A rainfall segmentation method, device and electronic equipment for a shallow loess landslide

Abstract

The present application relates to landslide early warning technical field, especially shallow loess landslide rainfall segmentation method, device and electronic equipment. Method includes: obtaining meteorological data of loess area to be measured, and determining rainfall critical value and rainfall intensity critical value according to meteorological data;And the real-time rainfall of loess area is obtained, and the collection time of real-time rainfall is accumulated and real-time rainfall, the total value of real-time rainfall and rainfall duration are obtained;And according to the comparison result of total value of real-time rainfall and rainfall critical value, according to the comparison result of rainfall duration and preset time length, whether to start calculating the rainfall data of shallow loess landslide, and the rainfall data of shallow loess landslide are calculated, so that the rainfall related to loess landslide and the rainfall unrelated to loess landslide are segmented, the rainfall data of shallow loess landslide is obtained, which is more in line with the characteristics of loess area, and more effective rainfall data is provided for shallow loess landslide early warning analysis.

Description

Technical Field

[0001] This invention relates to the field of landslide early warning technology, and in particular to a rainfall segmentation method, device and electronic equipment for shallow loess landslides. Background Technology

[0002] Two-thirds of my country's land area is mountainous, and landslides in these areas can cause casualties and property damage. Historical landslide data shows that most landslides in mountainous areas are caused by rainfall, especially in loess regions. To prevent landslide disasters, current technology utilizes rainfall data for landslide monitoring and early warning.

[0003] However, not all rainfall contributes to landslides. Without segmenting rainfall to distinguish between impactful and non-impactful rainfall, landslide misjudgments are likely, leading to low accuracy in landslide warnings. Furthermore, different mountainous areas possess varying geographical characteristics, resulting in different rainfall effects even under the same conditions. Currently, no rainfall segmentation method suitable for shallow loess landslides has been proposed, making it difficult to obtain effective rainfall data affecting shallow loess landslides and thus hindering the improvement of landslide warning accuracy. Summary of the Invention

[0004] This invention provides a rainfall segmentation method, apparatus, and electronic device for shallow loess landslides, used to obtain rainfall data affecting shallow loess landslides and improve the accuracy of early warning for shallow loess landslides.

[0005] The first aspect of this invention provides a rainfall segmentation method for shallow loess landslides, the method comprising:

[0006] S1: Obtain meteorological data for the Loess Plateau region to be tested, and determine the critical values ​​for rainfall amount and rainfall intensity based on the meteorological data;

[0007] S2: Obtain and accumulate the real-time rainfall in the Loess region to obtain the total real-time rainfall value, and accumulate the collection time of the real-time rainfall to obtain the rainfall duration;

[0008] S3: When the total real-time rainfall reaches the rainfall threshold, determine whether the rainfall duration is greater than the preset duration. If not, execute S4; if so, clear the total real-time rainfall and the rainfall duration, and re-execute S2.

[0009] S4: Calculate the rainfall intensity based on the rainfall duration and the total real-time rainfall. When the rainfall intensity is less than the rainfall intensity threshold, output the total real-time rainfall and the rainfall duration as the rainfall data that triggered the shallow loess landslide. Then clear the total real-time rainfall and the rainfall duration, and re-execute S2.

[0010] Optionally, S4 further includes:

[0011] When the rainfall intensity is not less than the rainfall intensity threshold, continue to update the total real-time rainfall and the rainfall duration according to S2, and update the rainfall intensity according to the updated total real-time rainfall and the updated rainfall duration, until the updated rainfall intensity is less than the rainfall intensity threshold.

[0012] Optionally, the meteorological data includes the annual average rainfall and the average annual maximum and minimum rainfall intensity.

[0013] The steps of determining the critical values ​​for rainfall amount and rainfall intensity based on the meteorological data include:

[0014] Calculate the critical rainfall value based on the annual average rainfall;

[0015] The critical value of rainfall intensity is calculated based on the average of the annual maximum and minimum rainfall intensity.

[0016] Optionally, the formula for calculating the rainfall threshold is:

[0017] R*=0.1RN

[0018] Where R* is the critical rainfall value, and RN is the average annual rainfall in the Loess region.

[0019] Optionally, the formula for calculating the critical value of rainfall intensity is:

[0020] I* = 0.02IM

[0021] Where I* is the critical value of rainfall intensity, and IM is the average annual maximum and minimum rainfall intensity in the Loess region.

[0022] Optionally, the real-time rainfall is the rainfall on the loess plateau in the loess region.

[0023] Optionally, the real-time rainfall is collected by sensors installed on the plateau.

[0024] Optionally, the number of sensors may be multiple.

[0025] In another aspect, the present invention provides a rainfall segmentation device for shallow loess landslides, the device comprising:

[0026] The acquisition module is used to acquire meteorological data of the Loess Plateau region to be measured, and to determine the critical values ​​for rainfall amount and rainfall intensity based on the meteorological data.

[0027] The accumulation module is used to acquire and accumulate the real-time rainfall in the Loess region to obtain the total real-time rainfall value, and to accumulate the acquisition time of the real-time rainfall to obtain the rainfall duration;

[0028] The first judgment module is used to determine whether the rainfall duration is greater than a preset duration when the total real-time rainfall value reaches the rainfall threshold. If not, the second judgment module is triggered; if so, the total real-time rainfall value and the rainfall duration are cleared, and the accumulation module is triggered again.

[0029] The second judgment module is used to calculate the rainfall intensity based on the rainfall duration and the total real-time rainfall. When the rainfall intensity is less than the rainfall intensity threshold, the module outputs the total real-time rainfall and the rainfall duration as the rainfall data that triggered the shallow loess landslide. Then, the module clears the rainfall duration and the total real-time rainfall and re-triggers the accumulation module.

[0030] In another aspect, the present invention provides an electronic device, the device comprising a processor and a memory:

[0031] The memory is used to store program code and transmit the program code to the processor;

[0032] The processor is used to execute the method described above according to the instructions in the program code.

[0033] As can be seen from the above technical solutions, the present invention has the following advantages:

[0034] This invention provides a rainfall segmentation method for shallow loess landslides, comprising: S1: acquiring meteorological data of the loess region to be measured, and determining a rainfall threshold and a rainfall intensity threshold based on the meteorological data; S2: acquiring and accumulating the real-time rainfall of the loess region to obtain a total real-time rainfall value, and accumulating the acquisition time of the real-time rainfall to obtain the rainfall duration; S3: when the total real-time rainfall value reaches the rainfall threshold, determining whether the rainfall duration is greater than a preset duration; if not, proceeding to S4; if so, clearing the total real-time rainfall value and the rainfall duration, and re-executing S2; S4: calculating the rainfall intensity based on the rainfall duration and the total real-time rainfall value; when the rainfall intensity is less than the rainfall intensity threshold, outputting the total real-time rainfall value and the rainfall duration as the rainfall data for triggering the shallow loess landslide, then clearing the total real-time rainfall value and the rainfall duration, and re-executing S2.

[0035] This invention acquires meteorological data of the loess region to be measured, and determines the critical values ​​for rainfall amount and rainfall intensity based on the meteorological data. It also acquires real-time rainfall data of the loess region, accumulates the collection time and the amount of real-time rainfall to obtain the total real-time rainfall value and rainfall duration. Based on the comparison between the total real-time rainfall value and the rainfall critical values, and the comparison between the rainfall duration and a preset duration, it determines whether to start calculating rainfall data that triggers shallow loess landslides. This separates rainfall related to loess landslides from rainfall unrelated to loess landslides, making the obtained rainfall data that triggers shallow loess landslides more consistent with the characteristics of the loess region. This provides more effective rainfall data for loess landslide early warning analysis, thereby improving the accuracy of shallow loess landslide early warning. Attached Figure Description

[0036] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0037] Figure 1 A schematic diagram of a rainfall segmentation method for shallow loess landslides provided in an embodiment of the present invention;

[0038] Figure 2 A schematic diagram of a rainfall segmentation method for shallow loess landslides provided in another embodiment of the present invention;

[0039] Figure 3 This is a schematic diagram of a rainfall segmentation device for shallow loess landslides provided in an embodiment of the present invention. Detailed Implementation

[0040] Rainfall increases the water content in the slope soil, raises the groundwater level, and increases pore water pressure, thereby reducing slope stability. Under the influence of continuous rainfall, landslides can be triggered. Natural rainfall processes are highly complex and do not repeat. Therefore, in current technology, rainfall preceding the main heavy rainfall that triggers a loess landslide is collectively referred to as pre-landslide rainfall. Identifying pre-landslide rainfall helps distinguish between rainfall that has an impact on and does not affect landslides.

[0041] Different geological regions, due to variations in vegetation, topography, characteristics, and rainwater infiltration channels, will produce different effects even under the same rainfall conditions. Based on the thickness of the landslide body, landslides can be classified into four types: shallow landslides, intermediate landslides, late-stage landslides, and very thick-layer landslides. However, current technology lacks rainfall analysis methods specifically for shallow loess landslides, making it difficult to effectively determine the rainfall data that triggers them, thus potentially reducing the accuracy of shallow loess landslide early warning systems.

[0042] To overcome the shortcomings of the prior art, this invention provides a rainfall segmentation method, device, and electronic device for shallow loess landslides, which distinguishes between rainfall that has no impact on landslides and rainfall that does, obtains rainfall data that affects shallow loess landslides, and improves the accuracy of early warning for shallow loess landslides.

[0043] To make the objectives, features, and advantages of this invention more apparent and understandable, the technical solutions of the embodiments of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described below are only some embodiments of this invention, and not all embodiments. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0044] It should be noted that the rainfall segmentation method for shallow loess landslides provided in this embodiment of the invention is applied to loess areas with landslide bodies that have specific topographic conditions. Specific topographic conditions refer to the fact that the upper catchment area of ​​the landslide body is located on the plateau, and the catchment area is a gentle terrain with an almost 0-degree slope, and there is an open surface at the bottom.

[0045] Example 1:

[0046] Please see Figure 1 , Figure 1 This is a schematic diagram of a rainfall segmentation method for shallow loess landslides provided in an embodiment of the present invention.

[0047] This embodiment provides a rainfall segmentation method for shallow loess landslides, the method including:

[0048] S1: Obtain meteorological data for the Loess Plateau region to be tested, and determine the critical values ​​for rainfall amount and rainfall intensity based on the meteorological data.

[0049] It should be noted that the loess region to be measured refers to the loess region to be monitored, which can be determined according to monitoring needs. Meteorological data includes the annual average rainfall and the average annual maximum and minimum rainfall intensity. The meteorological data is historical data, which can be obtained by consulting the hydrological handbook of loess climate or meteorological station data. Then, utilizing the unique geographical features of the loess region and combining it with the meteorological data, critical rainfall and intensity values ​​suitable for the loess region are determined, serving as the criteria for determining rainfall segmentation affecting shallow loess landslides.

[0050] S2: Obtain and accumulate the real-time rainfall in the Loess Plateau region to obtain the total real-time rainfall value, and accumulate the collection time of the real-time rainfall to obtain the rainfall duration.

[0051] It should be noted that sensors are set up in the loess area to be measured to collect rainfall data. Real-time rainfall refers to the hourly rainfall in the loess area, and this data is accumulated hourly.

[0052] When a real-time rainfall measurement is obtained, the current rainfall measurement is added to the previous accumulated real-time rainfall measurement to obtain the current accumulated total rainfall value. The previous accumulated rainfall duration is then incremented by 1 to obtain the current accumulated rainfall duration. For example, if the 12th measurement shows a accumulated rainfall duration of 12 hours and a total accumulated real-time rainfall of 20 mm, then the 13th measurement shows a rainfall of 0.5 mm. Therefore, the total accumulated real-time rainfall is 20.5 mm, and the accumulated rainfall duration is 12 + 1 = 13 hours.

[0053] It is understandable that when the first real-time rainfall data is collected, the cumulative rainfall duration is one hour. When the first real-time rainfall value is collected, the total cumulative real-time rainfall value is the rainfall amount itself. For example, if the first collected real-time rainfall value is A, then the total cumulative real-time rainfall value is A.

[0054] S3: When the total real-time rainfall value reaches the rainfall threshold, determine whether the rainfall duration is greater than the preset duration. If not, execute S4; if so, clear the total real-time rainfall value and rainfall duration, and re-execute S2.

[0055] S4: Calculate the rainfall intensity based on the rainfall duration and the total real-time rainfall. When the rainfall intensity is less than the rainfall intensity threshold, output the total real-time rainfall and rainfall duration as the rainfall data that triggered the shallow loess landslide. Then clear the total real-time rainfall and rainfall duration and re-execute S2.

[0056] In this embodiment, when the total real-time rainfall reaches a critical rainfall value and the rainfall duration is no greater than a preset duration, it indicates that rainfall affecting loess landslides has begun, and the process enters the rainfall calculation stage for triggering shallow loess landslides. During the rainfall calculation stage, the current total real-time rainfall is used as the initial rainfall value for this stage, i.e., the pre-landslide rainfall. The current rainfall duration is also used as the initial rainfall duration for the calculation stage. Based on this, the pre-landslide rainfall and its corresponding duration are determined, thus initially distinguishing rainfall unrelated to triggering shallow loess landslides. It is understood that rainfall data triggering shallow loess landslides refers to rainfall data that has an impact on loess landslides and may lead to landslides.

[0057] After entering the rainfall calculation stage to trigger shallow loess landslides, the current rainfall intensity is calculated based on the current real-time total rainfall and rainfall duration. It continuously checks whether the rainfall intensity is below a critical value. When the rainfall intensity is determined to be below the critical value, it indicates that the current rainfall will no longer affect the landslide, and therefore, the rainfall for triggering the shallow loess landslide ends. The current rainfall duration is taken as the rainfall duration for this triggering shallow loess landslide, and the current real-time total rainfall is taken as the total rainfall value for this triggering shallow loess landslide. The rainfall duration and total rainfall value are output as the rainfall data for this triggering shallow loess landslide. This separates rainfall that affects loess landslides from rainfall that does not, obtaining rainfall data for triggering shallow loess landslides, providing effective rainfall data for shallow loess landslide early warning, and improving the accuracy of shallow loess landslide early warning.

[0058] In this embodiment, when the total real-time rainfall reaches the rainfall threshold and the rainfall duration exceeds the preset duration, although the total real-time rainfall exceeds the rainfall threshold, the rainfall duration has exceeded the preset duration. Therefore, the current rainfall accumulation phase ends, and the rainfall calculation phase for triggering shallow loess landslides is not entered. Instead, the next round of rainfall accumulation phase is restarted. Therefore, the time of the end is taken as the current time, the current accumulated rainfall duration and total real-time rainfall are cleared, and S2 is executed again to enter the next round of rainfall accumulation to calculate the rainfall data for triggering shallow loess landslides.

[0059] Therefore, in this embodiment, by judging the total real-time rainfall and the duration of rainfall, it is determined whether to switch from the rainfall accumulation stage to the rainfall calculation stage that triggers shallow loess landslides. This determines the amount of rainfall preceding the triggering of shallow loess landslides and the start time of the rainfall. Furthermore, by judging the rainfall intensity, it is determined whether the rainfall that triggers the shallow loess landslide has ended. This avoids including rainfall data unrelated to loess landslides in the rainfall data that triggers shallow loess landslides, which would reduce the accuracy of shallow loess landslide early warnings, and improves the accuracy of shallow loess landslide early warnings.

[0060] Example 2:

[0061] Please see Figure 2 , Figure 2 This is a schematic diagram of a rainfall segmentation method for shallow loess landslides provided in an embodiment of the present invention.

[0062] S21: Obtain meteorological data for the Loess Plateau region to be tested, and determine the critical values ​​for rainfall amount and rainfall intensity based on the meteorological data.

[0063] It should be noted that the meteorological data includes the annual average rainfall and the average rainfall intensity during the annual maximum and minimum hours. The steps for determining the critical values ​​for rainfall amount and rainfall intensity based on meteorological data are as follows:

[0064] S211: Calculate the critical rainfall value based on the annual average rainfall; the formula for calculating the critical rainfall value is:

[0065] R*=0.1RN

[0066] Where R* is the critical rainfall value, and RN is the average annual rainfall in the Loess Plateau region.

[0067] It should be noted that the permeability coefficient of homogeneous loess is generally 10. -8 m / s ~ 10 -6 The speed of water infiltration (m / s) indicates that it typically takes 11.6 to 1157.4 days for rainwater to reach a depth of 1 meter in the soil. Since the thickness of shallow loess landslides is generally 0.5-2 meters, ordinary rainfall infiltration cannot directly affect landslide occurrence. However, loess soil has well-developed vertical fissures, and potential landslide bodies have steep slopes and gentler upper slopes, creating tensional fissures in the upper catchment area. This allows rainwater collected in the upper part of the landslide body to infiltrate through these vertical-tensional fissures to the sliding surface, thus triggering a landslide. Even with the presence of these vertical-tensional fissures, it still takes a considerable amount of time for rainwater to infiltrate through these fissures and reach the sliding surface. Smaller amounts of rainfall are intercepted by the loess layer in the infiltration channels and do not affect the landslide.

[0068] Therefore, based on the geological characteristics of the loess region, this embodiment calculates the critical rainfall value using 10% of the local average annual rainfall. Simultaneously, it sets a preset duration of 72 hours based on the infiltration time of rainwater in the loess soil fissures. Thus, using a duration range of 1-72 hours as one of the criteria for determining whether to enter the rainfall calculation stage that triggers shallow loess landslides makes the rainfall data for triggering shallow loess landslides more accurate, avoids excessive rainfall events being included in the rainfall data affecting loess landslides, reduces the possibility of misjudgment in shallow loess landslide early warnings, and further improves the accuracy of shallow loess landslide early warnings.

[0069] S212: Calculate the critical value of rainfall intensity based on the average of the annual maximum and minimum rainfall intensity.

[0070] The formula for calculating the critical value of rainfall intensity is:

[0071] I* = 0.02IM

[0072] Where I* is the critical value of rainfall intensity, and IM is the average annual maximum and minimum rainfall intensity in the Loess Plateau region.

[0073] It should be noted that the Loess Plateau is an arid region. While the average annual rainfall in arid regions generally does not exceed 1000 mm, the Loess Plateau typically receives around 500 mm. Furthermore, arid regions generally experience over 2000 hours of sunshine per day, while the Loess Plateau receives over 2500 hours. Therefore, the Loess Plateau is characterized by low rainfall, long sunshine hours, and high evaporation. In the Loess Plateau, the limited rainfall, coupled with long sunshine hours and high evaporation, makes the limited rainfall evaporate very easily. In particular, rainfall that does not penetrate the soil evaporates even more readily, becoming ineffective rainfall and failing to contribute to landslides. In addition, loess landslides typically have a nearly flat upper plateau, which serves as the landslide catchment area and the main rainwater collection zone for rain-induced landslides. However, because the slope of this catchment area is essentially zero, the rainwater cannot be quickly collected, leading to even faster evaporation. Finally, although vegetation exists in the Loess Plateau, it is sparse, resulting in minimal rainwater interception by vegetation and roots, leading to significant evaporation during the rainwater collection process.

[0074] Based on the characteristics of sunshine, topography, and vegetation in the Loess Plateau region, this embodiment calculates the critical value of rainfall intensity using 2% of the local multi-year average maximum hourly rainfall. This avoids the problem of excessively small rainfall being included in the rainfall process, thus prolonging the rainfall duration and causing very small rainfall to still be counted in the rainfall process affecting loess landslides, leading to misjudgments of loess landslides. This provides effective data support for the analysis of loess landslides and improves the accuracy of early warning for shallow loess landslides.

[0075] S22: Obtain and accumulate the real-time rainfall in the Loess Plateau region, obtain the total real-time rainfall value, and accumulate the collection time of the real-time rainfall to obtain the rainfall duration.

[0076] It should be noted that step S22 is the same as step S2 in Embodiment 1, and will not be repeated here.

[0077] S23: When the total real-time rainfall value reaches the rainfall threshold, determine whether the rainfall duration is greater than the preset duration. If not, execute S24; if so, clear the total real-time rainfall value and rainfall duration, and re-execute S22.

[0078] It should be noted that in steps S22-S23, the total real-time rainfall and rainfall duration are continuously accumulated every hour. After the accumulation, it is determined whether the total real-time rainfall has reached the rainfall threshold, until it is determined that the total real-time rainfall has reached the rainfall threshold, or the rainfall duration is greater than the preset duration.

[0079] When the total real-time rainfall is less than the rainfall threshold and the rainfall duration is not greater than the preset duration, it indicates that we are currently in the rainfall accumulation phase and need to continue accumulating before determining whether to perform rainfall segmentation. Therefore, continue executing S22 to obtain the next real-time rainfall, and add the next real-time rainfall to the current total real-time rainfall to obtain the next total real-time rainfall. Also, increment the current rainfall duration by 1 to obtain the next rainfall duration. Then, execute S23 to determine if the next total rainfall reaches the rainfall threshold. If it is still less than the threshold, continue executing S22 until the total real-time rainfall reaches the rainfall threshold or the rainfall duration exceeds the preset duration.

[0080] When the total real-time rainfall is less than the rainfall threshold and the rainfall duration is greater than the preset duration, it indicates that the rainfall has never exceeded the rainfall threshold within the preset duration. This means that the rainfall during this period has no impact on loess landslides and is therefore not included in the rainfall data that affects landslides. In other words, the current round of rainfall segmentation ends, and the rainfall calculation stage for triggering shallow loess landslides is not entered. Therefore, the total real-time rainfall and rainfall duration accumulated in this round are cleared, and S22 is executed again to enter the next round of rainfall segmentation.

[0081] When the total real-time rainfall reaches the rainfall threshold and the rainfall duration exceeds the preset duration, although the total real-time rainfall exceeds the rainfall threshold, the rainfall duration has exceeded the preset duration. Therefore, the current rainfall accumulation phase ends, and the rainfall calculation phase for triggering shallow loess landslides is not entered. Instead, the next rainfall accumulation phase begins. Therefore, the time of the end is taken as the current time, the current accumulated rainfall duration and total real-time rainfall are cleared, and S22 is executed again to enter the next rainfall accumulation phase to calculate the rainfall data for triggering the next shallow loess landslide.

[0082] S24: Calculate the rainfall intensity based on the rainfall duration and the total real-time rainfall. When the rainfall intensity is less than the rainfall intensity threshold, output the total real-time rainfall and rainfall duration as the rainfall data that triggered the shallow loess landslide. Then clear the total real-time rainfall and rainfall duration and re-execute S22. When the rainfall intensity is not less than the rainfall intensity threshold, continue to update the total real-time rainfall and rainfall duration according to S22, and update the rainfall intensity according to the updated total real-time rainfall and updated rainfall duration until the updated rainfall intensity is less than the rainfall intensity threshold.

[0083] It should be noted that when the total real-time rainfall reaches the critical rainfall value, and the rainfall duration is no longer than the preset duration, it indicates that rainfall affecting loess landslides has begun, and the process enters the rainfall calculation stage for triggering shallow loess landslides. In this rainfall calculation stage, the total real-time rainfall at this point is used as the initial rainfall value for the calculation stage, i.e., the pre-landslide triggering rainfall. The rainfall duration at this point is used as the initial rainfall duration for the calculation stage. Based on this, the pre-landslide triggering rainfall and its corresponding duration are determined, thus initially distinguishing rainfall unrelated to triggering shallow loess landslides. It can be understood that rainfall data triggering shallow loess landslides refers to rainfall data that has an impact on loess landslides and may lead to landslides.

[0084] After entering the rainfall calculation stage to trigger shallow loess landslides, the current rainfall intensity is calculated based on the current real-time total rainfall and rainfall duration. It is continuously judged whether the rainfall intensity is less than the rainfall intensity threshold. Based on the judgment result of the rainfall intensity, it can be divided into two cases.

[0085] (1) When the rainfall intensity is determined to be less than the critical value, it indicates that the rainfall will no longer have an impact on the landslide. Therefore, the rainfall that triggered the shallow loess landslide ends. The current rainfall duration is taken as the rainfall duration that triggered the shallow loess landslide, and the current real-time total rainfall value is taken as the total rainfall value that triggered the shallow loess landslide. The rainfall duration and total rainfall value are output as the rainfall data that triggered the shallow loess landslide. This separates the rainfall that has an impact on the loess landslide from the rainfall that has no impact on the loess landslide, and obtains the rainfall data that triggered the shallow loess landslide. This provides effective rainfall data for the early warning of shallow loess landslides and improves the accuracy of the early warning of shallow loess landslides.

[0086] (2) When the rainfall intensity is not less than the critical value of rainfall intensity, it means that the current rainfall intensity will continue to cause landslides in the loess area. That is, the rainfall that triggered the shallow loess landslide has not stopped and is still continuing. Therefore, based on the current accumulated total real-time rainfall, the next accumulated real-time rainfall is accumulated to obtain the next accumulated total real-time rainfall in the rainfall calculation stage. Then, 1 is added to the current accumulated rainfall duration to obtain the next accumulated rainfall duration. After that, the next rainfall intensity is calculated based on the next total real-time rainfall and rainfall duration. By judging whether the next rainfall intensity is less than the critical value of rainfall intensity, it is determined whether the rainfall that triggered the shallow loess landslide has ended.

[0087] For example: when the total real-time rainfall accumulated during the rainfall accumulation phase is greater than the rainfall threshold R*, and the corresponding rainfall duration does not exceed 72 hours, the rainfall calculation phase begins. The total real-time rainfall accumulated during the rainfall accumulation phase is used as the initial value R0 (i.e., previous rainfall) for the rainfall calculation phase; and the rainfall duration accumulated during the rainfall accumulation phase is used as the initial value D0 for the rainfall duration of the rainfall calculation phase.

[0088] During the rainfall calculation phase, the initial rainfall value R0 is divided by the initial rainfall duration D0 to obtain the rainfall intensity I0. When the rainfall intensity I0 is less than the critical rainfall intensity value, it indicates that the rainfall that triggered the shallow loess landslide has ended. The total rainfall value that triggered the shallow loess landslide is then R0, and the total rainfall duration is D0. Afterward, the current cumulative rainfall and rainfall duration are reset to zero to obtain the real-time total rainfall value and rainfall duration, and the next round of rainfall accumulation and calculation phases begins, thus completing the next round of rainfall segmentation.

[0089] When the rainfall intensity I0 is greater than or equal to the critical rainfall intensity value, the rainfall that triggered the shallow loess landslide is still continuing. Therefore, the real-time rainfall R1 collected in the next hour is added to R0, resulting in a total real-time rainfall value R of R0 + R1. Then, 1 is added to D0, resulting in the rainfall duration for the next hour of D = D0 + 1. Next, the rainfall intensity I1 is calculated as I1 = R / D = (R0 + R1) / (D0 + 1). Finally, it is determined whether the rainfall intensity I1 is less than the critical rainfall intensity. If so, it indicates that the rainfall that triggered the shallow loess landslide has ended, and the total rainfall amount that triggered the landslide is R0 + R1, with a rainfall duration of (D0 + 1). If not, it means that the rainfall that triggered the shallow loess landslide is still continuing. Then, based on R0+R1, the real-time rainfall R2 collected in the next hour is added to obtain the total real-time rainfall value R as R0+R1+R2. Based on D0+1, one hour is added to obtain the rainfall duration D=D0+1+1=D0+2. The current rainfall intensity I2=R / D=(R0+R1+R2) / (D0+2) is calculated. It is determined whether the current rainfall intensity I2 is less than the rainfall intensity threshold. If yes, it means that the rainfall that triggered the shallow loess landslide has ended. If not, the rainfall duration and the total real-time rainfall value are accumulated until it is determined that the rainfall intensity is less than the rainfall intensity threshold, and the rainfall calculation for this shallow loess landslide is ended. The total rainfall value and rainfall duration for this shallow loess landslide are obtained. The total rainfall value R = R0 + R1 + R2 + ... + Rn is calculated from the corresponding rainfall duration D = D0 + n, and the total rainfall intensity I is calculated using I = R / D. n represents the nth hour. Rn represents the real-time rainfall collected in the nth hour during the rainfall calculation phase.

[0090] In this embodiment, the determination of whether to enter the rainfall calculation stage for triggering shallow loess landslides is based on the real-time total rainfall value and rainfall duration. This determines the initial rainfall value and start time for triggering shallow loess landslides. Furthermore, the determination of whether the rainfall for triggering shallow loess landslides has ended is based on the rainfall intensity. This avoids including rainfall data unrelated to loess landslides in the rainfall data for triggering shallow loess landslides, which would reduce the accuracy of shallow loess landslide early warnings. This distinguishes between rainfall that has an impact on loess landslides and rainfall that has no impact, resulting in effective rainfall data for triggering shallow loess landslides and improving the accuracy of shallow loess landslide early warnings.

[0091] By employing the rainfall segmentation method for shallow loess landslides provided in this embodiment, the rainfall data that triggers shallow loess landslides is calculated without being limited by time, but only related to the rainfall process. There is no need to artificially control the attenuation coefficient of the rainfall in the early stage that triggers shallow loess landslides. Therefore, the rainfall data that affects landslides is more consistent with the actual situation and can effectively separate the rainfall that triggers shallow loess landslides from the rainfall that is unrelated to landslides. This can better reflect the infiltration effect of rainfall on loess tensile cracks, improve the reference value of the initial rainfall amount in the rainfall calculation stage for triggering shallow loess landslides, and thus improve the accuracy of landslide early warning.

[0092] In another specific embodiment, the real-time rainfall is the rainfall on the loess plateau.

[0093] In another specific embodiment, real-time rainfall is collected by sensors set up on the plateau.

[0094] It should be noted that in this embodiment, sensors are deployed on the loess plateau in the area to be tested to collect real-time rainfall data.

[0095] This embodiment deploys sensors on the loess plateau to collect real-time rainfall, ensuring that the elevation of the rainfall monitoring is the same as the elevation of the landslide catchment area. This makes the real-time rainfall collected by the sensors more accurate and more consistent with the rainfall characteristics of the loess region, greatly improving the data's reference value and accuracy, and further enhancing the accuracy of landslide early warning.

[0096] In one specific embodiment, the number of sensors is multiple.

[0097] It should be noted that in this embodiment, multiple sensors for collecting real-time rainfall are deployed on the loess plateau in the area to be measured, thereby improving the accuracy of data acquisition. After acquiring the real-time rainfall data collected by multiple sensors, the average value of the real-time rainfall data is calculated. This average value is then used as the real-time rainfall data for the loess plateau in the area to be measured, further improving the accuracy of real-time rainfall data and thus enhancing the accuracy of landslide early warning.

[0098] In another specific embodiment, when deploying sensors, the loess plateau can be divided into equal grid areas according to its area, and a sensor can be set at the center of each grid area to further improve the accuracy of the collected real-time rainfall data.

[0099] The following will further illustrate the rainfall segmentation method for shallow loess landslides provided by this invention with specific application examples.

[0100] From July 7th to 13th, 2013, continuous heavy rainfall in Yan'an City triggered a large-scale landslide in Baota District, causing damage to multiple cave dwellings and resulting in numerous casualties. The landslides occurred most frequently at 9:00 AM on July 13th, 2013. The local annual average rainfall RN = 572.3 mm, and the average maximum hourly rainfall intensity over many years is IM = 29.5 mm / h. Therefore, R... * =57.23mm, I * =0.59 mm / h. Table 1 shows the hourly rainfall values ​​from the start of rainfall to the occurrence of the landslide from 22:00 on July 7, 2013 to 9:00 on July 13, 2013, as well as the rainfall duration and total rainfall value after rainfall segmentation.

[0101] Table 1. Rainfall duration and total rainfall value after rainfall segmentation.

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[0103]

[0104]

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[0108]

[0109] As shown in Table 1, rainfall began at 22:00 on July 7, 2013, and reached a total of 71.2 mm by 23:00 on July 8, exceeding R. * =57.23mm, the rainfall period at this time was 26 hours, falling within the 1-72 hour range. Therefore, this rainfall period can be used as the initial rainfall in the calculation stage for triggering shallow loess landslides, D0=26h, R0=71.2mm, and the rainfall intensity at this time I=2.74mm / h. During the subsequent rainfall process, until 9:00 AM on July 13, 2013, when the landslide occurred, the rainfall intensity was greater than I. * =0.59 mm / h, so the rainfall process did not stop. The rainfall at the time of the final landslide was R = 247.9 mm, the rainfall duration was D = 132 h, and the rainfall intensity was I = 1.88 mm / h. It can be seen that the rainfall during the period from 22:00 on July 7th to 9:00 on July 13th should be included in the rainfall data that triggered the landslide.

[0110] In this application example, the rainfall reached 71.2 mm in 26 hours, which falls under the category of rainfall exceeding 57.23 mm within 1-72 hours. This triggers the rainfall calculation stage for shallow loess landslides. 26 hours is used as the initial value for the rainfall duration that triggers shallow loess landslides, and 71.2 mm is used as the initial rainfall value that triggers shallow loess landslides.

[0111] Understandably, according to my country's general rainfall classification standards, 10-24.9 mm of rainfall in 24 hours is considered moderate rain, 25-49.9 mm is heavy rain, and 50-99.9 mm is torrential rain. In this application example, the 26-hour rainfall reached 71.2 mm, which is considered torrential rain. During the subsequent rainfall, another 176.7 mm of rain fell (an average 24-hour rainfall of 40.0 mm, classified as heavy rain), bringing the total rainfall to 247.9 mm, reaching 43.3% of the local annual average rainfall. This subsequent rainfall occurred within 132 hours. Therefore, this one-day torrential rain, combined with 4.4 days of continuous heavy rain, triggered a shallow landslide in the loess.

[0112] Given the unique geographical location and topography of loess regions, moderate to heavy rains are infrequent, and heavy rains are extremely rare. This invention, based on the characteristics of loess regions, sets a minimum rainfall of 57.23 mm (equivalent to a minimum average 24-hour rainfall of 19.1 mm) within 1-72 hours as the initial rainfall point for triggering shallow loess landslides. This means that at least moderate to heavy rain is required to trigger shallow loess landslides, which better aligns with the characteristics of loess regions. This effectively separates rainfall that can trigger shallow loess landslides from rainfall unrelated to them, thereby accurately calculating the initial rainfall amount that triggers shallow loess landslides and improving the accuracy of landslide early warning.

[0113] In summary, the rainfall segmentation method for shallow loess landslides provided by this invention has the following beneficial effects:

[0114] I. In this embodiment of the invention, meteorological data of the loess region within a preset range is obtained, and the critical values ​​of rainfall amount and rainfall intensity are determined based on the meteorological data. Then, the real-time rainfall of the loess region is obtained, and the rainfall duration and the total real-time rainfall are accumulated. It is determined whether the total real-time rainfall reaches or exceeds the rainfall critical value within 1-72 hours. If so, it is counted as the initial rainfall value for triggering shallow loess landslides. Based on the calculated rainfall intensity, the corresponding rainfall data for triggering shallow loess landslides is accumulated to obtain the rainfall data for triggering shallow loess landslides.

[0115] By employing the rainfall segmentation method for shallow loess landslides provided in this embodiment of the invention, the rainfall data that triggers shallow loess landslides is calculated without being limited by time and is only related to the rainfall process. There is no need to artificially control the attenuation coefficient of the initial rainfall that triggers shallow loess landslides. Therefore, the calculated rainfall data that affects landslides is more consistent with the actual situation in loess areas. It can effectively separate the rainfall that triggers shallow loess landslides from rainfall unrelated to landslides, thus reflecting the infiltration effect of rainfall on loess tensile cracks. This improves the reference value of the initial rainfall amount in the rainfall calculation stage for triggering shallow loess landslides, thereby improving the accuracy of landslide early warning and reducing significant losses and casualties caused by landslides.

[0116] II. In this embodiment of the invention, multiple sensors are arranged on the loess plateau in the area to be tested, so that the elevation of the rainfall monitoring is consistent with the elevation of the landslide catchment area. By adopting this specific arrangement, the real-time monitoring of rainfall through the sensors is more accurate, which greatly improves the reference value of the rainfall data and helps to improve the accuracy of landslide early warning.

[0117] Third, in this embodiment of the invention, the determination of whether to recalculate the pre-landfall precipitation that triggers shallow loess landslides is made by calculating the rainfall intensity I for each time period. When the rainfall intensity I is less than the rainfall intensity threshold I*, the total real-time rainfall value is reset to zero, and the pre-landfall precipitation calculation starts again. Therefore, the calculated total real-time rainfall value that triggers shallow loess landslides is obtained through rainfall process and landslide probability analysis, and has a wider range of applications.

[0118] IV. Compared with existing technologies, the rainfall segmentation method of this invention is not based on the scenario of numerous collapses and landslides occurring in areas affected by strong earthquakes. Therefore, it is applicable to loess areas with little or no earthquake impact, as well as to loess areas within a long period after an earthquake. It has broad applicability for calculating the pre-landslide rainfall. Furthermore, this embodiment deploys multiple sensors on the loess plateau based on the monitored landslide point. The sensors monitor rainfall in real time and obtain hourly rainfall data for 1-72 hours. By comparing the rainfall threshold, the method determines the pre-landslide rainfall that triggers shallow loess landslides, greatly reducing misjudgments of landslides due to insufficient rainfall and significantly improving the accuracy of early warning.

[0119] V. In this embodiment of the invention, based on the special geology of the loess region, a preset duration of 72 hours is determined, and a rainfall threshold value is calculated using 10% of the local annual average rainfall. This threshold value is used as the criterion for determining whether to include the total real-time rainfall in the rainfall data that triggers shallow loess landslides. The calculated rainfall data that triggers shallow loess landslides includes the impact of short-term heavy rainfall, as well as moderate but longer-duration rainfall processes. It is not limited to rainfall processes of only 72 hours, thus avoiding interference from invalid rainfall durations on landslide early warning, greatly improving the accuracy of early warning, and reducing the occurrence of false early warnings.

[0120] VI. The segmentation method of this invention divides the rainfall that triggers shallow loess landslides into two processes: early rainfall (rainfall accumulation stage) + later rainfall (rainfall calculation stage). The early rainfall must be at least 10% of the local annual average rainfall. In the later rainfall, a critical rainfall intensity value is used as the criterion for determining the end point of the later rainfall. This ensures that in the rainfall data that triggers shallow loess landslides, the early rainfall is considered a relatively large rainfall event, and the subsequent rainfall must also maintain a relatively large amount to be classified as landslide-inducing rainfall. This avoids landslide warning misjudgments caused by insufficient rainfall, reduces the occurrence of landslide warning misjudgments, and greatly improves the accuracy of rainfall-based landslide warnings.

[0121] VII. In this embodiment of the invention, a critical rainfall value is calculated based on the annual average rainfall, and this critical rainfall value is used as the criterion for determining the starting point of rainfall that triggers shallow loess landslides. This eliminates interference from rainfall evaporation through the upper catchment area and absorption by the loess soil. As a result, it can analyze the situation where rainfall continues to infiltrate deeper into the soil along the tensile fracture channels, which may continue to affect the landslide, thus making the early warning more accurate.

[0122] 8. In this embodiment of the invention, a critical value for rainfall intensity is calculated based on the average of the annual maximum and minimum rainfall intensity. This critical value is used as the criterion for determining the end point of rainfall that triggers shallow loess landslides. Only rainfall with an intensity greater than or equal to the critical value is included in the rainfall data for triggering shallow loess landslides. This method eliminates the possibility that, under low rainfall intensity, rainwater in the catchment area above the landslide may evaporate or be absorbed by the loess soil and not continue to infiltrate into the tensile cracks to affect the landslide. This improves the reliability of the data for triggering shallow loess landslides and reduces the misjudgment rate of landslide early warning.

[0123] Example 4:

[0124] Please see Figure 3 , Figure 3 This invention illustrates a rainfall segmentation device for shallow loess landslides, as provided in an embodiment of the present invention. The device includes:

[0125] The acquisition module 301 is used to acquire meteorological data of the Loess Plateau region to be measured, and to determine the critical values ​​for rainfall and rainfall intensity based on the meteorological data.

[0126] The cumulative module 302 is used to acquire and accumulate real-time rainfall in the Loess Plateau region, obtain the total real-time rainfall value, accumulate the collection time of real-time rainfall, and obtain the rainfall duration.

[0127] The first judgment module 303 is used to determine whether the rainfall duration is greater than a preset duration when the total real-time rainfall value reaches the rainfall threshold. If not, the second judgment module is triggered; if so, the total real-time rainfall value and rainfall duration are cleared, and the accumulation module is triggered again.

[0128] The second judgment module 304 is used to calculate the rainfall intensity based on the rainfall duration and the total real-time rainfall. When the rainfall intensity is less than the rainfall intensity threshold, it outputs the total real-time rainfall and rainfall duration as the rainfall data for triggering the shallow loess landslide. Then, it clears the rainfall duration and the total real-time rainfall and re-triggers the accumulation module.

[0129] In a specific embodiment, the second judgment module 304 is further configured to continue updating the real-time total rainfall and rainfall duration according to S2 when the rainfall intensity is not less than the rainfall intensity threshold, and update the rainfall intensity according to the updated real-time total rainfall and updated rainfall duration, until the updated rainfall intensity is less than the rainfall intensity threshold.

[0130] The present invention also provides an electronic device, the device including a processor and a memory:

[0131] The memory is used to store program code and transfer the program code to the processor;

[0132] The processor is used to execute the method as described in any of the above embodiments according to instructions in the program code.

[0133] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0134] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, or indirect coupling or communication connection between apparatuses or units, and may be electrical, mechanical, or other forms.

[0135] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0136] Furthermore, in the various embodiments of the present invention, the functional units can be integrated into one processing unit, or each functional unit can be a separate physical entity, or two or more functional units can be integrated into one processing unit. The integrated unit described above can be implemented in hardware or as a software functional unit.

[0137] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0138] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A rainfall segmentation method for shallow loess landslides, characterized in that, The method includes: S1: Obtain meteorological data for the Loess Plateau region to be tested, and determine the critical values ​​for rainfall amount and rainfall intensity based on the meteorological data; The meteorological data includes the annual average rainfall and the average annual maximum and minimum rainfall intensity. The steps of determining the critical values ​​for rainfall amount and rainfall intensity based on the meteorological data include: Calculate the critical rainfall value based on the annual average rainfall; Calculate the critical value of rainfall intensity based on the average of the annual maximum and minimum rainfall intensity; The formula for calculating the critical value of rainfall is: R*=0.1RN; Where R* is the critical value for rainfall, and RN is the average annual rainfall in the Loess region; The formula for calculating the critical value of rainfall intensity is: I*=0.02IM; Where I* is the critical value of rainfall intensity, and IM is the average annual maximum and minimum rainfall intensity in the Loess region; S2: Obtain and accumulate the real-time rainfall in the Loess region to obtain the total real-time rainfall value, and accumulate the collection time of the real-time rainfall to obtain the rainfall duration; S3: When the total real-time rainfall reaches the rainfall threshold, determine whether the rainfall duration is greater than the preset duration. If not, execute S4; if so, clear the total real-time rainfall and the rainfall duration, and re-execute S2; wherein, the preset duration is 72 hours. S4: Calculate the rainfall intensity based on the rainfall duration and the total real-time rainfall. When the rainfall intensity is less than the rainfall intensity threshold, output the total real-time rainfall and the rainfall duration as the rainfall data that triggered the shallow loess landslide. Then clear the total real-time rainfall and the rainfall duration, and re-execute S2. When the rainfall intensity is not less than the rainfall intensity threshold, continue to update the total real-time rainfall and the rainfall duration according to S2, and update the rainfall intensity according to the updated total real-time rainfall and the updated rainfall duration, until the updated rainfall intensity is less than the rainfall intensity threshold.

2. The method according to claim 1, characterized in that, The real-time rainfall refers to the rainfall on the loess plateau in the Loess region.

3. The method according to claim 2, characterized in that, The real-time rainfall data was collected by sensors installed on the plateau.

4. The method according to claim 3, characterized in that, The number of sensors is multiple.

5. A rainfall segmentation device for shallow loess landslides, characterized in that, The device includes: The acquisition module is used to acquire meteorological data of the Loess Plateau region to be measured, and to determine the critical values ​​for rainfall amount and rainfall intensity based on the meteorological data. The accumulation module is used to acquire and accumulate the real-time rainfall in the Loess region to obtain the total real-time rainfall value, and to accumulate the acquisition time of the real-time rainfall to obtain the rainfall duration; The first judgment module is used to determine whether the rainfall duration is greater than a preset duration when the total real-time rainfall value reaches the rainfall threshold. If not, the second judgment module is triggered; if so, the total real-time rainfall value and the rainfall duration are cleared, and the accumulation module is re-triggered. The preset duration is 72 hours. The second judgment module is used to calculate the rainfall intensity based on the rainfall duration and the total real-time rainfall. When the rainfall intensity is less than the rainfall intensity threshold, the module outputs the total real-time rainfall and the rainfall duration as the rainfall data that triggered the shallow loess landslide. Then, the module clears the rainfall duration and the total real-time rainfall and re-triggers the accumulation module. The meteorological data includes the annual average rainfall and the average annual maximum and minimum rainfall intensity. The acquisition module is specifically used to calculate a rainfall threshold based on the annual average rainfall; and to calculate a rainfall intensity threshold based on the average rainfall intensity during the annual maximum and minimum hours. The formula for calculating the critical value of rainfall is: R*=0.1RN; Where R* is the critical value for rainfall, and RN is the average annual rainfall in the Loess region; The formula for calculating the critical value of rainfall intensity is: I*=0.02IM; Where I* is the critical value of rainfall intensity, and IM is the average annual maximum and minimum rainfall intensity in the Loess region; The second judgment module is further configured to, when the rainfall intensity is not less than the rainfall intensity threshold, continue to update the total real-time rainfall and the rainfall duration according to S2, and update the rainfall intensity according to the updated total real-time rainfall and the updated rainfall duration, until the updated rainfall intensity is less than the rainfall intensity threshold.

6. An electronic device, characterized in that, The device includes a processor and a memory: The memory is used to store program code and transmit the program code to the processor; The processor is configured to execute the method as described in any one of claims 1-4 according to instructions in the program code.

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