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1.
《水文科学杂志》2013,58(4):613-625
Abstract Estimates of rainfall elasticity of streamflow in 219 catchments across Australia are presented. The rainfall elasticity of streamflow is defined here as the proportional change in mean annual streamflow divided by the proportional change in mean annual rainfall. The elasticity is therefore a simple estimate of the sensitivity of long-term streamflow to changes in long-term rainfall, and is particularly useful as an initial estimate of climate change impact in land and water resources projects. The rainfall elasticity of streamflow is estimated here using a hydrological modelling approach and a nonparametric estimator. The results indicate that the rainfall elasticity of streamflow (? P ) in Australia is about 2.0–3.5 (observed in about 70% of the catchments), that is, a 1% change in mean annual rainfall results in a 2.0–3.5% change in mean annual streamflow. The rainfall elasticity of streamflow is strongly correlated to runoff coefficient and mean annual rainfall and streamflow, where streamflow is more sensitive to rainfall in drier catchments, and those with low runoff coefficients. There is a clear relation-ship between the ? P values estimated using the hydrological modelling approach and those estimated using the nonparametric estimator for the 219 catchments, although the values estimated by the hydrological modelling approach are, on average, slightly higher. The modelling approach is useful where a detailed study is required and where there are sufficient data to reliably develop and calibrate a hydrological model. The nonparametric estimator is useful where consistent estimates of the sensitivity of long-term streamflow to climate are required, because it is simple to use and estimates the elasticity directly from the historical data. The nonparametric method, being model independent, can also be easily applied in comparative studies to data sets from many catchments across large regions. 相似文献
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Waldo Sven Lavado Casimiro Josyane Ronchail David Labat Jhan Carlo Espinoza Jean Loup Guyot 《水文科学杂志》2013,58(4):625-642
Abstract We present a procedure for estimating Q95 low flows in both gauged and ungauged catchments where Q95 is the flow that is exceeded 95% of the time. For each step of the estimation procedure, a number of alternative methods was tested on the Austrian data set by leave-one-out cross-validation, and the method that performed best was used in the final procedure. To maximise the accuracy of the estimates, we combined relevant sources of information including long streamflow records, short streamflow records, and catchment characteristics, according to data availability. Rather than deriving a single low flow estimate for each catchment, we estimated lower and upper confidence limits to allow local information to be incorporated in a practical application of the procedure. The components of the procedure consist of temporal (climate) adjustments for short records; grouping catchments into eight seasonality-based regions; regional regressions of low flows with catchment characteristics; spatial adjustments for exploiting local streamflow data; and uncertainty assessment. The results are maps of lower and upper confidence limits of low flow discharges for 21 000 sub-catchments in Austria. 相似文献
3.
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
4.
《水文科学杂志》2013,58(6):1270-1285
Abstract The transport of sediment load in rivers is important with respect to pollution, channel navigability, reservoir filling, longevity of hydroelectric equipment, fish habitat, river aesthetics and scientific interest. However, conventional sediment rating curves cannot estimate sediment load accurately. An adaptive neuro-fuzzy technique is investigated for its ability to improve the accuracy of the streamflow—suspended sediment rating curve for daily suspended sediment estimation. The daily streamflow and suspended sediment data for four stations in the Black Sea region of Turkey are used as case studies. A comparison is made between the estimates provided by the neuro-fuzzy model and those of the following models: radial basis neural network (RBNN), feed-forward neural network (FFNN), generalized regression neural network (GRNN), multi-linear regression (MLR) and sediment rating curve (SRC). Comparison of results reveals that the neuro-fuzzy model, in general, gives better estimates than the other techniques. Among the neural network techniques, the RBNN is found to perform better than the FFNN and GRNN. 相似文献
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Abstract Agricultural watersheds in the Czech Republic are one of the primary sources of non-point-source phosphorus (P) loads in receiving waters. Since such non-point sources are generally located in headwater catchments, streamflow and P concentration data are sparse. We show how very short daily streamflow and P concentration records can be combined with nearby longer existing daily streamflow records to result in reliable estimates of daily and annual P concentrations and loads. Maintenance of variance streamflow record extension methods (MOVE) can be employed to extend short streamflow records. Constituent load regressions are used to predict daily P constituent loads from streamflow and other time varying characteristics. Annual P loads are then estimated for individual watersheds. Resulting annual P load estimates ranged from 0.21 to 95.4 kg year-1 with a mean value of 11.77 kg year-1. Similarly annual P yield estimates ranged from 0.01 to 0.3 kg ha-1 year-1 with an average yield of 0.07 kg ha-1 year-1. We document how short records of daily streamflow and P concentrations can be combined with a national network of daily streamflow records in the Czech Republic to arrive at meaningful and reliable estimates of annual P loads for small agricultural watersheds. Citation Beránková, T., Vogel, R. M., Fiala, D. & Rosendorf, P. (2010) Estimation of phosphorus loads with sparse data for agricultural watersheds in the Czech Republic. Hydrol. Sci. J. 55(8), 1417–1426. 相似文献
7.
《水文科学杂志》2013,58(6)
Abstract Abstract An approach was developed for combining streamflow drought information from synthetic (generated) data with data reconstructed based on palaeoclimatic information (tree ring widths). The tree ring data were used to reconstruct streamflow in periods when no streamflow data were collected. The reconstructed data were then used as a source of historical data for estimating drought severity quantiles. The generated data were obtained using a nearest neighbour resampling method while the tree ring reconstruction was accomplished using a regression model. The application of the approach was to data from the Athabasca River in Alberta, Canada. The results demonstrate the feasibility and the utility of the approach for obtaining more accurate and precise estimates of extreme drought severity quantiles. 相似文献
8.
The importance of incorporating diurnally fluctuating stream discharge in stream temperature energy balance models 
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下载免费PDF全文 Although stream temperature energy balance models are useful to predict temperature through time and space, a major unresolved question is whether fluctuations in stream discharge reduce model accuracy when not exactly represented. However, high‐frequency (e.g., subdaily) discharge observations are often unavailable for such simulations, and therefore, diurnal streamflow fluctuations are not typically represented in energy balance models. These fluctuations are common due to evapotranspiration, snow pack or glacial melt, tidal influences within estuaries, and regulated river flows. In this work, we show when to account for diurnally fluctuating streamflow. To investigate how diurnal streamflow fluctuations affect predicted stream temperatures, we used a deterministic stream temperature model to simulate stream temperature along a reach in the Quilcayhuanca Valley, Peru, where discharge varies diurnally due to glacial melt. Diurnally fluctuating streamflow was varied alongside groundwater contributions via a series of computational experiments to assess how uncertainty in reach hydrology may impact simulated stream temperature. Results indicated that stream temperatures were more sensitive to the rate of groundwater inflow to the reach compared with the timing and amplitude of diurnal fluctuations in streamflow. Although incorporating observed diurnal fluctuations in discharge resulted in a small improvement in model RMSE, we also assessed other diurnal discharge signals and found that high amplitude signals were more influential on modelled stream temperatures when the discharge peaked at specific times. Results also showed that regardless of the diurnal discharge signal, the estimated groundwater flux to the reach only varied from 1.7% to 11.7% of the upstream discharge. However, diurnal discharge fluctuations likely have a stronger influence over longer reaches and in streams where the daily range in discharge is larger, indicating that diurnal fluctuations in stream discharge should be considered in certain settings. 相似文献
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Assessing the influence of afforestation with Eucalyptus globulus on hydrological response from a small catchment in northwestern Spain using the HBV hydrological model 下载免费PDF全文
下载免费PDF全文 Land use change as conversion pasture to forest produces several changes on hydrological cycle. In this paper, we analyse the effects on stream discharge of afforestation of a small watershed devoted to pasture using the HBV hydrological model. Streamflow data obtained over the first 10 years after planting were employed to evaluate the capacity of HBV model to simulate hydrological behaviour of catchment after afforestation. Obtained results indicate that the estimation of streamflow was accurate as reflected by statistics (R2 = 0.90, NSC = 0.89 and PBIAS = 0.34). Afterwards, streamflow under pasture land use (if afforestation had not occurred) was simulated using hydrometeorological data collected during the period of study and model parameters optimized previously, together with two parameters, pcorr and cevpfo, that were adjusted for pasture conditions. The HBV model results indicate that afforestation produced a water yield reduction around 2000 mm (22% of total stream discharge) during the first 10 years of planting growth. The differences between forest and pasture land cover are increasing in all seasons year by year. The greatest streamflow reduction was observed in wet period (autumn and winter) with 76% of total reduction. In summer, streamflow reduction represents only 3% of total, however, represents 24.7% of discharge in this season. Streamflow reduction was related to increase of rainfall interception (mainly in wet periods) and the increase of evapotranspiration by plantation in dry periods. Copyright © 2013 John Wiley & Sons, Ltd. 相似文献
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《水文科学杂志》2013,58(3):640-655
Abstract Water temperature is an important abiotic variable in aquatic habitat studies and may be one of the factors limiting the potential fish habitat (e.g. salmonids) in a stream. Stream water temperatures are modelled using statistical approaches with air temperature and streamflow as exogenous variables in the Nivelle River, southern France. Two different models are used to model mean weekly maximum temperature data: a non-parametric approach, the k-nearest neighbours method (k-NN) and a parametric approach, the periodic autoregressive model with exogenous variables (PARX). The k-NN is a data-driven method, which consists of finding, at each point of interest, a small number of neighbours nearest to this value, and the prediction is estimated based on these neighbours. The PARX model is an extension of commonly-used autoregressive models in which parameters are estimated for each period within the years. Different variants of air temperature and flow are used in the model development. In order to test the performance of these models, a jack-knife technique is used, whereby model goodness of fit is assessed separately for each year. The results indicate that both models give good performances, but the PARX model should be preferred, because of its good estimation of the individual weekly temperatures and its ability to explicitly predict water temperature using exogenous variables. 相似文献
11.
Reservoir sizing is one of the most important aspects of water resources engineering as the storage in a reservoir must be sufficient to supply water during extended droughts. Typically, observed streamflow is used to stochastically generate multiple realizations of streamflow to estimate the required storage based on the Sequent Peak Algorithm (SQP). The main limitation in this approach is that the parameters of the stochastic model are purely derived from the observed record (limited to less than 80 years of data) which does not have information related to prehistoric droughts. Further, reservoir sizing is typically estimated to meet future increase in water demand, and there is no guarantee that future streamflow over the planning period will be representative of past streamflow records. In this context, reconstructed streamflow records, usually estimated based on tree ring chronologies, provide better estimates of prehistoric droughts, and future streamflow records over the planning period could be obtained from general circulation models (GCMs) which provide 30 year near-term climate change projections. In this study, we developed paleo streamflow records and future streamflow records for 30 years are obtained by forcing the projected precipitation and temperature from the GCMs over a lumped watershed model. We propose combining observed, reconstructed and projected streamflows to generate synthetic streamflow records using a Bayesian framework that provides the posterior distribution of reservoir storage estimates. The performance of the Bayesian framework is compared to a traditional stochastic streamflow generation approach. Findings based on the split-sample validation show that the Bayesian approach yielded generated streamflow traces more representative of future streamflow conditions than the traditional stochastic approach thereby, reducing uncertainty on storage estimates corresponding to higher reliabilities. Potential strategies for improving future streamflow projections and its utility in reservoir sizing and capacity expansion projects are also discussed. 相似文献
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ABSTRACTEvaluation of streamflow depletion induced by groundwater pumping is important for watershed management. Many analytical and numerical solutions exist for estimating depletion for various hydro-geologic scenarios. Numerical models are time consuming and require significant data input, and moreover, are problem-specific. Analytical models are convenient because of their ease of use, minimum data requirements, and instantaneous solutions, but are only applicable for idealistic scenarios. In many cases, analytical models are used for decision making on water-withdrawal permits, because they are assumed to offer conservative estimates of depletion. However, a systematic study of the applicability of these analytical models has not been done. In this research, we critically evaluate the performance of the analytical models in complex hydro-geologic settings, and list the factors that most significantly impact depletions. On the basis of this study, we find that the analytical models perform satisfactorily as a screening-level tool, though there are some situations when they perform poorly. The factors that most significantly impact streamflow depletion are spatial variability in hydraulic conductivity and the presence of other sources of water, such as lakes and wetlands. The analytical models do make conservative predictions of streamflow depletion especially for the most vulnerable streams.
Editor D. Koutsoyiannis; Associate editor X. Chen 相似文献
14.
Yanchun Zhou 《水文科学杂志》2015,60(7-8):1340-1360
AbstractThis paper quantifies the impacts of bushfire and climate variability on streamflow from three southeast Australian catchments where bushfires occurred in February 1983. Three hydrological models (AWRA-L, Xinanjiang and GR4J) were first calibrated against streamflow data from the pre-bushfire period and then used to simulate runoff for the post-bushfire period with the calibrated parameters. The difference in simulated streamflow between pre- and post-bushfire periods provides an estimate of the impact of climate variability on streamflow. The impact of bushfire on streamflow is quantified by removing the climate variability impact from the difference in mean annual observed streamflow between post- and pre-bushfire periods. For the first 15 years after the 1983 bushfires, the results from hydrological models for the three catchments indicate that there is a substantial increase in streamflow; this is attributed to initial decreases in evapotranspiration and soil infiltration rates resulting from the fires, followed by logging activity. After 15 years, streamflow dynamics are more heavily influenced by climate effects, although some impact from fire and logging regeneration may still occur. The results show that hydrological models provide reasonably consistent estimates of bushfire and climate impacts on streamflow for the three catchments. The models can be used to quantify relative contributions of forest disturbance (bushfire, logging and other forest management) and climate variability. The results presented can also help forest managers understand the relationship between bushfire and climate variability impacts on water yield in the context of climate variability. 相似文献
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Considerable uncertainty occurs in the parameter estimates of traditional rainfall–water level transfer function noise (TFN) models, especially with the models built using monthly time step datasets. This is due to the equal weights assigned for rainfall occurring during both water level rise and water level drop events while estimating the TFN model parameters using the least square technique. As an alternative to this approach, a threshold rainfall-based binary-weighted least square method was adopted to estimate the TFN model parameters. The efficacy of this binary-weighted approach in estimating the TFN model parameters was tested on 26 observation wells distributed across the Adyar River basin in Southern India. Model performance indices such as mean absolute error and coefficient of determination values showed that the proposed binary-weighted approach of fitting independent threshold-based TFN models for water level rise and water level drop scenarios considerably improves the model accuracy over other traditional TFN models.
EDITOR D. KoutsoyiannisASSOCIATE EDITOR A. Fiori 相似文献
16.
《水文科学杂志》2013,58(4)
Abstract The abilities of neuro-fuzzy (NF) and neural network (NN) approaches to model the streamflow–suspended sediment relationship are investigated. The NF and NN models are established for estimating current suspended sediment values using the streamflow and antecedent sediment data. The sediment rating curve and multi-linear regression are also applied to the same data. Statistic measures were used to evaluate the performance of the models. The daily streamflow and suspended sediment data for two stations—Quebrada Blanca station and Rio Valenciano station—operated by the US Geological Survey were used as case studies. Based on comparison of the results, it is found that the NF model gives better estimates than the other techniques. 相似文献
17.
Kwabena Kankam-Yeboah Emmanuel Obuobie Barnabas Amisigo Yaw Opoku-Ankomah 《水文科学杂志》2013,58(4):773-788
Abstract This study uses the Soil and Water Assessment Tool (SWAT) and downscaled climate projections from the ensemble of two global climate models (ECHAM4 and CSIRO) forced by the A1FI greenhouse-gas scenario to estimate the impact of climate change on streamflow in the White Volta and Pra river basins, Ghana. The SWAT model was calibrated for the two basins and subsequently driven by downscaled future climate projections to estimate the streamflow for the 2020s (2006–2035) and 2050s (2036–2075). Relative to the baseline, the mean annual streamflow estimated for the White Volta basin for the 2020s and 2050s showed a decrease of 22 and 50%, respectively. Similarly, the estimated streamflow for the 2020s and 2050s for the Pra basin showed a decrease of 22 and 46%, respectively. These results underscore the need to put in place appropriate adaptation measures to foster resilience to climate change in order to enhance water security within the two basins. Citation Kankam-Yeboah, K., Obuobie, E., Amisigo, B., and Opoku-Ankomah, Y., 2013. Impact of climate change on streamflow in selected river basins in Ghana. Hydrological Sciences Journal, 58 (4), 773–788. 相似文献
18.
Assimilation of historical head data to estimate spatial distributions of stream bed and aquifer hydraulic conductivity fields 下载免费PDF全文
下载免费PDF全文 Management of water resources in alluvial aquifers relies mainly on understanding interactions between hydraulically connected streams and aquifers. Numerical models that simulate this interaction often are used as decision support tools for water resource management. However, the accuracy of numerical predictions relies heavily on unknown system parameters (e.g., streambed conductivity and aquifer hydraulic conductivity), which are spatially heterogeneous and difficult to measure directly. This paper employs an ensemble smoother to invert groundwater level measurements to jointly estimate spatially varying streambed and alluvial aquifer hydraulic conductivity along a 35.6‐km segment of the South Platte River in Northeastern Colorado. The accuracy of the inversion procedure is evaluated using a synthetic experiment and historical groundwater level measurements, with the latter constituting the novelty of this study in the inversion and validation of high‐resolution fields of streambed and aquifer conductivities. Results show that the estimated streambed conductivity field and aquifer conductivity field produce an acceptable agreement between observed and simulated groundwater levels and stream flow rates. The estimated parameter fields are also used to simulate the spatially varying flow exchange between the alluvial aquifer and the stream, which exhibits high spatial variability along the river reach with a maximum average monthly aquifer gain of about 2.3 m3/day and a maximum average monthly aquifer loss of 2.8 m3/day, per unit area of streambed (m2). These results demonstrate that data assimilation inversion provides a reliable and computationally affordable tool to estimate the spatial variability of streambed and aquifer conductivities at high resolution in real‐world systems. 相似文献
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ABSTRACTThe Hargreaves method provides reference evapotranspiration (ETo) estimates when only air temperature data are available, although it requires previous local calibration for an acceptable performance. This method was evaluated using the data from 71 meteorological stations in the Seolma-cheon basin (8.48 km2), South Korea, comparing daily estimates against those from the Penman‐Monteith (PM) method, which was used as the standard. To estimate reference ETo more exactly, considering the climatological characteristics in South Korea, parameter regionalization of the Hargreaves equation is carried out. First, the modified Hargreaves equation is presented after an analysis of the relationship between solar radiation and temperature. Second, parameter (KET) optimization of the regional calibration of the Hargreaves equation (RCH) is performed using the PM method and the modified equation at 71 meteorological stations. Next, an application was carried out to evaluate the evapotranspiration methods (PM, original Hargreaves and RCH) in the SWAT (Soil and Water Assessment Tool) model by comparing these with the measured actual evapotranspiration (AET) in the basin. The SWAT model was calibrated using 3 years (2007–2009) of daily streamflow at the watershed outlet and 3 years (2007–2009) of daily AET measured at a mixed forest. The model was validated with 3 years (2010‐2012) of streamflow and AET. RCH will contribute to a better understanding of evapotranspiration of an ungauged watershed in areas where meteorological information is scarce.
EDITOR D. Koutsoyiannis ASSOCIATE EDITOR Not assigned 相似文献
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Low‐flow characteristics can be estimated by multiple linear regressions or the index‐streamgage approach. The latter transfers streamflow information from a hydrologically similar, continuously gaged basin (‘index streamgage’) to one with a very limited streamflow record, but often results in biased estimates. The application of the index‐streamgage approach can be generalized into three steps: (1) selection of streamflow information of interest, (2) definition of hydrologic similarity and selection of index streamgage, and (3) application of an information‐transfer approach. Here, we explore the effects of (1) the range of streamflow values, (2) the areal density of streamgages, and (3) index‐streamgage selection criteria on the bias of three information‐transfer approaches on estimates of the 7‐day, 10‐year minimum streamflow (Q7, 10). The three information‐transfer approaches considered are maintenance of variance extension, base‐flow correlation, and ratio of measured to concurrent gaged streamflow (Q‐ratio invariance). Our results for 1120 streamgages throughout the United States suggest that only a small portion of the total bias in estimated streamflow values is explained by the areal density of the streamgages and the hydrologic similarity between the two basins. However, restricting the range of streamflow values used in the index‐streamgage approach reduces the bias of estimated Q7, 10 values substantially. Importantly, estimated Q7, 10 values are heavily biased when the observed Q7, 10 values are near zero. Results of the analysis also showed that Q7, 10 estimates from two of the three index‐streamgage approaches have lower root‐mean‐square error values than estimates derived from multiple regressions for the large regions considered in this study. Published in 2011 by John Wiley & Sons, Ltd. 相似文献