地表高程变化、土壤湿度和积雪 深度都是研究活动动态的基本变量 层和永久冻土。GPS干涉反射仪（GPS-IR）已经 用于测量永久冻土中的地表高程变化和积雪深度 地区。然而，它在估计多年冻土土壤水分方面的适用性 尚未对区域进行评估。此外，这些变量通常是 在不同地点分别测量。将他们的估计整合为一个 场地促进多年冻土中GPS-IR的综合利用 研究。在这项研究中，我们运行模拟来阐明 常用的GPS-IR算法估算土壤含水量不能 直接用于永久冻土区，因为它不考虑偏差 由活动层引起的季节性表面高程变化引入 解冻。我们提出了一个解决方案来改进这种默认方法，方法是引入 建模的表面高程变化。我们使用 GPS数据和在永久冻土场的原位观测 青藏高原东北部。均方根误差和 GPS-IR估计土壤水分的相关系数 含量和原位含量从1.85%提高到1.51%，从0.71提高到 分别为0.82。我们还提出了一个集成GPS-IR的框架 在一个地点估计这三个变量，并使用 以 QTP 中的同一站点为例。这项研究强调了对 默认算法，使 GPS-IR 在估算土壤时有效 永久冻土区的水分含量。三合一框架能够 在永久冻土区充分利用GPS-IR，并可扩展到其他 诸如北极的地点。这项研究也是第一个使用 GPS-IR 用于估计 QTP 中的环境变量，该变量填充空间 间隙并提供对地面温度和活动的补充测量层厚。
", "ds_source": "青藏高原东北部多年冻土场地表高程变化、土壤湿度和积雪深度的 GPS-IR 测量
", "ds_process_way": "使用 GPS数据和在永久冻土场的原位观测
", "ds_quality": "数据质量良好
", "ds_acq_start_time": "2018-01-01 00:00:00", "ds_acq_end_time": "2018-12-31 00:00:00", "ds_acq_place": "青藏高原东北部", "ds_acq_lon_east": 100.4, "ds_acq_lat_south": 38.0, "ds_acq_lon_west": 100.4, "ds_acq_lat_north": 38.0, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "open-access", "ds_total_size": 3913, "ds_files_count": 4, "ds_format": "Excel", "ds_space_res": null, "ds_time_res": "年", "ds_coordinate": "无", "ds_projection": "", "ds_thumbnail": "d3650b70-bff8-4ad2-9fc0-2c0260b44ee3.png", "ds_thumb_from": 2, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "", "ds_from_station": null, "organization_id": "0a4269e1-65f4-45f1-aeba-88ea3068eebf", "ds_serv_man": "敏玉芳", "ds_serv_phone": "0931-4967596", "ds_serv_mail": "ncdc@lzb.ac.cn", "doi_value": "", "subject_codes": [ "170.4510" ], "quality_level": 3, "publish_time": "2023-07-25 14:58:57", "last_updated": "2025-06-30 16:20:07", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.NCDC.ZENODO.DB3947.2023", "i18n": { "en": { "title": "GPS-IR Measurements of Surface Elevation Changes, Surface Soil Moisture, and Snow Depth in the Permafrost Zone of the Northeastern Tibetan Plateau", "ds_format": "Excel", "ds_source": "&Emsp;GPS-IR Measurements of Surface Elevation Changes, Soil Moisture and Snow Depth in a Perennial Permafrost Field on the Northeastern Qinghai-Tibetan Plateau
", "ds_quality": "&Emsp; Good quality of data
", "ds_ref_way": "", "ds_abstract": "&Emsp Surface elevation change, soil moisture and snow depth are all essential variables for studying the dynamics of activity in permafrost and permafrost. GPS interferometric reflectometer (GPS-IR) has been used to measure surface elevation change and snow depth in permafrost in the region. However, its applicability in estimating soil moisture in permafrost has not been assessed regionally. In addition, these variables are usually measured separately at different locations. Integrating their estimates into a single site promotes a comprehensive utilization study of GPS-IR in permafrost. In this study, we run simulations to illustrate that the commonly used GPS-IR algorithm for estimating soil water content cannot be directly used in permafrost regions because it does not account for the bias introduced by seasonal surface elevation changes caused by the active layer to thaw. We propose a solution to improve this default method by introducing modeled surface elevation changes. We use GPS data and in situ observations in a permafrost field on the northeastern Tibetan Plateau. The correlation coefficients of the root mean square error and GPS-IR estimates of soil moisture content and in situ content improved from 1.85% to 1.51% and from 0.71 to 0.82, respectively, and we also present a framework for integrating GPS-IR to estimate these three variables at a single site, using the same site in the QTP as an example. This study emphasizes on the default algorithm to make GPS-IR effective in estimating soil moisture content in permafrost areas. The 3-in-1 framework is able to fully utilize GPS-IR in the permafrost region and can be extended to other sites such as the Arctic. This study is also the first to use GPS-IR for estimating environmental variables in the QTP that fill spatial gaps and provide complementary measurements of ground temperature and activity layer thickness.
", "ds_time_res": "年", "ds_acq_place": "Northeast Tibetan Plateau", "ds_space_res": "", "ds_projection": "", "ds_process_way": "Use of GPS data and in-situ observations in permafrost fields
", "ds_ref_instruction": "" } }, "submit_center_id": "ncdc", "data_level": 0, "license_type": "CC BY 4.0", "doi_reg_from": "reg_outside", "cstr_reg_from": "reg_outside", "doi_not_reg_reason": null, "cstr_not_reg_reason": null, "is_paper_in_submitting": false, "ds_topic_tags": [ "积雪深度", "地面标高", "地表土壤湿度" ], "ds_subject_tags": [ "自然地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "青藏高原东北部" ], "ds_time_tags": [ 2018 ], "ds_contributors": [ { "true_name": " 刘琳", "email": "liulin@cuhk.edu.hk", "work_for": "香港中文大学科学学院地球系统科学", "country": "中国" }, { "true_name": "车涛", "email": "chetao@lzb.ac.cn", "work_for": "中国科学院西北生态环境资源研究院", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "车涛", "email": "chetao@lzb.ac.cn", "work_for": "中国科学院西北生态环境资源研究院", "country": "中国" } ], "ds_managers": [ { "true_name": "车涛", "email": "chetao@lzb.ac.cn", "work_for": "中国科学院西北生态环境资源研究院", "country": "中国" } ], "category": "冻土" }