Meteorological disaster reservoir level risk early warning method and device and storage medium

Abstract

The invention discloses a meteorological disaster reservoir water level risk early warning method and device and a storage medium. The risk early warning method comprises the steps of determining at least one reservoir basin rainfall station in a basin where a target reservoir is located; determining the basin actual rainfall of the target reservoir according to the actually measured rainfall of the reservoir basin rainfall station, and determining the unit line lag time of the target reservoir according to the basin actual rainfall; determining a process net rain and a unit line of the target reservoir; and estimating the reservoir level of the target reservoir according to the process net rain and the unit line, and estimating the reservoir risk according to the reservoir characteristic level. According to the method, the grid rainfall forecasting method and the water level forecasting method are combined, numerical calculation of reservoir water level risk early warning influence forecasting is achieved, compared with an existing method, the scientificity of risk early warning is improved, compared with a hydrological model method, calculation resources and calculation time are saved, and urban reservoir flood control can be better guided.

Description

Technical Field

[0001] The present invention relates to the technical field of meteorological disaster risk warning, and in particular to a meteorological disaster reservoir water level risk warning method, device and storage medium. Background Art

[0002] Shenzhen is located on the coast of southern China and has a subtropical monsoon climate. The average annual precipitation is 1932.9 mm, and 86% of the annual rainfall occurs during the flood season (April to September). As climate change becomes increasingly obvious, extreme precipitation events are frequent. In 2023, the maximum 30-minute rainfall of the local heavy rain on May 23 was 108.2 mm, and the maximum 1-hour rainfall was 142.2 mm, both breaking Shenzhen's historical extremes. The "9.7" extreme heavy rainstorm was extremely strong, lasted for a long time, and had a large range of heavy rainfall. The maximum 24-hour sliding rainfall in Shenzhen was 560 mm, and the 7 sliding rainfalls of 2 hours, 3 hours, 6 hours, 12 hours, 24 hours, 48 ​​hours and 72 hours broke the historical extremes since meteorological records were kept in 1952. In 2023, nine sliding rainfalls throughout the year broke the city's historical extremes.

[0003] Risk warning of urban reservoirs is an important task for urban safety. Balancing the two functions of reservoir water supply and flood control is the focus of reservoir dispatching during the flood season. During the "9.7" extreme rainstorm, 33 small and medium-sized reservoirs out of the 177 reservoirs in Shenzhen exceeded the flood limit water level and discharged (overflowed) floodwaters. Affected by the continuous heavy rainfall, the water level of Shenzhen Reservoir reached a maximum of 29.7m, exceeding the design flood level by 0.29m, the highest water level in the history of Shenzhen Reservoir. In the context of climate change, sudden extreme precipitation seriously threatens the operational safety of urban reservoirs.

[0004] At present, the meteorological industry still lacks risk warning technology for reservoirs. Meteorological warning signals have realized the transition from meteorological monitoring data to meteorological disaster warnings, which is a big step forward in the development of meteorological factors into risk warnings. They provide a reference for reservoir flood season scheduling and are of great significance for the prevention and emergency response of meteorological disasters. However, there are still some deficiencies in the following aspects: 1. Meteorological warning signals emphasize the intensity of severe weather, lack an assessment of their impact on production safety, and their guidance for emergency responses by relevant departments (such as reservoir flood control and dispatching) needs to be enhanced.

[0005] 2. The current meteorological warning signals have the phenomenon of one signal commanding all. The emergency plans and corresponding management measures formed based on meteorological warning signals cannot achieve emergency responses by industry and region, which may easily lead to waste of social resources due to excessive response.

[0006] 3. There is confusion, disconnection and incoordination among meteorological warning signals, meteorological disaster warnings and meteorological emergency responses, which can easily lead to incoordination in social responses and make it difficult to achieve refinement and accuracy of meteorological warnings.

[0007] For the hydrological forecasting of urban reservoirs, both forecasting accuracy and timeliness need to be considered. Currently, there are mainly two methods in runoff yield and concentration calculation: 1. The SCS runoff yield model and the geomorphological instantaneous unit hydrograph concentration model, which is applicable to the flood forecasting of small reservoirs in data-deficient areas; 2. The semi-distributed hydrological model FLOWS-Tank, which is used to analyze the sub-processes of rainfall runoff and river flood routing in the upstream urban basin. The FLOWS-Tank model combines mechanism-driven and data-driven methods and is applicable to the simulation of urban flood processes; the advantage of this model is its low sensitivity to parameters and its ability to better simulate urban flood processes, especially in urban areas, but its disadvantage may lie in the need for high professional knowledge and experience in parameter adjustment and model calibration in complex urban environments.

[0008] In 1991, the Water Conservancy and Hydrology System of Guangdong Province produced and released the "Guangdong Province Rainstorm Runoff Calculation Manual" and the "Guangdong Province Rainstorm Runoff Calculation Charts". The design storm amounts at various time points of the central point of the project catchment area are calculated from the isohyet maps of the statistical parameters of the storm amounts at various time points, and are converted into the corresponding surface design storm amounts according to the fixed-point and fixed-area relationship of the rainstorm. The time-course distribution of the design storm (i.e., the design gross rain process) is obtained by controlling the long-term and short-term rainfall of the same frequency according to the design rain pattern; the design net rain process is obtained through runoff yield calculation; the design flood is obtained through concentration calculation (using the comprehensive unit hydrograph method or the rational formula method of Guangdong Province), and then the reservoir concentration is estimated. It has been more than 30 years since the release of this method. With the development of cities, the underlying surface conditions have changed greatly, and the precipitation concentration speed has also changed. This method is no longer applicable to the current urban reservoir concentration calculation.

[0009] Taking the Shenzhen River Bay Basin as the object, the Shenzhen Water Affairs System, with the urban flood model as the core, based on the smart city big data platform, couples multi-source historical, real-time, and forecast data, and designs and implements a flood warning and dispatching system, which also includes a reservoir water level prediction module. This system uses the method of coupling a two-dimensional plane model with a one-dimensional pipe network model for calculation, with relatively high accuracy, but the calculation speed is slow, and the calculation results cannot be released in time during extreme rainstorm processes. Summary of the Invention

[0010] The purpose of the present invention is to provide a method, device, and storage medium for warning the risk of reservoir water level in meteorological disasters to overcome the problem of slow calculation speed existing in the prior art.

[0011] To achieve this purpose, the present invention adopts the following technical solutions: A method for warning the risk of reservoir water level in meteorological disasters includes: Determining at least one reservoir basin rain gauge within the basin where the target reservoir is located; Based on the measured rainfall of the rain gauges in the reservoir basin, determine the actual rainfall in the basin of the target reservoir, and determine the unit hydrograph lag time of the target reservoir according to the actual rainfall in the basin; Determine the process net rainfall and unit hydrograph of the target reservoir; Estimate the reservoir water level of the target reservoir based on the process net rainfall and unit hydrograph.

[0012] Optionally, the determination of the actual rainfall in the basin of the target reservoir based on the measured rainfall of the rain gauges in the reservoir basin includes: Select multiple rain gauges in the reservoir basin; Take the average value of the measured rainfall of multiple rain gauges in the reservoir basin as the actual rainfall in the basin of the target reservoir.

[0013] Optionally, the unit hydrograph lag time of the target reservoir is determined by comparing the moving average of the actual rainfall in the basin with the rising and falling curve of the reservoir water level.

[0014] Optionally, the calculation of the reservoir water level based on the process net rainfall and unit hydrograph includes: Multiply the net rainfall of each time period by the unit hydrograph to obtain the runoff curve generated by the net rainfall of the current time period; Add up the runoff curves generated by the net rainfall of all time periods to obtain the runoff curve of the entire rainfall process.

[0015] Optionally, the calculation of the reservoir water level based on the process net rainfall and unit hydrograph further includes: adding the current reservoir storage capacity, adding all the inflow water volumes at the corresponding time, and then calculating the reservoir water level through the reservoir water level - storage capacity curve.

[0016] Optionally, when calculating the reservoir water level at any time, the contribution of the confluent water volume within the historical preset duration is taken into consideration.

[0017] Optionally, corresponding risk thresholds are set according to the characteristic water levels of each reservoir, including the normal storage level, flood control limit level, flood control high level, design flood level, and check flood level.

[0018] A meteorological disaster reservoir water level risk warning device includes a memory and a processor; The memory is used for storing instructions; The processor is used for executing the instructions in the memory to implement the reservoir water level prediction method described in any one of the above.

[0019] A computer - readable storage medium includes instructions, which when running on a computer, cause the computer to execute the reservoir water level prediction method described in any one of the above.

[0020] Compared with the prior art, the beneficial effects of the present invention are as follows: In the embodiment of the present invention, by combining the grid rainfall forecast and the water level forecast method, the numerical calculation of the reservoir water level risk early warning impact forecast is realized. Compared with the existing method, the scientific nature of the risk early warning is improved, and the calculation resources and calculation time are saved compared with the hydrological model method, which can better guide the flood control of urban reservoirs. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0022] Figure 1 It is a view of the circulation path of the Shawan River flowing into the Shenzhen Reservoir provided by the embodiment of the present invention.

[0023] Figure 2 It is a five-minute rainfall curve graph provided by the embodiment of the present invention.

[0024] Figure 3 It is a comparison graph of the rainfall moving average and the reservoir water level rise and fall curve provided by the embodiment of the present invention.

[0025] Figure 4 It is a process net rainfall graph provided by the embodiment of the present invention.

[0026] Figure 5 It is a dimensionless unit hydrograph provided by the embodiment of the present invention.

[0027] Figure 6 It is a water level change curve and detection data graph of the Shenzhen Reservoir provided by the embodiment of the present invention.

[0028] Figure 7 It is a comparison graph of the water level change curve and the water level - storage capacity curve of the Shenzhen Reservoir provided by the embodiment of the present invention.

[0029] Figure 8 It is a calculation error curve graph of the reservoir water level of the Shenzhen Reservoir provided by the embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0030] In order to make the object, features, and advantages of the present invention more obvious and understandable, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the following described embodiments are only a part of the embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0031] Currently, there is no risk warning impact forecasting algorithm specifically for reservoirs, and only rainfall warning signals and areal rainfall forecasts are used to guide reservoir operation. To overcome the deficiencies of the existing technology, the embodiments of the present invention achieve numerical calculation of the risk warning impact forecasting of reservoir water levels by combining grid rainfall forecasting and water level forecasting methods. Compared with the existing methods, the scientific nature of risk warning is improved, and calculation resources and calculation time are saved compared to hydrological model methods, which can better guide the flood control of urban reservoirs.

[0032] 1. Select rain gauges in the reservoir basin Take the Shenzhen Reservoir during the "9.7" extreme heavy rainstorm on September 7, 2023 as an example.

[0033] As Figure 1 shown, the Shenzhen Reservoir is located on the main stream of the Shawan River, with its geographical location being 114°09′ east longitude and 22°33′ north latitude, and the basin area is approximately 56 km 2 . The Shawan River basin is located within the Nanwan and Pinghu sub-districts of Longgang District, Shenzhen City, and belongs to a first-class tributary of the Shenzhen River in the Pearl River Delta water system. It originates from the Niuwei Ridge of Wutong Mountain, 214.5 meters above sea level, upstream of the Huangniuhu Reservoir, and is initially called the Lilang River. After converging with the Baini Keng River at Pudi Xia, it is then called the Shawan River. The general direction of the river channel is roughly north-south, flowing through the upper and lower Lilang communities, Danzhutou, Nanling community, Jixia, Shatangbu, Zhangshubu, Shawan Village along the way, and injecting into the Shenzhen Reservoir after converging with tributaries such as the Jianzhu River, Zhengkeng Water, Wutongshan River, and Xianhu Water. Therefore, the rainfall of automatic stations such as Danping G3518, Nanwan G3558, Dawang G1144, Liuyue G3758, and Henggang G3560 is selected as the actual rainfall in the Shenzhen Reservoir basin.

[0034] 2. Determine the unit hydrograph lag time Take the average value of the measured rainfall of the above 5 automatic station rain gauges as the actual rainfall in the basin. The five-minute rainfall curve from 18:00 on September 7 to 3:00 on September 8 is as Figure 2 shown.

[0035] After sliding averaging the rainfall and comparing it with the rising and falling curve of the reservoir water level, it is found that the rainfall peak in the Shenzhen Reservoir basin is at 21:10, and the peak change in the reservoir water level is at 22:10, as Figure 3 shown. Therefore, the unit hydrograph lag time is approximately 1 hour.

[0036] 3. Determine the net rainfall process According to the runoff generation parameters table for the Guangdong Province sub-regions shown in Appendix 1 of the "Guangdong Province Rainstorm Runoff Calculation Manual", Shenzhen belongs to the coastal area of eastern Guangdong / Pearl River Delta, and the basin area is less than 100 square kilometers. Therefore, the rainfall loss rate is 4.5 mm / h, which is converted to 0.375 mm / 5 minutes for every five minutes.

[0037]

[0038] 4. Calculate the unit hydrograph As shown in Table 2 below, Shenzhen belongs to the coastal area of eastern Guangdong / Pearl River Delta, and the basin area is less than 500 square kilometers. The dimensionless unit hydrograph of No. III is selected for calculation.

[0039] Table 2 Corresponding Table of Sub-regions in the "Guangdong Province Rainstorm Runoff Calculation Charts" and Rainstorm, Runoff Generation, and Confluence Sub-regions

[0040] The dimensionless unit hydrograph is as Figure 5 shown.

[0041] Select U m = 0.750, K = V u1 / t p = 1.547.

[0042] The rising duration of the unit hydrograph is: t p = V u1 / K = (m 1 + 0.5△t) / 1.547 = (1 + 0.5 / 12) / 1.547 = 0.673 hours.

[0043] The number of time intervals before the peak of the unit hydrograph is: 0.673 * 12 (round to the nearest integer) + 1 = 9.

[0044] The number of time intervals before the peak of the unit hydrograph is: 5 * 0.673 * 12 (round to the nearest integer) + 1 = 41.

[0045] Starting from the peak U m = 0.750, take the ti values at intervals of △t = 1 / 12 hour before and after, and list them in the second column of Table 3; calculate x i = t i / t p and list it in the third column of Table 3; through interpolation by querying Table 4, calculate the x i corresponding to u i value and list it in the fourth column of Table 3; through q i = u i *(W / t p),W = F / 3.6, where F is the catchment area, which is 56 for Shenzhen Reservoir, and q is calculated i , listed in the 5th column of Table 3, which is the unit hydrograph.

[0046] Table 3

[0047]

[0048]

[0049] Table 4

[0050]

[0051] 4. Calculate the design flood hydrograph and reservoir water level Multiply the net rainfall in each time period by the unit hydrograph q i to obtain the runoff hydrograph generated by the net rainfall in this time period. Add up the runoff hydrographs generated by the net rainfall in all time periods to obtain the runoff hydrograph of the entire rainfall process.

[0052] After obtaining the inflow water volume, based on the current reservoir storage capacity, add the total inflow water volume at the corresponding time, and then calculate the reservoir water level through the reservoir water level - storage capacity curve.

[0053] Example: For example, at 7:00 on September 7, it is necessary to predict the reservoir water level at 8:00 on September 7.

[0054] First, calculate the inflow water volume generated by the forecast rainfall from 7 to 8 o'clock. The total inflow water volume is 1.297 million m 3 .

[0055] 5. Calculate the reservoir water level considering the previous precipitation Through the unit hydrograph t i A total of 51 are known, and the total recession duration of any precipitation is 51 / 12 = 4.25 hours.

[0056] Therefore, when calculating the reservoir water level at any time, the precipitation within the previous 4.25 hours needs to be considered.

[0057] Taking the above situation as an example: For example, at 7:00 on September 7, it is necessary to predict the reservoir water level at 8:00 on September 7. It is necessary not only to include the forecast rainfall from 7 to 8 o'clock in the calculation, but also to consider the contribution of the runoff volume of the rainfall from 6 to 7 o'clock at 7 to 8 o'clock. The highlighted rows in Appendix 3 are the runoff volume of the rainfall from 6 to 7 o'clock at 7 to 8 o'clock, which is 0.575 million m 3 .

[0058] It is known from querying the data that: For exampleFigure 6 , the water level of Shenzhen Reservoir was 27.108m on September 7, 2023.

[0059] According to the information obtained from the query: the water level of Shenzhen Reservoir on September 7, 2023 is 27.108m, and the storage capacity is 28.7552 million m 3 Therefore, it is predicted that the storage capacity of Shenzhen Reservoir will reach 30.6272 million m3 without water discharge at 8:00 on the 7th. 3 ,like Figure 7 According to the corresponding water level and reservoir capacity curve, the estimated water level is about 27.65m.

[0060] The error line of reservoir water level calculation using this method is as follows Figure 8 As shown, it can be seen that the maximum error for 30 minutes is 0.201m, and the maximum error for 60 minutes is 0.332m.

[0061] 5. Determine the risk level of the reservoir According to the characteristic water level of Shenzhen Reservoir: flood control limit water level is 27.60m, design flood level is 28.83m, verification flood level is 30.24m, and dam top elevation water level is 31.50m.

[0062] Therefore, the estimated risk of Shenzhen Reservoir at 8:00 on the 7th is: Level 4 risk.

[0063] In summary, the embodiment of the present invention is based on grid rainfall forecast data and the watershed unit line method, and uses the "Guangdong Province Storm Runoff Calculation Manual" and "Guangdong Province Storm Runoff Calculation Chart" and other Shenzhen geographical basic data produced and released by the Guangdong Provincial Water Conservancy and Hydrology System in 1991 to improve and develop a reservoir water level risk warning algorithm that is more accurate, has a usable calculation speed, and has moderate computing power requirements, which meets the needs of reservoir water level risk warning impact forecasting and has the following characteristics: 1. Calculation based on grid rainfall data The traditional hydrological unit line method of calculating reservoir water collection requires the first step of checking the design point rainstorm amount, and the second step of calculating the design surface rainstorm, and then calculating the basin precipitation. This method actually uses the past rainstorm type to predict the future rainstorm type, which has great uncertainty. The present invention uses grid rainfall forecast data. This method integrates satellite data, radar data, AI artificial intelligence algorithm, automatic station real-time data and other data to estimate rainfall, and has high accuracy in short-term precipitation (1-6 hours). Since the basin of urban reservoirs is small and the degree of hardening of the basin's underlying surface is high, the water collection time of urban reservoirs is short. Therefore, short-term precipitation is the precipitation data most needed for urban reservoir flood control.

[0064] 2. Calculate the confluence time based on actual reservoir water level monitoring and rainfall monitoring data The calculation method of reservoir catchment using the traditional unit hydrograph method is obtained by looking up tables based on the geographical location of the basin, soil permeability, vegetation coverage, etc. The present invention directly uses the rainfall curve measured by the automatic rain gauges in the basin and compares it with the reservoir water level change curve to obtain the concentration time. Compared with the traditional unit hydrograph method, the method used in the present invention can avoid the influence of the shortening of the concentration time caused by urban ground hardening and is more in line with the actual situation.

[0065] 3. Replace the design storm pattern with actual precipitation monitoring and grid forecast data The original unit hydrograph method uses the maximum design storm pattern of each duration in the average situation of the basin where the reservoir is located to replace the actual forecast storm pattern, which is an empirical prediction method for future precipitation. The present invention directly uses the measured precipitation at the stations and grid forecast precipitation, which is more scientific than the original method.

[0066] 4. Fully consider the contribution of previous precipitation to the reservoir water level The original method only considers the water volume contribution of subsequent precipitation at the calculation moment, and the previous precipitation is not included in the calculation. However, this method incorporates the precipitation amount when the previous recession process has not ended into the calculation, which can more accurately predict the inflow water volume.

[0067] 5. Propose a relatively reasonable reservoir risk classification According to the actual situation and operation needs of the reservoir project, the present invention proposes a relatively scientific and reasonable risk classification standard for reservoir meteorological disasters. Corresponding risk thresholds are set according to the characteristic water levels of each reservoir, including the normal storage level, flood control limited level, design flood level, check flood level, and crest elevation level.

[0068] The risk levels are initially set as no risk (water level does not reach the flood control limited level), level four (water level reaches the flood control limited level), level three (water level reaches the design flood level), level two (water level reaches the check flood level) risk, and level one (water level reaches the crest elevation), a total of five levels. The above parameters such as the flood control limited level, design flood level, check flood level, and crest elevation are characteristic parameters of each reservoir during design and construction, and these characteristic parameters have high guiding significance for the operation of the reservoir during the flood season.

[0069] Based on the same concept, the embodiment of the present invention also provides a reservoir water level prediction device, which includes a memory and a processor. At least one instruction is stored in the memory, and at least one instruction is loaded and executed by the processor to implement the reservoir water level prediction method provided by the embodiment of the present invention.

[0070] Based on the same concept, the embodiment of the present invention provides a computer-readable storage medium, in which at least one instruction is stored, and the instruction is loaded and executed by the processor to implement the reservoir water level prediction method provided by the embodiment of the present invention.

[0071] Those of ordinary skill in the art can understand that all or part of the steps to implement the above embodiments can be completed by hardware, or can be completed by instructing relevant hardware through a program. The program can be stored in a computer-readable storage medium. The storage medium mentioned above can be a read-only memory, a disk, an optical disc, etc.

[0072] As mentioned above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A meteorological disaster reservoir water level risk early warning method, characterized in that: include: Identify at least one reservoir basin rainfall station within the basin where the target reservoir is located; Determine the actual rainfall in the target reservoir basin according to the measured rainfall at the rain gauge station in the reservoir basin, and determine the unit line lag time of the target reservoir according to the actual rainfall in the basin; Determine the process net rain and unit line of the target reservoir; The reservoir water level of the target reservoir is estimated according to the process net rainfall and the unit line.

2. The meteorological disaster reservoir water level risk early warning method according to claim 1 is characterized in that: The step of determining the actual rainfall package of the target reservoir basin according to the measured rainfall of the rain gauge station in the reservoir basin comprises: Selecting a plurality of rainfall stations in the reservoir basin; The average rainfall value measured at multiple rain gauges in the reservoir basin is taken as the actual rainfall in the basin of the target reservoir.

3. The meteorological disaster reservoir water level risk early warning method according to claim 1 is characterized in that: The unit line hysteresis of the target reservoir is determined by comparing the sliding average of the actual rainfall in the basin with the reservoir water level fluctuation curve.

4. The meteorological disaster reservoir water level risk early warning method according to claim 1 is characterized in that: The method of calculating the reservoir water level according to the net rainfall and the unit line of the process includes: Multiply the net rain in each period by the unit line to obtain the runoff curve generated by the net rain in the current period; Add up the runoff curves generated by net rain in all periods to obtain the runoff curve for the entire rainfall process.

5. The meteorological disaster reservoir water level risk early warning method according to claim 4 is characterized in that: The method of calculating the reservoir water level according to the net rainfall and the unit line of the process also includes: according to the current reservoir capacity, adding the total inflow of water at the corresponding moment, and then calculating the reservoir water level through the reservoir water level capacity curve.

6. The meteorological disaster reservoir water level risk early warning method according to claim 5 is characterized in that: When calculating the reservoir water level at any time, the contribution of runoff within a historical preset time period is taken into account.

7. The meteorological disaster reservoir water level risk early warning method according to claim 1 is characterized in that: It also includes setting corresponding risk thresholds according to the characteristic water levels of each reservoir, including normal water storage level, flood control limit water level, design flood level verification flood level and dam crest elevation water level.

8. A meteorological disaster reservoir water level risk early warning device, characterized in that: including memory and processor; The memory is used to store instructions; The processor is used to execute the instructions in the memory to implement the reservoir water level prediction method described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: The method comprises instructions which, when executed on a computer, enable the computer to execute the reservoir water level prediction method according to any one of claims 1 to 6.

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