Towards hydrological model calibration and validation: simulation of stable water isotopes using the isoWATFLOOD model

Calibration and validation of hydrological models is a challenge, particularly in remote regions that are minimally gauged. This paper develops a novel methodology for large‐scale (>1000 km²) hydrological model calibration and validation using stable water isotopes founded on the rigorous constraints imposed by the need to conserve both water mass and stable isotopes simultaneously. The isoWATFLOOD model is applied to five basins within the Fort Simpson, Northwest Territories region of northern Canada to simulate stream discharge and oxygen‐18 signals over a 3‐year period. The isotopic variation of river discharge, runoff components, and evaporative fractionation are successfully simulated on both a seasonal and continual basis over the watershed domain to demonstrate the application of isotope tracers to regional hydrologic calibration. The intended application of this research is to remote, large‐scale basins, showing promise for improving predictions in minimally gauged basins and climate change research where traditional, rigorous approaches to constraining parameter uncertainty may be impractical. This coupled isotope‐hydrological (i.e. iso‐hydrological) approach to modelling reduces the number of possible parameterizations, resulting in potentially more physically‐based hydrological predictions. isoWATFLOOD provides a tool for water resource managers and utilities to use operationally for water use, allocation, and runoff generation estimations. Copyright © 2012 John Wiley & Sons, Ltd.     

On the value of isotope-enabled hydrological model calibration

ABSTRACT

Calibration of hydrological models is challenging in high-latitude regions where hydrometric data are minimal. Process-based models are needed to predict future changes in water supply, yet often with high amounts of uncertainty, in part, from poor calibrations. We demonstrate the utility of stable isotopes (¹⁸O, ²H) as data employed for improving the amount and type of information available for model calibration using the isoWATFLOOD^TM model. We show that additional information added to calibration does not hurt model performance and can improve simulation of water volume. Isotope-enabled calibration improves long-term validation over traditional flow-only calibrated models and offers additional feedback on internal flowpaths and hydrological storages that can be useful for informing internal water distribution and model parameterization. The inclusion of isotope data in model calibration reduces the number of realistic parameter combinations, resulting in more constrained model parameter ranges and improved long-term simulation of large-scale water balance.     

Spatially distributed tracer‐aided modelling to explore water and isotope transport,storage and mixing in a pristine,humid tropical catchment

Rapidly transforming headwater catchments in the humid tropics provide important resources for drinking water, irrigation, hydropower, and ecosystem connectivity. However, such resources for downstream use remain unstudied. To improve understanding of the behaviour and influence of pristine rainforests on water and tracer fluxes, we adapted the relatively parsimonious, spatially distributed tracer‐aided rainfall–runoff (STARR) model using event‐based stable isotope data for the 3.2‐km² San Lorencito catchment in Costa Rica. STARR was used to simulate rainforest interception of water and stable isotopes, which showed a significant isotopic enrichment in throughfall compared with gross rainfall. Acceptable concurrent simulations of discharge (Kling–Gupta efficiency [KGE] ~0.8) and stable isotopes in stream water (KGE ~0.6) at high spatial (10 m) and temporal (hourly) resolution indicated a rapidly responding system. Around 90% of average annual streamflow (2,099 mm) was composed of quick, near‐surface runoff components, whereas only ~10% originated from groundwater in deeper layers. Simulated actual evapotranspiration (ET) from interception and soil storage were low (~420 mm/year) due to high relative humidity (average 96%) and cloud cover limiting radiation inputs. Modelling suggested a highly variable groundwater storage (~10 to 500 mm) in this steep, fractured volcanic catchment that sustains dry season baseflows. This groundwater is concentrated in riparian areas as an alluvial–colluvial aquifer connected to the stream. This was supported by rainfall–runoff isotope simulations, showing a “flashy” stream response to rainfall with only a moderate damping effect and a constant isotope signature from deeper groundwater (~400‐mm additional mixing volume) during baseflow. The work serves as a first attempt to apply a spatially distributed tracer‐aided model to a tropical rainforest environment exploring the hydrological functioning of a steep, fractured‐volcanic catchment. We also highlight limitations and propose a roadmap for future data collection and spatially distributed tracer‐aided model development in tropical headwater catchments.     

A methodology for simple and fast streamflow modelling

ABSTRACT

During the last few decades, hydrological models have become very powerful, capable of spatially analysing the hydrological information and accurately representing the geomorphological characteristics of the studied area. However, one of the drawbacks of this heightened intricacy is the amount of time required to set up a hydrological model. In this study, a simple methodology that requires only a minimum set-up time is presented. This methodology employs linear regression to combine the outputs of simple hydrological models to simulate hydrological responses. Two kinds of simple hydrological models are employed. The first one represents the characteristics of the streamflow attributed to overland flow, and the second the characteristics of the streamflow attributed to interflow and baseflow. The methodology was tested in 4 case studies, and the results were encouraging. The best performance was achieved in the case study with data of fine time step with significant length.     

Exploiting the use of physical information for the calibration of a lumped hydrological model

In hydrological modelling, the challenge is to identify an optimal strategy to exploit tools and available observations in order to enhance model reliability. The increasing availability of data promotes the use of new calibration techniques able to make use of additional information on river basins. In the present study, a lumped hydrological model—designed with the aim of utilizing remotely sensed data—is introduced and calibrated, adopting four different schemes that adopt, to varying extents, available physical information. The physically consistent conceptualization of the hydrological model used allowed development of a step by step calibration based on a combination of information, such as remotely sensed data describing snow cover, recession curves obtained from streamflow measurements, and time series of surface run‐off obtained with a baseflow mathematical filter applied to the streamflow time‐series. Results suggest that the use of physical information in the calibration procedure tends to increase model reliability with respect to approaches where the parameters are calibrated using an overall statistic based, considerably or exclusively, on streamflow data.     

Effects of streamflow isotope sampling strategies on the calibration of a tracer-aided rainfall-runoff model

Isotopes are increasingly used in rainfall-runoff models to constrain conceptualisations of internal catchment functioning and reduce model uncertainty. However, there is little guidance on how much tracer data is required to adequately do this, and different studies use data from different sampling strategies. Here, we used a 7-year time series of daily stable water isotope samples of precipitation and streamflow to derive a range of typical stream sampling regimes and investigate how this impacts calibration of a semi-distributed tracer-aided model in terms of flow, deuterium and flux age simulations. Over the 7 years weekly sampling facilitated an almost identical model performance as daily, and there were only slight deteriorations in performance for fortnightly sampling. Monthly sampling resulted in poorer deuterium simulations and greater uncertainty in the derived parameter sets ability to accurately represent catchment functioning, evidenced by unrealistic reductions in the volumes of water available for mixing in the saturation area causing simulated water age decreases. Reducing sampling effort and restricting data collection to 3 years caused reductions in the accuracy of deuterium simulation, though the deterioration did not occur if sampling continued for 5 years. Analysis was also undertaken to consider the effects of reduced sampling effort over the driest and wettest hydrological years to evaluate effects of more extreme conditions. This showed that the model was particularly sensitive to changes in sampling during dry conditions, when the catchment hydrological response is most non-linear. Across all dataset durations, sampling in relation to flow conditions, rather than time, revealed that samples collected at flows >Q50 could provide calibration results comparable to daily sampling. Targeting only extreme high flows resulted in poor deuterium and low flow simulations. This study suggests sufficient characterization of catchment functioning can be obtained through reduced sampling effort over longer timescales and the targeting of flows >Q50.     

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.     

Modelling non-stationary water ages in a tropical rainforest: A preliminary spatially distributed assessment

Pristine tropical forests play a critical role in regional and global climate systems. For a better understanding of the eco-hydrology of tropical “evergreen” vegetation, it is essential to know the partitioning of water into transpiration and evaporation, runoff and associated water ages. For this purpose, we evaluated how topography and vegetation influence water flux and age dynamics at high temporal (hourly) and spatial (10 m) resolution using the Spatially Distributed Tracer-Aided Rainfall-Runoff model for the tropics (STARRtropics). The model was applied in a tropical rainforest catchment (3.2 km²) where data were collected biweekly to monthly and during intensive monitoring campaigns from January 2013 to July 2018. The STARRtropics model was further developed, incorporating an isotope mass balance for evapotranspiration partitioning into transpiration and evaporation. Results exhibited a rapid streamflow response to rainfall inputs (water and isotopes) with limited mixing and a largely time-invariant baseflow isotope composition. Simulated soil water storage showed a transient response to rainfall inputs with a seasonal component directly resembling the streamflow dynamics which was independently evaluated using soil water content measurements. High transpiration fluxes (max 7 mm/day) were linked to lower slope gradients, deeper soils and greater leaf area index. Overall water partitioning resulted in 65% of the actual evapotranspiration being driven by vegetation with high transpiration rates over the drier months compared to the wet season. Time scales of water age were highly variable, ranging from hours to a few years. Stream water ages were conceptualized as a mixture of younger soil water and slightly older, deeper soil water and shallow groundwater with a maximum age of roughly 2 years during drought conditions (722 days). The simulated soil water ages ranged from hours to 162 days and for shallow groundwater up to 1,200 days. Despite the model assumptions, experimental challenges and data limitation, this preliminary spatially distributed model study enhances knowledge about the water ages and overall young water dominance in a tropical rainforest with little influence of deeper and older groundwater.     

Modelling and estimation of different components of streamflow for Gangotri Glacier basin,Himalayas / Modélisation et estimation des différentes composantes de l'écoulement fluviatile du bassin du Glacier Gangotri,Himalaya

Abstract

The understanding of the runoff generation processes is reviewed and simulation of daily streamflow is reported for the Gangotri Glacier basin (Central Himalayas) with area of ～556 km², of which ～286 km² is occupied by the glaciers, and altitude of 4000 to 7000 m.a.s.l. A hydro-meteorological database was established by collecting meteorological and hydrological data near the snout of the glacier for four melt seasons (2000–2003) covering the period from May to October every year. Flow was simulated using a snowmelt model (SNOWMOD) based on the temperature index approach. Two years (2000 and 2001) of the four-year data set were used to calibrate the model, and the remaining two years (2002 and 2003) were used for verification. The study was carried out during the ablation period, as the availability of data was restricted to that period, responsible for a major part of the runoff. The model performed well for both calibration and verification periods. The overall efficiency of the model, R ², was 0.96 and the difference in volume of computed and observed streamflow was ?2.5%, indicating a good model performance. Simulation of different components of streamflow clearly indicates that almost all the high peaks are attributed to melt. The model was also used to estimate the respective contributions by melt and rainfall to the total seasonal flow: for summer runoff, these were estimated to be about 97% and 3%. Such studies are very useful for the planning and management of water resources in high-altitude areas and for designing hydropower projects.     

Using lumped conceptual rainfall-runoff models to simulate daily isotope variability with fractionation in a nested mesoscale catchment

This paper presents 19 months of stable isotope (δ²H and δ¹⁸O) data to enhance understanding of water and solute transport at two spatial scales (2.3 km² and 122 km²) in the agricultural Lunan catchment, Scotland. Daily precipitation and stream isotope data, weekly lake and spring isotope data and monthly groundwater isotope data revealed important insights into flow pathways and mixing of water at both scales. In particular, a deeper groundwater flow path significantly contributes to total streamflow (25-50%). Upstream lake isotope dynamics, susceptible to evaporative fractionation, also appeared to have an important influence on the downstream isotope composition. This unique tracer data set facilitated the conceptualization of a lumped catchment-scale flow-tracer model. The incorporation of hydrological, mixing and fractionation processes based on these data improved simulations of the stream δ²H isotope response at the catchment outlet from 0.37 to 0.56 for the Nash-Sutcliffe statistic. The stable isotope data successfully aided model conceptualization and calibration in the quest for a simple water and solute transport model with improved representation of process dynamics.     

Multi‐variable and multi‐site calibration and validation of SWAT in a large mountainous catchment with high spatial variability

Many methods developed for calibration and validation of physically based distributed hydrological models are time consuming and computationally intensive. Only a small set of input parameters can be optimized, and the optimization often results in unrealistic values. In this study we adopted a multi‐variable and multi‐site approach to calibration and validation of the Soil Water Assessment Tool (SWAT) model for the Motueka catchment, making use of extensive field measurements. Not only were a number of hydrological processes (model components) in a catchment evaluated, but also a number of subcatchments were used in the calibration. The internal variables used were PET, annual water yield, daily streamflow, baseflow, and soil moisture. The study was conducted using an 11‐year historical flow record (1990–2000); 1990–94 was used for calibration and 1995–2000 for validation. SWAT generally predicted well the PET, water yield and daily streamflow. The predicted daily streamflow matched the observed values, with a Nash–Sutcliffe coefficient of 0·78 during calibration and 0·72 during validation. However, values for subcatchments ranged from 0·31 to 0·67 during calibration, and 0·36 to 0·52 during validation. The predicted soil moisture remained wet compared with the measurement. About 50% of the extra soil water storage predicted by the model can be ascribed to overprediction of precipitation; the remaining 50% discrepancy was likely to be a result of poor representation of soil properties. Hydrological compensations in the modelling results are derived from water balances in the various pathways and storage (evaporation, streamflow, surface runoff, soil moisture and groundwater) and the contributions to streamflow from different geographic areas (hill slopes, variable source areas, sub‐basins, and subcatchments). The use of an integrated multi‐variable and multi‐site method improved the model calibration and validation and highlighted the areas and hydrological processes requiring greater calibration effort. Copyright © 2005 John Wiley & Sons, Ltd.     

Using high resolution tracer data to constrain water storage,flux and age estimates in a spatially distributed rainfall‐runoff model

Models simulating stream flow and conservative tracers can provide a representation of flow paths, storage distributions and mixing processes that is advantageous for many predictive purposes. Compared with models that only simulate stream flow, tracer data can be used to investigate the internal consistency of model behaviour and to gain insight into model performance. Here, we examine the strengths and weaknesses of a data‐driven, spatially distributed tracer‐aided rainfall‐runoff model. The model structure allowed us to assess the influence of landscape characteristics on the routing and mixing of water and tracers. The model was applied to a site in the Scottish Highlands with a unique tracer data set; ~4 years of daily isotope ratios in stream water and precipitation were available, as well as 2 years of weekly soil and ground water isotopes. The model structure was based on an empirically based, lumped tracer‐aided model previously developed for the catchment. The best model runs were selected from Monte Carlo simulations based on dual calibration criteria using objective functions for both stream isotopes and discharge at the outlet. Model performance for these criteria was reasonable (Nash–Sutcliffe efficiencies for discharge and isotope ratios were ~0.4–0.6). The model could generally reproduce the variable isotope signals in the soils of the steeper hill slopes where storage was low, and damped isotope responses in valley bottom cells with high storage. The model also allowed us to estimate the age distributions of internal stores, water fluxes and stream flow. Average stream water age was ~1.6 years, integrating older groundwater in the valley bottom and dynamic younger soil waters. By tracking water ages and simulating isotopes, the model captured the changes in connectivity driven by distributed storage dynamics. This has substantially improved the representation of spatio‐temporal process dynamics and gives a more robust framework for projecting environmental change impacts. Copyright © 2016 The Authors Hydrological Processes Published by John Wiley & Sons Ltd.     

Performance of Multivariate Adaptive Regression Splines (MARS) in predicting runoff in mid-Himalayan micro-watersheds with limited data / Performances de régressions par splines multiples et adaptives (MARS) pour la prévision d'écoulement au sein de micro-bassins versants Himalayens d'altitudes intermédiaires avec peu de données

Abstract

Steep topography and land-use transformations in Himalayan watersheds have a major impact on hydrological characteristics and flow regimes, and greatly affect the perenniality and sustainability of water resources in the region. To identify the appropriate conservation measures in a watershed properly, and, in particular, to augment flow during lean periods, accurate estimation of streamflow is essential. Due to the complexity of rainfall—runoff relationships in hilly watersheds and non-availability of reliable data, process-based models have limited applicability. In this study, data-driven models, based upon the Multiple Adaptive Regression Splines (MARS) technique, were employed to predict streamflow (surface runoff, baseflow and total runoff) in three mid-Himalayan micro-watersheds. In addition, the effect of length of historical records on the performance of MARS models was critically evaluated. Though acceptable MARS models could be developed with a 2-year data set, their performance improved considerably with a 3-year data set. Various indicators of model performance, such as correlation coefficient, average deviation, average absolute deviation and modelling efficiency, showed significant improvement for simulation of surface runoff, baseflow and total flow. To further analyse the versatility and general applicability of the MARS approach, 2-year data sets were used to develop the model and test it on a third-year data set to assess its performance. The models simulated the surface runoff, baseflow and total flow reasonably well and can be reliably applied in ungauged small watersheds under identical agro-climatic settings.     

Application of a rainfall-runoff model to three catchments in Iraq

Abstract

The capability of the Surface inFiltration Baseflow (SFB) conceptual rainfall-runoff model to simulate streamflow for three catchments selected from northern Iraq is investigated. These catchments differ in their climatic regimes and physical characteristics. Three versions of the model were tested: the original three-parameter model (SFB), the modified five-parameter model (SFB-5), and the modified six-parameter model (SFB-6). The available daily precipitation, potential evapotranspiration and runoff data were used in conjunction with a simulated annealing (SA) optimization technique to calibrate the various versions of the SFB model. A simple sensitivity analysis was then carried out to determine the relative importance of the model parameters. The study indicated that use of the original three parameter model was not adequate to simulate monthly streamflow in the selected catchments. The modified version (SFB-5) provided better runoff simulation than the original SFB model; overall a 19% increase was observed in the coefficient of determination (R²) between simulated and observed monthly runoff. The SFB-5 model performed with varying degrees of success among the catchments. The model performance in the validation stage was reasonable and comparable to that of the calibration stage. The sensitivity analysis of the SFB model for arid catchments revealed that the baseflow parameter (B) was the most sensitive one, while the S and F parameters were less sensitive than the B parameter.     

Testing a spatially distributed tracer‐aided runoff model in a snow‐influenced catchment: Effects of multicriteria calibration on streamwater ages

Integrating stable isotope tracers into rainfall‐runoff models allows investigation of water partitioning and direct estimation of travel times and water ages. Tracer data have valuable information content that can be used to constrain models and, in integration with hydrometric observations, test the conceptualization of catchment processes in model structure and parameterization. There is great potential in using tracer‐aided modelling in snow‐influenced catchments to improve understanding of these catchments' dynamics and sensitivity to environmental change. We used the spatially distributed tracer‐aided rainfall‐runoff (STARR) model to simulate the interactions between water storage, flux, and isotope dynamics in a snow‐influenced, long‐term monitored catchment in Ontario, Canada. Multiple realizations of the model were achieved using a combination of single and multiple objectives as calibration targets. Although good simulations of hydrometric targets such as discharge and snow water equivalent could be achieved by local calibration alone, adequate capture of the stream isotope dynamics was predicated on the inclusion of isotope data in the calibration. Parameter sensitivity was highest, and most local, for single calibration targets. With multiple calibration targets, key sensitive parameters were still identifiable in snow and runoff generation routines. Water ages derived from flux tracking subroutines in the model indicated a catchment where runoff is dominated by younger waters, particularly during spring snowmelt. However, resulting water ages were most sensitive to the partitioning of runoff sources from soil and groundwater sources, which was most realistically achieved when isotopes were included in the calibration. Given the paucity of studies where hydrological models explicitly incorporate tracers in snow‐influenced regions, this study using STARR is an important contribution to satisfactorily simulating snowpack dynamics and runoff generation processes, while simultaneously capturing stable isotope variability in snow‐influenced catchments.     

Evaluating the SWAT's snow hydrology over a Northern Quebec watershed

The snow treatment becomes an important component of Soil and Water Assessment Tool (SWAT)’s hydrology when spring flows are dominated by snow melting. However, little is known about SWAT's snow hydrology performance because most studies using SWAT were conducted in rainfall‐driven catchments. To fill this gap, the present study aims to evaluate the ability of SWAT in simulating snow‐melting‐dominated streamflow in the Outardes Basin in Northern Quebec. SWAT performance in simulating snowmelt is evaluated against observed streamflow data and compared to simulations from the operationally used Streamflow Synthesis and Reservoir Regulation (SSARR) model over that catchment. The SWAT 5‐year calibration showed a satisfactory performance at the daily and seasonal time scales with low volume biases. The SWAT validation was conducted over two (17‐year and 15‐year) periods. Performances were similar to the calibration period in simulating the daily and seasonal streamflows again with low model biases. The spring‐snowmelt‐generated peak flow was accurately simulated by SWAT both in magnitude and timing. When SWAT's results are compared to SSARR, similar performances in simulating the daily discharges were observed. SSARR simulates more accurately streamflow generated at the snowmelt onset whereas SWAT better predicts streamflow in summer, fall and winter. SWAT provided reasonable streamflow simulations for our snow‐covered catchment, but refinement of the process‐driven baseflow during the snowmelt onset could improve spring performances. Therefore, SWAT becomes an attractive tool for evaluating water resources management in Nordic environments when a distributed model is preferred or when water quality information (e.g. temperature) is required. Copyright © 2013 John Wiley & Sons, Ltd.     

Spatial GR4J conceptualization of the Tamor glaciated alpine catchment in Eastern Nepal: evaluation of GR4JSG against streamflow and MODIS snow extent

Snow and glacial melt processes are an important part of the Himalayan water balance. Correct quantification of melt runoff processes is necessary to understand the region's vulnerability to climate change. This paper describes in detail an application of conceptual GR4J hydrological model in the Tamor catchment in Eastern Nepal using typical elevation band and degree‐day factor approaches to model Himalayan snow and glacial melt processes. The model aims to provide a simple model that meets most water planning applications. The paper contributes a model conceptualization (GR4JSG) that enables coarse evaluation of modelled snow extents against remotely sensed Moderate Resolution Imaging Spectroradiometer snow extent. Novel aspects include the glacial store in GR4JSG and examination of how the parameters controlling snow and glacial stores correlate with existing parameters of GR4J. The model is calibrated using a Bayesian Monte Carlo Markov Chain method against observed streamflow for one glaciated catchment with reliable data. Evaluation of the modelled streamflow with observed streamflow gave Nash Sutcliffe Efficiency of 0.88 and Percent Bias of <4%. Comparison of the modelled snow extents with Moderate Resolution Imaging Spectroradiometer gave R² of 0.46, with calibration against streamflow only. The contribution of melt runoff to total discharge from the catchment is 14–16% across different experiments. The model is highly sensitive to rainfall and temperature data, which suffer from known problems and biases, for example because of stations being located predominantly in valleys and at lower elevations. Testing of the model in other Himalayan catchments may reveal additional limitations. © 2016 The Authors. Hydrological Processes published by John Wiley & Sons Ltd.     

Parameter identification and uncertainty analysis for simulating streamflow in a river basin of Eastern India

Uncertainty is inherent in modelling studies. However, the quantification of uncertainties associated with a model is a challenging task, and hence, such studies are somewhat limited. As distributed or semi‐distributed hydrological models are being increasingly used these days to simulate hydrological processes, it is vital that these models should be equipped with robust calibration and uncertainty analysis techniques. The goal of the present study was to calibrate and validate the Soil and Water Assessment Tool (SWAT) model for simulating streamflow in a river basin of Eastern India, and to evaluate the performance of salient optimization techniques in quantifying uncertainties. The SWAT model for the study basin was developed and calibrated using Parameter Solution (ParaSol), Sequential Uncertainty Fitting Algorithm (SUFI‐2) and Generalized Likelihood Uncertainty Estimation (GLUE) optimization techniques. The daily observed streamflow data from 1998 to 2003 were used for model calibration, and those for 2004–2005 were used for model validation. Modelling results indicated that all the three techniques invariably yield better results for the monthly time step than for the daily time step during both calibration and validation. The model performances for the daily streamflow simulation using ParaSol and SUFI‐2 during calibration are reasonably good with a Nash–Sutcliffe efficiency and mean absolute error (MAE) of 0.88 and 9.70 m³/s for ParaSol, and 0.86 and 10.07 m³/s for SUFI‐2, respectively. The simulation results of GLUE revealed that the model simulates daily streamflow during calibration with the highest accuracy in the case of GLUE (R² = 0.88, MAE = 9.56 m³/s and root mean square error = 19.70 m³/s). The results of uncertainty analyses by SUFI‐2 and GLUE were compared in terms of parameter uncertainty. It was found that SUFI‐2 is capable of estimating uncertainties in complex hydrological models like SWAT, but it warrants sound knowledge of the parameters and their effects on the model output. On the other hand, GLUE predicts more reliable uncertainty ranges (R‐factor = 0.52 for daily calibration and 0.48 for validation) compared to SUFI‐2 (R‐factor = 0.59 for daily calibration and 0.55 for validation), though it is computationally demanding. Although both SUFI‐2 and GLUE appear to be promising techniques for the uncertainty analysis of modelling results, more and more studies in this direction are required under varying agro‐climatic conditions for assessing their generic capability. Copyright © 2015 John Wiley & Sons, Ltd.     

Spatiotemporal dynamics of water sources in a mountain river basin inferred through δ2H and δ18O of water

In mountainous river basins of the Pacific Northwest, climate models predict that winter warming will result in increased precipitation falling as rain and decreased snowpack. A detailed understanding of the spatial and temporal dynamics of water sources across river networks will help illuminate climate change impacts on river flow regimes. Because the stable isotopic composition of precipitation varies geographically, variation in surface water isotope ratios indicates the volume-weighted integration of upstream source water. We measured the stable isotope ratios of surface water samples collected in the Snoqualmie River basin in western Washington over June and September 2017 and the 2018 water year. We used ordinary least squares regression and geostatistical Spatial Stream Network models to relate surface water isotope ratios to mean watershed elevation (MWE) across seasons. Geologic and discharge data was integrated with water isotopes to create a conceptual model of streamflow generation for the Snoqualmie River. We found that surface water stable isotope ratios were lowest in the spring and highest in the dry, Mediterranean summer, but related strongly to MWE throughout the year. Low isotope ratios in spring reflect the input of snowmelt into high elevation tributaries. High summer isotope ratios suggest that groundwater is sourced from low elevation areas and recharged by winter precipitation. Overall, our results suggest that baseflow in the Snoqualmie River may be relatively resilient to predicted warming and subsequent changes to snowpack in the Pacific Northwest.