Mediating stream baseflow response to climate change: The role of basin storage

Inter‐basin differences in streamflow response to changes in regional hydroclimatology may reflect variations in storage characteristics that control the retention and release of water inputs. These aspects of storage could mediate a basin's sensitivity to climate change. The hypothesis that temporal trends in stream baseflow exhibit a more muted reaction to changes in precipitation and evapotranspiration for basins with greater storage was tested on the Oak Ridges Moraine (ORM) in Southern Ontario, Canada. Long‐term (>25 years) baseflow trends for 16 basins were compared to corresponding trends in precipitation amount and type and in potential evapotranspiration as well as shorter trends in groundwater levels for monitoring wells on the ORM. Inter‐basin differences in storage properties were characterized using physiographic, hydrogeologic, land use/land cover, and streamflow metrics. The latter included the slope of the basin's flow duration curve and basin dynamic storage. Most basins showed temporal increases in baseflow, consistent with limited evidence of increases and decreases in regional precipitation and snowfall: precipitation ratio, respectively, and recent increases in groundwater recharge along the crest of the ORM. Baseflow trend magnitude was uncorrelated to basin physiographic, hydrogeologic, land use/land cover, or flow duration curve characteristics. However, it was positively related to a basin's dynamic storage, particularly for basins with limited coverage of open water and wetlands. The dynamic storage approach assumes that a basin behaves as a first‐order dynamical system, and extensive open water and wetland areas in a basin may invalidate this assumption. Previous work suggested that smaller dynamic storage was linked to greater damping of temporal variations in water inputs and reduced interannual variability in streamflow regime. Storage and release of water inputs to a basin may assist in mediating baseflow response to temporal changes in regional hydroclimatology and may partly account for inter‐basin differences in that response. Such storage characteristics should be considered when forecasting the impacts of climate change on regional streamflow.     

Regionalization of constraints on expected watershed response behavior for improved predictions in ungauged basins

Approaches to modeling the continuous hydrologic response of ungauged basins use observable physical characteristics of watersheds to either directly infer values for the parameters of hydrologic models, or to establish regression relationships between watershed structure and model parameters. Both these approaches still have widely discussed limitations, including impacts of model structural uncertainty. In this paper we introduce an alternative, model independent, approach to streamflow prediction in ungauged basins based on empirical evidence of relationships between watershed structure, climate and watershed response behavior. Instead of directly estimating values for model parameters, different hydrologic response behaviors of the watershed, quantified through model independent streamflow indices, are estimated and subsequently regionalized in an uncertainty framework. This results in expected ranges of streamflow indices in ungauged watersheds. A pilot study using 30 UK watersheds shows how this regionalized information can be used to constrain ensemble predictions of any model at ungauged sites. Dominant controlling characteristics were found to be climate (wetness index), watershed topography (slope), and hydrogeology. Main streamflow indices were high pulse count, runoff ratio, and the slope of the flow duration curve. This new approach provided sharp and reliable predictions of continuous streamflow at the ungauged sites tested.     

A comparison of methods for low streamflow estimation from spot measurements

Low streamflow statistic estimators at ungauged river sites generally have large errors and uncertainties. This can be due to many reasons, including lack of data, complex hydrologic processes, and the inadequate or improper characterization of watershed hydrogeology. One potential solution is to take a small number of streamflow measurements at an ungauged site to either estimate hydrogeologic indices or transfer information from a nearby site using concurrent streamflow measurements. An analysis of four low streamflow estimation techniques, regional regression, regional plus hydrogeologic indices, baseflow correlation, and scaling, was performed within the Apalachicola–Chattahoochee–Flint watershed, a U.S. Geological Survey WaterSMART region in the south‐eastern United States. The latter three methods employ a nominal number of spot measurements at the ungauged site to improve low streamflow estimation. Results indicate that baseflow correlation and scaling methods, which transfer information from a donor site, can produce improved low streamflow estimators when spot measurements are available. Estimation of hydrogeologic indices from spot measurements improves regional regression models, with the baseflow recession constant having more explanatory power than the aquifer time constant, but these models are generally outperformed by baseflow correlation and scaling.     

Linking hydrologic signatures to hydrologic processes: A review

Hydrologic signatures are metrics that quantify aspects of streamflow response. Linking signatures to underlying processes enables multiple applications, such as selecting hydrologic model structure, analysing hydrologic change, making predictions in ungauged basins, and classifying watershed function. However, many lists of hydrologic signatures are not process-based, and knowledge about signature-process links has been scattered among studies from experimental watersheds and model selection experiments. This review brings together those studies to catalogue more than 50 signatures representing evapotranspiration, snow storage and melt, permafrost, infiltration excess, saturation excess, groundwater, baseflow, connectivity, channel processes, partitioning, and human alteration. The review shows substantial variability in the number, type, and timescale of signatures available to represent each process. Many signatures provide information about groundwater storage, partitioning, and connectivity, whereas snow processes and human alteration are underrepresented. More signatures are related to the seasonal scale than the event timescale, and land surface processes (ET, snow, and overland flow) have no signatures at the event scale. There are limitations in some signatures that test for occurrence but cannot quantify processes, or are related to multiple processes, making automated analysis more difficult. This review will be valuable as a reference for hydrologists seeking to use streamflow records to investigate a particular hydrologic process or to conduct large-sample analyses of patterns in hydrologic processes.     

Constraining water table depth simulations in a land surface model using estimated baseflow

Several recent studies have shown the significance of representing groundwater in land surface hydrologic simulations. However, optimal methods for model parameter calibration in order to realistically simulate baseflow and groundwater depth have received little attention. Most studies still use globally constant groundwater parameters due to the lack of available datasets for calibration. Moreover, when models are calibrated, various parameter combinations are found to exhibit equifinality in simulated total runoff due to model parameter interactions. In this study, a simple lumped groundwater model is incorporated into the Community Land Model (CLM), in which the water table is interactively coupled to soil moisture through the groundwater recharge fluxes. The coupled model (CLMGW) is successfully validated in Illinois using a 22-year (1984–2005) monthly observational dataset. Baseflow estimates from the digital recursive filter technique are used to calibrate the CLMGW parameters. The advantage obtained from incorporating baseflow calibration in addition to traditional calibration based on measured streamflow alone is demonstrated by a Monte Carlo-type simulation analysis. Using the optimal parameter sets identified from baseflow calibration, flow partitioning and water table depth simulations using CLMGW are improved, and the equifinality problem is alleviated. For other regions that lack observations of water table depth, the baseflow calibration approach can be used to enhance parameter estimation and constrain water table depth simulations.     

Application of distributed hydrological models for predictions in ungauged basins: a method to quantify predictive uncertainty

Stream flow predictions in ungauged basins are one of the most challenging tasks in surface water hydrology because of nonavailability of data and system heterogeneity. This study proposes a method to quantify stream flow predictive uncertainty of distributed hydrologic models for ungauged basins. The method is based on the concepts of deriving probability distribution of model's sensitive parameters by using measured data from a gauged basin and transferring the distribution to hydrologically similar ungauged basins for stream flow predictions. A Monte Carlo simulation of the hydrologic model using sampled parameter sets with assumed probability distribution is conducted. The posterior probability distributions of the sensitive parameters are then computed using a Bayesian approach. In addition, preselected threshold values of likelihood measure of simulations are employed for sizing the parameter range, which helps reduce the predictive uncertainty. The proposed method is illustrated through two case studies using two hydrologically independent sub‐basins in the Cedar Creek watershed located in Texas, USA, using the Soil and Water Assessment Tool (SWAT) model. The probability distribution of the SWAT parameters is derived from the data from one of the sub‐basins and is applied for simulation in the other sub‐basin considered as pseudo‐ungauged. In order to assess the robustness of the method, the numerical exercise is repeated by reversing the gauged and pseudo‐ungauged basins. The results are subsequently compared with the measured stream flow from the sub‐basins. It is observed that the measured stream flow in the pseudo‐ungauged basin lies well within the estimated confidence band of predicted stream flow. Copyright © 2013 John Wiley & Sons, Ltd.     

How informative are stream level observations in different geographic regions?

Simple runoff models with a low number of model parameters are generally able to simulate catchment runoff reasonably well, but they rely on model calibration, which makes their use in ungauged basins challenging. In a previous study it has been shown that a limited number of streamflow measurements can be quite informative for constraining runoff models. In practice, however, instead of performing such repeated flow measurements, it might be easier to install a stream level logger. Here, a dataset of 600+ gauged basins in the USA was used to study how well models perform when only stream level data, rather than streamflow data, are available. A runoff model (the HBV model) was calibrated assuming that only stream level observations were available, and the simulations were evaluated on the full observed streamflow record. The results indicate that stream level data alone can already provide surprisingly good model simulation results in humid catchments, whereas in arid catchments some form of quantitative information (e.g. a streamflow observation or a regional average value) is needed to obtain good results. These results are encouraging for hydrological observations in data scarce regions as level observations are much easier to obtain than streamflow measurements. Based on runoff modelling, it might even be possible to derive streamflow time series from the level data obtained from loggers, satellites or community‐based approaches. Copyright © 2016 John Wiley & Sons, Ltd.     

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.     

A novel approach to infer streamflow signals for ungauged basins

In this paper, we present a novel paradigm for inference of streamflow for ungauged basins. Our innovative procedure fuses concepts from both kernel methods and data assimilation. Based on the modularity and flexibility of kernel techniques and the strengths of the variational Bayesian Kalman filter and smoother, we can infer streamflow for ungauged basins whose hydrological and system properties and/or behavior are non-linear and non-Gaussian. We apply the proposed approach to two watersheds, one in California and one in West Virginia. The inferred streamflow signals for the two watersheds appear promising. These preliminary and encouraging validations demonstrate that our new paradigm is capable of providing accurate conditional estimates of streamflow for ungauged basins with unknown and non-linear dynamics.     

Observed hydrographs: on their ability to infer a time‐invariant hydrological transfer function for flow prediction in ungauged basins

Streamflow measurements provide information about the flow generation characteristics of land surfaces as well as the flow transferring nature of the channel network. In this study, such flow transferring properties of the channel network that were obtained from downstream flow observations were used for predicting flow in ungauged basins. A temporally averaged transfer function (ATF) of the channel segments of Kentucky River Basin (KRB) in Kentucky, USA, was extracted from observed hydrographs in a time‐invariant system as a function of drainage area. The ATF was regionalized through multiple regression analysis for 194 combinations of drainage areas that differ in topography, terrain, and geology. The application of ATF for flow prediction in ungauged basins was performed for Goose Creek, a subbasin of KRB by integrating ATF with the TOPMODEL. In addition, the ATF was shown to be capable of providing calibration and validation data for ungauged basins in a backward technique from a measured stream gauge downstream, with minimal data requirement of drainage area. The applicability of ATF was illustrated across a range of streamflow conditions from watersheds that varied greatly in their terrain and geology. Nash–Sutcliffe efficiency of the proposed method, as a function of drainage areas of the corresponding basins, to predict daily streamflow from ungauged basins ranged from 0.83 to 0.92. The results of the study concluded that the ATF obtained from measured streamflow thus proved to be a quick and simple tool for assessment of streamflow in both operational and modeling hydrology. Copyright © 2012 John Wiley & Sons, Ltd.     

Homogenization of spatial patterns of hydrologic response in artificially drained agricultural catchments

Anthropogenic modifications to the landscape, with agricultural activities being a primary driver, have resulted in significant alterations to the hydrologic cycle. Artificial drainage, including surface and subsurface drainage (tile drains), is one of the most extensive manipulations in agricultural landscapes and thus is expected to provide a distinct signature of anthropogenic modification. This study adopts a data synthesis approach in an effort to characterize the signature of artificial subsurface drainage. Daily discharge data from 24 basins across the state of Iowa, which encapsulate a range of anthropogenic modifications, are assessed using a variety of flow metrics. Results indicate that the presence of artificial subsurface drainage leads to a homogenization of landscape hydrologic response. Non‐tiled watersheds exhibit a decrease in the area‐normalized peak discharge and an increase in the baseflow ratio (baseflow/streamflow) with increases in the spatial scale, while scale invariance is apparent in tiled basins. Within‐basin variability in hydrograph recession coefficients also appears to decrease with increases in the proportion of the catchment that is artificially drained. Finally, the differences between tiled and non‐tiled landscapes disappear at scales greater than approximately 2200 km², indicating that this may be a threshold scale for studying the effects of tile drainage. This decrease in within‐basin variability and the scale invariance of hydrologic metrics in artificially drained watersheds are attributed to the creation of a bypass flow hydrologic pathway that bypasses the complexity of the catchment travel paths. Spatial homogeneity in responses implies that it may be possible to develop more parsimonious hydrologic models for these regions. Copyright © 2013 John Wiley & Sons, Ltd.     

Simulating low and high streamflow driven by snowmelt in an insufficiently gauged alpine basin

Snowmelt and water infiltration are two important processes of the hydrological cycle in alpine basins where snowmelt water is a main contributor of streamflow. In insufficiently gauged basins, hydrologic modeling is a useful approach to understand the runoff formation process and to simulate streamflow. In this study, an existing hydrologic model based on the principles of system dynamics was modified by using the effective cumulative temperature (>0 °C) to calculate snowmelt rate, and the soil temperature to adjust the influence of the soil’s physical state on water infiltration. This modified model was used to simulate streamflows in the Kaidu River basin from 1982 to 2002, including normal, high, and low flows categorized by the Z index. Sensitivity analyses, visual inspection, and statistical measures were employed to evaluate the capability of the model to simulate various components of the streamflow. Results showed that the modified model was robust, and able to simulate the three categories of flows well. The model’s ability to reproduce streamflow in low-flow and normal-flow years was better than that in high-flow years. The model was also able to simulate the baseflow. Further, its ability to simulate spring-peak flow was much better than its ability to simulate the summer-peak flow. This study could provide useful information for water managers in determining water allocations as well as in managing water resources.     

Scaling and physiographic controls on streamflow behaviour on the Precambrian Shield, south-central Ontario

Relationships explaining streamflow behaviour in terms of drainage basin physiography greatly assist efforts to extrapolate streamflow metrics from gauged to ungauged basins in the same landscape. The Dorset Environmental Science Centre (DESC) has monitored streamflow from 22 small basins (3.4–190.5 ha) on the Precambrian Shield in south-central Ontario, in some cases since 1976. The basins exhibit regional coherence in their interannual response to precipitation; however, there is often a poor correlation between streamflow metrics from basins separated by as little as 1 km. This study assesses whether inter-basin variations in such metrics can be explained in terms of basin scale and physiography. Several characteristics (annual maximum, minimum and average flow) exhibited simple scaling with basin area, while magnitude, range and timing of annual maximum daily runoff showed scaling behaviour consistent with the Representative Elementary Area (REA) concept. This REA behaviour is partly attributed to convergence of fractional coverage of the two dominant and hydrologically-contrasting land cover types in the DESC region with increasing basin size. Three Principal Components (PCs) explained 82.4% of the variation among basin physiographic properties, and several runoff metrics (magnitude and timing of annual minimum daily runoff, mean number of days per year with 0 streamflow) exhibited significant relationships with one or more PC. Significant relationships were obtained between basin quickflow (QF) production and the PCs on a seasonal and annual basis, almost all of which were superior to simple area-based relationships. Basin physiography influenced QF generation via its control on slope runoff, water storage and hydrologic connectivity; however, this role was minimized during Spring when QF production in response to large rain-on-snow events was relatively uniform across the DESC basins. The PC-based relationships and inter-seasonal changes in their form were consistent with previous research conducted at point, slope and basin scales in the DESC region, and perceptions of key hydrological processes in these small basins may not have been as readily obtained from scaling studies using streamflow from larger basins. This process understanding provides insights into scaling behaviour beyond those derived from simple scaling and REA analyses. The physiography of the study area is representative of large portions of the Precambrian Shield, such that basin streamflow behaviour could potentially be extended across much of south-central Ontario. This would assist predictions of streamflow conditions at ungauged locations, development and testing of hydrological models for this landscape, and interpretation of inter-basin and intra-annual differences in hydrochemical behaviour on the southern Precambrian Shield.     

Causes of systematic over‐ or underestimation of low streamflows by use of index‐streamgage approaches in the United States

Low‐flow characteristics can be estimated by multiple linear regressions or the index‐streamgage approach. The latter transfers streamflow information from a hydrologically similar, continuously gaged basin (‘index streamgage’) to one with a very limited streamflow record, but often results in biased estimates. The application of the index‐streamgage approach can be generalized into three steps: (1) selection of streamflow information of interest, (2) definition of hydrologic similarity and selection of index streamgage, and (3) application of an information‐transfer approach. Here, we explore the effects of (1) the range of streamflow values, (2) the areal density of streamgages, and (3) index‐streamgage selection criteria on the bias of three information‐transfer approaches on estimates of the 7‐day, 10‐year minimum streamflow (Q_{7, 10}). The three information‐transfer approaches considered are maintenance of variance extension, base‐flow correlation, and ratio of measured to concurrent gaged streamflow (Q‐ratio invariance). Our results for 1120 streamgages throughout the United States suggest that only a small portion of the total bias in estimated streamflow values is explained by the areal density of the streamgages and the hydrologic similarity between the two basins. However, restricting the range of streamflow values used in the index‐streamgage approach reduces the bias of estimated Q_{7, 10} values substantially. Importantly, estimated Q_{7, 10} values are heavily biased when the observed Q_{7, 10} values are near zero. Results of the analysis also showed that Q_{7, 10} estimates from two of the three index‐streamgage approaches have lower root‐mean‐square error values than estimates derived from multiple regressions for the large regions considered in this study. Published in 2011 by John Wiley & Sons, Ltd.     

Dynamic storage: a potential metric of inter‐basin differences in storage properties

The potential for dynamic storage to serve as a metric of basin behaviour was assessed using data from five drainage basins with headwaters on the thick sand and gravel deposits of the Oak Ridges Moraine in southern Ontario, Canada. Dynamic storage was directly correlated with the ratio of variability of δ²H in streamflow relative to that in precipitation. This ratio has previously been shown to be inversely related to basin mean transit time (MTT), suggesting an inverse relationship between dynamic storage and MTT for the study basins. Dynamic storage was also directly correlated with interannual variability in stream runoff, baseflow and baseflow:runoff ratio, implying that basins with smaller dynamic storage have less interannual variability in their streamflow regimes. These preliminary results suggest that dynamic storage may serve as a readily derived and useful metric of basin behaviour for inter‐basin comparisons. Copyright © 2016 John Wiley & Sons, Ltd.     

Hydrograph separation using tracers and digital filters to quantify runoff components in a semi‐arid mesoscale catchment

Chemical hydrograph separation using electrical conductivity and digital filters is applied to quantify runoff components in the 1,640 km² semi‐arid Kaap River catchment and its subcatchments in South Africa. A rich data set of weekly to monthly water quality data ranging from 1978 to 2012 (450 to 940 samples per site) was analysed at 4 sampling locations in the catchment. The data were routinely collected by South Africa's national Department of Water and Sanitation, using standard sampling procedures. Chemical hydrograph separation using electrical conductivity (EC) as a tracer was used as reference and a recursive digital filter was then calibrated for the catchment. Results of the two‐component hydrograph separation indicate the dominance of baseflow in the low flow regime, with a contribution of about 90% of total flow; however, during the wet season, baseflow accounts for 50% of total flow. The digital filter parameters were very sensitive and required calibration, using chemical hydrograph separation as a reference. Calibrated baseflow estimates ranged from 40% of total flow at the catchment outlet to 70% in the tributaries. The study demonstrates that routinely monitored water quality data, especially EC, can be used as a meaningful tracer, which could also aid in the calibration of a digital filter method and reduce uncertainty of estimated flow components. This information enhances our understanding of how baseflow is generated and contributed to streamflow throughout the year, which can aid in quantification of environmental flows, as well as to better parameterize hydrological models used for water resources planning and management. Baseflow estimates can also be useful for groundwater and water quality management.     

Is there a superior conceptual groundwater model structure for baseflow simulation?

Previous work has shown that streamflow response during baseflow conditions is a function of storage, but also that this functional relationship varies among seasons and catchments. Traditionally, hydrological models incorporate conceptual groundwater models consisting of linear or non‐linear storage–outflow functions. Identification of the right model structure and model parameterization however is challenging. The aim of this paper is to systematically test different model structures in a set of catchments where different aquifer types govern baseflow generation processes. Nine different two‐parameter conceptual groundwater models are applied with multi‐objective calibration to transform two different groundwater recharge series derived from a soil‐atmosphere‐vegetation transfer model into baseflow separated from streamflow data. The relative performance differences of the model structures allow to systematically improve the understanding of baseflow generation processes and to identify most appropriate model structures for different aquifer types. We found more versatile and more aquifer‐specific optimal model structures and elucidate the role of interflow, flow paths, recharge regimes and partially contributing storages. Aquifer‐specific recommendations of storage models were found for fractured and karstic aquifers, whereas large storage capacities blur the identification of superior model structures for complex and porous aquifers. A model performance matrix is presented, which highlights the joint effects of different recharge inputs, calibration criteria, model structures and aquifer types. The matrix is a guidance to improve groundwater model structures towards their representation of the dominant baseflow generation processes of specific aquifer types. Copyright © 2014 John Wiley & Sons, Ltd.     

Modification of the SWAT model to simulate regional groundwater flow using a multicell aquifer

The soil and water assessment tool (SWAT) has been widely used and thoroughly tested in many places in the world. The application of the SWAT model has pointed out that 2 of the major weaknesses of SWAT are related to the nonspatial reference of the hydrologic response unit concept and to the simplified groundwater concept, which contribute to its low performance in baseflow simulation and its inability to simulate regional groundwater flow. This study modified the groundwater module of SWAT to overcome the above limitations. The modified groundwater module has 2 aquifers. The local aquifer, which is the shallow aquifer in the original SWAT, represents a local groundwater flow system. The regional aquifer, which replaces the deep aquifer of the original SWAT, represents intermediate and regional groundwater flow systems. Groundwater recharge is partitioned into local and regional aquifer recharges. The regional aquifer is represented by a multicell aquifer (MCA) model. The regional aquifer is discretized into cells using the Thiessen polygon method, where centres of the cells are locations of groundwater observation wells. Groundwater flow between cells is modelled using Darcy's law. Return flow from cell to stream is conceptualized using a non‐linear storage–discharge relationship. The SWAT model with the modified aquifer module, the so‐called SWAT‐MCA, was tested in 2 basins (Wipperau and Neetze) with porous aquifers in a lowland area in Lower Saxony, Germany. Results from the Wipperau basin show that the SWAT‐MCA model is able (a) to simulate baseflow in a lowland area (where baseflow is a dominant source of streamflow) better than the original model and (b) to simulate regional groundwater flow, shown by the simulated groundwater levels in cells, quite well.     

Changes in monthly baseflow across the U.S. Midwest

Characterizing streamflow changes in the agricultural U.S. Midwest is critical for effective planning and management of water resources throughout the region. The objective of this study is to determine if and how baseflow has responded to land alteration and climate changes across the study area during the 50‐year study period by exploring hydrologic variations based on long‐term stream gage data. This study evaluates monthly contributions to annual baseflow along with possible trends over the 1966–2016 period for 458 U.S. Geological Survey streamflow gages within 12 different Midwestern states. It also examines the influence of climate and land use factors on the observed baseflow trends. Monthly contribution breakdowns demonstrate how the majority of baseflow is discharged into streams during the spring months (March, April, and May) and is overall more substantial throughout the spring (especially in April) and summer (June, July, and August). Baseflow has not remained constant over the study period, and the results of the trend detection from the Mann–Kendall test reveal that baseflows have increased and are the strongest from May to September. This analysis is confirmed by quantile regression, which suggests that for most of the year, the largest changes are detected in the central part of the distribution. Although increasing baseflow trends are widespread throughout the region, decreasing trends are few and limited to Kansas and Nebraska. Further analysis reveals that baseflow changes are being driven by both climate and land use change across the region. Increasing trends in baseflow are linked to increases in precipitation throughout the year and are most prominent during May and June. Changes in agricultural intensity (in terms of harvested corn and soybean acreage) are linked to increasing trends in the central and western Midwest, whereas increasing temperatures may lead to decreasing baseflow trends in spring and summer in northern Wisconsin, Kansas, and Nebraska.     

Regional regression models for hydro‐climate change impact assessment

Hydro‐climatic impacts in water resources systems are typically assessed by forcing a hydrologic model with outputs from general circulation models (GCMs) or regional climate models. The challenges of this approach include maintaining a consistent energy budget between climate and hydrologic models and also properly calibrating and verifying the hydrologic models. Subjective choices of loss, flow routing, snowmelt and evapotranspiration computation methods also increase watershed modelling uncertainty and thus complicate impact assessment. An alternative approach, particularly appealing for ungauged basins or locations where record lengths are short, is to predict selected streamflow quantiles directly from meteorological variable output from climate models using regional regression models that also include physical basin characteristics. In this study, regional regression models are developed for the western Great Lakes states using ordinary least squares and weighted least squares techniques applied to selected Great Lakes watersheds. Model inputs include readily available downscaled GCM outputs from the Coupled Model Intercomparison Project Phase 3. The model results provide insights to potential model weaknesses, including comparatively low runoff predictions from continuous simulation models that estimate potential evapotranspiration using temperature proxy information and comparatively high runoff projections from regression models that do not include temperature as an explanatory variable. Copyright © 2014 John Wiley & Sons, Ltd.