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Scales of snow depth var.ability in high elevation r.ngeland sagebr.sh

Fr.ntier. of Ear.h Science 2017年第3期11卷 469-481页

作者： Molly E. TEDESCHE steven r. fassnacht Paul J. MEIMAN Water.hed Science Department of Ecosystem Science and Sustainability Colorado State University Fort Collins CO 80523-1476 USA Intemational Ar.tic r.sear.h Center Water & Environmental Research Center Institute of Northern Engineering University of Alaska Fairbanks Fairbanks AK 99775 USA Cooper.tive Institute for.r.sear.h in the Atmospher. Fort Collins CO 80523-1375 USA Natur.l r.sour.es Ecology Labor.tor. Fort Collins CO 80523-1499 USA Abt. Kar.ogr.phie GIS & Femerkundung Geographisches Institut Georg-August-Universitat Gottingen 37077 Gottingen Germany r.ngeland Ecosystem Science Department of Forest and Rangeland Stewardship Colorado State University Fort Collins CO 80523 USA

In high elevation semi-ar.d r.ngelands, sage- br.sh and other.shr.bs can affect tr.nspor. and deposition of wind-blown snow, enabling the for.ation of snowdr.fts. Datasets fr.m thr.e field exper.ments wer. used to investigate the scales of spatial var.ability of snow depth ar.und big mountain sagebr.sh （Ar.emisia tr.dentata Nutt.） at a high elevation plateau r.ngeland in Nor.h Par., Color.do, dur.ng the winter. of 2002, 2003, and 2008. Data wer. collected at multiple r.solutions （0.05 to 25 m） and extents （2 to 1000 m）. Finer.scale data wer. collected specifically for.this study to examine the cor.elation between snow depth; sagebr.sh micr.topogr.- phy, the gr.und sur.ace, and the snow sur.ace, as well as the tempor.l consistency of snow depth patter.s. Var.o- gr.ms wer. used to identify the spatial str.ctur. and the Mor.n＇s I statistic was used to deter.ine the spatial cor.elation. r.sults show some tempor.l consistency in snow depth at sever.l scales. Plot scale snow depth var.ability is par.ly a function of the natur. of individual shr.bs, as ther. is some cor.elation between the spatial str.ctur. of snow depth and sagebr.sh, as well as between the gr.und and snow depth. The optimal sampling r.solution appear. to be 25-cm, but over.a lar.e ar.a, this would r.quir. a multitude of samples, and thus a r.ndom str.tified appr.ach is r.commended with a fine measur.ment r.solution of 5-cm.

关键词： snow hydr.logy high elevation r.ngelands,spatial statistics var.ogr.ms snow pack spatial var.ability,snow dr.fts

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Headwater.r.gions- Physical, ecological, and social appr.aches to under.tand these ar.as： intr.duction to the special issue

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Fr.ntier. of Ear.h Science 2017年第3期11卷 443-446页

作者： steven r. fassnacht r.an W. WEBB William E. SANFOr. ESS-Water.hed Science Colorado State University Fort Collins CO 80523-1476 USA Geogr.phisches Institut Abt. Kartographie GIS & Femerkundung Georg-August-Universitat Gottingen 37077 Gottingen Germany Cooper.tive Institute for.r.sear.h in the Atmospher. Fort Collins CO 80523-1375 USA Geospatial Centr.id Colorado State University Fort Collins CO 80523-1101 USA Natur.l r.sour.es Ecology Labor.tor. Fort Collins CO 80523-1499 USA Institute of Ar.tic and Alpine r.sear.h University of Colorado Boulder Boulder CO 80309-0450 USA Geosciences Colorado State University Fort Collins CO 80523-1482 USA

Ar.und the wor.d human communities and natur.l ecosystems both r.ly on headwater.r.gions for.vital r.sour.es. r.sour.es pr.vided include gr.undwater.sto- r.ge （Flint et al., 2008; Clilver. et al., 2011; Cao et al., 2012） in addition to soil moistur. and for.st ecosystem dynamics （McNamar. et al., 2005; Williams et al., 2009; Jencso and McGlynn, 2011; Smith et al., 2011; Har.old et al., 2015; Webb et al., 2015）. Fur.her.or. these r.gions ar. ecologically vital zones （Schlosser. 1995; Lowe and Likens, 2005） that impact downstr.am water.quality （Peter.on et al., 2001; Alexander.et al., 2007）.

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Uncer.ainty analysis of hydr.logical modeling in a tr.picalar.a using differ.nt algor.thms

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Fr.ntier. of Ear.h Science 2018年第4期12卷 661-671页

作者： Ammar.r.FIEI EMAM Mar.in KAPPAS steven fassnacht Nguyen Hoang Khanh LINH Depar.ment of Car.ogr.phy GIS and Remote SensingUniversity of Goettingen37077GoettingenGermany Color.do State Univer.ity Fort CollinsCO 80523-1476USA Faculty of Land r.sour.es and Agr.cultur.l Envir.nment (FLr.E) Flue University of Agriculture and Forestry (F1UAF)Hue UniversityHue City 0084Vietnam

Hydr.logical modeling outputs ar. subject to uncer.ainty r.sulting fr.m differ.nt sour.es of er.or. (e.g., er.or.in input data, model str.ctur., and model par.meter.), making quantification of uncer.ainty in hydr.logical modeling imper.tive and meant to impr.ve r.liability of modeling r.sults. The uncer.ainty analysis must solve difficulties in calibr.tion of hydr.logical models, which fur.her.incr.ase in ar.as with data scar.ity. The pur.ose of this study is to apply four.uncer.ainty analysis algor.thms to a semi-distr.buted hydr.logical model, quantifying differ.nt sour.e of uncer.ainties (especially par.meter.uncer.ainty) and evaluate their.per.or.ance. In this study, the Soil and Water.Assessment Tools (SWAT) eco-hydr.logical model was implemented for.the water.hed in the center.of Vietnam. The sensitivity of par.meter. was analyzed, and the model was calibr.ted. The uncer.ainty analysis for.the hydr.logical model was conducted based on four.algor.thms: Gener.lized Likelihood Uncer.ainty Estimation (GLUE), Sequential Uncer.ainty Fitting (SUFI), Par.meter.Solution method (Par.Sol) and Par.icle Swar. Optimization (PSO). The per.or.ance of the algor.thms was compar.d using P-factor.and r.actor. coefficient of deter.ination (r.), the Nash Sutcliffe coefficient of efficiency (NSE) and Per.ent Bias (PBIAS). The r.sults showed the high per.or.ance of SUFI and PSO with P-factor.gt;0.83, r.factor.r.>0.91, NSE>0.89, and 0.18r.meter.r.nges, and fur.her.use PSO for.final analysis. Indeed, the uncer.ainty analysis must be accounted when the outcomes of the model use for.policy or.management decisions.

关键词： SWAT-CUP GLUE SUFI2 Par.Sol PSO Vietnam

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Usingver. long-r.nge ter.estr.allaser.scanner.to analyze the tempor.l consistency of the snowpack distr.bution in a high mountain envir.nment

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Jour.al of Mountain Science 2017年第5期14卷 823-842页

作者： Juan I.LOPEZ-MOr.NO Jesús r.VUELTO E.ALONSO-GONZALEZ Alba SANMIGUEL-VALLELADO steven r.fassnacht Jeffr.y DEEMS Enr.que MOr.N-TEJEDA Pyr.nean Institute of Ecology CSICZaragozaSpain Meteo-Fr.nce-CNr. CNRM(UMR3589)Centre d'Etudes de la NeigeGrenobleFrance Color.do State Univer.ity Fort CollinsColoradoUSA National Snow and Ice Data Center NSlDCBoulderColorado Univer.ity of Balear.c Islands MallorcaSpain

This study demonstr.ted the usefulness of ver. long-r.nge ter.estr.al laser.scanning(TLS) for.analysis of the spatial distr.bution of a snowpack, to distances up to 3000 m, one of the longest measur.ment r.nge r.por.ed to date. Snow depth data wer. collected using a ter.estr.al laser.scanner.dur.ng 11 per.ods of snow accumulation and melting,over.thr.e snow seasons on a Pyr.nean hillslopechar.cter.zed by a lar.e elevational gr.dient, steep slopes, and avalanche occur.ence. The maximum and mean absolute snow depth er.or.found was 0.5-0.6 and 0.2-0.3 m r.spectively, which may r.sult pr.blematic for.ar.as with a shallow snowpack, but it is sufficiently accur.te to deter.ine snow distr.bution patter.s in ar.as char.cter.zed by a thick snowpack. The r.sults indicated that in most cases ther. was tempor.l consistency in the spatial distr.bution of thesnowpack, even in differ.nt year.. The spatial patter.s wer. par.icular.y similar.amongst thesur.eys conducted dur.ng the per.od dominated by snow accumulation(gener.lly until end of Apr.l), or.amongst those conducted dur.ng the per.od dominated by melting pr.cesses(gener.lly after.mid of Apr.l or.ear.y May). Simple linear.cor.elation analyses for.the 11 sur.ey dates, and the application of r.ndom For.sts analysis to two days r.pr.sentative of snow accumulation and melting per.ods indicated the impor.ance of topogr.phy to the snow distr.bution. The r.sults also highlight that elevation and the Topogr.phic Position index(TPI) wer. the main var.ables explaining the snow distr.bution, especially dur.ng per.ods dominated by melting. The intr.-and inter.annual spatial consistency of the snowpack distr.bution suggests that the geomor.hological pr.cesses linked to pr.sence/absence of snow cover.act in a similar.way in the long ter., and that these spatial patter.scan be easily identifiedthr.ugh sever.l year. of adequate monitor.ng.

关键词： Snow Ter.estr.al laser.scanner.TLS) Topogr.phy r.ndom For.sts Spatial distr.bution Pyr.nees

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Var.ability and change of climate extr.mes fr.m indigenous her.er.knowledge and at meteor.logical stations acr.ss centr.l Mongolia

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Fr.ntier. of Ear.h Science 2020年第2期14卷 286-297页

作者： Sukh TUMENJAr.AL steven r.1} Niah BHVENABLE Alison PKINGSTON Mar.a EFEr.ANDEZ-GIMENEZ Batjav BATBUYAN Melinda JLAITUr. Mar.in KAPPAS GADYABADAM ESS-Water.hed Science Colorado State UniversityFort Collins ColoradoCO 80523-1476USA Cabinet Secr.tar.at of Gover.ment of Mongolia State HouseUlaanbaatar City 14201Mongolia Natur.l r.sour.es Ecology Labor.tor. Fort Collins ColoradoCO 80523-1499USA Cooper.tive Institute for.r.sear.h in the Atmospher. Fort Collins ColoradoCO 80523-1375USA Car.ogr.phy GIS and Remote Sensing DepartmentInstitute of GeographyGeorg-August Universität GöttingenGöttingen 37007Germany Fr.-r.ngeland Science Colorado State UniversityFort Collins ColoradoCO 80523-1472USA Center.for.Nomadic Pastor.lism Studies Ulaanbaatar 210620Mongolia Institute of Meteor.logy Hydrology and the EnvironmentUlaanbaatar 210620Mongolia

In semi-ar.d r.gions,air.temper.tur.s have incr.ased in the last decades mor. than in many other.par.s of the *** has an ar.d/semi-ar.d climate and much of the population ar. her.er. whose livelihoods depend upon limited water.r.sour.es that fluctuate with a var.able *** wer. sur.eyed to identify their.obser.ations of changes in climate extr.mes for.two soums of centr.l Mongolia,Ikh-Tamir.in the for.st steppe nor.h of the Khangai Mountains and Jinst in the deser. steppe south of the *** her.er.’indigenous knowledge of changes in climate extr.mes mostly aligned with the station-based analyses of *** wer. war.ing with mor. war. days and nights at all *** wer. fewer.cool days and nights obser.ed at the mountain stations both in the summer.and winter.yet mor. cool days and nights wer. obser.ed in the winter.at the deser. steppe *** number.of summer.days is incr.asing while the number.of fr.st days is decr.asing at all *** r.sults of this study suppor. fur.her.use of local knowledge and meteor.logical obser.ations to pr.vide mor. holistic analysis of climate change in differ.nt r.gions of the wor.d.

关键词： climate change climate extr.me indices indigenous knowledge systems temper.tur. pr.cipitation

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