A method and system for rapid measurement of surface biomass of hillside and small watershed

Abstract

The application discloses a kind of slope and small watershed surface biomass rapid measurement method and system thereof.The method is based on water and sediment dynamics and similarity theory, constructs the three-dimensional physical model covering rainfall, soil and vegetation characteristics, obtains model biomass by dynamic simulation test, deduces biomass scale λ BH Combining static geometric scale and vegetation bulk density scale Y M BH M M Actual biomass of prototype area is converted to get by conversion formula. Corresponding system includes modeling module, dynamic simulation device, data processing unit and verification module. The method has the characteristics of high measurement accuracy, strong non-destructive and wide applicability, and is suitable for biomass monitoring, ecological assessment and vegetation restoration process analysis in ecologically fragile areas such as the Loess Plateau.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of water and soil conservation, ecological restoration and watershed management, and in particular to a method for rapid estimation of surface biomass for slope land and small watershed areas and a matching system thereof. BACKGROUND

[0002] With the deepening of ecological engineering such as "returning farmland to forest (grass)", the ecological environment of the Loess Plateau region has been significantly improved. For example, in the Yellow River Basin, by 2017, its vegetation coverage has increased from 31.6% before 1999 to 65%, the ecosystem function has been significantly enhanced, the soil erosion has been significantly reduced, and the water and sediment resources of the Yellow River and its tributaries have also been reduced. Although this achievement shows that the regional ecological restoration effect is good, it has also caused a number of new environmental problems. For example, the soil water consumption in the Loess Plateau region has increased significantly, the dry layer has intensified, and the vegetation in some areas has begun to degrade; at the same time, excessive vegetation restoration can also cause a sharp decrease in runoff, leading to the shrinkage of the lower reaches of the Yellow River and the increasing tension between water supply and demand.

[0003] In actual research and management work, surface vegetation biomass as an important indicator reflecting the structure and function of the watershed ecosystem, is widely used in ecological restoration evaluation, carbon storage accounting, hydrological process simulation and future management planning. However, the existing biomass estimation techniques mainly rely on two methods: one is large-scale field cutting sampling, although the sampling data is true and reliable, but it is time-consuming and labor-intensive, and destructive, especially the sampling of underground part is difficult and the overall representativeness of the sampling point limits the precision; the other is inversion estimation based on remote sensing image, although it has the advantage of non-destructive measurement, but the precision is easily affected by factors such as terrain, climate, sensor resolution, especially in the small watershed area with complex terrain and diverse vegetation structure, the estimation result is often difficult to accurately reflect the true biomass.

[0004] In addition, the traditional method often deviates from the background of water and sediment transport and other hydrodynamic processes in the operation process, and cannot realize the coupling of biomass estimation and dynamic processes such as rainfall, erosion and runoff, resulting in mismatch between biomass evaluation results and actual hydrological regime. Therefore, on the basis of considering the estimation efficiency, result accuracy and ecological integrity, a new method is needed to quickly and nearly non-destructively complete the biomass evaluation. The method should be able to integrate the geometric characteristics of the watershed, the terrain conditions, the vegetation distribution and the hydrodynamic process, and provide a method for estimating the biomass that can be promoted, simulated and predicted.

[0005] To address the aforementioned needs and the shortcomings of existing technologies, this invention proposes a method for deriving and calculating watershed surface vegetation biomass based on water and sediment dynamics and similarity principles, utilizing a physical scale model. By constructing a watershed model encompassing the three-dimensional solid structures of rainfall, soil, and vegetation, and combining parameters such as static geometric scale and vegetation bulk density scale, a biomass similarity conversion relationship is established between the prototype and the model, enabling rapid estimation and simulation of biomass at the watershed scale. This method features a simple calculation process, clear physical meaning, and high accuracy verified by field measurements, making it particularly suitable for ecological restoration monitoring and management assessment in ecologically fragile areas such as the Loess Plateau hilly and gully regions. Summary of the Invention

[0006] To address the limitations of existing biomass measurement methods, such as the representativeness of sampling points, difficulties in underground biomass sampling, the destructive nature of deforestation measurements, low accuracy, and difficulty in coupling with hydrodynamic processes, this invention provides a rapid method and system for measuring surface biomass on slopes and in small watersheds. Based on hydrodynamics and similarity theory, this method constructs a physical model and obtains model biomass through simulation experiments. By introducing static geometric scales and vegetation bulk density scales, a biomass scale is derived, enabling rapid, non-destructive, and high-precision conversion of surface vegetation biomass in the prototype watershed. This technology can significantly improve the efficiency of vegetation evolution monitoring in ecological restoration areas, especially in typical soil erosion areas such as the Loess Plateau, filling the gap in existing technologies regarding "multi-factor coupling and rapid quantitative estimation," and possesses significant theoretical value and engineering practical significance.

[0007] In one possible implementation, a method for rapid measurement of surface biomass in slopes and small watersheds is provided. This method is based on the principles of water and sediment dynamics and similarity theory. It constructs a three-dimensional solid model that can reflect the natural characteristics of the actual watershed, such as landforms, rainfall, soil structure and vegetation distribution. Through the simulation output data of this model, a high-precision prediction and quantitative assessment of biomass in the prototype area can be achieved.

[0008] The method includes the following steps:

[0009] Construct a three-dimensional solid model: Based on the topography, landforms, rainfall, soil and vegetation characteristics of the prototype watershed, construct a solid model that is similar to the prototype in terms of geometric movement dynamics. This model must at least meet the similarity requirements of key factors such as water and sediment transport and vegetation distribution.

[0010] Dynamic simulation to obtain model biomass M M Under artificially controlled rainfall and water flow conditions, dynamic simulation experiments were conducted on the physical model to record the vegetation growth status and related biomass parameters at different time points and in different watershed sections.

[0011] Calculate the biomass ratio λ BH: Combining the static geometric scale λ between the prototype watershed and the model l Compared with vegetation bulk density ratio λ ρ Based on the derivation of relation λ BH =λ ρ λ l Establish biomass conversion relationships;

[0012] Converting to prototype biomass M Y Using the conversion formula M Y =λ BH M M The biomass results measured in the model are converted into vegetation biomass values ​​of the actual prototype area.

[0013] In one possible implementation, the construction of the entity model includes the following technical means:

[0014] Collect basic data such as watershed length, width, slope, gradient, and geomorphological features;

[0015] Calculate the static geometric scale λ using these data. l This serves as the basis for model scaling.

[0016] A physical model was constructed based on the water-sediment similarity theory, and natural sand, gravel and other materials were used to simulate the topography and soil of the real watershed.

[0017] Rainfall simulation experiments were conducted under controlled conditions to verify the consistency between the physical model and the prototype watershed in terms of hydrodynamic processes.

[0018] In one possible implementation, to improve the accuracy of vegetation characteristic conversion, the vegetation bulk density scale λ needs to be determined by the following method. ρ :

[0019] In the prototype watershed, a typical area was selected, and the dry mass of aboveground vegetation was determined by the quadrat method or the excavation method.

[0020] Correspondingly, artificial vegetation materials with equivalent height and density are laid out in the physical model;

[0021] The scale λ is calculated using the ratio of vegetation bulk density between the prototype and the corresponding areas of the model. ρ The mean of multiple regional samples was used as the final scale input value.

[0022] In one possible implementation, the biomass ratio is λ. BH The derivation follows a similar theoretical process as follows:

[0023] Establish a biomass expression per unit area

[0024] Combining the first law of similarity, the following can be derived from the perspectives of geometry, mass, and volume scale:

[0025]

[0026] consider (where λ) V λ is the volume scale; A λ is the area scale; l After simplifying to obtain the final form (using static geometric scale), the final form is obtained.

[0027] In one possible implementation, the similarity conditions for biomass per unit area are further clarified to improve the consistency and suitability of the results. These conditions include:

[0028] The geometric shapes of the leaves, stems, and stalks of the above-ground parts of vegetation are similar between the model and the prototype;

[0029] The vegetation coverage in the simulated area reached a similar coverage rate to that of the prototype area, with an error within 10%.

[0030] The simulated root system structure layout conforms to the root distribution pattern or density of the prototype area.

[0031] In one possible implementation, to verify the accuracy and reliability of the calculation results, the following verification steps also need to be set up:

[0032] Select no fewer than three typical areas with different vegetation types or slope aspects in the prototype watershed;

[0033] Biomass measurements were conducted in the field.

[0034] The converted model predictions are compared with the measured values, and the relative error between the two is required to be controlled within 5% to ensure the reliability of the model output.

[0035] In one possible implementation, the present invention also provides a rapid land biomass measurement system supporting the execution of the above-described method, the system comprising:

[0036] 3D modeling module: used to collect prototype watershed data and build a physical model;

[0037] Dynamic simulation devices include artificial rainmaking equipment and water conveyance systems, used to reproduce actual meteorological and hydrological conditions;

[0038] Data processing unit: Equipped with data acquisition and processing software, it performs scale calculations and biomass calculations;

[0039] Verification module: Used to upload measured data, compare and analyze it with simulated output results, and generate an error analysis report.

[0040] In one possible implementation, the method is well-suited for ecological restoration projects, and is particularly applicable to:

[0041] Monitoring of biomass recovery during the process of converting farmland back to forest (grassland) in the Loess Plateau region;

[0042] Simulated biomass evolution trends under different rainfall scenarios and governance schemes;

[0043] It provides scientific biomass data support for regional soil and water conservation planning and ecological engineering design.

[0044] Based on the above technical solutions, the method and system for rapid calculation of surface biomass in slopes and small watersheds provided by this invention, by introducing physical model similarity theory and combining rainfall simulation, water and sediment transport and vegetation layout characteristics, can achieve rapid, non-destructive and high-precision calculation of surface vegetation biomass in a highly controllable manner.

[0045] Compared with the prior art, this application has the following beneficial effects:

[0046] 1. Non-destructive measurement: No destructive sampling of the prototype watershed is required, thus protecting the ecological environment;

[0047] 2. High precision: Through scale derivation and error verification control, the measurement accuracy can be controlled within 5%;

[0048] 3. Wide applicability: It can be widely applied to ecosystem simulation in different scales and types of watersheds;

[0049] 4. Strong dynamic simulation capability: Through adjustable simulation experiments, it is suitable for predicting extreme weather or future scenarios;

[0050] 5. Systematic Implementation: The complete supporting system equipment makes it easy to promote to laboratory teaching, scientific research and engineering practice.

[0051] In summary, this invention not only solves the problems of insufficient accuracy and high operational destructiveness of existing biomass measurement technologies, but also provides a new scientific, rapid, efficient, and visualized tool and method for regional ecosystem monitoring and governance assessment. Attached Figure Description

[0052] Figure 1 This is a technical flowchart of the method for rapid measurement of surface biomass in small watersheds as described in this invention, which shows the overall technical route from obtaining prototype watershed parameters, constructing physical models, deriving biomass scale, dynamic simulation experiments to prototype biomass conversion and verification.

[0053] Figure 2This is a schematic diagram illustrating the derivation process of biomass scale in this invention, showing the expression for biomass per unit area, the similarity analysis between the model and the prototype, the scale relationship, the derivation path of formulas (3) to (10), and the geometric scale λ. l Compared with the density ratio λ ρ The role and logic in biomass scale calculation. Detailed Implementation

[0054] This invention provides a rapid method and supporting system for measuring surface biomass in sloping areas and small watersheds. Based on hydrodynamics and similarity theory, it achieves rapid, non-destructive, and high-precision measurement of vegetation biomass in a prototype area through the construction of a physical model, simulation experiments, and scale conversion. The specific implementation of this invention is illustrated below using a practical application scenario from a typical small watershed in the Loess Plateau.

[0055] During implementation (e.g.) Figure 1 As shown in the figure, a prototype watershed with representative and typical water and sediment erosion characteristics is first selected as the modeling basis. In this embodiment, the Kangjiagelao small watershed in the Yanhe River Basin of the middle reaches of the Yellow River is selected as the study area. The small watershed is located between 109°20′ and 109°35′ east longitude and 36°21′ and 36°32′ north latitude. The landform type is an erosive loess hilly gully area with a gully density of 3-4 km / km. 2 The terrain is fragmented and heavily eroded, exhibiting typical characteristics of water and sediment transport. The drainage area is approximately 0.35 km². 2 The main ditch is 0.903 km long, with a maximum width of 0.723 km, an average width of 0.52 km, a shape coefficient of 0.52, and an elevation difference of 189.7 m. A silt-retaining dam is located at the watershed outlet, which is beneficial for the control and monitoring of subsequent runoff and sediment yield. The vegetation types in the watershed are mainly trees, shrubs, and herbaceous plants, with a coverage of over 80%. Typical vegetation includes black locust, sea buckthorn, and Artemisia annua, with a clear vegetation structure and a high degree of ecological restoration.

[0056] Based on the aforementioned prototype parameters, the static geometric scale λ is determined according to the watershed's geometric characteristics. l In this example, a scale of 1:100 is selected for physical modeling. The solid model is constructed using a steel frame structure as a support platform, with a compacted layer of coarse sand mixed with prototype soil laid on the base to reproduce the underlying surface conditions and soil erosion of the prototype area. Topographic reproduction is completed through laser template cutting and manual sculpting to ensure that the main ditch, secondary ditch, and slope structure maintain the same slope aspect and gradient as the prototype.

[0057] The model incorporates simulated vegetation materials to mimic ground cover. Fiber bundles and plastic plants of varying heights correspond to herbaceous, shrubby, and tree types, respectively, and are arranged according to actual density per unit area to ensure consistent coverage and structural hierarchy with the prototype area at the model scale. Simultaneously, an adjustable artificial rainmaking device is installed above the model, using high-density nozzles to simulate natural rainfall. The rainfall intensity is controlled between 0.01 and 6 mm / min, with raindrop kinetic energy and particle size closely resembling natural conditions. The spray height is approximately 10 m to achieve dynamic similarity.

[0058] During the simulation experiment, runoff processes, erosion, water and sediment transport pathways, and simulated vegetation status were recorded after a set rainfall intensity was applied. After the experiment, the dry mass of the simulated vegetation material was collected and measured within pre-set standard plots in the model to obtain the biomass M per unit area of ​​the model. M Value. In this embodiment, the average biomass measured by the model was 0.038 g / m³. 2 Subsequently, combining the model material density data obtained from the preliminary field survey with the measured vegetation bulk density data from the prototype, the vegetation bulk density scale λ was calculated. ρ It is approximately 4.1. Based on the geometric scale λ... l For 100, apply formula (2)λ BH =λ ρ λ l The biomass conversion scale λ was obtained. BH =410. Finally, according to M Y =λ BH M M The biomass per unit area of ​​the prototype was calculated, and M was obtained. Y Approximately 15.58 g / m 2 .

[0059] To verify the accuracy of the measurements, three representative sample areas were selected in the Kangjiagelao watershed, located on the south slope, north slope, and bottom of the gully. Three 1m sampling points were established in each sample area. 2 The biomass of the sampled samples, after field collection, drying, and weighing, was found to be 15.2–16.3 g / m². 2 The relative error between the conversion results and the measured data was controlled within 5%, which fully verified the applicability of the method and the accuracy of the model calculation.

[0060] Furthermore, to further strengthen the theoretical support for verification, this invention cites the results of a field study on vegetation biomass conducted by Xu Xuexuan et al. in 2002 in the Yangou watershed of the Loess Plateau (as shown in Table 1). This study measured the biomass per unit area for trees, shrubs, and herbs to be 522, 504, and 491 g / m², respectively. 2 The corresponding bulk density ranges are 0.40–0.80, 0.2–0.45, and 0.02–0.10 t / m³. 3In this invention, grass materials of different heights were used to replace the prototype trees, shrubs, and grasses in the model construction, and the density of the simulated materials was adjusted so that their bulk density ratio was 4. Under a 10×10cm quadrat plot, the simulated biomass of trees, shrubs, and grasses were measured to be 672, 560, and 576 g / m², respectively. 2 The relative error is controlled within 1% to 2%, which is far lower than the error range of traditional methods (5% to 10%), further demonstrating the superiority of this method in terms of accuracy control per unit area and vegetation structure restoration.

[0061] Table 1. Characteristic parameters for vegetation biomass similarity verification

[0062]

[0063] The above results demonstrate that the physical model and similarity scale system established in this invention can effectively reproduce the aboveground biomass distribution and density characteristics under various vegetation types in the prototype small watershed, verifying the accuracy and versatility of the method in real-world scenarios, and further confirming the feasibility and engineering adaptability of the scale derivation formula and model simulation system.

[0064] To further clarify the theoretical basis of the biomass scale conversion relationship in this invention, the derivation process of the biomass scale is hereby publicly explained (e.g., Figure 2 (As shown).

[0065] This invention assumes that the prototype watershed vegetation includes forests, shrubs, grasses, and litter. Based on similarity theory, it is assumed that the model and the prototype share morphological and parameter consistency in terms of geometric structure, cover density, and spatial distribution. To uniformly describe the vegetation quality characteristics of different regions, an expression for plant biomass per unit area is introduced.

[0066] According to formula (3):

[0067]

[0068] Wherein, pH is the plant biomass per unit area (kg / m²). 2 M is the dry mass per unit area, V is the volume, A is the area of ​​a certain region, and ρ is the bulk density. This formula uniformly combines the three-dimensional structure and density characteristics into a surface density parameter.

[0069] Applying this formula to both the prototype and model regions yields:

[0070] Formula (4):

[0071] Formula (5):

[0072] Among them, PH y With pH mThe biomass per unit area for the prototype and the model, respectively, M y A y V y ρ y and M m A m V m ρ m These are the biomass parameters for the prototype and the model, respectively.

[0073] Converting the above ratios to scale form, we get:

[0074] Formula (6): λ BH =PH y / PH m =(M y / M m )·(A m / A y )=(λ V ·λ ρ ) / λ A

[0075] This formula reveals the biomass ratio per unit area (λ) BH ) by volume scale (λ V ), density ratio (λ) ρ ) and area scale (λ) A The joint determination of biomass conversion is the core physical relationship.

[0076] To verify the consistency between the model and the prototype from another perspective, according to the first law of similarity, the model expression can also be written as:

[0077] Formula (7):

[0078] Comparing formulas (5) and (7), to make the equation hold, we have:

[0079] Formula (8):

[0080] Further transformation yields the general expression for the biomass ratio:

[0081] Formula (9):

[0082] Where, λ m =λ V ×λ ρ

[0083] Due to volume ratio Area scale Substituting it into formula (9), we get the final simplified formula:

[0084] Formula (10)

[0085] That is, the biomass scale is equal to the product of the static geometric scale and the vegetation bulk density scale.

[0086] Therefore, the biomass M per unit area of ​​the prototype region in this invention Y It can be calculated using the following formula:

[0087] Formula (1) (Final Conversion Relationship):

[0088] M Y =λ BH M M

[0089] Among them, M M This refers to the biomass per unit area measured by the model. The entire derivation process described above constitutes the core theoretical support for the "model-prototype conversion" of this invention. Under the premise of maintaining physically measurable input parameters, it constructs a measurement method framework with a clear mathematical structure and reliable traceability.

[0090] To achieve the systematic application of the above methods, this embodiment also constructs a supporting rapid calculation system, including a 3D modeling module, a dynamic simulation test platform, a data processing unit, and a result verification module. The modeling module can import DEM data to automatically generate model terrain parameters. The test platform includes an adjustable rainfall system and a runoff acquisition system. The data unit embeds conversion algorithms, and the verification module supports comparison of measured data and error report output. This system has strong adaptability in ecological restoration projects and can be used for vegetation biomass monitoring and dynamic simulation in different ecological types such as the Loess Plateau, karst regions, and arid areas. It is particularly suitable for comparative analysis of the impact of different restoration intensities and strategies on surface vegetation evolution in scenarios such as returning farmland to forest (grassland), closure and restoration, and comprehensive soil and water conservation. By adjusting the simulated rainfall parameters, it can also be applied to ecological response prediction research under extreme weather conditions.

[0091] In summary, this invention constructs a solid model that shares geometric, kinematic, and dynamic similarities with the prototype watershed. By combining scale derivation and simulation calculation methods, it achieves efficient simulation and accurate measurement of surface biomass in small watersheds under non-destructive conditions. This method is structurally rigorous, reliable in its conversion, and combines theoretical depth with engineering practicality, making it suitable for applications in various fields such as ecological restoration, vegetation monitoring, and soil and water conservation.

Claims

1. A method for rapid calculation of surface biomass on slopes and in small watersheds, characterized in that, include: S10: Construct a physical model that has geometric and dynamic similarity to the prototype watershed, wherein the model at least covers the three-dimensional similarity features of water and sediment transport in rainfall, soil and vegetation; S20: Obtaining model biomass through dynamic simulation experiments ; S30: Based on static geometric scale and vegetation bulk density ratio According to the formula Calculate the biomass scale; S40: According to the conversion formula Calculate prototype biomass ; The construction of the entity model includes: Static geometric scale determined based on watershed length, width, gradient, and topographic parameters. ; Physical models at the scale of slope, cross section, or watershed are created using the principles of hydrodynamics. The dynamic similarity between the model and the prototype was verified through rainfall and sediment transport experiments; The vegetation bulk density ratio The determination includes: Plant dry bulk density was measured in a typical area of ​​the prototype watershed. Calculate the ratio of vegetation bulk density in the corresponding areas of the model and the prototype; Determined by multi-regional measurement mean ; The biomass ratio The derivation includes: Establish a biomass expression per unit area ; Derived from the first law of similarity ; Substitute geometric relations ,in Volume scale; Area scale; As a static geometric scale, the final result is .

2. The method according to claim 1, characterized in that, The similarity requirements for biomass per unit area include: (1) The leaves, stems and stalks of the aboveground parts of vegetation have similar geometric shapes; (2) Vegetation coverage similarity ≥ 90%; (3) The distribution pattern of underground roots is consistent.

3. The method according to claim 1, characterized in that, It also includes a verification step: (1) Select at least 3 verification areas in the prototype watershed for field biomass measurement; (2) The relative error between the calculation result and the actual measured data is required to be ≤5%.

4. A system for implementing the method according to any one of claims 1-3, characterized in that, include: (1) 3D modeling module, used to construct geometric and dynamic similarity models; (2) Dynamic simulation device, equipped with test equipment for adjustable rainfall intensity; (3) Data processing unit, used to perform scale calculation and biomass conversion; (4) Verification module, used to compare the calculated value with the measured data.

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