共查询到20条相似文献，搜索用时 31 毫秒
1.
This paper characterizes the joint distribution of multiplicative errors (ME) in radar (R) and satellite (S) quantitative precipitation estimates (QPEs). A semi-parametric framework is established on the basis of this joint distribution to describe the probability of rainfall exceeding a particular threshold given concurrent R and S-based estimates (referred to as conditional exceedance probability, or CEP). This framework entails integrating copula-based joint distributions of MEs over a range of rainfall amounts to yield the joint probability of exceedance, which forms the basis for estimating CEP. In demonstrating this approach, MEs were computed for R (Weather Surveillance Radar-1988 Doppler) and S (Self-calibrating Multivariate Precipitation Retrieval) for central Texas over 2000–2007 using gauge records as the reference. Analysis of the MEs in R and S reveals a substantial correlation between the two, and it also shows that the interdependence is complex as a considerable portion of S QPEs are negatively biased while their concurrent R values are bias-neutral. CEP values from the semi-parametric approach is found to be generally superior to those empirically derived based on rainfall estimates: it yields values for a wide range of rainfall thresholds and suffers much fewer discontinuities and artifacts that the empirical results exhibit. For the lower range of S and R thresholds where sample size is relatively large (i.e., <20 mm h−1 for the summer), the two sets of CEPs bear close resemblance, with both showing a relatively weak, but nevertheless substantial dependence on the threshold value for S. These findings confirm the plausibility of the semi-parametric CEP values, and demonstrate the utility of S QPEs in improving the confidence in rainfall exceedance under this framework. 相似文献
2.
The infrared‐microwave rainfall algorithm (IMRA) was developed for retrieving spatial rainfall from infrared (IR) brightness temperatures (TBs) of satellite sensors to provide supplementary information to the rainfall field, and to decrease the traditional dependency on limited rain gauge data that are point measurements. In IMRA, a SLOPE technique (ST) was developed for discriminating rain/no‐rain pixels through IR image cloud‐top temperature gradient, and 243K as the IR threshold temperature for minimum detectable rainfall rate. IMRA also allows for the adjustment of rainfall derived from IR‐TB using microwave (MW) TBs. In this study, IMRA rainfall estimates were assessed on hourly and daily basis for different spatial scales (4, 12, 20, and 100 km) using NCEP stage IV gauge‐adjusted radar rainfall data, and daily rain gauge data. IMRA was assessed in terms of the accuracy of the rainfall estimates and the basin streamflow simulated by the hydrologic model, Sacramento soil moisture accounting (SAC‐SMA), driven by the rainfall data. The results show that the ST option of IMRA gave accurate satellite rainfall estimates for both light and heavy rainfall systems while the Hessian technique only gave accurate estimates for the convective systems. At daily time step, there was no improvement in IR‐satellite rainfall estimates adjusted with MW TBs. The basin‐scale streamflow simulated by SAC‐SMA driven by satellite rainfall data was marginally better than when SAC‐SMA was driven by rain gauge data, and was similar to the case using radar data, reflecting the potential applications of satellite rainfall in basin‐scale hydrologic modelling. Copyright © 2010 John Wiley & Sons, Ltd. 相似文献
3.
Siao Sun Günther Leonhardt Santiago Sandoval Jean-Luc Bertrand-Krajewski Wolfgang Rauch 《水文科学杂志》2017,62(15):2456-2468
The estimation of missing rainfall data is an important problem for data analysis and modelling studies in hydrology. This paper develops a Bayesian method to address missing rainfall estimation from runoff measurements based on a pre-calibrated conceptual rainfall–runoff model. The Bayesian method assigns posterior probability of rainfall estimates proportional to the likelihood function of measured runoff flows and prior rainfall information, which is presented by uniform distributions in the absence of rainfall data. The likelihood function of measured runoff can be determined via the test of different residual error models in the calibration phase. The application of this method to a French urban catchment indicates that the proposed Bayesian method is able to assess missing rainfall and its uncertainty based only on runoff measurements, which provides an alternative to the reverse model for missing rainfall estimates. 相似文献
4.
《水文科学杂志》2013,58(5):886-898
Abstract Temporal resolution of rainfall plays an important role in determining the hydrological response of river basins. Rainfall temporal variability can be considered as one of the most critical elements when dealing with input data of rainfall—runoff models. In this paper, a typical lumped rainfall—runoff model is applied to long- and short-term runoff prediction using rainfall data sets with different temporal resolution, including daily, hourly and 10-min interval data, and the dependency of model performance on the time interval of the rainfall data is discussed. Furthermore, the effect of temporal resolution on model parameter values is analysed. As results, rainfall data with shorter temporal resolution provide better performance in short-term river discharge estimation, especially for storm discharge estimation. The most accurate results are obtained on the peak discharge and recession part of the hydrograph by using 10-min interval rainfall data. It is concluded that model parameter values are influenced not only by the temporal resolution of calculation but also by the rainfall intensity—duration relationship. This study provides useful information about determination of hydrological model parameters using data of different temporal resolutions. 相似文献
5.
Climate change is expected to alter rainfall regimes across most parts of the world. The implications of this could be more severe in arid environments where rainfall is limited and highly variable in space and time. However, lack of good quality data, of sufficient record length and spatial coverage usually restricts model development and performance geared towards assessing the effects of climate change in these areas. This paper presents an analysis of rainfall and climate data in order to determine the time of change in rainfall series and identify possible correlations between rainfall and temperature. In addition, the paper aims to make predictions of future rainfall patterns in Botswana. This is achieved by using historical rainfall and climate data from rainfall stations spread across Botswana from 1965 to 2008. In addition, large scale reanalysis data from NCAR/NCEP and El Nino Southern Oscillation (ENSO) data were used to augment the limited observed spatial climate data series when developing a rainfall model. Temperature and ENSO indices have been used to predict rainfall regimes for the present climate. Based on these, the effects of climate change were quantified using a stochastic generalised linear rainfall model (GLM) driven by outputs of global climate models (GCMs). The results indicate that temperature is a significant rainfall predictor in Botswana compared to ENSO indices. 相似文献
6.
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
7.
F. Heuze R. Archuleta F. Bonilla S. Day M. Doroudian A. Elgamal S. Gonzales M. Hoehler T. Lai D. Lavallee B. Lawrence P. -C. Liu A. Martin L. Matesic B. Minster R. Mellors D. Oglesby S. Park M. Riemer J. Steidl F. Vernon M. Vucetic J. Wagoner Z. Yang 《Soil Dynamics and Earthquake Engineering》2004,24(3):199-223
The Campus Earthquake Program (CEP) of the University of California (UC) started in March 1996, and involved a partnership among seven campuses of the UC—Berkeley, Davis, Los Angeles, Riverside, San Diego, Santa Barbara, Santa Cruz—and the Lawrence Livermore National Laboratory (LLNL). The aim of the CEP was to provide University campuses with site-specific assessments of their earthquake strong motion exposure, to complement estimates they obtain from consultants according to the state-of-the-practice (SOP), i.e. Building Codes (UBC 97, IBC 2000), and Probabilistic Seismic Hazard Analysis (PSHA). The Building Codes are highly simplified tools, while the more sophisticated PSHA is still somewhat generic in its approach because it usually draws from many earthquakes not necessarily related to the faults threatening the site under study.Between 1996 and 2001, the site-specific studies focused on three campuses: Riverside, San Diego, and Santa Barbara. Each campus selected 1–3 sites to demonstrate the methods and procedures used by the CEP: Rivera Library and Parking Lots (PL) 13 and 16 at UCR, Thornton Hospital, the Cancer Center, and PL 601 at UCSD, and Engineering I building at UCSB. The project provided an estimate of strong ground motions at each selected site, for selected earthquake scenarios. These estimates were obtained by using an integrated geological, seismological, geophysical, and geotechnical approach, that brings together the capabilities of campus and laboratory personnel. Most of the site-specific results are also applicable to risk evaluation of other sites on the respective campuses.The CEP studies have provided a critical assessment of whether existing campus seismic design bases are appropriate. Generally speaking, the current assumptions are not acknowledging the severity of the majority of expected motions. Eventually, both the results from the SOP and from the CEP should be analyzed, to arrive at decisions concerning the design-basis for buildings on UC campuses. 相似文献
8.
Bellie Sivakumar Ashish Sharma 《Stochastic Environmental Research and Risk Assessment (SERRA)》2008,22(4):451-459
High-resolution temporal rainfall data sequences serve as inputs for a range of applications in planning, design and management
of small (especially urban) water resources systems, including continuous flow simulation and evaluation of alternate policies
for environmental impact assessment. However, such data are often not available, since their measurements are costly and time-consuming.
One alternative to obtain high-resolution data is to try to derive them from available low-resolution information through
a disaggregation procedure. This study evaluates a random cascade approach for generation of high-resolution rainfall data
at a point location. The approach is based on the concept of scaling in rainfall, or, relating the properties associated with
the rainfall process at one temporal scale to a finer-resolution scale. The procedure involves two steps: (1) identification
of the presence of scaling behavior in the rainfall process; and (2) generation of synthetic data possessing same/similar
scaling properties of the observed rainfall data. The scaling identification is made using a statistical moment scaling function,
and the log–Poisson distribution is assumed to generate the synthetic rainfall data. The effectiveness of the approach is
tested on the rainfall data observed at the Sydney Observatory Hill, Sydney, Australia. Rainfall data corresponding to four
different successively doubled resolutions (daily, 12, 6, and 3 h) are studied, and disaggregation of data is attempted only
between these successively doubled resolutions. The results indicate the presence of multi-scaling behavior in the rainfall
data. The synthetic data generated using the log–Poisson distribution are found to exhibit scaling behaviors that match very
well with that for the observed data. However, the results also indicate that fitting the scaling function alone does not
necessarily mean reproducing the broader attributes that characterize the data. This observation clearly points out the extreme
caution needed in the application of the existing methods for identification of scaling in rainfall, especially since such
methods are also prevalent in studies of the emerging satellite observations and thus in the broader spectrum of hydrologic
modeling. 相似文献
9.
利用昭通中心站YRY-4钻孔应变仪前兆观测数据资料,提取降雨对该仪器观测数据的干扰事件,采用降雨总量、瞬间最大值降雨量两类降雨分类统计方法,定量分析降雨对观测数据产生的影响。结果表明:当降雨总量达到40 mm、瞬间最大值降雨量大于0.4 mm时,YRY-4钻孔应变仪观测数据受降雨干扰明显;当降雨总量大于40 mm时,降雨总量与观测数据应变量呈线性关系,瞬间最大值降雨量与降雨总量之间无显著的对应关系。分析认为,降雨干扰影响主要来自降雨渗透和台站周边地质抗水体荷载量大小两个方面。定量分析降雨干扰,有利于区分异常与干扰,积累经验,以便于及时对有效异常进行判定,为地震研究服务。 相似文献
10.
11.
Knowledge of rainfall characteristics is very important for the accurate estimation of rainfall kinetic energy and prediction of soil erosion. In this study, a reliable and efficient data collection and analysis system was developed to analyse the natural raindrop data collected in subtropical Taiwan. Both raindrop size distributions by number and volume were carefully analysed. The seasonal variations of the rainfall erosivity factor R, which is an index of the erosive potential of rainfall and a function of rainfall kinetic energy, was also discussed. An isoerodent map of Taiwan was also developed based on the rainfall data recorded by 158 automated rainfall‐measuring stations within 26 years. Copyright © 2007 John Wiley & Sons, Ltd. 相似文献
12.
Satyaban Bishoyi Ratna 《Pure and Applied Geophysics》2012,169(1-2):259-273
This paper presents the results of an analysis of the daily rainfall of 329 rain gauge stations data over Maharashtra, a state in India, during the summer monsoon season, June to September, for the 11?year period from 1998 to 2008. Mesoscale analysis of the daily rainfall data is performed by converting the station rainfall data into gridded format with 15?km resolution. Various statistics have been carried out over 35 districts of four meteorological subdivisions of the Maharashtra state to understand the spatio-temporal variability of rainfall. Variation of monthly mean rainfall for the four monsoon months and a season as whole is analyzed for different rainfall statistics such as mean rainfall, rainfall variability, rainy days, maximum daily rainfall and classification of rainy days. Seasonal rainfall is maximum over the Konkan region followed by the eastern Vidharbha region whereas Madhya Maharashtra as a rain shadow region receives less rainfall. The rainfall is highly variable over all of Maharashtra with the coefficient of variability of the daily rainfall varying between 100 and 300%. Seasonal distribution of the number of rainy days shows 90–100 over southern Konkan, 80–90 over northern Konkan, 50–60 over eastern Vidharbha, and the southeast Madhya Maharashtra has the lowest number of about 15–20 rainy days. The highest values of maximum daily rainfall are located over the Sindhudurg, Ratnagiri, Raigadh, Mumbai and Thane districts of the Konkan region followed by that over eastern Vidharbha. The rainfall data have been divided into three categories (moderate rainfall, heavy rainfall and extreme heavy rainfall) based upon seven categories used by the India Meteorological Department. Heavy rainfall zones lie over the southern Konkan region, whereas extreme heavy rainfalls occur over northern latitudes. The data used in this study is having high resolution and district wise analysis over Maharashtra state is extremely beneficial. 相似文献
13.
Daily rainfall is a complex signal exhibiting alternation of dry and wet states, seasonal fluctuations and an irregular behavior at multiple scales that cannot be preserved by stationary stochastic simulation models. In this paper, we try to investigate some of the strategies devoted to preserve these features by comparing two recent algorithms for stochastic rainfall simulation: the first one is the modified Markov model, belonging to the family of Markov-chain based techniques, which introduces non-stationarity in the chain parameters to preserve the long-term behavior of rainfall. The second technique is direct sampling, based on multiple-point statistics, which aims at simulating a complex statistical structure by reproducing the same data patterns found in a training data set. The two techniques are compared by first simulating a synthetic daily rainfall time-series showing a highly irregular alternation of two regimes and then a real rainfall data set. This comparison allows analyzing the efficiency of different elements characterizing the two techniques, such as the application of a variable time dependence, the adaptive kernel smoothing or the use of low-frequency rainfall covariates. The results suggest, under different data availability scenarios, which of these elements are more appropriate to represent the rainfall amount probability distribution at different scales, the annual seasonality, the dry-wet temporal pattern, and the persistence of the rainfall events. 相似文献
14.
A computational method for the determination of rainfall distribution for applications in short term rainfall prediction is presented here. The method is strongly influenced by the experience gained from the observation and analysis of data gathered on a heavy rainfall event in 1986 that occurred during the Baiu Season in Japan. The method is based on the concept that rainfall occurs as an interaction between an instability field, appropriately modeled, and a field of water vapor under the influence of topography. The results from this computational method showed good agreement with the temporal variation in the rainband that moved across the observation field in 1986. Towards determination of the parameters in the computational model, another method for the determination of the rainfield is also developed. This second method determines the rainfall distribution from estimation of the conversion rate of water vapor to liquid water through use of data from a three dimensional scanning radar. The results are consistent with those obtained from the first method. 相似文献
15.
Spatial rainfall estimation by linear and non-linear co-kriging of radar-rainfall and raingage data 总被引：1，自引：0，他引：1
A. Azimi-Zonooz W. F. Krajewski D. S. Bowles D. J. Seo 《Stochastic Environmental Research and Risk Assessment (SERRA)》1989,3(1):51-67
The feasibility of linear and nonlinear geostatistical estimation techniques for optimal merging of rainfall data from raingage and radar observations is investigated in this study by use of controlled numerical experiments. Synthetic radar and raingage data are generated with their hypothetical error structures that explicitly account for sampling characteristics of the two sensors. Numerically simulated rainfall fields considered to be ground-truth fields on 4×4 km grids are used in the generation of radar and raingage observations. Ground-truth rainfall fields consist of generated rainfall fields with various climatic characteristics that preserve the space-time covariance function of rainfall events in extratropical cyclonic storms. Optimal mean areal precipitation estimates are obtained based on the minimum variance, unbiased property of kriging techniques under the second order homogeneity assumption of rainfall fields. The evaluation of estimated rainfall fields is done based on the refinement of spatial predictability over what would be provided from each sensor individually. Attention is mainly given to removal of measurement error and bias that are synthetically introduced to radar measurements. The influence of raingage network density on estimated rainfall fields is also examined. 相似文献
16.
The overall objective of this study is to improve the forecasting accuracy of the precipitation in the Singapore region by means of both rainfall forecasting and nowcasting. Numerical Weather Predication (NWP) and radar‐based rainfall nowcasting are two important sources for quantitative precipitation forecast. In this paper, an attempt to combine rainfall prediction from a high‐resolution mesoscale weather model and a radar‐based rainfall model was performed. Two rainfall forecasting methods were selected and examined: (i) the weather research and forecasting model (WRF); and (ii) a translation model (TM). The WRF model, at a high spatial resolution, was run over the domain of interest using the Global Forecast System data as initializing fields. Some heavy rainfall events were selected from data record and used to test the forecast capability of WRF and TM. Results obtained from TM and WRF were then combined together to form an ensemble rainfall forecasting model, by assigning weights of 0.7 and 0.3 weights to TM and WRF, respectively. This paper presented results from WRF and TM, and the resulting ensemble rainfall forecasting; comparisons with station data were conducted as well. It was shown that results from WRF are very useful as advisory of anticipated heavy rainfall events, whereas those from TM, which used information of rain cells already appearing on the radar screen, were more accurate for rainfall nowcasting as expected. The ensemble rainfall forecasting compares reasonably well with the station observation data. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献
17.
Tae-Woong Kim Hosung Ahn 《Stochastic Environmental Research and Risk Assessment (SERRA)》2009,23(3):367-376
Missing data in daily rainfall records are very common in water engineering practice. However, they must be replaced by proper
estimates to be reliably used in hydrologic models. Presented herein is an effort to develop a new spatial daily rainfall
model that is specifically intended to fill in gaps in a daily rainfall dataset. The proposed model is different from a convectional
daily rainfall generation scheme in that it takes advantage of concurrent measurements at the nearby sites to increase the
accuracy of estimation. The model is based on a two-step approach to handle the occurrence and the amount of daily rainfalls
separately. This study tested four neural network classifiers for a rainfall occurrence processor, and two regression techniques
for a rainfall amount processor. The test results revealed that a probabilistic neural network approach is preferred for determining
the occurrence of daily rainfalls, and a stepwise regression with a log-transformation is recommended for estimating daily
rainfall amounts. 相似文献
18.
A. Azimi-Zonooz W. F. Krajewski D. S. Bowles D. J. Seo 《Stochastic Hydrology and Hydraulics》1989,3(1):51-67
The feasibility of linear and nonlinear geostatistical estimation techniques for optimal merging of rainfall data from raingage and radar observations is investigated in this study by use of controlled numerical experiments. Synthetic radar and raingage data are generated with their hypothetical error structures that explicitly account for sampling characteristics of the two sensors. Numerically simulated rainfall fields considered to be ground-truth fields on 4×4 km grids are used in the generation of radar and raingage observations. Ground-truth rainfall fields consist of generated rainfall fields with various climatic characteristics that preserve the space-time covariance function of rainfall events in extratropical cyclonic storms. Optimal mean areal precipitation estimates are obtained based on the minimum variance, unbiased property of kriging techniques under the second order homogeneity assumption of rainfall fields. The evaluation of estimated rainfall fields is done based on the refinement of spatial predictability over what would be provided from each sensor individually. Attention is mainly given to removal of measurement error and bias that are synthetically introduced to radar measurements. The influence of raingage network density on estimated rainfall fields is also examined. 相似文献
19.
E. Nakakita S. Ikebuchi M. Shiiba T. Takasao 《Stochastic Environmental Research and Risk Assessment (SERRA)》1990,4(2):135-150
A computational method for the determination of rainfall distribution for applications in short term rainfall prediction is presented here. The method is strongly influenced by the experience gained from the observation and analysis of data gathered on a heavy rainfall event in 1986 that occurred during the Baiu Season in Japan. The method is based on the concept that rainfall occurs as an interaction between an instability field, appropriately modeled, and a field of water vapor under the influence of topography. The results from this computational method showed good agreement with the temporal variation in the rainband that moved across the observation field in 1986. Towards determination of the parameters in the computational model, another method for the determination of the rainfield is also developed. This second method determines the rainfall distribution from estimation of the conversion rate of water vapor to liquid water through use of data from a three dimensional scanning radar. The results are consistent with those obtained from the first method. 相似文献
20.
多年观测数据表明,代县地电阻率年变受降雨影响比较显著,通过褶积滤波法获取降雨量对视电阻率的影响值,定量分析降雨与视电阻率的相关性。在此基础上,利用代县地电阻率电测深数据及相关地质资料,建立三维有限元模型,模拟降雨对地电阻率的影响,进一步确定降雨对视电阻率影响的物理机制。结果表明:降雨是造成代县地电阻率年变的主要因素,且与视电阻率呈正相关性;降雨造成表层介质含水饱和度发生变化,使得相应电阻率下降近10倍,从而引起地电阻率年变幅度发生近1/10的改变。 相似文献