A method for quantifying water-sand functional connectivity in cold regions

Abstract

The application discloses a kind of cold region water sand function connectivity quantification method, comprising the following steps: S1: obtaining the basic grid data of study area and pre-processing;S2: determining the source of river in basin and the catchment condition is in GEE platform Catchment sediment transport unit identification;S3: application D-Infinity (DINF) algorithm determines the flow direction of water flow in basin, define the threshold of uphill drainage, and based on both iterative calculation obtains the contribution area of unit;S4: the weighted factor of each unit is written into and calculates the component factor of each unit;S5: the uphill component and downhill component of each catchment sediment transport unit are calculated, combined with S3 iteratively and quantitatively calculated in turn, obtain the entire basin high-resolution cold region water sand function connectivity grid data;The present application breaks through the present situation that existing is not applicable to the calculation of large area cold region basin, can analyze the response of thermal erosion to cold region basin scale, and can also clarify the complex cold region cold region water sand cascade process, and has important significance to cold region ecological protection and landscape evolution research.

Description

Technical Field

[0001] This invention relates to a method for quantifying the functional connectivity of water and sediment in cold regions, belonging to the field of cold region hydrological technology. Background Technology

[0002] Cryosphere degradation is fundamentally reshaping regional hydrological and geomorphological processes, leading to intensified sediment dynamics and profoundly impacting regional and downstream water resource security. Against the backdrop of global climate change, the transport of sediment from surface landscapes to river networks in cold regions is accelerating, directly threatening global water quality, reservoir capacity, and the stability of downstream ecosystems. Water-sediment connectivity is a crucial factor determining the mode, efficiency, and scale of sediment transport in watersheds. It forms the basis for exploring sediment sources and identifying key areas for soil and water conservation, playing a vital role in water-sediment processes related to runoff generation and sediment transport. Therefore, accurately and quantitatively characterizing the spatiotemporal dynamics of water-sediment connectivity at the watershed scale in cold regions has become a core scientific issue for predicting landscape evolution and assessing and mitigating related risks. This not only provides a theoretical foundation for research on the dynamic changes of regional cold-biological soil erosion and the evolution of land surface processes but also provides crucial data support for socio-economic activities such as water conservancy and hydropower engineering construction, reservoir capacity regulation, and river sand mining.

[0003] Existing quantitative paradigms mainly rely on static topographic structural connectivity to delineate potential sediment transport pathways. However, the scarcity and temporal continuity of high-resolution topographic data render existing structural connectivity products lacking in dynamic resolution, making it impossible to analyze the complex seasonal evolution processes unique to cold regions. Especially under non-steady-state conditions driven by climate change, this static quantitative method cannot capture the key dynamic processes controlling sediment migration and transport, severely limiting its predictive power. Although subsequent functional connectivity (FSC) indices integrate rainfall and soil properties, achieving a conceptual breakthrough in capturing dynamic processes, they are mostly developed for temperate environments and cannot be applied to cold regions. These models generally ignore the unique, highly nonlinear driving processes that dominate sediment dynamics in cold regions, especially failing to consider: (1) pulsed sediment release driven by glacial and snowmelt; (2) the profound impact of freeze-thaw cycles on soil erodibility, infiltration capacity, and slope stability; and (3) the dramatic changes in surface roughness and runoff resistance caused by the rapid seasonal succession of alpine vegetation. Therefore, in response to the aforementioned technical and research bottlenecks, there is an urgent need to construct a new method that can couple key physical processes and geomorphological features in cold regions, so as to achieve explicit quantification of dynamic water and sediment connectivity in cold regions under drastic changes, thereby addressing the technical challenges of geomorphological sensitivity and water and sediment dynamic prediction in rapidly evolving environments. Summary of the Invention

[0004] To address the aforementioned problems, this invention aims to provide a method for quantifying the functional connectivity of water and sediment in cold regions.

[0005] The technical solution of the present invention is as follows: A method for quantifying the functional connectivity of water and sediment in cold regions includes the following steps: Step S1: Obtain basic raster data such as hydrology, soil, and land use of the study area, establish a matching database, and perform preprocessing; Step S2: Determine the source and catchment of rivers within the watershed, and identify sub-watershed zones and uphill / downhill water catchment and sediment transport units on the GEE platform; Step S3: Apply the DINF algorithm on the Python platform to determine the direction of water flow in the basin, define the drainage threshold of each water catchment and sediment transport unit, and iterate to obtain the contribution area of ​​each water catchment and sediment transport unit. Step S4: Given the slope component algorithms for the corresponding slope water catchment and sediment transport units, write the corresponding weighting factors that consider the soil erosion characteristics of cold regions into each component (including water erosion force, residual topography, vegetation cover, freeze-thaw state, soil permeability, contribution area slope length and steepness factors, etc.), and calculate the component factors that affect the watershed water and sediment connectivity in turn. Step S5: Calculate the upslope and downslope components of each water catchment and sediment transport unit. Combined with the flow direction and water catchment grid subdivision given in Step S3, perform iterative and quantitative calculations in sequence to obtain high-resolution water and sediment functional connectivity raster data for the entire watershed.

[0006] Preferably, step S1 specifically includes the following sub-steps: Step S11: Collect existing basic data related to water and sediment connectivity in cold regions and establish a matching database, including DEM, watershed outlet, local drainage outlet, main stream and tributary sources, meteorological driving data, vegetation data, hydrological data, soil data, cryosphere features, and surface features. Step S12: Merge ERA5-Land, CMFD, and precipitation data from China Meteorological Administration stations using a triple configuration method, and select the thin plate spline function as the function. Step S13: Use the merged precipitation products as input to the DHTC model to obtain a gridded dataset of surface runoff, snowmelt runoff, and soil thermal parameters; Step S14: Use the variance-upgraded quantile mapping method to unify the spatiotemporal resolution of the multi-source datasets and satellite remote sensing sediment data obtained in steps S11 and S12.

[0007] Preferably, steps S2 and S3 specifically include the following sub-steps: Step S21: Define the confluence outlet on the GEE platform based on the source of the main stream and tributaries, the local drainage outlet and the watershed outlet, process the DEM data, segment the sub-watershed and identify the uphill and downhill water catchment and sediment transport units. Step S32: Apply the DINF flow algorithm to determine the flow direction on the Python platform; Step S33: Determine the average value of the flow accumulation grid as the threshold for defining the uphill drainage area, and iteratively calculate the contribution area for each grid cell based on the flow direction and the accumulation grid. A k ).

[0008] Preferably, step S4 specifically includes the following sub-steps: Step S41: Calculate the water erosivity factor, defined as the superposition of rainfall and meltwater-induced water erosivity components, calculated using the following formula: In the formula, The water erosion force is normalized to the interval (0.001, 1). Erosion caused by rainfall; It is the force of water erosion.

[0009] Step S42: Calculate the residual terrain factor, based on the slope gradient standard deviation parameterized within a 5*5 m moving window, using the following formula: In the formula, The normalized standard deviation of the local slope gradient is an indicator of relative surface roughness.

[0010] Step S43: Calculate the vegetation cover factor, derived from the relationship between land cover percentage and soil erosion rate, using the following formula: = In the formula, For the first i Monthly soil erosion rate; This represents the total percentage of ground coverage. Let be the vegetation cover factor for the i-th month; and These are monthly rainfall erosivity and annual rainfall erosivity, respectively.

[0011] Step S44: Calculate the freeze-thaw state factor, analyze the energy and moisture dynamics coupled between multiple soil layers under freeze-thaw conditions, derived from the daily average surface temperature of the DHTC heat transfer module, and classify the layers based on the surface thermal state using a threshold classification scheme. The specific calculation is as follows: In the formula, The average daily or monthly surface temperature ( ); An empirical coefficient for controlling the steepness of the transition phase in this interval is used. The freeze-thaw state factor ranges from 0.001 to 1.

[0012] Step S45: Calculate the soil permeability factor, which is derived based on the effective soil moisture content and then normalized and its reciprocal is taken.

[0013] Step S46: Calculate the contribution area, slope length, and steepness factor using the DINF algorithm, and normalize the slope values.

[0014] Preferably, step S41 specifically includes the following sub-steps: Step S411: Calculate rainfall erosivity using daily precipitation data from weather stations, supplemented by surface runoff data, and calculate using the following formula: In the formula, Rainfall erosivity (mm / ha·h) -1 ·y -1 ); Monthly precipitation; This represents annual precipitation.

[0015] Step S412: Calculate meltwater volume. This is done using the temperature index module built into the DHTC model to simulate key radiation and thermal factors controlling snowmelt. The calculation of glacier meltwater is the same as for snow cover, but is limited to glacier-covered areas. It is calculated using the following formula: In the formula, The accumulated temperature coefficient (mm· 。 C -1 ·day -1 ); Air temperature; The snow cover temperature threshold; Near-shortwave radiation (W·m) -2 ).

[0016] Step S413: Calculate the meltwater erosion force. Convert the meltwater obtained in S412 into a dimensionless meltwater erosion potential index, and assume that the meltwater has a basic erosion capacity proportional to its volume and flow velocity intensity. Calculate using the following formula: In the formula, To simulate meltwater runoff; The area is the grid area. Empirical scaling coefficients derived for observing the meltwater-runoff erosion relationship in watersheds in cold regions.

[0017] Preferably, the calculation of the uphill and downhill components in step S5 specifically includes the following sub-steps: Step S51: Calculate the upslope component. Based on the revised general soil loss equation, calculate the average values ​​of several factors within the catchment area, multiply them together, and subscript the dynamic factors as "". t "The monthly time-series changes are marked and calculated using the following formula:" In the formula, Water erosion force; Residual terrain; Vegetation cover; It is in a freeze-thaw state; For soil permeability; The average slope length and steepness (m / m); Contributing area to uphill slope (m²) 2 ).

[0018] Step S52: Calculate the downhill component for each corresponding component using the following formula: Preferably, the final calculation of the cold region water-sediment functional connectivity in step S5 specifically includes the following sub-steps: Substitute the uphill and downhill slope components obtained in steps S51 and S52 into the logarithmic structure to calculate the water-sediment functional connectivity in cold regions, using the following formula: In the formula, This is high-resolution (30m) raster data on functional connectivity of water and sediment in cold regions.

[0019] The beneficial effects of this invention are: This invention can accurately quantify the dynamic water and sediment connectivity of large-scale, high-resolution cold-region environments. On the one hand, it can solve the problem that traditional structural connectivity is limited to static topographic construction and lacks a detailed characterization of the spatiotemporal dynamic changes of water and sediment connectivity. On the other hand, it integrates key cold-region erosion and sediment transport elements that were ignored by previous models, establishes a quantitative correlation between functional connectivity and water and sediment flux, and effectively realizes the spatial explicit quantification of dynamic water and sediment connectivity under cold-region changes. Attached Figure Description

[0020] Figure 1 This is a schematic diagram of the process of the present invention; Figure 2 This is a specific example of the water and sediment functional connectivity and spatial heterogeneity of various component factors in the Yangtze River source region. Figure 3The specific examples show the interannual and intra-annual variations of water and sediment functional connectivity in the cold region of the Yangtze River source area, as well as the annual average functional connectivity trends of the eight secondary basins. Figure 4 This is a spatialization and static comparison of the water and sediment functional connectivity results in the cold region of the Yangtze River source area in a specific embodiment. Detailed Implementation

[0021] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0022] The structure of the method for quantifying the functional connectivity of water and sediment in cold regions according to the present invention is as follows: Figure 1 As shown. This invention is used to quantify the spatiotemporal connectivity of water and sediment functions in the Yangtze River source region of the Qinghai-Tibet Plateau. The Yangtze River source basin has various cryosphere landform units, with widespread distribution of permafrost, glaciers, and snow cover. It also has over fifty years of runoff and sediment observation data, making it a representative case study of cold regions. The temperature and thickness of permafrost are controlled by altitude; higher altitudes have thicker permafrost and thinner active layers, while lower altitudes have thinner permafrost and thicker active layers. The source region's river system consists of the Tongtian River, Tuotuo River, Dangqu River, Buqu River, and Chuerma River, mainly originating from the glaciers and permafrost areas of the Kunlun and Tanggula Mountains. Spatially, it is fan-shaped, characterized by a large river gradient and high river network density. The specific steps include: Step S1: Obtain basic raster data such as hydrology, soil, and land use of the study area, establish a matching database, and perform preprocessing; Step S11: Collect a comprehensive dataset, including meteorological driving data: air temperature, surface temperature, and precipitation; Vegetation data: land cover, vegetation change; Hydrological data: surface runoff, ice melt runoff, suspended sediment concentration and flux; Soil data: soil distribution, subsurface soil temperature, soil physical properties; Surface elements: structural connectivity; Cryosphere elements: permafrost, glaciers, and snow cover distribution; DEM, watershed outlet, local drainage outlet, source of main stream and tributaries; Step S12: Merge ERA5-Land, CMFD, and precipitation data from China Meteorological Administration stations using a triple configuration method, and select the thin plate spline function as the function. Step S13: Use the merged precipitation products as input to the DHTC model to obtain a gridded dataset of surface runoff, snowmelt runoff, and soil thermal parameters; Step S14: Use the variance-upgraded quantile mapping method to unify the spatiotemporal resolution of the multi-source datasets and satellite remote sensing sediment data obtained in steps S11 and S12.

[0023] Step S2: Determine the source and catchment of rivers within the watershed, and identify sub-watershed zones and uphill / downhill water catchment and sediment transport units on the GEE platform; Step S21: Define the confluence outlet on the GEE platform based on the source of the main stream and tributaries, the local drainage outlet and the watershed outlet, process the DEM data, segment the sub-watershed and identify the uphill and downhill water catchment and sediment transport units. Step S3: Apply the DINF algorithm on the Python platform to determine the direction of water flow in the basin, define the drainage threshold of each water catchment and sediment transport unit, and iterate to obtain the contribution area of ​​each water catchment and sediment transport unit. Step S31: Apply the DINF flow algorithm to determine the flow direction on the Python platform; Step S32: Determine the average value of the flow accumulation grid as the threshold for defining the uphill drainage area, and iteratively calculate the contribution area for each grid cell based on the flow direction and the accumulation grid. A k ) Step S4: Given the slope component algorithms for the corresponding slope water catchment and sediment transport units, write the corresponding weighting factors that consider the soil erosion characteristics of cold regions into each component (including water erosion force, residual topography, vegetation cover, freeze-thaw state, soil permeability, contribution area slope length and steepness factors, etc.), and calculate the component factors that affect the watershed water and sediment connectivity in turn. Step S41: Calculate the water erosivity factor, defined as the superposition of rainfall and meltwater-induced water erosivity components, calculated using the following formula: In the formula, The water erosion force is normalized to the interval (0.001, 1). Erosion caused by rainfall; For the erosive force of meltwater; Step S411: Calculate rainfall erosivity using daily precipitation data from weather stations, supplemented by surface runoff data, and calculate using the following formula: In the formula, Rainfall erosivity (mm / ha·h) -1 ·y -1 ); Monthly precipitation; Annual precipitation; Step S412: Calculate meltwater volume. This is done using the temperature index module built into the DHTC model to simulate key radiation and thermal factors controlling snowmelt. The calculation of glacier meltwater is the same as for snow cover, but is limited to glacier-covered areas. It is calculated using the following formula: In the formula, The accumulated temperature coefficient (mm· 。 C -1 ·day -1 ); Air temperature; The snow cover temperature threshold; Near-shortwave radiation (W·m) -2 ); Step S413: Calculate the meltwater erosion force. Convert the meltwater obtained in S412 into a dimensionless meltwater erosion potential index, and assume that the meltwater has a basic erosion capacity proportional to its volume and flow velocity intensity. Calculate using the following formula: In the formula, To simulate meltwater runoff; The area is the grid area. Empirical scaling coefficients derived for observing meltwater-runoff erosion relationships in watersheds of cold regions; Step S42: Calculate the residual terrain factor, based on the slope gradient standard deviation parameterized within a 5*5 m moving window, using the following formula: In the formula, The normalized standard deviation, representing the local slope gradient, is an indicator of relative surface roughness. Step S43: Calculate the vegetation cover factor, derived from the relationship between land cover percentage and soil erosion rate, using the following formula: = In the formula, For the first i Monthly soil erosion rate; This represents the total percentage of ground coverage. Let be the vegetation cover factor for the i-th month; and These are monthly rainfall erosivity and annual rainfall erosivity, respectively. Step S44: Calculate the freeze-thaw state factor, analyze the energy and moisture dynamics coupled between multiple soil layers under freeze-thaw conditions, derived from the daily average surface temperature of the DHTC heat transfer module, and classify the layers based on the surface thermal state using a threshold classification scheme. The specific calculation is as follows: In the formula, The average daily or monthly surface temperature ( ); An empirical coefficient for controlling the steepness of the transition phase in this interval is used. The freeze-thaw state factor ranges from 0.001 to 1. Step S45: Calculate the soil permeability factor, which is derived based on the effective soil water content and then normalized and its reciprocal is taken. Step S46: Calculate the contribution area, slope length, and steepness factor using the DINF algorithm, and normalize the slope values. Step S5: Calculate the upslope and downslope components of each water catchment and sediment transport unit. Combined with the flow direction and water catchment grid subdivision given in Step S3, perform iterative and quantitative calculations in sequence to obtain high-resolution water and sediment functional connectivity raster data for the entire watershed. Step S51: Calculate the upslope component. Based on the revised general soil loss equation, calculate the average values ​​of several factors within the catchment area, multiply them together, and subscript the dynamic factors as "". t "The monthly time-series changes are marked and calculated using the following formula:" In the formula, Water erosion force; Residual terrain; Vegetation cover; It is in a freeze-thaw state; For soil permeability; The average slope length and steepness (m / m); Contributing area to uphill slope (m²) 2 ).

[0024] Step S52: Calculate the downhill component for each corresponding component; Step S53: Substitute the uphill and downhill slope components calculated in steps S51 and S52 into the logarithmic structure to calculate the water-sediment functional connectivity in the cold region, using the following formula: In the formula, This is high-resolution (30m) raster data on functional connectivity of water and sediment in cold regions.

[0025] In summary, this invention can accurately calculate large-scale, high-resolution water and sediment functional connectivity in cold regions, and has the following significant advantages and advancements: Overcoming the limitations of traditional methods and overcoming the constraints of small to medium scales: Traditional methods mainly rely on software such as ArcGIS, and can usually only calculate watersheds of small to medium scale (< 10,000 km). 2 The present invention overcomes this limitation by enabling calculations on a large scale, significantly expanding its application scope.

[0026] Supports high-resolution computation: Traditional methods struggle to handle high-resolution (< 30m) data on a large scale, while this invention enables water and sediment functional connectivity calculations at a finer resolution. This is particularly important for detailed studies of complex terrain in high-altitude environments, providing more accurate and detailed analytical results.

[0027] Combining Dynamics and Functional Connectivity: Traditional structural connectivity algorithms are primarily limited to the static surface features of landscapes, failing to effectively characterize landscape functional connectivity. This invention, however, achieves a comprehensive characterization of functional connectivity by supplementing the weighting factor matrix. Furthermore, high-altitude regions are significantly impacted by climate change, with dynamic changes such as hydrological processes and soil erosion having a crucial influence on structural connectivity. This invention can dynamically respond to these changes, providing timely and accurate connectivity analysis, which is of great significance for formulating scientific environmental management and response measures.

[0028] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes, and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A method for quantifying the functional connectivity of water and sediment in cold regions, characterized in that, Includes the following steps: S1: Acquire basic data of the study area and preprocess the basic raster data of hydrology, soil and land use to adjust different data to the same resolution and establish a matching database; S2: Determine the source and catchment of rivers within the basin; identify sub-basin zones and uphill / downhill water catchment and sediment transport units on the GEE platform. S3: Apply the DINF algorithm on the Python platform to determine the direction of water flow in the basin, define the drainage threshold of each water catchment and sediment transport unit, and iterate to obtain the contribution area of ​​each water catchment and sediment transport unit. S4: Given the slope component algorithm of the corresponding slope water catchment and sediment transport unit, write the corresponding weighting factor considering the soil erosion characteristics of cold regions into each component, including water erosion force, residual topography, vegetation cover, freeze-thaw state, soil permeability, contribution area, slope length and steepness factor, and calculate the component factors that affect the watershed water and sediment connectivity in turn. S5: Calculate the upslope and downslope components of each water catchment and sediment transport unit. Combined with the flow direction and water catchment grid subdivision given in S3, perform iterative and quantitative calculations in sequence to obtain high-resolution cold region water and sediment functional connectivity raster data for the entire watershed. In step S4, the specific process for calculating the water erosivity factor, residual topographic factor, vegetation cover factor, freeze-thaw factor, soil permeability factor, contributing area slope length, and steepness factor for each unit includes the following sub-steps: S41: Calculate the water erosivity factor, defined as the superposition of rainfall and meltwater-induced water erosivity components, calculated using the following formula: （1） In the formula, For water erosion force, normalized to the (0.001-1) range; Erosion caused by rainfall; For the erosive force of meltwater; S42: Calculate the residual terrain factor, based on the slope gradient standard deviation parameterized within a 5*5 m moving window, using the following formula: （2） In the formula, The normalized standard deviation, representing the local slope gradient, is an indicator of relative surface roughness. S43: Calculate the vegetation cover factor, derived from the relationship between land cover percentage and soil erosion rate, using the following formula: （3） = （4） In the formula, Let be the soil loss rate in month i; This represents the total percentage of ground coverage. Let be the vegetation cover factor for the i-th month; and These are monthly rainfall erosivity and annual rainfall erosivity, respectively. S44: Calculate the freeze-thaw state factor and analyze the energy and moisture dynamics coupled between multiple soil layers under freeze-thaw conditions. The factor is derived from the daily average surface temperature of the DHTC heat transfer module. A threshold classification scheme is used to classify the surface thermal state. The specific calculation is as follows: （5） In the formula, The average daily or monthly surface temperature. ; To control the steepness of the transition phase in this interval, an empirical coefficient is used; the freeze-thaw state factor ranges from 0.001 to 1. S45: Calculate the soil permeability factor, which is derived from the effective soil water content and then normalized and its reciprocal is taken. S46: Calculate the contribution area, slope length, and steepness factor using the DINF algorithm, and normalize the slope values. The calculation of water erosion power integrates rainfall and meltwater; meltwater includes glacial and snowmelt. The erosion potential in cold regions includes rainfall components, meltwater components, and combined and normalized components. Step S41 specifically includes the following sub-steps: S411: Calculate rainfall erosivity using daily precipitation data from weather stations, supplemented by surface runoff data, using the following formula: （6） In the formula, For rainfall erosivity, mm / ha·h -1 ·y -1 ; Monthly precipitation; Annual precipitation; S412: Calculate meltwater volume using the built-in temperature index module of the DHTC model to capture key radiation and thermal factors controlling snowmelt. The calculation of glacial meltwater is the same as for snow cover, but is limited to glacier-covered areas, and is performed using the following formula: （7） In the formula, The accumulated temperature coefficient is expressed in mm·C. -1 ·day -1 ; Air temperature; The snow cover temperature threshold; For near-shortwave radiation, W·m -2 ; S413: Calculate the meltwater erosion force. Convert the meltwater obtained in S412 into a dimensionless meltwater erosion potential index, and assume that the meltwater has a basic erosion capacity proportional to its volume and flow velocity intensity. Calculate using the following formula: （8） In the formula, To simulate meltwater runoff; The area is the grid area. Empirical scaling coefficients derived for observing meltwater-runoff erosion relationships in watersheds of cold regions; In step S5, the uphill component D up ,k and downhill component D dn The formula for calculating k is: S51: Calculate the upslope component. Based on the revised general soil loss equation, calculate the average value of several factors within the catchment area, multiply them together, and label the monthly time series changes of dynamic factors with the subscript "t". （9） In the formula, Water erosion force; Residual terrain; Vegetation cover; It is in a freeze-thaw state; For soil permeability; Average slope length, m / steepness, m; Contributing area to the uphill slope, m 2 ; S52: Calculate the downhill component for each corresponding component; （10）； （11）。 2. The method for quantifying the functional connectivity of water and sediment in cold regions according to claim 1, wherein the acquisition and preprocessing of basic raster data in step S1 specifically includes the following sub-steps: S11: Collect existing basic data related to water and sediment connectivity in cold regions and establish a matching database, including DEM, watershed outlet, local drainage outlet, main and tributary sources, meteorological driving data, vegetation data, hydrological data, soil data, cryosphere elements, and surface elements. S12: The Triple Collocation method is used to merge precipitation data from ERA5-Land, CMFD, and China Meteorological Administration stations, with thin plate spline function selected as the function. S13: Use the merged precipitation products as input to the distributed hydro-thermal coupled DHTC model to obtain a gridded dataset of surface runoff, snowmelt runoff and soil thermal parameters; S14: The Variance-Upgraded Quantile Mapping (VUQM) method is used to unify the spatiotemporal resolution of the multi-source datasets and satellite remote sensing sediment data obtained in steps S11 and S12.

3. The method according to claim 1, characterized in that, The specific implementation of steps S2 and S3 includes: S21: On the GEE platform, based on the sources of main streams and tributaries, local drainage outlets and watershed outlets, define the confluence outlets, process the DEM data, segment the sub-watersheds and identify the uphill and downhill water catchment and sediment transport units. S32: Determining flow direction using the DINF flow algorithm on the Python platform; S33: Determine the average value of the flow accumulation grid as the threshold for defining the uphill drainage area, and iteratively calculate the contribution area A for each grid cell based on the flow direction and the accumulation grid. k .

4. The method according to claim 1, characterized in that, Ultimate cold region water and sediment functional connectivity The structure is obtained by taking the logarithmic structure of the uphill and downhill components: （12） In the formula, This is high-resolution 30m raster data on the functional connectivity of water and sediment in cold regions.

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