A semi‐distributed parallel‐type linear reservoir rainfall‐runoff model and its application in Taiwan

The main purpose of this paper is to introduce a semi‐distributed parallel surface rainfall‐runoff conceptual model. In this paper, a general solution of the instantaneous unit hydrograph (IUH) has been derived successfully for N linearly connected reservoirs, each having a different storage constant. The solution is a function of geomorphologic parameters, meteorologic factors and roughness coefficients. The model also takes into account the hydrologic response which is influenced by outflow downstream of a reservoir. For calibration, the shuffled complex evolution (SCE) algorithm is used to search for the global optimal parameters of the model. Because of the parallel structure, the mean roughness parameter of the channel becomes a “conceptual” parameter without a real physical meaning. To evaluate the adaptability of the model adopted, three watersheds around the city of Taipei in Taiwan were chosen to test the effectiveness of the model. The study provides an appropriate rainfall‐runoff model for planning flood mitigation in Taiwan. Copyright © 1999 John Wiley & Sons, Ltd.     

SCE-UA方法在新安江模型参数优化中的应用

以前在使用新安江模型时人们遇到的最大困难可归因于缺乏有效的参数全局优化的数学方法,事实上对于一个缺乏经验的人来说,模型参数的人工试错计算的过程是一个相当不容易的过程,并且耗时颇多,为此,近些年来研究者们正在探索把概念性水文模型中的专家经验与自动优化计算相结合的方法或者数学优化中的全局优化方法,如SEC-UA方法,本文首先简述新安江模型,而后采用3个大小和气候条件各不相同的流域对SCE-UA算法就在新安江模型计算的参数优化进行了研究,研究结果表明,SCE-UA算法用来进行新安江模型的参数优化所取得的效果是好的,从率定和检验的结果来看,SCE-UA算法可以使得率定的新安江模型的参数达到全局最优并且从概念上也合理。     

Improvement of SWAT2000 modelling to assess the impact of dams and sluices on streamflow in the Huai River basin of China

Hydrological simulation and assessment in a dam–sluice regulated river basin are a complex and challenging issue. In this article, an improved SWAT2000 modelling system was developed that incorporated the Shuffled complex evolution (SCE‐UA) optimization algorithm and the multi‐site and multi‐objective calibration strategy. The implication of multi‐objective is different for different types of outlets, i.e. streamflow for an ordinary outlet, inflow for a sluice, and water storage for a reservoir. Model parameters were redefined to improve model simulations. The surface runoff lag time (SURLAG) was extended as a spatially distributed parameter, and a correction coefficient was introduced to modify the saturated hydraulic conductivity. The modelling system was then applied to the Huai River basin of China under various climatic conditions, including a very dry year (1999), a dry year (1981), an average year (1971), and wet year (1991). In all, 26 dams and 35 sluices were considered, among which about 20 dams/sluices were used for model calibration. The impact assessment primarily focused on the very dry year (1999). The results indicated that the released water from large reservoirs was blocked in the river channels by sluices located downstream. In the very dry year, the dam–sluice operations could result in an increase of the runoff volume during the non‐flood season and a decrease in runoff during the flood season, but the changing magnitude during the non‐flood season was much greater. An important conclusion of this case study is that the sluices in the Sha‐Yin branch located in the north region and the dams in the southern mountainous region above the Wangjiaba Hydrological Station have played the most significant role in regulating the streamflow of the entire river basin. The methods addressed in this article can simulate hydrological regime in the river basins regulated by dams and sluices under different climatic conditions at the whole‐watershed scale. Copyright © 2010 John Wiley & Sons, Ltd.     

An efficiency-improved genetic algorithm and its application on multimodal functions and a 2D common reflection surface stacking problem

Although Genetic Algorithms have found many successful applications in the field of exploration geophysics, the convergence speed remains a big challenge as Genetic Algorithms usually require a huge amount of fitness function evaluations. In this paper, we propose an efficiency-improved Genetic Algorithm, which has both a good global search capability and a good local search capability, and is also capable of robustly handling the premature convergence challenge commonly seen in linear and directed non-linear optimization methods. In our new genetic algorithm, the global search capability is performed via a modified island model, while the local search capability is provided by a novel self-adaptive differential evolution fine tuning scheme. Premature convergence is dealt with via a local exhaustive search method. We first demonstrate the much improved convergence speed of this efficiency-improved Genetic Algorithm over that of our previously proposed advanced Genetic Algorithm on several multimodal functions. We further demonstrate the effectiveness of our efficiency-improved Genetic Algorithm by applying it to a two-dimensional common reflection surface stacking problem, which is a highly nonlinear geophysical optimization problem, to obtain very encouraging results.     

Enhancing gradient-based parameter estimation with an evolutionary approach

Traditionally, the calibration of groundwater models has depended on gradient-based local optimization methods. These methods provide a reasonable degree of success only when the objective function is smooth, second-order differentiable, and satisfies the Lipschitz's condition. For complicated and highly nonlinear objective functions it is almost impractical to satisfy these conditions simultaneously. Research in the calibration of conceptual rainfall-runoff models, has shown that global optimization methods are more successful in locating the global optimum in the region of multiple local optima. In this study, a global optimization technique, known as shuffle complex evolution (SCE), is coupled to the gradient-based Lavenberg–Marquardt algorithm (GBLM). The resultant hybrid global optimization algorithm (SCEGB) is then deployed in parallel testing with SCE and GBLM to solve several inverse problems where parameters of a nonlinear numerical groundwater flow model are estimated. Using perfect (i.e. noise-free) observation data, it is shown SCEGB and SCE are successful at identifying the global optimum and predicting all model parameters; whereas, the commonly applied GBLM fails to identify the optimum. In subsequent inverse simulations using observation data corrupted with noise, SCEGB and SCE again outperform GBLM by consistently producing more accurate parameter estimates. Finally, in all simulations the hybrid SCEGB is seen to be equally effective as SCE but computationally more efficient.     

Differential evolution with subpopulations for high‐dimensional seismic inversion

Seismic inversion has drawn the attention of researchers due to its capability of building an accurate earth model. Such a model will need to be discretised finely, and the dimensions of the inversion problem will be very high. In this paper, we propose an efficient differential evolution algorithm and apply it to high‐dimensional seismic inversion. Our method takes into account the differences among individuals, which are disregarded in conventional differential evolution methods, resulting to a better balance between exploration and exploitation. We divide the entire population into three subpopulations and propose a novel mutation strategy with two phases. Furthermore, we optimise the crossover operator by applying the components having the best objective function values into the crossover operator. We embed this strategy into a cooperative coevolutionary differential evolution and propose a new differential evolution algorithm referred to as a differential evolution with subpopulations. Then, we apply our scheme to both synthetic and field data; the results of high‐dimensional seismic inversion have shown that the proposed differential evolution with subpopulations achieves faster convergence and a higher‐quality solution for seismic inversion.     

Comparison of genetic algorithms and shuffled complex evolution approach for calibrating distributed rainfall–runoff model

Three methods, Shuffled Complex Evolution (SCE), Simple Genetic Algorithm (SGA) and Micro‐Genetic Algorithm (µGA), are applied in parameter calibration of a grid‐based distributed rainfall–runoff model (GBDM) and compared by their performances. Ten and four historical storm events in the Yan‐Shui Creek catchment, Taiwan, provide the database for model calibration and verification, respectively. The study reveals that the SCE, SGA and µGA have close calibration results, and none of them are superior with respect to all the performance measures, i.e. the errors of time to peak, peak discharge and the total runoff volume, etc. The performances of the GBDM for the verification events are slightly worse than those in the calibration events, but still quite satisfactory. Among the three methods, the SCE seems to be more robust than the other two approaches because of the smallest influence of different initial random number seeds on calibrated model parameters, and has the best performance of verification with a relatively small number of calibration events. Copyright © 2009 John Wiley & Sons, Ltd.     

On the estimation of antecedent wetness conditions in rainfall–runoff modelling

The analysis of the physical processes involved in a conceptual model of soil water content balance is addressed with the objective of its application as a component of rainfall–runoff modelling. The model uses routinely measured meteorological variables (rainfall and air temperature) and incorporates a limited number of significant parameters. Its performance in estimating the soil moisture temporal pattern was tested through local measurements of volumetric water content carried out continuously on an experimental plot located in central Italy. The analysis was carried out for different periods in order to test both the representation of infiltration at the short time‐scale and drainage and evapotranspiration processes at the long time‐scale. A robust conceptual model was identified that incorporated the Green–Ampt approach for infiltration and a gravity‐driven approximation for drainage. A sensitivity analysis was performed for the selected model to assess the model robustness and to identify the more significant parameters involved in the principal processes that control the soil moisture temporal pattern. The usefulness of the selected model was tested for the estimation of the initial wetness conditions for rainfall–runoff modelling at the catchment scale. Specifically, the runoff characteristics (runoff depth and peak discharge) were found to be dependent on the pre‐event surface soil moisture. Both observed values and those estimated by the model gave good results. On the contrary, with the antecedent wetness conditions furnished by two versions of the antecedent precipitation index (API), large errors were obtained. Copyright © 2007 John Wiley & Sons, Ltd.     

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.     

An approach for evaluating the hydrological effects of urbanization and its application

This study focuses mainly on observing urban development in Taiwan's Wu‐Tu watershed from the perspective of urban hydrological theory. An approach is proposed for developing a method for incorporating available meteorological data to define the degree of change in a runoff hydrograph for urbanizing basins. The mean rainfall was estimated using the Kriging method. For calibration, two methods of calculating the effective rainfall (the Φ‐index method and the non‐linear‐programming (NLP) method) were used as model inputs, and the optimal global parameters of the linear reservoir model were then obtained from the shuffled complex evolution (SCE) algorithm. Twenty‐six (1966–1991) and eight (1994–1997) rainfall–runoff events were used for calibration and verification, respectively. The NLP method yielded better results than the Φ‐index method, especially for multipeak rainfall–runoff events. The regression equation determined the relationship between the parameters of the model and impervious areas. A comparison based on the results of the instantaneous unit hydrograph of the study area revealed that three decades of urbanization had increased the peak flow by 27%, and the time to peak was decreased by 4 h. The study simply describes the results of the impact of imperviousness on hydrological modelling. Copyright © 2002 John Wiley & Sons, Ltd.     

Topographic analysis for the prairie pothole region of Western Canada

The unique topography of the pothole region of the North American prairies creates challenges for properly determining basin contributing area. Numerous depressions or potholes within the landscape impound runoff. However, potholes can ‘fill‐spill’ resulting in surface water connections between the potholes. Surface water connectivity between potholes ultimately influences basin contributing area. Currently, automated methods, such as landscape analysis tools, treat depressions in the landscape as artifacts and simply fill the depressions to delineate a drainage basin. Using this method to calculate contributing area assumes that all surface storage has been satisfied (threshold) and the drainage basin will contribute 100% of its area for all runoff events. However, most runoff events in the prairie pothole region are pre‐threshold events that contribute only a portion of surface runoff to the outlet. These pre‐threshold events have surface storage that varies because of antecedent water levels and have a variable or dynamic potential to store further runoff in the basin. Government agencies have developed methodologies for determining pre‐threshold contributing areas, but these methodologies do not incorporate current technologies and, as a result, have limitations. We propose an automated method for determining contributing area that incorporates the fill‐spill of prairie potholes. The algorithm, which uses the D‐8 drainage direction method, automates a methodology for identifying and quantifying runoff contributing area. Any algorithm that determines pre‐threshold contributing area, must allow the DEM to be filled in an incremental manner. This will simulate increasing pond levels, and the resulting decrease in available storage in the basin, in response to runoff events. The SPILL algorithm is an iterative solution that increases the magnitude of input runoff events and records the decreasing change in available surface storage and the increase in contributing area until the storage threshold is reached and the contributing area reaches 100%. Through application of the algorithm on prairie pothole region basins, we test proposed conceptual curves that describe a hypothesized non‐linear relationship between decreasing potential storage in the landscape and contributing area. Results indicate that the proposed conceptual curves represent the relationship between potential surface storage and contributing area in the test basins very well. Copyright © 2012 John Wiley & Sons, Ltd.     

2D多尺度混合优化地球物理反演方法及其应用(英文)

局部优化和全局优化方法广泛应用到地球物理反演,但是两者各有其优缺点。将两类方法结合起来可以取长补短。将退火遗传算法（SAGA）和单纯形算法相结合,得到了一种高效、健全的2D非线性混合地震走时反演方法。首先,利用SAGA进行大范围的全局搜索,然后由单纯形方法进行快速局部搜索。为了降低层析成像的多解性,我们采用了多尺度逐次逼近的技巧。把速度场划分为不同的空间尺度,定义网格节点上的速度作为待反演参数,采用双三次样条函数模型参数化,正问题采用有限差分走时计算方法,反问题采用多尺度混合反演方法。一个低速度异常体的数值模拟试验和抗走时扰动试验表明该方法是有效和健全的。我们将该方法应用到青藏高原东北缘阿尼玛卿rlet,Meyer,Marr,缝合带东段上部地壳速度结构研究中。数字模型试验和实际资料的应用表明了方法的有效性和健全性。     

Non‐linear prestack seismic inversion with global optimization using an edge‐preserving smoothing filter

Estimating elastic parameters from prestack seismic data remains a subject of interest for the exploration and development of hydrocarbon reservoirs. In geophysical inverse problems, data and models are in general non‐linearly related. Linearized inversion methods often have the disadvantage of strong dependence on the initial model. When the initial model is far from the global minimum, inversion iteration is likely to converge to the local minimum. This problem can be avoided by using global optimization methods. In this paper, we implemented and tested a prestack seismic inversion scheme based on a quantum‐behaved particle swarm optimization (QPSO) algorithm aided by an edge‐preserving smoothing ( EPS) operator. We applied the algorithm to estimate elastic parameters from prestack seismic data. Its performance on both synthetic data and real seismic data indicates that QPSO optimization with the EPS operator yields an accurate solution.     

Enhancements to,and forthcoming developments in the Interactive Multisensor Snow and Ice Mapping System (IMS)

The National Oceanic and Atmospheric Administration's National Environmental Satellite Data and Information Service (NOAA/NESDIS) Interactive Multisensor Snow and Ice Mapping System (IMS) has undergone substantial changes since its inception in 1997. These changes include the data sources used to generate the product, methodology of product creation, and even changes in the output. Among the most notable of the past upgrades to the IMS are a 4‐km resolution grid output, ingest of an automated snow detection algorithm, expansion to a global extent, and a static Digital Elevation Model for mapping based on elevation. Further developments to this dynamic system will continue as NOAA strives to improve snow parameterization for weather forecast modeling. Several future short‐term enhancements will be evaluated for possible transition to operations before the Northern Hemisphere winter of 2006–2007. Current and historical data will be adopted to a geographic information systems (GIS) format before 2007, as well. Longer‐term enhancements are also planned to account for new snow data sources, mapping methodologies and user requirements. These modifications are being made with care to preserve the integrity of the long‐standing satellite‐derived snow record that is vital to global change detection. Published in 2007 by John Wiley & Sons, Ltd.     

Precipitation‐runoff processes in Shimen hillslope micro‐catchment of Taihang Mountain,north China

Precipitation runoff is a critical hillslope hydrological process for downslope streamflow and piedmont/floodplain recharge. Shimen hillslope micro‐catchment is strategically located in the central foothill region of Taihang Mountains, where runoff is crucial for water availability in the piedmont corridors and floodplains of north China. This study analyzes precipitation‐runoff processes in the Shimen hillslope micro‐catchment for 2006–2008 using locally designed runoff collection systems. The study shows that slope length is a critical factor, next only to precipitation, in terms of runoff yield. Regression analysis also shows that runoff is related positively to precipitation, and negatively to slope length. Soil mantle in the study area is generally thin and is therefore not as critical a runoff factor as slope length. The study shows a significant difference between overland and subsurface runoff. However, that between the 0–10 and 10–20 cm subsurfaces is insignificant. Runoff hardly occurs under light rains (<10 mm), but is clearly noticeable under moderate‐to‐rainstorm events. In the hillslope catchment, vertical infiltration (accounting for 42–84% of the precipitation) dominates runoff processes in subsurface soils and weathered granite gneiss bedrock. A weak lateral flow (at even the soil/bedrock interface) and the generally small runoff suggest strong infiltration loss via deep percolation. This is critical for groundwater recharge in the downslope piedmont corridors and floodplains. This may enhance water availability, ease water shortage, avert further environmental degradation, and reduce the risk of drought/flood in the event of extreme weather conditions in the catchment and the wider north China Plain. Copyright © 2011 John Wiley & Sons, Ltd.     

Assessment of the effectiveness of a multi-site stochastic weather generator on hydrological modelling in the Red Deer River watershed,Canada

ABSTRACT

To improve the convergence of multiple-site weather generators (SWGs) based on the brute force algorithm (MBFA), a genetic algorithm (GA) is proposed to search the overall optimal correlation matrix. Precipitation series from weather generators are used as input to the hydrological model, the soil and water assessment tool (SWAT), to generate runoff over the Red Deer watershed, Canada for further runoff analysis. The results indicate that the SWAT model using SWG-generated data accurately represents the mean monthly streamflow for most of the months. The multi-site generators were capable of better representing the monthly streamflow variability, which was notably underestimated by the single-site version. In terms of extreme flows, the proposed method reproduced the observed extreme flow with smaller bias than MBFA, while the single-site generator significantly underestimated the annual maximum flows due to its poor capability in addressing partial precipitation correlations.     

Optimal Decision Making Algorithm for Managed Aquifer Recharge and Recovery Operation Using Near Real‐Time Data: Benchtop Scale Laboratory Demonstration

Aquifers show troubling signs of irreversible depletion as climate change, population growth, and urbanization lead to reduced natural recharge rates and overuse. One strategy to sustain the groundwater supply is to recharge aquifers artificially with reclaimed water or stormwater via managed aquifer recharge and recovery (MAR) systems. Unfortunately, MAR systems remain wrought with operational challenges related to the quality and quantity of recharged and recovered water stemming from a lack of data‐driven, real‐time control. This paper presents a laboratory scale proof‐of‐concept study that demonstrates the capability of a real‐time, simulation‐based control optimization algorithm to ease the operational challenges of MAR systems. Central to the algorithm is a model that simulates water flow and transport of dissolved chemical constituents in the aquifer. The algorithm compensates for model parameter uncertainty by continually collecting data from a network of sensors embedded within the aquifer. At regular intervals the sensor data is fed into an inversion algorithm, which calibrates the uncertain parameters and generates the initial conditions required to model the system behavior. The calibrated model is then incorporated into a genetic algorithm that executes simulations and determines the best management action, for example, the optimal pumping policy for current aquifer management goals. Experiments to calibrate and validate the simulation‐optimization algorithm were conducted in a small two‐dimensional synthetic aquifer under both homogeneous and heterogeneous packing configurations. Results from initial experiments validated the feasibility of the approach and suggested that our system could improve the operation of full‐scale MAR facilities.     

Performance of a conceptual and physically based model in simulating the response of a semi‐urbanized watershed in San Antonio,Texas

The need for accurate hydrologic analysis and rainfall–runoff modelling tools has been rapidly increasing because of the growing complexity of operational hydrologic and hydraulic problems associated with population growth, rapid urbanization and expansion of agricultural activities. Given the recent advances in remote sensing of physiographic features and the availability of near real‐time precipitation products, rainfall–runoff models are expected to predict runoff more accurately. In this study, we compare the performance and implementation requirements of two rainfall–runoff models for a semi‐urbanized watershed. One is a semi‐distributed conceptual model, the Hydrologic Engineering Center‐Hydrologic Modelling System (HEC‐HMS). The other is a physically based, distributed‐parameter hydrologic model, the Gridded Surface Subsurface Hydrologic Analysis (GSSHA). Four flood events that took place on the Leon Creek watershed, a sub‐watershed of the San Antonio River basin in Texas, were used in this study. The two models were driven by the Multisensor Precipitation Estimator radar products. One event (in 2007) was used for HEC‐HMS and GSSHA calibrations. Two events (in 2004 and 2007) were used for further calibration of HEC‐HMS. Three events (in 2002, 2004 and 2010) were used for model validation. In general, the physically based, distributed‐parameter model performed better than the conceptual model and required less calibration. The two models were prepared with the same minimum required input data, and the effort required to build the two models did not differ substantially. Copyright © 2012 John Wiley & Sons, Ltd.     

Steered migration in hard rock environments

Hard rock seismic exploration normally has to deal with rather complex geological environments. These types of environments are usually characterized by a large number of local heterogeneity (e.g., faults, fracture zones, and steeply dipping interfaces). The seismic data from such environments often have a poor signal‐to‐noise ratio because of the complexity of hard rock geology. To be able to obtain reliable images of subsurface structures in such geological conditions, processing algorithms that are capable of handling seismic data with a low signal‐to‐noise ratio are required for a reflection seismic exploration. In this paper, we describe a modification of the 3D Kirchhoff post‐stack migration algorithm that utilizes coherency attributes obtained by the diffraction imaging algorithm in 3D to steer the main Kirchhoff summation. The application to a 3D synthetic model shows the stability of the presented steered migration to the presence of high level of the random noise. A test on the 3D seismic volume, acquired on a mine site located in Western Australia, reveals the capability of the approach to image steep and sharp objects such as fracture and fault zones and lateral heterogeneity.