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 winter atmospheric circulation on temporal and spatial variability in annual streamflow in the western United States

Abstract

Winter mean 700-hectoPascal (hPa) height anomalies, representing the average atmospheric circulation during the snow season, are compared with annual streamflow measured at 140 streamgauges in the western United States. Correlation and anomaly pattern analyses are used to identify relationships between winter mean atmospheric circulation and temporal and spatial variability in annual streamflow. Results indicate that variability in winter mean 700-Hpa height anomalies accounts for a statistically significant portion of the temporal variability in annual streamflow in the western United States. In general, above-average annual streamflow is associated with negative winter mean 700-Hpa height anomalies over the eastern North Pacific Ocean and/or the western United States. The anomalies produce an anomalous flow of moist air from the eastern North Pacific Ocean into the western United States that increases winter precipitation and snowpack accumulations, and subsequently streamflow. Winter mean 700-hPa height anomalies also account for statistically significant differences in spatial distributions of annual streamflow. As part of this study, winter mean atmospheric circulation patterns for the 40 years analysed were classified into five winter mean 700-hPa height anomaly patterns. These patterns are related to statistically significant and physically meaningful differences in spatial distributions of annual streamflow.     

Characterizing and understanding the variability of streamflow drought indicators within the USA

ABSTRACT

Low streamflow conditions can have adverse consequences for society and river ecology. The variability and drivers of streamflow drought indicators within the USA were investigated using observed streamflow records from 603 gauges across the USA. The analysis was based on two main approaches: (i) low-flow magnitude indicators, and (ii) streamflow deficit indicators. First, we examined how streamflow drought indicators vary spatially across the USA. Second, we used a data-driven clustering method to identify spatial clusters for each indicator. Finally, we assessed the association with regional climate drivers. The results show that the spatial variability of low-flow magnitude indicators is significantly different from the deficit indicators. Further, our clustering approach identifies regions of spatial homogeneity, which can be linked to the extreme regional climate drivers and land–atmosphere interactions. The influence of regional climate on streamflow drought indicators varies more between clusters than between indicators.     

Can climate variability information constrain a hydrological model for an ungauged Costa Rican catchment?

Long‐term hydrological data are key to understanding catchment behaviour and for decision making within water management and planning. Given the lack of observed data in many regions worldwide, such as Central America, hydrological models are an alternative for reproducing historical streamflow series. Additional types of information—to locally observed discharge—can be used to constrain model parameter uncertainty for ungauged catchments. Given the strong influence that climatic large‐scale processes exert on streamflow variability in the Central American region, we explored the use of climate variability knowledge as process constraints to constrain the simulated discharge uncertainty for a Costa Rican catchment, assumed to be ungauged. To reduce model uncertainty, we first rejected parameter relationships that disagreed with our understanding of the system. Then, based on this reduced parameter space, we applied the climate‐based process constraints at long‐term, inter‐annual, and intra‐annual timescales. In the first step, we reduced the initial number of parameters by 52%, and then, we further reduced the number of parameters by 3% with the climate constraints. Finally, we compared the climate‐based constraints with a constraint based on global maps of low‐flow statistics. This latter constraint proved to be more restrictive than those based on climate variability (further reducing the number of parameters by 66% compared with 3%). Even so, the climate‐based constraints rejected inconsistent model simulations that were not rejected by the low‐flow statistics constraint. When taken all together, the constraints produced constrained simulation uncertainty bands, and the median simulated discharge followed the observed time series to a similar level as an optimized model. All the constraints were found useful in constraining model uncertainty for an—assumed to be—ungauged basin. This shows that our method is promising for modelling long‐term flow data for ungauged catchments on the Pacific side of Central America and that similar methods can be developed for ungauged basins in other regions where climate variability exerts a strong control on streamflow variability.     

Changes in snowmelt runoff timing in the contiguous United States

Changes in timing of snowmelt-fed streamflow have great importance for water supply, flood management, and ecological processes, as well as being a common indicator of climate change. In this study, snowmelt runoff timing change in the contiguous United States between 1957 and 2016 was investigated by analysing data from 97 streamflow gages. The annual snowmelt runoff timing shift was identified using ‘Center Time (CT)’ and ‘Spring Pulse Onset (SPO)’ methods, jointly with the monthly fractional streamflow (MFS) analysis, conducted between January and June. Since snowmelt-derived streamflow timing change is mainly induced by regional meteorological factors, such as air temperature and precipitation, their trends and relationship with CT were also examined. Shifts toward earlier snowmelt runoff timing were found by both methods, CT (8.3 days on average) and SPO (8.5 days on average). Although the results of the CT change are stronger than the SPO change, both outcomes are mostly correlated, particularly in the central and northwestern parts of the country. MFS trends support the outcomes of CT and SPO. In January, February, and especially March, a higher number of the stations indicated increasing trends in MFS. In April, May, and June, their number decreased and the number of gages with diminishing trends rose sharply. The timing difference is highly related to temperature change. Annual average temperature and temperature in the melting period increase considerably. The annual average temperature is significantly negatively correlated with CT in the vast majority of the regions. Although precipitation is not as effective as the temperature, its trends have impacts on snowmelt runoff timing change depending on the region and elevation. These results demonstrate the importance of the impacts of snowmelt runoff timing changes due to global warming on the regional and large-scale hydrology in the contiguous United States.     

Regional patterns of postwildfire streamflow response in the Western United States: The importance of scale‐specific connectivity

Wildfires can impact streamflow by modifying net precipitation, infiltration, evapotranspiration, snowmelt, and hillslope run‐off pathways. Regional differences in fire trends and postwildfire streamflow responses across the conterminous United States have spurred concerns about the impact on streamflow in forests that serve as water resource areas. This is notably the case for the Western United States, where fire activity and burn severity have increased in conjunction with climate change and increased forest density due to human fire suppression. In this review, we discuss the effects of wildfire on hydrological processes with a special focus on regional differences in postwildfire streamflow responses in forests. Postwildfire peak flows and annual water yields are generally higher in regions with a Mediterranean or semi‐arid climate (Southern California and the Southwest) compared to the highlands (Rocky Mountains and the Pacific Northwest), where fire‐induced changes in hydraulic connectivity along the hillslope results in the delivery of more water, more rapidly to streams. No clear streamflow response patterns have been identified in the humid subtropical Southeastern United States, where most fires are prescribed fires with a low burn severity, and more research is needed in that region. Improved assessment of postwildfire streamflow relies on quantitative spatial knowledge of landscape variables such as prestorm soil moisture, burn severity and correlations with soil surface sealing, water repellency, and ash deposition. The latest studies furthermore emphasize that understanding the effects of hydrological processes on postwildfire dynamic hydraulic connectivity, notably at the hillslope and watershed scales, and the relationship between overlapping disturbances including those other than wildfire is necessary for the development of risk assessment tools.     

Estimating minimum streamflow from measurements at ungauged sites in regions with streamflow‐gauging networks

Estimation of low flows in rivers continues to be a vexing problem despite advances in statistical and process‐based hydrological models. We develop a method to estimate minimum streamflow at seasonal to annual timescales from measured streamflow based on regional similarity in the deviations of daily streamflow from minimum streamflow for a period of interest. The method is applied to 1,019 gauged sites in the Western United States for June to December 2015. The gauges were clustered into six regions with distinct timing and magnitude of low flows. A gamma distribution was fit each day to the deviations in specific discharge (daily streamflow divided by drainage area) from minimum specific discharge for gauges in each region. The Kolmogorov–Smirnov test identified days when the gamma distribution was adequate to represent the distribution of deviations in a region. The performance of the gamma distribution was evaluated at gauges by comparing daily estimates of minimum streamflow with estimates from area‐based regression relations for minimum streamflow. Each region had at least 8 days during the period when streamflow measurements would provide better estimates than the regional regression equation, but the number of such days varied by region depending on aridity and homogeneity of streamflow within the region. Synoptic streamflow measurements at ungauged sites have value for estimating minimum streamflow and improving the spatial resolution of hydrological model in regions with streamflow‐gauging networks.     

Simulating precipitation in the Northeast United States using a climate-informed K-nearest neighbour algorithm

Decadal prediction using climate models faces long-standing challenges. While global climate models may reproduce long-term shifts in climate due to external forcing, in the near term, they often fail to accurately simulate interannual climate variability, as well as seasonal variability, wet and dry spells, and persistence, which are essential for water resources management. We developed a new climate-informed K-nearest neighbour (K-NN)-based stochastic modelling approach to capture the long-term trend and variability while replicating intra-annual statistics. The climate-informed K-NN stochastic model utilizes historical data along with climate state information to provide improved simulations of weather for near-term regional projections. Daily precipitation and temperature simulations are based on analogue weather days that belong to years similar to the current year's climate state. The climate-informed K-NN stochastic model is tested using 53 weather stations in the Northeast United States with an evident monotonic trend in annual precipitation. The model is also compared to the original K-NN weather generator and ISIMIP-2b GFDL general circulation model bias-corrected output in a cross-validation mode. Results indicate that the climate-informed K-NN model provides improved simulations for dry and wet regimes, and better uncertainty bounds for annual average precipitation. The model also replicates the within-year rainfall statistics. For the 1961–1970 dry regime, the model captures annual average precipitation and the intra-annual coefficient of variation. For the 2005–2014 wet regime, the model replicates the monotonic trend and daily persistence in precipitation. These improved modelled precipitation time series can be used for accurately simulating near-term streamflow, which in turn can be used for short-term water resources planning and management.     

Spatial scaling properties of annual streamflow in the United States

Abstract

The spatial scaling properties of annual average streamflow is examined using records from 1 433 river basins across the continental United States. The log-linear relationship ln(E[Q^r _i]) = a + b_r ln(A_i) is representative throughout the United States, where E[Q^r _i] represents the expectation of the rth moment of annual streamflow at site i, and A_i represents drainage area. The scaling model parameters a_r and b_r follow nearly perfect linear relationships a_r = rα and b_r = rβ throughout the continental United States. We conclude that the probability distribution of annual streamflow follows simple scaling relationships in all regions of the United States. In temperate regions where climate is relatively homogeneous, scale alone describes most of the variability in the moments of annual streamflow. In the more climatically heterogeneous regions, such as in the Upper Colorado and Missouri river basins, scale alone is a poor predictor of the moments of annual flow.     

Modeling the effects of climate change projections on streamflow in the Nooksack River basin,Northwest Washington

The Nooksack River has its headwaters in the North Cascade Mountains and drains an approximately 2000 km² watershed in northwestern Washington State. The timing and magnitude of streamflow in a snowpack‐dominated drainage basin such as the Nooksack River basin are strongly influenced by temperature and precipitation. Projections of future climate made by general circulation models (GCMs) indicate increases in temperature and variable changes in precipitation for the Nooksack River basin. Understanding the response of the river to climate change is crucial for regional water resources planning because municipalities, tribes, and industry depend on the river for water use and for fish habitat. We combine three different climate scenarios downscaled from GCMs and the Distributed‐Hydrology‐Soil‐Vegetation Model to simulate future changes to timing and magnitude of streamflow in the higher elevations of the Nooksack River. Simulations of future streamflow and snowpack in the basin project a range of magnitudes, which reflects the variable meteorological changes indicated by the three GCM scenarios and the local natural variability employed in the modeling. Simulation results project increased winter flows, decreased summer flows, decreased snowpack, and a shift in timing of the spring melt peak and maximum snow water equivalent. These results are consistent with previous regional studies, but the magnitude of increased winter flows and total annual runoff is higher. Increases in temperature dominate snowpack declines and changes to spring and summer streamflow, whereas a combination of increases in temperature and precipitation control increased winter streamflow. Copyright © 2013 John Wiley & Sons, Ltd.     

The impacts of climate change on local hydrology and low flow frequency in the Geum River Basin,Korea

The climate sensitive analysis of potential climate change on streamflow has been conducted using a hydrologic model to identify hydrologic variability associated with climate scenarios as a function of perturbed climatic variables (e.g. carbon dioxide, temperature, and precipitation). The interannual variation of water resources availability as well as low flow frequency driven by monsoonal time shifts have been investigated to evaluate the likelihood of droughts in a changing climate. The results show that the timing shift of the monsoon window associated with future climate scenarios clearly affect annual water yield change of ? 12 and ? 8% corresponding to 1‐month earlier and 1‐month later monsoon windows, respectively. Also, a more severe low flow condition has been predicted at 0·03 m³/s as opposed to the historic 7Q10 flow of 1·54 m³/s given at extreme climate scenarios. Copyright © 2011 John Wiley & Sons, Ltd.     

Decoupling the effects of deforestation and climate variability in the Tapajós river basin in the Brazilian Amazon

Tropical river basins are experiencing major hydrological alterations as a result of climate variability and deforestation. These drivers of flow changes are often difficult to isolate in large basins based on either observations or experiments; however, combining these methods with numerical models can help identify the contribution of climate and deforestation to hydrological alterations. This paper presents a study carried out in the Tapaj?s River (Brazil), a 477,000 km² basin in South‐eastern Amazonia, in which we analysed the role of annual land cover change on daily river flows. Analysis of observed spatial and temporal trends in rainfall, forest cover, and river flow metrics for 1976 to 2008 indicates a significant shortening of the wet season and reduction in river flows through most of the basin despite no significant trend in annual precipitation. Coincident with seasonal trends over the past 4 decades, over 35% of the original forest (140,000 out of 400,000 km²) was cleared. In order to determine the effects of land clearing and rainfall variability to trends in river flows, we conducted hindcast simulations with ED2 + R, a terrestrial biosphere model incorporating fine scale ecosystem heterogeneity arising from annual land‐use change and linked to a flow routing scheme. The simulations indicated basin‐wide increases in dry season flows caused by land cover transitions beginning in the early 1990s when forest cover dropped to 80% of its original extent. Simulations of historical potential vegetation in the absence of land cover transitions indicate that reduction in rainfall during the dry season (mean of ?9 mm per month) would have had an opposite and larger magnitude effect than deforestation (maximum of +4 mm/month), leading to the overall net negative trend in river flows. In light of the expected increase in future climate variability and water infrastructure development in the Amazon and other tropical basins, this study presents an approach for analysing how multiple drivers of change are altering regional hydrology and water resources management.     

Long‐term streamflow trends in the middle reaches of the Yellow River Basin: detecting drivers of change

The catchments in the Loess Plateau, in China's middle reaches of the Yellow River Basin, experienced unprecedented land use changes in the last 50 years as a result of large‐scale soil conservation measure to control soil erosion. The climate of the region also exhibited some levels of change with decreased precipitation and increased temperature. This study combined the time‐trend analysis method with a sensitivity‐based approach and found that annual streamflow in the Loess Plateau decreased significantly since the 1950s and surface runoff trends appear to dominate the streamflow trends in most of the catchments. Annual baseflow exhibited mostly downward trends, but significant upward trends were also observed in 3 out of 38 gauging stations. Mean annual streamflow during 1979?2010 decreased by up to 65% across the catchments compared with the period of 1957?1978, indicating significant changes in the hydrological regime of the Loess Plateau. It is estimated that 70% of the streamflow reduction can be attributed to land use change, while the remaining 30% is associated with climate variability. Land use change because of the soil conservation measures and reduction in precipitation are the key drivers for the observed streamflow trends. These findings are consistent with results of previous studies for the region and appear to be reasonable given the accelerated level of the soil conservation measures implemented since the late 1970s. Changes in sea surface temperature in the Pacific Ocean, as indicated by variations in El Niño–Southern Oscillation and phase shifts of the Pacific Decadal Oscillation, appear to have also affected the annual streamflow trends. The framework described in this study shows promising results for quantifying the effects of land use change and climate variability on mean annual streamflow of catchments within the Loess Plateau. Copyright © 2015 John Wiley & Sons, Ltd.     

Detailed streamflow data for understanding hydrologic responses in the Logan River Observatory

The Logan River watershed, located in Northern Utah, USA, consists of a relatively pristine, mountainous area that drains to a lower elevation, valley area influenced by both urban development and agriculture. The Logan River Observatory has been collecting aquatic (streamflow and water quality) and climate data throughout the Logan River watershed since 2014. While streamflow measurements are commonly made at the outlets of research watersheds, the Logan River watershed consists of diverse hydrologic, topographic, and geologic settings that require a detailed understanding of streamflow variability over time at many locations. Here, we illustrate: (a) the importance of collecting streamflow time series throughout complex watersheds, and (b) how simple flow balances can provide much needed hydrologic insight into the locations and timing of gains and losses over reaches to guide future investigations.     

Hydrogeologic controls on streamflow sensitivity to climate variation

Climate models project warmer temperatures for the north‐west USA, which will result in reduced snowpacks and decreased summer streamflow. This paper examines how groundwater, snowmelt, and regional climate patterns control discharge at multiple time scales, using historical records from two watersheds with contrasting geological properties and drainage efficiencies. In the groundwater‐dominated watershed, aquifer storage and the associated slow summer recession are responsible for sustaining discharge even when the seasonal or annual water balance is negative, while in the runoff‐dominated watershed subsurface storage is exhausted every summer. There is a significant 1 year cross‐correlation between precipitation and discharge in the groundwater‐dominated watershed (r = 0·52), but climatic factors override geology in controlling the inter‐annual variability of streamflow. Warmer winters and earlier snowmelt over the past 60 years have shifted the hydrograph, resulting in summer recessions lasting 17 days longer, August discharges declining 15%, and autumn minimum discharges declining 11%. The slow recession of groundwater‐dominated streams makes them more sensitive than runoff‐dominated streams to changes in snowmelt amount and timing. Copyright © 2008 John Wiley & Sons, Ltd.     

Spatial variability in specific discharge and streamwater chemistry during low flows: Results from snapshot sampling campaigns in eleven Swiss catchments

Catchments consist of distinct landforms that affect the storage and release of subsurface water. Certain landforms may be the main contributors to streamflow during extended dry periods, and these may vary for different catchments in a given region. We present a unique dataset from snapshot field campaigns during low‐flow conditions in 11 catchments across Switzerland to illustrate this. The catchments differed in size (10 to 110 km²), varied from predominantly agricultural lowlands to Alpine areas, and covered a range of physical characteristics. During each snapshot campaign, we jointly measured streamflow and collected water samples for the analysis of major ions and stable water isotopes. For every sampling location (basin), we determined several landscape characteristics from national geo‐datasets, including drainage area, elevation, slope, flowpath length, dominant land use, and geological and geomorphological characteristics, such as the lithology and fraction of quaternary deposits. The results demonstrate very large spatial variability in specific low‐flow discharge and water chemistry: Neighboring sampling locations could differ significantly in their specific discharge, isotopic composition, and ion concentrations, indicating that different sources contribute to streamflow during extended dry periods. However, none of the landscape characteristics that we analysed could explain the spatial variability in specific discharge or streamwater chemistry in multiple catchments. This suggests that local features determine the spatial differences in discharge and water chemistry during low‐flow conditions and that this variability cannot be assessed a priori from available geodata and statistical relations to landscape characteristics. The results furthermore suggest that measurements at the catchment outlet during low‐flow conditions do not reflect the heterogeneity of the different source areas in the catchment that contribute to streamflow.     

Roles of forest disturbance and climate variability on streamflow components in snow-dominated paired watersheds at multiple temporal scales

The paired watershed experimental (PWE) approach has long been used as an effective means to assess the impacts of forest change on hydrology in small watersheds (<100 km²). Yet, the effects of climate variability on streamflow are not often assessed in PWE design. In this study, two sets of paired watersheds, (1) Camp and Greata Creeks and (2) 240 and 241 Creeks located in the Southern Interior of British Columbia, Canada, were selected to explore relative roles of forest disturbance and climate variability on streamflow components (i.e., baseflow and surface runoff) at different time scales. Our analyses showed that forest disturbance is positively related to annual streamflow components. However, this relationship is statistically insignificant since forest disturbance can either increase or decrease seasonal streamflow components, which eventually limited the positive effect on streamflow at the annual scale. Interestingly, we found that forest disturbance consistently decreased summer streamflow components in the two PWEs as forest disturbance can augment earlier and quicker snow-melt processes and hence reduce soil moisture to maintain summer streamflow components. More importantly, this study revealed that climate variability played a more significant role than forest disturbance in both annual and seasonal streamflow components, for instance, climate variability can account for as much as 90% of summer streamflow components variation in Camp, suggesting the role of climate variability on streamflow should be highlighted in the traditional PWE approach to truly advance our understanding of the interactions of forest change, climate variability and water for sustainable water resource management.     

Anomalies in the US precipitation extremes and their association with different modes of climate variability

ABSTRACT

In this study, we investigate the temporal oscillations of precipitation extremes in different climate regions of the United States. We apply quantile perturbation analysis to average daily precipitation and, to 1041 weather stations with high-quality data from 1900 to 2016. Moreover, we explore the relationship between the extreme precipitation and different well-known cyclical climate modes. Overall, the analysis of average daily precipitation identifies a drier condition in the middle decades of the twentieth century and, a wetter climate in the early century and recent decades. Moreover, the in situ analysis reveals a significant anomaly, mainly prevalent in the Central and Southern regions of the United States. We applied a finite set of linear regression models with different combinations of cyclical climate modes to inform the variability of anomalies with best performing models. Our results highlight the dominant effect of ENSO and NAO in the wide area of the United States.     

Comparative streamflow characteristics in urbanizing basins in the Portland Metropolitan Area,Oregon, USA

This study investigates changes in streamflow characteristics for urbanizing watersheds in the Portland Metropolitan Area of Oregon for the period from 1951 to 2000. The objective of this study was to assess how mean annual runoff ratio, mean seasonal runoff ratio, annual peak runoff ratio, changes in streamflow in response to storm amount, the fraction of time that the daily mean flow exceeds the annual mean flow, 3‐day recession constants, and dry/wet flow ratio vary among watersheds with different degrees of urban development. There were no statistically significant changes in annual runoff ratio and annual peak runoff ratio for the mixed land‐use watershed (Tualatin River watershed) and the urban watershed (Johnson Creek watershed) during the entire study period. The Tualatin River watershed, where most of the urban development occurred in a lower part of the watershed, showed a statistically significant increase in annual peak runoff ratio during the 1976 and 2000 period. The Upper Tualatin River watershed illustrated a significant decrease in annual peak runoff ratio for the entire study period. With significant differences in seasonal runoff ratio, only Johnson Creek exhibited a significant increase in both wet and dry season runoff ratios. Streamflow during storm events declined rapidly in the urban watershed, with a high 3‐day recession constant. At an event storm scale, streamflow in Fanno Creek, which is the most urbanized watershed, responded quickly to precipitation input. The fraction of time that the daily mean flow exceeded the annual mean flow and dry/wet flow ratio are all lower in Johnson Creek. This suggests a shorter duration of storm runoff and lower baseflow in the urbanized watershed when compared to the mixed land use watershed. The findings of this study demonstrate the importance of spatial and temporal scale, climate variability, and basin physiographic characteristics in detecting the hydrologic effects of urbanization in the Pacific Northwest of the USA. Copyright © 2006 John Wiley & Sons, Ltd.