Hang Su , Xin-Yue Zhong , Bin Cao , Yuan-Tao Hu , Lei Zheng , Tingjun Zhang
{"title":"使用不同方法测量积雪密度的比较","authors":"Hang Su , Xin-Yue Zhong , Bin Cao , Yuan-Tao Hu , Lei Zheng , Tingjun Zhang","doi":"10.1016/j.accre.2024.07.005","DOIUrl":null,"url":null,"abstract":"<div><p>Snow density is one of the basic properties used to describe snow cover characteristics, and it is critical for remote sensing retrieval, water resources assessment and modeling inputs. There are many instruments available to measure snow density <em>in situ</em>. However, there are measurement errors of snow density for bulk and layers or gravimetric and electronic instruments, which may affect the accuracy of remote sensing retrieval and model simulation. Especially in China, due to the noticeable heterogeneity of snowpacks, it is necessary to evaluate in detail the performance and applicability of snow density instruments in different snowpack conditions. This study evaluated the performance of different snow density instruments: the Federal Sampler, the model VS–43 snow density cylinder (VS–43), the wedge snow density cutter (WC1000 and WC250), and the Snow Fork. The average bulk snow density of all instrument measurements was set as the reference value for evaluation. The results showed that as compared with the reference, the VS–43 cylinder presented the best performance for bulk snow density measurement in the measured range with the lowest RMSE (11 kg m<sup>−3</sup>), BIAS (3 kg m<sup>−3</sup>), and MRE (1.6%). For layer observation, bulk snow density was overestimated by 8.1% with WC1000 and underestimated by 11.4% with Snow Fork which was the worst performance compared with the reference value, and there were greater measurement errors of snow density in the depth hoar than other snow layers. Compared with grassland, the uncertainty of snow density measurements was slightly lower in forests. Overall, the Federal Sampler and VS–43 cylinder are more suitable for bulk snow density measurement in deep snowpack regions across China, and it is recommended to use WC1000, WC250 and Snow Fork to measure the snow density of snow layers in the snow stratigraphy.</p></div>","PeriodicalId":6,"journal":{"name":"ACS Applied Nano Materials","volume":null,"pages":null},"PeriodicalIF":5.3000,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1674927824001059/pdfft?md5=a0854ea767ae2730e730177c84936b5c&pid=1-s2.0-S1674927824001059-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Comparison of bulk snow density measurements using different methods\",\"authors\":\"Hang Su , Xin-Yue Zhong , Bin Cao , Yuan-Tao Hu , Lei Zheng , Tingjun Zhang\",\"doi\":\"10.1016/j.accre.2024.07.005\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Snow density is one of the basic properties used to describe snow cover characteristics, and it is critical for remote sensing retrieval, water resources assessment and modeling inputs. There are many instruments available to measure snow density <em>in situ</em>. However, there are measurement errors of snow density for bulk and layers or gravimetric and electronic instruments, which may affect the accuracy of remote sensing retrieval and model simulation. Especially in China, due to the noticeable heterogeneity of snowpacks, it is necessary to evaluate in detail the performance and applicability of snow density instruments in different snowpack conditions. This study evaluated the performance of different snow density instruments: the Federal Sampler, the model VS–43 snow density cylinder (VS–43), the wedge snow density cutter (WC1000 and WC250), and the Snow Fork. The average bulk snow density of all instrument measurements was set as the reference value for evaluation. The results showed that as compared with the reference, the VS–43 cylinder presented the best performance for bulk snow density measurement in the measured range with the lowest RMSE (11 kg m<sup>−3</sup>), BIAS (3 kg m<sup>−3</sup>), and MRE (1.6%). For layer observation, bulk snow density was overestimated by 8.1% with WC1000 and underestimated by 11.4% with Snow Fork which was the worst performance compared with the reference value, and there were greater measurement errors of snow density in the depth hoar than other snow layers. Compared with grassland, the uncertainty of snow density measurements was slightly lower in forests. Overall, the Federal Sampler and VS–43 cylinder are more suitable for bulk snow density measurement in deep snowpack regions across China, and it is recommended to use WC1000, WC250 and Snow Fork to measure the snow density of snow layers in the snow stratigraphy.</p></div>\",\"PeriodicalId\":6,\"journal\":{\"name\":\"ACS Applied Nano Materials\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":5.3000,\"publicationDate\":\"2024-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S1674927824001059/pdfft?md5=a0854ea767ae2730e730177c84936b5c&pid=1-s2.0-S1674927824001059-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Applied Nano Materials\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1674927824001059\",\"RegionNum\":2,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MATERIALS SCIENCE, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Nano Materials","FirstCategoryId":"89","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1674927824001059","RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, MULTIDISCIPLINARY","Score":null,"Total":0}
Comparison of bulk snow density measurements using different methods
Snow density is one of the basic properties used to describe snow cover characteristics, and it is critical for remote sensing retrieval, water resources assessment and modeling inputs. There are many instruments available to measure snow density in situ. However, there are measurement errors of snow density for bulk and layers or gravimetric and electronic instruments, which may affect the accuracy of remote sensing retrieval and model simulation. Especially in China, due to the noticeable heterogeneity of snowpacks, it is necessary to evaluate in detail the performance and applicability of snow density instruments in different snowpack conditions. This study evaluated the performance of different snow density instruments: the Federal Sampler, the model VS–43 snow density cylinder (VS–43), the wedge snow density cutter (WC1000 and WC250), and the Snow Fork. The average bulk snow density of all instrument measurements was set as the reference value for evaluation. The results showed that as compared with the reference, the VS–43 cylinder presented the best performance for bulk snow density measurement in the measured range with the lowest RMSE (11 kg m−3), BIAS (3 kg m−3), and MRE (1.6%). For layer observation, bulk snow density was overestimated by 8.1% with WC1000 and underestimated by 11.4% with Snow Fork which was the worst performance compared with the reference value, and there were greater measurement errors of snow density in the depth hoar than other snow layers. Compared with grassland, the uncertainty of snow density measurements was slightly lower in forests. Overall, the Federal Sampler and VS–43 cylinder are more suitable for bulk snow density measurement in deep snowpack regions across China, and it is recommended to use WC1000, WC250 and Snow Fork to measure the snow density of snow layers in the snow stratigraphy.
期刊介绍:
ACS Applied Nano Materials is an interdisciplinary journal publishing original research covering all aspects of engineering, chemistry, physics and biology relevant to applications of nanomaterials. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrate knowledge in the areas of materials, engineering, physics, bioscience, and chemistry into important applications of nanomaterials.