Hydrological drought in the west of Iran and possible association with large‐scale atmospheric circulation patterns

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.     

The influences of the Southern and North Atlantic Oscillations on climatic surface variables in Turkey

In this study, Turkish climatic variables (precipitation, stream flow and maximum and minimum temperatures) were first analysed in association with both the Southern Oscillation (SO) and the North Atlantic Oscillation (NAO). The relationships between Turkish maximum and minimum monthly temperatures and the extreme phases of the SO (El Niño and La Niña events) were examined. The results of this analysis showed that relationships between Turkish monthly maximum temperatures and El Niño and La Niña contain some complexity still to be identified, because both events produce a signal indicating a correspondence with cold anomalies in the aggregate composites. A relationship between turkish minimum temperatures and El Niño was detected in western Anatolia, whereas there was no significant and consistent signal associated with La Niña. Moreover a series of cross‐correlation analyses was carried out to demonstrate the teleconnections between the climatic variables and both the NAO and SO. The NAO during winter was found to influence precipitation and stream‐flow patterns. In contrast temperature patterns appeared to be less sensitive to the NAO. Furthermore, lag‐correlation results indicated a prediction potential for both precipitation and stream‐flow variables in connection with the NAO. Simultaneous and time‐lag correlations between the climatic variables and the SO index, in general, indicated weaker relationships in comparison with those for the NAO. These analyses also showed that the influences of the SO on Turkish temperature data are negligible. The outcomes were presented in conjunction with an explanation regarding physical mechanisms behind the implied teleconnections. Copyright © 2004 John Wiley & Sons, Ltd.     

Time scale effect and uncertainty in reconstruction of paleo‐hydrology

Tree‐ring‐based reconstructions of paleo‐hydrology have proved useful for better understanding the irregularities and extent of past climate changes, and therefore, for more effective water resources management. Despite considerable advances in the field, there still exist challenges that introduce significant uncertainties into paleo‐reconstructions. This study outlines these challenges and address them by developing two themes: (1) the effect of temporal scaling on the strength of the relationship between the hydrologic variables, streamflow in this study, and tree growth rates and (2) the reconstruction uncertainty of streamflow due to the dissimilarity or inconsistency in the pool of tree‐ring chronologies (predictors in reconstruction) in a basin. Based on the insight gained, a methodology is developed to move beyond only relying on the annual hydrology‐growth correlations, and to utilize additional information embedded in the annual time series at longer time scales (e.g. multi‐year to decadal time scales). This methodology also generates an ensemble of streamflow reconstructions to formally account for uncertainty in the pool of chronology sites. The major headwater tributaries of the Saskatchewan River Basin, the main source of surface water in the Canadian Prairie Provinces, are used as the case study. It is shown that the developed methodology explains the variance of streamflows to a larger extent than the conventional approach and better preserves the persistence and variability of streamflows across time scales (Hurst‐type behaviour). The resulting ensemble of paleo‐hydrologic time series is able to more credibly pinpoint the timing and extent of past dry and wet periods and provides a dynamic range of uncertainty in reconstruction. This range varies with time over the course of the reconstruction period, indicating that the utility of tree‐ring chronologies for paleo‐reconstruction differs for different time periods over the past several centuries in the history of the region. The proposed ensemble approach provides a credible range of multiple‐century‐long water availability scenarios that can be used for vulnerability assessment of the existing water infrastructure and improving water resources management. Copyright © 2015 John Wiley & Sons, Ltd.     

Simulated water budget of a small forested watershed in the continental/maritime hydroclimatic region of the United States

Annual streamflows have decreased across mountain watersheds in the Pacific Northwest of the United States over the last ~70 years; however, in some watersheds, observed annual flows have increased. Physically based models are useful tools to reveal the combined effects of climate and vegetation on long‐term water balances by explicitly simulating the internal watershed hydrological fluxes that affect discharge. We used the physically based Simultaneous Heat and Water (SHAW) model to simulate the inter‐annual hydrological dynamics of a 4 km² watershed in northern Idaho. The model simulates seasonal and annual water balance components including evaporation, transpiration, storage changes, deep drainage, and trends in streamflow. Independent measurements were used to parameterize the model, including forest transpiration, stomatal feedback to vapour pressure, forest properties (height, leaf area index, and biomass), soil properties, soil moisture, snow depth, and snow water equivalent. No calibrations were applied to fit the simulated streamflow to observations. The model reasonably simulated the annual runoff variations during the evaluation period from water year 2004 to 2009, which verified the ability of SHAW to simulate the water budget in this small watershed. The simulations indicated that inter‐annual variations in streamflow were driven by variations in precipitation and soil water storage. One key parameterization issue was leaf area index, which strongly influenced interception across the catchment. This approach appears promising to help elucidate the mechanisms responsible for hydrological trends and variations resulting from climate and vegetation changes on small watersheds in the region. Copyright © 2015 John Wiley & Sons, Ltd.     

Trends and multi‐annual variability of water temperatures in the river Danube,Serbia

The relationship between air (Ta) and water temperature (Tw) is very important because it shows how the temperature of a water body might respond to future changes in surface Ta. Mean monthly Tw records of three gauging stations (Bezdan, Bogojevo i Veliko Gradi?te) were analysed alongside mean monthly discharge (Q) for the same stations. Additionally, Ta series from two meteorological stations (Sombor and Veliko Gradi?te) were correlated with Tw variations over the period 1950–2012. Locally weighted scatter point smoothing (LOWESS) was used to investigate long‐term trends in the raw data, alongside the Mann–Kendall (MK) trend test. Trend significance was established using Yue–Pilon's pre‐whitening approaches to determine trends in climate data. Also, the rescaled adjusted partial sums (RAPS) method was used to detect dates of possible changes in the time series. Statistically significant warming trends were observed for annual and seasonal minimum and maximum Tw at all investigated sites. The strongest warming was observed at Bogojevo gauging station for seasonal maximum Tw, with +0.05 °C per year on average. RAPS established that the trend began in the 1980s. This behaviour is linked to climate patterns in the North and East Atlantic which determine the amount of heat advected onto mainland Europe. Statistically significant correlations were found for all Tw on an annual basis. Overall, the strongest correlations (p < 0.01) between Tw residuals and the North Atlantic Oscillation (NAO) were recorded for the winter period. These findings suggest possible predictability of Tw over seasonal time‐scales. Copyright © 2016 John Wiley & Sons, Ltd.     

Disaggregation modelling of monthly streamflows using a new approach of the method of fragments

Abstract

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

Editor D. Koutsoyiannis; Associate editor C. Onof

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

The links between the categorised Southern Oscillation indicators and climate and hydrologic variables in Turkey

Some previous global and regional studies have indicated teleconnection between the extreme phases of the Southern Oscillation (SO) and Turkish climate and hydrologic variables; however, they failed to suggest a strong correlation structure. In this study, categorised Southern Oscillation index (SOI) and Multivariate ENSO (El Nino Southern Oscillation) index (MEI) series were used to examine the far‐reaching effects of the SO on temperature, precipitation and streamflow patterns in Turkey. These SO indicators were categorised into five subgroups according to their empirical distributions. Correlations between the categorised SO indicators and three analysis variables were computed using the Spearman's rho from lag‐0 to lag‐4. Significance of calculated correlations was tested at the 0·01 level for station‐based analysis and at the 0·05 level for regional analysis. Temperature records demonstrated significant correlations with the categorised SOI and MEI in nearly half of the entire stations. For some categories, precipitation and streamflow were found to be correlated with the SO indicators in some stations mainly in western Turkey. Regional analyses of temperature and precipitation revealed a clear and strong correlation structure with the categorised SO indicators on a large portion of Turkey. This was not concluded by the earlier pertinent studies. Besides, this study showed that significant correlations were obtained not only for the SO extreme phases (namely, El Nino and La Nina) but also for neutral and moderate phases of the SO. Plausible explanations for the observed teleconnection are presented. Copyright © 2009 John Wiley & Sons, Ltd.     

Stochastic time series modelling of arid zone streamflows / Modèle stochastique des séries des temps élémentaires des valeurs d'écoulement total dans une zone aride

Abstract

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

Impact of climate change on streamflow in the arid Shiyang River Basin of northwest China

Climate change may significantly affect the hydrological cycle and water resource management, especially in arid and semi‐arid regions. In this paper, output from the Providing Regional Climates for Impacts Studies (PRECIS) regional climate model were used in conjunction with the Soil and Water Assessment Tool (SWAT) to analyse the effects of climate change on streamflow of the Xiying and Zamu rivers in the Shiyang River basin, an important arid region in northwest China. After SWAT model calibration and validation, streamflow in the Shiyang River Basin was simulated using the PRECIS climate model data for greenhouse gas emission scenarios A2 (high emission rate) and B2 (low emission rate) developed by Intergovernmental Panel on Climate Change. Monthly streamflow and hydrological extremes were compared for present‐day years (1961–1990), the 2020s (2011–2040), 2050s (2041–2070) and 2080s (2071–2100). The results show that mean monthly streamflow in Shiyang River Basin generally increased in the 2020s, 2050s and 2080s between 0.7–6.1% at the Zamu gauging station and 0.1–4.8% at the Xiying gauging station. The monthly minimum streamflow increased persistently, but the maximum monthly streamflows increased in the 2020s and slightly decreased in the 2050s and 2080s. This study provides valuable information for guiding future water resource management in the Shiyang River Basin and other arid and semi‐arid regions in China. Copyright © 2011 John Wiley & Sons, Ltd.     

Forms and drivers of annual streamflow variability in the headwaters of Canadian Prairies during the 20th century

Headwater streamflows in the Rocky Mountain foothills are the key to water availability in the Canadian Prairies. Headwater characteristics, however, have been and continue to be subject to major variability and change. Here, we identify various forms of change in the annual mean streamflow and timing of the annual peak and attempt to distinguish between the effects of multiple drivers using a generalized regression scheme. Our investigation shows that the Pacific Decadal Oscillation (PDO) is the main driver of significant monotonic trends and shifts in the central tendency of annual mean streamflow in major headwaters. In parallel, the cumulative effects of non‐PDO climatic drivers and human‐induced land use and land management are the main causes of significant variations in the timing of the annual peak. Additional analyses show that time sequences with significant trends in annual mean streamflow and timing of the annual peak coincide with those that show significant trends in the PDO or non‐PDO component of the air temperature, respectively. The natural streamflow characteristics are substantially perturbed by anthropogenic river flow regulation, depending on the form of change and/or the level of regulation. Evidence suggests that the general tendency of human regulation is to alleviate the severity of above‐ and below‐average streamflow conditions; however, it may also intensify the variability in natural streamflow characteristics during drier years and/or those with earlier annual peak timing. These are circumstances to which the regional water resource system is vulnerable. Our findings are important for the provision of effective regional water resource management in the Canadian Prairies and contribute to a better understanding of the complex interactions between natural and anthropogenic drivers in coupled human–water systems.     

Effects of a century of land cover and climate change on the hydrology of the Puget Sound basin

The Puget Sound basin in northwestern Washington, USA has experienced substantial land cover and climate change over the last century. Using a spatially distributed hydrology model (the Distributed Hydrology‐Soil‐Vegetation Model, DHSVM) the concurrent effects of changing climate (primarily temperature) and land cover in the basin are deconvolved, based on land cover maps for 1883 and 2002, and gridded climate data for 1915–2006. It is found that land cover and temperature change effects on streamflow have occurred differently at high and low elevations. In the lowlands, land cover has occurred primarily as conversion of forest to urban or partially urban land use, and here the land cover signal dominates temperature change. In the uplands, both land cover and temperature change have played important roles. Temperature change is especially important at intermediate elevations (so‐called transient snow zone), where the winter snow line is most sensitive to temperature change—notwithstanding the effects of forest harvest over the same part of the basin. Model simulations show that current land cover results in higher fall, winter and early spring streamflow but lower summer flow; higher annual maximum flow and higher annual mean streamflow compared with pre‐development conditions, which is largely consistent with a trend analysis of model residuals. Land cover change effects in urban and partially urban basins have resulted in changes in annual flow, annual maximum flows, fall and summer flows. For the upland portion of the basin, shifts in the seasonal distribution of streamflows (higher spring flow and lower summer flow) are clearly related to rising temperatures, but annual streamflow has not changed much. Copyright © 2009 John Wiley & Sons, Ltd.     

Flow dynamics at the continental scale: Streamflow correlation and hydrological similarity

Streamflow variability in space and time critically affects anthropic water uses and ecosystem services. Unfortunately, spatiotemporal patterns of flow regimes are often unknown, as discharge measurements are usually recorded at a limited number of hydrometric stations unevenly distributed along river networks. Advances in understanding the physical processes that control the spatial patterns of river flows are therefore necessary to predict water availability at ungauged locations or to extrapolate pointwise streamflow observations. This work explores the use of the spatial correlation of river flows as a metric to quantify the similarity between hydrological responses of two catchments. Following a stochastic framework, 340,000 cross‐correlations between pairs of daily streamflows time series are predicted at a seasonal timescale across the contiguous United States using 413 catchments of the MOPEX dataset. Model predictions of streamflow correlation obtained in absence of run‐off information are successfully used to identify catchment outlets sharing similar discharge dynamics and flow regimes across a broad range of geomorphoclimatic conditions, without relying on calibration. The selection of reference streamgauges based on predicted streamflow correlation generally outperforms the selection based on spatial proximity, especially as the density of available gauged sections decreases. Interestingly, correlated outlets share a broad spectrum of hydrological signatures (mean discharge, flow variability, and recession properties), suggesting that catchments forced by analogous frequency and intensity of effective rainfall events might exhibit common geomorphoecological traits leading to similar hydrological responses. The proposed framework provides a physical basis to assist the regionalization of flow dynamics and to interpret the spatial variability of flow regimes along stream networks.     

North Atlantic Oscillation influences on Turkish lake levels

The North Atlantic Oscillation (NAO) is a large‐scale mode of natural climate variability governing the path of Atlantic mid‐latitude storm tracks and precipitation regimes in the Atlantic and Mediterranean sectors. The primary focus of this study is to investigate the variability of lake levels in seven lakes scattered across Turkey using the method of continuous wavelet transforms and global spectra. The long winter (December, January, February and March) lake‐level series and the NAO index (NAOI) series were subjected to wavelet transform. The global wavelet spectrum (energy spectrum of periodicities) of lake levels and winter NAOI anomalies, in most cases, revealed a significant correlation. It was shown that the Tuz, Sapanca, and Uluabat lakes reflect much stronger influences of the NAO than the other four lakes. In contrast, weak correlations were found in the coastal areas of the Mediterranean and eastern Turkey. The periodic structures of Turkish lake levels in relation to the NAO revealed a spectrum between the 1‐year and 10‐year scale level. Although the periodicities of more than 10‐year scale levels were detected, explaining significant relations between the NAO and these long‐term periodicities remains a challenging task. The results of this study are consistent with the earlier studies concerning the teleconnection between the NAO and climate variables in Turkey. Copyright © 2009 John Wiley & Sons, Ltd.     

Climate moderates potential shifts in streamflow from changes in pinyon‐juniper woodland cover across the western U.S.

Pinyon‐juniper (PJ) cover has increased up to 10‐fold in many parts of the western U.S. in the last 140+ years. The impacts of these changes on streamflows are unclear and may vary depending on the intra‐annual distribution and amount of precipitation. Given the importance of streamflow in the western U.S., it is important to understand how shifts in PJ woodland cover may produce changes in streamflow across the region's diverse hydroclimates. To this end, we simulated the land surface water balance with contrasting woodland and grassland cover with the Hydrologiska Byråns Vattenbalansavdelning (HBV) model at a 4‐km resolution across the distribution of PJ woodlands in the western U.S. We used shifts in evapotranspiration (ET) between woodland and grassland cover as a proxy for potential changes in streamflows. Comparison of HBV model results with paired catchment studies indicated the model reasonably simulated annual decreases in ET with changes from woodland to grassland cover. For the northern and western ecoregions of the PJ distribution in the western U.S. where precipitation predominantly occurs in the winter, HBV simulated a 25 mm (37%) annual decrease in ET with conversion to grassland from woodland. Conversely, in southern ecoregions of PJ distribution with prominent summer monsoons, annual differences in ET were only 6 mm (19%). Our results suggest that only 29% of the PJ distribution, compared to an estimated 45% based on precipitation amount alone, has the potential for meaningful increases in streamflow with land cover change from woodland to grassland.     

Stochastic renewal model of low-flow streamflow sequences

It is shown that runs of low-flow annual streamflow in a coastal semiarid basin of Central California can be adequately modelled by renewal theory. For example, runs of below-median annual streamflows are shown to follow a geometric distribution. The elapsed time between runs of below-median streamflow are geometrically distributed also. The sum of these two independently distributed geometric time variables defines the renewal time elapsing between the initiation of a low-flow run and the next one. The probability distribution of the renewal time is then derived from first principles, ultimately leading to the distribution of the number of low-flow runs in a specified time period, the expected number of low-flow runs, the risk of drought, and other important probabilistic indicators of low-flow. The authors argue that if one identifies drought threat with the occurrence of multiyear low-flow runs, as it is done by water supply managers in the study area, then our renewal model provides a number of interesting results concerning drought threat in areas historically subject to inclement, dry, climate. A 430-year long annual streamflow time series reconstructed by tree-ring analysis serves as the basis for testing our renewal model of low-flow sequences.     

Determining the amplitude and timing of streamflow discontinuities: A cross wavelet analysis approach

Records of natural processes, such as gradual streamflow fluctuations, are commonly interrupted by long or short disruptions from natural non‐linear responses to gradual changes, such as from river‐ice break‐ups, freezing as a result of annual solar cycles, or human causes, such as flow blocking by dams and other means, instrument calibrations and failure. The resulting abrupt or gradual shifts and missing data are considered to be discontinuities with respect to the normal signal. They differ from random noise as they do not follow any fixed distribution over time and, hence, cannot be eliminated by filtering. The multi‐scale resolution features of continuous wavelet analysis and cross wavelet analysis were used in this study to determine the amplitude and timing of such streamflow discontinuities for specific wavebands. The cross wavelet based method was able to detect the strength and timing of abrupt shifts to new streamflow levels, gaps in data records longer than the waveband of interest and a sinusoidal discontinuity curve following an underlying modeled annual signal at ±0.5 year uncertainty. Parameter testing of the time‐frequency resolution demonstrated that high temporal resolution using narrow analysis windows is favorable to high‐frequency resolution for detection of waveband‐related discontinuities. Discontinuity analysis on observed daily streamflow records from Canadian rivers showed the following: (i) that there is at least one discontinuity/year related to the annual spring flood in each record studied, and (ii) neighboring streamflows have similar discontinuity patterns. In addition, the discontinuity density of the Canadian streamflows studied in this paper exhibit 11‐year cycles that are inversely correlated with the solar intensity cycle. This suggests that more streamflow discontinuities, such as through fast freezing, snowmelt, or ice break‐up, may occur during years with slightly lowered solar insolation. Copyright © 2013 John Wiley & Sons, Ltd.     

Using large‐scale climatic patterns for improving long lead time streamflow forecasts for Gunnison and San Juan River Basins

In a water‐stressed region, such as the western United States, it is essential to have long lead times for streamflow forecasts used in reservoir operations and water resources management. Current water supply forecasts provide a 3‐month to 6‐month lead time, depending on the time of year. However, there is a growing demand from stakeholders to have forecasts that run lead times of 1 year or more. In this study, a data‐driven model, the support vector machine (SVM) based on the statistical learning theory, was used to predict annual streamflow volume with a 1‐year lead time. Annual average oceanic–atmospheric indices consisting of the Pacific decadal oscillation, North Atlantic oscillation (NAO), Atlantic multidecadal oscillation, El Niño southern oscillation (ENSO), and a new sea surface temperature (SST) data set for the ‘Hondo’ region for the period of 1906–2006 were used to generate annual streamflow volumes for multiple sites in the Gunnison River Basin and San Juan River Basin, both located in the Upper Colorado River Basin. Based on the performance measures, the model showed very good forecasts, and the forecasts were in good agreement with measured streamflow volumes. Inclusion of SST information from the Hondo region improved the model's forecasting ability; in addition, the combination of NAO and Hondo region SST data resulted in the best streamflow forecasts for a 1‐year lead time. The results of the SVM model were found to be better than the feed‐forward, back propagation artificial neural network and multiple linear regression. The results from this study have the potential of providing useful information for the planning and management of water resources within these basins. Copyright © 2012 John Wiley & Sons, Ltd.     

A nonlinear data‐driven model for synthetic generation of annual streamflows

A hybrid model that blends two non‐linear data‐driven models, i.e. an artificial neural network (ANN) and a moving block bootstrap (MBB), is proposed for modelling annual streamflows of rivers that exhibit complex dependence. In the proposed model, the annual streamflows are modelled initially using a radial basis function ANN model. The residuals extracted from the neural network model are resampled using the non‐parametric resampling technique MBB to obtain innovations, which are then added back to the ANN‐modelled flows to generate synthetic replicates. The model has been applied to three annual streamflow records with variable record length, selected from different geographic regions, namely Africa, USA and former USSR. The performance of the proposed ANN‐based non‐linear hybrid model has been compared with that of the linear parametric hybrid model. The results from the case studies indicate that the proposed ANN‐based hybrid model (ANNHM) is able to reproduce the skewness present in the streamflows better compared to the linear parametric‐based hybrid model (LPHM), owing to the effective capturing of the non‐linearities. Moreover, the ANNHM, being a completely data‐driven model, reproduces the features of the marginal distribution more closely than the LPHM, but offers less smoothing and no extrapolation value. It is observed that even though the preservation of the linear dependence structure by the ANNHM is inferior to the LPHM, the effective blending of the two non‐linear models helps the ANNHM to predict the drought and the storage characteristics efficiently. Copyright © 2007 John Wiley & Sons, Ltd.     

Impact of climate change on water resources in Yongdam Dam Basin,Korea

The main purpose of this study is to investigate and evaluate the impact of climate change on the runoff and water resources of Yongdam basin, Korea. First, we construct global climate change scenarios using the YONU GCM control run and transient experiments, then transform the YONU GCM grid-box predictions with coarse resolution of climate change into the site-specific values by statistical downscaling techniques. The downscaled values are used to modify the parameters of a stochastic weather generator model for the simulation of the site-specific daily weather time series. The weather series is fed into a semi-distributed hydrological model called SLURP to simulate the streamflows associated with other water resources for the condition of 2CO₂. This approach is applied to the Yongdam dam basin in the southern part of Korea. The results show that under the condition of 2CO₂, about 7.6% of annual mean streamflow is reduced when it is compared with the current condition. Seasonal streamflows in the winter and autumn are increased, while streamflow in the summer is decreased. However, the seasonality of the simulated series is similar to the observed pattern An erratum to this article can be found at     

Seasonal and spatial variations in the scaling and correlation structure of streamflow data

Seasonal and spatial variability in scaling, correlation and wavelet variance parameter of daily streamflow data were investigated using 56 gauging stations from five basins located in two different climate zones. Multifractal temporal scaling properties were detected using a multiplicative cascade model. The wavelet variance parameter yielded persistence properties of the streamflow time series. Seasonal variations were found to be significant in that winter and spring seasons where large‐scale frontal events are dominant showed higher long‐term correlations and less multifractality than did summer and fall seasons. Coherent spatial variations were apparent. The Neches River basin located in a subtropic humid climate zone exhibited high persistence and long‐term correlation as well as less multifractality as compared with other basins. It is found that larger drainage areas tend to have smaller multifractality and higher persistence structure, and this tendency becomes apparent in regions that receive large amounts of precipitation and decreases towards arid regions. Copyright © 2012 John Wiley & Sons, Ltd.