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1.
This paper reports the results of an investigation into flood simulation by areal rainfall estimated from the combination of gauged and radar rainfalls and a rainfall–runoff model on the Anseong‐cheon basin in the southern part of Korea. The spatial and temporal characteristics and behaviour of rainfall are analysed using various approaches combining radar and rain gauges: (1) using kriging of the rain gauge alone; (2) using radar data alone; (3) using mean field bias (MFB) of both radar and rain gauges; and (4) using conditional merging technique (CM) of both radar and rain gauges. To evaluate these methods, statistics and hyetograph for rain gauges and radar rainfalls were compared using hourly radar rainfall data from the Imjin‐river, Gangwha, rainfall radar site, Korea. Then, in order to evaluate the performance of flood estimates using different rainfall estimation methods, rainfall–runoff simulation was conducted using the physics‐based distributed hydrologic model, Vflo?. The flood runoff hydrograph was used to compare the calculated hydrographs with the observed one. Results show that the rainfall field estimated by CM methods improved flood estimates, because it optimally combines rainfall fields representing actual spatial and temporal characteristics of rainfall. Copyright © 2008 John Wiley & Sons, Ltd.  相似文献   

2.
The study presents a theoretical framework for estimating the radar-rainfall error spatial correlation (ESC) using data from relatively dense rain gauge networks. The error is defined as the difference between the radar estimate and the corresponding true areal rainfall. The method is analogous to the error variance separation that corrects the error variance of a radar-rainfall product for gauge representativeness errors. The study demonstrates the necessity to consider the area–point uncertainties while estimating the spatial correlation structure in the radar-rainfall errors. To validate the method, the authors conduct a Monte Carlo simulation experiment with synthetic fields with known error spatial correlation structure. These tests reveal that the proposed method, which accounts for the area–point distortions in the estimation of radar-rainfall ESC, performs very effectively. The authors then apply the method to estimate the ESC of the National Weather Service’s standard hourly radar-rainfall products, known as digital precipitation arrays (DPA). Data from the Oklahoma Micronet rain gauge network (with the grid step of about 5 km) are used as the ground reference for the DPAs. This application shows that the radar-rainfall errors are spatially correlated with a correlation distance of about 20 km. The results also demonstrate that the spatial correlations of radar–gauge differences are considerably underestimated, especially at small distances, as the area–point uncertainties are ignored.  相似文献   

3.
Catchment modelling for water resources assessment is still mainly based on rain gauge measurements as these are more easily available and cover longer periods than radar and satellite-based measurements. Rain gauges however measure the rain falling on an extremely small proportion of the catchment and the areal rainfall obtained from these point measurements are consequently substantially uncertain. These uncertainties in areal rainfall estimation are generally ignored and the need to assess their impact on catchment modelling and water resources assessment is therefore imperative. A method that stochastically generates daily areal rainfall from point rainfall using multiplicative perturbations as a means of dealing with these uncertainties is developed and tested on the Berg catchment in the Western Cape of South Africa. The differences in areal rainfall obtained by alternately omitting some of the rain gauges are used to obtain a population of plausible multiplicative perturbations. Upper bounds on the applicable perturbations are set to prevent the generation of unrealistically large rainfall and to obtain unbiased stochastic rainfall. The perturbations within the set bounds are then fitted into probability density functions to stochastically generate the perturbations to impose on areal rainfall. By using 100 randomly-initialized calibrations of the AWBM catchment model and Sequent Peak Analysis, the effects of incorporating areal rainfall uncertainties on storage-yield-reliability analysis are assessed. Incorporating rainfall uncertainty is found to reduce the required storage by up to 20%. Rainfall uncertainty also increases flow-duration variability considerably and reduces the median flow-duration values by an average of about 20%.  相似文献   

4.
Issues associated with microwave link rainfall estimation such as the effects of spatial and temporal variation in rain, the nonlinearity of R–kRk relations, temporal sampling, power resolution, and wet antenna attenuation are investigated using more than 1.5 years of data from a high-resolution X-band weather radar. Microwave link signals are generated for different link frequencies and lengths from these radar data, so that retrieved path-averaged rainfall intensities can be compared to true path-averaged values. Results of these simulations can be linked to the space–time structure of rain. A frequency-dependent relation between the rainfall intensity at an antenna and the attenuation caused by its wetting is derived using microwave link and rain gauge data. It is shown that if the correct temporal sampling strategy is chosen, the effects of the degradation of power resolution and of wet antenna attenuation (if a correction is applied) are minor (i.e., MBE and bias-corrected RMSE are >−20% and <20% of the mean rainfall intensity, respectively) for link frequencies and lengths above ∼20 GHz and ∼2 km, respectively.  相似文献   

5.
Intense Mediterranean precipitation can generate devastating flash floods. A better understanding of the spatial structure of intense rainfall is critical to better identify catchments that will produce strong hydrological responses. We focus on two intense Mediterranean rain events of different types that occured in 2002. Radar and rain gauge measurements are combined to have a data set with a high spatial (1 × 1 km2) and temporal (5 min) resolution. Two thresholds are determined using the quantiles of the rain rate values, corresponding to the precipitating system at large and to the intense rain cells. A method based on indicator variograms associated with the thresholds is proposed in order to automatically quantify the spatial structure at each time step during the entire rain events. Therefore, its variability within intense rain events can be investigated. The spatial structure is found to be homogeneous over periods that can be related to the dynamics of the events. Moreover, a decreasing time resolution (i.e., increasing accumulation period) of the rain rate data will stretch the spatial structure because of the advection of rain cells by the wind. These quantitative characteristics of the spatial structure of intense Mediterranean rainfall will be useful to improve our understanding of the dynamics of flash floods.  相似文献   

6.
There is a significant spatial sampling mismatch between radar and rain gauge data. The use of rain gauge data to estimate radar-rainfall error variance requires partitioning of the variance of the radar and rain gauge difference to account for the sampling mismatch. A key assumption in the literature pertaining to the error variance separation method used to partition the variance is that the covariance between radar-rainfall error and the error of rain gauges in representing radar sampling domain is negligible. Our study presents the results of an extensive test of this assumption. The test is based on empirical data and covers temporal scales ranging from 0.25 to 24 h and spatial scales ranging from 1 to 32 km. We used a two-year data set from two high quality and high density rain gauge networks in Oklahoma and excluded the winter months. The results obtained using a resampling procedure show that covariance can be considerable at large scales due to the significant variability. As the variability of the covariance rapidly increases with larger spatial and shorter temporal scales, applications of the error variance separation method at those scales require more caution. The variability of the covariance and one of its constituting variables, the variance ratio of radar and gauge errors, shows simple scaling behavior well characterized by a power-law.  相似文献   

7.
Extreme rainfall events are of particular importance due to their severe impacts on the economy, the environment and the society. Characterization and quantification of extremes and their spatial dependence structure may lead to a better understanding of extreme events. An important concept in statistical modeling is the tail dependence coefficient (TDC) that describes the degree of association between concurrent rainfall extremes at different locations. Accurate knowledge of the spatial characteristics of the TDC can help improve on the existing models of the occurrence probability of extreme storms. In this study, efficient estimation of the TDC in rainfall is investigated using a dense network of rain gauges located in south Louisiana, USA. The inter-gauge distances in this network range from about 1 km to 9 km. Four different nonparametric TDC estimators are implemented on samples of the rain gauge data and their advantages and disadvantages are discussed. Three averaging time-scales are considered: 1 h, 2 h and 3 h. The results indicate that a significant tail dependency may exist that cannot be ignored for realistic modeling of multivariate rainfall fields. Presence of a strong dependence among extremes contradicts with the assumption of joint normality, commonly used in hydrologic applications.  相似文献   

8.
Observation of a storm approaching from the ocean to the in-land area is very important for the flood forecasting. Radar is generally used for this purpose. However, as rain gauges are mostly located within the in-land area, detection of the mean-field bias of radar rain rate cannot be easily made. This problem is obviously different from that with evenly-spaced rain gauges over the radar umbrella. This study investigated the detection problem of mean-field bias of radar rain rate when rain gauges are available within a small portion of radar umbrella. To exactly determine the mean-field bias, i.e. the difference between the radar rain rate and the rain gauge rain rate, the variance of the difference between two observations must be small; thus, a sufficient number of observations are indispensable. Therefore, the problem becomes determining the number of rain gauges that will satisfy the given accuracy, that being the variance of the difference between two observations. The dimensionless error variance derived by dividing the expected value of the error variance by the variance of the areal average rain rate was introduced as a criteria to effectively detect the mean field bias. Here, the variance of the areal average rain rate was assumed to be the climatological one and the expectation for the error variance could be changed depending one the sampling characteristics. As an example, this study evaluated the rainfall observation over the East Sea by the Donghae radar. About 6.8 % of the entire radar umbrella covered in-land areas, where the rain gauges were available. It was found that, to limit the dimensionless error variance to 2 %, a total of 26 rain gauges are required for the entire radar umbrella; whereas, a total of 24 rain gauges would be required within the in-land area with available for the rain gauge data.  相似文献   

9.
司伟  包为民  瞿思敏  石朋 《湖泊科学》2018,30(2):533-541
空间集总式水文模型的洪水预报精度会受到面平均雨量估计误差的严重影响.点雨量监测值的误差类型、误差大小以及流域的雨量站点密度和站点的空间分布都会影响到面平均雨量的计算.为提高实时洪水预报精度,本文提出了一种基于降雨系统响应曲线洪水预报误差修正方法.通过此方法估计降雨输入项的误差,从而提高洪水预报精度.此方法将水文模型做为输入和输出之间的响应系统,用实测流量和计算流量之间的差值做为信息,通过降雨系统响应曲线,使用最小二乘估计原理,对面平均雨量进行修正,再用修正后的面平均雨量重新计算出流过程.将此修正方法结合新安江模型使用理想案例进行检验,并应用于王家坝流域的16场历史洪水以及此流域不同雨量站密度的情况下,结果证明均有明显修正效果,且在雨量站密度较低时修正效果更加明显.该方法是一种结构简单且不增加模型参数和复杂度的实时洪水修正的新方法.  相似文献   

10.
Rain‐gauge catch efficiencies are affected by wind. Wind makes raindrops fall at an angle of inclination and the effective diameter of the rain gauge orifice smaller than if raindrops fall into the gauge vertically. Two spherical and two semi‐spherical orifices were designed to modify standard gauges and others in use today. The two spherical orifices catch rain with an effective diameter always equal to the actual diameter regardless of wind speed and direction. The semi‐spherical orifices, used side‐by‐side with a standard gauge, correct 50% of catch deficiencies made by the standard gauge. Tests based on 115 storms show that the four new gauges caught more rainfall than the standard gauge, with an average catch increase ranging from 8% to 16%. Compared with the pit gauge, average deficiency in catch ranged from ?1% (spherical rain gauge orifice with cylinders) to 4%, whereas the deficiency for the standard gauge was ?10%. Percentage deficiencies of the new gauges were positively affected by wind speed, raindrop inclination and rainfall intensity. Although the new gauges tended to underestimate the standard gauge in small storms (<0·25 cm) and overestimated the pit gauge under strong winds, their deviations are small. Underestimates for small storms could be improved by using gauge materials that reduce surface temperature, evaporation and water retention. The gauges are simple in design, easy to operate and inexpensive. In order to maintain a historically consistent set of rainfall data, a dual‐gauge (standard gauge + spherical gauge) is recommended for existing rainfall stations. The new rain gauge orifices are suitable for large‐scale applications. Copyright © 2001 John Wiley & Sons, Ltd.  相似文献   

11.
The aim of this study is to assess rainfall estimates by a dual polarized X-band radar. This study was part of the European project FRAMEA (Flood forecasting using Radar in Alpine and Mediterranean Areas). Two radars were set up near the small town of Collobrières in South Eastern France. The first radar was a dual polarized X-band radar (Hydrix®) associated with a ZPHI® algorithm while the second one was an S-band radar (Météo France). We compared radar rainfall data with measurements obtained by two rain gauge networks (Météo France and Cemagref). During the experiments from February 2006 to June 2007, four significant rainfall events occurred. The accuracy of the rain rate obtained with both S-band and X-band radars decreased significantly beyond 60 km, in particular for the X-band radar. At closer ranges, such as 30–60 km from the radars, the X-band and the S-band radar retrievals showed similar performance with Nash criteria around 0.80 for the X-band radar and 0.75 for the S-band radar. Furthermore, the X-band radar did not require calibration on rainfall records, which tends to make it a useful method to assess rainfall in areas without a rain gauge network.  相似文献   

12.
The main objective of this paper is to estimate the error in the rainfall derived from a polarimetric X-band radar, by comparison with the corresponding estimate of a rain gauge network. However the present analysis also considers the errors inherent to rain gauge, in particular instrumental and representativeness errors. A special emphasis is addressed to the spatial variability of the rainfall in order to appreciate the representativeness error of the rain gauge with respect to the 1 km square average, typical of the radar derived estimate. For this purpose the spatial correlation function of the rainfall is analyzed.  相似文献   

13.
Nozzle‐type rainfall simulators are commonly used in hydrologic and soil erosion research. Simulated rainfall intensity, originating from the nozzle, increases as the distance between the point of measurement and the source is decreased. Hence, rainfall measured using rain gauges would systematically overestimate the rainfall received at the ground level. A simple model was developed to adjust rainfall measured anywhere under the simulator to plot‐wide average rainfall at the ground level. Nozzle height, plot width, gauge diameter and height, and gauge location are required to compute this adjustment factor. Results from 15 runs at different rain intensities and durations, and with different rain gauge layouts, showed that a simple average of measured rain would overestimate the plot‐wide rain by about 20 per cent. Using the adjustment factor to convert measured rainfall for individual gauges before averaging improved the estimate of plot‐wide rainfall considerably. For the 15 runs considered, overall discrepancy between actual and measured rain is reduced to less than 1 per cent with a standard error of 0·97 mm. This model can be easily tested in the ?eld by comparing rainfall depths of different sized gauges. With the adjustment factor they should all give very similar values. Copyright © 2003 John Wiley & Sons, Ltd.  相似文献   

14.
Quantification of rainfall and its spatial and temporal variability is extremely important for reliable hydrological and meteorological modeling. While rain gauge measurements do not provide reasonable areal representation of rainfall, remotely sensed precipitation estimates offer much higher spatial resolution. However, uncertainties associated with remotely sensed rainfall estimates are not well quantified. This issue is important considering the fact that uncertainties in input rainfall are the main sources of error in hydrologic processes. Using an ensemble of rainfall estimates that resembles multiple realizations of possible true rainfall, one can assess uncertainties associated with remotely sensed rainfall data. In this paper, ensembles are generated by imposing rainfall error fields over remotely sensed rainfall estimates. A non-Gaussian copula-based model is introduced for simulation of rainfall error fields. The v-transformed copula is employed to describe the dependence structure of rainfall error estimates without the influence of the marginal distribution. Simulations using this model can be performed unconditionally or conditioned on ground reference measurements such that rain gauge data are honored at their locations. The presented model is implemented for simulation of rainfall ensembles across the Little Washita watershed, Oklahoma. The results indicate that the model generates rainfall fields with similar spatio-temporal characteristics and stochastic properties to those of observed rainfall data.  相似文献   

15.
Rainfall is a phenomenon difficult to model and predict, for the strong spatial and temporal heterogeneity and the presence of many zero values. We deal with hourly rainfall data provided by rain gauges, sparsely distributed on the ground, and radar data available on a fine grid of pixels. Radar data overcome the problem of sparseness of the rain gauge network, but are not reliable for the assessment of rain amounts. In this work we investigate how to calibrate radar measurements via rain gauge data and make spatial predictions for hourly rainfall, by means of Monte Carlo Markov Chain algorithms in a Bayesian hierarchical framework. We use zero-inflated distributions for taking zero-measurements into account. Several models are compared both in terms of data fitting and predictive performances on a set of validation sites. Finally, rainfall fields are reconstructed and standard error estimates at each prediction site are shown via easy-to-read spatial maps.  相似文献   

16.
Two methods estimating areal precipitation for selected river basins in the Czech Republic are compared. The methods use radar precipitation (the radar-derived precipitation estimate based on column maximum reflectivity) and data from 81 on-line rain gauges routinely provided by the Czech Hydrometeorological Institute. Data from a dense network of climatological rain gauges (the average inter-station distance is approximately 8 km), the measurements of which are not available in real time, are utilized for the verification. The mean areal precipitation, which is used as the ground truth, is obtained by the weighted interpolation of the dense rain gauge network. The accuracy of the methods is evaluated by the root-mean-square-error.The first, pixel-related method merges radar precipitation with rain gauge data to obtain adjusted pixel values. The adjusting procedure combines radar and gauge values in one variable that is interpolated into all radar pixels. The adjusted pixel precipitation is calculated from radar precipitation and from the value of the combined variable. The areal estimates are determined by adding the corresponding pixel values. The second method applies a linear regression model to describe the relationship between the areal precipitation (dependent variable) and its estimates, which are determined from (i) non-adjusted radar precipitation and (ii) on-line rain gauge measurements interpolated into pixels. Classical linear regression, ridge regression and robust regression models are tested.Both the methods decrease the average areal error in comparison with the reference method, which uses the on-line rain gauge data only. The decrease is about 10% and 15% for the pixel-related and regression methods, respectively. When the estimates of the pixel-related method are included as predictors into the regression method then the improvement of accuracy is almost 25%.  相似文献   

17.
Rain‐gauge networks are often used to provide estimates of area average rainfall or point rainfalls at ungauged locations. The level of accuracy a network can achieve depends on the total number and locations of gauges in the network. A geostatistical approach for evaluation and augmentation of an existing rain‐gauge network is proposed in this study. Through variogram analysis, hourly rainfalls are shown to have higher spatial variability than annual rainfalls, with hourly Mei‐Yu rainfalls having the highest spatial variability. A criterion using ordinary kriging variance is proposed to assess the accuracy of rainfall estimation using the acceptance probability defined as the probability that estimation error falls within a desired range. Based on the criterion, the percentage of the total area with acceptable accuracy Ap under certain network configuration can be calculated. A sequential algorithm is also proposed to prioritize rain‐gauges of the existing network, identify the base network, and relocate non‐base gauges. Percentage of the total area with acceptable accuracy is mostly contributed by the base network. In contrast, non‐base gauges provide little contribution to Ap and are subject to removal or relocation. Using a case study in northern Taiwan, the proposed approach demonstrates that the identified base network which comprises of approximately two‐thirds of the total rain‐gauges can achieve almost the same level of performance (expressed in terms of percentage of the total area with acceptable accuracy) as the complete network for hourly Mei‐Yu rainfall estimation. The percentage of area with acceptable accuracy can be raised from 56% to 88% using an augmented network. A threshold value for the percentage of area with acceptable accuracy is also recommended to help determine the number of non‐base gauges which need to be relocated. Copyright © 2007 John Wiley & Sons, Ltd.  相似文献   

18.
J. Ndiritu 《水文科学杂志》2013,58(8):1704-1717
Abstract

Raingauge measurements are commonly used to estimate daily areal rainfall for catchment modelling. The variation of rainfall between the gauges is usually inadequately captured and areal rainfall estimates are therefore very uncertain. A method of quantifying these uncertainties and incorporating them into ensembles of areal rainfall is demonstrated and tested. The uncertainties are imposed as perturbations based on the differences in areal rainfall that result when half of the raingauges are alternately omitted. Also included is a method of: (a) estimating the proportion rainfall that falls on areas where no gauges are located that are consequently computed as having zero rain, and (b) replacing them with plausible non-zero rainfalls. The model is tested using daily rainfall from two South African catchments and is found to exhibit the expected behaviour. One of the two parameters of the model is obtained from the rainfall data, while the other has direct physical interpretation.

Editor D. Koutsoyiannis; Associate editor C. Onof

Citation Ndiritu, J., 2013. Using data-derived perturbations to incorporate uncertainty in generating stochastic areal rainfall from point rainfall. Hydrological Sciences Journal, 58 (8), 1704–1717.  相似文献   

19.
Rainfall data are a fundamental input for effective planning, designing and operating of water resources projects. A well‐designed rain gauge network is capable of providing accurate estimates of necessary areal average and/or point rainfall estimates at any desired ungauged location in a catchment. Increasing network density with additional rain gauge stations has been the main underlying criterion in the past to reduce error and uncertainty in rainfall estimates. However, installing and operation of additional stations in a network involves large cost and manpower. Hence, the objective of this study is to design an optimal rain gauge network in the Middle Yarra River catchment in Victoria, Australia. The optimal positioning of additional stations as well as optimally relocating of existing redundant stations using the kriging‐based geostatistical approach was undertaken in this study. Reduction of kriging error was considered as an indicator for optimal spatial positioning of the stations. Daily rainfall records of 1997 (an El Niño year) and 2010 (a La Niña year) were used for the analysis. Ordinary kriging was applied for rainfall data interpolation to estimate the kriging error for the network. The results indicate that significant reduction in the kriging error can be achieved by the optimal spatial positioning of the additional as well as redundant stations. Thus, the obtained optimal rain gauge network is expected to be appropriate for providing high quality rainfall estimates over the catchment. The concept proposed in this study for optimal rain gauge network design through combined use of additional and redundant stations together is equally applicable to any other catchment. © 2014 The Authors. Hydrological Processes published by John Wiley & Sons Ltd.  相似文献   

20.
In an effort to reduce wind effect on rainfall catch to a minimum level, Chang and Flannery (2001. Hydrological Processes 15 : 643–654) designed two spherical orifices to modify the standard gauge and other gauges in use today. Because of the spherical shape, the two orifices will catch rain with an effective diameter always equal to the actual diameter, regardless of wind speed and direction. This report covers the testing of spherical gauges at two different locations, one at the City Landfill, Nacogdoches, TX, and the other at the NWS Forecast Office, Shreveport, LA. Based on 131 storms at Nacogdoches and 94 storms at Shreveport, observed between May 1998 and February 2001, the results showed: (1) spherical gauges recorded an average 6–9% greater than standard gauge and 3–4% less than pit gauge, only 1–2% less than reported in the original study; (2) the catch of spherical gauges was not significantly affected by three gauge heights at 0·91, 1·83, and 2·74 m above the ground, but catch by the standard gauge decreased with increasing gauge height; (3) improvements of the spherical gauges were most significant for larger storms and for winds at higher speeds; (4) the spherical gauge with cylinders recorded 1–2% more rainfall than the spherical gauge with vanes; and (5) correlation coefficients between catch deficiencies and wind speed were low and weak because of the distance and height of the existing wind sensor. Owing to greater surface wetting and evaporation loss, the spherical gauges may underestimate rainfall catch by standard gauge for small storms (generally less than 5·0 mm), especially on hot summer afternoons and for smaller storms. However, the underestimates do not overshadow the merits of spherical gauges, because the differences are too small to be of hydrologic significance. Using polyethylene or other synthesized materials to construct spherical orifices may improve the catch for small storms. The results of the study agreed with the previous claims that spherical gauges are effective in reducing wind effects on rainfall measurements. The spherical gauges could greatly improve the accuracy of hydrologic simulations and the efficiency on the designs and management of water resources. They are suitable for large‐scale applications. Copyright © 2004 John Wiley & Sons, Ltd.  相似文献   

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