Similarity search and pattern discovery in hydrological time series data mining

The rapid development of data mining provides a new method for water resource management, hydrology and hydroinformatics research. In the paper, based on data mining theory and technology, we analyse hydrological daily discharge time series of the Shaligunlanke Station in the Tarim River Basin in China from the year 1961 to 2000. Firstly, according to the four monthly statistics, namely mean monthly discharge, monthly maximum discharge, monthly amplitude and monthly standard deviation, K‐mean clustering was used to segment the annual process of the daily discharge. The clustering result showed that the annual process of the daily discharge can be divided into five segments: snowmelt period I (April), snowmelt period II (May), rainfall period I (June–August), rainfall period II (September) and dry period (October–December and January–March). Secondly, dynamic time warping (DTW), which is a different distance metric method from the traditional Euclidian distance metric, was used to look for similarities in the discharge process. On the basis of the similarity matrix, the similar discharge processes can be mined in each period. Thirdly, agglomerative hierarchical clustering was used to cluster and discover the discharge patterns in terms of the autoregressive model. It was found that the discharge had a close relationship with the temperature and the precipitation, and the discharge processes were more similar under the same climatic condition. Our study shows that data mining is a feasible and efficient approach to discover the hidden information in the historical hydrological data and mining the implicative laws under the hydrological process. Copyright © 2010 John Wiley & Sons, Ltd.     

Including daily constraints in a monthly reservoir operation model for low-flow

In many real-world situations, operation of water resources systems are subject to constraints which are formulated on a daily basis. Since mathematical models (simulation or optimization models) are often developed on a monthly basis to avoid dimensionality problems and to reduce necessary computer time, some degree of approximation is necessary. Two examples are presented in order to show how this approximation can be done:

• •- a reservoir is operated for hydroelectric power production and low-flow augmentation is provided on a daily basis as a function of inflows (Lech River System in Germany)
• •- a reservoir is operated optimally for daily low-flow augmentation at a control gage downstream. The model includes also mandatory releases as constraints (Wupper River System in Germany).

In the first example the daily requirements are part of the constraints in the system, while in the second example the daily constraint concerns directly the objective function. Further, in the first case water can be saved and in the second case more water is needed as compared to calculations on a monthly basis.These examples are presented to show two solutions using envelope curves but other possibilities (i.e., regression analysis, constraints, coefficients) could be considered.     

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.     

A method for finding the optimal predictor indices for local wave climate conditions

In this study, a method to obtain local wave predictor indices that take into account the wave generation process is described and applied to several locations. The method is based on a statistical model that relates significant wave height with an atmospheric predictor, defined by sea level pressure fields. The predictor is composed of a local and a regional part, representing the sea and the swell wave components, respectively. The spatial domain of the predictor is determined using the Evaluation of Source and Travel-time of wave Energy reaching a Local Area (ESTELA) method. The regional component of the predictor includes the recent historical atmospheric conditions responsible for the swell wave component at the target point. The regional predictor component has a historical temporal coverage (n-days) different to the local predictor component (daily coverage). Principal component analysis is applied to the daily predictor in order to detect the dominant variability patterns and their temporal coefficients. Multivariate regression model, fitted at daily scale for different n-days of the regional predictor, determines the optimum historical coverage. The monthly wave predictor indices are selected applying a regression model using the monthly values of the principal components of the daily predictor, with the optimum temporal coverage for the regional predictor. The daily predictor can be used in wave climate projections, while the monthly predictor can help to understand wave climate variability or long-term coastal morphodynamic anomalies.     

Evaporation estimation models for Lake Eğirdir,Turkey

Lake E?irdir is located in the Lakes District in southwestern Turkey and it is the second largest freshwater resource lake. Evaporation is an important parameter in hydrological and meteorological practical studies. This study has three objectives: (1) to develop models for the estimation of daily evaporation using measured data from the automated GroWeather meteorological station located near Lake E?irdir; (2) to compare the evaporation models with the classical Penman approach; (3) to evaluate the potential of each model. The comparisons are based on daily and monthly available data from 2001 and 2002. The evaporation estimation models (EEMs) developed in this paper have lower mean absolute errors and higher coefficient of determination R² values than the Penman method. In order to evaluate the potential of the EEMs, daily evaporation values are calculated by the Priestley–Taylor, Brutsaert–Stricker, de Bruin, Makkink and Hamon methods. The EEMs are statistically indistinguishable from the classical methods on the basis of the parameters of mean, standard deviation, etc. In the evaluation of daily and monthly values, the relative error percentage for daily evaporation has lower values than for monthly evaporation. It can be seen that the EEMs help in calculating daily evaporation rather than monthly. Final evaluation and comparison indicate that there is a good agreement between the results of EEMs and the Penman approach than with the classical methods. Copyright © 2006 John Wiley & Sons, Ltd.     

Hydrological modelling of a small watershed using generated rainfall in the soil and water assessment tool model

An adequately tested soil and water assessment tool (SWAT) model was applied to the runoff and sediment yield of a small agricultural watershed in eastern India using generated rainfall. The capability of the model for generating rainfall was evaluated for a period of 18 years (1981–1998). The watershed and subwatershed boundaries, drainage networks, slope, soil series and texture maps were generated using a geographical information system (GIS). A supervised classification method was used for land‐use/cover classification from satellite imageries. Model simulated monthly rainfall for the period of 18 years was compared with observations. Simulated monthly rainfall, runoff and sediment yield values for the monsoon season of 8 years (1991–1998) were also compared with their observed values. In general monthly average rainfall predicted by the model was in close agreement with the observed monthly average values. Also, simulated monthly average values of surface runoff and sediment yield using generated rainfall compared well with observed values during the monsoon season of the years 1991–1998. Results of this study revealed that the SWAT model can generate monthly average rainfall satisfactorily and thereby can produce monthly average values of surface runoff and sediment yield close to the observed values. Therefore, it can be concluded that the SWAT model could be used for developing a multiple year management plan for the critical erosion prone areas of a small watershed. Copyright © 2004 John Wiley & Sons, Ltd.     

Stationarity is undead: Uncertainty dominates the distribution of extremes

The increasing effort to develop and apply nonstationary models in hydrologic frequency analyses under changing environmental conditions can be frustrated when the additional uncertainty related to the model complexity is accounted for along with the sampling uncertainty. In order to show the practical implications and possible problems of using nonstationary models and provide critical guidelines, in this study we review the main tools developed in this field (such as nonstationary distribution functions, return periods, and risk of failure) highlighting advantages and disadvantages. The discussion is supported by three case studies that revise three illustrative examples reported in the scientific and technical literature referring to the Little Sugar Creek (at Charlotte, North Carolina), Red River of the North (North Dakota/Minnesota), and the Assunpink Creek (at Trenton, New Jersey). The uncertainty of the results is assessed by complementing point estimates with confidence intervals (CIs) and emphasizing critical aspects such as the subjectivity affecting the choice of the models’ structure. Our results show that (1) nonstationary frequency analyses should not only be based on at-site time series but require additional information and detailed exploratory data analyses (EDA); (2) as nonstationary models imply that the time-varying model structure holds true for the entire future design life period, an appropriate modeling strategy requires that EDA identifies a well-defined deterministic mechanism leading the examined process; (3) when the model structure cannot be inferred in a deductive manner and nonstationary models are fitted by inductive inference, model structure introduces an additional source of uncertainty so that the resulting nonstationary models can provide no practical enhancement of the credibility and accuracy of the predicted extreme quantiles, whereas possible model misspecification can easily lead to physically inconsistent results; (4) when the model structure is uncertain, stationary models and a suitable assessment of the uncertainty accounting for possible temporal persistence should be retained as more theoretically coherent and reliable options for practical applications in real-world design and management problems; (5) a clear understanding of the actual probabilistic meaning of stationary and nonstationary return periods and risk of failure is required for a correct risk assessment and communication.     

Predicting water yield from a mountain ash forest catchment using a terrain analysis based catchment model

The structure, capabilities and performance of a distributed parameter hydrologic model are described. The model, called Topog-Yield, permits a transient analysis of unsaturated-saturated flow and evapotranspiration to be performed across complex terrain using a one-dimensional framework. It is applied to a 0.32 km² mountain ash (Eucalyptus regnans) forest catchment in the central Victorian highlands, Australia. We compare observed and predicted daily runoff values for the site over a continuous 12 year period (1972–1983) when the catchment vegetation was in an undisturbed climax condition. All input parameter values were based on published or measured data, although some variables were adjusted within the range of known variability to yield a best fit between predicted and observed streamflow in the first year of simulation, 1972. Although the model was ‘calibrated’ for the first year, all variables other than climatic inputs remained fixed for the following 11 years. Modelled and observed daily runoff values compare well throughout the period of simulation, despite a wide range of climatic conditions. When modelled daily runoff values were lumped on a monthly basis, the model was able to explain 87% of the variation in observed monthly streamflows over the 12 year period. Modelled annual runoff was within ±5% of observed values for 6 of the 12 years of record. Annual runoff prediction errors exceeded ±10% of observed values in only 2 of the 12 years. By the end of the 12 year simulation, the model had over-predicted runoff by less than 5%. Input data requirements and model results are discussed in the light of a preliminary sensitivity analysis.     

京津冀地区井水位的数字化观测及其地震前兆监测效能评估

在较为系统地调查北京、 天津、 河北地区井水位数字化观测现状的基础上, 分析了各井水位的年、 月、 日动态特征, 并根据以往的震例评估了地震前兆监测的效能。 研究结果表明, 约90%井的水位年动态有一定规律性, 可在地震中期前兆监测中发挥效能, 约50%井的水位日、 月动态有一定规律性, 无阶变与超3倍均方差的脉冲, 可在地震短期和短临前兆监测中发挥一定效能。 研究结果还表明, 数字化井水位观测中目前较为突出的问题是, 约一半的井水位动态中存在较大幅度的脉冲状"异常"变化, 严重影响地震前兆监测效能。     

WATER BALANCE STUDIES IN THE EXPERIMENTAL BASINS OF THE UPPER HARZ MOUNTAINS / Des études du bilan hydrologique faites sur les bassins expérimentaux dans les montagnes Upper Harz

Abstract

Evaporation in the Upper Harz experimental basins is computed and compared to the values calculated according to formulae. Potential evaporation is determined for mean daily and monthly values by different methods. For the computation of the terms generally lacking in water balance studies, such as actual evaporation and changes in snow and soil storage, a model was established on the basis of daily values. As a result water balances can also be drawn up for shorter periods such as single years or months.     

Monthly rainfall-runoff models applied to arid and semiarid catchments for water resource estimation purposes

Abstract

Problems associated with the application of monthly rainfall-runoff models to arid and semiarid areas for water resource estimation purposes are discussed with respect to the representation of hydrological processes and the model rainfall input. The problems are illustrated using a specific monthly model applied to catchments within the semiarid to arid parts of southern Africa. Some model improvements are suggested and briefly evaluated and the application of a daily model to one of the catchments is compared. The overall conclusion is that while a detailed examination of the available rainfall data can account for many of the inadequate simulation results on an individual month basis, it is difficult to make allowances for the lack of resolution in the normally available information. Other problems related to the structure of individual models can be surmounted by limited model developments, but very little can be done to bypass the rainfall quantification problem.     

A simplified model for the generation of daily streamflows / Modèle simplifié pour la génération des événements d'écoulement total journaliers

Abstract

A technique for generating sequences of daily streamflows is presented which preserves the important characteristics of the daily flow hydrograph by the the use of a number of simple processes. The daily flow model is applied, in conjunction with a disaggregation model to preserve statistics of monthly and annual flows, to historic data for a river in the northwest of England. Several sets of synthetic data generated by the model are tested for their acceptability.     

A high-resolution satellite-derived sea surface temperature climatology for the western North Atlantic Ocean

Long-term and high-resolution (∼1.2 km) satellite-derived sea surface temperature (SST) fields of a monthly mean time series for the 1985–1999 period, and a daily climatology have been calculated for the North West Atlantic Ocean. The SST fields extend from 78°W to 41°W in longitude, and 30°N to 56°N in latitude, encompassing the region off Cape Hatteras, North Carolina, to the southern Labrador Sea. The monthly mean time series, consists of 180 cloud-masked monthly mean SST fields, derived from a full-resolution NOAA/NASA Pathfinder SST data set for the 1985–1999 period. The satellite-derived monthly mean SST fields, as compared with in situ monthly mean near-surface ocean temperatures from buoys located in the western North Atlantic, yield an overall RMS difference of 1.15 °C. The daily climatology, which consists of 365 fields, was derived by applying a least-squares harmonic regression technique on the monthly mean SST time series for the full study period. The monthly mean and daily climatological SST fields will be useful for studying inter-annual variability related to climate variability of SST over the study domain.     

A two steps disaggregation method for highly seasonal monthly rainfall

 The need for high resolution rainfall data at temporal scales varying from daily to hourly or even minutes is a very important problem in hydrology. For many locations of the world, rainfall data quality is very poor and reliable measurements are only available at a coarse time resolution such as monthly. The purpose of this work is to apply a stochastic disaggregation method of monthly to daily precipitation in two steps: 1. Initialization of the daily rainfall series by using the truncated normal model as a reference distribution. 2.␣Restructuring of the series according to various time series statistics (autocorrelation function, scaling properties, seasonality) by using a Markov chain Monte Carlo based algorithm. The method was applied to a data set from a rainfall network of the central plains of Venezuela, in where rainfall is highly seasonal and data availability at a daily time scale or even higher temporal resolution is very limited. A detailed analysis was carried out to study the seasonal and spatial variability of many properties of the daily rainfall as scaling properties and autocorrelation function in order to incorporate the selected statistics and their annual cycle into an objective function to be minimized in the simulation procedure. Comparisons between the observed and simulated data suggest the adequacy of the technique in providing rainfall sequences with consistent statistical properties at a daily time scale given the monthly totals. The methodology, although highly computationally intensive, needs a moderate number of statistical properties of the daily rainfall. Regionalization of these statistical properties is an important next step for the application of this technique to regions in where daily data is not available.     

On the temporal resolution of mass balance models for soluble chemicals in soils

A daily step model of chemical mass balance in the topsoil is presented and validated at the three experimental sites in Europe, and subsequently applied to perform two distinct numerical experiments. First, an experiment was run using hypothetic soluble chemicals with half‐lives ranging from 10^?1 to 10⁴, with a range of representative European climate and soil properties, assuming uniform constant emissions of the chemicals throughout the year. Chemical mass in soil from the daily step model calculations can be surrogated by the monthly step model consistently parameterized in terms of absolute values, patterns and inter‐monthly variability with decreasing accuracy at higher chemical half‐lives. Leaching fluxes can be also surrogated by the monthly step calculation, although with higher errors. Runoff is correct in the order of magnitude, but it shows only a weak correlation with the monthly mean of the daily model output. For leaching and runoff, the accuracy depends mainly on soil properties. Variability is well reproduced for both leaching and runoff. The second experiment represented a pulse emission of chemicals discharged on a single day in a 12‐month period. Results from the annual average mass of chemicals in the soil, annual runoff and leaching fluxes from the daily step model were compared with the results obtained from the experiment assuming constant‐removal rates for the year. The two values are within a factor of 10 for half‐lives longer than 10 days; therefore, it is possible to emulate the daily step model with a simple constant‐removal rate model for screening‐level assessment. The experiments suggest that simpler schemes may be a practical screening‐level approximation of detailed daily step models for both continuous and pulse emissions, two cases providing extreme bounds of variation to real world emissions. Copyright © 2010 John Wiley & Sons, Ltd.     

Impact of time-scale of the calibration objective function on the performance of watershed models

Many of the continuous watershed models perform all their computations on a daily time step, yet they are often calibrated at an annual or monthly time-scale that may not guarantee good simulation performance on a daily time step. The major objective of this paper is to evaluate the impact of the calibration time-scale on model predictive ability. This study considered the Soil and Water Assessment Tool for the analyses, and it has been calibrated at two time-scales, viz. monthly and daily for the War Eagle Creek watershed in the USA. The results demonstrate that the model's performance at the smaller time-scale (such as daily) cannot be ensured by calibrating them at a larger time-scale (such as monthly). It is observed that, even though the calibrated model possesses satisfactory ‘goodness of fit’ statistics, the simulation residuals failed to confirm the assumption of their homoscedasticity and independence. The results imply that evaluation of models should be conducted considering their behavior in various aspects of simulation, such as predictive uncertainty, hydrograph characteristics, ability to preserve statistical properties of the historic flow series, etc. The study enlightens the scope for improving/developing effective autocalibration procedures at the daily time step for watershed models. Copyright © 2007 John Wiley & Sons, Ltd.     

Comparison of two approaches for generation of daily rainfall data

There has been extensive research on the problem of stochastically generating daily rainfall sequences for use in water management applications. Srikanthan and McMahon [Australia Water Resources Council, Canberra, 1985] proposed a transition probability matrix (TPM) model that performs better for Australian rainfall than many alternative models, particularly where long records (say 100 years) are available. Boughton [Report 99/9, CRC for Catchment Hydrology, Monash University, Melbourne, 21pp, 1999] incorporated an empirical adjustment into the TPM model that allows the model to reproduce the observed variability in the annual rainfall. More recently, Harrold et al. [Water Resour Res 39(10, 12):1300, 1343, 2003a,b] proposed nonparametric models for the generation of daily rainfall occurrences and rainfall amounts on wet days. By conditioning on short, medium and long-term characteristics, this approach is also able to preserve the variability in annual rainfall. In this study, the above two approaches were used to generate daily rainfall data for Sydney and Melbourne, and the results evaluated. Both approaches preserved most of the daily, monthly and annual characteristics that were compared, with the nonparametric approach providing marginally better performance at the cost of greater model complexity. The nonparametric approach was also able to preserve the variability and persistence in the annual number of wet days.     

Long‐term hydrological simulation based on the Soil Conservation Service curve number

Presenting a critical review of daily flow simulation models based on the Soil Conservation Service curve number (SCS‐CN), this paper introduces a more versatile model based on the modified SCS‐CN method, which specializes into seven cases. The proposed model was applied to the Hemavati watershed (area = 600 km²) in India and was found to yield satisfactory results in both calibration and validation. The model conserved monthly and annual runoff volumes satisfactorily. A sensitivity analysis of the model parameters was performed, including the effect of variation in storm duration. Finally, to investigate the model components, all seven variants of the modified version were tested for their suitability. Copyright © 2004 John Wiley & Sons, Ltd.     

压制空间非平稳地震勘探随机噪声的ROAD径向时频峰值滤波算法

径向时频峰值滤波算法是一种有效保持低信噪比地震勘探记录中反射同相轴的随机噪声压制方法,但该算法对空间非平稳地震勘探随机噪声压制效果不理想.本文研究空间非平稳地震勘探随机噪声,即各道噪声功率不同的地震勘探随机噪声,其在径向滤波轨线上表征近似脉冲噪声,在径向时频峰值滤波过程中干扰相邻道滤波结果.为了减小空间非平稳随机噪声的影响,本文提出一种基于绝对级差统计量(ROAD)的径向时频峰值滤波随机噪声压制方法.该方法首先根据径向轨线上信号的绝对级差统计量检测空间非平稳地震勘探随机噪声,然后结合局部时频峰值滤波和径向时频峰值滤波压制地震勘探记录中的随机噪声.将ROAD径向时频峰值滤波方法应用于合成记录和实际共炮点地震记录,结果表明ROAD径向时频峰值滤波方法可以压制空间非平稳地震勘探随机噪声且不损害有效信号,有效抑制随机噪声空间非平稳对滤波结果的影响.与径向时频峰值滤波相比,ROAD径向时频峰值滤波方法更适用于空间非平稳地震勘探随机噪声压制.