共查询到20条相似文献，搜索用时 645 毫秒
1.
Effective typhoon characteristics and their effects on hourly reservoir inflow forecasting 总被引：1，自引：0，他引：1
This paper describes the identification of effective typhoon characteristics and the development of a new type of hourly reservoir inflow forecasting model with the effective typhoon characteristics. Firstly, a comparison of support vector machines (SVMs), which is a novel kind of neural networks (NNs), and back-propagation networks (BPNs) is made to select an appropriate NN-based model. The results show that SVM-based models are more appropriate than BPN-based models because of their higher accuracy and much higher efficiency. In addition, effective typhoon characteristics for improving forecasting performance are identified from all the collected typhoon information. Then the effective typhoon characteristics (the position of the typhoon and the distance between the typhoon center and the reservoir) are added to the proposed SVM-based models. Next, a performance comparison of models with and without effective typhoon characteristics is conducted to clearly highlight the effects of effective typhoon characteristics on hourly reservoir inflow forecasting. To reach a just conclusion, the performance is evaluated by cross validation, and the improvement in performance due to the addition of effective typhoon characteristics is tested by paired comparison t-tests at the 5% significance level. The results confirm that effective typhoon characteristics do improve the forecasting performance and the improvement increases with increasing lead-time, especially when the rainfall data are not available. For four- to six-hour ahead forecasts, the improvement due to the addition of effective typhoon characteristics increases from 3% to 18% and from 10% to 113% for Categories I (rainfall data are available) and II (rainfall data are not available), respectively. In conclusion, effective typhoon characteristics are recommended as key inputs for reservoir inflow forecasting during typhoons. The proposed SVM-based models with effective typhoon characteristics are expected to provide more accurate forecasts than BPN-based models. The proposed modeling technique is also expected to be useful to support reservoir operation systems and other disaster warning systems. 相似文献
2.
AbstractThis paper develops an algorithm for computing spatially-distributed monthly potential evaporation (PE) over a mountainous region, the Lhasa River basin in China. To develop the algorithm, first, correlation analysis of different meteorological variables was conducted. It was observed that PE is significantly correlated with vapour pressure and temperature differences between the land surface and the atmosphere. Second, the Dalton model, which was developed based on the mass transfer mechanism, was modified by including the influence of the related meteorological variables. Third, the influence of elevation on monthly temperature, vapour pressure and wind velocity was analysed, and functions for extending these meteorological variables to any given altitude were developed. Fourth, the inverse distance weighting method was applied to integrate the extended meteorological variables from five stations adjacent to and within the Lhasa River basin. Finally, using the modified Dalton model and the integrated meteorological variables, we computed the spatially-distributed monthly PE. This study indicated that spatially-distributed PE can be obtained using data from sparse meteorological stations, even if only one station is available; the results show that in the Lhasa River basin PE decreases when elevation increases. The new algorithm, including the modified model and the method for spatially extending meteorological variables can provide the basic inputs for distributed hydrological models.
Editor Z.W. Kundzewicz 相似文献
3.
Özgür Kişi 《水文研究》2009,23(2):213-223
This paper reports on investigations of the abilities of three different artificial neural network (ANN) techniques, multi‐layer perceptrons (MLP), radial basis neural networks (RBNN) and generalized regression neural networks (GRNN) to estimate daily pan evaporation. Different MLP models comprising various combinations of daily climatic variables, that is, air temperature, solar radiation, wind speed, pressure and humidity were developed to evaluate the effect of each of these variables on pan evaporation. The MLP estimates are compared with those of the RBNN and GRNN techniques. The Stephens‐Stewart (SS) method is also considered for the comparison. The performances of the models are evaluated using root mean square errors (RMSE), mean absolute error (MAE) and determination coefficient (R2) statistics. Based on the comparisons, it was found that the MLP and RBNN computing techniques could be employed successfully to model the evaporation process using the available climatic data. The GRNN was found to perform better than the SS method. Copyright © 2008 John Wiley & Sons, Ltd. 相似文献
4.
《水文科学杂志》2013,58(6)
Abstract Abstract Evaporation is one of the fundamental elements in the hydrological cycle, which affects the yield of river basins, the capacity of reservoirs, the consumptive use of water by crops and the yield of underground supplies. In general, there are two approaches in the evaporation estimation, namely, direct and indirect. The indirect methods such as the Penman and Priestley-Taylor methods are based on meteorological variables, whereas the direct methods include the class A pan evaporation measurement as well as others such as class GGI-3000 pan and class U pan. The major difficulty in using a class A pan for the direct measurements arises because of the subsequent application of coefficients based on the measurements from a small tank to large bodies of open water. Such difficulties can be accommodated by fuzzy logic reasoning and models as alternative approaches to classical evaporation estimation formulations were applied to Lake Egirdir in the western part of Turkey. This study has three objectives: to develop fuzzy models for daily pan evaporation estimation from measured meteorological data, to compare the fuzzy models with the widely-used Penman method, and finally to evaluate the potential of fuzzy models in such applications. Among the measured meteorological variables used to implement the models of daily pan evaporation prediction are the daily observations of air and water temperatures, sunshine hours, solar radiation, air pressure, relative humidity and wind speed. Comparison of the classical and fuzzy logic models shows a better agreement between the fuzzy model estimations and measurements of daily pan evaporation than the Penman method. 相似文献
5.
Downscaling of precipitation for climate change scenarios: A support vector machine approach 总被引：7，自引：0，他引：7
The Climate impact studies in hydrology often rely on climate change information at fine spatial resolution. However, general circulation models (GCMs), which are among the most advanced tools for estimating future climate change scenarios, operate on a coarse scale. Therefore the output from a GCM has to be downscaled to obtain the information relevant to hydrologic studies. In this paper, a support vector machine (SVM) approach is proposed for statistical downscaling of precipitation at monthly time scale. The effectiveness of this approach is illustrated through its application to meteorological sub-divisions (MSDs) in India. First, climate variables affecting spatio-temporal variation of precipitation at each MSD in India are identified. Following this, the data pertaining to the identified climate variables (predictors) at each MSD are classified using cluster analysis to form two groups, representing wet and dry seasons. For each MSD, SVM- based downscaling model (DM) is developed for season(s) with significant rainfall using principal components extracted from the predictors as input and the contemporaneous precipitation observed at the MSD as an output. The proposed DM is shown to be superior to conventional downscaling using multi-layer back-propagation artificial neural networks. Subsequently, the SVM-based DM is applied to future climate predictions from the second generation Coupled Global Climate Model (CGCM2) to obtain future projections of precipitation for the MSDs. The results are then analyzed to assess the impact of climate change on precipitation over India. It is shown that SVMs provide a promising alternative to conventional artificial neural networks for statistical downscaling, and are suitable for conducting climate impact studies. 相似文献
6.
Evaluation of gene expression programming approaches for estimating daily evaporation through spatial and temporal data scanning 总被引：1，自引：0，他引：1 
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下载免费PDF全文 Evaporation of water from free water surfaces or from land surfaces is one of the main components of the hydrological cycle, and its occurrence is governed by various meteorological and physical factors. There is a multitude of models developed for estimating daily evaporation values by using weather data. This paper evaluates a Gene Expression Programming (GEP) model for estimating evaporation through spatial and temporal data scanning techniques. It is by using ‘leave‐one‐out’ procedures, a complete scan of the possible train and test set configurations is carried out according to temporal and spatial criteria. Comparison of the GEP model with empirical‐physical models shows that daily evaporation values computed by the GEP model are more accurate. Further, local calibration of the GEP model may not be needed, if enough climatic data are available at other stations. The performance of the GEP model fluctuates throughout the period of study and between stations. A suitable assessment of the model should consider a complete temporal and/or spatial scan of the data set used. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献
7.
An objective assessment of soil-moisture deficit models 总被引：1，自引：0，他引：1
The performance of different soil-moisture deficit models was assessed by comparing model predictions with over 3000 neutron-probe observations of soil-moisture content at six grassland experimental sites operated by the Institute of Hydrology. The models were formulated using combinations of different equations for estimating potential evaporation and different regulating functions relating actual to potential evaporation via the moisture status of the soil. The inclusion of sophisticated evaporation equations (Priestley-Taylor, Penman, Thom-Oliver) gave no improvement in SMD prediction over a proposed simple evaporation formula requiring no direct meteorological measurements other than rainfall. The success of this formula demonstrates the conservative nature of annual potential evaporation within the U.K. both spatially and temporally and also suggests a possible natural feedback mechanism between atmospheric demand and grass transpiration. 相似文献
8.
A complementary relationship evaporation model has been proposed and verified based on evaluations of the advection–aridity model and the Granger's complementary relationship model (Granger model) in dimensionless forms. Normalized by Penman potential evaporation, the Granger model and the advection–aridity model have been transformed into similar dimensionless forms. Evaporation ratio (ratio of actual evaporation to Penman potential evaporation) has been expressed as a function of dimensionless variable based on radiation and atmospheric conditions. Similar dimensionless variables for the different functions have been used in the two models. By referring to the dimensionless variable from the advection–aridity model and the function from the Granger model, a new model to estimate actual evaporation was proposed. The performance of the new model has been validated by the observed data from four sites under different land covers. The new model is an enhanced Granger model with better evaporation prediction over the aforementioned different land covers. It also offers more stable optimized parameters in a grassland site than the Granger model. The new model somewhat approximates the advection–aridity model under neither too wet nor too dry conditions, but without its system bias. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
9.
Abstract Evaporation is an important reference for managers of water resources. This study proposes a hybrid model (BD) that combines back-propagation neural networks (BPNN) and dynamic factor analysis (DFA) to simultaneously precisely estimate pan evaporation at multiple meteorological stations in northern Taiwan through incorporating a large number of meteorological data sets into the estimation process. The DFA is first used to extract key meteorological factors that are highly related to pan evaporation and to establish the common trend of pan evaporation among meteorological stations. The BPNN is then trained to estimate pan evaporation with the inputs of the key meteorological factors and evaporation estimates given by the DFA. The BD model successfully inherits the advantages from the DFA and BPNN, and effectively enhances its generalization ability and estimation accuracy. The results demonstrate that the proposed BD model has good reliability and applicability in simultaneously estimating pan evaporation for multiple meteorological stations. Citation Chang, F.J., Sun, W., and Chung, C.H., 2013. Dynamic factor analysis and artificial neural network for estimating pan evaporation at multiple stations in northern Taiwan. Hydrological Sciences Journal, 58 (4), 813–825. 相似文献
10.
Gridded climate data products are an alternative to instrumental measurements as inputs to rainfall–runoff models 下载免费PDF全文
下载免费PDF全文 Rainfall–runoff models are widely used to predict flows using observed (instrumental) time series of air temperature and precipitation as inputs. Poor model performance is often associated with difficulties in estimating catchment‐scale meteorological variables from point observations. Readily available gridded climate products are an underutilized source of temperature and precipitation time series for rainfall–runoff modelling, which may overcome some of the performance issues associated with poor‐quality instrumental data in small headwater monitoring catchments. Here we compare the performance of instrumental measured and E‐OBS gridded temperature and precipitation time series as inputs in the rainfall–runoff models “PERSiST” and “HBV” for flow prediction in six small Swedish catchments. For both models and most catchments, the gridded data produced statistically better simulations than did those obtained using instrumental measurements. Despite the high correspondence between instrumental and gridded temperature, both temperature and precipitation were responsible for the difference. We conclude that (a) gridded climate products such as the E‐OBS dataset could be more widely used as alternative input to rainfall–runoff models, even when instrumental measurements are available, and (b) the processing applied to gridded climate products appears to provide a more realistic approximation of small catchment‐scale temperature and precipitation patterns needed for flow simulations. Further research on this issue is needed and encouraged. 相似文献
11.
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. 相似文献
12.
We used data from 1960.0, 1970.0, 1980.0, 1990.0, and 2000.0 to study the geomagnetic anomaly field over the Chinese mainland by using the three-dimensional Taylor polynomial (3DTP) and the surface spline (SS) models. To obtain the pure anomaly field, the main field and the induced field of the ionospheric and magnetospheric fields were removed from measured data. We also compared the SS model anomalies and the data obtained with Kriging interpolation (KI). The geomagnetic anomaly distribution over the mainland was analyzed based on the SS and 3DTP models by transferring all points from 1960.0–1990.0 to 2000.0. The results suggest that the total intensity F anomalies estimated based on the SS and KI for each year are basically consistent in distribution and intensity. The anomalous distributions in the X-, Y-, and Z-direction and F are mainly negative. The 3DTP model anomalies suggest that the intensity in the X-direction increases from ?100 nT to 0 nT with longitude, whereas the intensity in the Y-direction decreases from 400 nT to 20 nT with longitude and over the eastern mainland is almost negative. The intensity in the Z-direction and F are very similar and in most areas it is about ?50nT and higher in western Tibet. The SS model anomalies overall reflect the actual distribution of the magnetic field anomalies; however, because of the uneven distribution of measurements, it yields several big anomalies. Owing to the added altitude term, the 3DTP model offers higher precision and is consistent with KI. 相似文献
13.
用稳定同位素方法估算大型浅水湖泊蒸发量——以太湖为例 总被引：2，自引：1，他引：1
湖泊蒸发量的准确估算对于水文学、气象学和湖泊学等研究有重要的意义.基于2013-2015年太湖水量收支资料、气象观测数据和稳定同位素观测资料,采用稳定同位素质量守恒模型、水量平衡法和Priestley-Taylor模型估算太湖蒸发量,分析太湖蒸发量的季节变化和年际变化特征,并以Priestley-Taylor模型结果为参考值,评价水量平衡法和同位素质量守恒方程的计算精度.结果表明:5-9月太湖蒸发量较高,冬季最低.2013-2015年太湖年总蒸发量分别为1069、894和935 mm,蒸发量的年际变化受到天气条件的影响.2013年12月2014年11月期间,用Priestley-Taylor模型计算的湖泊蒸发量为885 mm;同位素质量守恒模型的估算结果较一致,为893 mm;而水量平衡方程的估算结果明显偏高,为1247 mm. 相似文献
14.
Mountain water resources management often requires hydrological models that need to handle both snow and ice melt. In this study, we compared two different model types for a partly glacierized watershed in central Switzerland: (1) an energy‐balance model primarily designed for snow simulations; and (2) a temperature‐index model developed for glacier simulations. The models were forced with data extrapolated from long‐term measurement records to mimic the typical input data situation for climate change assessments. By using different methods to distribute precipitation, we also assessed how various snow cover patterns influenced the modelled runoff. The energy‐balance model provided accurate discharge estimations during periods dominated by snow melt, but dropped in performance during the glacier ablation season. The glacier melt rates were sensitive to the modelled snow cover patterns and to the parameterization of turbulent heat fluxes. In contrast, the temperature‐index model poorly reproduced snow melt runoff, but provided accurate discharge estimations during the periods dominated by glacier ablation, almost independently of the method used to distribute precipitation. Apparently, the calibration of this model compensated for the inaccurate precipitation input with biased parameters. Our results show that accurate estimates of snow cover patterns are needed either to correctly constrain the melt parameters of the temperature‐index model or to ensure appropriate glacier surface albedos required by the energy‐balance model. Thus, particularly when only distant meteorological stations are available, carefully selected input data and efficient extrapolation methods of meteorological variables improve the reliability of runoff simulations in high alpine watersheds. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
15.
Soil evaporation in arid and semi-arid regions is generally moisture-limited. Evaporation in these regions is expected to increase monotonically with increase in precipitation. In contrast, model simulations in a snow-dominated, semi-arid Reynolds Mountain East (RME) watershed point to the existence of an anomalous trend in soil evaporation. Results indicate that soil evaporation in snow-dominated watersheds first increases and then subsequently decreases with increasing precipitation. The anomalous variation is because of two competing evaporation controls: (a) higher soil moisture in wetter years which leads to larger evaporation, and (b) prolonged snow cover period in wetter years which shields the soil from the atmosphere, thus reducing soil evaporation. To further evaluate how the competition is mediated by meteorological and hydrogeological characteristics of the watershed, changes in the trend due to different watershed hydraulic conductivity, vegetation cover, and snowfall area fraction are systematically studied. Results show considerable persistence in the anomalous trend over a wide range of controls. The controlling factors, however, have significant influence both on the magnitude of the WY evaporation and the location of the inflection point in the trend curve. 相似文献
16.
利用长江上游最近30年(66个测站)蒸发皿蒸发量和最近50年(90个测站)的7种气象要素,分析了蒸发皿蒸发量的区域变化趋势和影响蒸发皿蒸发量变化的因素;针对7个水文站的年径流量变化,探讨了蒸发皿蒸发量变化后对水分循环的影响.结果表明,长江上游蒸发皿蒸发量的变化可以划分为三个分区,研究区域东西两侧(青藏高原和大巴山一带)为显著减少区,分别命名为RⅠ和RⅡ,中间(云贵高原北部到黄土高原南缘以及由二者包围的四川盆地一带)为显著增大区,命名为RⅢ区.影响区域蒸发皿蒸发量变化的原因各有不同,青藏高原一带(RⅠ区)蒸发皿蒸发量减少的原因可归结于太阳辐射强度和风动力扰动减弱所致.大巴山一带(RⅡ区)减少原因是太阳辐射强度、风动力扰动强度、湿度条件都在显著下降所引起的.云贵高原到四川盆地一带(RⅢ区)蒸发皿蒸发量增加是环境气温强烈升高,导致其上空大气水汽含量显著减少,大气很干燥,引发蒸发过程加强所致.蒸发皿蒸发量发生变化的直接后果就是导致水分循环强弱发生变化,对于RⅠ区,尽管蒸发皿蒸发量减少,由于降水量和径流量增加的作用,这一区域的水分循环有所加强.在RⅡ区,降水量、径流量和蒸发量都在减少,因此RⅡ区水分循环显著减弱.在RⅢ区,降水量和径流量同时减少,而蒸发量增大,水量消耗增大,因此RⅢ区水分循环有减弱趋势. 相似文献
17.
Marzieh Mortezapour Brian Menounos Peter L. Jackson Andre R. Erler Ben M. Pelto 《水文研究》2020,34(25):5085-5103
Glaciers are commonly located in mountainous terrain subject to highly variable meteorological conditions. High resolution meteorological (HRM) data simulated by atmospheric models can complement meteorological station observations in order to assess changes in glacier energy fluxes and mass balance. We examine the performance of two snow models, SnowModel and Alpine3D, forced by different meteorological data for winter mass balance simulations at four glaciers in the Canadian portion of the Columbia Basin. The Weather Research and Forecasting model (WRF) with resolution of 1 km and the North American Land Data Assimilation System with ~12 km resolution, provide HRM data for the two snow models. Evaluation is based on the ability of the snow models to simulate snow depth at both point locations (automated snow weather stations) and over the entire glacier surface (airborne LiDAR [Light Detection and Ranging] surveys) during the 2015/2016 winter accumulation. When forced with HRM data, both models can reproduce snow depth to within ±15% of observed values. Both models underestimate winter mass balance when forced by HRM data. When driven with WRF data, SnowModel underestimates winter mass balance integrated over the glacier area by 1 and 10%, whilst Alpine3D underestimates winter mass balance by 12 and 22% compared with LiDAR and stake measurements, respectively. The overall results show that SnowModel forced by WRF simulated winter mass balance the best. 相似文献
18.
In order to study the sensitivity of snow cover to changes in meteorological variables at a regional scale, a numerical snow model and an analysis system of the meteorological conditions adapted to relief were used. This approach has been successfully tested by comparing simulated and measured snow depth at 37 sites in the French Alps during a ten year data period. Then, the sensitivity of the snow cover to a variation in climatic conditions was tested by two different methods, which led to very similar results. To assess the impact of a particular “doubled CO2” scenario, coherent perturbations were introduced in the input data of the snow model. It was found that although the impact would be very pronounced, it would also be extremely differentiated, dependent on the internal state of the snow cover. The most sensitive areas are the elevations below 2400 m, especially in the southern part of the French Alps. 相似文献
19.
Evaporation modelling by heuristic regression approaches using only temperature data 总被引：1，自引：1，他引：0
Accurate estimation of pan evaporation (Epan) is very important in water resources management, irrigation scheduling and water budget of lakes. This study investigates the accuracy of two heuristic regression approaches, multivariate adaptive regression splines (MARS) and M5 model tree (M5Tree) in estimating pan evaporation using only temperature data as input. Monthly minimum temperature, maximum temperature and Epan data from three Turkish stations were used, with month number (periodicity information) added as input to see its effect on estimation accuracy. The models were compared with the calibrated Hargreaves-Samani (CHS), Stephens-Stewart (SS) and multiple linear regression methods. Three different train-test splitting strategies (50%–50%, 60%–40% and 75%–25%) were employed for better evaluation of the applied methods. The results show that the MARS method generally estimated monthly Epan with higher accuracy compared to the M5Tree, CHS and SS methods. When extraterrestrial radiation, calculated from Julian date and latitude information, was used as input to the SS instead of solar radiation, satisfactory estimates were obtained. A positive effect on model accuracy was observed when involving periodicity information in inputs and increasing training data length. 相似文献
20.
This paper proposes a simple class of threshold autoregressive model for purpose of forecasting daily maximum ozone concentrations
in Southern California. Linear time series model has been widely considered in environmental modeling. However, this class
of models fails to capture the nonlinearity in ozone process and the complexity of meteorological interactions with ozone.
In this article, we used the threshold autoregressive models with two classes of regimes; periodic and meteorological regimes.
Days in week were used for the periodic regimes and the regression tree method was used to define the regimes as a function
of meteorological variables. As the reference model we used the autoregressive model with lagged ozone and various lagged
meteorological variables as the covariates. The proposed models were applied to a 3-year dataset of daily maximum ozone concentrations
obtained from five monitoring stations in San Bernardino County, CA and their forecast performances were evaluated using an
independent year-long dataset from the same stations. The results showed that the threshold models well capture the nonlinearity
in ozone process and remove the nonstationarity in model residuals. The threshold models outperformed the non-threshold autoregressive
models in day-ahead forecasts. The tree-based model showed slightly better performance than the periodic threshold model. 相似文献