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1.
Obtaining representative meteorological data for watershed‐scale hydrological modelling can be difficult and time consuming. Land‐based weather stations do not always adequately represent the weather occurring over a watershed, because they can be far from the watershed of interest and can have gaps in their data series, or recent data are not available. This study presents a method for using the Climate Forecast System Reanalysis (CFSR) global meteorological dataset to obtain historical weather data and demonstrates the application to modelling five watersheds representing different hydroclimate regimes. CFSR data are available globally for each hour since 1979 at a 38‐km resolution. Results show that utilizing the CFSR precipitation and temperature data to force a watershed model provides stream discharge simulations that are as good as or better than models forced using traditional weather gauging stations, especially when stations are more than 10 km from the watershed. These results further demonstrate that adding CFSR data to the suite of watershed modelling tools provides new opportunities for meeting the challenges of modelling un‐gauged watersheds and advancing real‐time hydrological modelling. Copyright © 2013 John Wiley & Sons, Ltd.  相似文献   

2.
Correctly representing weather is critical to hydrological modelling, but scarce or poor quality observations can often compromise model accuracy. Reanalysis datasets may help to address this basic challenge. The Climate Forecast System Reanalysis (CFSR) dataset provides continuous, globally available records, and CFSR data have produced satisfactory hydrological model performance in some temperate and monsoonal locations. However, the use of CFSR for hydrological modelling in tropical and semi‐tropical basins has not been adequately evaluated. Taking advantage of exceptionally high rainfall station density in the catchments of the Rio Grande de Loiza above San Juan, Puerto Rico, we compared model performance based on CFSR records with that based on publicly available weather stations in the Global Historical Climate Network (GHCN, n = 21) and on a dataset of rainfall records maintained by the United States Geological Survey Caribbean Water Science Center (USGS, n = 24). For an implementation of the Soil and Water Assessment Tool (SWAT) with subbasins defined at 11 streamflow gages, uncalibrated measures of Nash–Sutcliffe efficiency (NSE) were >0 at 8 of 11 gages using USGS precipitation data for daily simulations over the period 1998–2012, but were <0 using GHCN weather station records (8 of 11) and CFSR reanalysis data (9 of 11). Autocalibration of individual SWAT models for each of the 11 basins against each of the available weather datasets yielded NSE values > 0 using all precipitation inputs, including CFSR. However, the ground weather station closest to the geographic basin centre produced the highest NSE values in only 5 of 11 cases. The spatially interpolated CFSR data performed as well or better than single ground observations made further than 20–30 km, and sometimes better than individual weather stations <10 km from the basin centroid. In addition to demonstrating the need to evaluate available weather inputs, this research reinforces the value of CFSR data as a means to supplement ground records and consistently determine a baseline for hydrologic model performance. Copyright © 2016 John Wiley & Sons, Ltd.  相似文献   

3.
In a previous study a spatially distributed hydrological model, based on the MIKE SHE code, was constructed and validated for the 375 000 km2 Senegal River basin in West Africa. The model was constructed using spatial data on topography, soil types and vegetation characteristics together with time‐series of precipitation from 112 stations in the basin. The model was calibrated and validated based on river discharge data from nine stations in the basin for 11 years. Calibration and validation results suggested that the spatial resolution of the input data in parts of the area was not sufficient for a satisfactory evaluation of the modelling performance. The study further examined the spatial patterns in the model input and output, and it was found that particularly the spatial resolution of the precipitation input had a major impact on the model response. In an attempt to improve the model performance, this study examines a remotely sensed dryness index for its relationship to simulated soil moisture and evaporation for six days in the wet season 1990. The index is derived from observations of surface temperature and vegetation index as measured by the NOAA Advanced Very High Resolution Radiometer (AVHRR) sensor. The correlation results between the index and the simulation results are of mixed quality. A sensitivity analysis, conducted on both estimates, reveals significant uncertainties in both. The study suggests that the remotely sensed dryness index with its current use of NOAA AVHRR data does not offer information that leads to a better calibration or validation of the simulation model in a spatial sense. The method potentially may become more suitable with the use of the upcoming high‐resolution temporal Meteosat Second Generation data. Copyright © 2002 John Wiley & Sons, Ltd.  相似文献   

4.
Temporal streamflow variability in an inland hydrologic station and temporal trends and frequency changes at three weather stations in a semiarid river basin located in Loess Plateau, China, were detected by using linear regression, Mann–Kendall analysis, and wavelet transform methods. Double cumulative curve and ordered clustering were used to identify the hydrological periods of upper Sang‐kan (USK) basin between 1957 and 2012. The results indicate that (1) precipitation in the USK basin over the study period did not show any trend, while the temperature showed a significant increase; (2) streamflow flowing out of the USK basin indicated a significant decrease; (3) two distinct hydrological periods – the ‘natural period’ from 1957 to 1984 and the ‘human impact period’ from 1985 to 2012 – were present; and (4) the contributions of climate change and human activities to reduce the streamflow were 36.9% and 63.1% respectively. The results indicate that human activities may be contributing to a decrease in streamflow in the USK basin. Copyright © 2016 John Wiley & Sons, Ltd.  相似文献   

5.
The ecological situation of the Tarim River basin in China seriously declined since the early 1950s, mainly due to a strong increase in water abstraction for irrigation purposes. To restore the ecological system and support sustainable development of the Tarim River basin region in China, more hydrological studies are demanded to properly understand the processes of the watershed and efficiently manage the water resources. Such studies are, however, complicated due to the limited data availability, especially in the mountainous headwater regions of the Tarim River basin. This study investigated the usefulness of remote sensing (RS) data to overcome that lack of data in the spatially distributed hydrological modelling of the basin. Complementary to the conventional station‐based (SB) data, the RS products that are directly used in this study include precipitation, evapotranspiration and leaf area index. They are derived from raw image data of the Chinese Fengyun meteorological satellite and from the Moderate Resolution Imaging Spectroradiometer (MODIS). The MODIS land surface temperature was used to calculate the atmospheric temperature lapse rate to describe the temperature dependency on topographical variations. Moreover, MODIS‐based snow cover images were used to obtain model initial conditions and as validation reference for the snow model component. Comparison of model results based on RS input versus conventional SB input exhibited similar results in terms of high and low river runoff extremes, cumulative runoff volumes in both runoff and snow melting seasons and spatial and temporal variability of snow cover. During summer time, when the snow cover shrinks in the permanent glacier region, it was found that the model resolution influences the model results dramatically, hence, showing the importance of detailed (RS based) spatially distributed input data. Copyright © 2011 John Wiley & Sons, Ltd.  相似文献   

6.
Precipitation and temperature time series suffer from many problems, such as short time, inadequate spatial coverage, missing data, and biases from various causes, which are particularly critical in remote areas such as Northern Canada. The development of alternative datasets for using as proxies for inadequate/missing weather data represents a key research area. In this paper, the performance of 6 alternative datasets is evaluated for hydrological modelling over 12 watersheds located across Canada and the contiguous United States. The datasets can be classified into 3 distinct categories: (a) interpolated gridded data, (b) reanalysis data, and (c) climate model outputs. Hydrological simulations were carried out using a lumped conceptual hydrological model calibrated using standard weather data and compared against results using a calibration specific to each alternative dataset. Prior to the hydrological simulations, the alternative datasets were all evaluated with respect to their ability to reproduce gridded daily precipitation and temperature characteristics over North America. The results show that both the reanalysis data and climate model data adequately represent the spatial pattern of daily precipitation and temperature over North America. The North American Regional Reanalysis (NARR) dataset consistently shows the best performance. With respect to hydrological modelling, the observed discharges are accurately represented by both the gridded and NARR datasets, and more so for the NARR data. The National Centers for Environmental Prediction dataset consistently performs worst as it is unable to even capture the seasonal pattern of observed streamflow for 3 out of the 12 watersheds. These results indicate that the NARR dataset could be used as a proxy for gauged precipitation and temperature for hydrological modelling over watersheds where observational datasets are deficient. The results also illustrate the ability of climate model data to be used for performing hydrological modelling when driven by reanalysis data at their boundaries, and especially so for high‐resolution models.  相似文献   

7.
Stochastic weather generators are widely used in hydrological, environmental, and agricultural applications to simulate weather time series. However, such stochastic models produce random outputs hence the question on how representative the generated data are if obtained from only one simulation run (realization) as is common practice. In this study, the impact of different numbers of realizations (1, 25, 50, and 100) on the suitability of generated weather data was investigated. Specifically, 50 years of daily precipitation, and maximum and minimum temperatures were generated for three weather stations in the Western Lake Erie Basin (WLEB), using three widely used weather generators, CLIGEN, LARSWG and WeaGETS. Generated results were compared with 50 years of observed data. For all three generators, the analyses showed that one realization of data for 50 years of daily precipitation, and maximum and minimum temperatures may not be representative enough to capture essential statistical characteristics of the climate. Results from the three generators captured the essential statistical characteristics of the climate when the number of realizations was increased from 1 to 25, 50 or 100. Performance did not improve substantially when realizations were increased above 25. Results suggest the need for more than a single realization when generating weather data and subsequently utilizing in other models, to obtain suitable representations of climate.  相似文献   

8.
A physically based model of runoff formation with daily resolution has been developed for the upper part of the Ussuri basin with an area of 24400 km2 based on ECOMAG hydrological modeling platform. Two versions of the hydrological model have been studied: (1) a crude version with the spatial schematization of the drainage area and river network based on DEM 1 × 1 km with the use of soil and landscape maps at a scale of 1: 2500000 and (2) a detailed version with DEM 80 × 80 m and soil and landscape maps of the scale of 1: 100000. Each version of the model has been tested for two variants of meteorological inputs: (1) meteorological forcing data (temperature, air humidity, precipitation) at eight weather stations and (2) with the involvement of additional data on precipitation collected at 15 gages in the basin. The model has been calibrated and validated over a 34-year period (1979–2012) with the use of runoff data for the Ussuri R. and its tributaries. The results of numerical experiments for assessing the sensitivity of model hydrological response to the spatial resolution of land surface characteristics and the density of precipitation gaging stations are discussed.  相似文献   

9.
1961-2003年间鄱阳湖流域气候变化趋势及突变分析   总被引：21，自引：2，他引：19  
本文利用1961-2003年间鄱阳湖流域14个气象站的气温、降水量、蒸发量等观测数据和8个主要水文站的流量数据,研究该时段内鄱阳湖流域的气候变化趋势、突变及其空间分布的差异．研究表明,鄱阳潮流域气温和降水均在1990年发生突变,继而呈现显著的上升趋势;在季节变化上,冬季平均气温在1986年发生突变,增温显著;夏季降水量和夏季暴雨频率均在1992年发生突变增加,暴雨频率增加是夏季降水量增加的主要原因;蒸发皿蒸发量和参照蒸散量均呈现显著下降趋势,该变化在夏季尤为明显．上述变化趋势均以1990s最为显著,这与长江流域气候变化趋势基本一致．在空间分布上,饶河水系、信江水系和赣江下游等气候变化更为显著．笔者认为,鄱阳湖流域气候变化在长江流域中比较突出．该流域1990s暖湿气候在加强;气温的升高、降水量和暴雨频率的增加以及蒸发量的下降强化了五河流量的增加趋势,由此可大致判定鄱阳湖流域气候变化与洪涝灾害之间可能存在的关系,这可为理解气候变化在该流域的响应和预测该流域未来可能的洪涝灾害提供依据．  相似文献   

10.
Snowmelt is an important source of runoff in high mountain catchments. Snowmelt modelling for alpine regions remains challenging with scarce gauges. This study simulates the snowmelt in the Karuxung River catchment in the south Tibetan Plateau using an altitude zone based temperature‐index model, calibrates the snow cover area and runoff simulation during 2003–2005 and validates the model performance via snow cover area and runoff simulation in 2006. In the snowmelt and runoff modelling, temperature and precipitation are the two most important inputs. Relevant parameters, such as critical snow fall temperature, temperature lapse rate and precipitation gradient, determine the form and amount of precipitation and distribution of temperature and precipitation in hydrological modelling of the sparsely gauged catchment. Sensitivity analyses show that accurate estimation of these parameters would greatly help in improving the snowmelt simulation accuracy, better describing the snow‐hydrological behaviours and dealing with the data scarcity at higher elevations. Specifically, correlation between the critical snow fall temperature and relative humidity and seasonal patterns of both the temperature lapse rate and the precipitation gradient should be considered in the modelling studies when precipitation form is not logged and meteorological observations are only available at low elevation. More accurate simulation of runoff involving snowmelt, glacier melt and rainfall runoff will improve our understanding of hydrological processes and help assess runoff impacts from a changing climate in high mountain catchments. Copyright © 2013 John Wiley & Sons, Ltd.  相似文献   

11.
Hydrological processes change from the impacts of climate variability and human activities. Runoff in the upper reaches of the Hun‐Taizi River basin, which is mainly covered by forests in northeast China, decreased from 1960 to 2006. The data used in this study were based on runoff records from six hydrological stations in the upper reaches of the Hun‐Taizi River basin. Nonparametric Mann–Kendall statistic was used to identify change trends and abrupt change points and consequently analyze the change characteristics in hydrological processes. The abrupt change in the annual runoff in most subcatchments appeared after 1975. Finally, the effects of climate change and land cover change on water resources were identified using regression analysis and a hydrology model. Results of the regression analysis suggest that the correlation coefficients between precipitation and runoff prior to the abrupt change were higher compared with those after the abrupt change. Moreover, using hydrology model analysis, the water yield was found to increase because of the decrease in forest land. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   

12.
Over the past few years, many international initiatives and collaborations were launched to improve and share knowledge in hydrology research. Large databases allowed finding patterns and relationships across regions and scales. This paper introduces the Canadian model parameter experiment (CANOPEX) database, which is adapted from the US MOPEX project data and methods. The CANOPEX database includes meteorological and hydrometric data as well as watershed boundaries for 698 basins. Two sets of basin‐averaged meteorological data (Maximum and minimum temperature and precipitation) are provided. The first dataset is directly taken from Environment Canada's weather stations whereas the second is extracted from the Natural Resources Canada gridded climate data product. Data are provided in MOPEX and Matlab formats. CANOPEX watersheds are well distributed over Canada, which allows investigating a variety of physiological and climatological conditions. The CANOPEX database can be used in a variety of hydrologic research projects such as climate change impact studies, model comparisons, multi‐modelling, ensemble streamflow prediction and model parameter estimation. CANOPEX could be used to generalize findings to other cold climate catchments as well as assess the robustness of research methodologies and procedures. Copyright © 2016 John Wiley & Sons, Ltd.  相似文献   

13.
The question of which climate model bias correction methods and spatial scales for correction are optimal for both projecting future hydrological changes as well as removing initial model bias has so far received little attention. For 11 climate models (CMs), or GCM/RCM – Global/Regional Climate Model pairing, this paper analyses the relationship between complexity and robustness of three distribution‐based scaling (DBS) bias correction methods applied to daily precipitation at various spatial scales. Hydrological simulations are forced by CM inputs to assess the spatial uncertainty of groundwater head and stream discharge given the various DBS methods. A unique metric is devised, which allows for comparison of spatial variability in climate model bias and projected change in precipitation. It is found that the spatial variability in climate model bias is larger than in the climate change signals. The magnitude of spatial bias seen in precipitation inputs does not necessarily correspond to the magnitude of biases seen in hydrological outputs. Variables that integrate basin responses over time and space are more sensitive to mean spatial biases and less so on extremes. Hydrological simulations forced by the least parameterized DBS approach show the highest error in mean and maximum groundwater heads; however, the most highly parameterised DBS approach shows less robustness in future periods compared with the reference period it was trained in. For hydrological impacts studies, choice of bias correction method should depend on the spatial scale at which hydrological impacts variables are required and whether CM initial bias is spatially uniform or spatially varying. Copyright © 2015 John Wiley & Sons, Ltd.  相似文献   

14.
2013年第23号“菲特”台风期间太湖流域洪水运动分析   总被引：1，自引：0，他引：1  
林荷娟  甘月云  胡艳  武剑  吴娟 《湖泊科学》2015,27(3):548-552
2013年"菲特"台风影响期间,太湖流域普降暴雨,10月6-8日杭嘉湖区、浙西区和浦东浦西区过程降雨量均位列1951年以来第1位;在强风、暴雨、高潮、洪水"四碰头"的影响下,湖泊河网水位、沿江沿海潮位迅速上涨,多个站点水位(潮位)超历史记录,严重制约流域排洪和区域排涝.通过模型计算、统计分析等方法,计算"菲特"台风造峰期的径流量、调蓄量、外排水量,分析流域洪水运动规律,并与降雨特性较为相似的1999年大水相比较,提出流域防洪的蓄泄关系建议,可为水利工程调度以及今后防洪工程布局设计提供参考依据.  相似文献   

15.
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   

16.
Meteorologic-driven processes exert large and diverse impacts on lakes’ internal heating, cooling, and mixing. Thus, continued global warming and climate change will affect lakes’ thermal properties, dynamics, and ecosystem. The impact of climate change on Lake Tahoe (in the states of California and Nevada in the United States) is investigated here, as a case study of climate change effects on the physical processes occurring within a lake. In the Tahoe basin, air temperature data show upward trends and streamflow trends indicate earlier snowmelt. Precipitation in the basin is shifting from snow to rain, and the frequency of intense rainfall events is increasing. In-lake water temperature records of the past 38 years (1970–2007) show that Lake Tahoe is warming at an average rate of 0.013°C/year. The future trends of weather variables, such as air temperature, precipitation, longwave radiation, downward shortwave radiation, and wind speed are estimated from predictions of three General Circulation Models (GCMs) for the period 2001–2100. Future trends of weather variables of each GCM are found to be different to those of the other GCMs. A series of simulation years into the future (2000–2040) is established using streamflows and associated loadings, and meteorologic data sets for the period 1994–2004. Future simulation years and trends of weather variables are selected so that: (1) future simulated warming trend would be consistent with the observed warming trend (0.013°C/year); and (2) future mixing pattern frequency would closely match with the historical mixing pattern frequency. Results of 40-year simulations show that the lake continues to become warmer and more stable, and mixing is reduced. Continued warming in the Tahoe has important implications for efforts towards managing biodiversity and maintaining clarity of the lake.  相似文献   

17.
Using a nonstationary flood frequency model, this study investigates the impact of trends on the estimation of flood frequencies and flood magnification factors. Analysis of annual peak streamflow data from 28 hydrological stations across the Pearl River basin, China, shows that: (1) northeast parts of the West and the North River basins are dominated by increasing annual peak streamflow, whereas decreasing trends of annual peak streamflow are prevailing in other regions of the Pearl River basin; (2) trends significantly impact the estimation of flood frequencies. The changing frequency of the same flood magnitude is related to the changing magnitude or significance/insignificance of trends, larger increasing frequency can be detected for stations with significant increasing trends of annual peak streamflow and vice versa, and smaller increasing magnitude for stations with not significant increasing annual peak streamflow, pointing to the critical impact of trends on estimation of flood frequencies; (3) larger‐than‐1 flood magnification factors are observed mainly in the northeast parts of the West River basin and in the North River basin, implying magnifying flood processes in these regions and a higher flood risk in comparison with design flood‐control standards; and (4) changes in hydrological extremes result from the integrated influence of human activities and climate change. Generally, magnifying flood regimes in the northeast Pearl River basin and in the North River basin are mainly the result of intensifying precipitation regime; smaller‐than‐1 flood magnification factors along the mainstream of the West River basin and also in the East River basin are the result of hydrological regulations of water reservoirs. Copyright © 2014 John Wiley & Sons, Ltd.  相似文献   

18.
We use two hydrological models of varying complexity to study the Juncal River Basin in the Central Andes of Chile with the aim to understand the degree of conceptualization and the spatial structure that are needed to model present and future streamflows. We use a conceptual semi‐distributed model based on elevation bands [Water Evaluation and Planning (WEAP)], frequently used for water management, and a physically oriented, fully distributed model [Topographic Kinematic Wave Approximation and Integration ETH Zurich (TOPKAPI‐ETH)] developed for research purposes mainly. We evaluate the ability of the two models to reproduce the key hydrological processes in the basin with emphasis on snow accumulation and melt, streamflow and the relationships between internal processes. Both models are capable of reproducing observed runoff and the evolution of Moderate‐resolution Imaging Spectroradiometer snow cover adequately. In spite of WEAP's simple and conceptual approach for modelling snowmelt and its lack of glacier representation and snow gravitational redistribution as well as a proper routing algorithm, this model can reproduce historical data with a similar goodness of fit as the more complex TOPKAPI‐ETH. We show that the performance of both models can be improved by using measured precipitation gradients of higher temporal resolution. In contrast to the good performance of the conceptual model for the present climate, however, we demonstrate that the simplifications in WEAP lead to error compensation, which results in different predictions in simulated melt and runoff for a potentially warmer future climate. TOPKAPI‐ETH, using a more physical representation of processes, depends less on calibration and thus is less subject to a compensation of errors through different model components. Our results show that data obtained locally in ad hoc short‐term field campaigns are needed to complement data extrapolated from long‐term records for simulating changes in the water cycle of high‐elevation catchments but that these data can only be efficiently used by a model applying a spatially distributed physical representation of hydrological processes. Copyright © 2013 John Wiley & Sons, Ltd.  相似文献   

19.
Bias correction methods remove systematic differences in the distributional properties of climate model outputs with respect to observations, often as a means of pre-processing model outputs for use in hydrological impact studies. Traditionally, bias correction is applied at each weather station individually, neglecting the dependence that exists between different sites, which could negatively affect simulations from a distributed hydrological model. In this study, three multi-variate bias correction (MBC) methods—initially proposed to correct the inter-variable correlation or multi-variate dependence of climate model outputs—are used to correct biases in distributional properties and spatial dependence at multiple weather stations. To reveal the benefits of correcting spatial dependence, two distribution-based single-site bias correction methods are used for comparison. The effects of multi-site correction on hydro-meteorological extremes are assessed by driving a distributed hydrological model and then evaluating the model performance in terms of several meteorological and hydrological extreme indices. The results show that the multi-site bias correction methods perform well in reducing biases in spatial correlation measures of raw global climate model outputs. In addition, the multi-site methods consistently reproduce watershed-averaged meteorological variables better than single-site methods, especially for extreme values. In terms of representing hydrological extremes, the multi-site methods generally perform better than the single-site methods, although the benefits vary according to the hydrological index. However, when applying the multi-site methods, the original temporal sequence of precipitation occurrence may be altered to some extent. Overall, all multi-site bias correction methods are able to reproduce the spatial correlation of observed meteorological variables over multiple stations, which leads to better hydrological simulations, especially for extremes. This study emphasizes the necessity of considering spatial dependence when applying bias correction to ccc outputs and hydrological impact studies.  相似文献   

20.
基于鄱阳湖流域五河水文站1960-2013年逐日径流量和14个国家级气象站的日气象数据,本文利用长短记忆模型框架构建神经网络模型来开展鄱阳湖流域的径流过程模拟,结合生态赤字与生态盈余等生态径流指标,定量分析了鄱阳湖流域的水文变异特征.同时,利用差异化的情景模拟方式,定量区分了人类活动和气候变化对鄱阳湖流域生态径流变化的...  相似文献   

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