基于模块的分布式水文模拟系统及其应用

由于水文循环过程的复杂性和空间变异性,集成不同的水循环模型,基于模块化结构、构建面向多目标的水文模拟系统已经成为当今水文模拟技术发展的一个重要方向。本文从科学研究和水资源管理的实际需要,首次研发国内基于模块化的分布式水文模拟系统,并提出了“信息化水文模拟系统(HydroInformatic Modeling System, 简称HIMS)”。HIMS是一个以水循环信息平台为基础,基于组件式结构设计的开放式综合水循环模拟系统,侧重于分布式水文过程的模拟与应用。文中对HIMS的设计思路,主要功能与结构进行了详细介绍,包括基于国产GIS软件SuperMap的水循环信息系统、模型数据前/后处理系统和水文模型方法库系统。其中,HIMS的水文模型方法库系统集成了水文过程方法库和多种水文模型,并提供定制水文模型的功能。HIMS的提出发展了水文模型理论和建模技术,拓宽了国内分布式水文模型的研究思路。     

地表物质能量交换过程中的水循环综合模拟系统(HIMS)研究进展

基于地学的理念,特别是陆地表层系统研究理论,探讨了水循环研究发展趋势,从单一要素过程、到流域多过程综合、再到水系统多要素、多过程、多尺度的集成,阐述了发展水循环综合模拟技术的重要性。系统介绍了自主研发的水循环综合模拟系统HIMS(Hydro-Informatic Modeling System)的发展历程、主体结构与特色功能,包括水循环多源信息集成平台、水循环多元要素定量遥感反演系统、水循环过程模块库集成系统、多尺度分布式水循环定制模拟系统等。指出多学科交叉,与信息技术的融合是水循环模拟发展的重要方向之一。HIMS系统及其定制模型在国内外的大量验证和应用,显示出其水循环综合模拟技术的实用性和先进性。可望为变化环境下的复杂陆地表层过程中涉水问题研究提供技术支撑工具,适应水系统研究的需要。     

水文模型参数敏感性快速定量评估的RSMSobol方法

水文模型参数敏感性分析是模型不确定性量化研究的重要环节,其可以有效识别关键参数,减少模型率定的不确定性,提高模型优化效率。然而如何快速有效地定量评估参数敏感性已成为当前大尺度分布式水文模型优化的瓶颈。针对传统的全局定量敏感性分析方法在多参数复杂水文模型的不足,本文采用基于统计学习理论的支持向量机(SVM) 建立非参数响应曲面(称为代理模型),再结合基于方差的Sobol 方法,建立了基于响应曲面方法的Sobol 定量全局敏感性分析方法(RSMSobol 方法),实现复杂模型系统参数敏感性的快速定量化评估。本文选用淮河流域的日尺度分布式时变增益水文模型进行实例研究,采用水量平衡系数(WB),Nash-Sutcliffe 效率系数(NS) 和相关系数(RC) 三个目标函数综合评价模拟效果。研究结果显示RSMSobol方法在实现定量全局敏感性分析的同时降低了模型运行时耗,提高了模型评估效率,且与传统定量方法Sobol 方法具有同样的评估效果。该方法的有效应用为大型复杂水文动力模拟系统的参数定量化敏感性评价提供了参考,为模型参数进一步优化提供了可靠依据。     

《现代水文学》出版发行

反映水文学最新发展的学术专著《现代水文学》 ,近日由黄河水利出版社正式出版发行。《现代水文学》是以现代新技术新理论应用为支撑 ,系统阐述现代水文学的理论、方法及应用 ,为水问题研究 ,提供现代水文学的研究基础。全书系统阐述了水循环的概念、原理及研究进展 ,水文不确定性问题、非线性问题和尺度问题的研究意义与基本方法 ,水文系统识别的概念、原理和方法 ,“3Ｓ”技术及在水文学中的应用 ,水资源可再生性研究和可持续水资源管理量化研究 ;还介绍了代表水文模型发展方向的分布式水文模型、水文 -生态耦合系统模型等。该书作者左其…     

水文模型参数敏感性分析—优化—区域化方法研究进展

水文模型是认识水文科学规律、分析水文过程及研究水文循环机理的重要科学工具。水文模型模拟结果的不确定分析是提高模型可靠性、进行有效水情预报的一个重要研究内容。参数不确定性是影响水文模型模拟结果不确定性的关键因素之一,开展模型参数不确定性及其影响因素分析对水文预报具有重要现实意义。目前的参数不确定性分析方法大致可分为3类：参数敏感性分析、参数优化以及考虑无资料流域参数值估计的参数区域化方法。论文归纳总结了近年来国内外水文模型参数不确定性分析工作的主要研究进展,分析了不同方法的优点与不足,提出了未来水文模型不确定性分析方法研究的潜在发展方向。借助多学科理论和技术方法,加强水文模型不确定性分析系统性方法的研究,是水文学科当前的迫切需求及发展趋势。     

塔里木河源流山区径流模拟及不确定性研究

自然环境恶劣、站点稀少、观测困难是干旱区水文系统研究面临的基本问题。特殊的自然地理条件给水文过程带来了极大的复杂性和不确定性,也阻碍了干旱区水文过程和机理研究的发展。选取塔里木河源区开都河流域为研究区,采用分布式水文模型MIKE SHE模拟大尺度资料稀缺地区水文过程,将流域内气象、水文站点数据与遥感数据相结合,利用气象、土壤类型、土地利用和地表覆盖、数字高程(DEM)和降雨等资料,模拟流域水文过程;在出山口径流数据的基础上对模型进行率定和验证;分析了模型中的不确定性的来源,探讨模型优化方法。结果表明,MIKE SHE模型能在水文、气象站点稀少,土壤及水文地质数据缺乏的条件下,模拟开都河流域的日径流过程,但精度仍有待提高;通过分析识别出了隐含于模型结构、输入及参数等3个方面的8种不确定性来源。     

黄河典型流域分布式水文过程模拟

基于水循环物理过程的分布式水文模型的研究和应用已经成为当前水文学研究的热点之一。本文应用大尺度分布式水文模型SVAT&HYCY ,选择黄河的主要支流洛河卢氏以上流域进行实例研究。根据 1990～ 1996年的资料进行的模拟结果表明 ,模型可以反映流域蒸散发的空间分布特征以及径流的形成过程。但是在模拟的径流值与实测值之间还有一些差异。这种差别一方面是因为实际径流包含了人类活动的影响 ,另一方面 ,空间插值方法是否准确反映模型的输入量 (特别是降水 )的空间分布特征也将影响模拟精度。     

陆面水文—气候耦合模拟研究进展

陆面水文过程是全球/区域气候模式十分重要而又十分薄弱的环节。本文通过科学文献计量法,分析了陆面水文—气候耦合研究的发展状况及研究热点和趋势,并进一步对研究中存在的问题和挑战进行综述和探讨。现有多数气候模式中的陆面模式主要基于一维垂向结构设计,缺乏对流域尺度水文过程的精细描述,尤其缺乏下垫面人类活动影响的描述。因此,为了科学认识水文过程与气候变化的相互反馈作用机制,大量研究主要通过耦合流域水文模型与气候模式,研究不同时空尺度下水文过程变化的气候反馈效应。陆面过程模式中水文过程的改进和大尺度水文模型发展为陆面水文—气候耦合模拟奠定基础,在此基础上,陆面水文—气候耦合研究正从传统的单向耦合研究逐步发展为考虑气候—水文反馈的双向耦合研究。然而,双向耦合研究远未成熟,其问题集中表现为陆面水文—气候模型耦合过程如何匹配并提高系统稳定性、研制有效的尺度转换方案、完善参数化方案并评估参数不确定性、研制有效参数移植方法并提高模型适用性以及高分辨率甚至超分辨率模拟等方面,逐步解决上述问题并提高模拟精度是未来水文—气候耦合模拟研究的重要发展方向。     

潮河流域时变增益分布式水循环模型研究

在广泛了解有关分布式水文模型研究进展的基础上,结合中国实际资料条件和问题,提出了一种"水文循环机理-系统理论"相耦合的分布式水循环模型——时变增益分布式水循环模型(DTVGM),并建立了潮河流域分布式水文循环模型。实例研究表明,DTVGM的应用是比较成功的,基本上能够满足水资源管理的要求。     

湿地水文研究的若干热点问题

湿地水文研究是认识湿地生态系统的结构、过程与功能,进行湿地生态保护和恢复重建以及水资源合理配置的前提与基础。重点对湿地水文研究的几个热点问题进行了评述。这些问题包括,全球气候变化与人类活动影响下的湿地水文响应;湿地水文过程对湿地生态系统的影响机制;湿地水循环过程与水文模型。在此基础上,提出了基于水循环模拟的流域湿地水资源合理配置的基本思路,并对目前中国湿地水文亟待研究的重要议题进行了阐述。     

大尺度水循环模拟系统不确定性研究进展(英文)

The regional hydrological system is extremely complex because it is affected not only by physical factors but also by human dimensions.And the hydrological models play a very important role in simulating the complex system.However,there have not been effective methods for the model reliability and uncertainty analysis due to its complexity and difficulty.The uncertainties in hydrological modeling come from four important aspects:uncertainties in input data and parameters,uncertainties in model structure,uncertainties in analysis method and the initial and boundary conditions.This paper systematically reviewed the recent advances in the study of the uncertainty analysis approaches in the large-scale complex hydrological model on the basis of uncertainty sources.Also,the shortcomings and insufficiencies in the uncertainty analysis for complex hydrological models are pointed out.And then a new uncertainty quantification platform PSUADE and its uncertainty quantification methods were introduced,which will be a powerful tool and platform for uncertainty analysis of large-scale complex hydrological models.Finally,some future perspectives on uncertainty quantification are put forward.     

分布式水文模型全局敏感性高效分析方法研究(英文)

Sensitivity analysis of hydrological model is the key for model uncertainty quantification. However, how to effectively validate model and identify the dominant parameters for distributed hydrological models is a bottle-neck to achieve parameters optimization. For this reason, a new approach was proposed in this paper, in which the support vector machine was used to construct the response surface at first. Then it integrates the SVM-based response surface with the Sobol’ method, i.e. the RSMSobol’ method, to quantify the parameter sensitivities. In this work, the distributed time-variant gain model (DTVGM) was applied to the Huaihe River Basin, which was used as a case to verify its validity and feasibility. We selected three objective functions (i.e. water balance coefficient WB, Nash-Sutcliffe efficiency coefficient NS, and correlation coefficient RC) to assess the model performance as the output responses for sensitivity analysis. The results show that the parameters g1 and g2 are most important for all the objective functions, and they are almost the same to that of the classical approach. Furthermore, the RSMSobol method can not only achieve the quantification of the sensitivity, and also reduce the computational cost, with good accuracy compared to the classical approach. And this approach will be effective and reliable in the global sensitivity analysis for a complex modelling system.     

A framework for uncertainty assessment in simulation models

In this article, we introduce a conceptual framework for systematic identification and assessment of sources of uncertainty in simulation models. This concept builds on a novel typology of uncertainty in model validation and extends the GIScience research focus on uncertainty in spatial data to uncertainty in simulation modelling. Such a concept helps a modeller to interpret and handle uncertainty in order to efficiently optimise a model and better understand simulation results.

To illustrate our approach, we apply the proposed framework for uncertainty assessment to the TREE LIne Model (TREELIM), an individual-based model that simulates forest succession at the alpine tree line. Using this example, uncertainty is identified in the modelling workflow during conceptualisation, formalisation, parameterisation, analysis and validation. With help of a set of indicators we quantify the emerging uncertainties and assess the overall model uncertainty as a function of all occurring sources of uncertainty.

An understanding of the sources of uncertainty in an ecological model proves beneficial for: (1) developing a structurally valid model in a systematic way; (2) deciding if further refinement of the conceptual model is beneficial for the modelling purpose; and (3) interpreting the overall model uncertainty by understanding its sources. Our approach results in a guideline for assessing uncertainty in the validation of simulation models in a feasible and defensible way, and thus functions as a toolbox for modellers. We consider this work as a contribution towards a general concept of uncertainty in spatially explicit simulation models.     

新安江模型参数的不确定性分析

水文模型的不确定性研究是水文科学研究的重要课题。模型参数的不确定性分析是水文模型不确定性研究的重要内容之一。本文采用GLUE方法分析新安江模型参数的不确定性,结论基于对不同水文特征流域的长时间径流模拟,研究发现大量"等效性"参数组存在。据此将参数总结为三类:第一类为非敏感参数,如上层张力水容量UM等。它们对似然判据,及确定性系数(R²)影响小。第二类为敏感性参数,如河网蓄水消退系数CS等,其特点是对R²的影响大。第三类为区域性敏感参数,如张力水蓄水容量曲线的方次B等,它们对R²的影响力跟流域特征密切相关。这些结论有助于理解新安江模型参数,为今后流域水文模拟提供参考。文中还展望了未来水文模型不确定性研究的发展方向。     

GIS-based modelling of topography-induced solar radiation variability in complex terrain for data sparse region

Solar radiation not only sustains the lives on the Earth, but also creates spatial and temporal variations of hydrological ingredients, such as vegetation, soil moisture, and snow. Precise quantification of spatial solar radiation incident on the Earth's surface which accounts for the topographic modulation, especially in complex terrain, underpins the study of many catchment hydro-meteorological and hydro-ecological processes. Topography is a key parameter that affects the spatial solar radiation pattern across different scales. This article addresses the issue of modelling spatial variability of actual solar radiation caused by topography from the hydrological perspective. Models with different algorithms and different complexities, from the simple empirical equations to process-based physical approach, have been developed to parameterize and calculate the potential radiation (under clear-sky condition) and the actual radiation (under overcast cloudy condition). Based on a review of the general steps of solar radiation modelling and the corresponding models for each step, two models with easily or globally available data for spatial solar radiation modelling in complex terrain, namely, the physically parameterized, remote-sensing-oriented Heliosat-2 model and the sunshine duration-based Angström–Prescott regression model are selected and implemented in a GIS framework. The capability of both models for simulation of cloudy-sky radiation on horizontal surfaces has been verified against observed station data showing an R ² greater than 0.9. The validity of the models for modelling inclined surface is tested by comparing against each other, which has shown a satisfactory agreement and demonstrated that the simple Angström–Prescott method performed reasonably well compared with the more elaborate Heliosat-2 method. Scale sensitivity of the models and the shading effect are examined with different digital elevation model (DEM) resolutions from 30 to 500 m and reveal the existence of a threshold grid size to resolve the topography-induced spatial solar radiation variability. Spatial mapping of potential solar radiation and actual solar radiation has been demonstrated in a small catchment in Southern Germany, with a spatial difference up to 30% in winter and 5% in summer. This may lead to a significant difference for the energy-limited hydrological processes, such as snowmelt, and evapotranspiration.     

水文系统不确定性分析方法及应用研究进展

水文系统是一个复杂的系统,包含了很多不确定性因素,增加了精确模拟和预测水文过程的困难。为了提高计算结果的可靠性,水文系统的不确定性分析已成为当前研究的热点。本文对水文系统不确定性分析方法及应用研究进展进行了分类综述,介绍了它们的数学原理、操作程序和应用现状,并对值得进一步研究的问题进行了展望,指出加强水文过程机理研究、在水文循环过程更多环节上拓宽不确定性研究、以及将多种不确定性分析方法进行综合是未来的研究趋势。     

Reconstructing past precipitation from lake levels and inverse modelling for Andean Lake La Cocha

Knowledge of paleoclimates and past climate change is important to put recent and future climate change in perspective. In the absence of well-developed methodology to reconstruct paleoprecipitation the majority of climate reconstructions focus on temperature, whereas precipitation is an equally important climate parameter. This paper explores the possibility of inferring paleoprecipitation from lake-level records by inverse hydrological modelling. Pollen spectra of a lacustrine sediment core were used to infer changes in past temperatures and lake levels during the past 14,000 years. A hydrological model that calculates lake levels using meteorological parameters and a digital terrain model were developed for the catchment area of Lake La Cocha. After calibration the model accurately simulated modern lake levels. A sensitivity analysis shows that the model results are most sensitive to temperature and precipitation. This hydrological model was subsequently used to estimate mean annual precipitation needed to reproduce the pollen-based reconstructed lake levels (inverse modelling). The lake currently discharges through the permanent Guamués River, with a modelled mean annual discharge of 3.6 m³ s^?1. However, past lake levels and hydrological modelling results suggest that Lake La Cocha has been free of discharge during most of the Holocene, and after an intermittent phase only recently started discharging permanently. The uncertainty in the inferred precipitation during the discharge-free period is estimated at ~22 mm. Quasi stable lake levels seem to justify using equilibrium conditions when reconstructing precipitation. Early Holocene lake levels were ~10 m lower than modern values, implying that precipitation must have been 30–40 % less than today.     

流域多尺度土壤水分监测与模拟研究进展

土壤水分调控着陆地表层系统空间格局和过程,作为地表不同圈层中物质和能量输移转化的关键纽带和驱动力,连接着一系列的水文、生态、气候和地质学过程。论文首先介绍了流土壤水分静态特征(土壤含水量和基质势时空变化)在流域范围内不同空间尺度上监测方法的优缺点,包括直接手动监测、直接自动监测、地球物理探测和遥感监测等;同时介绍了其动态特征(土壤水分运动)监测方法(径流小区法、示踪剂法和地球物理探测)的局限性和模拟模型(动力波模型、水量平衡模型和水动力模型等)的关键参数和过程。在此基础上提出了：① 加强土壤水分监测尺度与方法的集成;② 消除土壤水分运动模型不确定性;③ 耦合土壤水分与碳氮输移循环过程等3个方面的研究展望和建议,从而为高时空分辨率和高精度的土壤水分数据获取,以及土壤水分运动与分布及其驱动下的碳氮排放过程、机理的揭示和模拟提供新的研究视角与思路。