Hydrologic simulation of clay‐settling areas in the phosphate mining district,Florida

Clay‐settling areas (CSAs) are one of the most conspicuous and development‐limiting landforms remaining after phosphate mining. Many questions are asked by the mining and regulatory communities with regard to the correct modelling (predictive) methods and assumptions that should be used to yield viable hydrologic post‐reclamation landforms within CSAs. Questions as to the correct methodology to use in modelling/predicting long‐term CSA hydrologic performance have historically been difficult to answer because the data and analysis to support popular hypotheses did not exist. The goal of this paper was to substantially improve the data, analysis and predictive methodology necessary to return CSAs to viable hydrologic units, and moreover, to develop better understanding of the hydrology of CSAs and their ability to support wetlands. The study site is located at the Fort Meade Mine in Polk County, Florida. In this paper, continuous model simulation and calibration of study site were conducted for the hydrologic model, Hydrological Simulation Program – FORTRAN, which was generally selected on the basis of its popularity in predicting the hydrologic behaviour of CSAs. The objective of this study was to simulate streamflow discharges and stage to estimate runoff response from these areas on the basis of the observed rainfall within the CSA. A set of global hydrologic parameters was selected and tested during the calibration by the parameter estimation software PEST. A comparison of the simulated and observed flow data indicates that the model calibration adequately reproduces the hydrologic response of the CSAs. The estimated parameters can be used as references for future application of the model. Copyright © 2012 John Wiley & Sons, Ltd.     

基于FEFLOW的采区放水实验数值模拟与模型评估

采区安全开采受底板徐灰水,奥灰水威胁,确定含水层的富水性和准确的水文地质参数对于评价采区安全开采,评价徐灰水疏水降压可行性,正确预计工作面涌水量均具有重要的意义。基于有限元剖分方法的FEFLOW软件能对地下水流向进行模拟．其内置的PEST能有效地对模型的参数最优化,达到精确求参,从而增加模型的可行性和与实地水文地质条件的拟合度。     

Modélisation directe et inverse de l'écoulement souterrain dans les milieux poreux

Résumé

Le présent article montre l'intérêt des simulations mathématiques dans la compréhension des aquifères complexes et hétérogènes. Le réservoir côtier du Maroc occidental est un exemple qui traduit une répartition spatiale des corps perméables et imperméables, d'où la nécessité d'approfondir la connaissance de son fonctionnement hydrogéologique en termes de modélisation numérique. Le modèle hydrodynamique proposé repose sur la résolution du problème direct et inverse. La simulation de l'écoulement (problème direct) en régime permanent a montré la persistance de grands écarts entre la piézométrie mesurée et calculée. Cette anomalie de calage est expliquée principalement par le caractère hétérogène et fissuré, incompatible avec la dérivation de l'équation de diffusivité qui présuppose un milieu continu et un régime laminaire plutôt que turbulent. Deux cartes principales ont été obtenues: (a) une carte des polygones de la conductivité hydraulique dont les valeurs varient entre 50 × 10^?4 et 80 × 10^?4 m/s; et (b) une carte des polygones de recharge avec des valeurs comprises entre 4.5 × 10^?9 et 5 × 10^?14 m/s. Le calage du modèle d'écoulement recherché dans la résolution du problème inverse consiste à identifier les paramètres de l'aquifère à partir de la piézométrie connue. Le code d'inversion PEST (Parameter ESTimation) a été utilisé pour créer des cartes montrant des polygones de la conductivité hydraulique et de la recharge avec des valeurs très similaires aux résultats du modèle conceptuel.     

ETWatch中的参数标定方法

使用遥感手段估算区域范围的蒸散量一直是热红外定量遥感的研究热点。ETWatch是用于流域蒸散遥感监测、针对遥感应用而设计的集成框架。方法集成了具有不同应用优势的遥感蒸散模型,并以Penman-Monteith方法为基础建立时间扩展方法,利用气象数据与晴好日的通量遥感估算结果,获得逐日连续的蒸散分布图。所生成的从流域级到地块级的数据产品能动态反映区域蒸散发的时空变化规律。为深入了解遥感蒸散量估算中的不确定因素,本文将其通量计算过程分为地表参数获取(以地表温度为主)、日净辐射、蒸发比等环节与地面数据进行对比和逐项的标定。并分别采用地表阻抗扩展法和蒸发比不变法进行了时间插补的对比研究。利用站点地面观测资料对蒸散遥感监测产品的验证表明,在全年内模型蒸发比结果与实测的时段平均蒸发比的相关系数可达到0.7左右,在更长的时间尺度上(月、季、年)平均百分比误差可以减小到10％以下。     

Improving the calibration strategy of the physically-based model WaSiM-ETH using critical events

Abstract

The use of a physically-based hydrological model for streamflow forecasting is limited by the complexity in the model structure and the data requirements for model calibration. The calibration of such models is a difficult task, and running a complex model for a single simulation can take up to several days, depending on the simulation period and model complexity. The information contained in a time series is not uniformly distributed. Therefore, if we can find the critical events that are important for identification of model parameters, we can facilitate the calibration process. The aim of this study is to test the applicability of the Identification of Critical Events (ICE) algorithm for physically-based models and to test whether ICE algorithm-based calibration depends on any optimization algorithm. The ICE algorithm, which uses the data depth function, was used herein to identify the critical events from a time series. Low depth in multivariate data is an unusual combination and this concept was used to identify the critical events on which the model was then calibrated. The concept is demonstrated by applying the physically-based hydrological model WaSiM-ETH on the Rems catchment, Germany. The model was calibrated on the whole available data, and on critical events selected by the ICE algorithm. In both calibration cases, three different optimization algorithms, shuffled complex evolution (SCE-UA), parameter estimation (PEST) and robust parameter estimation (ROPE), were used. It was found that, for all the optimization algorithms, calibration using only critical events gave very similar performance to that using the whole time series. Hence, the ICE algorithm-based calibration is suitable for physically-based models; it does not depend much on the kind of optimization algorithm. These findings may be useful for calibrating physically-based models on much fewer data.

Editor D. Koutsoyiannis; Associate editor A. Montanari

Citation Singh, S.K., Liang, J.Y., and Bárdossy, A., 2012. Improving calibration strategy of physically-based model WaSiM-ETH using critical events. Hydrological Sciences Journal, 57 (8), 1487–1505.     

目标函数权重对PEST-HSPF水文率定的影响研究

参数率定是水文模型构建与应用的重要基础。在多目标水文校准中,不同目标函数的权重设置直接影响校准的结果,如何确定不同目标函数的权重是水文校准的关键问题。选择典型半分布式水文模型HSPF(Hydrological Simulation Program-Fortran),基于PEST多目标校准模型,以牛栏江上游流域为研究对象,研究目标函数权重对HSPF水文模拟拟合优度的影响,为HSPF模型参数自动率定提供指导与借鉴。结果表明:(1)当PEST-HSPF水文校准的单目标函数权重(日流量、月流量、超流天数)上升时,模型的纳什系数和相对偏差呈现非线性变化特征,不规则波动幅度较大;(2)3个目标函数的权重在1~10量级内模型能够获得较高的预测能力和较低的误差,模型的纳什系数平均可达到0.8以上,相对偏差在10%以内;(3)超流量天数权重设置对模型的预测能力变化影响较大,日流量天数权重对相对偏差的波动影响较大,当超流天数的相对权重在1~1 000范围内变化时,模型纳什系数在0.02~0.86之间波动剧烈,当日流量相对权重值超过30时,相对偏差变化明显。     

Rainfall–runoff model parameter estimation and uncertainty evaluation on small plots

Four seasonal rainfall simulations in 2009 and 2010 were applied to a field containing 36 plots (0.75 × 2 m each), resulting in 144 runoff events. In all simulations, a constant rate of rainfall was applied then halted 60 min after initiation of runoff, with plot‐scale monitoring of runoff every 5 min during that period. Runoff was simulated with the Kinematic Runoff and Erosion/Simulator of Transport with Infiltration and Runoff (KINEROS2/STWIR) field‐scale model, whose hydrodynamics are based on the kinematic wave equation. Because of the non‐linear nature of the model and a highly parameterized model with respect to the available data, several approaches were investigated to upscale nine runoff‐related parameters from a series of small monitored plots to the field scale. Inverse modeling was performed using the model‐independent Parameter ESTimation (PEST) algorithm to individually calibrate the nine KINEROS2/STWIR parameters on 36 plots. The parameters were averaged, and bootstrapping was used to assess uncertainty of the parameters via estimation of confidence intervals (CI). A Monte Carlo simulation using the bootstrap results showed reasonable field‐scale representation of flow rates. Median values of calibrated parameters were within the 95% CI obtained with bootstrapping. The simulated results for the median values associated with the 90% CI flow rates produced similar trends as those exhibited with the observed data, suggesting that median values of the calibrated parameters from the PEST inverse modeling could be used to represent the field scale. Copyright © 2013 John Wiley & Sons, Ltd.     

The cost of uniqueness in groundwater model calibration

Calibration of a groundwater model requires that hydraulic properties be estimated throughout a model domain. This generally constitutes an underdetermined inverse problem, for which a solution can only be found when some kind of regularization device is included in the inversion process. Inclusion of regularization in the calibration process can be implicit, for example through the use of zones of constant parameter value, or explicit, for example through solution of a constrained minimization problem in which parameters are made to respect preferred values, or preferred relationships, to the degree necessary for a unique solution to be obtained.     

PEST在WetSpa分布式水文模型参数率定中的应用

分布式水文模型随着计算机、遥感和地理信息系统等信息技术的发展成为水文模拟的热点,但面临着参数过多难以率定的问题.PEST是独立于模型的非线性参数估计和不确定性分析的综合软件,能通过尽量少的模型运行次数估计参数.本文应用以ArcView3.2为操作平台的WetSpa分布式水文模型,结合人工试错法和PEST独立参数自动率定程序联合对WetSpa模型进行参数率定,对白盆珠水库流域1992～2001年日径流进行连续模拟研究,取得较好效果.     

应用并行PEST算法优化地下水模型参数

基于列文伯格-马夸尔特（Levenberg-Marquardt）算法的PEST参数优化程序具有寻优速度快、健壮性好的优点,在地下水模型参数优化研究中有许多成功的应用实例。但是,对于大尺度、高精度和高复杂性的大规模地下水模拟,使用PEST进行参数优化需要大量的计算时间,优化效率较低。本文应用OpenMP并行编程方法对PEST算法进行了并行化,使之可以在共享存储并行计算机上进行参数优化的并行计算。并将此方法应用于甘肃北山区域地下水模型的参数优化中,并行实验表明,使用并行化的PEST可以将地下水模型参数优化效率提高3.7倍。 