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1.
Reservoir operation is generally based on the inflows of the upstream catchment of the reservoir. If the arriving inflows can be forecasted, that can benefit reservoir operation and management. This study attempts to construct a long‐term inflow‐forecasting model by combining a continuous rainfall–runoff model with the long‐term weather outlook from the Central Weather Bureau of Taiwan. The analytical results demonstrate that the continuous rainfall–runoff model has good inflow simulation performance by using 10‐day meteorological and inflow records over a 33‐year period for model calibration and verification. The long‐term inflow forecasting during the dry season was further conducted by combining the continuous rainfall–runoff model and the long‐term weather outlook, which was found to have good performance. Copyright © 2005 John Wiley & Sons, Ltd. 相似文献
2.
The objective of this paper is to investigate the variation of geomorphology and runoff characteristics in saturated areas under different partial contributing area (PCA) conditions. Geomorphologic information and hydrologic records from two mid‐size watersheds in northern Taiwan were selected for analysis. The PCA ratio in the watershed during a storm was assumed equal to the ratio of the surface‐flow volume to the direct runoff volume from measured hydrologic data. The extents of PCA regions were then determined by using a topographic‐index threshold. Consequently, the geomorphologic factors in saturated and unsaturated areas could be calculated using a digital elevation model, and these factors could then be linked to a geomorphology‐based IUH model for runoff simulation, which can consider both the surface‐ and subsurface‐flow processes in saturated and unsaturated areas, respectively. The results show that geomorphologic characteristics in the saturated areas vary significantly with different PCA ratios especially for higher order streams. A large PCA ratio results in a sharp hydrograph because the quick surface flow dominates the runoff process, whereas the hydrologic response in a low PCA case is dominated by the delayed subsurface flow. Copyright © 2007 John Wiley & Sons, Ltd. 相似文献
3.
This study investigates how medium‐term gully‐development data differ from short‐term data, and which factors influence their spatial and temporal variability at nine selected actively retreating bank gullies situated in four Spanish basin landscapes. Small‐format aerial photographs using unmanned, remote‐controlled platforms were taken at the gully sites in short‐term intervals of one to two years over medium‐term periods of seven to 13 years and gully change during each period was determined using stereophotogrammetry and a geographic information system. Results show a high variability of annual gully retreat rates both between gullies and between observation periods. The mean linear headcut retreat rates range between 0·02 and 0·26 m a–1. Gully area loss was between 0·8 and 22 m² a–1 and gully volume loss between 0·5 to 100 m³ a–1, of which sidewall erosion may play a considerable part. A non‐linear relationship between catchment area and medium‐term gully headcut volume change was found for these gullies. The short‐term changes observed at the individual gullies show very high variability: on average, the maximum headcut volume change observed in 7–13 years was 14·3 times larger than the minimum change. Dependency on precipitation varies but is clearly higher for headcuts than sidewalls, especially in smaller and less disturbed catchments. The varying influences of land use and human activities with their positive or negative effects on runoff production and connectivity play a dominant role in these study areas, both for short‐term variability and medium‐term difference in gully development. The study proves the value of capturing spatially continuous, high‐resolution three‐dimensional data using small‐format aerial photography for detailed gully monitoring. Results confirm that short‐term data are not representative of longer‐term gully development and demonstrate the necessity for medium‐ to long‐term monitoring. However, short‐term data are still required to understand the processes – particularly human activity at varying time scales – causing fluctuations in gully erosion rates. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
4.
Adjusting wavelet‐based multiresolution analysis boundary conditions for long‐term streamflow forecasting 
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下载免费PDF全文 We propose a novel technique for improving a long‐term multi‐step‐ahead streamflow forecast. A model based on wavelet decomposition and a multivariate Bayesian machine learning approach is developed for forecasting the streamflow 3, 6, 9, and 12 months ahead simultaneously. The inputs of the model utilize only the past monthly streamflow records. They are decomposed into components formulated in terms of wavelet multiresolution analysis. It is shown that the model accuracy can be increased by using the wavelet boundary rule introduced in this study. A simulation study is performed to evaluate the effects of different wavelet boundary rules using synthetic and real streamflow data from the Yellowstone River in the Uinta Basin in Utah. The model based on the combination of wavelet and Bayesian machine learning regression techniques is compared with that of the wavelet and artificial neural networks‐based model. The robustness of the models is evaluated. Copyright © 2015 John Wiley & Sons, Ltd. 相似文献
5.
This paper analyses the skills of fuzzy computing based rainfall–runoff model in real time flood forecasting. The potential of fuzzy computing has been demonstrated by developing a model for forecasting the river flow of Narmada basin in India. This work has demonstrated that fuzzy models can take advantage of their capability to simulate the unknown relationships between a set of relevant hydrological data such as rainfall and river flow. Many combinations of input variables were presented to the model with varying structures as a sensitivity study to verify the conclusions about the coherence between precipitation, upstream runoff and total watershed runoff. The most appropriate set of input variables was determined, and the study suggests that the river flow of Narmada behaves more like an autoregressive process. As the precipitation is weighted only a little by the model, the last time‐steps of measured runoff are dominating the forecast. Thus a forecast based on expected rainfall becomes very inaccurate. Although good results for one‐step‐ahead forecasts are received, the accuracy deteriorates as the lead time increases. Using the one‐step‐ahead forecast model recursively to predict flows at higher lead time, however, produces better results as opposed to different independent fuzzy models to forecast flows at various lead times. Copyright © 2004 John Wiley & Sons, Ltd. 相似文献
6.
The primary objective of this study is to investigate the possibility of including more temporal and spatial information on short‐term inflow forecasting, which is not easily attained in the traditional time‐series models or conceptual hydrological models. In order to achieve this objective, an artificial neural network (ANN) model for short‐term inflow forecasting is developed and several issues associated with the use of an ANN model are examined in this study. The formulated ANN model is used to forecast 1‐ to 7‐h ahead inflows into a hydropower reservoir. The root‐mean‐squared error (RMSE), the Nash–Sutcliffe coefficient (NSC), the A information criterion (AIC), B information criterion (BIC) of the 1‐ to 7‐h ahead forecasts, and the cross‐correlation coefficient between the forecast and observed inflows are estimated. Model performance is analysed and some quantitative analysis is presented. The results obtained are satisfactory. Perceived strengths of the ANN model are the capability for representing complex and non‐linear relationships as well as being able to include more information in the model easily. Although the results obtained may not be universal, they are expected to reveal some possible problems in ANN models and provide some helpful insights in the development and application of ANN models in the field of hydrology and water resources. Copyright © 2002 John Wiley & Sons, Ltd. 相似文献
7.
Jan F. Adamowski 《水文研究》2008,22(25):4877-4891
In this study, short‐term river flood forecasting models based on wavelet and cross‐wavelet constituent components were developed and evaluated for forecasting daily stream flows with lead times equal to 1, 3, and 7 days. These wavelet and cross‐wavelet models were compared with artificial neural network models and simple perseverance models. This was done using data from the Skrwa Prawa River watershed in Poland. Numerical analysis was performed on daily maximum stream flow data from the Parzen station and on meteorological data from the Plock weather station in Poland. Data from 1951 to 1979 was used to train the models while data from 1980 to 1983 was used to test the models. The study showed that forecasting models based on wavelet and cross‐wavelet constituent components can be used with great accuracy as a stand‐alone forecasting method for 1 and 3 days lead time river flood forecasting, assuming that there are no significant trends in the amplitude for the same Julian day year‐to‐year, and that there is a relatively stable phase shift between the flow and meteorological time series. It was also shown that forecasting models based on wavelet and cross‐wavelet constituent components for forecasting river floods are not accurate for longer lead time forecasting such as 7 days, with the artificial neural network models providing more accurate results. Copyright © 2008 John Wiley & Sons, Ltd. 相似文献
8.
River temperature regimes of England and Wales: spatial patterns,inter‐annual variability and climatic sensitivity 下载免费PDF全文
下载免费PDF全文 Identification of the most sensitive hydrological regions to a changing climate is essential to target adaptive management strategies. This study presents a quantitative assessment of spatial patterns, inter‐annual variability and climatic sensitivity of the shape (form) and magnitude (size) of annual river/stream water temperature regimes across England and Wales. Classification of long‐term average (1989–2006) annual river (air) temperature regime dynamics at 88 (38) stations within England and Wales identified spatially differentiable regions. Emergent river temperature regions were used to structure detailed hydroclimatological analyses of a subset of 38 paired river and air temperature stations. The shape and magnitude of air and water temperature regimes were classified for individual station‐years; and a sensitivity index (SI, based on conditional probability) was used to quantify the strength of associations between river and air temperature regimes. The nature and strength of air–river temperature regime links differed between regions. River basin properties considered to be static over the timescale of the study were used to infer modification of air–river temperature links by basin hydrological processes. The strongest links were observed in regions where groundwater contributions to runoff (estimated by basin permeability) were smallest and water exposure time to the atmosphere (estimated by basin area) was greatest. These findings provide a new large‐scale perspective on the hydroclimatological controls driving river thermal dynamics and, thus, yield a scientific basis for informed management and regulatory decisions concerning river temperature within England and Wales. © 2013 The Authors. Hydrological Processes published by John Wiley & Sons, Ltd. 相似文献
9.
Global sensitivity analysis is a useful tool to understand process‐based ecosystem models by identifying key parameters and processes controlling model predictions. This study reported a comprehensive global sensitivity analysis for DRAINMOD‐FOREST, an integrated model for simulating water, carbon (C), and nitrogen (N) cycles and plant growth in lowland forests. The analysis was carried out for multiple long‐term model predictions of hydrology, biogeochemistry, and plant growth. Results showed that long‐term mean hydrological predictions were highly sensitive to several key plant physiological parameters. Long‐term mean annual soil organic C content and mineralization rate were mainly controlled by temperature‐related parameters for soil organic matter decomposition. Mean annual forest productivity and N uptake were found to be mainly dependent upon plant production‐related parameters, including canopy quantum use efficiency and carbon use efficiency. Mean annual nitrate loss was highly sensitive to parameters controlling both hydrology and plant production, while mean annual dissolved organic nitrogen loss was controlled by parameters associated with its production and physical sorption. Parameters controlling forest production, C allocation, and specific leaf area highly affected long‐term mean annual leaf area. Results of this study could help minimize the efforts needed for calibrating DRAINMOD‐FOREST. Meanwhile, this study demonstrates the critical role of plants in regulating water, C, and N cycles in forest ecosystems and highlights the necessity of incorporating a dynamic plant growth model for comprehensively simulating hydrological and biogeochemical processes. Copyright © 2013 John Wiley & Sons, Ltd. 相似文献
10.
The Budyko formula for estimating the long‐term average annual evaporation is applied to calculate the long‐term water balance in 29 humid watersheds of southern China. As a result of overestimation of evaporation, the long‐term average annual runoff is underestimated, with the Nash‐Sutcliffe efficiency (NSE) at just ? 17%. A one‐variable linear regression model is employed to find that the Budyko scatter and the relative errors of Budyko runoff and evaporation estimates are all closely related to the long‐term aridity index. Through combining the original Budyko formula with the different linear regression models for estimating the Budyko estimation errors, three forms of revised Budyko equation for estimating the long‐term average annual runoff are derived, with all their NSE values to be around 66%. After calibration, both one‐parameter Turc‐Pike and one‐parameter Fu equations lead to the NSE value of 60% in estimating long‐term average annual runoff. Two conclusions are made, with the first one being that, the nonparametric Budyko formula, although very intuitive and very simple, does not apply well in calculating long‐term water balance in 29 humid watersheds in southern China. The second one is that, the parametric evaporation formulae, with locally optimized parameter values, can achieve better accuracy in estimating long‐term average annual evaporation and runoff than the nonparametric Budyko evaporation formula. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
11.
A degree‐day‐based model is presented for a 1 year ahead runoff forecast, with 1 day time steps. The input information is a single snowpack evaluation collected at the beginning of the snowmelt season. The snow‐cover dynamics, the key information for long‐term snowmelt forecast, are described by the snow‐line dynamics, i.e. by the movements of the downhill snowpack limit. The snowmelt volume, estimated by the snow‐line dynamics, is the exogenous input of an autoregressive transformation model. The model is calibrated by a least‐squares procedure on the basis of observed daily runoff data and the corresponding measurements of the snowpack volume (one measurement per year). A real‐world case study on the Alto Tunuyan River basin (2380 km2, Argentinean Andes) is presented. The 1 year ahead Alto Tunuyan River runoff patterns, computed for both calibration and validation periods, reveal high agreement with observed streamflows. Copyright © 2004 John Wiley & Sons, Ltd. 相似文献
12.
AbstractAn artificial neural network, mid- to long-term runoff forecasting model of the Nenjiang basin was established by deciding predictors using the physical analysis method, combined with long-term hydrological and meteorological information. The forecasting model was gradually improved while considering physical factors, such as the main flood season and non-flood season by stage, runoff sources and hydrological processes. The average relative errors in the simulation tests of the prediction model were 0.33 in the main flood season and 0.26 in the non-flood season, indicating that the prediction accuracy during the non-flood season was greater than that in the main flood season. Based on these standards, forecasting accuracy evaluation was conducted by comparing forecasting results with actual conditions: for 2001 to 2003 data, the pass rate of forecasting in the main flood season was 50%, while it was 93% in the non-flood season; for 2001–2010, the respective values were 45% and 72%. The accuracy of prediction was found to decrease as the length of record increases.Editor D. Koutsoyiannis, Associate editor A. ViglioneCitation Li, H.-Y. Tian, L., Wu, Y., and Xie, M., 2013. Improvement of mid- to long-term runoff forecasting based on physical causes: application in Nenjiang basin, China. Hydrological Sciences Journal, 58 (7), 1414–1422. 相似文献
13.
Various types of neural networks have been proposed in previous papers for applications in hydrological events. However, most of these applied neural networks are classified as static neural networks, which are based on batch processes that update action only after the whole training data set has been presented. The time variate characteristics in hydrological processes have not been modelled well. In this paper, we present an alternative approach using an artificial neural network, termed real‐time recurrent learning (RTRL) for stream‐flow forecasting. To define the properties of the RTRL algorithm, we first compare the predictive ability of RTRL with least‐square estimated autoregressive integrated moving average models on several synthetic time‐series. Our results demonstrate that the RTRL network has a learning capacity with high efficiency and is an adequate model for time‐series prediction. We also investigated the RTRL network by using the rainfall–runoff data of the Da‐Chia River in Taiwan. The results show that RTRL can be applied with high accuracy to the study of real‐time stream‐flow forecasting networks. Copyright © 2002 John Wiley & Sons, Ltd. 相似文献
14.
This paper presents the application of a multimodel method using a wavelet‐based Kalman filter (WKF) bank to simultaneously estimate decomposed state variables and unknown parameters for real‐time flood forecasting. Applying the Haar wavelet transform alters the state vector and input vector of the state space. In this way, an overall detail plus approximation describes each new state vector and input vector, which allows the WKF to simultaneously estimate and decompose state variables. The wavelet‐based multimodel Kalman filter (WMKF) is a multimodel Kalman filter (MKF), in which the Kalman filter has been substituted for a WKF. The WMKF then obtains M estimated state vectors. Next, the M state‐estimates, each of which is weighted by its possibility that is also determined on‐line, are combined to form an optimal estimate. Validations conducted for the Wu‐Tu watershed, a small watershed in Taiwan, have demonstrated that the method is effective because of the decomposition of wavelet transform, the adaptation of the time‐varying Kalman filter and the characteristics of the multimodel method. Validation results also reveal that the resulting method enhances the accuracy of the runoff prediction of the rainfall–runoff process in the Wu‐Tu watershed. Copyright © 2004 John Wiley & Sons, Ltd. 相似文献
15.
The effects of land‐use changes on the runoff process in the midstream plain of this arid inland river basin are a key factor in the rational allocation of water resources to the middle and lower reaches. The question is whether and by how much increasingly heavy land use impacts the hydrological processes in such an arid inland river basin. The catchment of the Heihe River, one of the largest inland rivers in the arid region of northwest China, was chosen to investigate the hydrological responses to land‐use change. Flow duration curves were used to detect trends and variations in runoff between the upper and lower reaches. Relationships among precipitation, upstream runoff, and hydrological variables were identified to distinguish the effects of climatic changes and upstream runoff changes on middle and downstream runoff processes. The quantitative relation between midstream cultivated land use and various parameters of downstream runoff processes were analysed using the four periods of land‐use data since 1956. The Volterra numerical function relation of the hydrological non‐linear system response was utilized to develop a multifactor hydrological response simulation model based on the three factors of precipitation, upstream runoff, and cultivated land area. The results showed that, since 1967, the medium‐ and high‐coverage natural grassland area in the midstream region has decreased by 80·1%, and the downstream runoff has declined by 27·32% due to the continuous expansion of the cultivated land area. The contribution of cultivated land expansion to the impact on the annual total runoff is 14–31%, on the annual, spring and winter base flow it is 44–75%, and on spring and winter discharge it is 23–64%. Once the water conservation plan dominated by land‐use structural adjustments is implemented over the next 5 years, the mean annual discharge in the lower reach could increase by 8·98% and the spring discharge by 26·28%. This will significantly alleviate the imbalance between water supply and demand in both its quantity and temporal distribution in the middle and lower reaches. Copyright © 2006 John Wiley & Sons, Ltd. 相似文献
16.
Inflow forecasting is essential for decision making on reservoir operation during typhoons. In this paper, a radial basis function (RBF)‐based model with an information processor is proposed for more accurate forecasts of hourly reservoir inflow. Firstly, based on the multilayer perceptron neural (MLP) network, an information processor is developed to pre‐process the typhoon information (namely, typhoon characteristics and rainfall) and to produce forecasts of rainfall. The forecasted rainfall and the observed inflow are then used as input to the RBF‐based model, which is a nonlinear function approximator, to produce forecasts of hourly inflow. For parameter estimation of the RBF‐based model, the fully‐supervised learning algorithm is used. Actual applications of the proposed model are performed to yield 1‐ to 6‐h ahead forecasts of inflow. To assess the improvement due to the use of the typhoon information processor, models without the typhoon information processor are constructed and compared with the proposed model. The results show that the proposed model performs the best and is capable of providing improved forecasts of hourly inflow, especially for long lead‐time. In conclusion, the proposed model with a typhoon information processor can extract useful information from typhoon characteristics and rainfall, and consequently improve the forecasting performance. Copyright © 2009 John Wiley & Sons, Ltd. 相似文献
17.
The retreat of mountain glaciers and ice caps has dominated the rise in global sea level and is likely to remain an import component of eustatic sea‐level rise in the 21st century. Mountain glaciers are critical in supplying freshwater to populations inhabiting the valleys downstream who heavily rely on glacier runoff, such as arid and semi‐arid regions of western China. Owing to recent climate warming and the consequent rapid retreat of many glaciers, it is essential to evaluate the long‐term change in glacier melt water production, especially when considering the glacier area change. This paper describes the structure, principles and parameters of a modified monthly degree‐day model considering glacier area variation. Water balances in different elevation bands are calculated with full consideration of the monthly precipitation gradient and air temperature lapse rate. The degree‐day factors for ice and snow are tuned by comparing simulated variables to observation data for the same period, such as mass balance, equilibrium line altitude and glacier runoff depth. The glacier area–volume scaling factor is calibrated with the observed glacier area change monitored by remote sensing data of seven sub‐basins of the Tarim interior basin. Based on meteorological data, the glacier area, mass balance and runoff are estimated. The model can be used to evaluate the long‐term changes of melt water in all glacierized basins of western China, especially for those with limited observation data. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
18.
The overarching objective of this research was to provide an improved understanding of the role of land use and associated management practices on long‐term water‐driven soil erosion in small agricultural watersheds by coupling the established, physically based, distributed parameter Water Erosion Prediction Project (WEPP) model with long‐term hydrologic, land use and soil data. A key step towards achieving this objective was the development of a detailed methodology for model calibration using physical ranges of key governing parameters such as effective hydraulic conductivity, critical hydraulic shear stress and rill/inter‐rill erodibilities. The physical ranges for these governing parameters were obtained based on in situ observations within the South Amana Sub‐Watershed (SASW) (～26 km2) of the Clear Creek, IA watershed where detailed documentation of the different land uses was available for a period of nearly 100 years. A quasi validation of the calibrated model was conducted through long‐term field estimates of water and sediment discharge at the outlet of SASW and also by comparing the results with data reported in the literature for other Iowa watersheds exhibiting similar biogeochemical properties. Once WEPP was verified, ‘thought experiments’ were conducted to test our hypothesis that land use and associated management practices may be the major control of long‐term erosion in small agricultural watersheds such as SASW. Those experiments were performed using the dominant 2‐year crop rotations in the SASW, namely, fall till corn–no till bean (FTC‐NTB), no till bean–spring till corn (NTB‐STC) and no till corn–fall till bean (NTC‐FTB), which comprised approximately 90% of the total acreage in SASW. Results of this study showed that for all crop rotations, a strong correspondence existed between soil erosion rates and high‐magnitude precipitation events during the period of mid‐April and late July, as expected. The magnitude of this correspondence, however, was strongly affected by the crop rotation characteristics, such as canopy/residue cover provided by the crop, and the type and associated timing of tillage. Tillage type (i.e. primary and secondary tillages) affected the roughness of the soil surface and resulted in increases of the rill/inter‐rill erodibilities up to 35% and 300%, respectively. Particularly, the NTC‐FTB crop rotation, being the most intense land use in terms of tillage operations, caused the highest average annual erosion rate within the SASW, yielding quadrupled erosion rates comparatively to NTB‐STC. The impacts of tillage operation were further exacerbated by the timing of the operations in relation to precipitation events. Timing of operations affected the ‘life‐time’ of residue cover and as a result, the degree of protection that residue cover offers against the water action on the soil surface. In the case of NTC‐FTB crop rotation, dense corn residue stayed on the ground for only 40 days, whereas for the other two rotations, corn residue provided a protective layer for nearly 7 months, lessening thus the degree of soil erosion. The cumulative effects of tillage type and timing in conjunction with canopy/residue cover led to the conclusion that land management practices can significantly amplify or deamplify the impact of precipitation on long‐term soil erosion in small agricultural watersheds. Copyright © 2009 John Wiley & Sons, Ltd. 相似文献
19.
In this paper, the controls of different indicators on the statistical moments (i.e. mean annual flood (MAF), coefficient of variation (CV) and skewness (CS)) of the maximum annual flood records of 459 Austrian catchments are analysed. The process controls are analysed in terms of the correlation of the flood moments within five hydrologically homogeneous regions to two different types of indicators. Indicators of the first type are static catchment attributes, which are associated with long‐term observations such as mean annual precipitation, the base flow index, and the percentage of catchment area covered by a geological unit or soil type. Indicators of the second type are dynamic catchment attributes that are associated with the event scale. Indicators of this type used in the study are event runoff coefficients and antecedent rainfall. The results indicate that MAF and CV are strongly correlated with indicators characterising the hydro‐climatic conditions of the catchments, such as mean annual precipitation, long‐term evaporation and the base flow index. For the catchments analysed, the flood moments are not significantly correlated with static catchment attributes representing runoff generation, such as geology, soil types, land use and the SCS curve number. Indicators of runoff generation that do have significant predictive power for flood moments are dynamic catchment attributes such as the mean event runoff coefficients and mean antecedent rainfall. The correlation analysis indicates that flood runoff is, on average, more strongly controlled by the catchment moisture state than by event rainfall. Copyright © 2008 John Wiley & Sons, Ltd. 相似文献
20.
A rainfall‐runoff model based on an artificial neural network (ANN) is presented for the Blue Nile catchment. The best geometry of the ANN rainfall‐runoff model in terms of number of hidden layers and nodes is identified through a sensitivity analysis. The Blue Nile catchment (about 300 000 km2) in the Nile basin is selected here as a case study. The catchment is classified into seven subcatchments, and the mean areal precipitation over those subcatchments is computed as a main input to the ANN model. The available daily data (1992–99) are divided into two sets for model calibration (1992–96) and for validation (1997–99). The results of the ANN model are compared with one of physical distributed rainfall‐runoff models that apply hydraulic and hydrologic fundamental equations in a grid base. The results over the case study area and the comparative analysis with the physically based distributed model show that the ANN technique has great potential in simulating the rainfall‐runoff process adequately. Because the available record used in the calibration of the ANN model is too short, the ANN model is biased compared with the distributed model, especially for high flows. Copyright © 2005 John Wiley & Sons, Ltd. 相似文献