The main goal of this study has been to map flood and assess land surface short-term dynamics in relation with snowy weather. The two recent snowfall events, which happened in, February 14<sup>th</sup> and...The main goal of this study has been to map flood and assess land surface short-term dynamics in relation with snowy weather. The two recent snowfall events, which happened in, February 14<sup>th</sup> and 15<sup>th</sup>, of year 2021, and February 3<sup>rd</sup> and 4<sup>th</sup>, of year 2022, were chosen. A pre-analysis correlation was assumed between, the snow events, recurrency of floods, and changes in the land surface characteristics (i.e., wetness, energy, temperature), in a “Before-During-After” scenario. Active and passive microwave satellites data such as, Sentinel-1 synthetic aperture radar (SAR), Sentinel-2 multispectral instrument (MSI) and Landsat-9 Operation Land Imager-2/Thermal Infrared Sensors-2 (OLI-2/TIRS-2), as well as cloud databased global models for water and urban layers were used. The first step of processing was thresholding of SAR image, at 0.25 cutoff, based on bimodal histogram distribution, followed by the change analysis. The following processing consisted in the images transformation, by computing the tasseled cap transformation wetness (TCTw) and the surface albedo on MSI image. In addition, the land surface temperature (LST) was modeled from OLI-2/TIRS-2 image. Then, a 5<sup>th</sup> order polynomial regression was computed, between TCTw as dependent variable and, albedo and LST as independent variables. As a first result, an area of 5.6 km<sup>2</sup> has been mapped as recurrently flooded from the two years assessment. The other output highlighted a constant increase of wetness (TCTw), considered most influential on land surface dynamics, comparatively to energy exchange (albedo) and temperature (LST). The “After” event dependency between the three indicators was highest, with a correlation coefficient, R<sup>2</sup> = 0.682, confirming the persistence of wetness after-snowmelt. Validation over topographic layers confirmed that, recurrently flooded areas are mostly distributed on, lowest valley depth points, farthest distances from channel network (i.e., from perennial waters), and lowest relative slope position areas. Whereas, 88.9% of the validation sampling were confirmed in the laboratory, and 86.7% of urban validation points were assessed as recurrently flooded when combining pre-/post-field-work campaign.展开更多
新疆春季积雪融化极易引发融雪性洪水,给当地的农牧业生产和人民生活都带来严重影响和财产损失.融雪中包含复杂的水-热耦合过程,融雪水产流机制受冻土影响,融雪洪水模拟与预报十分复杂,一直是水文研究的难点.新疆大学刘志辉研究团队长...新疆春季积雪融化极易引发融雪性洪水,给当地的农牧业生产和人民生活都带来严重影响和财产损失.融雪中包含复杂的水-热耦合过程,融雪水产流机制受冻土影响,融雪洪水模拟与预报十分复杂,一直是水文研究的难点.新疆大学刘志辉研究团队长期开展季节性融雪洪水模拟与预报研究,在积雪特性监测、冻土融雪水产流机制、分布式融雪径流模型以及融雪洪水预警等方面进行了深入研究.首次提出冻土条件下的融雪水的三个产流机制,即冻土未融化时的超渗产流、冻土部分融化时的饱和产流以及冻融期的交替产流;基于热量平衡和水量平衡研制出分布式融雪径流模型,耦合WRF(Weather Research and Forcasting model)模型实现融雪洪水预报;研制出新疆融雪洪水预警决策支持系统,实现融雪洪水预警系统的应用.研究成果有助于融雪洪水模拟的进一步研究,也为政府部门融雪洪水预警决策提供科学依据.展开更多
文摘The main goal of this study has been to map flood and assess land surface short-term dynamics in relation with snowy weather. The two recent snowfall events, which happened in, February 14<sup>th</sup> and 15<sup>th</sup>, of year 2021, and February 3<sup>rd</sup> and 4<sup>th</sup>, of year 2022, were chosen. A pre-analysis correlation was assumed between, the snow events, recurrency of floods, and changes in the land surface characteristics (i.e., wetness, energy, temperature), in a “Before-During-After” scenario. Active and passive microwave satellites data such as, Sentinel-1 synthetic aperture radar (SAR), Sentinel-2 multispectral instrument (MSI) and Landsat-9 Operation Land Imager-2/Thermal Infrared Sensors-2 (OLI-2/TIRS-2), as well as cloud databased global models for water and urban layers were used. The first step of processing was thresholding of SAR image, at 0.25 cutoff, based on bimodal histogram distribution, followed by the change analysis. The following processing consisted in the images transformation, by computing the tasseled cap transformation wetness (TCTw) and the surface albedo on MSI image. In addition, the land surface temperature (LST) was modeled from OLI-2/TIRS-2 image. Then, a 5<sup>th</sup> order polynomial regression was computed, between TCTw as dependent variable and, albedo and LST as independent variables. As a first result, an area of 5.6 km<sup>2</sup> has been mapped as recurrently flooded from the two years assessment. The other output highlighted a constant increase of wetness (TCTw), considered most influential on land surface dynamics, comparatively to energy exchange (albedo) and temperature (LST). The “After” event dependency between the three indicators was highest, with a correlation coefficient, R<sup>2</sup> = 0.682, confirming the persistence of wetness after-snowmelt. Validation over topographic layers confirmed that, recurrently flooded areas are mostly distributed on, lowest valley depth points, farthest distances from channel network (i.e., from perennial waters), and lowest relative slope position areas. Whereas, 88.9% of the validation sampling were confirmed in the laboratory, and 86.7% of urban validation points were assessed as recurrently flooded when combining pre-/post-field-work campaign.
文摘新疆春季积雪融化极易引发融雪性洪水,给当地的农牧业生产和人民生活都带来严重影响和财产损失.融雪中包含复杂的水-热耦合过程,融雪水产流机制受冻土影响,融雪洪水模拟与预报十分复杂,一直是水文研究的难点.新疆大学刘志辉研究团队长期开展季节性融雪洪水模拟与预报研究,在积雪特性监测、冻土融雪水产流机制、分布式融雪径流模型以及融雪洪水预警等方面进行了深入研究.首次提出冻土条件下的融雪水的三个产流机制,即冻土未融化时的超渗产流、冻土部分融化时的饱和产流以及冻融期的交替产流;基于热量平衡和水量平衡研制出分布式融雪径流模型,耦合WRF(Weather Research and Forcasting model)模型实现融雪洪水预报;研制出新疆融雪洪水预警决策支持系统,实现融雪洪水预警系统的应用.研究成果有助于融雪洪水模拟的进一步研究,也为政府部门融雪洪水预警决策提供科学依据.
