A regional water-carbon cycle process coupling simulation prediction system

Abstract

This invention discloses a coupled simulation and prediction system for regional water and carbon cycle processes, relating to the field of watershed carbon cycle simulation. The system includes a data acquisition module that determines the watershed extent and identifies riverbank areas within a unified grid system. Simultaneously, vegetation type and soil organic carbon are mapped to riverbank grid cells, consistently expressing the spatial location of carbon sources in relation to hydrological watershed migration. This facilitates subsequent clarification of carbon source distribution. Based on a DEM (Digital Elevation Model), flow direction and confluence paths are constructed. Runoff in each grid is calculated under meteorological conditions and gradually converges into the river channel, establishing hydrodynamic transport paths with clear upstream and downstream relationships. This provides a physical carrier for carbon transport. Based on soil organic carbon and vegetation type in the riverbank grids, the system quantifies the differences in carbon supply capacity of different riverbank areas during regional water migration. Riverbank carbon sources are traced along the confluence paths. Spatial weights are constructed using distance attenuation and connectivity, mapping carbon sources to each grid cell. Carbon flux is then coupled with runoff to calculate and accumulate through gradual transport.

Description

Technical Field

[0001] This invention relates to the field of watershed carbon cycle simulation, specifically a coupled simulation and prediction system for regional water and carbon cycle processes. Background Technology

[0002] At regional or watershed scales, the water-carbon cycle involves the gradual transport of carbon from terrestrial ecosystems, which are fixed and stored, to watersheds via hydrological transport. In existing research, these two processes are typically treated separately: on the one hand, carbon fixation in terrestrial ecosystems is primarily estimated using vegetation models, focusing on carbon stock; on the other hand, carbon transport in river basins relies on hydrodynamic model simulations, focusing on carbon transport. Due to the differences in their temporal scales, spatial representations, and driving mechanisms, the carbon stored on land and the carbon transport process in rivers are effectively linked.

[0003] In real-world watersheds, this inconsistency becomes more pronounced when hydrological processes such as rainfall intensify. For instance, carbon may be concentratedly exported in a short period, but models struggle to simulate and predict this. Consequently, the simulated carbon input, output, and storage within the watershed become inconsistent, resulting in a budgetary discrepancy. Furthermore, this inconsistency makes it difficult to reliably compare and assess the overall carbon cycle status of the watershed under different hydrological conditions (such as short-duration heavy rainfall scenarios). Summary of the Invention

[0004] (a) Technical problems to be solved This invention provides a coupled simulation and prediction system for regional water and carbon cycle processes, which can achieve consistent mapping of the entire process from riverbank carbon sources to carbon transport within the river basin.

[0005] (II) Technical Solution To achieve the above objectives, the present invention provides the following technical solution: a coupled simulation and prediction system for regional water and carbon cycle processes, comprising the following modules: The data acquisition module performs raster discretization on selected watersheds and riverbanks under a unified geographic space and time step; and obtains the vegetation type and soil organic carbon content within each riverbank raster unit. The hydrological process simulation module uses a digital elevation model to extract the flow direction relationship of each watershed grid cell, constructs the watershed's confluence path and upstream and downstream topology, and calculates the runoff of each watershed grid cell under given meteorological conditions. The carbon status update module defines the carbon source intensity for each riverbank grid unit based on the soil organic carbon content and vegetation type of each riverbank grid unit. The carbon source intensity is used to characterize the potential level of dissolved carbon released by the riverbank grid unit into the watershed under the action of unit runoff. The coupled simulation module identifies, for any watershed grid cell, riparian grid cells with hydrological connectivity to the carbon input of that watershed grid cell along the upstream confluence path; constructs spatial weighting coefficients based on the confluence path distance, slope aspect consistency, and flow connectivity between the riparian grid cells and the target watershed grid cell, which characterize the attenuation effect of carbon during transport; based on the spatial weighting coefficients, the runoff at the corresponding time step is coupled with the carbon source intensity of the riparian grid cell to calculate its carbon output flux; and according to the confluence path, the carbon output flux of each watershed grid cell is transmitted and accumulated downstream step by step to calculate the carbon flux at the watershed outlet. The carbon budget prediction module uses the outlet of the basin as the control position to perform time integration of carbon flux to obtain the total carbon output of the selected basin; and calculates the carbon concentration change process in combination with the flow at the basin outlet. By adjusting the given meteorological conditions to drive runoff changes, it predicts the change characteristics of basin carbon output under different meteorological conditions.

[0006] In some executable embodiments, the following processing is performed in the acquisition module under uniform geographic raster units and time steps; Obtain digital elevation model data for the selected watershed, determine the watershed range based on the digital elevation model, and perform rasterization on the watershed range; based on the extracted spatial location of the river channel, identify the riverbank area according to a preset distance range, and mark the corresponding riverbank raster units; The vegetation type data and soil organic carbon content data corresponding to the riverbank grid unit are obtained, and the vegetation type data and soil organic carbon data are mapped to a unified geographic grid unit according to their spatial location to form the vegetation type distribution and soil organic carbon spatial distribution corresponding to each riverbank grid unit.

[0007] In some executable embodiments, after the hydrological process simulation module fills the depressions in the digital elevation model, it uses a flow direction algorithm to determine the flow direction of each watershed grid unit, and determines the confluence path of each watershed grid unit and its upstream and downstream connection relationship. Under given meteorological conditions, the hydrological process simulation module calculates the runoff at the current time step based on the rainfall input and underlying surface characteristics of each watershed grid cell. Along the confluence path, the runoff generated by each watershed grid unit is transmitted downstream and accumulated step by step to obtain the flow process in the watershed channel.

[0008] In some executable embodiments, based on the riverbank grid cells marked in the acquisition module, the carbon state update module extracts all riverbank grid cells as carbon source calculation objects and obtains soil organic carbon content and vegetation type data corresponding to each riverbank grid cell. Based on the preset vegetation type classification parameters, different vegetation types are assigned corresponding carbon release coefficients, and the carbon source intensity of each riverbank grid unit is calculated by combining the product of the soil organic carbon content of the corresponding riverbank grid unit.

[0009] In some executable embodiments, for any watershed grid cell, the coupled simulation module traces upstream based on the constructed confluence path and upstream-downstream topology to identify all the riverbank grid cells located on its confluence path as the source grid set that contributes carbon to the watershed grid cell.

[0010] In some executable embodiments, within the source grid set, the coupling simulation module constructs corresponding spatial weight coefficients based on the confluence path distance, topographic slope consistency, and flow connectivity of each riverbank grid cell in the set to the current watershed grid cell. : ; in, Riverbank Grid Unit To the current watershed grid cell distance, The attenuation coefficient is used; for riverbank grid cells that do not satisfy the confluence connectivity relationship, their spatial weight coefficient is set to zero.

[0011] In some executable embodiments, the coupled simulation module performs a weighted summation of the carbon source intensity of each riverbank grid cell based on the spatial weighting coefficient to obtain the equivalent carbon source intensity of the current watershed grid cell; the equivalent carbon source intensity is combined with the runoff of the watershed grid cell at the current time step to calculate the carbon output flux of the watershed grid cell. According to the aforementioned confluence path, the carbon output flux generated by each watershed grid unit is transmitted step by step to the downstream grid units and the river channel, and is accumulated with the carbon flux carried by the upstream water during the transmission process to obtain the carbon flux process at the watershed outlet.

[0012] In some executable embodiments, the carbon budget prediction module uses a specified watershed outlet as the control position to extract carbon flux time series data accumulated step by step through the confluence path from the coupled simulation module, as well as river flow data at the corresponding time step. According to the set time window, the carbon flux at the outlet of the basin is accumulated over time to obtain the total carbon output of the basin within the time window. At each time step, the carbon flux at the river cross-section is calculated as a ratio to the corresponding river flow to obtain the carbon concentration change process at the corresponding time step.

[0013] In some executable embodiments, the carbon budget prediction module constructs input data sequences under different hydrological scenarios by adjusting the input meteorological condition parameters when making predictions. The meteorological condition parameters include rainfall and rainfall time series. Under different hydrological scenarios, the hydrological process simulation module and the coupled simulation module are repeatedly executed to obtain the carbon flux and flow process at the river cross section under the corresponding scenario. The carbon output fluxes obtained under different hydrological scenarios are compared and analyzed, and their cumulative differences or changes within a set time window are calculated to characterize the impact of changes in hydrological conditions on the watershed carbon output process.

[0014] (III) Beneficial Effects: Compared with the prior art, this invention has the following beneficial effects: This invention determines the watershed extent based on DEM and unifies the rasterized representation, further identifies riverbank areas and overlays vegetation type and soil organic carbon information, realizing a standardized representation of the spatial location and basic attributes of carbon sources within the watershed. By constructing the topological relationship between flow direction and confluence path, and calculating the raster runoff generation and its successive confluence process of each watershed under meteorological drive, it provides clear hydrodynamic paths and driving conditions for carbon transport.

[0015] The carbon state update module in the system converts soil organic carbon in the riverbank area into carbon source intensity that can be mobilized by runoff. Then, the coupled simulation module traces the riverbank carbon source along the confluence path and constructs spatial weight coefficients based on connectivity and path distance to map the dispersed carbon source into the equivalent carbon source intensity of each grid. The carbon flux is then coupled with the runoff to calculate the carbon flux, thus realizing the spatial coupling between terrestrial carbon and hydrological processes. Attached Figure Description

[0016] Figure 1 A schematic diagram of a coupled simulation and prediction system for regional water and carbon cycle processes provided in an embodiment of the present invention; Figure 2 A block diagram illustrating the connection principle of each module in a coupled simulation and prediction system for regional water and carbon cycle processes provided in an embodiment of the present invention. Figure 3 A schematic block diagram illustrating the sequence from hydrological process simulation to two types of carbon cycle simulation in a regional water and carbon cycle coupled simulation and prediction system provided in an embodiment of the present invention. Figure 4 This is a schematic diagram illustrating spatial rasterization discretization processing in a selected watershed and its banks, provided in an embodiment of the present invention, for a coupled simulation and prediction system of regional water and carbon cycle processes. Detailed Implementation

[0017] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0018] It should be noted that, where there is no conflict, the features in the embodiments of the present invention can be combined with each other.

[0019] Combination Figures 1 to 4 The system illustrates a coupled simulation and prediction system for regional water and carbon cycle processes. This system spatially weights and maps riverbank carbon sources along hydrological confluence paths within a unified grid system, and couples this with runoff processes to calculate carbon flux. This achieves a consistent representation of terrestrial carbon and hydrological transport in terms of space, pathways, and processes, thereby effectively solving the problem of non-closed carbon flux at the watershed scale and improving the ability to predict carbon output processes under different hydrological scenarios.

[0020] First, it's important to understand that the goal of the acquisition module is not simply to obtain various types of data, but rather to build a highly unified water and carbon-driven data foundation across temporal, spatial, and physical scales, enabling subsequent simulations to run collaboratively within the same physical framework. Specifically, this involves transforming spatial information related to carbon production in the watershed into structured inputs within a unified grid system that can directly participate in hydrological coupling calculations.

[0021] To achieve this goal, the acquisition module first needs to obtain a digital elevation model (DEM) of the selected area. A DEM is essentially a regular grid, with each cell recording the surface elevation; it forms the basis for all subsequent spatial analyses.

[0022] However, considering that the original DEM may contain local depressions caused by data errors, if left untreated, water flow will stagnate at these locations, leading to breaks in subsequent flow direction analysis. Therefore, in some embodiments of this invention, a depression-filling algorithm is used to smooth out these non-real depressions, making the water flow path continuous.

[0023] After obtaining the processed DEM, the flow direction of water in each grid cell is determined by flow direction analysis, that is, which adjacent grid cell the water flows from. This step is usually based on the physical principle that water flows from high to low. In the DEM, the flow direction can be identified by analyzing the elevation values ​​of each point and following the elevation values ​​from high to low.

[0024] Next, a watershed outlet is selected, usually a river cross-section location. Based on the flow direction, all areas flowing into that point are traced in reverse to determine the entire watershed range.

[0025] After determining the watershed boundaries, the area (watershed only) needs to be divided into regular grids. See the attached document for details. Figure 4 This method transforms continuous geographic space into discrete computational units. Specifically, it sets a uniform resolution (e.g., 10m-30m) and divides the entire watershed into raster cells of uniform size. Each raster cell will serve as an independent basic unit in subsequent calculations.

[0026] After completing the rasterization, it is necessary to further identify the areas related to water-carbon coupling, namely the riparian areas, from the entire watershed.

[0027] First, runoff accumulation is calculated based on the DEM (Digital Elevation Model). This indicator reflects how much upstream water each grid cell receives; a higher value indicates a greater likelihood of channel formation. By setting a threshold, grid cells with large runoff accumulation are identified as channel cells, thus extracting the entire watershed's channel network. After obtaining the channels, buffer zones are constructed by extending outwards from the channel center at preset distances (e.g., tens of meters). All grid cells falling within these buffer zones are defined as riverbank grid cells.

[0028] It is particularly important to note that carbon is not transported uniformly throughout the entire watershed. A portion originates from dissolved carbon in the riparian region, based on the high soil moisture content and abundant organic matter input in this area, which is in direct contact with runoff. Therefore, this step narrows down the potential carbon sources from the entire watershed to a reasonable spatial range, providing a clear source region for subsequent calculations.

[0029] After determining the riverbank grid, these grids need to be assigned carbon-related attributes, starting with obtaining vegetation type data. This data typically comes from remote sensing classification products, which are essentially spatial classification maps, with each location corresponding to a land surface type (such as woodland, grassland, farmland, etc.). Through spatial overlay, this data is mapped onto the previously established grid system, thereby assigning a clear vegetation type label to each riverbank grid.

[0030] It's important to understand that obtaining the vegetation type of the riverbank raster area is crucial because different vegetation systems have varying capacities for inputting and maintaining soil organic carbon, making it a key control factor for determining carbon release capacity. Subsequently, soil organic carbon (SOC) data is acquired at a uniform time step. This data can come from soil databases or survey results and essentially describes the amount of organic carbon stored in the soil per unit area. Through resampling and spatial matching, the SOC data is also mapped onto a uniform raster system, and the SOC values ​​corresponding to the riverbank raster are extracted.

[0031] After completing the above operations, each riverbank grid will have two specific attributes: vegetation type (controlling carbon production / input characteristics) and soil organic carbon content (determining the scale of carbon sources).

[0032] The final step in the data acquisition module is to integrate all the above information into a unified raster data structure. At this point, each raster cell (especially the riverbank raster) has clearly defined attributes, including: Spatial location; Does it belong to the riverside area? Vegetation type; Soil organic carbon content.

[0033] In summary, the data acquisition module constructs watershed and runoff structures using a DEM, identifies riverbank carbon source areas under a unified grid system, and maps vegetation and soil organic carbon information to grid cells, thereby transforming carbon distribution in natural space into standardized inputs that can participate in hydrological coupling calculations.

[0034] After the above-mentioned data acquisition module has constructed each grid area, the hydrological process simulation module mainly focuses on the watershed grid unit, and under a given meteorological input, how water is generated in the watershed, along what path it moves, and finally forms a flow process in the river channel.

[0035] Specifically, based on the DEM that has already undergone depression filling, a flow direction algorithm is used to calculate the flow direction for each grid cell. Taking the D8 algorithm as an example, among the eight adjacent grid cells of a grid cell, the direction with the lowest elevation is selected as the water flow direction. In this way, each grid cell is assigned a clear downstream direction.

[0036] Once the flow direction of all grids is determined, the entire watershed is effectively transformed into a directed network structure, meaning each watershed grid has a unique downstream grid. Based on this structure, one can start from any grid and trace the flow direction step by step to reach the watershed outlet. This path is the confluence path of that grid.

[0037] After obtaining the flow direction, it is possible to further calculate how much water each grid receives from upstream grids. In some embodiments, the upstream contribution is accumulated step-by-step along the flow direction; the larger the accumulated flow, the more water is collected. Based on this indicator, channels can be identified by setting thresholds. For example, when the accumulated flow of a grid exceeds a set value, it is considered that a stable flow has formed at that location, thus defining it as a channel grid. This divides the entire watershed into two categories: slope grids (runoff-generating) and channel grids (runoff-collecting). Simultaneously, the upstream and downstream relationships of each watershed grid are clearly defined, providing a pathway basis for all subsequent material transport (primarily carbon).

[0038] Only after the spatial structure is constructed can the actual hydrological calculation stage begin. Specifically, for each time step (e.g., daily), meteorological conditions are input, the most crucial of which is rainfall. At this stage, the calculation focuses on how much of the rainfall falling on each grid will be converted into runoff.

[0039] Specifically, starting from the upstream, each grid not only generates its own runoff but also receives water from upstream grids. Therefore, when calculating the flow of a particular grid, it is necessary to accumulate the local runoff and the upstream inflow, and then continue to transfer the total water volume to downstream grids along the flow direction. Finally, at the river outlet, the total flow of the entire basin at that time step is obtained.

[0040] It should be noted that the above process is completed at a single time step. Therefore, it is necessary to repeat the above calculation for continuous time steps (such as daily rainfall) to obtain the flow process (flow time series) at the river cross-section as a function of time.

[0041] In summary, the hydrological process simulation module uses DEM to determine the flow direction and confluence structure within the watershed, calculates the runoff generation of each grid under meteorological drive, and accumulates the flow process of the river channel step by step along the predetermined confluence path, thereby constructing a hydrodynamic transport framework and providing a foundation for subsequent carbon transport.

[0042] After completing the data acquisition module, the system has obtained the location of the riverbank grid cells, as well as the soil organic carbon (SOC) content and vegetation type information corresponding to each riverbank grid cell. At this point, these data are still only a static spatial representation of the carbon inventory and cannot be directly used in subsequent hydrological transport calculations. Therefore, the core role of the carbon state update module is to construct a quantitative representation that reflects the potential for carbon to be carried away by runoff based on this existing information.

[0043] Specifically, the first step is to extract the labeled riverbank grid cells from the entire watershed grid and use them as the carbon source calculation objects. The essence of this step is to spatially limit the effective source range of carbon, that is, to assume that only areas close to the river channel and capable of direct exchange with runoff make a major contribution to the carbon output of the water body, thereby avoiding the indiscriminate inclusion of soil carbon from the entire watershed in the calculation.

[0044] After determining the computational objects, for each riverbank grid, the corresponding soil organic carbon content and vegetation type are read. Soil organic carbon content represents the total potential carbon output at that location, while vegetation type reflects the activity level of the carbon cycle and the ability of organic matter to be converted into soluble forms in that area.

[0045] Based on this, in order to characterize the ability of terrestrial carbon to migrate to water bodies, the embodiments of the present invention introduce the parameter of carbon source intensity. This parameter mainly reflects the amount of carbon that can be mobilized and output by water in the riverbank grid unit under the action of unit runoff. Its magnitude is mainly determined by two aspects: one is the amount of organic carbon in the soil that can be migrated, and the other is the ability of this part of carbon to be transformed into dissolved or transportable forms.

[0046] For ease of calculation, this embodiment uses soil organic carbon (SOC) to characterize carbon supply and introduces a carbon release coefficient to characterize carbon mobility under different underlying surface conditions. This carbon release coefficient comprehensively reflects the influence of vegetation type on organic carbon input, soil structure, and dissolved organic carbon formation. For example, forested areas, due to abundant litter input and high humification levels, typically have a high capacity for dissolved organic carbon generation, corresponding to a larger carbon release coefficient, while bare land or sparsely vegetated areas have relatively weak carbon release capacity due to limited organic carbon sources.

[0047] By combining the carbon release coefficient with the soil organic carbon content, the carbon source intensity of each riverbank grid cell can be calculated, for example, by the following formula: ; in, Let be the carbon source intensity of the i-th riverbank grid cell. The organic carbon content detected within this grid cell is typically expressed in units of 1. , is the carbon emission coefficient, which is a dimensionless constant.

[0048] For information on setting the carbon emission factor, please refer to the following: Figure 3 In some implementations, a set of empirical ranges is set for the carbon emission coefficients of various land types. For example, the range of carbon emission coefficients for forest land types is successively larger than that for grassland, mulberry land, and bare land. The ranges of carbon emission coefficients for various types of forest land are generally obtained from studies on the SOC-DOC output of small watersheds.

[0049] This carbon source intensity does not represent the actual carbon concentration in the water body, nor is it the carbon flux at a specific moment. Rather, it is an indicator of potential supply capacity, used to describe the extent to which the region can provide carbon to the water flow when runoff passes through the grid. In other words, it describes the difference in the potential contribution of different spatial locations in the carbon output process.

[0050] When entering the coupled simulation module, refer to this section. Figure 2 The system already possesses three types of key information: First, the hydrological module provides the confluence path and upstream and downstream topological relationships, and the runoff of each watershed grid at the current time step; Second, the carbon source intensity of the riverbank grid provided by the carbon status module; Third, a unified grid space system.

[0051] It is particularly important to note that the essence of this coupling is to distribute and transport carbon sources located on the riverbanks along the water flow path to any location in the watershed, ultimately forming the carbon flux of the river cross section.

[0052] In practice, for any watershed grid cell, we first trace upstream along its predetermined confluence path to identify all riverbank grid cells located along that path, forming a set of source grids that have potential carbon contributions to that grid.

[0053] This step involves strictly limiting the spatial source, meaning that the carbon source can only affect the current grid if water can flow from the riverbank grid along the terrain path, thus linking the carbon source with the water path one by one.

[0054] After determining the source grid set, the core problem to be solved is: how should the contributions of these riverbank carbon sources, distributed in different locations, to the current grid be allocated? This allocation is achieved through spatial weighting coefficients. To achieve this.

[0055] This coefficient The construction follows two basic constraints: One constraint is connectivity. A hydrological connection is considered to exist between riverbank grid r and the current grid i only if they are on the same confluence path and the flow direction is continuous (there is no reverse slope or break). If this condition is not met, the contribution of the riverbank grid to the current grid is set to zero.

[0056] Secondly, there is the distance decay law, which can be understood as follows: even if there is a connection, as the distance between the riverbank grid and the current grid along the confluence path increases, its influence should gradually weaken.

[0057] Based on the above two principles, the spatial weight coefficient is expressed as a decreasing function. : ; in, Riverbank Grid Unit To the current watershed grid cell The distance, it is important to note, is here It is not a straight-line distance, but a distance accumulated segment by segment along the water flow path.

[0058] This is the attenuation coefficient, used to control the range of influence. Its physical meaning is that during carbon migration with water, it undergoes dilution, deposition, or transformation, leading to a relative weakening of the contribution from distant sources. The larger the value, the stronger the attenuation and the smaller the impact of distant carbon sources; conversely, the smaller the value, the wider the impact range. For riverbank grid cells that do not satisfy the confluence connectivity relationship, their spatial weight coefficient is set to zero.

[0059] After obtaining the weights of each riverbank grid cell to the current grid cell, these weights are weighted and summed with the corresponding carbon source intensities to obtain the equivalent carbon source intensity of the current grid cell: ; Here This can be understood as the equivalent carbon supply capacity per unit volume of water at the current grid location, after taking into account the influence of all upstream riverbank carbon sources.

[0060] Next, the equivalent carbon source intensity is combined with the current runoff of the grid at this time step to calculate the carbon output flux of the grid: ; in, This represents the runoff of the watershed grid. This represents the carbon flux output downstream from the grid in this watershed. The larger the water volume and the higher the carbon level that a unit of water can carry, the greater the carbon flux output at that location. In other words, water determines the scale of transport, while the intensity of the carbon source determines the carbon content carried per unit volume of water.

[0061] After obtaining the carbon output flux of each grid, the final step is the transmission and accumulation along the confluence path. The specific process is consistent with hydrological confluence: each grid not only outputs its own generated carbon flux but also receives carbon flux transmitted from all upstream grids, and then combines the two to continue downstream transmission. As this process progresses step by step, carbon flux continuously accumulates spatially, ultimately forming a complete carbon flux process at the river grids and the watershed outlet section.

[0062] Finally, there is the carbon budget prediction module of the system. When entering this module, the coupled simulation module has already output that: in the entire watershed space, each grid and each time step has the corresponding runoff and carbon flux, and these carbon fluxes have been accumulated to the river system step by step along the confluence path.

[0063] The carbon budget prediction module first needs to select one or more river sections as control locations, typically the watershed outlet or key monitoring sections. At these sections, the carbon flux sequence over time is extracted. and the corresponding river flow sequence .

[0064] The carbon flux here is the result of the accumulation of contributions from all upstream grids after confluence, and therefore can be regarded as the total carbon output process at this cross section.

[0065] After obtaining the time series, the next step is to integrate the carbon flux over time within a defined time window. Specifically, this involves summing the carbon flux at each daily time step to obtain the total carbon output of the basin within that time window (e.g., on a monthly scale). ; This indicator reflects the total amount of carbon output from the watershed to the river system through hydrological processes during that period, and is one of the core quantities in carbon budget analysis.

[0066] Based on this, in order to characterize the change process of carbon concentration in the water body, it is necessary to calculate the ratio of carbon flux to the corresponding river flow at each time step: ; in, This indicates that the cross-section is in time. Carbon concentration, in its physical sense, is the amount of carbon carried per unit volume of water.

[0067] This calculation yields a concentration sequence that changes over time, reflecting the dilution or enrichment process of carbon in water bodies under different hydrological conditions. For example, during flood season, although carbon flux may be high, the concentration may actually decrease due to the significant increase in flow; while during dry season, the concentration may increase due to the lower flow.

[0068] After calculating carbon flux and concentration under a single scenario, the carbon budget prediction module further constructs different hydrological scenarios to predict and analyze the carbon output process. Specifically, it adjusts the input meteorological parameters, mainly including total rainfall and its temporal distribution (rainfall time series).

[0069] In some embodiments, different input sequences such as "concentrated heavy rainfall", "uniform rainfall", or "low rainfall scenario" can be constructed.

[0070] In each scenario, the hydrological process simulation module and the coupled simulation module are re-executed. Changes in rainfall conditions directly affect the runoff generation process and confluence intensity of each grid, thereby altering the water distribution along the runoff path and consequently influencing carbon mobilization and transport processes. Therefore, different carbon flux sequences will be obtained under different scenarios. and the corresponding river flow sequence .

[0071] These future hydrological and meteorological data, input as new boundary conditions into the hydrological process simulation module at a unified time step, enable the evolution of SOC migration and river runoff to be re-enacted under future scenarios.

[0072] After obtaining results under multiple scenarios, they are compared and analyzed. Typically, the total carbon output for each scenario is calculated within the same time window, and the differences or magnitudes of change are further compared. For example, the cumulative flux difference or relative rate of change between different scenarios can be calculated to quantify the sensitivity of changes in hydrological conditions to carbon output.

[0073] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. The scope of protection of the present invention is defined by the claims. Similarly, any equivalent structural changes made based on the description and drawings of the present invention should also be included within the scope of protection of the present invention.

Claims

1. A regional water-carbon cycle process coupling simulation prediction system, characterized in that, include: The data acquisition module performs raster discretization on selected watersheds and riverbanks under a unified geographic space and time step; and obtains the vegetation type and soil organic carbon content within each riverbank raster unit. The hydrological process simulation module uses a digital elevation model to extract the flow direction relationship of each watershed grid cell, constructs the watershed's confluence path and upstream and downstream topology, and calculates the runoff of each watershed grid cell under given meteorological conditions. The carbon status update module defines the carbon source intensity for each riverbank grid unit based on the soil organic carbon content and vegetation type of each riverbank grid unit. The carbon source intensity is used to characterize the potential level of dissolved carbon released by the riverbank grid unit into the watershed under the action of unit runoff. The coupled simulation module identifies, for any watershed grid cell, riverbank grid cells with hydrological connectivity to the carbon input of that watershed grid cell along the upstream confluence path; and constructs spatial weighting coefficients based on the confluence path distance, slope aspect consistency, and flow direction connectivity of the riverbank grid cells to the target watershed grid cell. These spatial weighting coefficients are used to characterize the attenuation effect of carbon during transport. Based on the spatial weighting coefficient, the runoff at the corresponding time step is coupled with the carbon source intensity of the riverbank grid cell to calculate its carbon output flux; according to the confluence path, the carbon output flux of each watershed grid cell is transmitted and accumulated downstream step by step to calculate the carbon flux at the watershed outlet. The carbon budget prediction module uses the outlet of the basin as the control position to perform time integration of carbon flux to obtain the total carbon output of the selected basin; and calculates the carbon concentration change process in combination with the flow at the basin outlet. By adjusting the given meteorological conditions to drive runoff changes, it predicts the change characteristics of basin carbon output under different meteorological conditions.

2. The regional water-carbon cycle process coupling simulation and prediction system according to claim 1, characterized in that, In the acquisition module, under a unified geographic raster unit and time step, the following processing is performed; Obtain digital elevation model data for the selected watershed, determine the watershed range based on the digital elevation model, and perform rasterization on the watershed range; based on the extracted spatial location of the river channel, identify the riverbank area according to a preset distance range, and mark the corresponding riverbank raster units; The vegetation type data and soil organic carbon content data corresponding to the riverbank grid unit are obtained, and the vegetation type data and soil organic carbon data are mapped to a unified geographic grid unit according to their spatial location to form the vegetation type distribution and soil organic carbon spatial distribution corresponding to each riverbank grid unit.

3. The coupled simulation and prediction system for regional water and carbon cycle processes according to claim 2, characterized in that, After filling depressions in the digital elevation model, the hydrological process simulation module uses a flow direction algorithm to determine the flow direction of each watershed grid unit, and determines the confluence path of each watershed grid unit and its upstream and downstream connection relationship. Under given meteorological conditions, the hydrological process simulation module calculates the runoff at the current time step based on the rainfall input and underlying surface characteristics of each watershed grid cell. Along the confluence path, the runoff generated by each watershed grid unit is transmitted downstream and accumulated step by step to obtain the flow process in the watershed channel.

4. The coupled simulation and prediction system for regional water and carbon cycle processes according to claim 1, characterized in that, Based on the riverbank grid cells marked in the acquisition module, the carbon state update module extracts all riverbank grid cells as carbon source calculation objects and obtains the soil organic carbon content and vegetation type data corresponding to each riverbank grid cell. Based on the preset vegetation type classification parameters, different vegetation types are assigned corresponding carbon release coefficients, and the carbon source intensity of each riverbank grid unit is calculated by combining the product of the soil organic carbon content of the corresponding riverbank grid unit.

5. The coupled simulation and prediction system for regional water and carbon cycle processes according to claim 1, characterized in that, For any watershed grid cell, the coupled simulation module traces upstream based on the constructed confluence path and upstream-downstream topology to identify all the riverbank grid cells located on its confluence path, as the source grid set that contributes carbon to the watershed grid cell.

6. The coupled simulation and prediction system for regional water and carbon cycle processes according to claim 4, characterized in that, In the source grid set, the coupled simulation module constructs corresponding spatial weight coefficients based on the confluence path distance from each riverbank grid cell to the current watershed grid cell, topographic slope consistency, and flow connectivity. : ； in, Riverbank Grid Unit To the current watershed grid cell distance, The attenuation coefficient is used; for riverbank grid cells that do not satisfy the confluence connectivity relationship, their spatial weight coefficient is set to zero.

7. The coupled simulation and prediction system for regional water and carbon cycle processes according to claim 6, characterized in that, The coupled simulation module, based on the spatial weighting coefficient, performs a weighted summation of the carbon source intensity of each riverbank grid cell to obtain the equivalent carbon source intensity of the current watershed grid cell; the equivalent carbon source intensity is then combined with the runoff of the watershed grid cell at the current time step to calculate the carbon output flux of the watershed grid cell. According to the aforementioned confluence path, the carbon output flux generated by each watershed grid unit is transmitted step by step to the downstream grid units and the river channel, and is accumulated with the carbon flux carried by the upstream water during the transmission process to obtain the carbon flux process at the watershed outlet.

8. The coupled simulation and prediction system for regional water and carbon cycle processes according to claim 1, characterized in that, The carbon budget prediction module uses the designated watershed outlet as the control position to extract the carbon flux time series data accumulated step by step through the confluence path from the coupled simulation module, as well as the river flow data at the corresponding time step. According to the set time window, the carbon flux at the outlet of the basin is accumulated over time to obtain the total carbon output of the basin within the time window. At each time step, the ratio of carbon flux at the watershed outlet to the corresponding river flow is calculated to obtain the carbon concentration change process at the corresponding time step.

9. The coupled simulation and prediction system for regional water and carbon cycle processes according to claim 8, characterized in that, When making predictions, the carbon budget prediction module constructs input data sequences under different hydrological scenarios by adjusting the input meteorological condition parameters, which include rainfall amount and rainfall time series. Under different hydrological scenarios, the hydrological process simulation module and the coupled simulation module were repeatedly executed to obtain the carbon flux and flow process at the watershed outlet under the corresponding scenarios. The carbon output fluxes obtained under different hydrological scenarios were compared and analyzed, and their variation within a set time window was calculated to characterize the impact of changes in hydrological conditions on the watershed carbon output process.

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