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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
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With the introduction of high‐resolution digital elevation models, it is possible to use digital terrain analysis to extract small streams. In order to map streams correctly, it is necessary to remove errors and artificial sinks in the digital elevation models. This step is known as preprocessing and will allow water to move across a digital landscape. However, new challenges are introduced with increasing resolution because the effect of anthropogenic artefacts such as road embankments and bridges increases with increased resolution. These are problematic during the preprocessing step because they are elevated above the surrounding landscape and act as artificial dams. The aims of this study were to evaluate the effect of different preprocessing methods such as breaching and filling on digital elevation models with different resolutions (2, 4, 8, and 16 m) and to evaluate which preprocessing methods most accurately route water across road impoundments at actual culvert locations. A unique dataset with over 30,000 field‐mapped road culverts was used to assess the accuracy of stream networks derived from digital elevation models using different preprocessing methods. Our results showed that the accuracy of stream networks increases with increasing resolution. Breaching created the most accurate stream networks on all resolutions, whereas filling was the least accurate. Burning streams from the topographic map across roads from the topographic map increased the accuracy for all methods and resolutions. In addition, the impact in terms of change in area and absolute volume between original and preprocessed digital elevation models was smaller for breaching than for filling. With the appropriate methods, it is possible to extract accurate stream networks from high‐resolution digital elevation models with extensive road networks, thus providing forest managers with stream networks that can be used when planning operations in wet areas or areas near streams to prevent rutting, sediment transport, and mercury export. 相似文献
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Flow network derivation from a high resolution DEM in a low relief,agrarian landscape 总被引：1，自引：0，他引：1
Wolfgang Schwanghart Geoff Groom Nikolaus J. Kuhn Goswin Heckrath 《地球表面变化过程与地形》2013,38(13):1576-1586
Digital flow networks derived from digital elevation models (DEMs) sensitively react to errors due to measurement, data processing and data representation. Since high‐resolution DEMs are increasingly used in geomorphological and hydrological research, automated and semi‐automated procedures to reduce the impact of such errors on flow networks are required. One such technique is stream‐carving, a hydrological conditioning technique to ensure drainage connectivity in DEMs towards the DEM edges. Here we test and modify a state‐of‐the‐art carving algorithm for flow network derivation in a low‐relief, agricultural landscape characterized by a large number of spurious, topographic depressions. Our results show that the investigated algorithm reconstructs a benchmark network insufficiently in terms of carving energy, distance and a topological network measure. The modification to the algorithm that performed best, combines the least‐cost auxiliary topography (LCAT) carving with a constrained breaching algorithm that explicitly takes automatically identified channel locations into account. We applied our methods to a low relief landscape, but the results can be transferred to flow network derivation of DEMs in moderate to mountainous relief in situations where the valley bottom is broad and flat and precise derivations of the flow networks are needed. Copyright © 2013 John Wiley & Sons, Ltd. 相似文献
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The role of hydrological modelling uncertainties in climate change impact assessments of Irish river catchments 总被引：5，自引：0，他引：5
This study attempts to assess the uncertainty in the hydrological impacts of climate change using a multi-model approach combining multiple emission scenarios, GCMs and conceptual rainfall-runoff models to quantify uncertainty in future impacts at the catchment scale. The uncertainties associated with hydrological models have traditionally been given less attention in impact assessments until relatively recently. In order to examine the role of hydrological model uncertainty (parameter and structural uncertainty) in climate change impact studies a multi-model approach based on the Generalised Likelihood Uncertainty Estimation (GLUE) and Bayesian Model Averaging (BMA) methods is presented. Six sets of regionalised climate scenarios derived from three GCMs, two emission scenarios, and four conceptual hydrological models were used within the GLUE framework to define the uncertainty envelop for future estimates of stream flow, while the GLUE output is also post processed using BMA, where the probability density function from each model at any given time is modelled by a gamma distribution with heteroscedastic variance. The investigation on four Irish catchments shows that the role of hydrological model uncertainty is remarkably high and should therefore be routinely considered in impact studies. Although, the GLUE and BMA approaches used here differ fundamentally in their underlying philosophy and representation of error, both methods show comparable performance in terms of ensemble spread and predictive coverage. Moreover, the median prediction for future stream flow shows progressive increases of winter discharge and progressive decreases in summer discharge over the coming century. 相似文献
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A key aspect of large river basins partially neglected in large‐scale hydrological models is river hydrodynamics. Large‐scale hydrologic models normally simulate river hydrodynamics using simplified models that do not represent aspects such as backwater effects and flood inundation, key factors for some of the largest rivers of the world, such as the Amazon. In a previous paper, we have described a large‐scale hydrodynamic approach resultant from an improvement of the MGB‐IPH hydrological model. It uses full Saint Venant equations, a simple storage model for flood inundation and GIS‐based algorithms to extract model parameters from digital elevation models. In the present paper, we evaluate this model in the Solimões River basin. Discharge results were validated using 18 stream gauges showing that the model is accurate. It represents the large delay and attenuation of flood waves in the Solimões basin, while simplified models, represented here by Muskingum Cunge, provide hydrographs are wrongly noisy and in advance. Validation against 35 stream gauges shows that the model is able to simulate observed water levels with accuracy, representing their amplitude of variation and timing. The model performs better in large rivers, and errors concentrate in small rivers possibly due to uncertainty in river geometry. The validation of flood extent results using remote sensing estimates also shows that the model accuracy is comparable to other flood inundation modelling studies. Results show that (i) river‐floodplain water exchange and storage, and (ii) backwater effects play an important role for the Amazon River basin hydrodynamics. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
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Assessing hydrological model predictive uncertainty using stochastically generated geological models 
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下载免费PDF全文 In distributed and coupled surface water–groundwater modelling, the uncertainty from the geological structure is unaccounted for if only one deterministic geological model is used. In the present study, the geological structural uncertainty is represented by multiple, stochastically generated geological models, which are used to develop hydrological model ensembles for the Norsminde catchment in Denmark. The geological models have been constructed using two types of field data, airborne geophysical data and borehole well log data. The use of airborne geophysical data in constructing stochastic geological models and followed by the application of such models to assess hydrological simulation uncertainty for both surface water and groundwater have not been previously studied. The results show that the hydrological ensemble based on geophysical data has a lower level of simulation uncertainty, but the ensemble based on borehole data is able to encapsulate more observation points for stream discharge simulation. The groundwater simulations are in general more sensitive to the changes in the geological structure than the stream discharge simulations, and in the deeper groundwater layers, there are larger variations between simulations within an ensemble than in the upper layers. The relationship between hydrological prediction uncertainties measured as the spread within the hydrological ensembles and the spatial aggregation scale of simulation results has been analysed using a representative elementary scale concept. The results show a clear increase of prediction uncertainty as the spatial scale decreases. Copyright © 2015 John Wiley & Sons, Ltd. 相似文献
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Automatically extracting drainage networks from digital elevation models coupled with the constant stream threshold value is a regular method. These extracted networks can be verified by comparing the channel initiation points with those from real networks. From the results analysed, the differences in channel initiation points will affect the network geometries, geomorphological indices and hydrological responses. This paper develops two automatic algorithms, the headwater‐tracing method and the fitness index, to trace the flow paths from headwaters to the outlet and to calculate the reasonable stream threshold. Instead of the method determined by trial and error or field survey, the accurate channel initiation points can be obtained from airborne photographs coupled with high‐resolution SPOT images for suitable drainage network extraction. Copyright © 2005 John Wiley & Sons, Ltd. 相似文献
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D. A. Hughes 《水文研究》2010,24(6):767-774
Understanding hydrological processes has always been important to the development and successful application of conceptual hydrological models. It can also contribute to informed water resources management, particularly in the context of understanding the potential impacts of both land use and climate change. Improved conceptual and quantitative understanding of near‐surface hydrological processes emerged through field studies during the 1960s to1980s; however, there remains a degree of ambiguity about the processes that link surface water and groundwater. This is especially the case in South Africa where a great deal of confusion has arisen about the source of the ‘baseflow’ signal in stream flow observations. This paper suggests that fracture flow within the unsaturated zone could have a lateral component and therefore re‐emerge and contribute to stream flow in catchments with relatively steep topography. The implication is that ‘baseflows’ could be made up of groundwater contributions (caused by intersection of the water table with stream channels) as well as an unsaturated zone flow component. Evidence for the existence of the process is presented on the basis of small‐scale observations and interpretations of stream flow observations. The potential importance of the process relates to interpreting different methods of recharge estimation, assessing the impacts of groundwater abstraction on stream flow, as well as the application and interpretation of the results of hydrological models. The conclusions are that the process does exist, but that there is less than conclusive evidence for its importance. There is therefore a need for further studies that can quantify the scale of the process and therefore its importance. Only then will it be possible to develop a consistent understanding of the processes of surface water and groundwater interaction and therefore manage water resources in a truly integrated manner. Copyright © 2009 John Wiley & Sons, Ltd. 相似文献
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Lu Chen Vijay P. Singh Shenglian Guo Jianzhong Zhou Lei Ye 《Stochastic Environmental Research and Risk Assessment (SERRA)》2014,28(7):1755-1767
The rainfall–runoff relationship is not only nonlinear and complex but also difficult to model. Artificial neural network (ANN), as a data-driven technique, has gained significant attention in recent years and has been shown to be an efficient alternative to traditional methods for hydrological modeling. However, for different input combinations, ANN models can yield different results. Therefore, input variables and ANN types need to be carefully considered, when using an ANN model for stream flow forecasting. This study proposes the copula-entropy (CE) theory to identify the inputs of an ANN model. The CE theory permits to calculate mutual information (MI) and partial MI directly which avoids calculating the marginal and joint probability distributions. Three different ANN models, namely multi-layer feed (MLF) forward networks, radial basis function networks and general regression neural network, were applied to predict stream flow of Jinsha River, China. Results showed that the inputs selected by the CE method were better than those by the traditional linear correlation analysis, and the MLF ANN model with the inputs selected by CE method obtained the best predicted results for the Jinsha River at Pingshan gauging station. 相似文献
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Andrew Watson Sven Kralisch Jodie Miller Yuliya Vystavna Shaeden Gokool Annika Künne Jörg Helmschrot Saul Arciniega-Esparza Ricardo Sanchez-Murillo Christian Birkel 《水文研究》2024,38(2):e15065
Realistic projections of the future climate and how this translates to water availability is crucial for sustainable water resource management. However, data availability constrains the capacity to simulate streamflow and corresponding hydrological processes. Developing more robust hydrological models and methods that can circumvent the need for large amounts of hydro-climatic data is crucial to support water-related decisions, particularly in developing countries. In this study, we use natural isotope tracers in addition to hydro-climate data within a newly developed version of the spatially-distributed J2000iso as an isotope-enabled rainfall-runoff model simulating both water and stable isotope (δ2H) fluxes. We pilot the model for the humid tropical San Carlos catchment (2500 km2) in northeastern Costa Rica, which has limited time series, but spatially distributed data. The added benefit of simulating stable isotopes was assessed by comparing different amounts of observation data using three model calibration strategies (i) three streamflow gauges, (ii) three gauges with stream isotopes and (iii) isotopes only. The J2000iso achieved a streamflow Kling–Gupta efficiency (KGE) of 0.55–0.70 across all the models and gauges, but differences in hydrological process simulations emerged when including stable water isotopes in the rainfall-runoff calibration. Hydrological process simulation varied between the standard J2000 rainfall-runoff model with a high simulated surface runoff proportion of 37% as opposed to the isotope version with 84%–89% simulated baseflow or interflow. The model solutions that used only isotope data for calibration exhibited differences in simulated interflow, baseflow and model performance but captured bulk water balances with a reasonable match between the simulated and observed hydrographs. We conclude that J2000iso has shown the potential to support water balance modelling for ungauged catchments using stable isotope, satellite and global reanalysis data sets. 相似文献
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Stream network morphometrics have been used frequently in environmental applications and are embedded in several hydrological models. This is because channel network geometry partly controls the runoff response of a basin. Network indices are often measured from channels that are mapped from digital elevation models (DEMs) using automated procedures. Simulations were used in this paper to study the influence of elevation error on the reliability of estimates of several common morphometrics, including stream order, the bifurcation, length, area and slope ratios, stream magnitude, network diameter, the flood magnitude and timing parameters of the geomorphological instantaneous unit hydrograph (GIUH) and the network width function. DEMs of three UK basins, ranging from high to low relief, were used for the analyses. The findings showed that moderate elevation error (RMSE of 1·8 m) can result in significant uncertainty in DEM‐mapped network morphometrics and that this uncertainty can be expressed in complex ways. For example, estimates of the bifurcation, length and area ratios and the flood magnitude and timing parameters of the GIUH each displayed multimodal frequency distributions, i.e. two or more estimated values were highly likely. Furthermore, these preferential estimates were wide ranging relative to the ranges typically observed for these indices. The wide‐ranging estimates of the two GIUH parameters represented significant uncertainty in the shape of the unit hydrograph. Stream magnitude, network diameter and the network width function were found to be highly sensitive to elevation error because of the difficulty in mapping low‐magnitude links. Uncertainties in the width function were found to increase with distance from outlet, implying that hydrological models that use network width contain greater uncertainty in the shape of the falling limb of the hydrograph. In light of these findings, care should be exercised when interpreting the results of analyses based on DEM‐mapped stream networks. Copyright © 2007 John Wiley & Sons, Ltd. 相似文献
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Conservative solute injections were conducted in three first-order montane streams of different geological composition to assess the influence of parent lithology and alluvial characteristics on the hydrological retention of nutrients. Three study sites were established: (1) Aspen Creek, in a sandstone–siltstone catchment with a fine-grained alluvium of low hydraulic conductivity (1·3×10−4 cm/s), (2) Rio Calaveras, which flows through volcanic tuff with alluvium of intermediate grain size and hydraulic conductivity (1·2×10−3 cm/s), and (3) Gallina Creek, located in a granite/gneiss catchment of coarse, poorly sorted alluvium with high hydraulic conductivity (4·1×10−3 cm/s). All sites were instrumented with networks of shallow groundwater wells to monitor interstitial solute transport. The rate and extent of groundwater–surface water exchange, determined by the solute response in wells, increased with increasing hydraulic conductivity. The direction of surface water–groundwater interaction within a stream was related to local variation in vertical and horizontal hydraulic gradients. Experimental tracer responses in the surface stream were simulated with a one-dimensional solute transport model with inflow and storage components (OTIS). Model-derived measures of hydrological retention showed a corresponding increase with increasing hydraulic conductivity. To assess the temporal variability of hydrological retention, solute injection experiments were conducted in Gallina Creek under four seasonal flow regimes during which surface discharge ranged from baseflow (0·75 l/s in October) to high (75 l/s during spring snowmelt). Model-derived hydrological retention decreased with increasing discharge. The results of our intersite comparison suggest that hydrological retention is strongly influenced by the geologic setting and alluvial characteristics of the stream catchment. Temporal variation in hydrological retention at Gallina Creek is related to seasonal changes in discharge, highlighting the need for temporal resolution in studies of the dynamics of surface water–groundwater interactions in stream ecosystems. © 1997 by John Wiley & Sons, Ltd. 相似文献
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Simple runoff models with a low number of model parameters are generally able to simulate catchment runoff reasonably well, but they rely on model calibration, which makes their use in ungauged basins challenging. In a previous study it has been shown that a limited number of streamflow measurements can be quite informative for constraining runoff models. In practice, however, instead of performing such repeated flow measurements, it might be easier to install a stream level logger. Here, a dataset of 600+ gauged basins in the USA was used to study how well models perform when only stream level data, rather than streamflow data, are available. A runoff model (the HBV model) was calibrated assuming that only stream level observations were available, and the simulations were evaluated on the full observed streamflow record. The results indicate that stream level data alone can already provide surprisingly good model simulation results in humid catchments, whereas in arid catchments some form of quantitative information (e.g. a streamflow observation or a regional average value) is needed to obtain good results. These results are encouraging for hydrological observations in data scarce regions as level observations are much easier to obtain than streamflow measurements. Based on runoff modelling, it might even be possible to derive streamflow time series from the level data obtained from loggers, satellites or community‐based approaches. Copyright © 2016 John Wiley & Sons, Ltd. 相似文献
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This paper presents the results of an investigation into the problems associated with using downscaled meteorological data for hydrological simulations of climate scenarios. The influence of both the hydrological models and the meteorological inputs driving these models on climate scenario simulation studies are investigated. A regression‐based statistical tool (SDSM) is used to downscale the daily precipitation and temperature data based on climate predictors derived from the Canadian global climate model (CGCM1), and two types of hydrological model, namely the physically based watershed model WatFlood and the lumped‐conceptual modelling system HBV‐96, are used to simulate the flow regimes in the major rivers of the Saguenay watershed in Quebec. The models are validated with meteorological inputs from both the historical records and the statistically downscaled outputs. Although the two hydrological models demonstrated satisfactory performances in simulating stream flows in most of the rivers when provided with historic precipitation and temperature records, both performed less well and responded differently when provided with downscaled precipitation and temperature data. By demonstrating the problems in accurately simulating river flows based on downscaled data for the current climate, we discuss the difficulties associated with downscaling and hydrological models used in estimating the possible hydrological impact of climate change scenarios. Copyright © 2007 John Wiley & Sons, Ltd. 相似文献
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A number of previous studies using models of integrated surface‐subsurface hydrology have adopted the Panday and Huyakorn (P&H) tilted V‐catchment test case (Panday S, Huyakorn PS. 2004. A fully coupled spatially distributed model for evaluating surface/subsurface flow. Advances in Water Resources 27: 361–382) to show inter‐code comparability. The P&H test case is used to evaluate models that simulate a broad range of hydrological processes, and yet only the catchment outflow hydrograph has been presented as verification of the consistency between codes. Therefore, a more comprehensive evaluation of the surface‐subsurface hydrology of the P&H case is needed. This study explores the internal catchment functioning of the P&H case, using the popular catchment simulator MODHMS. The processes leading to streamflow generation in the model are illustrated, including separation of overland flow (OLF) and groundwater discharge to the stream. The results identify non‐physical flow processes due to the problem set‐up, and modifications to the P&H case are suggested that include changes to stream roughness and incision of the stream channel to overcome these shortcomings. A modified P&H case produced more plausible transfers between OLF and the stream, and an increased groundwater discharge to the stream (6·5% of streamflow in the modified case compared to 0·5% in the original case). Despite changes to internal flow processes, near‐identical outflow hydrographs were obtained, showing the importance of considering and comparing internal flow processes when using surface‐subsurface hydrology test cases to evaluate integrated hydrological simulators. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
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Systematic variations in atmospheric heat exchange, surface residence time, and groundwater influx across montane stream networks commonly produce an increasing stream temperature trend with decreasing elevation. However, complex stream temperature profiles that differ from this common longitudinal trend also exist, suggesting that stream temperatures may be influenced by complex interactions among hydrologic and atmospheric processes. Lakes within stream networks form one potential source of temperature profile complexity due to the spatially variable contribution of lake-sourced water to stream flow. We investigated temperature profile complexity in a multi-season stream temperature dataset collected across a montane stream network containing many alpine lakes. This investigation was performed by making comparisons between multiple statistical models that used different combinations of stream and lake characteristics to represent specific hypotheses for the controls on stream temperature. The compared models included a set of models which used a topographically derived estimate of the hydrologic influence of lakes to separate and quantify the effects of stream elevation and lake source-water contributions to longitudinal stream temperature patterns. This source-water mixing model provided a parsimonious explanation for complex stream-network temperature patterns in the summer and autumn, and this approach may be further applicable to other systems where stream temperatures are influenced by multiple water sources. Simpler models that discounted lake effects were more optimal during the winter and spring, suggesting that complex patterns in stream temperature profiles may emerge and subside temporally, across seasons, in response to diversity of water temperatures from different sources. 相似文献
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Mathematical models are being used to develop a decision support system for integrated management of the Ythan catchment in NE Scotland. One component of this has involved the development of a distributed catchment-scale hydrological model. The model is based on subsurface flow routing and calculates the contribution to stream flow from each 50 m×50 m cell in the 548 km2 catchment. It uses two topographic parameters, slope and distance to stream following the main line of flow, and five physical parameters. The topographic analysis and distributed flow accumulation are performed by linking the single cell model with a geographic information system. Preliminary results from a three-year simulation of daily flows indicate that the model successfully predicts the main characteristics of the catchment flow. © 1998 John Wiley & Sons, Ltd. 相似文献
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The aim of this review is to provide a basis for selecting a suitable hydrological model, or combination of models, for hydrological drought forecasting in Africa at different temporal and spatial scales; for example short and medium range (1–10 days or monthly) forecasts at medium to large river basin scales or seasonal forecasts at the Pan-African scale. Several global hydrological models are currently available with different levels of complexity and data requirements. However, most of these models are likely to fail to properly represent the water balance components that are particularly relevant in arid and semi-arid basins in sub-Saharan Africa. This review critically looks at weaknesses and strengths in the representation of different hydrological processes and fluxes of each model. The major criteria used for assessing the suitability of the models are (1) the representation of the processes that are most relevant for simulating drought conditions, such as interception, evaporation, surface water-groundwater interactions in wetland areas and flood plains and soil moisture dynamics; (2) the capability of the model to be downscaled from a continental scale to a large river basin scale model; and (3) the applicability of the model to be used operationally for drought early warning, given the data availability of the region. This review provides a framework for selecting models for hydrological drought forecasting, conditional on spatial scale, data availability and end-user forecast requirements. Among 16 well known hydrological and land surface models selected for this review, PCR-GLOBWB, GWAVA, HTESSEL, LISFLOOD and SWAT show higher potential and suitability for hydrological drought forecasting in Africa based on the criteria used in this evaluation. 相似文献