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1.
Soil erosion caused by water flow is a complex problem. Both empirical and physically based approaches were used for the estimation of surface erosion rates. Their applications are mainly limited to experimental areas or laboratory studies. The maximum sediment concentration overland flow can carry is not considered in most of the existing surface erosion models. The lack of erosion capacity limitation may cause over estimations of sediment concentration. A correlation analysis is used in this study to determine significant factors that impact surface erosion capacity. The result shows that the unit stream power is the most dominant factor for overland flow erosion which is consistent with experimental data. A bounded regression formula is used to reflect the limits that sediment concentration cannot be less than zero nor greater than a maximum value. The coefficients used in the model are calibrated using published laboratory data. The computed results agree with laboratory data very well. A one dimensional overland flow diffusive wave model is used in conjunction with the developed soil erosion equation to simulate field experimental results. This study concludes that the non-linear regression method using unit stream power as the dominant factor performs well for estimating overland flow erosion capacity. 相似文献
2.
A rigorous and practical approach for interpretation of impeller flow log data to determine vertical variations in hydraulic conductivity is presented and applied to two well logs from a Chalk aquifer in England. Impeller flow logging involves measuring vertical flow speed in a pumped well and using changes in flow with depth to infer the locations and magnitudes of inflows into the well. However, the measured flow logs are typically noisy, which leads to spurious hydraulic conductivity values where simplistic interpretation approaches are applied. In this study, a new method for interpretation is presented, which first defines a series of physical models for hydraulic conductivity variation with depth and then fits the models to the data, using a regression technique. Some of the models will be rejected as they are physically unrealistic. The best model is then selected from the remaining models using a maximum likelihood approach. This balances model complexity against fit, for example, using Akaike's Information Criterion. 相似文献
3.
Estimation of instantaneous peak flows from maximum mean daily flows using the HBV hydrological model 
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下载免费PDF全文 The record length and quality of instantaneous peak flows (IPFs) have a great influence on flood design, but these high resolution flow data are not always available. The primary aim of this study is to compare different strategies to derive frequency distributions of IPFs using the Hydrologiska Byråns Vattenbalansavdelning (HBV) hydrologic model. The model is operated on a daily and an hourly time step for 18 catchments in the Aller‐Leine basin, Germany. Subsequently, general extreme value (GEV) distributions are fitted to the simulated annual series of daily and hourly extreme flows. The resulting maximum mean daily flow (MDF) quantiles from daily simulations are transferred into IPF quantiles using a multiple regression model, which enables a direct comparison with the simulated hourly quantiles. As long climate records with a high temporal resolution are not available, the hourly simulations require a disaggregation of the daily rainfall. Additionally, two calibrations strategies are applied: (1) a calibration on flow statistics; (2) a calibration on hydrographs. The results show that: (1) the multiple regression model is capable of predicting IPFs with the simulated MDFs; (2) both daily simulations with post‐correction of flows and hourly simulations with pre‐processing of precipitation enable a reasonable estimation of IPFs; (3) the best results are achieved using disaggregated rainfall for hourly modelling with calibration on flow statistics; and (4) if the IPF observations are not sufficient for model calibration on flow statistics, the transfer of MDFs via multiple regressions is a good alternative for estimating IPFs. Copyright © 2015 John Wiley & Sons, Ltd. 相似文献
4.
The impact force on retaining structure, which is caused by granular flow comprised of dry particles originated from shallow landslide failure, still lacks systematic studies. In order to support the potential design requirement of structure used to resist this kind of impact, a series of dry granular impact experiments are conducted on one rigid barrier model. According to parametric analysis results, one nonlinear regression model is proposed to correlate total normal impact force at critical time (Fcr) with its influential parameters. Further, we complete a systematic statistics analysis and obtain a subsequent optimum regression equation based on the proposed model. According to experience and dimension balance, the equation is modified and finally transformed into one non-dimensional equation, which shows good agreement between predicted and observed results. 相似文献
5.
Estimating the amount of irrigation water is challenging at the catchment scale because of the difficulties in direct measurement and interactions between the flow components. The objectives of the study were to characterize the catchment flows in an agricultural catchment with an irrigation system in subtropical China and to estimate catchment irrigation flow using hydrograph analysis methods. A weighting model and multiple regression models were established to estimate catchment irrigation outflow according to the hydrographs of the inflows and outflows of the catchment. The multiple regression models took into consideration the drainage time of base flow, resulting in better estimation on an event and annual basis. Using the MR‐6d method, the estimated irrigation outflows amounted to 3700 mm, 2600 mm and 2760 mm during 2001, 2002 and 2003 respectively, which covered 70%, 60% and 64% respectively of the total catchment outflows in the corresponding years. Copyright © 2007 John Wiley & Sons, Ltd. 相似文献
6.
The primary purpose of this study is to develop regional models of the lower part of flow duration curves (LPFDCs) to synthesize low‐flow characteristics at ungauged sites in southern Taiwan. Because of the close relationship between low streamflow regimes and hydrogeological features, the model development first involved delimiting homogeneous hydrogeological regions by using two‐step cluster analysis. Each homogeneous region was then discriminated by an equation developed on the basis of its hydrogeological features, which was then used to determine which of three sets of regional LPFDC models would be appropriate for a particular ungauged site. Each of the three sets of regional LPFDC models were developed using both conventional multivariate statistical regression and fuzzy regression. Thirty‐four stream‐gauged watersheds located in southern Taiwan provide the data set. The study results reveal that the regional LPFDC models developed in this study could be applied reasonably at ungauged sites. Copyright © 2002 John Wiley & Sons, Ltd. 相似文献
7.
Identifying physical catchment processes from streamflow data, such as quick- and slow-flow paths, remains challenging. This study is designed to explore whether a flexible nonparametric regression model (generalized additive model, GAM) can be used to infer different flow paths. This assumes that the data relationship in data-driven models is also a reflection of catchment physical processes. The GAM, using time-lagged flow covariates, was fitted to synthetic rainfall–runoff data simulated using simple linear reservoirs. Partial plots of the time-lagged covariates show that the model could differentiate simple and more complex flow paths in simulated synthetic data with short and long memory systems and varying between dry and wet climates. Further analysis of data from real catchments showed that the model could differentiate catchments dominated by slow flow and by quick flow. Therefore, this study indicates that GAM can be used to identify catchment storages and delay processes from streamflow data. 相似文献
8.
It is known that construction of large sewers based on consideration of flow with non-deposition without a bed deposit is not economical. Sewer design based on consideration of flow with non-deposition with a bed deposit reduces channel bed slope and construction cost in which the presence of a small depth of sediment deposition on the bed increases the sediment transport capacity of the flow. This paper suggests a new Pareto-optimal model developed by the multigene genetic programming (MGGP) technique to estimate particle Froude number (Frp) in large sewers with conditions of sediment deposition on the bed. To this end, four data sets including wide ranges of sediment size and concentration, deposit thickness, and pipe size are used. On the basis of different statistical performance indices, the efficiency of the proposed Pareto-optimal MGGP model is compared to those of the best MGGP model developed in the current study as well as the conventional regression models available in the literature. The results indicate the higher efficiency of the MGGP-based models for Frp estimation in the case of no additional deposition onto a bed with a sediment deposit. Inasmuch as the Pareto-optimal MGGP model utilizes a lower number of input parameters to yield comparatively higher performance than the conventional regression models, it can be used as a parsimonious model for self-cleansing design of large sewers in practice. 相似文献
9.
《水文科学杂志》2013,58(3):365-370
Abstract Gauging stations where the stage—discharge relationship is affected by hysteresis due to unsteady flow represent a challenge in hydrometry. In such situations, the standard hydrometric practice of fitting a single-valued rating curve to the available stage—discharge measurements is inappropriate. As a solution to this problem, this study provides a method based on the Jones formula and nonlinear regression, which requires no further data beyond the available stage—discharge measurements, given that either the stages before and after each measurement are known along with the duration of each measurement, or a stage hydrograph is available. The regression model based on the Jones formula rating curve is developed by applying the monoclinal rising wave approximation and the generalized friction law for uniform flow, along with simplifying assumptions about the hydraulic and geometric properties of the river channel in conjunction with the gauging station. Methods for obtaining the nonlinear least-squares rating-curve estimates, while factoring in approximated uncertainty, are discussed. The broad practical applicability and appropriateness of the method are demonstrated by applying the model to: (a) an accurate, comprehensive and detailed database from a hydropower-generated highly dynamic flow in the Chattahoochee River, Georgia, USA; and (b) data from gauging stations in two large rivers in the USA affected by hysteresis. It is also shown that the model is especially suitable for post-modelling hydraulic and statistical validation and assessment. 相似文献
10.
Sensitivity analysis of the probability distribution of groundwater level series based on information entropy 总被引：2，自引：2，他引：0
Xiankui Zeng Dong Wang Jichun Wu 《Stochastic Environmental Research and Risk Assessment (SERRA)》2012,26(3):345-356
Information entropy is an effective method to analyze uncertainty in various processes. The principle of maximum entropy (POME)
provides a guide line for the parameter estimation of probability density function (PDF). Mutual entropy analysis is well
qualified for delineating the nonlinear and complex multivariable relationship. The probability distribution of model output
is the element of model uncertainty analysis. In this paper, a synthetic groundwater flow field is build to produce groundwater
level series (GLS). The probability distribution of GLS is obtained by the frequency analysis method based on POME and Chi-Squared
test. The important uncertainty factors that affect the parameters of PDF of GLS are assessed by the sensitivity analysis
methods, which include stepwise regression analysis and mutual entropy analysis. Results of this analysis indicate that most
of the GLS follow normal distribution (or log-normal distribution), while a few obey others. The mean and variance of normal
GLS are affected differently by the input variables of groundwater model. Mutual entropy analysis is more competitive and
appropriate for delineating the nonlinear and nonmonotonic multivariable relationship than stepwise regression analysis. 相似文献
11.
Stream‐flow recessions are commonly characterized by the exponential equation or in the alternative power form equation of a single linear reservoir. The most common measure of recession is the recession constant K, which relates to the power function form of the recession equation for a linear reservoir. However, in reality it can be seen that the groundwater dynamics of even the simplest of aquifers may behave in a non‐linear fashion. In this study three different storage–outflow algorithms; single linear, non‐linear and multiple linear reservoir were considered to model the stream‐flow recession of the upper Blue Nile. The recession parameters for the linear and non‐linear models were derived by the use of least‐squares regression procedures. Whereas, for the multiple linear reservoir model, a second‐order autoregressive AR (2) model was applied first in order to determine the parameters by the least‐squares method. The modelling of the upper Blue Nile recession flow performed shortly after the wet season, when interflow and bank storage may be contributing considerably to the river flow, showed that the non‐linear reservoir model simulates well with the observed counterparts. The variation related to preceding flow on a recession parameter of the non‐linear reservoir remains significant, which was obtained by stratification of the recession curves. Although a similar stratification did not show any systematic variation on the recession parameters for the linear and multiple linear reservoir models. Copyright © 2004 John Wiley & Sons, Ltd. 相似文献
12.
Peak flow rate from watersheds is an important criterion used to develop soil conservation plans and to design engineering projects. A peak flow rate equation used in the CREAMS model, with four parameters, can be employed to predict peak flow rate. The purpose of this study was to test and improve this equation of peak flow rate in CREAMS for use on the Loess Plateau of China. Data from 331 storms in 20 small watersheds were used to verify the the peak flow rate equation in CREAMS. The calculated flow rates using the CREAMS equation greatly underestimated the measured peak flows. The model efficiency was only 0·15. Nonlinear regression analysis was then performed to develop a new equation: which gave a model efficiency of 0·94. A second set of data, including 68 storms from four completely different watersheds, was used to test the new equation, with a resultant model efficiency of 0·90. The result has significant implications for improving the design of soil and water supporting practices, for assessing the soil and water resources, and for implementing conservation programmes. Copyright © 2008 John Wiley & Sons, Ltd. 相似文献
13.
14.
Trond Reitan Asgeir Petersen-Øverleir 《Stochastic Environmental Research and Risk Assessment (SERRA)》2006,20(6):445-453
Practical application of the power-law regression model with an unknown location parameter can be plagued by non-finite least squares parameter estimates. This presents a serious problem in hydrology, since stream flow data is mainly obtained using an estimated stage–discharge power-law rating curve. This study provides a set of sufficient requirements for the data to ensure the existence of finite least squares parameter estimates for a power-law regression with an unknown location parameter. It is shown that in practice, these requirements act as necessary for having a finite least squares solution, in most cases. Furthermore, it is proved that there is a finite probability for the model to produce data having non-finite least squares parameter estimates. The implications of this result are discussed in the context of asymptotic predictions, inference and experimental design. A Bayesian approach to the actual regression problem is recommended. 相似文献
15.
Fatih Ünes 《洁净——土壤、空气、水》2010,38(3):296-308
Experimental findings and observations indicate that plunging flow is related to the formation of bed load deposition in dam reservoirs. The sediment delta begins to form in the plunging region where the inflow river water meets the ambient reservoir water. Correct estimation of dam reservoir flow, plunging point, and plunging depth is crucial for dam reservoir sedimentation and water quality issues. In this study, artificial neural network (ANN), multi‐linear regression (MLR), and two‐dimensional hydrodynamic model approaches are used for modeling the plunging point and depth. A multi layer perceptron (MLP) is used as the ANN structure. A two‐dimensional model is adapted to simulate density plunging flow through a reservoir with a sloping bottom. In the model, nonlinear and unsteady continuity, momentum, energy, and k–ε turbulence equations are formulated in the Cartesian coordinates. Density flow parameters such as velocity, plunging points, and plunging depths are determined from the simulation and model results, and these are compared with previous experimental and model works. The results show that the ANN model forecasts are much closer to the experimental data than the MLR and mathematical model forecasts. 相似文献
16.
Assessing the digital filter method for base flow estimation in glacier melt dominated basins 下载免费PDF全文
下载免费PDF全文 Base flow is an important component of streamflow. Although the simple digital filter method is widely used for base flow separation, the applicability in alpine rivers mainly dominated by glacier melt has not been described in detail. To assess and improve the performance of base flow estimates using the filter method for catchments dominated by glacier melt, the enhanced Soil Water Assessment Tool (SWAT) is used to obtain the estimates of streamflow and base flow for three catchments with different glacier melt contribution in arid and cold Northwestern China. The digital filter is then applied to the simulated streamflow to separate base flow and assess how well the base flow by the filter method matches these obtained using the SWAT model. In order to obtain the best match between the base flow by the filter method and those using the SWAT model, the linear regression model is used to estimate the relation between the filtered base flow and the glacier melt. It was found that the filtered base flow was matched well with base flow using the SWAT model during the low‐flow period. However, the base flow based on the digital filter method was overestimated during the high‐flow period, especially for the Manas River and Kumarik River. The base flow indexes by the digital filter estimates were 2.9%, 33.3% and 100% larger than those of the model method for the Gongnaisi River, Manas River and Kumarik River, respectively. The differences are larger with bigger glacier melt contribution. The performance of the digital filter is affected by the glacier melt, and it can be improved significantly by the combination of filtered base flow and the glacier melt. The base flow indexes by the improved filter are 1.5%, 4.4% and 10.7% larger than those of the model method for the Gongnaisi River, Manas River and Kumarik River, respectively. Copyright © 2015 John Wiley & Sons, Ltd. 相似文献
17.
The purpose of this study was to investigate the interacting mechanism between the saltating particles near a channel bed. A three-dimensional real-time flow visualization technique was developed to measure the interparticle collision behaviors during the saltating process. Based on the experimental data, the distribution of the collision points was found to be symmetric. This confirms the assumption that the projections of the collision points onto the reasonable plane are uniformly distributed. A three-dimensional saltating model was also developed. This model produced satisfactory results. The model is able to simulate the continuous saltating trajectories of several particles. The simulated dimensionless saltating height, longitudinal and vertical saltation velocity components were found to increase as the dimensionless particle diameter and the dimensionless flow transport capacity parameter increase, while the simulated lateral saltation velocity component varies inversely with the dimensionless flow transport capacity parameter. A regression equation for the bed load transport rate was also obtained. 相似文献
18.
A comparison is carried out between historical records of the flow measured in Kinneret watershed during and prior to the time of cloud seeding for rainfall enhancement. Precipitation series for the control area of the meteorological experimentation serve as a reference for the comparison. The fluctuations of the flow, which would have occurred unless the effect of the seeding, are estimated by a linear regression on the precipitation as the control. The regression parameters are calibrated separately for the unseeded and for the seeded time series. The model with the parameters calibrated for the unseeded series is applied on the rainfall recorded during the seeded time, and vice versa. The difference between the measured and the computed data is attributed to the effect of cloud seeding. Similar comparisons are carried out with respect to rainfall series recorded at the target area and at the edge of the enhanced area.The results indicate that the flow from the affected sector of the watershed has been enhanced, with respect to the control, by 31×106
m
3/year, at a significance level of 31. This enhancement is 5% of the volume which is generated in that area. The rates found with respect to the rainfall at the edge are higher than those found with respect to the control, while those with respect to the rainfall at the center of the target area are lower. 相似文献
19.
Top‐kriging is a method for estimating stream flow‐related variables on a river network. Top‐kriging treats these variables as emerging from a two‐dimensional spatially continuous process in the landscape. The top‐kriging weights are estimated by regularising the point variogram over the catchment area (kriging support), which accounts for the nested nature of the catchments. We test the top‐kriging method for a comprehensive Austrian data set of low stream flows. We compare it with the regional regression approach where linear regression models between low stream flow and catchment characteristics are fitted independently for sub‐regions of the study area that are deemed to be homogeneous in terms of flow processes. Leave‐one‐out cross‐validation results indicate that top‐kriging outperforms the regional regression on average over the entire study domain. The coefficients of determination (cross‐validation) of specific low stream flows are 0.75 and 0.68 for the top‐kriging and regional regression methods, respectively. For locations without upstream data points, the performances of the two methods are similar. For locations with upstream data points, top‐kriging performs much better than regional regression as it exploits the low flow information of the neighbouring locations. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献
20.
We examine the low flow records for six urbanized watersheds in the Maryland Piedmont region and develop regression equations to predict annual minimum low flow events. The effects of both future climate (based on precipitation and temperature projections from two climate models: Hadley and the Canadian Climate Centre (CCC)) and land use change are incorporated to illustrate possible future trends in low flows. A regression modelling approach is pursued to predict the minimum annual 7‐day low flow estimates for the proposed future scenarios. A regional regression model was calibrated with between 10 and 50 years of daily precipitation, daily average temperature, annual imperviousness, and the daily observed flow time‐series across six watersheds. Future simulations based on a 55 km2 urbanizing watershed just north of Washington, DC, were performed. When land use and climate change were employed singly, the former predicted no trends in low flows and the latter predicted significant increasing trends under Hadley and no trends under CCC. When employed jointly, however, low flows were predicted to decrease significantly under CCC, whereas Hadley predicted no significant trends in low flows. Antecedent precipitation was the most influential predictor on low flows, followed by urbanization. Copyright © 2006 John Wiley & Sons, Ltd. 相似文献