AVALANCHE FORECASTING IN A HEAVY SNOWFALL AREA USING THE SNOWPACK MODEL

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1 AVALANCHE FORECASTING IN A HEAVY SNOWFALL AREA USING THE SNOWPACK MODEL Hiroyuki Hirshim*, Kouichi Nishimur**, Storu Ymguchi*, Atsushi Sto* nd Michel Lehning*** * Snow nd Ice Reserch Center, NIED, Suyoshi, Meym, Ngok , Jpn ** Fculty of Science, Niigt University, Ikrshi, Niigt , Jpn *** WSL, Swiss Federl Institute for Snow nd Avlnche Reserch, SLF, Fluelstrsse 11, CH-726 Dvos Dorf, Switzerlnd ABSTRACT: We descrie the use of snow cover model SNOWPACK for hevy snowfll re. The re long the Se of Jpn received record-reking snowfll in the winter of 25/26. Avlnche forecsting ws crried out t Tunn, Niigt prefecture where snow exceeded 4m. Automted Meteorologicl Dt Acquisition System operted y the Jpn Meteorologicl Agency (AMEDAS) ws used s the model input dt. To verify the model output, snow pit oservtions were crried out in 1-dy intervls. The snow profiles simulted using the SNOWPACK model greed firly well with the oserved profiles. However, the equtions for the stility index (SI) were not suitle for the study re considered. The empiricl equtions formulted y Ymnoi nd Endo (22) were most suitle for this region for simulting SI; therefore, they were incorported into the SNOWPACK model. To expnd the forecsting re to include the re round route 45, ntionl rod, the distriutions of meteorologicl prmeters in the study re were estimted for grid points with 1-m spcing. One of the vlnches cused disster in which cr ws pushed wy from the rod into vlley on 24 th Decemer. The snow depth incresed y out 7cm within 24 hours; this cused lrge lod efore densifiction. Thus, snow stility decresed. This ws reproduced y the SNOWPACK model. Further, the stility index mps showed tht most of slopes were dngerous on tht dy. KEYWORDS: SNOWPACK model, vlnche forecsting, hevy snow, stility index 1. INTRODUCTION In the winter of 25/26, the region long the Se of Jpn received record-reking snowfll. Hundred nd fifty one people perished due to snow dissters such s ccidents during the removl of snow, snow flling from the roof of houses, nd vlnches. The Jpn Meteorologicl Agency termed this winter of heve snowfll s Heisei 18-nen Gousetsu. The res most ffected due to this hevy snowfll re locted in Tunn, Niigt prefecture, Jpn. The depth of the snow in this region ws greter thn 4 m. Route 45, ntionl rod tht psses the mountinous regions etween the Niigtprefecture nd the Ngno- prefecture, ws exposed to n vlnche risk nd ws therefore closed. Further, the people living in these mountinous res were isolted. In such situtions, the estimtion of the proility of n vlnche event would hve een useful to decide whether the rod should hve een opened. Some professionls conducted field survey nd reported their findings to rod dministrtor. In ddition to this, computtionl forecsting is useful tool ecuse it cn simulte the snow conditions nd the snow stility index tht chnges hourly. A computtionl model SNOWPACK for vlnche forecsting ws developed in Switzerlnd (Lehning et l. (22), Lehning et l. (22), Brtelt et l. (22)). It cn lso simulte the stility index (Lehning et l, 24) nd forecst vlnches y comining 3D model of surfce process in steep terrin (ALPINE3D, Lehning et l(24)). 54

2 The SNOWPACK model ws introduced in Jpn. It ws pplied to the Honshu- re (Ymguchi et l., 24) nd the Hokkido- re (Hirshim et l., 24); nd ws therey modified for ppliction for Jpnese winters. SNOWPACK simultions for complex terrin were crried out y Nishimur et l. (25) y comining the SNOWPACK model nd the snow redistriution model (Liston nd Sturm (1998), Hirshim et l. (24)). The vlidtion of the vlnche forecsting y Nishimur et l. (25) focused on the exmple of sl vlnche. In this study, the vlnche forecsting model ws pplied round route 45, which is wet nd is hevy snow re. This pper discusses suitle prmeteriztion for estimting the stility index, predictle vlnche types, nd future issues for n ccurte vlnche forecsting. 2. STUDY SITE The study site Tunn ( N, E), Niigt prefcture, Jpn is n re of hevy snowfll. Figure 1 shows loction nd mps of the study re. The mximum snow depth this yer ws 416 cm, wheres it is 215 cm for n verge yer. Since this re lies in temperte region in snowy re, fceted crystls nd depth hor re rrely formed. Avlnches tend to occur during hevy snowfll nd on wrm dys. The Automted Meteorologicl Dt Acquisition System operted y the Jpn Meteorologicl Agency (AMEDAS) oserves ir temperture, wind speed, wind direction, precipittion, durtion of sunshine, nd snow depth. The AMEDAS dt ws used s model input dt. Since the AMEDAS does not oserve solr rdition nd longwve rdition, the empiricl equtions suggested y Kondo et l. (1991) were used in order to estimte them. The input solr rdition S (Wm -2 ) ws clculted s follows y using the incident solr rdition t the top of the tmosphere S (Wm -2 ) nd the durtion of sunshine. S N N S < L 1 = N N N.144S = LLLLLLL N (1) Figure 1: Study re (:Loctions of Tunn, Yuzw, nd Nyuto, :Mp of Tunn). The dotted rectngle shows the re simulted. The solid rectngle shows the re of Fig d S = I cosθ (2) d Where, N is the durtion of sunshine; N, the possile durtion of sunshine; I, the solr constnt ( = 1365 Wm -2 ); d, the distnce etween the erth nd the sun; d, the verge of distnce etween the erth nd sun; nd θ, is the zenith ngle. Longwve rdition is lso estimted from meteorologicl dt s follows: L = σt Tunn Nyuto Yuzw 2 4 6km 4 [ 1 ( 1 χ ) C] (3) 3 2 N N N < L = N N N C.2235LLLLLLLLLLLLLLLLLLL 2 χ = x +.7x N N N N 1 = where x is the logrithm of the column effective wter vpour. 3. OBSERVATIONS 3.1 Snow pit oservtions Mitm Mitm Skm ki Mekur Akinr Border i orde of Niigt-Ngno r 5 1km Snow pit oservtions were crried out from Jnury to Mrch t the AMEDAS point t 1- dy intervls. The snow conditions oserved re shown in Fig. 2. The snow profiles showed tht the snow comprises new snow, decomposed Tunn urn re (4) 55

3 Snow depth(cm) Snow depth(cm) new snow rounded grins 1/25 2/2 Figure 2: Snow cover structures for ech oserved dy. The left profiles re the oserved results, nd those on the right re the simulted ones. snow, rounded grins, nd wet grins. However, no fceted grins nd depth hor were oserved. The wet grins oserved t the ottom lyer were formed t the eginning of winter. The wet grins t the middle lyer were formed on 14 th nd 15 th, Jnury, which were wrm dys with rinfll. Most of the lyers ecme wet grins fter 2 th Ferury. 3.2 Remote sensing 2/1 2/2 2/27 3/5 //decomposed snow wet grins Remote sensing oservtions were crried out for topogrphic surveys nd vlnche detections. First, the topogrphic surveys y lser mesurements were crried out using n ALS5 Airorne Lser Scnner nd ircrft on 25 th Ferury, 26 in order to evlute the distriution of snow depth. This depth distriution cn e otined from the difference etween the surfce ltitude of the ground surfce in snow seson nd in non- snow seson. Since the topogrphic dt of the non- snow seson were not otined from the lser mesurement, 1-m mesh DEM, which ws otined from 1:25 mp of the Geogrphicl Survey Institute (GSI), ws sustituted for topogrphic dt for the non- snow seson. Since the error in topogrphic dt ws too lrge for estimting the snow depth y sutrction, the snow depth otined ws of poor qulity. Therefore, the lser mesurements in the non- snow seson need to e crried out in order to correct the snow depth distriution. This is under considertion. Second, eril photogrphs were tken in order to develop the vlnche distriution mp on 5 th Mrch. Hundred nd sixty four surfce vlnches nd five full- depth vlnches were detected in n re of 4.2km 2. Further, 5.9% res were ffected y vlnches. The slope ngles of frcture line (α) nd sighting ngles from the extreme runout position to the top of the strting point (β) were estimted for ech vlnche. The frequency distriutions of α nd β for surfce vlnches re shown in Fig. 3. The verge vlue of α ws 41.2º. Two-thirds of vlnches (out 69%) occur for slopes with inclintions etween 35º to 45º (Fig.3). This result shows tht vlnches frequently occur vlnches (%) vlnches (%) α β Figure 3: Frequency distriution of α nd β for surfce vlnche. 56

4 more steep slopes thn the result of frcture line study conducted y McClung nd Scherer (1993). The verge vlue of β ws 37.9º. Further, 88.6% of β of vlnches rnged 3-45º (Fig.3). 4. NUMERICAL SIMULATIONS 4.1 SNOWPACK result Simulted snow profiles re shown in Fig. 4. Snow ccumultion egins in erly Decemer. The snow depth pproched out 4 m in erly Jnury. Since snow metmorphosed under smll temperture grdient conditions, fceted grins nd depth hor were rrely formed. On 14 th nd 15 th Jnury, the upper lyer snow metmorphosed to wet grins since they were wrm dys with rinfll. All the snow lyers were trnsformed into wet grins on 15 th Ferury. The comprisons etween the oserved snow types re shown in Fig. 2. The simulted snow profiles greed firly well with the oserved result. However, the simulted results ppered to overestimte snowmelt. One of the cuses of this discrepncy is the shortwve nd longwve rdition tht ws estimted using n empiricl eqution. 4.2 Estimtion of snow stility index Snow stility index (SI) is the sher strength divided y the sher stress. The clculted profiles of SI re shown in Fig.4. The SI of compcted snow lyer ws out 1. from erly Jnury to middle Ferury. Thus, the compcted snow ppered to e wek lyer, nd this dngerous sitution lsted longer thn month. However, in fct, compcted snow is stle ginst n vlnche. The originl SNOWPACK model estimtes sher strength using the empiricl eqution suggested y Jmieson nd Johnston (21) who formulted the reltionship etween the sher strength nd the snow density for ech snow type. This reltionship ws derived for reltively light snow (less thn 27 kg/m 3 ). However, in hevy snow re, the snow density t the lower lyer exceeds 4kg/m 3 even if the snow is dry. Thus, the equtions of Jmieson nd Johnston (21) re not suitle for estimting sher strength in such hevy snow re. This formul underestimted the /1 1/1 2/1 3/1 4/1 ++new snow rounded grins //decomposed snow wet grins 1 12/1 1/1 2/1 3/1 4/ /1 1/1 2/1 3/1 4/1 c Stility index Figure 4: Simulted snow profile t the Tunn AMEDAS point. : snow type, : SI clculted using the originl SNOWPACK, c: SI clculted using the eqution of Ymnoi nd Endo(22) nd Ae et l. (25). 57

5 sher strength of hevy snow. Further, rounded grins t the lower lyer were considered s unstle lthough compcted snow t the lower lyer is in fct stle. Therefore, n lternte formul is needed for mesuring sher strength for hevy snow. The reltionships etween snow density nd sher strength hve lso een studied in Jpn. Ymnoi nd Endo (22) formulted the sher strength σ (Nm -2 ) s: θ Kρ 2 dry (5) σ = e where ρ dry is the dry density; θ, the volumetric wter content; nd K, constnt tht is determined experimentlly y the snow type. K is for new snow, decomposed snow nd rounded grins, nd on wet grins. This formultion ws derived from snow where densities rnge from 5 kgm -3 to 5 kgm -3. The sher strength of fceted grins nd depth hor is formulted y Ae et l. (25) s follows: 2 σ = K exp( ρ dry ) (6) where K is This formultion ws derived from snow densities rnging from 15 kgm -3 to 35 kgm -3. Ymnoi et l. (24) formulted sher strength depending on the hrdness mesured y digitl push guge. This eqution is expressed s: 1.18 σ =.18H (7) where H is hrdness (Nm -2 ). The hrdness profiles were mesured on 27 th Ferury. On tht dy, ll the snow lyers were wet, nd unfortuntely no hrdness dt for dry snow could e mesured in the snow pit oservtions t Tunn. However, the hrdness profiles for dry snow were oserved t Yuzw, which is locted out 13km southest of Tunn on 4 th Jnury. The sher strength profiles were estimted using these hrdness profiles nd Eq. (7). Further, sher strengths were clculted from snow types nd snow densities y using the equtions y Ymnoi nd Endo (22) (Eq. (5)), Jmieson nd Johnston (21), nd Perl (1982). The comprisons etweenn these estimtions re shown in Fig. 5. The men is error (MBE), the root men squre error (RMSE) nd the correltion coefficient (r 2 ) for ech eqution compred with the vlue estimted from hrdness re shown in Tle. 1. Oviously, the sher strengths estimted y Ymnoi nd Endo (22) exhiited the smllest error for the dry snow condition. Thus, their estimtion is most suitle for this region. On the other hnd, the errors for wet snow were comprle with the eqution of Perl (1982). Equtions (5) nd (6) were incorported into SNOWPACK. The simulted result using new prmeteriztion ws shown in Fig. 4c. The SI decresed during hevy snowfll, nd wet grins sometimes served s wek lyer E+ 1.E+1 1.E+2 1.E+3 1.E+4 1.E+5 1.E+6 Sher strength(p) Estimtion from hrdness Ymnoi nd Endo(22) Jmieson nd Johnston(21),A(ρ/ρice)B Jmieson nd Johnston(21),A+Bln(ρ/ρice) Pelr et l.(1982) 1.E+ 1.E+1 1.E+2 1.E+3 1.E+4 1.E+5 1.E+6 Sher strength(p) Estimtion from hrdness Ymnoi nd Endo(22) Pelr et l.(1982) Figure 5: Comprisons of ech estimtion technique for SI. Estimted vlue from hrdness is used s true vlue. : profiles of sher strength t Yuzw where snow ws dry. : profiles t Tunn where snow ws wet. 58

6 Tle 1: MBE, RMSE, nd r 2 for ech clculted results compred with estimted vlue from hrdness. In the column of Jmieson nd Johnston (21), (1) is the result using the eqution formulted y liner regression of lnσ=a+b (ρ/ρ ice ) nd (2) is the result of σ=a(ρ/ρ ice ) B. Jmieson Jmieson Ymnoi nd nd Johnston nd Johnston Perl et l. Endo (22) (21) (1) (21) (2) (1982) MBE RMSE r c Stility index Figure 6: Simulted SI mps. : 23 rd, :24 th, nd c:25 th in Decemer. White circles on lck ckground indicte the position of the vlnche point. 4.3 Simultions for the re of route 45 SI distriution mps were chrted using 1-m mesh round route 45. GISMAP Terrin 1-m mesh DEM otined from 1:25, mps of GSI ws used s topogrphic dt. Locl vrition of meteorologicl conditions such s ir temperture, solr rdition, nd wind speed were clculted using techniques similr to those of Nishimur et l. (25). As n exmple, the SI mps etween 23 rd nd 25 th Decemer re shown in Fig. 6. The SI mps show tht most of the steep slopes were suject to vlnche dnger on 24 th Decemer despite eing reltively sfe on the previous nd next dys. In fct, on tht dy, the vlnche tht occurred pushed cr wy from the rod into the vlley. Thus, this region ws vlnche prone. The profiles for snow type nd SI round the dy of the vlnche re shown in Fig. 7. The SNOWPACK result shows tht SI decreses in new snow lyer. The snow depth incresed y out 7cm within 24 hours. This leds to n unstle snow condition since the snow ws strongly loded with newer snow efore /23 12/24 12/25 12/26 12/27 ++new snow //lightly compcted snow compcted snow grnulr snow /23 12/24 12/25 12/26 12/ Stility index Figure 7: SNOWPACK result round the dy of vlnche. : snow structure, : SI 59

7 densifiction. The wek lyer ws not detected in the snow pit oservtion of 25 th Decemer. However, the depth of the new snow lyer exceeded 4cm. The simulted result reproduced this condition well. 5 DISCUSSION 5.1 Predictility of n vlnche ccident SNOWPACK simultion needs meteorologicl input. However, vlnche ccidents do not occur in loctions tht re complete with meteorologicl instruments. Thus, meteorologicl dt of some distnce (out 1 km on n verge) hve to e used. Moreover, the use of n estimte eqution for non-oserved prmeters (solr nd long wve rdition in this study cse) leds to n increse in simultion errors. Nevertheless, the vlnche due to hevy snowfll round route 45 could hve een predicted y using this method. Severl lrge vlnche ccidents occurred in other regions in this yer. SNOWPACK simultions were crried out when these vlnche ccidents occurred. In this pper, two exmples of comprisons etween the SNOWPACK simultions nd the vlnche ccidents re discussed. One is the vlnche tht occurred t Yuzw, Niigt- prefecture, nd the other is the one tht occurred t Nyuto-Onsen, Akit- prefecture. () vlnche t Yuzw Figure 1 lso shows the loction of Yuzw where some vlnche ccidents occurred. Lrge scle vlnche with deris size m 3 occurred on 28 th Decemer t Tuchitl (out 1 km south-southest from the Yuzw urn re). The verticl drop etween the vlnche genertion point nd the deris deposited re ws more thn 6 m. The vlnche hit nd uprooted n electric pole nd snpped the wires. Furthermore, severl vlnches occurred on 3 rd nd 4 th Jnury t three ski res nd ntionl rod route 17, which connects Tokyo nd Niigt. The SNOWPACK simultion ws crried out y using the AMEDAS meteorologicl dt of Yuzw nd the snow depth dt of Tuchitl (sttion nerest to the vlnche point) s the model input dt. When the vlnche ccident occurred t Tutitl (on 28 th Decemer), the SI declined to 1.4 in the new snow lyer. Hevy snowfll nd collpse of new snow lyer pper to e the cuses of the vlnche, similr to the vlnche discussed in section 4.3. While severl vlnches occurred (from 3 rd nd 4 th Jnury), the SI rnged in the new snow lyer. Rounding fcets, which is n intermedite condition etween decomposed snow nd fceted grins, were detected. Such lyer ws lso detected in snow pit oservtion crried out on Jnury 4 th. Although the oserved SI ws 1.8 t the rounding fcets lyer, the simulted SI ws 3.. The clculted sher strength of the rounding fcets ws similr to tht of decomposed snow. If sher strength ws clculted s fceted grins, it would hve een.7. This result suggests tht the estimtion of sher strength for intermedite condition is importnt for the vlnche prediction generted y the filure of the intermedite snow types. () vlnche t Nyuto Onsen Most lrge vlnche ccidents in this winter occurred on 1 th Ferury t Nyuto-onsen, which is hot spring resort in the Akit- prefecture. The vlnche occurred t three points on the northwest fcing slope, resulting in the deth of one nd the injury of 16 people. The ir temperture nd the snow depth oserved ner the vlnche point ws used s model input dt. The other meteorologicl prmeters were otined from AMEDAS t Tzwko, which is locted out 12.6 km southwest from the vlnche point. The SNOWPACK simultion showed tht the SI declined to 1.7 in new snow lyer when n vlnche ccident occurred. A reltively wek lyer ws detected 1 cm under the surfce. This lyer ws lso detected y snow pit oservtion crried out on 11 th Ferury. Both the oserved SI nd the simulted SI were 2.9; these vlues were too lrge to generte n vlnche. Thus, this vlnche ppers to e generted y the collpse of the new snow. 5.2 Future issues 6

8 Destiliztion during hevy snowfll ws predicted y the SNOWPACK model. However, some issues exist. First, SI declines remrkly in most of steep slopes during hevy snowfll (Fig. 6). The specifiction of dngerous loction of n vlnche is difficult t present. One of the useful methods to specify dngerous plce is the prediction of snow cornice. The snow cornice cn e predicted y simulting snow redistriution. It hs to e vlidted y using the oserved snow depth distriution. Since topogrphic surveys using lser mesurements in snowy seson hve lredy een crried out, snow depth distriution cn e otined y lser mesurement during the non- snow seson mentioned in section 3.2. Then, the ccurcy enhncement for vlnche prediction will e fvourle. Second, surfce vlnches due to the filure of wet grins nd full depth vlnches s well s the vlnches cused y collpse of new snow often occur in temperte snowy re. The sher strength of wet grins declines exponentilly with volumetric wter content (Ymnoi nd Endo, 22). Full depth vlnches tend to occur when liquid wter (snowmelt wter or rin) rrives t the oundry of the ground. Accurte simultion for moisture movement in the snowpck is necessry for the prediction of these vlnches. The moisture movement scheme in the SNOWPACK model is tht the liquid wter moves downwrds when exceeds certin vlue. However, the ove two vlnche types re ffected y more complex wter movement. Thus, we pln to develop numericl snowpck model considering existence regime of liquid wter (cpillry regime, pendulr regime, nd funiculr regime (Coleck, 1973)), the formtion of wter pss, nd the wter movement through the wter pss (Coleck, 1978). 6. CONCLUSIONS Appliction of the snow cover model SNOWPACK to vlnche forecsting for hevy snow re ws crried out. Snow pit oservtions were lso crried out in 1- dy intervls. During this winter, snow depth exceeded 4m in the study region, Tunn. The pit oservtions reveled tht the snowpck comprises new snow, decomposed snow, rounded grins, nd wet grins without fceted grins nd depth hor. The profiles simulted y the SNOWPACK model greed with the oserved profiles firly well. However, the equtions for stility index (SI) were not suitle for this study re. The empiricl equtions formulted y Ymnoi nd Endo (22) nd Ae et l. (25) were incorported to clculte SI. Then, the clculted SI greed etter with the SI estimted from the hrdness. In order to expnd the forecsting re to include route 45, ntionl rod, we used dt from n AMEDAS nd DEM with grid size of 1 m. The distriution of meteorologicl prmeters were estimted nd used for the SNOWPACK simultion in order to otin the distriution of SI. The SI mps showed considerle decline during the hevy snowfll; however, they stilized fter the snow stopped. Avlnche ccidents occurred when the SI mps depicted n unstle condition. Further, it ws shown tht this model cn e used for vlnche prediction. However, numer of improvements re necessry. The specifiction of dngerous vlnche loction is still difficult since the chrcteristic of snow depth distriution is uncler. However, it is expected to e clrified y lser mesurement. Modelling liquid wter movement is lso n importnt issue for temperte nd hevy snow region like this study region. We re plnning to develop Jpnese snowpck model tht focuses on liquid wter movement in the snowpck. ACKNOWLEDGEMENT This study ws supported y Specil Coordintion Fund for the Promotion of Science nd Technology, nd grnt from the Ministry of Eduction, Science, Sports nd Culture, Jpn (No. 1786: principl investigtor A. Sto). We specilly thnk T. Sto nd M. Nemoto of the NIED, nd K. Izumi nd K. Kwshim of the Niigt University for their ssistnce with the snow pit oservtions. We re lso grteful to Highlnd Agriculturl Technology Center for providing us with plce for crring out the oservtions. REFERENCES 61

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