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1.
An ensemble of stochastic daily rainfall projections has been generated for 30 stations across south‐eastern Australia using the downscaling nonhomogeneous hidden Markov model, which was driven by atmospheric predictors from four climate models for three IPCC emissions scenarios (A1B, A2, and B1) and for two periods (2046–2065 and 2081–2100). The results indicate that the annual rainfall is projected to decrease for both periods for all scenarios and climate models, with the exception of a few scenarios of no statistically significant changes. However, there is a seasonal difference: two downscaled GCMs consistently project a decline of summer rainfall, and two an increase. In contrast, all four downscaled GCMs show a decrease of winter rainfall. Because winter rainfall accounts for two‐thirds of the annual rainfall and produces the majority of streamflow for this region, this decrease in winter rainfall would cause additional water availability concerns in the southern Murray–Darling basin, given that water shortage is already a critical problem in the region. In addition, the annual maximum daily rainfall is projected to intensify in the future, particularly by the end of the 21st century; the maximum length of consecutive dry days is projected to increase, and correspondingly, the maximum length of consecutive wet days is projected to decrease. These changes in daily sequencing, combined with fewer events of reduced amount, could lead to drier catchment soil profiles and further reduce runoff potential and, hence, also have streamflow and water availability implications. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献
2.
It is well recognized that the time series of hydrologic variables, such as rainfall and streamflow are significantly influenced by various large‐scale atmospheric circulation patterns. The influence of El Niño‐southern oscillation (ENSO) on hydrologic variables, through hydroclimatic teleconnection, is recognized throughout the world. Indian summer monsoon rainfall (ISMR) has been proved to be significantly influenced by ENSO. Recently, it was established that the relationship between ISMR and ENSO is modulated by the influence of atmospheric circulation patterns over the Indian Ocean region. The influences of Indian Ocean dipole (IOD) mode and equatorial Indian Ocean oscillation (EQUINOO) on ISMR have been established in recent research. Thus, for the Indian subcontinent, hydrologic time series are significantly influenced by ENSO along with EQUINOO. Though the influence of these large‐scale atmospheric circulations on large‐scale rainfall patterns was investigated, their influence on basin‐scale stream‐flow is yet to be investigated. In this paper, information of ENSO from the tropical Pacific Ocean and EQUINOO from the tropical Indian Ocean is used in terms of their corresponding indices for stream‐flow forecasting of the Mahanadi River in the state of Orissa, India. To model the complex non‐linear relationship between basin‐scale stream‐flow and such large‐scale atmospheric circulation information, artificial neural network (ANN) methodology has been opted for the present study. Efficient optimization of ANN architecture is obtained by using an evolutionary optimizer based on a genetic algorithm. This study proves that use of such large‐scale atmospheric circulation information potentially improves the performance of monthly basin‐scale stream‐flow prediction which, in turn, helps in better management of water resources. Copyright © 2007 John Wiley & Sons, Ltd. 相似文献
3.
An extensive dataset (230 precipitation gauges and 79 stream gauges) was used to analyse rainfall–runoff relationships in 10 subregions of a 482000 km2 area in the south‐eastern USA (Maryland, Virginia, North Carolina, South Carolina and Georgia). The average annual rainfall and runoff for this study area between 1938 and 2005 were 1201 and 439 mm, respectively. Average runoff/rainfall ratios during this period varied between 0·24 in the southernmost Coastal Plain subregion to 0·64 in the Blue Ridge Province. Watershed elevation and relief are the principal determinants governing the conversion of rainfall to runoff. Temporal rainfall variation throughout the south‐eastern USA ranges from ～40% above and below normal while the variation for runoff is higher, from ? 75% to + 100%. In any given year there can exist a ± 25–50% error in predicted runoff deviation using the annual rainfall–runoff regression. Fast Fourier Transform and autoregressive spectral analysis revealed dominant cyclicities for rainfall and runoff between 14 and 17 years. Secondary periodicities were typically between 6–7 and 10–12 years. The inferred cyclicity may be related to ENSO and/or Central North Pacific atmospheric phenomena. Mann–Kendall analyses indicate that there were no consistent statistically significant temporal trends with respect to south‐eastern US rainfall and runoff during the study period. The results of U‐tests similarly indicated that rainfall between 1996 and 2005 was not statistically higher or lower than during earlier in the study period. Copyright © 2008 John Wiley & Sons, Ltd. 相似文献
4.
At present, Bangladesh has a flood forecasting lead time of only 3 days or so. There is demand for a forecasting lead time of a month to a season. The primary objectives of this paper are to study the variability and predictability of seasonal flooding in Bangladesh, as revealed by large‐scale predictors of the climate across the watersheds. To explore the source of predictability, accessible Bangladesh hydrological indicators are related to large‐scale oceanic variability and to large‐scale atmospheric circulation patterns predicted by general circulation models (GCMs). Correlation analyses between the flood‐affected area (FAA) for July–September and tropical sea‐surface temperature (SST) indicate connections to tropical Pacific and Indian Ocean SSTs, at a short lead time of a month or so. These are related to El Niño–southern oscillation (ENSO). Correlations between the SSTs of the preceding October–December and the July–September FAA are weaker but notable. Forecasts of the FAA using the leading principal components (PCs) of SST were made, which provided good skill with a lead time of a month or so. The streamflows and rainfall observed in Bangladesh have been added to these prediction models. Finally, the SST PCs were replaced with PCs of GCM prediction fields (precipitation). The prediction models at short lead time that were constructed for FAA were of generally similar levels of skill to that for SST. This is encouraging, as it suggests that linkages with SST can be successfully recovered in a physical model of the climate system in Bangladesh. This study concludes that seasonal flood prediction in Bangladesh is possible from the unusually warm or cold SST in parts of the tropics. This predictability can be enhanced with the information achievable from monitoring the downstream streamflows (which are generated mainly from upstream rainfall conditions) in advance of the flooding season. Finally, this study recommends formalizing a regional cooperation among the countries in the principal co‐basin areas of the Ganges–Brahmaputra–Meghna to achieve this goal. Copyright © 2006 John Wiley & Sons, Ltd. 相似文献
5.
Under a climate change, the physical factors that influence the rainfall regime are diverse and difficult to predict. The selection of skilful inputs for rainfall forecasting models is, therefore, more challenging. This paper combines wavelet transform and Frank copula function in a mutual information‐based input variable selection (IVS) for non‐linear rainfall forecasting models. The marginal probability density functions (PDFs) of a set of potential rainfall predictors and the rainfall series (predictand) were computed using a wavelet density estimator. The Frank copula function was applied to compute the joint PDF of the predictors and the predictand from their marginal PDFs. The relationship between the rainfall series and the potential predictors was assessed based on the mutual information computed from their marginal and joint PDFs. Finally, the minimum redundancy maximum relevance was used as an IVS stopping criterion to determine the number of skilful input variables. The proposed approach was applied to four stations of the Nigerien Sahel with rainfall series spanning the period 1950–2016 by considering 24 climate indices as potential predictors. Adaptive neuro‐fuzzy inference system, artificial neural networks, and random forest‐based forecast models were used to assess the skill of the proposed IVS method. The three forecasting models yielded satisfactory results, exhibiting a coefficient of determination between 0.52 and 0.69 and a mean absolute percentage error varying from 13.6% to 21%. The adaptive neuro‐fuzzy inference system performed better than the other models at all the stations. A comparison made with KDE‐based mutual information showed the advantage of the proposed wavelet–copula approach. 相似文献
6.
A number of previous studies have identified changes in the climate occurring on decadal to multi‐decadal time‐scales. Recent studies also have revealed multi‐decadal variability in the modulation of the magnitude of El Niño–Southern Oscillation (ENSO) impacts on rainfall and stream flow in Australia and other areas. This study investigates multi‐decadal variability of drought risk by analysing the performance of a water storage reservoir in New South Wales, Australia, during different climate epochs defined using the Inter‐decadal Pacific Oscillation (IPO) index. The performance of the reservoir is also analysed under three adaptive management techniques and these are compared with the reservoir performance using the current ‘reactive’ management practices. The results indicate that IPO modulation of both the magnitude and frequency of ENSO events has the effect of reducing and elevating drought risk on multi‐decadal time‐scales. The results also confirm that adaptive reservoir management techniques, based on ENSO forecasts, can improve drought security and become significantly more important during dry climate epochs. These results have marked implications for improving drought security for water storage reservoirs. Copyright © 2004 John Wiley & Sons, Ltd. 相似文献
7.
Mountain‐range topography is determined by the complex interplay between tectonics and climate. However, often it is not clear to what extent climate forces topographic evolution and how past climatic episodes are reflected in present‐day relief. The Andes are a tectonically active mountain belt encompassing various climatic zones with pronounced differences in rainfall, erosion, and glacier extent under similar plate‐boundary conditions. In the central to south‐western Andes, climatic zones range from hyperarid desert with mean annual rainfall of 5 mm/a (22·5°S) to year‐round humidity with 2500 mm/a (40°S). The Andes thus provide a unique setting for investigating the relationship between tectonics, climate, and topography. We present an analysis of 120 catchments along the western Andean watersheds between 15·5° and 41·5°S, which is based on SRTMV3‐90m data and new medium‐resolution rainfall, tropical rainfall measurement mission (TRMM) dataset. For each basin, we extracted geometry, relief, and climate parameters to test whether Andean topography shows a climatic imprint and to analyze how climate influences relief. Our data document that elevation and relief decrease with increasing rainfall and descending snowline elevation. Furthermore, we show that local relief reaches high values of 750 m in a zone between 28°S to 35°S. During Pleistocene glacial stages this region was affected by the northward shifting southern hemisphere Westerlies, which provided moisture for valley‐glacier formation and extended glacial coverage as well as glacial erosion. In contrast, the southern regions between 35°S to 40°S receive higher rainfall and have a lower local relief of 200 m, probably related to an increased drainage density. We distinguish two different, climatically‐controlled mechanisms shaping topography: (1) fluvial erosion by prolonged channel‐hillslope coupling, which smoothes relief, and (2) erosion by valley glaciers that generates relief. Finally, Our results suggests that the catchment‐scale relief of the Andes between 28°S to 35°S is characterized by a pronounced transient component reflecting past climatic conditions. Copyright © 2010 John Wiley & Sons, Ltd. 相似文献
8.
Particle‐size evidence of barrier estuary regime as a new proxy for ENSO climate variability 
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下载免费PDF全文 We investigate a new proxy for ENSO climate variability based on particle‐size data from long‐term, coastal sediment records preserved in a barrier estuary setting. Corresponding ~4–8 year periodicities identified from Wavelet analysis of particle‐size data from Pescadero Marsh in Central Coast California and rainfall data from San Francisco reflect established ENSO periodicity, as further evidenced in the Multivariate ENSO Index (MEI), and thus confirms an important ENSO control on both precipitation and barrier regime variability. Despite the fact that barrier estuary mean particle size is influenced by coastal erosion, precipitation and streamflow, balanced against barrier morphology and volume, it is encouraging that considerable correspondence can also be observed in the time series of MEI, regional rainfall and site‐based mean particle size over the period 1871–2008. This correspondence is, however, weakened after c.1970 by temporal variation in sedimentation rate and event‐based deposition. These confounding effects are more likely when: (i) accommodation space may be a limiting factor; and (ii) particularly strong El Niños, e.g. 1982/1983 and 1997/1998, deposit discrete >cm‐thick units during winter storms. The efficacy of the sediment record of climate variability appears not to be compromised by location within the back‐barrier setting, but it is limited to those El Niños that lead to barrier breakdown. For wider application of this particle size index of ENSO variability, it is important to establish a well‐resolved chronology and to sample the record at the appropriate interval to characterize deposition at a sub‐annual scale. Further, the sample site must be selected to limit the influence of decreasing accommodation space through time (infilling) and event‐based deposition. It is concluded that particle‐size data from back‐barrier sediment records have proven potential for preserving evidence of sub‐decadal climate variability, allowing researchers to explore temporal and spatial patterns in phenomena such as ENSO. Copyright © 2017 John Wiley & Sons, Ltd. 相似文献
9.
Global warming can potentially lead to changes in future rainfall and runoff and can significantly impact the regional hydrology and future availability of water resources. All the large‐scale climate impact studies use the future climate projections from global climate models (GCMs) to estimate the impact on future water availability. This paper presents results from a detailed assessment to investigate the capability of 15 GCMs to reproduce the observed historical annual and seasonal mean rainfalls, the observed annual rainfall series and the observed daily rainfall distribution across south‐east Australia. The assessment shows that the GCMs can generally reproduce the spatial patterns of mean seasonal and annual rainfalls. However, there can be considerable differences between the mean rainfalls simulated by the GCMs and the observed rainfall. The results clearly show that none of the GCMs can simulate the actual annual rainfall time series or the trend in the annual rainfall. The GCMs can also generally reproduce the observed daily (ranked) rainfall distribution at the GCM scale. The GCMs are ranked against their abilities to reproduce the observed historical mean annual rainfall and daily rainfall distribution, and, based on the combined score, the better GCMs include MPI‐ECHAM5, MIUB, CCCMA_T47, INMCM, CSIRO‐MK3·0, CNRM, CCCMA_T63 and GFDL 2·0 and those with poorer performances are MRI, IPSL, GISS‐AOM, MIROC‐M, NCAR‐PCM1, IAP and NCAR‐CCSM. However, the reduction in the combined score as we move from the best‐ to the worst‐performing GCMs is gradual, and there is no evident cut‐off point or threshold to remove GCMs from climate impact studies. There is some agreement between the results here and many similar studies comparing the performance of GCMs in Australia, but the results are not always consistent and do significantly disagree with several of the studies. Copyright © 2010 John Wiley & Sons, Ltd. 相似文献
10.
Identification of best predictors for forecasting seasonal rainfall and runoff in Australia 总被引：2，自引：0，他引：2
The first step towards developing a reliable seasonal runoff forecast is identifying the key predictors that drive rainfall and runoff. This paper investigates the lag relationships between rainfall across Australia and runoff across southeast Australia versus 12 atmospheric‐oceanic predictors, and how the relationships change over time. The analysis of rainfall data indicates that the relationship is greatest in spring and summer in northeast Australia and in spring in southeast Australia. The best predictors for spring rainfall in eastern Australia are NINO4 [sea surface temperature (SST) in western Pacific] and thermocline (20 °C isotherm of the Pacific) and those for summer rainfall in northeast Australia are NINO4 and Southern Oscillation Index (SOI) (pressure difference between Tahiti and Darwin). The relationship in northern Australia is greatest in spring and autumn with NINO4 being the best predictor. In western Australia, the relationship is significant in summer, where SST2 (SST over the Indian Ocean) and II (SST over the Indonesian region) is the best predictor in the southwest and northwest, respectively. The analysis of runoff across southeast Australia indicates that the runoff predictability in the southern parts is greatest in winter and spring, with antecedent runoff being the best predictor. The relationship between spring runoff and NINO4, thermocline and SOI is also relatively high and can be used together with antecedent runoff to forecast spring runoff. In the northern parts of southeast Australia, the atmospheric‐oceanic variables are better predictors of runoff than antecedent runoff, and have significant correlation with winter, spring and summer runoff. For longer lead times, the runoff serial correlation is reduced, especially over the northern parts, and the atmospheric‐oceanic variables are likely to be better predictors for forecasting runoff. The correlations between runoff versus the predictors vary with time, and this has implications for the development of forecast relationship that assumes stationarity in the historical data. Copyright © 2010 John Wiley & Sons, Ltd. 相似文献
11.
Rajib Maity 《水文研究》2012,26(21):3182-3194
In this paper, Split Markov Process (SMP) is developed to assess one‐step‐ahead variation of daily rainfall at a rain gauge station. SMP is an advancement of general Markov Process and specially developed for probabilistic assessment of change in daily rainfall magnitude. The approach is based on a first‐order Markov chain to simulate daily rainfall variation at a point through state/sub‐state transitional probability matrix (TPM). The state/sub‐state TPM is based on the historical transitions from a particular state to a particular sub‐state, which is the basic difference between SMP and general Markov Process. The cumulative state/sub‐state TPM is represented in a contour plot at different probability levels. The developed cumulative state/sub‐state TPM is used to assess the possible range of rainfall in next time step, in a probabilistic sense. Application of SMP is investigated for daily rainfall at four rain gauge stations – Khandwa, Jabalpur, Sambalpur, and Puri, located at various parts in India. There are 99 years of record available out of which approximately 80% of data are used for calibration, and 20% of data are used to assess the performance. Thus, 80 years of daily monsoon rainfall is used to develop the state/sub‐state TPM, and 19 years data are used to investigate its performance. Model performance is assessed in terms of hit rate (HR), false alarm rate (FAR), and percentage captured. It is found that percentage captured is maximum for Khandwa (70%) and minimum for Sambalpur (44%) whereas hit rate is maximum for Sambalpur and minimum for Khandwa (73%). FAR is around 30% or below for Jabalpur, Sambalpur, and Puri. FAR is maximum for Khandwa (37%). Overall, the assessed range, particularly the upper limit, provides a quantification possible extreme value in the next time step, which is a very useful information to tackle the extreme events, such as flooding, water logging and so on. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
12.
A temporal artificial neural network‐based model is developed and applied for long‐lead rainfall forecasting. Tapped delay lines and recurrent connections are two different components that are used along with a static multilayer perceptron network to design a time‐delay recurrent neural network. The proposed model is, in fact, a combination of time‐delay and recurrent neural networks. The model is applied in three case studies of the Northwest, West, and Southwest basins of Iran. In addition, an autoregressive moving average with exogenous inputs (ARMAX) model is used as a baseline in order to be compared with the time‐delay recurrent neural networks developed in this study. Large‐scale climate signals, such as sea‐level pressure, that affect the rainfall of the study area are used as the predictors in the models, as well as the persistence between rainfall data. The results of winter‐spring rainfall forecasts are discussed thoroughly. It is demonstrated that in all cases the proposed neural network results in better forecasts in comparison with the statistical ARMAX model. Moreover, it is found that in two of three case studies the time‐delay recurrent neural networks perform better than either recurrent or time‐delay neural networks. The results demonstrate that the proposed method can significantly improve the long‐lead forecast by utilizing a non‐linear relationship between climatic predictors and rainfall in a region. Copyright © 2007 John Wiley & Sons, Ltd. 相似文献
13.
Numerous studies have examined the event‐specific hydrologic response of hillslopes and catchments to rainfall. Knowledge gaps, however, remain regarding the relative influence of different meteorological factors on hydrologic response, the predictability of hydrologic response from site characteristics, or even the best metrics to use to effectively capture the temporal variability of hydrologic response. This study aimed to address those knowledge gaps by focusing on 21 sites with contrasting climate, topography, geology, soil properties, and land cover. High‐frequency rainfall and discharge records were analysed, resulting in the delineation of over 1,600 rainfall–runoff events, which were described using a suite of hydrologic response metrics and meteorological factors. Univariate and multivariate statistical techniques were then applied to synthesize the information conveyed by the computed metrics and factors, notably measures of central tendency and variability, variation partitioning, partial correlations, and principal component analysis. Results showed that some response magnitude metrics generally reported in the literature (e.g., runoff ratio and area‐normalized peak discharge) did not vary significantly among sites. The temporal variability in site‐specific hydrologic response was often attributable to the joint influence of storage‐driven (e.g., total event rainfall and antecedent precipitation) and intensity‐driven (e.g., rainfall intensity and antecedent potential evapotranspiration) meteorological factors. Mean annual temperature and potential evapotranspiration at a given site appeared to be good predictors of hydrologic response timing (e.g., response lag and lag to peak). Response timing metrics, particularly those associated with response initiation, were also identified as the metrics most critical for capturing intrasite response variability. This study therefore contributes to the growing knowledge on event‐specific hydrologic response by highlighting the importance of response timing metrics and intensity‐driven meteorological factors, which are infrequently discussed in the literature. As few correlations were found between physiographic variables and response metrics, more data‐driven studies are recommended to further our understanding of landscape–hydrology interactions. 相似文献
14.
Projection of future rainfall for the North China Plain using two statistical downscaling models and its hydrological implications 总被引：1，自引：1，他引：0
Wenbin Liu Guobin Fu Changming Liu Xiaoyan Song Rulin Ouyang 《Stochastic Environmental Research and Risk Assessment (SERRA)》2013,27(8):1783-1797
This study projected the future rainfall (2046–2065 and 2081–2100) for the North China Plain (NCP) using two stochastic statistical downscaling models, the non-homogeneous hidden Markov model and the generalized linear model for daily climate time series, conditioned by the large-scale atmospheric predictors from six general circulation models for three emission scenarios (A1B, A2 and B1). The results indicated that the annual total rainfall, the extreme daily rainfall and the maximum length of consecutive wet/dry days would decline, while the number of annual rainfall days would slightly increase (correspondingly rainfall intensity would decrease) in the NCP, in comparison with the base period (1961–2010). Moreover, the summer monsoon rainfall, which accounted for 50–75 % of the total annual rainfalls in NCP, was projected to decrease in the latter half of twenty-first century. The spatial patterns of change showed generally north–south gradients with relatively larger magnitude decrease in the northern NCP and less decrease (or even slightly increase) in the southern NCP. This could result in decline of the annual runoff by ?5.5 % (A1B), ?3.3 % (A2) and ?4.1 % (B1) for 2046–2065 and ?5.3 % (A1B), ?4.6 % (A2) and ?1.9 % (B1) decrease for 2081–2100. These rainfall changes, combined with the warming temperature, could lead to drier catchment soil profiles and further reduce runoff potential, would hence provide valuable references for the water availability and related climate change adaption in the NCP. 相似文献
15.
Hydrological drought in the west of Iran and possible association with large‐scale atmospheric circulation patterns 下载免费PDF全文
下载免费PDF全文 Drought is a slow‐onset, creeping natural hazard which is an inevitable part of normal climate fluctuation especially in arid and semiarid regions, and its variability can be explained in terms of large‐scale atmospheric circulation patterns. Standardized streamflow index (SSFI) was utilized to characterize hydrological drought in the west of Iran for the hydrological years of 1969–1970 to 2008–2009. The linkage of atmospheric circulation patterns (ENSO, NAO) to hydrological drought was also used to reveal relations of climate variability affecting hydrological drought. River discharges exhibited negative anomalies during the warm phase of ENSO (El Niño) which caused the extreme and severe droughts in the study area, being strongest during the hydrological years of 2007–2008 and 2008–2009. The analysis also indicated the teleconnection impact of ENSO on the hydrological drought severity in the first half of the hydrological year especially between November and March. Moreover, the concurrent and lag correlations revealed a weak relationship between the SSFI drought severity and the NAO index. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献
16.
Land‐cover/climate changes and their impacts on hydrological processes are of widespread concern and a great challenge to researchers and policy makers. Kejie Watershed in the Salween River Basin in Yunnan, south‐west China, has been reforested extensively during the past two decades. In terms of climate change, there has been a marked increase in temperature. The impact of these changes on hydrological processes required investigation: hence, this paper assesses aspects of changes in land cover and climate. The response of hydrological processes to land‐cover/climate changes was examined using the Soil and Water Assessment Tool (SWAT) and impacts of single factor, land‐use/climate change on hydrological processes were differentiated. Land‐cover maps revealed extensive reforestation at the expense of grassland, cropland, and barren land. A significant monotonic trend and noticeable changes had occurred in annual temperature over the long term. Long‐term changes in annual rainfall and streamflow were weak; and changes in monthly rainfall (May, June, July, and September) were apparent. Hydrological simulations showed that the impact of climate change on surface water, baseflow, and streamflow was offset by the impact of land‐cover change. Seasonal variation in streamflow was influenced by seasonal variation in rainfall. The earlier onset of monsoon and the variability of rainfall resulted in extreme monthly streamflow. Land‐cover change played a dominant role in mean annual values; seasonal variation in surface water and streamflow was influenced mainly by seasonal variation in rainfall; and land‐cover change played a regulating role in this. Surface water is more sensitive to land‐cover change and climate change: an increase in surface water in September and May due to increased rainfall was offset by a decrease in surface water due to land‐cover change. A decrease in baseflow caused by changes in rainfall and temperature was offset by an increase in baseflow due to land‐cover change. Copyright © 2009 John Wiley & Sons, Ltd. 相似文献
17.
Testing a spatially distributed tracer‐aided runoff model in a snow‐influenced catchment: Effects of multicriteria calibration on streamwater ages 下载免费PDF全文
下载免费PDF全文 Thea I. Piovano Doerthe Tetzlaff Pertti Ala‐aho Jim Buttle Carl P. J. Mitchell Chris Soulsby 《水文研究》2018,32(20):3089-3107
Integrating stable isotope tracers into rainfall‐runoff models allows investigation of water partitioning and direct estimation of travel times and water ages. Tracer data have valuable information content that can be used to constrain models and, in integration with hydrometric observations, test the conceptualization of catchment processes in model structure and parameterization. There is great potential in using tracer‐aided modelling in snow‐influenced catchments to improve understanding of these catchments' dynamics and sensitivity to environmental change. We used the spatially distributed tracer‐aided rainfall‐runoff (STARR) model to simulate the interactions between water storage, flux, and isotope dynamics in a snow‐influenced, long‐term monitored catchment in Ontario, Canada. Multiple realizations of the model were achieved using a combination of single and multiple objectives as calibration targets. Although good simulations of hydrometric targets such as discharge and snow water equivalent could be achieved by local calibration alone, adequate capture of the stream isotope dynamics was predicated on the inclusion of isotope data in the calibration. Parameter sensitivity was highest, and most local, for single calibration targets. With multiple calibration targets, key sensitive parameters were still identifiable in snow and runoff generation routines. Water ages derived from flux tracking subroutines in the model indicated a catchment where runoff is dominated by younger waters, particularly during spring snowmelt. However, resulting water ages were most sensitive to the partitioning of runoff sources from soil and groundwater sources, which was most realistically achieved when isotopes were included in the calibration. Given the paucity of studies where hydrological models explicitly incorporate tracers in snow‐influenced regions, this study using STARR is an important contribution to satisfactorily simulating snowpack dynamics and runoff generation processes, while simultaneously capturing stable isotope variability in snow‐influenced catchments. 相似文献
18.
Khouloud Gader Ahlem Gara Marnik Vanclooster Slaheddine Khlifi Mohamed Slimani 《水文科学杂志》2020,65(8):1300-1315
ABSTRACT Predicting the impacts of climate change on water resources remains a challenging task and requires a good understanding of the dynamics of the forcing terms in the past. In this study, the variability of precipitation and drought patterns is studied over the Mediterranean catchment of the Medjerda in Tunisia based on an observed rainfall dataset collected at 41 raingauges during the period 1973–2012. The standardized precipitation index and the aridity index were used to characterize drought variability. Multivariate and geostatistical techniques were further employed to identify the spatial variability of annual rainfall. The results show that the Medjerda is marked by a significant spatio-temporal variability of drought, with varying extreme wet and dry events. Four regions with distinct rainfall regimes are identified by utilizing the K-means cluster analysis. A principal component analysis identifies the variables that are responsible for the relationships between precipitation and drought variability. 相似文献
19.
There has been little work to date into the controls on slope‐to‐channel fine sediment connectivity in alpine environments largely ice‐free for most of the Holocene. Characterization of these controls can be expected to result in better understanding of how landscapes “relax” from such perturbations as climate shock. We monitored fine sediment mobilization on a slope segment hydrologically connected to a stream in the largely ice‐free 8·3 km2 Hoophorn Valley, New Zealand. Gerlach traps were installed in ephemeral slope channels to trap surficial material mobilized during rainfall events. Channel sediment flux was measured using turbidimeters above and below the connected slope, and hysteresis patterns in discharge‐suspended sediment concentrations were used to determine sediment sources. Over the 96 day measurement period, sediment mobilization from the slope segment was limited to rainfall events, with increasingly larger particles trapped as event magnitude increased. Less than 1% of the mass of particles collected during these events was fine sediment. During this period, 714 t of suspended sediment was transported through the lower gauging station, 60% of it during rainfall events. Channel sediment transfer patterns during these events were dominated by clockwise hysteresis, interpreted as remobilization of nearby in‐channel sources, further suggesting limited input of fine sediment from slopes in the lower valley. Strong counterclockwise hysteresis, representing input of fine sediment from slope segments, was restricted to the largest storm event (JD2 2009) when surfaces in the upper basin were activated. The results indicate that the slopes of the lower Hoophorn catchment are no longer functioning as sources of fine sediment, but rather as sources of coarse material, with flux rates controlled by the intensity and duration of rainfall events. Although speculative, these findings suggest a shift to a coarse sediment dominated slope‐to‐channel transfer system as the influence of pre‐Holocene glacial erosion declines. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
20.
Richard P. Allan Chunlei Liu Matthias Zahn David A. Lavers Evgenios Koukouvagias Alejandro Bodas-Salcedo 《Surveys in Geophysics》2014,35(3):533-552
Robust and physically understandable responses of the global atmospheric water cycle to a warming climate are presented. By considering interannual responses to changes in surface temperature (T), observations and AMIP5 simulations agree on an increase in column integrated water vapor at the rate 7 %/K (in line with the Clausius–Clapeyron equation) and of precipitation at the rate 2–3 %/K (in line with energetic constraints). Using simple and complex climate models, we demonstrate that radiative forcing by greenhouse gases is currently suppressing global precipitation (P) at ～?0.15 %/decade. Along with natural variability, this can explain why observed trends in global P over the period 1988?2008 are close to zero. Regional responses in the global water cycle are strongly constrained by changes in moisture fluxes. Model simulations show an increased moisture flux into the tropical wet region at 900 hPa and an enhanced outflow (of smaller magnitude) at around 600 hPa with warming. Moisture transport explains an increase in P in the wet tropical regions and small or negative changes in the dry regions of the subtropics in CMIP5 simulations of a warming climate. For AMIP5 simulations and satellite observations, the heaviest 5-day rainfall totals increase in intensity at ～15 %/K over the ocean with reductions at all percentiles over land. The climate change response in CMIP5 simulations shows consistent increases in P over ocean and land for the highest intensities, close to the Clausius?Clapeyron scaling of 7 %/K, while P declines for the lowest percentiles, indicating that interannual variability over land may not be a good proxy for climate change. The local changes in precipitation and its extremes are highly dependent upon small shifts in the large-scale atmospheric circulation and regional feedbacks. 相似文献