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1.
This paper presents the development of a multiple‐station neural network for predicting tidal currents across a coastal inlet. Unlike traditional hydrodynamic models, the neural network model does not need inputs of coastal topography and bathymetry, grids, surface and bottom frictions, and turbulent eddy viscosity. Without solving hydrodynamic equations, the neural network model applies an interconnected neural network to correlate the inputs of boundary forcing of water levels at a remote station to the outputs of tidal currents at multiple stations across a local coastal inlet. Coefficients in the neural network model are trained using a continuous dataset consisting of inputs of water levels at a remote station and outputs of tidal currents at the inlet, and verified using another independent input and output dataset. Once the neural network model has been satisfactorily trained and verified, it can be used to predict tidal currents at a coastal inlet from the inputs of water levels at a remote station. For the case study at Shinnecock Inlet in the southern shore of New York, tidal currents at nine stations across the inlet were predicted by the neural network model using water level data located from a station about 70 km away from the inlet. A continuous dataset in May 2000 was used for the training, and another dataset in July 2000 was used for the verification of the neural network model. Comparing model predictions and observations indicates correlation coefficients range from 0·95 to 0·98, and the root‐mean‐square error ranges from 0·04 to 0·08 m s?1 at the nine current locations across the inlet. Copyright © 2007 John Wiley & Sons, Ltd. 相似文献
2.
Ioannis N. Daliakopoulos 《水文科学杂志》2013,58(15):2763-2774
ABSTRACTThe rainfall–runoff process is governed by parameters that can seldom be measured directly for use with distributed models, but are rather inferred by expert judgment and calibrated against historical records. Here, a comparison is made between a conceptual model (CM) and an artificial neural network (ANN) for their ability to efficiently model complex hydrological processes. The Sacramento soil moisture accounting model (SAC-SMA) is calibrated using a scheme based on genetic algorithms and an input delay neural network (IDNN) is trained for variable delays and hidden layer neurons which are thoroughly discussed. The models are tested for 15 ephemeral catchments in Crete, Greece, using monthly rainfall, streamflow and potential evapotranspiration input. SAC-SMA performs well for most basins and acceptably for the entire sample with R2 of 0.59–0.92, while scoring better for high than low flows. For the entire dataset, the IDNN improves simulation fit to R2 of 0.70–0.96 and performs better for high flows while being outmatched in low flows. Results show that the ANN models can be superior to the conventional CMs, as parameter sensitivity is unclear, but CMs may be more robust in extrapolating beyond historical record limits and scenario building.
EDITOR M.C. Acreman; ASSOCIATE EDITOR not assigned 相似文献
3.
Abstract This paper describes a fuzzy rule-based approach applied for reconstruction of missing precipitation events. The working rules are formulated from a set of past observations using an adaptive algorithm. A case study is carried out using the data from three precipitation stations in northern Italy. The study evaluates the performance of this approach compared with an artificial neural network and a traditional statistical approach. The results indicate that, within the parameter sub-space where its rules are trained, the fuzzy rule-based model provided solutions with low mean square error between observations and predictions. The problems that have yet to be addressed are overfitting and applicability outside the range of training data. 相似文献
4.
ABSTRACTAssessment of forecast precipitation is required before it can be used as input to hydrological models. Using radar observations in southeastern Australia, forecast rainfall from the Australian Community Climate Earth-System Simulator (ACCESS) was evaluated for 2010 and 2011. Radar rain intensities were first calibrated to gauge rainfall data from four research rainfall stations at hourly time steps. It is shown that the Australian ACCESS model (ACCESS-A) overestimated rainfall in low precipitation areas and underestimated elevated accumulations in high rainfall areas. The forecast errors were found to be dependent on the rainfall magnitude. Since the cumulative rainfall observations varied across the area and through the year, the relative error (RE) in the forecasts varied considerably with space and time, such that there was no consistent bias across the study area. Moreover, further analysis indicated that both location and magnitude errors were the main sources of forecast uncertainties on hourly accumulations, while magnitude was the dominant error on the daily time scale. Consequently, the precipitation output from ACCESS-A may not be useful for direct application in hydrological modelling, and pre-processing approaches such as bias correction or exceedance probability correction will likely be necessary for application of the numerical weather prediction (NWP) outputs.
EDITOR M.C. Acreman ASSOCIATE EDITOR A. Viglione 相似文献
5.
Analysis and forecasting of water temperature are important for water ecological management. The objective of this study is to compare models for water temperature during the summer season for an impounded river. In a case study, we consider hydro-climatic and water temperature data for the Fourchue River (St-Alexandre-de-Kamouraska, Quebec, Canada) between 2011 and 2014. Three different models are applied, which are broadly characterized as deterministic (CEQUEAU), stochastic (Auto-regressive Moving Average with eXogenous variables or ARMAX) and nonlinear (Nonlinear Autoregressive with eXogenous variables or NARX). The efficiency of each model is analysed and compared. The results show that the ARMAX is the best performing water temperature model for the Fourchue River and the CEQUEAU model also simulates water temperature adequately without the overfitting issues that seem to plague the autoregressive models.
EDITOR M.C. AcremanASSOCIATE EDITOR R. Hirsch 相似文献
6.
ABSTRACTIn this paper we develop a coupled analytical model for salinity and tidal propagation in estuaries where the cross-sectional area varies exponentially. A simple analytical model for tidal dynamics has been used to estimate the tidal excursion, which has an important influence on the salt intrusion process since it determines the extreme salinities (i.e. salinity distribution for high water slack and low water slack). The objective of the coupling is to reduce the number of calibration parameters, which subsequently strengthens the reliability of the salt intrusion model. Moreover, the coupling enables us to assess the potential impacts of external changes, both human-induced interventions (e.g. dredging) and natural changes (e.g. global sea level rise), on the salt intrusion process. In addition, the fully analytical solution for hydrodynamics allows immediate estimation of the tidally averaged depth and friction coefficient for given water level recordings and salinity measurements. This is particularly useful when a geometric survey is not available. The coupled model has been applied to six previously unsurveyed estuaries in Malaysia and the results show that the correspondence between analytical estimations and observations is very good. Thus, the coupled model proves to be a useful tool to obtain estimates of salt intrusion in estuaries based on a minimum amount of information required and for assessing the effect of human-induced or natural changes.
EDITOR D. Koutsoyiannis ASSOCIATE EDITOR B. Dewals 相似文献
7.
Vassilis Z. Antonopoulos Soultana K. Gianniou Athanasios V. Antonopoulos 《水文科学杂志》2013,58(14):2590-2599
ABSTRACTEvaporation is one of the most important components in the energy and water budgets of lakes and is a primary process of water loss from their surfaces. An artificial neural network (ANN) technique is used in this study to estimate daily evaporation from Lake Vegoritis in northern Greece and is compared with the classical empirical methods of Penman, Priestley-Taylor and the mass transfer method. Estimation of the evaporation over the lake is based on the energy budget method in combination with a mathematical model of water temperature distribution in the lake. Daily datasets of air temperature, relative humidity, wind velocity, sunshine hours and evaporation are used for training and testing of ANN models. Several input combinations and different ANN architectures are tested to detect the most suitable model for predicting lake evaporation. The best structure obtained for the ANN evaporation model is 4-4-1, with root mean square error (RMSE) from 0.69 to 1.35 mm d?1 and correlation coefficient from 0.79 to 0.92.
EDITOR M.C. AcremanASSOCIATE EDITOR not assigned 相似文献
8.
Rainfall–runoff models with different conceptual structures for the hydrological processes can be calibrated to effectively reproduce the hydrographs of the total runoff, while resulting in water budget components that are essentially different. This finding poses an open question on the reliability of rainfall–runoff models in reproducing hydrological components other than those used for calibration. In an effort to address this question, we use data from the Glafkos catchment in western Greece to calibrate and compare the ENNS model, a research-oriented lumped model developed for the river Enns in Austria developed for the river Enns in Austria, with the operational MIKE SHE model. Model performance is assessed in the light of the conceptual/structural differences of the modelled hydrological processes, using indices calculated independently for each year, rather than for the whole calibration period, since the former are stricter. We show that even small differences in the representation of hydrological processes may impact considerably on the water budget components that are not measured (i.e. not used for model calibration). From all water budget components, direct runoff exhibits the highest sensitivity to structural differences and related model parameters.
EDITOR M.C. AcremanASSOCIATE EDITOR S. Huang 相似文献
9.
Since a river system is a unidirectional network, the upstream influencing factors often interfere with those downstream. We quantify the effects of the TGD on the sediment exchange processes between the Yangtze River and Dongting Lake. Based on yearly sediment load data from 1981 to 2008, two multi-layer perceptron (MLP) models were constructed to predict the potential sedimentation in Dongting Lake without implementation of the TGD. The sediment discharge at Yichang station decreased from 622.5 to 61.1 Mt/year between 1981–1985 and 2003–2008, while the sedimentation in Dongting Lake reduced from 127.3 to 6.6 Mt/year. The MLP models indicate that only 27.9% of the decreased sediment load at Yichang station and 16.9% of that in Dongting Lake is caused by the TGD, while the rest is caused mostly by other upstream climate variations and anthropogenic impacts.
EDITOR A. Castellarin; ASSOCIATE EDITORN. Ilich 相似文献
10.
The synthetic tidal parameters with high spatial resolution for gravity over China and its neighbor area are con- structed with Earth’s tidal model and ocean tide loading calculated using TPXO7 global ocean tide model as well as tidal data over China seas. The comparison between synthetic parameters and ones observed by spring gravime- ters at some seismic network stations and Hong Kong station and one observed by super-conducting gravimeter at Wuhan station shows that the average differences in amplitude factors and phases are smaller than 0.005 and 0.5° respectively; and that the discrepancies between observational and synthetic parameters are dependent on gravim- etric technique in that the synthetic parameters are in well agreement with the superconducting gravimetric obser- vations. This also indicates that the synthetic result is a good estimation for tidal gravity, and the numerical results in the present paper not only can provide ground and space gravimetry such as absolute gravimetry with correction model of tidal gravity, but also provide effective tidal parameters over areas where no observation is carried out. 相似文献
11.
ABSTRACTThe southern coast of the Caspian Sea in northern Iran is bordered by a mountain range with forested catchments which are susceptible to droughts and floods. This paper examines possible changes to runoff patterns from one of these catchments in response to climate change scenarios. The HEC-HMS rainfall–runoff model was used with downscaled future rainfall and temperature data from 13 global circulation models, and meteorological and hydrometrical data from the Casilian (or “Kassilian”) Catchment. Annual and seasonal predictions of runoff change for three future emissions scenarios were obtained, which suggest significantly higher spring rainfall with increased risk of flooding and significantly lower summer rainfall leading to a higher probability of drought. Flash floods arising from extreme rainfall may become more frequent, occurring at any time of year. These findings indicate a need for strategic planning of water resource management and mitigation measures for increasing flood hazards.
EDITOR M.C. Acreman ASSOCIATE EDITOR not assigned 相似文献
12.
Yeugeniy M. Gusev Vladimir A. Semenov Olga N. Nasonova Evgeny E. Kovalev 《水文科学杂志》2017,62(8):1181-1199
Assessments of hydrological response to climatic changes are characterized by different types of uncertainties. Here, the uncertainty caused by weather noise associated with the chaotic character of atmospheric processes is considered. A technique for estimating such uncertainty in simulated water balance components based on application of the land surface model SWAP and the climate model ECHAM5 is described. The technique is applied for estimating the uncertainties in the simulated water balance components (precipitation, river runoff and evapotranspiration) of some northern river basins of Russia. It is shown that the larger the area of a basin the less the uncertainty. This dependency is smoothed by differences in natural conditions of the basins. Analysis of the spectral densities of water balance components shows that a river basin filters out high-frequency harmonics of spectral density of precipitation (corresponding to synoptic or sub-seasonal scale) during its transformation into evapotranspiration and especially into runoff.
EDITOR D. KoutsoyiannisASSOCIATE EDITOR H. Kreibich 相似文献
13.
Generalized extreme value shape parameter and its nature for extreme precipitation using long time series and the Bayesian approach 总被引：2，自引：2，他引：0
Assessing the probability of extreme precipitation events is consequential in civil planning. This requires an understanding of how return values change with return periods, which is essentially described by the generalized extreme value (GEV) shape parameter. Some works in the field suggest a constant shape parameter, while our analysis indicates a non-universal value. We re-analysed an older precipitation dataset (169 stations) extended by Norwegian data (71 stations). We showed that while each set seems to have a constant shape parameter, it differs between the two datasets, indicating regional differences. For a more comprehensive analysis of spatial effects, we examined a global dataset (1495 stations). We provided shape parameter maps for two models and found clear evidence that the shape parameter depends on elevation, while the effect of latitude remains uncertain. Our results confirm an explanation in terms of dominating precipitation systems based on a proxy derived from the Köppen-Geiger climate classification.
EDITOR D. KoutsoyiannisASSOCIATE EDITOR not assigned 相似文献
14.
15.
ABSTRACTThe impacts of future climate change on the agricultural water supply capacities of irrigation facilities in the Geum River basin (9645.5 km2) of South Korea were investigated using an integrated modeling framework that included a water balance network model (MODSIM) and a watershed-scale hydrologic model (Soil and Water Assessment Tool, SWAT). The discharges and baseflows from upland drainage areas were estimated using SWAT, and the predicted flow was used to feed agricultural reservoirs and multipurpose dams in subwatersheds. Using a split sampling method, we calibrated the daily streamflows and dam inflows at three locations using data from 6 years, including 3 years of calibration data (2005–2007) followed by 3 years of validation data (2008–2010). In the MODSIM model, the entire basin was divided into 14 subwatersheds in which various agricultural irrigation facilities such as agricultural reservoirs, pumping stations, diversions, culverts and groundwater wells were defined as a network of hydraulic structures within each subwatershed. These hydraulic networks between subwatersheds were inter-connected to allow watershed-scale analysis and were further connected to municipal and industrial water supplies under various hydrologic conditions. Projected climate data from the HadGEM3-RA RCP 4.5 and 8.5 scenarios for the period of 2006–2099 were imported to SWAT to calculate the water yield, and the output was transferred to MODSIM in the form of time-series boundary conditions. The maximum shortage rate of agricultural water was estimated as 38.2% for the 2040s and 2080s under the RCP 4.5 scenario but was lower under the RCP 8.5 scenario (21.3% in the 2040s and 22.1% in the 2080s). Under the RCP 4.5 scenario, the projected shortage rate was higher than that during the measured baseline period (1982–2011) of 25.6% and the RCP historical period (1982–2005) of 30.1%. The future elevated drought levels are primarily attributed to the increasingly concentrated rainfall distribution throughout the year under a monsoonal climate, as projected by the IPCC climate scenarios.
EDITOR Z.W. Kundzewicz; ASSOCIATE EDITOR not assigned 相似文献
16.
《水文科学杂志》2013,58(1)
Abstract Abstract Accurate application of the longitudinal dispersion model requires that specially designed experimental studies are performed in the river reach under consideration. Such studies are usually very expensive, so in order to quantify the longitudinal dispersion coefficient, as an alternative approach, various researchers have proposed numerous empirical formulae based on hydraulic and morphometric characteristics. The results are presented of the application of artificial neural networks as a parameter estimation technique. Five different cases were considered with the network trained for different arrangements of input nodes, such as channel depth, channel width, cross-sectionally averaged water velocity, shear velocity and sinuosity index. In the case where the sinuosity index is included as an input node, the results turned out to be better than those presented by other authors. 相似文献
17.
ABSTRACTSedimentation in navigable waterways and harbours is of concern for many water and port managers. One potential source of variability in sedimentation is the annual sediment load of the river that empties in the harbour. The main objective of this study was to use some of the regularly monitored hydro-meteorological variables to compare estimates of hourly suspended sediment concentration in the Saint John River using a sediment rating curve and a model tree (M5?) with different combinations of predictors. Estimated suspended sediment concentrations were multiplied by measured flows to estimate suspended sediment loads. Best results were obtained using M5? with four predictors, returning an R2 of 0.72 on calibration data and an R2 of 0.46 on validation data. Total load was underestimated by 1.41% for the calibration period and overestimated by 2.38% for the validation period. Overall, the model tree approach is suggested for its relative ease of implementation and constant performance.
EDITOR M.C. Acreman; ASSOCIATE EDITOR B. Touaibia 相似文献
18.
ABSTRACTEstimating river flows at ungauged sites is generally recognised as an important area of research. In countries or regions with rapid land development and sparse hydrological gauging networks, three particular challenges may arise—data scarcity, data quality, and hydrological non-stationarity. Using data from 44 gauged sub-catchments of the upper Ping catchment in northern Thailand from the period 1995–2006, three relevant flow response indices (runoff coefficient, base flow index and seasonal elasticity of flow) were regionalised by regression against available catchment properties. The runoff coefficient was the most successfully regionalised, followed by base flow index and lastly the seasonal elasticity. The non-stationarity (represented by the differences between two 6-year sub-periods) was significant both in the flow response indices and in land use indices; however relationships between the two sets of indices were weak. The regression equations derived from regionalisation were not helpful in predicting the non-stationarity in the flow indices except somewhat for the runoff coefficient. A partly subjective data quality scoring system was devised, and showed the clear influence of rainfall and flow data quality on regionalisation uncertainty. Recommendations towards improving data support for hydrological regionalisation in Thailand include more relevant soils databases, improved records of abstractions and investment in the gauge network. Widening of the regionalisation beyond the upper Ping and renewed efforts at using remotely sensed rainfall data are other possible ways forward.
EDITOR Z.W. Kundzewicz ASSOCIATE EDITOR T. Wagener 相似文献
19.
Potential evaporation (PE) is the basic component of the global hydrological cycle and energy balance. This study detected the temporal and spatial variations of PE and related driving factors in Tibet, China, for the period 1961–2001, based on observed data recorded at 22 meteorological stations. The results showed that (1) Tibet experienced a statistically significant decrease of PE between 1961 and 2001, which started mainly in the 1980s, along with accelerated warming; (2) the mean annual PE in Tibet showed an east–west increasing trend, and the annual PE at most stations presented decreasing trends; (3) an inverse correlation of mean annual PE with elevation was detected (low–high decreasing trend), and the statistical equations to estimate PE were established based on longitude, latitude and elevation; and (4) PE in Tibet can be well expressed by related meteorological variables, with vapour pressure deficit the dominant factor in determining PE.
EDITOR Z. W. Kundzewicz ASSOCIATE EDITOR not assigned 相似文献
20.
ABSTRACTDischarges and water levels are essential components of river hydrodynamics. In unreachable terrains and ungauged locations, it is quite difficult to measure these parameters due to rugged topography. In the present study an artificial neural network model has been developed for the Ramganga River catchment of the Ganga Basin. The modelled network is trained, validated and tested using daily water flow and level data pertaining to 4 years (2010–2013). The network has been optimized using an enumeration technique and a network topology of 4-10-2 with a learning rate set at 0.06, which was found optimum for predicting discharge and water-level values for the considered river. The mean square error values obtained for discharge and water level for the tested data were found to be 0.046 and 0.012, respectively. Thus, monsoon flow patterns can be estimated with an accuracy of about 93.42%.
Editor M.C. Acreman; Associate editor E. Gargouri 相似文献