large earthquakes (Kosout, magnitude 6.8, and Talarrud, magnitude 5.8) shook the eastern Mazandaran, northern Iran. Despite the historical and instrumental seismic activity of the eastern region of Mazandaran, little is known about the status of seismotectonics and consequences of these earthquakes. This paper presents a compilation of available data from early reports of these earthquakes with new structural, geomorphic and local data on the effects of this earthquake, especially co-seismic landslides and liquefaction, to assess the seismotectonics and probable causative faults of the earthquakes. It is proposed that the close times of occurrence of two earthquakes might be due to local loading or triggering effect of the first earthquake on the second one. Like many other instrumental earthquakes in the Central Alborz, it is difficult to find the exact causative faults of important earthquakes, however the Qadikola, Chachkam or North Alborz Fault have the potential of producing Kosout earthquake and the Lalehband fault is more promising for Talarrud earthquake. Additionally, the structural complexity of the area is also discussed in the form of a hybrid tectonic model. In this model, the boundary zone of thick-skinned and active thin-skinned domains has more structural complexity than outer portions. Konim-Badeleh Shahvar pop-up structure is bounded by major faults with thick-skinned deformation style. The role of older inherited fault structures and their interaction with low-slope Neogene thrusts driven from north to south by crustal tectonics and deformation is discussed. Co-seismic landslides and rock falls have great potential to be investigated in the Alborz Range for identification of prehistoric earthquakes.",{"EN":770},"Seismotectonics and consequences of the 1930s large earthquakes in eastern Mazandaran, north of Iran",{"VOID":772},"[]",{"VOID":774},"Aghanabati A (2004) Geology of Iran. Geological survey of Iran. (In Persian).\nAbbassi MR (2007) Active Tectonics And Deformation Pattern Of The Central-East Alborz (Iran). 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Pure Appl Geophys 171(7): 1219–1236. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs00024-013-0711-9",{"VOID":776},"10.1007\u002Fs11629-021-6958-1","2024-06-26T12:03:06.468+00:00","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs11629-021-6958-1",[780,795,808],{"id":781,"sortIndex":23,"researcher":22,"roles":782,"affiliations":783,"properties":792,"displayName":794,"givenName":22,"familyName":22},"b18c33ee-09a8-434d-8efc-3a1179fffb37",[215],[784],{"id":785,"sortIndex":23,"affiliation":786,"properties":22},"14e233d5-1167-48f2-b3a3-1c0dab6d2901",{"id":785,"createTime":22,"updateTime":22,"relativeEntities":787,"slug":22,"properties":788,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":791,"statistic":22},[],{"title":789},{"VI":790},"Department of Sedimentary Basins and Petroleum, Shahid Beheshti University, Tehran, Iran",[],{"title":793},{"VI":794},"Mohsen Ehteshami-Moinabadi",{"id":796,"sortIndex":168,"researcher":22,"roles":797,"affiliations":798,"properties":805,"displayName":807,"givenName":22,"familyName":22},"64df6b00-f1a8-4f8e-95b7-88a29c5eb171",[215],[799],{"id":785,"sortIndex":23,"affiliation":800,"properties":22},{"id":785,"createTime":22,"updateTime":22,"relativeEntities":801,"slug":22,"properties":802,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":804,"statistic":22},[],{"title":803},{"VI":790},[],{"title":806},{"VI":807},"Ehsan 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Qilian Mountains, located in the northeastern Qinghai-Tibet Plateau, is a sensitive zone of both East Asian summer monsoon (EASM) and westerly winds (WW). The evolution history and driving mechanism of the ecosystem and hydrologic cycle in this region on long-term timescales have not yet been clarified. In this study, we comprehensively study the hydrologic and ecological evolution history in the sensitive zone since the Last Glacial Maximum (LGM) by integrating surface sediments, paleoclimate records, TraCE-21ka transient simulations, and PMIP3-CMIP5 multi-model simulation. Results show that hydrologic and ecological proxies from surface sediments are significantly different from west to east and mainly divided into three sections: the monsoon-affected region in the eastern Qilian Mountains, the intersection region in the central Qilian Mountains, and the westerly-affected region in the western Qilian Mountains. Meanwhile, paleo-ecological and paleohydrologic reconstructions from the surroundings uncover a synchronous climate evolution that the EASM mainly controls the eastern Qilian Mountains and penetrates the central Qilian Mountains in monsoon intensity maximum, while the WW dominates the central and western Qilian Mountains on both glacial-interglacial and millennial timescales. The simulation results further bear out the glacial humid climate in the central and western Qilian Mountains caused by the enhanced WW, and the humidity maximum in the eastern Qilian Mountains controlled by the strong mid-Holocene monsoon. In general, east-west differences in climate pattern and response for the EASM and the WW are integrally stable on both short-term and long-term timescales.",{"EN":895},"Ecological and hydrologic evolution history in the sensitive zone of both East Asian summer monsoon and Westerly since the Last Glacial Maximum",{"VOID":897},"[\"8029563260744467996\"]",{"VOID":899},"An Z, Colman SM, Zhou W, et al. (2012) Interplay between the Westerlies and Asian monsoon recorded in Lake Qinghai sediments since 32 ka. Sci Rep 2: 619. https:\u002F\u002Fdoi.org\u002F10.1038\u002Fsrep00619\nAn Z, Wu G, Li J, et al. (2015) Global monsoon dynamics and climate change. Annu Rev Earth Planet Sci 43: 29–77. https:\u002F\u002Fdoi.org\u002F10.1146\u002Fannurev-earth-060313-054623\nCai Y, Tan L, Cheng H, et al. (2010) The variation of summer monsoon precipitation in central China since the last deglaciation. 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China",[],{"title":918},{"VI":919},"Yu Li",{"id":921,"sortIndex":168,"researcher":22,"roles":922,"affiliations":923,"properties":930,"displayName":932,"givenName":22,"familyName":22},"81c6bdf9-5095-4c5f-a8eb-9d4cae580390",[215],[924],{"id":910,"sortIndex":23,"affiliation":925,"properties":22},{"id":910,"createTime":22,"updateTime":22,"relativeEntities":926,"slug":22,"properties":927,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":929,"statistic":22},[],{"title":928},{"VI":915},[],{"title":931},{"VI":932},"Si-min 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discharge of flood in small mountainous watershed is usually calculated using the “Rainstorm–runoff calculation method in small watersheds in Sichuan Province” (RRM). This study evaluated the RRM calculation using real-time monitored rainfall and hydrologic data from a small watershed in the Wenchuan Earthquake area of Sichuan Province, China. The results indicated that the discharge values given by the RRM are commonly overestimating the measured discharge. The overestimation rate was discussed and empirical equations were proposed for improving RRM estimations, based on the relationship between calculated and measured discharge values at different watershed scales (2, 30, and 40 km2), under different rainfall probabilities (0.97–0.5, 0.5–0.2, and 0.2–0.002), and for different rainfall durations (0–6, 6–24, and >24 h). The results of this study help contribute to the understanding of water floods formation and help provide more accurate estimations of peak flow discharge in small watersheds in the Wenchuan Earthquake area.",{"EN":1008},"Evaluation of a traditional method for peak flow discharge estimation for floods in the Wenchuan Earthquake area, Sichuan Province, China",{"VOID":1010},"[\"2433465750929878578\"]",{"VOID":1012},"Arnold JG, Williams JR, Srinivasan R, et al. (1998) Large area hydrologic modeling and assessment part I: model development. Journal of the American Water Resources Association 34(1): 73–89. https:\u002F\u002Fdoi.org\u002F10.1111\u002Fj.1752-1688.1998.tb05961.x\nBeven K, Kirkby M (1979) A physically based, variable contributing area model of watershed hydrology. Hydrological Sciences Journal 24(1): 43–69. https:\u002F\u002Fdoi.org\u002F10.1080\u002F02626667909491834\nChen XC, Cui YF (2017) The formation of the Wulipo landslide and the resulting debris flow in Dujiangyan City, China. Journal of Mountain Sciences 14(6): 1100–1112. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs11629-017-4392-1\nCui P, Chen XQ, Zhu YY, et al. (2011) The Wenchuan Earthquake(May 12, 2008), Sichuan Province, China, and resulting geohazards. Natural Hazards 56: 19–36. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs11069-009-9392-1\nCui P, Guo XJ, Yan Y, et al (2018) Real-time observation of an active debris flow watershed in the Wenchuan Earthquake area. Geomorphology 2018 321: 153–166. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.geomorph.2018.08.024\nGuo XJ, Cui P, Li Y, Zhang JQ, et al. (2016a) Spatial features of debris flows and their rainfall thresholds in the Wenchuan Earthquake-affected area. Landslides 13: 1215–1229. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10346-015-0608-z\nGuo XJ, Cui P, Li Y, et al. (2016b) Intensity-duration threshold of rainfall triggering debris flows in Wenchuan earthquake area, China. Geomorphology 263: 208–216. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.geomorph.2015.10.009\nGuo XJ, Cui P, Ma L, et al. (2014) Triggering rainfall characteristics for Debris Flows along Dujiangyan-Wenchuan Highway of Sichuan. Journal of Mountain Research 32: 739–746(In Chinese) https:\u002F\u002Fdoi.org\u002F10.16089\u002Fj.cnki.1008-2786.2014.06.030\nHorton R E. (1933) The role of infiltration in the hydrologic-cycle. Eos, Transactions American Geophysical Union 14(1): 446–460. https:\u002F\u002Fdoi.org\u002F10.1029\u002FTR014i001p00446\nHorton R E. (1939) Analysis of runoff-plat experiments with varying infiltration-capacity. Eos, Transactions American Geophysical Union 20(4): 693–711. https:\u002F\u002Fdoi.org\u002F10.1029\u002FTR020i004p00693\nHorton R E. (1941) An approach toward a physical interpretation of infiltration-capacity. Soil Science Society of America Journal 5(C): 399–417. https:\u002F\u002Fdoi.org\u002F10.2136\u002Fsssaj1941.036159950005000C0075x\nHuang PN, Li ZJ, Chen J, et al. (2016) Event-based hydrological modeling for detecting dominant hydrological process and suitable model strategy for semi-arid catchments. Journal of Hydrology 542: 292–303. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.jhydrol.2016.09.001\nHuang R, Li W (2009) Analysis of the geo-hazards triggered by the 12 May 2008 Wenchuan Earthquake. China. Bull. Eng. Geol. Environ. 68: 363–371. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10064-009-0207-0\nHungr O (2000) Analysis of debris flow surges using the theory of uniformly progressive flow. Earth Surface Processes and Landforms 25: 483–495. https:\u002F\u002Fdoi.org\u002F10.1002\u002F(SICI)1096-9837(200005)25:5\u003C483::AID-ESP76>3.0.CO;2-Z\nHungr O, Leroueil S, Picarelli L (2014) The Varnes classification of landslide types, an update. Landslides 11(2): 167–194. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10346-013-0436-y\nHurgr O, Morgan GC, Kellerhals R(1984). Quantitative analysis of debris torrent hazards for design of remedial measures. Canadian Geotechnical Journal 21(4): 663–677. https:\u002F\u002Fdoi.org\u002F10.1139\u002Ft84-073\nHürlimann M, Abancó C, Moya J, et al. (2014) Results and experiences gathered at the Rebaixader debris-flow monitoring site, Central Pyrenees, Spain. Landslides 11(6): 939–953. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10346-013-0452-y\nLi J, Wang ZG, Liu CM (2015) A combined rainfall infiltration model based on Green-Ampt and SCS-curve number. Hydrological Processes 29(11): 2628–2634. https:\u002F\u002Fdoi.org\u002F10.1002\u002Fhyp.10379\nLiu JF, Nakatani K, Mizuyama T (2013) Effect assessment of debris flow mitigation works based on numerical simulation by using Kanako 2D. Landslides 10: 161–173. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10346-012-0316-x\nLiu JF, You Y, Chen XQ, et al. (2014) Characteristics and hazard prediction of large-scale debris flow of Xiaojia Gully in Yingxiu Town, Sichuan Province, China. Engineering Geology 180: 55–67. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.enggeo.2014.03.017\nMasson D, Frei C (2014) Spatial analysis of precipitation in a high-mountain region: exploring methods with multi-scale topographic predictors and circulation types. Hydrology and Earth System Sciences 18(11): 4543–4563. https:\u002F\u002Fdoi.org\u002F10.5194\u002Fhess-18-4543-2014\nMarchi L, Arattano M, Deganutti, A.M. (2002) Ten years of debris-flow monitoring in the Moscardo Torrent (Italian Alps). Geomorphology 46(1): 1–17. https:\u002F\u002Fdoi.org\u002F10.1016\u002FS0169-555X(01)00162-3\nMcCoy S, Kean J, Coe J, et al. (2010) Evolution of a natural debris flow: In situ measurements of flow dynamics, video imagery, and terrestrial laser scanning. Geology 38(8): 735–738. https:\u002F\u002Fdoi.org\u002F10.1130\u002FG30928\nNavratil O, Liébault F, Bellot H, et al. (2013) High-frequency monitoring of debris-flow propagation along the Réal Torrent, Southern French Alps. Geomorphology 201: 157–171. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.geomorph.2013.06.017\nNikolopoulos EI, Crema S, Marchi L, et al. (2014) Impact of uncertainty in rainfall estimation on the identification of rainfall thresholds for debris flow occurrence. Geomorphology 221: 286–297. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.geomorph.2014.06.015\nNikolopoulos EI, Borga M, Creutin JD, et al. (2015) Estimation of debris flow triggering rainfall: Influence of rain gauge density and interpolation methods. Geomorphology 243: 40–50. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.geomorph.2015.04.028\nParajka J, Viglione A, Rogger M, et al. (2013) Comparative assessment of predictions in ungauged watersheds-Part 1: Runoff-hydrograph studies. Hydrology and Earth System Sciences 17(5): 1783–1795. https:\u002F\u002Fdoi.org\u002F10.5194\u002Fhessd-10-375-2013\nPatil J, Sarangi A, Singh A, et al. (2008) Evaluation of modified CN methods for watershed runoff estimation using a GIS-based interface. Biosystems engineering 100(1): 137–146. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.biosystemseng.2008.02.001\nRathjens H, Oppelt N, Bosch DD, et al.(2015). Development of a grid-based version of the SWAT landscape model. Hydrological Processes 29: 900–914. https:\u002F\u002Fdoi.org\u002F10.1002\u002Fhyp.10197\nRozalis S, Morin E, Yair Y, et al. (2010) Flash flood prediction using an uncalibrated hydrological model and radar rainfall data in a Mediterranean watershed under changing hydrological conditions. Journal of Hydrology 394(1–2): 245–255. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.jhydrol.2010.03.021\nRainstorm-runoff calculation method in small watershed, Sichuan Hydrological Manual. 1984, Sichuan Water Conservancy and Power Department. Electronic publishing. Available on: http:\u002F\u002Fwww.gong123.com\u002Fkanchacehui\u002F2012-04-30\u002F535301.html\nTang C, Li WL, Ding J, et al. (2011) Field investigation and research on giant debris flow on August 14, 2014 in Yingxiu Town, epicenter of Wenchuan Earthquake. Earth Science Journal of Geosciences 35: 172–180. https:\u002F\u002Fdoi.org\u002F10.3799\u002Fdqkx.2011.018\nTakahashi T (1991) Debris flow. Monograph of IAHR., AA Balkema Rotterdam, Netherlands.\nVarnes DJ (1978) Slope movement types and processes. In: Schuster RL, Krizek RJ(eds) Landslides, analysis and control, special report 176: Transportation research board, National Academy of Sciences, Washington, DC, pp. 11–33.\nWorld Meteorological Organization (1975) Intercomparison of Conceptual Models Used in Operational Hydrological Forecasting. Secretariat of the World Meteorological Organization, Geneva, Switzerland.\nYan Y, Cui P, Guo XJ, Ge YG (2016) Trace projection transformation: A new method for measurement of debris flow surface velocity fields. Frontiers of Earth Science 10(4): 761–771. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs11707-015-0576-6\nYang D, Koike T, Tanizawa H(2004). Application of a distributed hydrological model and weather radar observations for flood management in the upper Tone River of Japan. Hydrological Processes 18: 3119–3132. https:\u002F\u002Fdoi.org\u002F10.1002\u002Fhyp.5752\nZhang A, Li TJ, Si Y, et al. (2016) Double-layer parallelization for hydrological model calibration on HPC systems. Journal of Hydrology 535:737–747. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.jhydrol.2016.01.024\nZhou BF, Li DJ, Luo DF (1991) Guide to Prevention of Debris Flow. Science Press, Beijing, China(In Chinese).\nZhou W, Tang C (2013) Rainfall thresholds for debris flow initiation in the Wenchuan Earthquake stricken area, southwestern China. Landslides 11: 877–887. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10346-013-0421-5",{"VOID":1014},"10.1007\u002Fs11629-018-4983-5","2024-06-26T08:15:59.008+00:00","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs11629-018-4983-5",[1018,1042,1063,1076,1089,1109],{"id":1019,"sortIndex":23,"researcher":22,"roles":1020,"affiliations":1021,"properties":1039,"displayName":1041,"givenName":22,"familyName":22},"1a3c26d9-b651-4843-aa9d-d34d31cb8229",[215],[1022,1030],{"id":1023,"sortIndex":23,"affiliation":1024,"properties":22},"e705a563-ce9b-47a3-8e8f-e633b01d7167",{"id":1023,"createTime":22,"updateTime":22,"relativeEntities":1025,"slug":22,"properties":1026,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":1029,"statistic":22},[],{"title":1027},{"VI":1028},"Key Laboratory of Mountain Surface Process and Hazards\u002FInstitute of Mountain Hazards and Environment, Chinese Academy of 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Wang",{"url":1016,"publisher":1125,"properties":1178},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":1126,"slug":10,"properties":1127,"entityType":20,"verifyStatus":21,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":23,"subjectFields":1131,"manageAffiliations":1152,"indexDatabases":1158,"url":22,"thumbnailPath":22,"statistic":1173,"gsStatistic":22,"type":183,"analyzePriority":22},[],{"issn":1128,"title":1129,"eissn":1130},{"VOID":15},{"EN":17},{"VOID":13},[1132,1136,1140,1144,1148],{"id":26,"createTime":22,"updateTime":22,"relativeEntities":1133,"label":1134,"description":1135,"parentId":22,"standard":22,"scholarHubFieldId":22},[],{"EN":29},{},{"id":32,"createTime":22,"updateTime":22,"relativeEntities":1137,"label":1138,"description":1139,"parentId":22,"standard":22,"scholarHubFieldId":22},[],{"EN":35},{},{"id":38,"createTime":22,"updateTime":22,"relativeEntities":1141,"label":1142,"description":1143,"parentId":22,"standard":22,"scholarHubFieldId":22},[],{"EN":41},{},{"id":44,"createTime":22,"updateTime":22,"relativeEntities":1145,"label":1146,"description":1147,"parentId":22,"standard":22,"scholarHubFieldId":22},[],{"EN":47},{},{"id":50,"createTime":22,"updateTime":22,"relativeEntities":1149,"label":1150,"description":1151,"parentId":22,"standard":22,"scholarHubFieldId":22},[],{"EN":53},{},[1153],{"id":57,"createTime":22,"updateTime":22,"relativeEntities":1154,"slug":22,"properties":1155,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":1157,"statistic":22},[],{"title":1156},{"EN":61},[],[1159,1166],{"id":65,"indexDatabase":1160,"url":78,"indexYears":22,"academicFieldIds":1165,"indexDatabaseRanking":22},{"id":67,"createTime":22,"updateTime":22,"relativeEntities":1161,"label":1162,"description":1163,"key":74,"publicationTags":1164,"standard":22},[],{"EN":70,"VI":70},{"EN":72,"VI":73},[76,77],[80],{"id":82,"indexDatabase":1167,"url":93,"indexYears":94,"academicFieldIds":1172,"indexDatabaseRanking":101},{"id":84,"createTime":22,"updateTime":22,"relativeEntities":1168,"label":1169,"description":1170,"key":90,"publicationTags":1171,"standard":22},[],{"EN":87,"VI":87},{"EN":87,"VI":89},[92],[96,97,98,99,100],{"impactFactor":23,"impactFactorByYear":1174,"i10Index":115,"i10IndexLast5Year":116,"totalPublication":117,"totalPublicationByYear":1175,"totalCitation":139,"totalCitationByYear":1176,"totalCitationPerPublication":160,"totalCitationPerPublicationByYear":1177,"hindexLast5Year":182,"hindex":182},{"2012":104,"2013":105,"2014":106,"2015":107,"2016":107,"2017":108,"2018":109,"2019":110,"2020":111,"2021":112,"2022":113,"2023":114},{"2004":119,"2005":120,"2006":121,"2007":122,"2008":123,"2009":120,"2010":124,"2011":125,"2012":126,"2013":127,"2014":128,"2015":129,"2016":130,"2017":131,"2018":132,"2019":133,"2020":134,"2021":135,"2022":136,"2023":137,"2024":138},{"2004":141,"2005":142,"2006":143,"2007":144,"2008":145,"2009":146,"2010":124,"2011":147,"2012":148,"2013":149,"2014":150,"2015":151,"2016":152,"2017":153,"2018":154,"2019":155,"2020":156,"2021":157,"2022":158,"2023":159},{"2004":162,"2005":163,"2006":164,"2007":165,"2008":166,"2009":167,"2010":168,"2011":169,"2012":170,"2013":171,"2014":172,"2015":173,"2016":174,"2017":175,"2018":176,"2019":177,"2020":178,"2021":179,"2022":180,"2023":181},{"pages":1179,"volume":1181},{"VOID":1180},"641-656",{"VOID":1182},"16","2019-03-08",2019,"2026-07-15T23:57:49.389+00:00",[101,76],{"id":1188,"createTime":1189,"updateTime":1190,"relativeEntities":1191,"slug":1192,"properties":1193,"entityType":204,"verifyStatus":205,"verifyTime":1204,"verifyNote":207,"languages":22,"translateLanguages":22,"viewCount":23,"primaryUrl":1205,"fullTextUrl":22,"authors":1206,"publicationType":273,"publisherRelationship":1258,"citationCount":1317,"citationInfo":1318,"publishDate":1322,"publishYear":1319,"citationAnalyzeStatus":757,"lastCitationAnalyze":1190,"indexDatabases":1323,"openAccess":22,"references":22,"isForceReanalyzing":336},"ff30b2b4-ca4d-4127-8085-3ec00c68bf20","2023-12-09T17:47:07.799+00:00","2026-07-15T11:06:05.839+00:00",[],"Vegetation-dynamics-of-ephemeral-and-perennial-streams-in-mountainous-headwater-catchments",{"abstract":1194,"title":1196,"gsPaper":1198,"references":1200,"doi":1202},{"EN":1195},"Ephemeral and perennial streams of mountainous catchments in Sabaragamuwa Province of Sri Lanka and Hong Kong of China were studied for two years on vegetation dynamics. Each year, sampling was conducted during a period when ephemeral streams had low surface flows. Sampling was realized contiguously using belt transects. The standing crop biomass (hereafter biomass) of herbaceous vegetation in ephemeral channels was comparatively lower than perennials and so was the herb diversity. Herb diversity showed a peak from 1.5 to 4.5 m from the centerline\u002Fthalweg of ephemeral and perennial streams. Out of 24 herbs, only three were common for both. A peak herb biomass zone was observed in perennials in the same region where diversity peaked. In ephemerals, herb biomass increased laterally up to ∼1.5 m, and was constant thereafter. Seedling experiment results tallied with the field diversity observations of both stream types, and suggested that seed dispersion was the main reason for herb colonization. Furthermore, it showed sapling emergence to be significantly higher in perennials than ephemerals. Return period of annual maximum monthly rainfall was a strong indicator of age of trees in ephemeral streams, and elucidated the possibility of hindcasting past flow episodes. Electrical conductivity was significantly high in ephemeral streams among all the water quality parameters. The contents of the water nutrients were approximately the same in both stream types. While recommending further studies on eco-hydrology of ephemerals, we recognize ephemeral streams to be valuable references in climate change studies due to their responsiveness and representativeness in long term hydrological changes.",{"EN":1197},"Vegetation dynamics of ephemeral and perennial streams in mountainous headwater catchments",{"VOID":1199},"[\"7266706148836860515\"]",{"VOID":1201},"Asaeda T, Gomes PIA, Takeda E (2010) Spatial and temporal tree colonization in a midstream sediment bar and the mechanisms governing tree mortality during a flood event. 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Hydrobiologia 589(1): 91–106.https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10750-007-0723-5\nDai F, Lee CF (2002) Assessment of landslides on natural terrain: Physical characteristics and susceptibility mapping in Hong Kong. Mountain Research and Development 22(1): 40–47. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs002540000163\nDatry T, Larned ST, Tockner K (2014) Intermittent Rivers: a challenge for freshwater ecology. Bioscience, bit027. https:\u002F\u002Fdoi.org\u002F10.1093\u002Fbiosci\u002Fbit027\nDeng W, Bai JH, Yan MH (2002) Problems and countermeasures of water resources for sustainable utilization in China. Chinese Geographical Science 12(4): 289–293.\nDepartment of Meteorology (2017) Home page and weather forecasts. http:\u002F\u002Fwww.meteo.gov.lk\u002Findex.php?lang=en (accessed on 12-12-2017)\nEnquist BJ, Brown JH, West GB (1998) Allometric scaling of plant energetics and population density. 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Annales de Limnologie-International Journal of Limnology 45(3): 181–193.\nGomes PIA, Wai OWH (2014) Sampling at mesoscale physical habitats to explain headwater stream water quality variations: Its comparison to equal-spaced sampling under seasonal and rainfall aided flushing states. Journal of hydrology 519: 3615–3633. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.jhydrol.2014.11.009\nGomes PIA, Wai OW, Yan XF (2017) Eco —. hydraulic evaluation of herbaceous ecosystems below headwater dams without a base flow: Observing below dam reaches as new stream sources. Ecohydrology 10(1). https:\u002F\u002Fdoi.org\u002F10.1002\u002Feco.1774\nGunawardene NR, Majer JD, Edirisinghe JP (2010) Investigating residual effects of selective logging on ant species assemblages in Sinharaja Forest Reserve, Sri Lanka. Forest Ecology and Management 259(3): pp 555–562. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.foreco.2009.11.012\nHerschy RW (1995) Streamflow Measurement. E & F N Spon, London.\nJacobson PJ, Jacobson KM, Angermeier PL, et al. (1999) Transport, retention, and ecological significance of woody debris within a large ephemeral river. Journal of the North American Benthological Society 18(4): 429–444. https:\u002F\u002Fdoi.org\u002F10.2307\u002F1468376\nJacquez GM, Maruca S, Fortin MJ (2000) From fields to objects: a review of geographic boundary analysis. Journal of Geographical Systems, 2: 221–241. https:\u002F\u002Fdoi.org\u002F10.1007\u002FPL00011456\nKolb TE, Hart SC, Amundson R (1997) Boxelder water sources and physiology at perennial and ephemeral stream sites in Arizona. Tree Physiology 17(3): 151–160. https:\u002F\u002Fdoi.org\u002F10.1093\u002Ftreephys\u002F17.3.151\nMeinzer OE (1923) Outline of groundwater hydrology. US Geology Survey Water Supply, United States Government printing office. https:\u002F\u002Fpubs.usgs.gov\u002Fwsp\u002F0494\u002Freport.pdf Date accessed 25-01-2017.\nMurphy J, Riley JP (1962) A modified single solution method for the determination of phosphate in natural waters. Analytica Chimica Acta 27: 31–36. https:\u002F\u002Fdoi.org\u002F10.1016\u002FS0003-2670(00)88444-5\nNaiman RJ, Decamps H (1997). The ecology of interfaces: riparian zones. Annual review of Ecology and Systematics 28(1): 621–658. https:\u002F\u002Fdoi.org\u002F10.1146\u002Fannurev.ecolsys.28.1.621\nNolin AW (2012) Perspectives on climate change, mountain hydrology, and water resources in the Oregon Cascades, USA. Mountain Research and Development 32: 35–46. https:\u002F\u002Fdoi.org\u002F10.1659\u002FMRD-JOURNAL-D-11-00038.S1\nPanabokke CR (2002) Small tanks in Sri Lanka: evolution, present status, and issues. IWMI.\nSieben EJJ (2015) Influence of flow regime on the vegetation zonation along mountain streams in the Western Cape, South Africa. Journal of Mountain Science 12(6): 1484–1498. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs11629-014-3420-7\nSeghieri J, Galle S, Rajot JL, et al. (1997) Relationships between soil moisture and growth of herbaceous plants in a natural vegetation mosaic in Niger. Journal of Arid Environments 36(1): 87–102. https:\u002F\u002Fdoi.org\u002F10.1006\u002Fjare.1996.0195\nStromberg JC, Hazelton AF, White MS (2009) Plant species richness in ephemeral and perennial reaches of a dryland river. Biodiversity and Conservation 18(3): 663–677. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10531-008-9532-z\nStromberg JC, Merritt DM (2016) Riparian plant guilds of ephemeral, intermittent and perennial rivers. Freshwater Biology 61(8): 1259–1275. https:\u002F\u002Fdoi.org\u002F10.1111\u002Ffwb.12686\nSubramanya K (2013) Engineering Hydrology, 4th edition. Tata McGraw-Hill Education.\nViviroli D, Archer DR, Buytaert W, et al. (2011) Climate change and mountain water resources: overview and recommendations for research, management and policy. Hydrology and Earth System Sciences 15(2): 471–504. https:\u002F\u002Fdoi.org\u002F10.5194\u002Fhess-15-471-2011\nWeingartner R, Viviroli D, Schädler B (2005) Assessment of water resources in headwaters and their significance for the lowlands. In Proceedings of the International Conference on Headwater Control VI: Hydrology, Ecology and Water Resources in Headwaters. Bergen, Norway. pp. 20–23.",{"VOID":1203},"10.1007\u002Fs11629-017-4640-4","2024-05-05T10:06:39.696+00:00","https:\u002F\u002Flink.springer.com\u002F10.1007\u002Fs11629-017-4640-4",[1207,1232,1245],{"id":1208,"sortIndex":23,"researcher":22,"roles":1209,"affiliations":1210,"properties":1227,"displayName":1229,"givenName":22,"familyName":22},"1ca923f6-a3c7-4083-84bf-4784539ced5b",[215],[1211,1219],{"id":1212,"sortIndex":23,"affiliation":1213,"properties":22},"4b3c07fc-5c9c-4b06-b495-b4ce253cd98c",{"id":1212,"createTime":22,"updateTime":22,"relativeEntities":1214,"slug":22,"properties":1215,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":1218,"statistic":22},[],{"title":1216},{"VI":1217},"Department of Civil Engineering, Faculty of Engineering, Sri Lanka Institute of Information Technology, Malabe, Sri Lanka",[],{"id":1220,"sortIndex":168,"affiliation":1221,"properties":22},"5ff19222-006d-4cdd-b95a-efada9919564",{"id":1220,"createTime":22,"updateTime":22,"relativeEntities":1222,"slug":22,"properties":1223,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":1226,"statistic":22},[],{"title":1224},{"EN":1225},"Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong, China",[],{"title":1228,"gsAuthor":1230},{"VI":1229},"Pattiyage I. 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In this study, we obtained high-resolution images of mature forests of Chinese fir by unmanned aerial vehicle (UAV) flying through cross-route flight, and then reconstructed the three-dimensional point clouds in the UAV aerial area by SfM technique. The point cloud segmentation (PCS) algorithm was used for the individual tree segmentation, and the F-score of the three sample plots were 0.91, 0.94, and 0.94, respectively. Individual tree biomass modeling was conducted using 155 mature Chinese fir forests which were correctly segmented. The relative root mean squared error (rRMSE) values of random forest (RF), bagged tree (BT) and support vector regression (SVR) were 34.48%, 35.74% and 40.93%, respectively. Our study demonstrated that DAP point clouds had great potential to extract forest vertical parameters and could be applied successfully in individual tree segmentation and individual tree biomass modeling.",{"EN":1334},"Individual tree segmentation and biomass estimation based on UAV Digital aerial photograph",{"VOID":1336},"[\"3272698824195922855\"]",{"VOID":1338},"Almeida CT, Galvão LS, Aragão LE, et al. (2019) Combining LiDAR and hyperspectral data for aboveground biomass modeling in the Brazilian Amazon using different regression algorithms. Remote Sens Environ 232: 111323. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.rse.2019.111323\nAlonzo M, Andersen HE, Morton DC, et al. (2018) Quantifying Boreal Forest Structure and Composition Using UAV Structure from Motion. Forests 9(3): 119. https:\u002F\u002Fdoi.org\u002F10.3390\u002Ff9030119\nAndersen HE, McGaughey RJ, Reutebuch SE (2005) Estimating forest canopy fuel parameters using LIDAR data. 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Province is an important component of the Qinghai-Tibet Plateau in China. Scientific evaluation of the suitability of Qinghai’s climate for tourism can contribute to overcoming obstacles posed by climate on sustainable tourism development in Qinghai Province, including disparities between the low and high seasons, high altitude health concerns, and weather events. A tourism climate suitability evaluation model of the Qinghai-Tibet Plateau is constructed (Tourism Climate Suitability Index, or TCSI), and tourism climate suitability is comprehensively evaluated for Qinghai Province from climate data from 1960 to 2009. Results show that: (I) There is clear distributional characteristics of spatial-temporal variability of TCSI values in Qinghai Province. (II) Tourism climate suitability in Qinghai Province has significant seasonal and regional differences. The year is divided into a very suitable period (July and August), suitable tourism periods (from April and October), less suitable periods (From Nov to Mar). June to August is the most suitable tourism period in Qinghai. Qinghai Province is divided into five levels of tourism climate suitability: most suitable regions, very suitable regions, suitable regions, less suitable regions, and unsuitable region. (III) The key factor which influences regional differences in tourism climatic suitability is atmospheric oxygen. And the key factors which chiefly influence seasonal differences of tourism climate suitability are temperature and humidity, the wind chill factor, and barrier weather.",{"EN":1540},"A comprehensive evaluation of tourism climate suitability in Qinghai Province, China",{"VOID":1542},"[\"8087706610792595457\"]",{"VOID":1544},"Bigano A, Hamilton JM, Tol RSJ (2006) The impact of climate on holiday destination choice. Climatic Change 76: 389–406.\nChang A, Ge QS, Fang XQ (2007) Climatic suitability for tourism along the Qinghai-Tibet Railway. Geographical Research 26(3): 533–540. (In Chinese)\nCoombes EG, Jones AP (2010) Assessing the impact of climate change on visitor behavior and habitat use at the coast: A UK case study. Global Environmental Change 20(2): 303–313.\nDai JX (1990) The climate in Qinghai-Tibet Plateau. Beijing: China Meteorological Press. (In Chinese)\nDai SN (1987) Tourism industry and climate. Tourism tribune (2): 73–74. (In Chinese)\nDe FCR, Scott D, McBoyle G (2008) A second generation climate index for tourism (CIT): Specification and verification. International Journal of Biometeorology 52(5): 399–407.\nDing YL, Lu L (2008) Study on status quo about tourism climate and its enlightenment. Human Geography 23(5):7–11. (In Chinese)\nFan YZ, Guo LX (1998) The climate suitability of tourism at the coastline destinations of China. Journal of Natural Resources 13(4): 304–311. (In Chinese)\nFu WD (2000) Distribution laws of ultraviolet and infrared solar radiation in Xinjiang. Arid Land Geography 23(2): 116–122. (In Chinese)\nGarrod Brian (2011) Applying the Delphi method in an ecotourism context: A response to Deng et al. “Development of a point evaluation system for ecotourism destinations: A Delphi method’. Journal of Ecotourism 10(1): 77–85.\nGómez Martín M B (2005) Weather, climate and tourism a geographical perspective. Annals of Tourism Research 32(3): 571–591.\nJuan LEM, Juan ACS (2009) Climate in the region of origin and destination choice in outbound tourism demand. Tourism Management 30(7): 1–10.\nOliver JE (1973) Climate and man’s environment: An introduction applied climatology. John Wiley & Son’s Inc. pp 195–206.\nPearce D (1972) Weather, climate and tourism. Weather 27: 199–203.\nLin TP, Matzarakis A (2010) Tourism climate information based on human thermal perception in Taiwan and Eastern China. Tourism Management 31(3): 1–9.\nLise W, Tol RSJ (2002) Impact of climate on tourist demand. Climatic Change 55: 429–449.\nLiu QC, Wang Z, Xu SY (2007) Climate suitability index for city tourism in China. Resources Science 29(1): 133–141. (In Chinese)\nLu L, Xuan GF, Zhang JH, et al. (2002) An approach to seasonality of tourist flows between coastland resorts and mountain resorts: Examples of Sanya, Beihai, Mt. Putuo, Mt. Huangshan and Mt. Jiuhu. Acta Geographica Sinica 57(6): 731–740. (In Chinese)\nMa LJ, Sun GN, Li FL, et al. (2007) Evaluation of tourism climate comfortableness in Shanxi Province. Resources Science 29(6): 40–44. (In Chinese)\nMieczkowski Z (1985) The tourism climate index: A method for evaluating world climates for tourism. The Canadian Geographer 29: 220–233.\nRen JM, Niu JJ, Hu CH, et al. (2004) Tourism climate and evaluation of comfortableness in Wutai Mountain. Geographical Research 23(6): 856–861. (In Chinese)\nSarah Nicholls (2004) Climate change and tourism. Annals of Tourism Research 31(1): 238–240.\nScott D, Jones B, Konopek J (2007) Implications of climate and environmental change for nature-based tourism in the Canadian Rocky Mountains: A case study of Waterton Lakes National Park. Tourism Management 28: 570–579.\nSu M M, Wall G (2009) The Qinghai-Tibet railway and Tibetan tourism: Travelers’ perspectives. Tourism Management 30(5): 650–657.\nSun GN, Ma LJ (2007) An analysis of tourist climate comfortable degree and yearly variation of tourist traffic in Xi’an. Tourism tribune 22(7): 34–39. (In Chinese)\nSuzanne Goldenberg (2011a) Everest’s ice is retreating as climate change grips the Himalayas. The Observer 7–25. http:\u002F\u002Fwww.guardian.co.uk\u002Fworld\u002F2011\u002Fsep\u002F25\u002Fclimate-change-himalayas-glaciers-melting?INTCMP=SRCH [accessed on 2012-09-25].\nSuzanne Goldenberg (2011b) Climate change may leave Mount Everest ascent ice-free, say climbers. The Observer 7–25. http:\u002F\u002Fwww.guardian.co.uk\u002Fworld\u002F2011\u002Fsep\u002F24\u002Fclimate-change-mount-everest-melting?INTCMP=SRCH [accessed on 2012-09-24].\nTSETQT (The comprehensive scientific expedition team of Qinghai-Tibet Plateau in Chinese Academy of Sciences) (1984) Climate in Qinghai-Tibet Plateau. Beijing: Science Press. (In Chinese)\nWu P, Xi JC, Ge QS (2010) Research on the tourism climatology: Review and preview. Progress in Geography 29(2): 131–137. (In Chinese)\nXu JH (2002) Mathematical methods in contemporary geography. Higher Education Press. (In Chinese)\nZhou LZ, Zhou GM, Ying M (1998) Analysis on the indexes of climate suitability for tourism activity. Meteorological Science and Technology (1): 60–63. 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