Simulatin the Hydrologic Response
HEC-HMS Validation Guide Version 4.1说明书
Hydrologic Engineering CenterHydrologic Modeling SystemHEC-HMSValidation GuideVersion 4.1July 2015Approved for Public Release – Distribution UnlimitedHydrologic Modeling System HEC-HMS, Release Notes2015. This Hydrologic Engineering Center (HEC) Manual is a U.S. Government document and is not subject to copyright. It may be copied and used free ofcharge. Please acknowledge the U.S. Army Corps of Engineers HydrologicEngineering Center as the author of this Manual in any subsequent use of thiswork or excerpts.Use of the software described by this Manual is controlled by certain terms andconditions. The user must acknowledge and agree to be bound by the terms and conditions of usage before the software can be installed or used. For reference,a copy of the terms and conditions of usage are included in Appendix E of thesoftware User's Manual so that they may be examined before obtaining thesoftware.This document contains references to product names that are used astrademarks by, or are federally registered trademarks of, their respective owners.Use of specific product names does not imply official or unofficial endorsement.Product names are used solely for the purpose of identifying products availablein the public market place.Excel is a registered trademark of Microsoft Corp.Mathcad is a registered trademark of PTC Inc.iiValidation Guide IntroductionThe Hydrologic Modeling System (HEC-HMS) is designed to simulate thehydrologic cycle. This broad simulation capability requires many differentcomponents: shortwave and longwave radiation, precipitation, potentialevapotranspiration, snowmelt, infiltration, surface runoff, baseflow, andchannel routing. Water control structures such as reservoirs anddiversions also contain a number of simulation components for spillways,pumps, and culverts, to name a few. These simulation componentsrequire an extensive array of time-series data, paired data, and griddeddata. The interaction of these various data and simulation componentsleads to a software package that is very complex.Hydrologic engineers in Corps of Engineers' offices nationwide supportplanning, design, operation, permitting, and regulating activities byproviding information about current and potential future runoff fromwatersheds, with and without water control structures. HEC-HMS cansupport these activities by simulating the behavior of watersheds, andcomputing estimates of runoff volumes, of peak flow rates, and of timing offlows. It is critical that these estimates be precise and accurate if they areto be useful. By precise we mean that every time the software computesa simulation, it must obtain the exact same numerical results for the sameinput data. By accurate we mean that the equations that are thefoundation of each of the simulation components are solved correctly.Code validation can be described as the process of determining that acomplex software program such as HEC-HMS produces precise andaccurate results. Code validation should not be confused with other typesof testing. For example, model validation is the process of determining if aproposed model (often a mathematical model) accurately represents aphysical process and provides predictive capability. In another example,verification is the process of determining if a set of model parametersestimated during calibration performs well under different but similarconditions. Code validation instead focuses on the very specific questionof whether the software accurately solves the equations used to model orrepresent the physical process. Software should not be used for any ofthe tasks undertaken by a hydrologic engineer unless it first candemonstrate code validation of all its internal components.The models and equations incorporated in HEC-HMS have been validatedby the research community. The equations in each of the simulationcomponents included in the program have been sourced from publishedhydrology textbooks and from papers published in peer-reviewed journals.The code validation process described here is designed to determine if thepublished models and equations have been incorporated correctly in theHEC-HMS software. However, code validation does not mean that aparticular model can be applied in any and every watershed. A variety of1Validation Guide2 simulation components are included in HEC-HMS because not every model is applicable in every watershed. The HEC-HMS user is responsible for selecting simulation components in the software appropriate to the selected watershed, and configuring them to appropriately represent the hydrological processes in the watershed. A calibration and verification process should be developed by the hydrologic engineer to determine if appropriate choices have been made in how the software is applied.The Test SuiteThe team responsible for the development of HEC-HMS has created anextensive set of code validation tests. The tests are designed todetermine if input data including time-series, paired data, and gridded dataare processed correctly. This includes tests of unit system conversion andinterpolation. The code validation tests also determine if the simulationresults are accurate. The accuracy of the results is determined by one oftwo methods. In some cases it is possible, given the input data andparameters, to calculate the correct result by hand. In these cases theequations are simple enough that hand calculations with the aid of acalculator can determine that the results computed by HEC-HMS arecorrect. Other cases require independent software such as ParametricTechnology Corporation Mathcad® or Microsoft Excel®. This secondapproach is required when the equations used in a simulation componentare differential equations, or some other type of complex equation.Mathcad and Excel are developed independently by teams of industryspecialists. The results from these independent software tools can beused to confirm that HEC-HMS is calculating accurate results.The code validation test suite created for HEC-HMS includes 38 projects.Each of these projects focuses on a separate simulation component, asshown in Table 1. Each of these projects contains from several to manysimulation runs. Each simulation run tests one component of the softwarein isolation from all other components. These tests have been carefullydeveloped and have a known, accurate solution. The test suite alsoincludes 18 projects from actual watershed applications, as shown inTable 2. These projects were selected because they are complex andrequire the interaction of many of the different simulation componentsincluded in HEC-HMS. These complex projects do not have rigorouslydeveloped accurate solutions. They are still useful because they can beused to detect any changes in simulated values that may arise fromincremental changes in the software. A change in the software thatcauses a computed result to change can be detected with these 18projects. If such a change occurs, then the source of the change must befound, investigated, and resolved.Validation Guide The projects used in the code validation test suite compute thousands oftime-series and paired data records. A total of 2,245 of these records arecompared against known standards. Each value of the time-series orpaired data record is compared and a test is deemed to have failed if evena single value is outside the allowable range. As a general rule, tests usean allowable error range of 0.02% of the correct value. This means thatHEC-HMS is deemed to have failed a validation test if it makes an errorgreater than 0.02% of the correct value. The development team reviewsthe results from the entire test suite before certifying a new softwareversion for general release. The validation suite is used to find errors sothey can be repaired.A new software version is not released for general use until it cansuccessfully pass all of the code validation tests in the suite. We makethe test suite available through the HEC website() so that users may, if desired, review the datasets included in the suite, and optionally compute them and compare theresults to the benchmark values. The projects do not need to beevaluated after downloading the software to know that the software isworking correctly. The software is fully tested before it is released for useand therefore will pass all of the tests successfully after it is installed. Thedigital certificate included in the installation package guarantees that thesoftware has not changed since it was certified as passing all validationtests. Any change that might occur in the software between the time itleaves HEC, and the time it is actually installed, could cause errors duringvalidation. Because a digital certificate is included in the installationpackage, the user would be alerted to any such changes during theinstallation process. Nevertheless, users have the option of independentlyconfirming the results already achieved by HEC staff preparing thesoftware for release.The following sections serve as documentation of the procedures used byHEC staff during testing. All of these steps are followed by HEC staffduring the testing required before a new version of HEC-HMS is releasedfor use. A user could follow these same steps if they wished toindependently validate the software.3Validation Guide4 Table 1. Listing of the projects for testing each of the HEC-HMS simulation components in isolation from other components.Project Simulation ComponentBench1 Sources, junctions, and sinksBench2 DiversionsBench3 Lag reach routingBench4 Kinematic wave reach routingBench5 Modified Puls reach routingBench6 Muskingum reach routingBench7 Muskingum-Cunge reach routingBench8 Muskingum-Cunge reach routingBench9 Reservoir routing and structuresBench9A Reservoir specified release routingBench9B Reservoir culvert outletsBench10 Subbasin loss rateBench11 Subbasin transformBench12 Subbasin baseflowBench13 Straddle stagger reach routingBench14 Specified hyetograph precipitationBench15 Inverse distance precipitationBench16Gage weights precipitationBench17 SCS storm precipitationBench18 Standard project storm precipitationBench19 Frequency stormBench20 Gridded precipitationBench21 Specified, monthly, and Priestley-Taylor ETBench22 Temperature index snowmeltBench23 Reach nutrient water qualityBench24 Reservoir nutrient water qualityBench25 Subbasin canopy and surfaceBench26 Source, junction, diversion, sink water qualityBench27 Source, junction, diversion, sink sedimentBench28 Optimization trial simulation componentValidation Guide Table 1. ContinuedProject Simulation ComponentBench29 Depth-area analysis simulation componentBench30 Forecasting alternative simulation componentBench31 Subbasin surface erosionBench32 Reach sediment transportBench33 Reservoir sediment settlingBench34 Uncertainty analysis simulation componentBench35 Shortwave radiationBench36 Longwave radiationTable 2. Listing of the projects from watershed applications with HEC-HMS for testing complex interactions of simulationcomponents.Project Primary Testing FocusAmerican Gridded snowmelt and time interpolationBald Eagle Creek Continuous simulation with deficit constant Bald Eagle Dam Break Dam failure and flood wave routingBall Mtn HMR52 probable maximum precipitationCulvert 111P Pond with culvert outletH100 PE REV Green Ampt loss, Modified Puls routinghms trmm Unit hydrographs and save statesKerrDam PMF HMR52 probable maximum precipitationLakeBistineau Reservoir spillway gatesMill Creek Event Gridded deficit constant loss rateMincio Soil moisture accounting, save statesMonongahela Forecasting and blendingPenman Monteith Penman Monteith potential evapotranspiration Pistol Creek Gridded deficit constantRogue Gridded precipitation, monthly ET, ModClarkTaro Canopy, surface, soil moisture accountingUNBR Reservoirs Sediment in reaches and reservoirsUNBR Reservoirs 2 Sediment in reaches and reservoirs5Validation GuideProject DataThe code validation test suite includes 38 projects for individualcomponents plus an additional 18 projects for testing complexinteractions. All of the files in each project directory are set with "read-only" file permission. The permission must be changed to "read-write" filepermission before the files can be used with HEC-HMS. Additionally, theproject DSS file in each project does not contain any simulation results. Ifthe user plans to compute the simulation runs included in these projects, abackup copy of these projects should be kept. Each time the benchmarkvalidation tests will be computed, a fresh copy of the backup projectsshould be used. Any changes to the data in the validation projects willcause the tests to fail.Established Accurate ResultsHand calculations and independent software have been used to establishknown accurate results for each code validation test. These known resultsare stored in a DSS file. There is a separate DSS file for each of thecorresponding projects used in validation testing. The simulation results ineach DSS file have been checked very carefully. Some of the methodsused to check the results include HEC-RAS for culvert calculations,Mathcad®, Excel®, and hand calculations by calculator. These files shouldnever be modified.Automated ComparisonIt would be very onerous to compare all of the 2,245 time-series andpaired data records manually. The development team has created a smallutility program to automate this task. The utility program reads the time-series and paired data of computed results from the project DSS file. Italso reads the records from the known result. The utility program thencompares value by value the two records. If two values do not agreewithin the error range, the error is recorded in a log file. A successfulpassage of the test is recorded in the log file if all values match within thenecessary error range. The log file is the only place to determine thesuccess or failure of each test.The configuration information for the comparison utility is stored in textfiles that have "in" as a prefix. These files contain the configuration datanecessary for the automated comparison of the simulated results with theestablished standard results. These files are designed to be used by the"Compare" utility. The utility reads the configuration file and according tothe instructions, compares simulated results against the establishedstandard results. A CMD script file is provided for each validation project.The script file can be executed by double-clicking on it in WindowsExplorer. The script file will cause the Compare program to start, read a6Validation Guide configuration file, and then perform certain comparisons. The results ofthe comparisons will be written to an output report file.Application StepsThe following steps should be used to execute the validation tests:1) Place a fresh copy of the benchmark projects in the directories andmake sure the file permission is set to "read-write."2) Start HEC-HMS and open the first project.3) Compute all of the simulation runs in the project.4) Open each of the additional projects and also compute all of thesimulation runs.5) Close HEC-HMS.6) Using Windows Explorer, double-click on each of the CMD script filesexcept for the one called "compare.cmd".7) Open each of the output report files and examine the results.7。
外文翻译蒸汽发生器水位模糊控制
学号389南湖学院毕业设计（论文）英文翻译英文题目：Research on Fuzzy Control for Steam Generator Water Level中文题目：蒸汽发生器水位模糊控制研究文献出处：Computer, Mechatronics, Control and Electronic Engineering(CMCE), 2010 International Conference on Date ofConference: 24-26 Aug. 2010作者姓名：Pengwei译者姓名：杨胜专业：机械设计制造及其自动化完成时间：on Fuzzy Control for Steam Generator Water LevelI. INTRODUCTIONThe steam generator is one of the main devices in PWR nuclear power plant, in order to ensure the safety of nuclear power plant during operation; the steam generator’s water level must be controlled in a certain range. When the nuclear power plant is running, as the steam flow or the water flow changing, the amount of boiling bubbles in the steam generator will change due to local pressure or temperature change, the instantaneous water level showed “false water level” phenomenon . The existence of “false water level” made it difficult to control the water level. The introduction of feed-forward control to the traditional single-loop PID control can, in a certain extent, overcome the "false water level" phenomenon. But the conventional PID control method in the process of steam generator water level control has some shortcomings. To the steam generator that has highly complex, large time-delay and nonlinear time-varying characteristics, the PID parameters tuning is a tedious job and the control effect is very poor. Furthermore, to achieve good control performance still as conditions changing, it often needs to change the PID controller parameters. But the analog PID controller parameters are difficult to regulate online. Fuzzy control is a kind of nonlinear control strategy based on fuzzy reasoning, which express operating experience of skilled manipulation men and common sense rules of inference through vague language. Fuzzy control do not need to know precise mathematical model of controlled object, is not sensitive to the change of process parameters, is highly robust and can overcome non-linear factors, so, fuzzy control has faster response and smaller ultra- tone, can get better control effect. Based on understanding above, this paper design a steam generator water level fuzzy controller, the simulation shows that the controller has good control performance and practical value.II. DYNAMIC CHARACTERISTICS OF STEAM GENERATORThe transfer function of PWR steam generator’s mathematical model of the general form shows below:y(s)=GW(s)QW(s)+GS(s)QS(s) （1）where y is the steam generator water level; QW for the water flow; QS for the steam flow; GW (s) for the impact of the water flow to the steam generator water level; GS (s) for the effect of the steam flow (load) to the steam generator water level.The balance of the steam generator water level is maintained through the match between the water flow and steam flow. The process that water level changes with the steam flow or water flow changing can be regarded as a simple integration process, but impact of the water flow and steam flow ‘s change on water level is different.A. Dynamics Characteristics under Water Flow DisturbanceSuppose steam flow GS remains unchanged, and water flow GW step increases, on the one handbecause the temperature of feed water is much lower than the temperature of saturated water in the steam generator, so that , when feed water entering, it will absorb a lot of extra heat, the vapor phase bubble contents will reduce, resulting in water level decreasing; on the other hand, the increase in water flow GW made it greater than steam load, and cause water level increases linearly. Comprehensive two factors, after the step increase of the water flow, the water level rise has a time delay process, showing a down then up.B. Dynamic Characteristics under Steam Load DisturbanceSuppose feed water flow GW remains unchanged, and steam load GS step increases, on the one hand the water level will flow down because the steam flow rate is greater than the water flow rate. On the other hand, as the steam load increased, vapor pressure is reduced; the bubble volume on the liquid surface increases, causing the water level increased. Comprehensive two factors, after the step increase of the steam flow rate, the water level down has a time delay process, showing a up then down.The impact on the water level of water flow or steam flow stepping decreased has similar principle as above.As analysis can be seen as above, when the water flow or steam load change, the water level did not follow the change immediately, but there is an opposite process at first. This phenomenon is called "false water level" phenomenon.III. DESIGN OF W ATER LEVEL FUZZY CONTROLLERThe conventional PID controller has a poor control performance to the steam generator that exist “false water level”characteristics, showing a greater overshoot in the tracking time. But a well-designed fuzzy controller is able to overcome the "false water level" phenomenon, and has good control performance.A. Sstructure of Fuzzy ControllerThe structure showed in Figure 1.Figure 1. Structure of steam generator water level fuzzy controllerChoose the water level error (e) and change rate of error (ec) as input of the fuzzy controller, the output of the fuzzy controller is the added value of the valve opening signal Δu. Meanwhile, use the steam flow feed-forward to overcome the "false water level" phenomenon, use water flow feedback to overcome fluctuations in water supply side . k1, k2 were water flow and steam flow transmitter conversion factor. To ensure the water flow to match the steam flow, k1 and k2 values should be equal to.B. Fuzzy theory, fuzzy subset and Membership FunctionThe fuzzy Analects of e, ec and u are [-6, 6], both with seven fuzzy sets NB (negative big), NM (negative middle), NS (negative small), ZO (zero), PS (positive small), PM (positive middle) and PB (positive big) to describe. e, ec and, Δu are all using triangular membership function (see Figure 2).Figure 2. Input and output variable membership functionC. Fuzzy control rule tableThe establishment principle of fuzzy control rules are: when the error is large, the output control volume should give priority to eliminate error as soon as possible; when the error is small, the output control volume should givepriority to prevent overshoot. Where ec is negative ,it shows that water level has a rising trend, if the water level is high at this time, then we should reduce the valveFuzzycontrollerK1 valveG W (s) dx/dtK2G S (s) expected water lever Stream flowWater leverwaterfloweec + -+ +- + ++opening signal; whereas, we should open the valve more. Through a comprehensive analysis of expertise, the establishment of rule table shown in Table 1.Table 1. Fuzzy control rule tableD. Fuzzy Reasoning and SolutionThis fuzzy inference system uses Mamdani. The basic properties of fuzzy inference system set to: "and" operation with a very small operation; "or" operation uses the maximum operation. Using a very small operation fuzzy implication, fuzzy rules integrated with great operations center Defuzzification method used. IV . SIMULATION EXAMPLESA pressurized water reactor steam generator in Chinese Qinshan nuclear power station has empirical model G1 (s), G2 (s) below:()()()()⎪⎪⎩⎪⎪⎨⎧+⋅++++==---7%15,)128(415.0)13)(129(19.36%90,)13)(129(19.3)()(551Ps s s s s e Ps s s s e e s G s G sssp τ()()8%90,14398.0)124(819.3)(2Ps s s s s e s G +++--=where Ps denote the rated load. When load at 15% ~ 90% Ps, use (6) and (8); when load less than 15% Ps, use (7) and (8).Figure 3. Expected water level step response diagramThe coefficients in Control system are k1=k2=. Water control valve is a king of linear valve, its gain is 4. The quantitative coefficients of e and ec are 6 and 60 respectively; the scale factor of u is . We limit water flow the range of 0 kg / s to the rated flow 258kg / s when simulation. Consider the expected level step from the initial 0m to 10m, water level response is shown use the solid line in Figure 3. For contrasting the increase effect of fuzzy controller, we also carried out using the traditional PID control simulation. We can see, compared with traditional PID control, fuzzy controller has reported significant improvements in overshoot, settling time, steady degrees.V. CONCLUSIONThis paper designed a water level fuzzy control system aimed at steam generator‘s characteristics of large time delay and model uncertainty. We also gave a simulation to the steam generator of Qinshan nuclear power plant, and achieved satisfactory results. The method can also be used for other large time -delay and time-varying process control model, and has broad application prospects.蒸汽发生器水位模糊控制研究1.导论蒸汽发生器是压水反应堆式核电厂里的一个重要的设备。
HydroGeoSphere在锦屏水电站坝址区水流和溶质运移模拟中的应用
黄勇，等：HydroGeoSphere在锦屏水电站坝址区水电站坝址区水流和溶质运移模拟中的应用2431 引言裂隙岩体主要由岩体基质和裂隙网络组成，岩体基质以贮水为主，通常采用等效连续介质模型描述；裂隙网络以导水为主，常采用离散网络模型描述。
模型的求解主要采用有限体积法，如Therrien 和Sudicky[1]，Graf和Therrien[2], Bodin等[3], Bodin等[4], Peratta等[5]和Ito等[6]分别采用有限体积法对连续-离散裂隙耦合模型进行了研究，刘玉玲[7]将基于流向量分裂技术的两步有限体积分量方向TVD格式应用于求解浅水方程和污染物输运方程，建立了二者耦合求解的高分辨率计算模型。
基于有限体积法，He Feng-yun[8]对非稳定粘性流体的方程进行了离散。
此外，McKennaa等[9]将两种不同的随机模型应用在Yucca Mountain地区的溶质运移模拟，获得了很好的结果。
何杨等(2007) [10]针对稀疏的三维主干岩体裂隙网络，以渗流区内的水量平衡原理为依据建立基本方程，推导三维岩体裂隙网络非稳定渗流的基本方程，并利用Monte-Carlo模拟了岩体中的裂隙网路。
Zhang Qian-fei（2008）[11]利用欧拉-拉格朗日方法对裂隙岩体中的水流和对流-弥散过程进行了研究，Li Min（2007）使用积分变换法获得了承压含水层中地下水流运移规律的解析解[12]。
裂隙岩体中渗透参数和溶质迁移参数主要采用示踪试验获得（Weatherill和Salve[13，14]）基于HydroGeoSphere软件包，本文采用等效连续介质模型和耦合模型来模拟裂隙岩体中的水流和溶质运移规律，含水层参数的率定主要利用实测的地下水位和示踪试验的结果，并对两种模型的模拟结果进行了对比。
2 地质概况锦屏Ι级水电站位于四川省的木里和盐源县境内，距雅砻江的下游出口约358 km，研究区域介于雅砻江、锦屏断层、普斯罗沟和手爬沟之间（图1），雅砻江的水流方向为N25~27 E。
geo-hms分布式水文建模流程
geo-hms分布式水文建模流程English Answer:Geo-HMS Distributed Hydrologic Modeling Workflow.The Geo-HMS Distributed Hydrologic Modeling Workflow provides a comprehensive framework for simulating hydrologic processes at the watershed scale. It combines the capabilities of GIS, remote sensing, and hydrologic modeling to create a robust and flexible modeling environment.Key Components of the Workflow:Data Preprocessing: This step involves preparing the input data, including terrain data, land use maps, soil properties, and climate data. The data is processed to ensure consistent formats and projections.Hydrologic Model Setup: The Geo-HMS platform includesa library of hydrologic models that can be used to simulate various hydrologic processes. The user selects the appropriate model for their application and defines the model parameters.Model Calibration and Validation: The model is calibrated using observed data, such as streamflow measurements, to ensure that it accurately represents the physical system. The model is then validated using an independent dataset to evaluate its predictive capabilities.Scenario Analysis: Once the model is calibrated and validated, it can be used to perform scenario analysis.This involves changing the input parameters to represent different conditions, such as climate change or land use change, and assessing the impact on hydrologic response.Visualization and Analysis: The results of themodeling process can be visualized using GIS tools tocreate maps and charts. The user can analyze the results to identify areas of concern, evaluate the effectiveness of management practices, and make informed decisions.Advantages of the Geo-HMS Workflow:Distributed Approach: The workflow allows for the distributed representation of hydrologic processes, providing a more accurate representation of the spatial variability of the watershed.Data Integration: The workflow seamlessly integrates GIS, remote sensing, and hydrologic modeling data, providing a comprehensive platform for data management and analysis.User-Friendly Interface: The Geo-HMS platform features a user-friendly interface that simplifies the modeling process, making it accessible to users of all levels.Flexible Modeling Options: The workflow supports a wide range of hydrologic models, allowing users to select the most appropriate model for their specific needs.Scalability: The workflow is designed to handle largedatasets and complex models, making it suitable for modeling large watersheds and river basins.Applications of the Geo-HMS Workflow:Watershed management.Flood risk assessment.Water quality modeling.Climate change impact assessment.Land use planning.中文回答：Geo-HMS分布式水文建模流程。
机器学习模型在岩溶地区水文预报中的适用性分析
ｈｔｔｐ：／／ｗｗｗ．ｒｅｎｍｉｎｚｈｕｊｉａｎｇ．ｃｎＤＯＩ：１０ ３９６９／ｊ ｉｓｓｎ １００１ ９２３５ ２０２４ ０３ ００７第４５卷第３期人民珠江 ２０２４年３月 ＰＥＡＲＬＲＩＶＥＲ基金项目：国家自然科学基金（９１８４７３０１、９２０４７２０３、４２０７５１９１、５２００９０８０、４２１７５１７７）；蒙开个地区河库连通工程梯级泵站运行调度研究科技项目（ＭＫＧ〔２０２１〕 ＫＹＫＴ ０１）；中央级公益性科研院所基本科研业务费专项资金（Ｙ５２１０１１、Ｙ５２１０１３）收稿日期：２０２３－０７－１９作者简介：赵泽锦（１９７５—），男，本科，高级工程师，主要从事水文水资源研究。
Ｅ－ｍａｉｌ：ｚｈａｏｚｅｊｉｎ７７００＠１６３．ｃｏｍ通信作者：张轩（１９９６—），男，硕士，工程师，主要从事水文物理规律模拟及水文预报研究。
Ｅ－ｍａｉｌ：ｘｚｈａｎｇ＠ｎｈｒｉ．ｃｎ赵泽锦，孙伟，周斌，等．机器学习模型在岩溶地区水文预报中的适用性分析［Ｊ］．人民珠江，２０２４，４５（３）：５９－６８．机器学习模型在岩溶地区水文预报中的适用性分析赵泽锦１，孙 伟２，周 斌１，张 轩３，王高旭３，吴 巍３，李文杰１，姚 业１（１．红河州南源供水有限公司，云南 蒙自 ６５１４００；２．南京瑞迪水利信息科技有限公司，江苏 南京 ２１００２９；３．南京水利科学研究院水文水资源与水利工程科学国家重点实验室，江苏 南京 ２１００２９）摘要：现有岩溶地区的水文预报主要采用基于物理机制的水文模型，而机器学习模型的应用较为罕见。
为了探索机器学习模型在岩溶地区水文预报的适用性，以云南省沙甸河流域为研究区，采用了ＬＳＴＭ模型与随机森林模型对倘甸水文站的逐日径流量与场次洪水进行了模拟，并以针对岩溶地区的改进型新安江模型做参照。
研究表明：机器学习模型与改进型新安江模型在日径流过程模拟方面都取得较好的效果，ＬＳＴＭ模型模拟效果更优；场次洪水模拟方面，改进型新安江模型达到了甲级预报精度，机器学习模型６ｈ预见期预报结果整体优于改进型新安江模型，但２４ｈ预见期的预报结果不能满足预报业务的精度需求。
江洪老师
江洪博士南京大学国际地球系统科学研究所，教授电话：传真：电子邮件：jianghong@A.学习及工作简历:1.中国南京大学国际地球系统科学研究所，教授（2004.1 -）进行生态和环境模拟、全球变化生态学、定量环境遥感和生态系统进化等方面的研究。
2.美国,保护生物学研究所,高级研究员(2001.4- 2006), 在该所负责生态学与保护生物学研究和遥感与空间分析。
3.加拿大阿尔伯塔大学可更新资源系访问教授和博士后(1997.4-2001.3),同时兼任加拿大自然资源部北方林业研究中心合作研究员(1998.11-2001.3),进行全球高纬度北方森林过渡带的碳循环研究, 负责空间分析和陆地生态系统过程模型的模拟, 并进行火干扰生态, 景观生态和遥感应用的合作研究.4.美国俄勒冈州立大学森林科学系访问教授(1995.8-1996.3), 合作进行景观生态和生态模拟的研究.5.中国科学院植物研究所研究员(1994.11-1995.7),中国科学院地理与自然资源研究所研究员(1995.7-1997.3),从事生态学, 空间分析和模拟,保护生物学和遥感应用的研究,“中国生态系统研究网络”研究和建设.6.美国新墨西哥大学生物系高级访问学者(1993.9-12),参加美国科学院和中国科学院合作项目”长期生态数据管理和信息系统研究”的高级培训班.7.中国科学院植物研究所博士后(1990.1-1992.2)和副研究员(1992.2 -1994.10),从事植物生态学, 生态模型和模拟,保护生物学的研究,“中国生态系统研究网络”研究和建设.8.中国东北林业大学(1985-1989.12)进行生态学及其相关学科的学习, 1989年底获生态学博士学位.B. 最近主持和参加的研究项目:1．国家重点基础研究发展规划( 973计划)项目“我国东部沿海城市带的气候效应及对策研究”,课题“城市群区大气污染物的辐射强迫及其对能量平衡的影响（2010CB428503）”，2010-2014。
水文模拟在自然科学中的使用教程
水文模拟在自然科学中的使用教程随着科学技术的不断进步，水文模拟成为了自然科学领域中一种重要的工具。
它可以帮助我们预测水文过程，分析水资源的利用和保护，以及评估水环境的变化。
本文将介绍水文模拟的基本原理和常用方法，以及如何应用它来解决实际问题。
一、水文模拟的基本原理水文模拟是通过建立数学模型来模拟和预测水文过程的一种方法。
它基于一系列的物理方程和统计关系，通过计算机程序对水文系统进行数值模拟。
水文模拟可以分为两种类型：分布式模型和集中式模型。
分布式模型是将流域划分为多个子流域，每个子流域都有自己的特征和参数。
这种模型可以更准确地模拟流域内不同地区的水文过程，如降雨、蒸发、径流等。
常用的分布式模型有SWAT（Soil and Water Assessment Tool）和HEC-HMS （Hydrologic Engineering Center's Hydrologic Modeling System）等。
集中式模型则将整个流域看作一个整体，通过简化和统计的方法来模拟水文过程。
这种模型适用于数据较少或对模拟精度要求不高的情况。
常用的集中式模型有HBV（Hydrologiska Byråns Vattenbalansavdelning）和VIC（Variable Infiltration Capacity）等。
二、常用的水文模拟方法1. 降雨径流模型：降雨径流模型是水文模拟中最基本的模型之一。
它通过描述降雨和径流之间的关系来模拟流域的径流过程。
常用的降雨径流模型有SCS-CN （Soil Conservation Service Curve Number）模型和IHACRES（Identification of Hydrographs And Component flows from Rainfall, Evaporation and Streamflow data）模型等。
2. 地下水模型：地下水模型用于模拟地下水的流动和补给过程。
融合多源信息的水文水资源综合模拟系统
汇报提纲
一、若干认知的讨论 二、HIMS系统的研发 三、HIMS系统的应用 四、结语
HIMS水循环综合模拟系统的研制目标
时资不 空料确 变稀定 异缺性 性性
多尺度综合模拟
全球气候模式 区域水循环模式
流域分布式水循环模式
气气候候变变化化
系统集成 模式耦合
水
原型观测 过程机理
水水系系统统 水水管管理理
7. 水文模型应层次清晰，包含水循环的关键过程，兼顾 水量和水质的模拟，以便应用于面源污染、富营养化 等生态环境问题
8. 考虑水循环在地球圈层之间的交互作 用
➢水循环是地球系统各圈层的纽带。如果水循环融入地球系统科
学，或者现代水文学要沿地球系统科学方向发展，重要的是水文
学需要跨向生物地球化学循环和能量循环的研究。
10. 人类活动对水循环的影响认知
中国当前面临大规模的人类活动主要是： ➢ 城市化，由当前的52%增加到大约70% ➢ 工业化包括矿山、煤炭能源化工基地等等 ➢ 农业现代化与大规模水土保持、退耕还林、
生态文明建设等等、、、
所有的建设与发展都会引起土地利用与覆盖即 “LUCC”的变化。而其变化将导致水文水 资源的变化。因此我们集中关注LUCC变化 的水文响应
6、水库调蓄 7、汇流结构 8、地下单元 9、模型控制 10、数据模块
水面蒸发
下一个单元流域
河川 水库(湖泊)
径流
调蓄
坡面 水库 河道 地下水
开始
读入控制代码、参数、 初始状态、流域特征
读入降水、气温或蒸 发、入流、灌溉数据
是否最后时段？
是
否
是否最后子流域？
否 子流域产流计算
河段汇流计算
模型控制、参 数、状态数据库
陆面水文模型发展、参数标定与移植
裸土蒸发Eg（bare soil surface evaporation）
冠层水量平衡
冠层持水量Mc的平衡方程可由下式表达： M c P E w Dc t
P-降水率； Ew -土壤湿部蒸发； Dc-大于叶片最大持水量而滴落到地面的部分。
R
E K1 K2
P D1 D2
z=0 z=-z1 z=-z2
基于全国50 kmX50 km网格 大尺度陆面水文模型
基于全国50 kmX50 km网格 大尺度陆面水文模型
陆 面 过 程 模 式 （ ）
水分收支过程
VIC
能量收支过程
Grid Cell Energy and Moisture Fluxes
Grid Cell Vegetation Coverage
z2
3 .( z3 z2 ) K ( ) z2 D( ) t z
z2
Qb
径流和排水
P z2 .( s 2 ), i0 p im 1 b R i0 P P z2 .( s 2 ) z2 . s .1 i , i0 P im m
陆面过程研究前沿问题
• 水文过程研究需要深入； • 生态过程机制（C,N循环）需要发展，植被 动态演替； • 各种非均匀性问题； • 陆面模型的参数标定与移植； • 陆面数据同化问题，全球土壤湿度等陆面分 量的时空分布； • 与区域与全球气候模式的耦合； • 各种应用问题； • 雪盖、冻土和旱土、大面积水面作用的描述 简单，冻土、雪盖占陆面面积都远大于1/4， 沙漠区占1/4。
• 陆面水文模型发展、参数标定与移植
及其耦合、模拟研究； • 基于全国50 kmX50 km大尺度陆面水文模型； • 陆面模型的参数标定、移植与模拟； • 讨论
VIC模型在东江流域城市化水文响应研究中的应用
Journal of Water Resources Research水资源研究, 2014, 3(1), 78-83/10.12677/jwrr.2014.31013 Published Online February 2014 (/journal/jwrr.html) Application of VIC Model to Hydrological Response Caused by Urbanization in Dongjiang BasinZengxin Yu1, Jiaquan Deng2, Cheng Liu21South China University of Technology, Guangzhou2Pearl River Hydraulic Research Institute, GuangzhouEmail: jiaquandeng@Received: Sep. 30th, 2013; revised: Nov. 20th, 2013; accepted: Nov. 26th, 2013Copyright © 2014 Zengxin Yu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. In accordance of the Creative Commons Attribution License all Copyrights © 2014 are reserved for Hans and the owner of the intellectual property Zengxin Yu et al. All Copyright © 2014 are guarded by law and by Hans as a guardian.Abstract:As a grid based semi-distributed hydrological model, VIC is the important tool in evaluating the basin hydrological response to environmental changes. The Dongjiang VIC model is established at the spatial resolution of 0.25˚ by using the University of Maryland Global Land Cover Facility 1 km dataset, Harmo-nized World Soil Database and the Meteorological Data from the meteorological or precipitation stations lo-cated in the Dongjiang basin. Based on the characteristics of the flow confluence in Dongjiang Basin, the routing model developed by Dag Lohmann is coupled with the VIC to calculate the stream-flow. Monthly values of simulated stream-flow are compared with observations collected from Boluo hydrologic station (1961-1970) to calibrate and verify the VIC model. The results show that the relative errors of average annual runoff are respectively 6.2% and 2.0%, and the Nash-Sutcliffe coefficients are respectively 90.1% and 84.3%, which means that VIC model has good adaptability to the hydrological simulation of Dongjiang Basin. Aim-ing at the parameterization deficiency of VIC model for stream-flow generation from urbanized areas, the in-fluence of different types of land use and K sat values to stream-flow generation for grid cell is discussed. The results show that there are no key parameters in the vegetation file for stream-flow generation from urbanized areas, while to adjust the value of K sat in the soil file has a positive effect on simulating the base-flow and runoff generation from urbanized areas.Keywords:VIC Model; Hydrologic Simulation; Dongjiang Basin; UrbanizationVIC模型在东江流域城市化水文响应研究中的应用余增鑫1，邓家泉2，刘诚21华南理工大学，广州2珠江水利科学研究院，广州Email: jiaquandeng@收稿日期：2013年9月30日；修回日期：2013年11月20日；录用日期：2013年11月26日摘要：VIC作为基于单元网格的半分布式水文模型，是目前评价流域环境变化下水文响应的重要工具。