Farzam Fatolazadeh , Shusen Wang , Mehdi Eshagh , Kalifa Goïta
{"title":"利用改进的光谱组合理论从GRACE/GRACE- fo陆地蓄水异常中提取雪水当量","authors":"Farzam Fatolazadeh , Shusen Wang , Mehdi Eshagh , Kalifa Goïta","doi":"10.1016/j.jhydrol.2025.133754","DOIUrl":null,"url":null,"abstract":"<div><div>Snow Water Equivalent (SWE) refers to the quantity of water contained within the snowpack, which is a critical component of the seasonal water cycle in cold regions, notably Canada. The Gravity Recovery and Climate Experiment (GRACE) mission primarily focuses on quantifying Terrestrial Water Storage Anomalies (TWSA), which is the sum of anomalies in groundwater, soil moisture, surface water, and snow/ice. Separating the individual components with high precision is a challenging task due to the complex interactions of these parameters and their uncertainties involved. This study proposes an enhanced estimator which is modified based on the spectral combination theory, to extract the SWE component from GRACE/GRACE-FO (Follow-On) TWS measurements. This estimator uses a hydrological model and its uncertainty to optimally extract the SWE component from the GRACE monthly models in spectral domain. The approach was applied in eight selected basins across Canada, covering a diverse range of climatic and geographical conditions. Different winter seasons of each basin were considered, including the peak accumulation and ablation phases of the snowpack, from January 2003 to the end of 2022. Among the basins examined, the Fraser-Lower Mainland and Ottawa basins exhibited the most pronounced seasonal variations in SWE, with maximum value of about 200 mm. In contrast, the Saint John-St basin demonstrated the lowest SWE variability, with maximum amount of 50 mm. All the studied basins across Canada except for Okanagan-Similkameen basin and Saint John-St basin displayed a positive trend in SWE. The results from the proposed approach were compared to the SWE component derived from Canadian Historical Snow Water Equivalent dataset (CanSWE), Canadian Meteorological Centre (CMC), and GlobSnow. Varying levels of agreement were found depending on the basins (correlations between <em>r</em> = 0.40 and <em>r</em> = 0.83, and RMSE between 10 mm and 55 mm). The best agreements were found with CMC and CanSWE products. The inclusion of streamflow component highlighted the relationship between maximum SWE and the peak flow. The results found indicate significant correlations between SWE derived from our modified spectral combination approach and peak flow in several basins (<em>r</em> varying from 0.42 to 0.80); thus emphasizing the critical role of snowmelt in influencing peak flows in the basins.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"661 ","pages":"Article 133754"},"PeriodicalIF":6.3000,"publicationDate":"2025-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Retrieving snow water equivalent from GRACE/GRACE-FO terrestrial water storage anomalies using modified spectral combination theory\",\"authors\":\"Farzam Fatolazadeh , Shusen Wang , Mehdi Eshagh , Kalifa Goïta\",\"doi\":\"10.1016/j.jhydrol.2025.133754\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Snow Water Equivalent (SWE) refers to the quantity of water contained within the snowpack, which is a critical component of the seasonal water cycle in cold regions, notably Canada. The Gravity Recovery and Climate Experiment (GRACE) mission primarily focuses on quantifying Terrestrial Water Storage Anomalies (TWSA), which is the sum of anomalies in groundwater, soil moisture, surface water, and snow/ice. Separating the individual components with high precision is a challenging task due to the complex interactions of these parameters and their uncertainties involved. This study proposes an enhanced estimator which is modified based on the spectral combination theory, to extract the SWE component from GRACE/GRACE-FO (Follow-On) TWS measurements. This estimator uses a hydrological model and its uncertainty to optimally extract the SWE component from the GRACE monthly models in spectral domain. The approach was applied in eight selected basins across Canada, covering a diverse range of climatic and geographical conditions. Different winter seasons of each basin were considered, including the peak accumulation and ablation phases of the snowpack, from January 2003 to the end of 2022. Among the basins examined, the Fraser-Lower Mainland and Ottawa basins exhibited the most pronounced seasonal variations in SWE, with maximum value of about 200 mm. In contrast, the Saint John-St basin demonstrated the lowest SWE variability, with maximum amount of 50 mm. All the studied basins across Canada except for Okanagan-Similkameen basin and Saint John-St basin displayed a positive trend in SWE. The results from the proposed approach were compared to the SWE component derived from Canadian Historical Snow Water Equivalent dataset (CanSWE), Canadian Meteorological Centre (CMC), and GlobSnow. Varying levels of agreement were found depending on the basins (correlations between <em>r</em> = 0.40 and <em>r</em> = 0.83, and RMSE between 10 mm and 55 mm). The best agreements were found with CMC and CanSWE products. The inclusion of streamflow component highlighted the relationship between maximum SWE and the peak flow. The results found indicate significant correlations between SWE derived from our modified spectral combination approach and peak flow in several basins (<em>r</em> varying from 0.42 to 0.80); thus emphasizing the critical role of snowmelt in influencing peak flows in the basins.</div></div>\",\"PeriodicalId\":362,\"journal\":{\"name\":\"Journal of Hydrology\",\"volume\":\"661 \",\"pages\":\"Article 133754\"},\"PeriodicalIF\":6.3000,\"publicationDate\":\"2025-06-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Hydrology\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0022169425010923\",\"RegionNum\":1,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, CIVIL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Hydrology","FirstCategoryId":"89","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0022169425010923","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, CIVIL","Score":null,"Total":0}
Retrieving snow water equivalent from GRACE/GRACE-FO terrestrial water storage anomalies using modified spectral combination theory
Snow Water Equivalent (SWE) refers to the quantity of water contained within the snowpack, which is a critical component of the seasonal water cycle in cold regions, notably Canada. The Gravity Recovery and Climate Experiment (GRACE) mission primarily focuses on quantifying Terrestrial Water Storage Anomalies (TWSA), which is the sum of anomalies in groundwater, soil moisture, surface water, and snow/ice. Separating the individual components with high precision is a challenging task due to the complex interactions of these parameters and their uncertainties involved. This study proposes an enhanced estimator which is modified based on the spectral combination theory, to extract the SWE component from GRACE/GRACE-FO (Follow-On) TWS measurements. This estimator uses a hydrological model and its uncertainty to optimally extract the SWE component from the GRACE monthly models in spectral domain. The approach was applied in eight selected basins across Canada, covering a diverse range of climatic and geographical conditions. Different winter seasons of each basin were considered, including the peak accumulation and ablation phases of the snowpack, from January 2003 to the end of 2022. Among the basins examined, the Fraser-Lower Mainland and Ottawa basins exhibited the most pronounced seasonal variations in SWE, with maximum value of about 200 mm. In contrast, the Saint John-St basin demonstrated the lowest SWE variability, with maximum amount of 50 mm. All the studied basins across Canada except for Okanagan-Similkameen basin and Saint John-St basin displayed a positive trend in SWE. The results from the proposed approach were compared to the SWE component derived from Canadian Historical Snow Water Equivalent dataset (CanSWE), Canadian Meteorological Centre (CMC), and GlobSnow. Varying levels of agreement were found depending on the basins (correlations between r = 0.40 and r = 0.83, and RMSE between 10 mm and 55 mm). The best agreements were found with CMC and CanSWE products. The inclusion of streamflow component highlighted the relationship between maximum SWE and the peak flow. The results found indicate significant correlations between SWE derived from our modified spectral combination approach and peak flow in several basins (r varying from 0.42 to 0.80); thus emphasizing the critical role of snowmelt in influencing peak flows in the basins.
期刊介绍:
The Journal of Hydrology publishes original research papers and comprehensive reviews in all the subfields of the hydrological sciences including water based management and policy issues that impact on economics and society. These comprise, but are not limited to the physical, chemical, biogeochemical, stochastic and systems aspects of surface and groundwater hydrology, hydrometeorology and hydrogeology. Relevant topics incorporating the insights and methodologies of disciplines such as climatology, water resource systems, hydraulics, agrohydrology, geomorphology, soil science, instrumentation and remote sensing, civil and environmental engineering are included. Social science perspectives on hydrological problems such as resource and ecological economics, environmental sociology, psychology and behavioural science, management and policy analysis are also invited. Multi-and interdisciplinary analyses of hydrological problems are within scope. The science published in the Journal of Hydrology is relevant to catchment scales rather than exclusively to a local scale or site.