共查询到20条相似文献，搜索用时 31 毫秒
1.
To predict future river flows, empirical trend projection (ETP) analyses and extends historic trends, while hydroclimatic modelling (HCM) incorporates regional downscaling from global circulation model (GCM) outputs. We applied both approaches to the extensively allocated Oldman River Basin that drains the North American Rocky Mountains and provides an international focus for water sharing. For ETP, we analysed monthly discharges from 1912 to 2008 with non‐parametric regression, and extrapolated changes to 2055. For modelling, we refined the physical models MTCLIM and SNOPAC to provide water inputs into RIVRQ (river discharge), a model that assesses the streamflow regime as involving dynamic peaks superimposed on stable baseflow. After parameterization with 1960–1989 data, we assessed climate forecasts from six GCMs: CGCM1‐A, HadCM3, NCAR‐CCM3, ECHAM4 and 5 and GCM2. Modelling reasonably reconstructed monthly hydrographs (R2 about 0·7), and averaging over three decades closely reconstructed the monthly pattern (R2 = 0·94). When applied to the GCM forecasts, the model predicted that summer flows would decline considerably, while winter and early spring flows would increase, producing a slight decline in the annual discharge (?3%, 2005–2055). The ETP predicted similarly decreased summer flows but slight change in winter flows and greater annual flow reduction (?9%). The partial convergence of the seasonal flow projections increases confidence in a composite analysis and we thus predict further declines in summer (about ? 15%) and annual flows (about ? 5%). This composite projection indicates a more modest change than had been anticipated based on earlier GCM analyses or trend projections that considered only three or four decades. For other river basins, we recommend the utilization of ETP based on the longest available streamflow records, and HCM with multiple GCMs. The degree of correspondence from these two independent approaches would provide a basis for assessing the confidence in projections for future river flows and surface water supplies. Copyright © 2010 John Wiley & Sons, Ltd. 相似文献
2.
Gopal Chandra Saha 《水文科学杂志》2020,65(12):2142-2158
ABSTRACT The temporal dynamics of groundwater–surface water interaction under the impacts of various water abstraction scenarios are presented for hydraulic fracturing in a shale gas and oil play area (23 984.9 km2), Alberta, Canada, using the MIKE-SHE and MIKE-11 models. Water-use data for hydraulic fracturing were obtained for 433 wells drilled in the study area in 2013 and 2014. Modelling results indicate that water abstraction for hydraulic fracturing has very small (<0.35%) negative impacts on mean monthly and annual river and groundwater levels and stream and groundwater flows in the study area, and small (1–4.17%) negative impacts on environmental flows near the water abstraction location during low-flow periods. The impacts on environmental flow depend on the amount of water abstraction and the daily flow over time at a specific river cross-section. The results also indicate a very small (<0.35%) positive impact on mean monthly and annual groundwater contributions to streamflow because of the large study area. The results provide useful information for planning long-term seasonal and annual water abstractions from the river and groundwater for hydraulic fracturing in a large study area. 相似文献
3.
D. M. SARGENT 《水文科学杂志》2013,58(4):509-527
Abstract A technique for generating sequences of daily streamflows is presented which preserves the important characteristics of the daily flow hydrograph by the the use of a number of simple processes. The daily flow model is applied, in conjunction with a disaggregation model to preserve statistics of monthly and annual flows, to historic data for a river in the northwest of England. Several sets of synthetic data generated by the model are tested for their acceptability. 相似文献
4.
ABSTRACTThe application of remotely-sensed data for hydrological modeling of the Congo Basin is presented. Satellite-derived data, including TRMM precipitation, are used as inputs to drive the USGS Geospatial Streamflow Model (GeoSFM) to estimate daily river discharge over the basin from 1998 to 2012. Physically-based parameterization was augmented with a spatially-distributed calibration that enables GeoSFM to simulate hydrological processes such as the slowing effect of the Cuvette Centrale. The resulting simulated long-term mean of daily flows and the observed flow at the Kinshasa gauge were comparable (40 631 and 40 638 m3/s respectively), in the 7-year validation period (2004–2010), with no significant bias and a Nash-Sutcliffe model efficiency coefficient of 0.70. Modeled daily flows and aggregated monthly river outflows (compared to historical averages) for additional sites confirm the model reliability in capturing flow timing and seasonality across the basin, but sometimes fails to accurately predict flow magnitude. The results of this model can be useful in research and decision-making contexts and validate the application of satellite-based hydrological models driven for large, data-scarce river systems such as the Congo. 相似文献
5.
《水文科学杂志》2013,58(3):503-518
Abstract Two parameters of importance in hydrological droughts viz. the longest duration, LT and the largest severity, ST (in standardized form) over a desired return period, T years, have been analysed for monthly flow sequences of Canadian rivers. An important point in the analysis is that monthly sequences are non-stationary (periodic-stochastic) as against annual flows, which fulfil the conditions of stochastic stationarity. The parameters mean, μ, standard deviation, σ (or coefficient of variation), lag1 serial correlation, ρ, and skewness, γ (which is helpful in identifying the probability distribution function) of annual flow sequences, when used in the analytical relationships, are able to predict expected values of the longest duration, E(LT ) in years and the largest standardized severity, E(ST ). For monthly flow sequences, there are 12 sets of these parameters and thus the issue is how to involve these parameters to derive the estimates of E(LT ) and E(ST ). Moreover, the truncation level (i.e. the monthly mean value) varies from month to month. The analysis in this paper demonstrates that the drought analysis on an annual basis can be extended to monthly droughts simply by standardizing the flows for each month. Thus, the variable truncation levels corresponding to the mean monthly flows were transformed into one unified truncation level equal to zero. The runs of deficits in the standardized sequences are treated as drought episodes and thus the theory of runs forms an essential tool for analysis. Estimates of the above parameters (denoted as μav, σav, ρav, and γav) for use in the analytical relationships were obtained by averaging 12 monthly values for each parameter. The product- and L-moment ratio analyses indicated that the monthly flows in the Canadian rivers fit the gamma probability distribution reasonably well, which resulted in the satisfactory prediction of E(LT ). However, the prediction of E(ST ) tended to be more satisfactory with the assumption of a Markovian normal model and the relationship E(ST ) ≈ E(LT ) was observed to perform better. 相似文献
6.
ABSTRACTThere is an implicit assumption in most work that the parameters calibrated based on observations remain valid for future climatic conditions. However, this might not be true due to parameter instability. This paper investigates the uncertainty and transferability of parameters in a hydrological model under climate change. Parameter transferability is investigated with three parameter sets identified for different climatic conditions, which are: wet, intermediate and dry. A parameter set based on the baseline period (1961–1990) is also investigated for comparison. For uncertainty analysis, a k-simulation set approach is proposed instead of employing the traditional optimization method which uses a single best-fit parameter set. The results show that the parameter set from the wet sub-period performs the best when transferred into wet climate condition, while the parameter set from the baseline period is the most appropriate when transferred into dry climate condition. The largest uncertainty of simulated daily high flows for 2011–2040 is from the parameter set trained in the dry sub-period, while that of simulated daily medium and low flows lies in the parameter set from the intermediate calibration sub-period. For annual changes in the future period, the uncertainty with the parameter set from the intermediate sub-period is the largest, followed by the wet sub-period and dry sub-period. Compared with high and medium flows/runoffs, the uncertainty of low flows/runoffs is much smaller for both simulated daily flows and annual runoffs. For seasonal runoffs, the largest uncertainty is from the intermediate sub-period, while the smallest is from the dry sub-period. Apart from that, the largest uncertainty can be observed for spring runoffs and the lowest one for autumn runoffs. Compared with the traditional optimization method, the k-simulation set approach shows many more advantages, particularly being able to provide uncertainty information to decision support for watershed management under climate change.
EDITOR Z.W. Kundzewicz ASSOCIATE EDITOR not assigned 相似文献
7.
Amadou Angelina Abdouramane Gado Djibo Ibrah Seidou Sanda Ketvara Sittichok 《水文科学杂志》2013,58(10):1709-1723
AbstractA significant decrease in mean river flow as well as shifts in flood regimes have been reported at several locations along the River Niger. These changes are the combined effect of persistent droughts, damming and increased consumption of water. Moreover, it is believed that climate change will impact on the hydrological regime of the river in the next decades and exacerbate existing problems. While decision makers and stakeholders are aware of these issues, it is hard for them to figure out what actions should be taken without a quantitative estimate of future changes. In this paper, a Soil and Water Assessment Tool (SWAT) model of the Niger River watershed at Koulikoro was successfully calibrated, then forced with the climate time series of variable length generated by nine regional climate models (RCMs) from the AMMA-ENSEMBLES experiment. The RCMs were run under the SRES A1B emissions scenario. A combination of quantile-quantile transformation and nearest-neighbour search was used to correct biases in the distributions of RCM outputs. Streamflow time series were generated for the 2026–2050 period (all nine RCMs), and for the 2051–2075 and 2076–2100 periods (three out of nine RCMs) based on the availability of RCM simulations. It was found that the quantile-quantile transformation improved the simulation of both precipitation extremes and ratio of monthly dry days/wet days. All RCMs predicted an increase in temperature and solar radiation, and a decrease in average annual relative humidity in all three future periods relative to the 1981–1989 period, but there was no consensus among them about the direction of change of annual average wind speed, precipitation and streamflow. When all model projections were averaged, mean annual precipitation was projected to decrease, while the total precipitation in the flood season (August, September, October) increased, driving the mean annual flow up by 6.9% (2026–2050), 0.9% (2051–2075) and 5.6% (2076–2100). A t-test showed that changes in multi-model annual mean flow and annual maximum monthly flow between all four periods were not statistically significant at the 95% confidence level. 相似文献
8.
《水文科学杂志》2013,58(5):852-871
Abstract To reflect the uncertainties of a hydrological model in simulating and forecasting observed discharges according to rainfall inputs, the estimated result for each time step should not be just a point estimate (a single numerical value), but should be expressed as a prediction interval, i.e. a band defined by the prediction bounds of a particular confidence level α. How best to assess the quality of the prediction bounds thus becomes very important for understanding the modelling uncertainty in a comprehensive and objective way. This paper focuses on seven indices for characterizing the prediction bounds from different perspectives. For the three case-study catchments presented, these indices are calculated for the prediction bounds generated by the generalized likelihood uncertainty estimation (GLUE) method for various threshold values. In addition, the relationships among these indices are investigated, particularly that of the containing ratio (CR) to the other indices. In this context, three main findings are obtained for the prediction bounds estimated by GLUE. Firstly, both the average band-width and the average relative band-width are seen to have very strong linear correlations with the CR index. Secondly, a high CR value, a narrow band-width, and a high degree of symmetry with respect to the observed hydrograph, all of which are clearly desirable properties of the prediction bounds estimated by the uncertainty assessment methods, cannot all be achieved simultaneously. Thirdly, for the prediction bounds considered, the higher CR values and the higher degrees of symmetry with respect to the observed hydrograph are found to be associated with both the larger band-widths and the larger deviation amplitudes. It is recommended that a set of different indices, such as those considered in this study, be employed for assessing and comparing the prediction bounds in a more comprehensive and objective way. 相似文献
9.
Michael E. McClain Amanda L. Subalusky Elizabeth P. Anderson Shimelis Behailu Dessu Assefa M. Melesse Preksedis M. Ndomba 《水文科学杂志》2014,59(3-4):801-819
AbstractEquatorial rivers of East Africa exhibit unusually complex seasonal and inter-annual flow regimes, and aquatic and adjacent terrestrial organisms have adapted to cope with this flow variability. This study examined the annual flow regime over the past 40 years for three gauging stations on the Mara River in Kenya and Tanzania, which is of international importance because it is the only perennial river traversing the Mara-Serengeti ecoregion. Select environmental flow components were quantified and converted to ecologically relevant hydraulic variables. Vegetation, macroinvertebrates, and fish were collected and identified at target study sites during low and high flows. The results were compared with available knowledge of the life histories and flow sensitivities of the riverine communities to infer flow–ecology relationships. Management implications are discussed, including the need to preserve a dynamic environmental flow regime to protect ecosystems in the region. The results for the Mara may serve as a useful model for river basins of the wider equatorial East Africa region.
Editor Z.W. Kundzewicz; Guest editor M. Acreman 相似文献
10.
To set accurate critical values for the protection of lakes and coastal areas, it is crucial to know the seasonal variation of nutrient exports from rivers. This article presents an improved method for estimating export and in‐stream nutrient retention and its seasonal variation. For 13 lowland river catchments in Western Europe, inputs to surface water and exports were calculated on a monthly basis. The catchments varied in size (21 to 486 km2), while annual in‐stream retention ranged from 23 to 84% for N and 39 to 72% for P. A novel calculation method is presented that quantifies monthly exports from lowland rivers based on an annual load to the river system. Inputs in the calculation are annual emission to the surface waters, average monthly river discharge, average monthly water temperature and fraction of surface water area in the catchment. The method accounts for both seasonal variation of emission to the surface water and seasonal in‐stream retention. The agreement between calculated values and calibration data was high (N: r2 = 0·93; p < 0·001 and P: r2 = 0·81; p < 0·001). Validation of the model also showed good results with model efficiencies for the separate catchments ranging from 31 to 95% (average 76%). This indicates that exports of nitrogen and phosphorus on a monthly basis can be calculated with few input data for a range of West European lowland rivers. Further analysis showed that retention in summer is higher than that in winter, resulting in lower summer nutrient concentrations than that calculated with an average annual input. This implies that accurate evaluation of critical thresholds for eutrophication effects must account for seasonal variation in hydrology and nutrient loading. Our quantification method thus may improve the modelling of eutrophication effects in standing waters. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
11.
If the maximum annual peak flow series are a mixture of summer and winter flows, a seasonal approach to flood frequency analysis is necessary. While considering seasonal maxima as mutually independent events, the annual maxima distribution is defined as the product of seasonal distributions. However, if the independency assumption does not hold, a bivariate approach with dependent margins should be applied, i.e. the copula approach. The impact of dependency on design quantiles is investigated here in the context of the Fréchet-Hoeffding inequality defining copula bounds and the definition of dependency. The results of the two approaches are compared using six catchments in the San River basin, where in four cases the dependency of seasonal maxima has been identified as positive significant and no strong dominance of any one season is observed. The product model leads to higher estimates of design quantiles than do models where the dependency is taken into account and, therefore, is safe.
EDITOR R. Woods ASSOCIATE EDITOR A. Fiori 相似文献
12.
Good modelling practice requires the incorporation of uncertainty analysis into hydrologic/water quality models. The generalized likelihood uncertainty estimation procedure was used to evaluate the uncertainty in DRAINMOD predictions of daily, monthly, and yearly subsurface drain flow. A variance‐based sensitivity analysis technique, the extended Fourier amplitude sensitivity test, was used to identify the main sources of prediction uncertainty. The analysis was conducted for the experimental drainage field at the Southeast Purdue Agricultural Center in Indiana. Six years of data were used and the uncertainties in eight model parameters were considered to analyse how uncertainties in input parameters propagate to model outputs. The width of 90% confidence interval bands of drain flow ranged from 0 to 0·6 cm day?1 for daily predictions, from 0 to 3·1 cm month?1 for the monthly predictions, and from 7·6 to 12·4 cm year?1 for yearly predictions. Annual drain flow predicted by DRAINMOD fell well within the 90% confidence bounds. Model results were most sensitive to the vertical saturated hydraulic conductivity of the restrictive layer and the lateral hydraulic conductivity of the deepest soil layer, followed by the lateral hydraulic conductivity of the top soil layer and surface micro‐storage. Parameter interactions also contributed to the prediction uncertainty. Copyright © 2006 John Wiley & Sons, Ltd. 相似文献
13.
Projecting climate change impacts on stream flow regimes with tracer‐aided runoff models ‐ preliminary assessment of heterogeneity at the mesoscale 
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下载免费PDF全文 The northern mid‐high latitudes form a region that is sensitive to climate change, and many areas already have seen – or are projected to see – marked changes in hydroclimatic drivers on catchment hydrological function. In this paper, we use tracer‐aided conceptual runoff models to investigate such impacts in a mesoscale (749 km2) catchment in northern Scotland. The catchment encompasses both sub‐arctic montane sub‐catchments with high precipitation and significant snow influence and drier, warmer lowland sub‐catchments. We used downscaled HadCM3 General Circulation Model outputs through the UKCP09 stochastic weather generator to project the future climate. This was based on synthetic precipitation and temperature time series generated from three climate change scenarios under low, medium and high greenhouse gas emissions. Within an uncertainty framework, we examined the impact of climate change at the monthly, seasonal and annual scales and projected impacts on flow regimes in upland and lowland sub‐catchments using hydrological models with appropriate process conceptualization for each landscape unit. The results reveal landscape‐specific sensitivity to climate change. In the uplands, higher temperatures result in diminishing snow influence which increases winter flows, with a concomitant decline in spring flows as melt reduces. In the lowlands, increases in air temperatures and re‐distribution of precipitation towards autumn and winter lead to strongly reduced summer flows despite increasing annual precipitation. The integration at the catchment outlet moderates these seasonal extremes expected in the headwaters. This highlights the intimate connection between hydrological dynamics and catchment characteristics which reflect landscape evolution. It also indicates that spatial variability of changes in climatic forcing combined with differential landscape sensitivity in large heterogeneous catchments can lead to higher resilience of the integrated runoff response. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献
14.
《水文科学杂志》2013,58(3):582-595
Abstract This paper explores the potential for seasonal prediction of hydrological variables that are potentially useful for reservoir operation of the Three Gorges Dam, China. The seasonal flow of the primary inflow season and the peak annual flow are investigated at Yichang hydrological station, a proxy for inflows to the Three Gorges Dam. Building on literature and diagnostic results, a prediction model is constructed using sea-surface temperatures and upland snow cover available one season ahead of the prediction period. A hierarchical Bayesian approach is used to estimate uncertainty in the parameters of the prediction model and to propagate these uncertainties to the predictand. The results show skill for both the seasonal flow and the peak annual flow. The peak annual flow model is then used to estimate a design flood (50-year flood or 2% exceedence probability) on a year-to-year basis. The results demonstrate the inter-annual variability in flood risk. The predictability of both the seasonal total inflow and the peak annual flow (or a design flood volume) offers potential for adaptive management of the Three Gorges Dam reservoir through modification of the operating policy in accordance with the year-to-year changes in these variables. 相似文献
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16.
Scaling aspects of river flow routing are studied by comparing two flow routing schemes, one designed for use in coupled general circulation models (GCMs) and operated at large spatial scales (～350 km), and the other designed for use in typical hydrological applications at small spatial scales (～25 km). The same runoff data are used as input into the two routing schemes, and comparisons are made between mean annual, mean monthly and daily streamflow simulated at four locations within the Mackenzie River Basin. The results suggest that for the purpose of realistically modelling monthly streamflow at the mouth of the rivers in GCMs, flow routing at large spatial scales gives similar results. However, the amplitude of the annual streamflow cycle is slightly but characteristically larger, when routing is performed at large spatial scales. Flow routing at large spatial scales also results in overestimation of high flows, while low flows are underestimated. Copyright © 2001 John Wiley & Sons, Ltd. 相似文献
17.
Abstract A major goal in hydrological modelling is to identify and quantify different sources of uncertainty in the modelling process. This paper analyses the structural uncertainty in a streamflow modelling system by investigating a set of models with increasing model structure complexity. The models are applied to two basins: Kielstau in Germany and XitaoXi in China. The results show that the model structure is an important factor affecting model performance. For the Kielstau basin, influences from drainage and wetland are critical for the local runoff generation, while for the XitaoXi basin accurate distributions of precipitation and evapotranspiration are two of the determining factors for the success of the river flow simulations. The derived model uncertainty bounds exhibit appropriate coverage of observations. Both case studies indicate that simulation uncertainty for the low-flow period contributes more to the overall uncertainty than that for the peak-flow period, although the main hydrological features in these two basins differ greatly. Citation Zhang, X. Y., Hörmann, G., Gao, J. F. & Fohrer, N. (2011) Structural uncertainty assessment in a discharge simulation model. Hydrol. Sci. J. 56(5), 854–869. 相似文献
18.
Stewart B. Rood Sobadini Kaluthota Laurens J. Philipsen Neil J. Rood Karen P. Zanewich 《水文研究》2017,31(1):150-160
The Mackenzie River, Canada's longest and largest river system, provides the greatest Western Hemisphere discharge to the Arctic Ocean. Recent reports of declining flows have prompted concern because (1) this influences Arctic Ocean salinity, stratification and polar ice; (2) a major tributary, the Peace River, has large hydroelectric projects, and further dams are proposed; and (3) the system includes the extensive and biodiverse Peace–Athabasca, Slave and Mackenzie deltas. To assess hydrological trends over the past century that could reflect climate change, we analysed historic patterns of river discharges. We expanded the data series by infilling for short gaps, calculating annual discharges from early summer‐only records (typical r2 > 0.9), coordinating data from sequential hydrometric gauges (requiring r2 > 0.8) and advancing the data to 2013. For trend detection, Pearson correlation provided similar outcomes to non‐parametric Kendall's τ and Spearman's ρ tests. There was no overall pattern for annual flows of the most southerly Athabasca River (1913–2013), while the adjacent, regulated Peace River displayed increasing flows (1916–2013, p < 0.05). These rivers combine to form the Slave River, which did not display an overall trend (1917–2013). The more northerly, free‐flowing Liard River is the largest tributary and displayed increasing annual flows (1944–2013, p < 0.01, ~3.5% per decade) because of increasing winter, spring, and summer flows, and annual maximum and minimum flows also increased. Following from the tributary contributions, the Mackenzie River flows gradually increased (Fort Simpson 1939–2013, p < 0.05, ~1.5% per decade), but the interannual patterns for the Liard and other rivers were correlated with the Pacific Decadal Oscillation, complicating the pattern. This conclusion of increasing river flows to the Arctic Ocean contrasts with some prior reports, based on shorter time series. The observed flow increase is consistent with increasing discharges of the large Eurasian Arctic drainages, suggesting a common northern response to climate change. Analyses of historic trends are strengthened with lengthening records, and with the Pacific Decadal Oscillation influence, we recommend century‐long records for northern rivers. Copyright © 2016 John Wiley & Sons, Ltd. 相似文献
19.
Assessment of the effectiveness of a multi-site stochastic weather generator on hydrological modelling in the Red Deer River watershed,Canada 总被引：1，自引：0，他引：1
ABSTRACTTo 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
20.
Abstract A river flow regime describes an average seasonal behaviour of flow and reflects the climatic and physiographic conditions in a basin. Differences in the regularity (stability) of the seasonal patterns reflect different dimensionality of the flow regimes, which can change subject to changes in climate conditions. The empirical orthogonal functions (EOF) approach can be used to describe the intrinsic dimension of river flow regimes and is also an adopted method for reducing the phase space in connection to climate change studies, especially in studies of nonlinear dynamic systems with preferred states. A large data set of monthly river flow for the Nordic countries has been investigated in the phase space reduced to the first few amplitude functions to trace a possible signature of climate change on the seasonal flow patterns. The probability density functions (PDF) of the weight coefficients and their possible change over time were used as an indicator of climate change. Two preferred states were identified connected to stable snowmelt-fed and rainfed flow regimes. The results indicate changes in the PDF patterns with time towards higher frequencies of rainfed regime types. The dynamics of seasonal patterns studied in terms of PDF renders it an adequate and convenient characterization, helping to avoid bias connected to flow regime classifications as well as uncertainties inferred by a modelling approach. 相似文献