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1.
Abstract

The method of fragments is applied to the generation of synthetic monthly streamflow series using streamflow data from 34 gauging stations in mainland Portugal. A generation model based on the random sampling of the log-Pearson Type III distribution was applied to each sample to generate 1200 synthetic series of annual streamflow with an equal length to that of the sample. The synthetic annual streamflow series were then disaggregated into monthly streamflows using the method of fragments, by three approaches that differed in terms of the establishment of classes and the selection of fragments. The results of the application of such approaches were compared in terms of the capacity of the method to preserve the main monthly statistical parameters of the historical samples.

Editor D. Koutsoyiannis; Associate editor C. Onof

Citation Silva, A.T. and Portela, M.M., 2012. Disaggregation modelling of monthly streamflows using a new approach of the method of fragments. Hydrological Sciences Journal, 57 (5), 942–955.  相似文献   

2.
C. Dai 《水文科学杂志》2013,58(13):1616-1628
ABSTRACT

To improve the convergence of multiple-site weather generators (SWGs) based on the brute force algorithm (MBFA), a genetic algorithm (GA) is proposed to search the overall optimal correlation matrix. Precipitation series from weather generators are used as input to the hydrological model, the soil and water assessment tool (SWAT), to generate runoff over the Red Deer watershed, Canada for further runoff analysis. The results indicate that the SWAT model using SWG-generated data accurately represents the mean monthly streamflow for most of the months. The multi-site generators were capable of better representing the monthly streamflow variability, which was notably underestimated by the single-site version. In terms of extreme flows, the proposed method reproduced the observed extreme flow with smaller bias than MBFA, while the single-site generator significantly underestimated the annual maximum flows due to its poor capability in addressing partial precipitation correlations.  相似文献   

3.
Abstract

The method of L-moment ratio diagrams along with the averaged weighted distance (AWD) is applied to identify a probability distribution of annual minimum streamflow, namely annual minimum daily streamflow in 11 climatic regions of Canada. Across the entire country, the Pearson type III probability distribution is an acceptable distribution for describing annual minimum streamflow with the 3-parameter lognormal and log Pearson type III distributions as potential candidates. Some minor differences in the probability distribution type among different climatic regions are also observed, which may be taken into account in the selection of the distribution type of annual minimum streamflow.  相似文献   

4.
Abstract

Two parameter and modified three parameter lognormal lag one Markov models are applied to twelve arid zone streams. A modified method of fragments is used to disaggregate the annual generated flows to yield monthly values. Parameters based on the generated flows are compared with historical values. It is concluded that it is possible to generate satisfactorily both annual and monthly streamflows for arid zone streams.  相似文献   

5.
Abstract

A modelling experiment is used to examine different land-use scenarios ranging from extreme deforestation (31% forest cover) to pristine (95% forest cover) conditions and related Payment for Ecosystem Services (PES) schemes to assess whether a change in streamflow dynamics, discharge extremes and mean annual water balance of a 73.4-km2 tropical headwater catchment in Costa Rica could be detected. A semi-distributed, conceptual rainfall–runoff model was adapted to conceptualize the empirically-based, dominant hydrological processes of the study area and was multi-criteria calibrated using different objective functions and empirical constraints on model simulations in a Monte Carlo framework to account for parameter uncertainty. The results suggest that land-use change had relatively little effect on the overall mean annual water yield (<3%). However, streamflow dynamics proved to be sensitive in terms of frequency, timing and magnitude of discharge extremes. For low flows and peak discharges of return periods greater than one year, land use had a minor influence on the runoff response. Below these thresholds (<1-year return period), forest cover potentially decreased runoff peaks and low flows by as much as 10%, and non-forest cover increased runoff peaks and low flows by up to 15%. The study demonstrated the potential for using hydrological modelling to help identify the impact of protection and reforestation efforts on ecosystem services.

Editor Z.W. Kundzewicz

Citation Birkel, C., Soulsby, C., and Tetzlaff, D., 2012. Modelling the impacts of land-cover change on streamflow dynamics of a tropical rainforest headwater catchment. Hydrological Sciences Journal, 57 (8), 1543–1561.  相似文献   

6.
ABSTRACT

As time irreversibility of streamflow is marked for time scales up to several days, while common stochastic generation methods are good only for time-symmetric processes, the need for new methods to handle irreversibility, particularly in flood simulations, has been recently highlighted. From an investigation of the historical evolution of existing stochastic generation methods, which is a useful step before proposing new methods, the strengths and weaknesses of current approaches are located. Following this investigation, a generic solution to the stochastic generation problem is proposed. This is an analytical exact method based on an asymmetric moving-average scheme, capable of handling time irreversibility in addition to preserving the second-order stochastic structure, as well as higher-order marginal statistics, of a process. The method is studied theoretically in its general setting, as well as in its most interesting special cases, and is successfully applied to streamflow generation at an hourly scale.  相似文献   

7.
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   

8.
《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   

9.
Abstract

In determining the possible influence of climate change, it is important to understand the temporal and spatial variability in streamflow response for diverse climate zones. Thus, the aim of this study was to determine the presence of changes in annual maximum peak flow for two climate zones in Chile over the past few decades. A general analysis, a flood frequency analysis and a trend analysis were used to study such changes between 1975 and 2008 for a semi-arid (29°S–32°S) and a temperate (36°S–38°S) climatic zone. The historic annual maxima, minima and mean flows, as well as decadal mean peak flow, were compared over the period of record. The Gumbel distribution was selected to compare the 30-year flood values of two ±15-year intervals, which showed that streamflow decreased by an average of 19.5% in the semi-arid stations and increased by an average of 22.6% in the temperate stations. The Mann-Kendall test was used to investigate the temporal changes in streamflows, with negative trends being observed in 87% of the stations analysed in the semi-arid zone, and positive trends in 57% of those analysed in the temperate zone. These differences in streamflow response between climate zones could be related to recent documented increases in altitude of the zero-degree isotherm in the Andes Mountains of Chile, since most of the significant positive and negative changes were detected in first-order rivers located closer to this mountain range.

Editor D. Koutsoyiannis; Associate editor H. Lins

Citation Pizarro, R., Vera, M., Valdés, R., Helwig, B., and Olivares, C., 2013. Multi-decadal variations in annual maximum peak flows in semi-arid and temperate regions of Chile. Hydrological Sciences Journal, 59 (2), 300–311.  相似文献   

10.
Abstract

The objectives of this work are: (a) to statistically test and quantify the decreasing trends of streamflow and sediment discharge of the Yellow River in China during 1950–2005, (b) to identify change points or transition years of the decreasing trends, and (c) to diagnose whether the decreasing trends were caused by precipitation changes or human intervention, or both. The results show that significant decreasing trends in annual streamflow and sediment discharge have existed since the late 1950s at three stations located in the upper, middle, and lower reaches of the Yellow River (P?=?0.01). Change-point analyses further revealed that transition years existed and that rapid decline in streamflow and sediment discharge began in 1985 in most parts of the basin (P?=?0.05). Adoption of conservation measures in the 1980s and 1990s corroborates the identified transition years. Double-mass curves of precipitation vs streamflow (sediment) for the periods before and after the transition years show remarkable decreases in proportionality of streamflow (sediment) generation. All percentiles of streamflow and sediment discharge after the transition years showed rapid reduction. In the absence of significantly decreasing precipitation trends, it is concluded that the decreasing trends were very likely caused by human intervention. Relative to the period before the transition, human intervention during 1985–2005 reduced cumulative streamflow by 13.5, 14.3 and 24.6% and cumulative sediment discharge by 29.0, 24.8 and 26.5%, at Toudaoguai, Huayuankou and Lijin, respectively, showing the quantitative conservation effect in the basin.

Citation Gao, P., Zhang, X.-C., Mu, X.-M., Wang, F., Li, R. & Zhang, X. (2010) Trend and change-point analyses of streamflow and sediment discharge in the Yellow River during 1950–2005. Hydrol. Sci. J. 55(2), 275–285.  相似文献   

11.
Abstract

Trends in high and low flows are valuable indicators of hydrological change because they highlight changes in various parts of the frequency distribution of streamflow series. This enables improved assessment of water availability in regions with high seasonal and inter-annual variability. There has been a substantial reduction in water resources in the Duero basin (Iberian Peninsula, Spain) and other areas of the Mediterranean region during the last 50 years, and this is likely to continue because of climate change. In this study, we investigated the evolution and trends in high and low flows in the Spanish part of the Duero basin, and in equivalent or closely-related precipitation indices for the period 1961–2005. The results showed a general trend of decrease in the frequency and magnitude of high flows throughout most of the basin. Moreover, the number of days with low flows significantly increased over this period. No clear relationship was evident between the evolution of high/low flows and changes in the distribution frequencies of the precipitation series. In contrast to what was expected, the number of days with heavy precipitation and the mean annual precipitation did not show significant trends across the basin, and the number of days without rainfall decreased slightly. The divergence between precipitation and runoff evolution was more accentuated in spring and summer. In the absence of trends in precipitation, it is possible that reforestation processes in the region, and increasing temperatures in recent decades, could be related to the decreasing frequency of high flows and the increasing frequency of low flows.

Editor Z.W. Kundzewicz; Associate editor S. Grimaldi

Citation Morán-Tejeda, E., López-Moreno, J.I., Vicente-Serrano, S.M., Lorenzo-Lacruz, J. and Ceballos-Barbancho, A., 2012. The contrasted evolution of high and low flows and precipitation indices in the Duero basin (Spain). Hydrological Sciences Journal, 57 (4), 591–611.  相似文献   

12.
ABSTRACT

In this study, the distributed catchment-scale model, DiCaSM, was applied on five catchments across the UK. Given its importance, river flow was selected to study the uncertainty in streamflow prediction using the Generalized Likelihood Uncertainty Estimation (GLUE) methodology at different timescales (daily, monthly, seasonal and annual). The uncertainty analysis showed that the observed river flows were within the predicted bounds/envelope of 5% and 95% percentiles. These predicted river flow bounds contained most of the observed river flows, as expressed by the high containment ratio, CR. In addition to CR, other uncertainty indices – bandwidth B, relative bandwidth RB, degrees of asymmetry S and T, deviation amplitude D, relative deviation amplitude RD and the R factor – also indicated that the predicted river flows have acceptable uncertainty levels. The results show lower uncertainty in predicted river flows when increasing the timescale from daily to monthly to seasonal, with the lowest uncertainty associated with annual flows.  相似文献   

13.
Abstract

Streamflow variability in the Upper and Lower Litani basin, Lebanon was modelled as there is a lack of long-term measured runoff data. To simulate runoff and streamflow, daily rainfall was derived using a stochastic rainfall generation model and monthly rainfall data. Two distinct synthetic rainfall models were developed based on a two-part probabilistic distribution approach. The rainfall occurrence was described by a Markov chain process, while the rainfall distribution on wet days was represented by two different distributions (i.e. gamma and mixed exponential distributions). Both distributions yielded similar results. The rainfall data were then processed using water balance and routing models to generate daily and monthly streamflow. Compared with measured data, the model results were generally reasonable (mean errors ranging from 0.1 to 0.8?m3/s at select locations). Finally, the simulated monthly streamflow data were used to investigate discharge trends in the Litani basin during the 20th century using the Mann-Kendall and Sen slope nonparametric trend detection methods. A significant drying trend of the basin was detected, reaching a streamflow reduction of 0.8 and 0.7 m3/s per decade in January for the Upper and Lower basin, respectively.

Editor D. Koutsoyiannis; Associate editor Sheng Yue

Citation Ramadan, H.H., Beighley, R.E., and Ramamurthy, A.S., 2012. Modelling streamflow trends for a watershed with limited data: case of the Litani basin, Lebanon. Hydrological Sciences Journal, 57 (8), 1516–1529.  相似文献   

14.
Abstract

This study aims to assess the potential impact of climate change on flood risk for the city of Dayton, which lies at the outlet of the Upper Great Miami River Watershed, Ohio, USA. First the probability mapping method was used to downscale annual precipitation output from 14 global climate models (GCMs). We then built a statistical model based on regression and frequency analysis of random variables to simulate annual mean and peak streamflow from precipitation input. The model performed well in simulating quantile values for annual mean and peak streamflow for the 20th century. The correlation coefficients between simulated and observed quantile values for these variables exceed 0.99. Applying this model with the downscaled precipitation output from 14 GCMs, we project that the future 100-year flood for the study area is most likely to increase by 10–20%, with a mean increase of 13% from all 14 models. 79% of the models project increase in annual peak flow.

Citation Wu, S.-Y. (2010) Potential impact of climate change on flooding in the Upper Great Miami River Watershed, Ohio, USA: a simulation-based approach. Hydrol. Sci. J. 55(8), 1251–1263.  相似文献   

15.
Abstract

Discharge in most rivers consists mainly of baseflow exfiltrating from shallow groundwater reservoirs, while surface or other direct flows cease soon after rain storms or snowmelt. Analysis of observed baseflow recessions of two rivers in Turkey with intermittent flows and different geographical and climatic characteristics yielded nonlinear storage–outflow relationships of the highly seasonal aquifers. Baseflow separation was carried out using a nonlinear reservoir algorithm. Baseflow seasonality is related to the hydro-climatic conditions influencing groundwater recharge and evapotranspiration of groundwater. As intermittent streams generally have zero flows in the dry season, calibration of recession parameters is in many cases a complicated task.

Citation Aksoy, H. & Wittenberg, H. (2011) Nonlinear baseflow recession analysis in watersheds with intermittent streamflow. Hydrol. Sci. J. 56(2), 226–237.  相似文献   

16.
ABSTRACT

The 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   

17.
Abstract

The annual water balance of Lake Kyoga is estimated by a comparison of upstream and downstream flows in the Nile channel during a period of reliable measurements (1940–1977), supported by rainfall records over the basin. The relative contributions of net lake rainfall and tributary inflows are estimated. Changes in annual rainfall and seasonal distribution are examined.

Editor Z.W. Kundzewicz

Citation Brown, E. and Sutcliffe, J.V., 2013. The water balance of Lake Kyoga, Uganda. Hydrological Sciences Journal, 58 (2), 342–353.  相似文献   

18.
Provision of reliable scientific support to socio‐economic development and eco‐environmental conservation is challenged by complexities of irregular nonlinearities, data uncertainties, and multivariate dependencies of hydrological systems in the Three Gorges Reservoir (TGR) region, China. Among them, the irregular nonlinearities mainly represent unreliability of regular functions for robust simulation of highly complicated relationships between variables. Based on the proposed discrete principal‐monotonicity inference (DPMI) approach, streamflow generation in the Xingshan Watershed, a representative watershed in this region, is examined. Based on system characterization, predictor identification, and streamflow distribution transformation, DPMI parameters are calibrated through a two‐stage strategy. Results indicate that the modelling efficiency of DPMI is satisfactory for streamflow simulation under these complexities. The distribution transformation method and the two‐stage calibration strategy can deal with non‐normality of streamflow and temporally unstable accuracy of hydrological models, respectively. The DPMI process and results reveal that both streamflow uncertainty and its rising tendency increase with flow levels. The dominant driving forces of streamflow generation are daily lowest temperature and daily cumulative precipitation in consideration of performances in global and local scales. The temporal heterogeneity of local significances to streamflow is insignificant for meteorological conditions. There is significant nonlinearity between meteorological conditions and streamflow and dependencies among meteorological conditions. The generation mechanism of low flows is more complicated than medium flows and high flows. The DPMI approach can facilitate improving robustness of hydro‐system analysis studies in the Xingshan Watershed or the TGR region. Copyright © 2016 John Wiley & Sons, Ltd.  相似文献   

19.
ABSTRACT

Understanding streamflow patterns by incorporating climate signal information can contribute remarkably to the knowledge of future local environmental flows. Three machine learning models, the multivariate adaptive regression splines (MARS), the M5 Model Tree and the least squares support vector machine (LSSVM) are established to predict the streamflow pattern over the Mediterranean region of Turkey (Besiri and Baykan stations). The structure of the predictive models is built using synoptic-scale climate signal information and river flow data from antecedent records. The predictive models are evaluated and assessed using quantitative and graphical statistics. The correlation analysis demonstrates that the North Pacific (NP) and the East Central Tropical Pacific Sea Surface Temperature (Niño3.4) indices have a substantial influence on the streamflow patterns, in addition to the historical information obtained from the river flow data. The model results reveal the utility of the LSSVM model over the other models through incorporating climate signal information for modelling streamflow.  相似文献   

20.
ABSTRACT

Much of New Hampshire and Vermont (combined area = 50 000 km2) has hilly to mountainous topography. Elevations range from 0 to 1900 m a.s.l. (average = 360 m), and many peaks exceed 1200 m. Mean annual precipitation increases strongly with elevation (adjusted for additional orographic effects and distance from moisture sources), as do mean monthly precipitation, snow depth, and snow water equivalents. Mean monthly temperatures decrease with elevation, largely masking latitudinal effects, and can be used with other information to show how potential evapotranspiration changes with elevation. These effects combine to produce strong elevational increases in mean annual streamflow and, more surprisingly, cause streamflow variability, both short term and annual, to decrease with mean drainage basin elevation. Low flows for a given exceedance probability increase markedly as mean basin elevation increases above 340 m. Flood peaks for a given return period also increase with mean basin elevation. Slope and aspect affect the timing of snowmelt runoff, but otherwise appear to have only second order effects on hydrology. The effect of elevation is so dominant in the region that it can be used as the single independent variable in predicting many streamflow parameters.  相似文献   

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