Calibration of conceptual models for rainfall-runoff simulation

Abstract

Conceptual mathematical models are a useful tool for rainfallrunoff modelling of a basin. The calibration of such models has attracted the attention of a number of hydrologists since unique and optimal parameters are difficult to obtain. The calibration of a conceptual model is discussed through a simple conceptual model whose parameters are determined using a search technique. It is shown that the optimization algorithm converges to a global optimum even when the errors in the initial parameters are quite significant and the input environment is noisy.     

The simulation of far-field wavelets using frequency-domain air-gun array near-field wavelets

Air-gun arrays are used in marine-seismic exploration. Far-field wavelets in subsurface media represent the stacking of single air-gun ideal wavelets. We derived single air-gun ideal wavelets using near-field wavelets recorded from near-field geophones and then synthesized them into far-field wavelets. This is critical for processing wavelets in marine- seismic exploration. For this purpose, several algorithms are currently used to decompose and synthesize wavelets in the time domain. If the traveltime of single air-gun wavelets is not an integral multiple of the sampling interval, the complex and error-prone resampling of the seismic signals using the time-domain method is necessary. Based on the relation between the frequency-domain phase and the time-domain time delay, we propose a method that first transforms the real near-field wavelet to the frequency domain via Fourier transforms; then, it decomposes it and composes the wavelet spectrum in the frequency domain, and then back transforms it to the time domain. Thus, the resampling problem is avoided and single air-gun wavelets and far-field wavelets can be reliably derived. The effect of ghost reflections is also considered, while decomposing the wavelet and removing the ghost reflections. Modeling and real data processing were used to demonstrate the feasibility of the proposed method.     

Assessing spatially dependent errors in radar rainfall estimates for rainfall-runoff simulation

Weather radar been widely employed to measure precipitation and to predict flood risks. However, it is still not considered accurate enough because of radar errors. Most previous studies have focused primarily on removing errors from the radar data. Therefore, in the current study, we examined the effects of radar rainfall errors on rainfall-runoff simulation using the spatial error model (SEM). SEM was used to synthetically generate random or cross-correlated errors. A number of events were generated to investigate the effect of spatially dependent errors in radar rainfall estimates on runoff simulation. For runoff simulation, the Nam River basin in South Korea was used with the distributed rainfall-runoff model, Vflo?. The results indicated that spatially dependent errors caused much higher variations in peak discharge than independent random errors. To further investigate the effect of the magnitude of cross-correlation among radar errors, different magnitudes of spatial cross-correlations were employed during the rainfall-runoff simulation. The results demonstrated that a stronger correlation led to a higher variation in peak discharge up to the observed correlation structure while a correlation stronger than the observed case resulted in lower variability in peak discharge. We concluded that the error structure in radar rainfall estimates significantly affects predictions of the runoff peak. Therefore, efforts to not only remove the radar rainfall errors, but to also weaken the cross-correlation structure of the errors need to be taken to forecast flood events accurately.     

Development of a fuzzy logic-based rainfall-runoff model

Abstract

Rainfall-runoff models are used to describe the hydrological behaviour of a river catchment. Many different models exist to simulate the physical processes of the relationship between precipitation and runoff. Some of them are based on simple and easy-to-handle concepts, others on highly sophisticated physical and mathematical approaches that require extreme effort in data input and handling. Recently, mathematical methods using linguistic variables, rather than conventional numerical variables applied extensively in other disciplines, are encroaching in hydrological studies. Among these is the application of a fuzzy rule-based modelling. In this paper an attempt was made to develop fuzzy rule-based routines to simulate the different processes involved in the generation of runoff from precipitation. These routines were implemented within a conceptual, modular, and semi-distributed model-the HBV model. The investigation involved determining which modules of this model could be replaced by the new approach and the necessary input data were identified. A fuzzy rule-based routine was then developed for each of the modules selected, and application and validation of the model was done on a rainfall-runoff analysis of the Neckar River catchment, in southwest Germany.     

A real-time combination method for the outputs of different rainfall-runoff models

Abstract

Application of the concept of combining the estimated forecast output of different rainfall-runoff models to yield an overall combined estimated output in the context of real-time river flow forecasting is explored. A Real-Time Model Output Combination Method (RTMOCM) is developed, based on the structure of the Linear Transfer Function Model (LTFM) and utilizing the concept of the Weighted Average Method (WAM) for model output combination. A multiple-input single-output form of the LTFM is utilized in the RTMOCM. This form of the LTFM model uses synchronously the daily simulation-mode model-estimated discharge time series of the rainfall-runoff models selected for combination, its inherent updating structure being used for providing updated combined discharge forecasts. The RTMOCM is applied to the daily data of five catchments, using the simulation-mode estimated discharges of three selected rainfall-runoff models, comprising one conceptual model (Soil Moisture Accounting and Routing Procedure—SMAR) and two black-box models (Linear Perturbation Model—LPM and Linearly-Varying Variable Gain Factor Model—LVGFM). In order to get an indication of the accuracy of the updated combined discharge forecasts relative to the updated discharge forecasts of the individual models, the LTFM is also used for updating the simulation-mode discharge time series of each of the three individual models. The results reveal that the updated combined discharge forecasts provided by the RTMOCM, with parameters obtained by linear regression, can improve on the updated discharge forecasts of the individual rainfall-runoff models.     

Comparing performance of different loss methods in rainfall-runoff modeling

Water Resources - With respect to the effect of precipitation loss on runoff generation, different loss methods of Soil and Conservation Service (SCS), Green and Ampt (G.A.), Initial-Constant...     

The applicability of a parsimonious model for local and regional prediction of runoff

Abstract

The Hydrological Recursive Model (HRM), a conceptual rainfall-runoff model, was applied for local and regional simulation of hourly discharges in the transnational Alzette River basin (Luxembourg-France-Belgium). The model was calibrated for a range of various sub-basins with a view to analysing its ability to reproduce the variability of basin responses during flood generation. The regionalization of the model parameters was obtained by fitting simultaneously the runoff series of calibration sub-basins after their spatial discretization in lithological contrasting isochronal zones. The runoff simulations of the model agreed well with the recorded runoff series. Significant correlations with some basin characteristics and, noticeably, the permeability of geological formations, could be found for two of the four free model parameters. The goodness of fit for runoff predictions using the derived regional parameter set was generally satisfactory, particularly for the statistical characteristics of streamflow. A more physically-based modelling approach, or at least an explicit treatment of quick surface runoff, is expected to give better results for high peak discharge.     

A data-based regional scale autoregressive rainfall-runoff model: a study from the Odra River

This paper aims to compare the performances of multivariate autoregressive (MAR) techniques and univariate autoregressive (AR) methods applied to regional scale rainfall-runoff modelling. We focus on the case study from the upper and middle reaches of the Odra River with its main tributaries in SW Poland. The rivers drain both the mountains (the Sudetes) and the lowland (Nizina Śląska). The region is exposed to extreme hydrologic and meteorological events, especially rain-induced and snow-melt floods. For the analysis, four hydrologic and meteorological variables are chosen, i.e., discharge (17 locations), precipitation (7 locations), thickness of snow cover (7 locations) and groundwater level (1 location). The time period is November 1971–December 1981 and the temporal resolution of the time series is of 1 day. Both MAR and AR models of the same orders are fitted to various subsets of the data and subsequently forecasts of discharge are derived. In order to evaluate the predictions the stepwise procedure is applied to make the validation independent of the specific sample path of the stochastic process. It is shown that the model forecasts peak discharges even 2–4 days in advance in the case of both rain-induced and snow-melt peak flows. Furthermore, the accuracy of discharge predictions increases if one analyses the combined data on discharge, precipitation, snow cover, and groundwater level instead of the pure discharge multivariate time series. MAR-based discharge forecasts based on multivariate data on discharges are more accurate than AR-based univariate predictions for a year with a flood, however, this relation is reverse in the case of the free-of-flooding year. In contrast, independently of the occurrence of floods within a year, MAR-based discharge forecasts based on discharges, precipitation, snow cover, and groundwater level are more precise than AR-based predictions.     

地震动加速度过程的四阶基数B—样条小波模拟

应用四阶基数B-样条小波来模拟地震动加速度过程，将小波分析引入了地震动加速度过程的研究。     

蒸散发时间尺度转换在日降雨径流过程模拟中的应用

针对目前研究蒸散发时间尺度转换方面的不足,构建了月蒸散发时间尺度转换模型,对淮河史灌河流域黄泥庄小流域1982-1987年月蒸散发能力进行逐栅格解集,并与改进后的AFFDEF分布式水文模型耦合进行日径流过程模拟.结果显示:解集产生的日蒸散发能力随时间在平均值附近波动变化,能很好地体现日蒸发量的时间变异特点;模拟的日径流过程的精度较高,平均Nash效率系数在80%以上,径流深相对误差都在10%以内,平均泊松相关系数为0.912,模拟流量过程曲线与实测值匹配的较好;经与采用平均解集模式的模拟结果对比发现,耦合蒸散发时间尺度转换模型后的模拟精度与前者大体相当,部分指标略优于前者.蒸散发时间尺度转换模型解集产生的日蒸散发量序列能够反映日蒸发量的时间变异特点,更能满足区域日降雨径流过程模拟的需要,可为解决资料匮乏区域水文模拟提供一个新途径.     

不同小波基下的结构位移反应动力可靠性分析

本文从三种不同小波即：修正的Meyer小波，littlewood-Paley小波，谐波小波的基本概念出发，得出这三种小波基下的地震输入瞬时功率谱，并求出在地震作用下各自的结构位移反应瞬时功率谱，同时定量给出了在这三种小波基下的自由度体系结构位移反应的动力可靠度时程。     

Application of a rainfall-runoff model to three catchments in Iraq

Abstract

The capability of the Surface inFiltration Baseflow (SFB) conceptual rainfall-runoff model to simulate streamflow for three catchments selected from northern Iraq is investigated. These catchments differ in their climatic regimes and physical characteristics. Three versions of the model were tested: the original three-parameter model (SFB), the modified five-parameter model (SFB-5), and the modified six-parameter model (SFB-6). The available daily precipitation, potential evapotranspiration and runoff data were used in conjunction with a simulated annealing (SA) optimization technique to calibrate the various versions of the SFB model. A simple sensitivity analysis was then carried out to determine the relative importance of the model parameters. The study indicated that use of the original three parameter model was not adequate to simulate monthly streamflow in the selected catchments. The modified version (SFB-5) provided better runoff simulation than the original SFB model; overall a 19% increase was observed in the coefficient of determination (R²) between simulated and observed monthly runoff. The SFB-5 model performed with varying degrees of success among the catchments. The model performance in the validation stage was reasonable and comparable to that of the calibration stage. The sensitivity analysis of the SFB model for arid catchments revealed that the baseflow parameter (B) was the most sensitive one, while the S and F parameters were less sensitive than the B parameter.     

Application of wavelets to analysis and simulation of earthquake motions

A method of applying wavelet transform to earthquake motion analysis is developed from the viewpoint of energy input structures, in which relationships between wavelet coefficients and energy input, namely energy principles in wavelet analysis are derived. By using the principles, time–frequency characteristics of the 1995 Hyogoken-Nanbu earthquake ground motions are analysed and time histories of energy input for various ranges of frequencies and epicentral distances are identified. Furthermore, a technique to simulate earthquake ground accelerations by wavelet inverse transform is developed on the condition that target time-frequency characteristics are specified. Structural responses to the simulated accelerations are compared with the target time–frequency characteristics, which shows satisfactory correlations between wavelet coefficients and energy responses in both time and frequency domains. Copyright © 1999 John Wiley & Sons, Ltd.     

一种ARMA模型地震子波提取方法研究

在地震子波因果、混合相位的假设下,本文突破突破滑动平均(MA)型假设的地震子波提取技术,提出一种阶数吝啬的自回归滑动平均(ARMA)模型对地震子波进行参数化准确建模的方法.针对地震子波ARMA模型定阶困难,超定阶容易造成计算量大、运算速度慢,欠定阶不能满足精确子波的要求,本文采用基于自相关函数的奇异值分解(SVD)法确定AR模型阶数,同时将信息量准则法与高阶累积量法相结合,提出了一种新的MA模型定阶法.数值仿真和实际地震数据处理结果表明,本文所用方法可以有效地压制加性高斯色噪声,信息量准则法可有效提高MA定阶的准确率,在保证子波精度的同时尽可能降低模型阶数,实现运算高效率.     

A numerical model for simulation of fluid mud with different rheological behaviors

In this paper, a three-dimensional isopycnal approach is presented to simulate the dynamics of fluid mud covering the formation, development, transport, and disappearance of fluid mud. The basic assumption is the assignment of the fluid’s density as the indicating parameter for the rheological behavior. Considering stable stratification, as is usually the case for fluid mud, layers of constant density discretize the vertical domain. The non-Newtonian dynamics of fluid mud is simulated by solving the Cauchy equations for general continuum dynamics. Instead of using a turbulent viscosity approach, the viscosity is allowed to vary according to the rheological behavior of mud suspensions. This apparent viscosity can be determined for different rheological formulations in dependence of the volume solid fraction and the shear rate. An existing three-dimensional isopycnal hydrodynamic model was extended for vertical mass transport processes and was applied on a schematic system with hindered settling. For including the rheological behavior of fluid mud, the Worrall–Tuliani approach was parameterized and implemented. The resulting flow behavior is shown on a model application of fluid mud layers moving down an inclined plane. With these changes, it is demonstrated that the isopycnal model is capable of simulating fluid mud dynamics.     

Uncertainty-based multi-criteria calibration of rainfall-runoff models: a comparative study

This study compares formal Bayesian inference to the informal generalized likelihood uncertainty estimation (GLUE) approach for uncertainty-based calibration of rainfall-runoff models in a multi-criteria context. Bayesian inference is accomplished through Markov Chain Monte Carlo (MCMC) sampling based on an auto-regressive multi-criteria likelihood formulation. Non-converged MCMC sampling is also considered as an alternative method. These methods are compared along multiple comparative measures calculated over the calibration and validation periods of two case studies. Results demonstrate that there can be considerable differences in hydrograph prediction intervals generated by formal and informal strategies for uncertainty-based multi-criteria calibration. Also, the formal approach generates definitely preferable validation period results compared to GLUE (i.e., tighter prediction intervals that show higher reliability) considering identical computational budgets. Moreover, non-converged MCMC (based on the standard Gelman–Rubin metric) performance is reasonably consistent with those given by a formal and fully-converged Bayesian approach even though fully-converged results requires significantly larger number of samples (model evaluations) for the two case studies. Therefore, research to define alternative and more practical convergence criteria for MCMC applications to computationally intensive hydrologic models may be warranted.     

Indoor imitation experimental study on driving factors of rainfall-runoff process

The driving actions are varied during the rain-fall-runoff process in a catchment. The impacts on therunoff process, caused by human activities or climatechange, can be attributed to two aspects: the charac-teristics of rainfall process and ground pad changes.To clarify their impacts on hydrological cycle is thefoundation of mechanism research of scientific hy-drology. So far, all of the research results, domestic andabroad, indicate that the advances on the understand-ing of hydrologica…     

不同仪器烈度算法在四川地区 历次地震中的比较应用

强震观测资料包括强震动时程记录资料和宏观震害调查资料两大类, 前者是定量的微观数据, 后者则是定性的宏观指标. 本文明晰给出了微观仪器烈度与宏观仪器烈度、 微观考察烈度与宏观考察烈度的概念, 并在此基础上提出了只有在宏观仪器烈度与宏观考察烈度之间进行比较才具有实质性的意义;同时对国内外常见的仪器烈度算法进行了比较性研究, 得出了袁一凡仪器烈度算法可靠性更高的结论;最后以四川地区历年来重要震例的强震动记录为依据, 对修正的袁一凡仪器烈度算法的可靠性进行了比较应用. 结果表明, 对袁一凡仪器烈度算法修正与扩展的应用是可行的, 同时也验证了将微观仪器烈度与宏观考察烈度直接进行比较会存在较大的差距.      

Representation of canopy snow interception,unloading and melt in a parsimonious snowmelt model

Recent improvements in the Utah Energy Balance (UEB) snowmelt model are focused on snow–vegetation–atmosphere interactions to understand how different types of vegetation affect snow processes in the mountains of Western USA. This work presents field work carried out in the Rocky Mountains of Northern Utah to evaluate new UEB model algorithms that represent the processes of canopy snow interception, sublimation, mass unloading and melt. Four years' continuous field observations showed generally smaller accumulations of snow beneath the forest canopies in comparison with open (sage and grass) areas, a difference that is attributed to interception and subsequent sublimation and redistribution of intercepted snow by wind, much of it into surrounding open areas. Accumulations beneath the denser forest (conifer) canopies were found to be less than the accumulation beneath the less dense forest (deciduous) canopies. The model was able to represent the accumulation of snow water equivalent in the open and beneath the deciduous forest quite well but without accounting for redistribution tended to overestimate the snow water equivalent beneath the conifer forest. Evidence of redistribution of the intercepted snow from the dense forest (i.e. conifer forest) to the adjacent area was inferred from observations. Including a simple representation of redistribution in the model gave satisfactory prediction of snow water equivalent beneath the coniferous forest. The simulated values of interception, sublimation and unloading were also compared with previous studies and found in agreement. Copyright © 2013 John Wiley & Sons, Ltd.