Bias adjustment methods usually do not account for the origins of biases in climate models and instead perform empirical adjustments. Biases in the synoptic circulation are for instance often overlooked when postprocessing regional climate model (RCM) simulations driven by general circulation models (GCMs). Yet considering atmospheric circulation helps to establish links between the synoptic and the regional scale, and thereby provides insights into the physical processes leading to RCM biases. Here we investigate how synoptic circulation biases impact regional climate simulations and influence our ability to mitigate biases in precipitation and temperature using quantile mapping. We considered 20 GCM-RCM combinations from the ENSEMBLES project and characterized the dominant atmospheric flow over the Alpine domain using circulation types. We report in particular a systematic overestimation of the frequency of westerly flow in winter. We show that it contributes to the generalized overestimation of winter precipitation over Switzerland, and this wet regional bias can be reduced by improving the simulation of synoptic circulation. We also demonstrate that statistical bias adjustment relying on quantile mapping is sensitive to circulation biases, which leads to residual errors in the postprocessed time series. Overall, decomposing GCM-RCM time series using circulation types reveals connections missed by analyses relying on monthly or seasonal values. Our results underscore the necessity to better diagnose process misrepresentation in climate models to progress with bias adjustment and impact modeling.
Nine mid-latitude to high-latitude headwater catchments - part of the Northern Watershed Ecosystem Response to Climate Change (North-Watch) programme - were used to analyze threshold response to rainfall and snowmelt-driven events and link the different responses to the catchment characteristics of the nine sites. The North-Watch data include daily time-series of various lengths of multiple variables such as air temperature, precipitation and discharge. Rainfall and meltwater inputs were differentiated using a degree-day snowmelt approach. Distinct hydrological events were identified, and precipitation-runoff response curves were visually assessed. Results showed that eight of nine catchments showed runoff initiation thresholds and effective precipitation input thresholds. For rainfall-triggered events, catchment hydroclimatic and physical characteristics (e.g. mean annual air temperature, median flow path distance to the stream, median sub-catchment area) were strong predictors of threshold strength. For snowmelt-driven events, however, thresholds and the factors controlling precipitation-runoff response were difficult to identify. The variability in catchments responses to snowmelt was not fully explained by runoff initiation thresholds and input magnitude thresholds. The quantification of input intensity thresholds (e.g. snow melting and permafrost thawing rates) is likely required for an adequate characterization of nonlinear spring runoff generation in such northern environments.
Soil moisture is an important variable for hillslope and catchment hydrology. There are various computational methods to estimate soil moisture and their complexity varies greatly: from one box with vertically constant volumetric soil water content to fully saturated-unsaturated coupled physically-based models. Different complexity levels are applicable depending on the simulation scale, computational time limitations, input data and knowledge about the parameters. The Vertical Equilibrium Model (VEM) is a simple approach to estimate the catchment-wide soil water storage at a daily time-scale on the basis of water table level observations, soil properties and an assumption of hydrological equilibrium without vertical fluxes above the water table. In this study VEM was extended by considering vertical fluxes, which allows conditions with evaporation and infiltration to be represented. The aim was to test the hypothesis that the simulated volumetric soil water content significantly depends on vertical fluxes. The water content difference between the no-flux, equilibrium approach and the new constant-flux approach greatly depended on the soil textural class, ranging between similar to 1% for silty clay and similar to 44% for sand at an evapotranspiration rate of 5 mm.d(-1). The two approaches gave a mean volumetric soil water content difference of 1 mm for two case studies (sandy loam and organic rich soils). The results showed that for many soil types the differences in estimated storage between the no-flux and the constant flux approaches were relatively small.
In the past, hydrologic modeling of surface water resources has mainly focused on simulating the hydrologic cycle at local to regional catchment modeling domains. There now exists a level of maturity among the catchment, global water security, and land surface modeling communities such that these communities are converging toward continental domain hydrologic models. This commentary, written from a catchment hydrology community perspective, provides a review of progress in each community toward this achievement, identifies common challenges the communities face, and details immediate and specific areas in which these communities can mutually benefit one another from the convergence of their research perspectives. Those include: (1) creating new incentives and infrastructure to report and share model inputs, outputs, and parameters in data services and open access, machine-independent formats for model replication or reanalysis; (2) ensuring that hydrologic models have: sufficient complexity to represent the dominant physical processes and adequate representation of anthropogenic impacts on the terrestrial water cycle, a process-based approach to model parameter estimation, and appropriate parameterizations to represent large-scale fluxes and scaling behavior; (3) maintaining a balance between model complexity and data availability as well as uncertainties; and (4) quantifying and communicating significant advancements toward these modeling goals.
Water's journey from rain to stream by Harald Grip and Allan Rodhe (1985, in Swedish: Vattnets vag fran regn till back) was one of the first textbooks to present groundwater contributions as a major feature of runoff generation, with implications for water quality and management. Three decades later, we have the privilege of presenting a special issue of Hydrological Processes, Runoff Generation in a Nordic Light: 30Years with Water's Journey from Rain to Stream' that seeks to introduce the book to a larger audience and continue the journey of ideas that the authors set in motion with their book.
This paper explores the flow paths and turnover times within a catchment characterized by the transmissivity feedback mechanism where there is a strong increase in the saturated hydraulic conductivity towards the soil surface and precipitation inputs saturate progressively more superficial layers of the soil profile. The analysis is facilitated by the correlation between catchment water storage and groundwater levels, which made it possible to model the daily spatial distribution of water storage, both vertically in different soil horizons and horizontally across a 6300-m2 till catchment. Soil properties and episodic precipitation input dynamics, combined with the influence of topographic features, concentrate flow in the horizontal, vertical, and temporal dimensions. Within the soil profile, there was a vertical concentration of lateral flow to superficial soil horizons (upper 30?cm of the soil), where much of the annual flow occurred during runoff episodes. Overland flow from a limited portion of the catchment can contribute to peak flows but is not a necessary condition for runoff episodes. The spatial concentration of flow, and the episodic nature of runoff events, resulted in a strong and spatially structured differentiation of local flow velocities within the catchment. There were large differences in the time spent by the laterally flowing water at different depths, with turnover times of lateral flow across a 1-m-wide soil pedon ranging from under 1?h at 10- to 20-cm depth to a month at 70- to 80-cm depth. In many regards, the hydrology of this catchment appears typical of the hydrology in till soils, which are widespread in Fenno-Scandia.
Design flood estimates for a given return period are required in both gauged and ungauged catchments for hydraulic design and risk assessments. Contrary to classical design estimates, synthetic design hydrographs provide not only information on the peak magnitude of events but also on the corresponding hydrograph volumes together with the hydrograph shapes. In this study, we tested different regionalization approaches to transfer parameters of synthetic design hydrographs from gauged to ungauged catchments. These approaches include classical regionalization methods such as linear regression techniques, spatial methods, and methods based on the formation of homogeneous regions. In addition to these classical approaches, we tested nonlinear regression models not commonly used in hydrological regionalization studies, such as random forest, bagging, and boosting. We found that parameters related to the magnitude of the design event can be regionalized well using both linear and nonlinear regression techniques using catchment area, length of the main channel, maximum precipitation intensity, and relief energy as explanatory variables. The hydrograph shape, however, was found to be more difficult to regionalize due to its high variability within a catchment. Such variability might be better represented by looking at flood-type specific synthetic design hydrographs.
Flood hydrograph shapes contain valuable information on the flood-generation mechanisms of a catchment. To make good use of this information, we express flood hydrograph shapes as continuous functions using a functional data approach. We propose a clustering approach based on functional data for flood hydrograph shapes to identify a set of representative hydrograph shapes on a catchment scale and use these catchment-specific sets of representative hydrographs to establish regions of catchments with similar flood reactivity on a regional scale. We applied this approach to flood samples of 163 medium-size Swiss catchments. The results indicate that three representative hydrograph shapes sufficiently describe the hydrograph shape variability within a catchment and therefore can be used as a proxy for the flood behavior of a catchment. These catchment-specific sets of three hydrographs were used to group the catchments into three reactivity regions of similar flood behavior. These regions were not only characterized by similar hydrograph shapes and reactivity but also by event magnitudes and triggering event conditions. We envision these regions to be useful in regionalization studies, regional flood frequency analyses, and to allow for the construction of synthetic design hydrographs in ungauged catchments. The clustering approach based on functional data which establish these regions is very flexible and has the potential to be extended to other geographical regions or toward the use in climate impact studies.
Accurate estimates of flood peaks, corresponding volumes, and hydrographs are required to design safe and cost-effective hydraulic structures. In this paper, we propose a statistical approach for the estimation of the design variables peak and volume by constructing synthetic design hydrographs for different flood types such as flash-floods, short-rain floods, long-rain floods, and rain-on-snow floods. Our approach relies on the fitting of probability density functions to observed flood hydrographs of a certain flood type and accounts for the dependence between peak discharge and flood volume. It makes use of the statistical information contained in the data and retains the process information of the flood type. The method was tested based on data from 39 mesoscale catchments in Switzerland and provides catchment specific and flood type specific synthetic design hydrographs for all of these catchments. We demonstrate that flood type specific synthetic design hydrographs are meaningful in flood-risk management when combined with knowledge on the seasonality and the frequency of different flood types.
Estimates of flood event magnitudes with a certain return period are required for the design of hydraulic structures. While the return period is clearly defined in a univariate context, its definition is more challenging when the problem at hand requires considering the dependence between two or more variables in a multivariate framework. Several ways of defining a multivariate return period have been proposed in the literature, which all rely on different probability concepts. Definitions use the conditional probability, the joint probability, or can be based on the Kendall's distribution or survival function. In this study, we give a comprehensive overview on the tools that are available to define a return period in a multivariate context. We especially address engineers, practitioners, and people who are new to the topic and provide them with an accessible introduction to the topic. We outline the theoretical background that is needed when one is in a multivariate setting and present the reader with different definitions for a bivariate return period. Here, we focus on flood events and the different probability concepts are explained with a pedagogical, illustrative example of a flood event characterized by the two variables peak discharge and flood volume. The choice of the return period has an important effect on the magnitude of the design variable quantiles, which is illustrated with a case study in Switzerland. However, this choice is not arbitrary and depends on the problem at hand.
Traditional design flood estimation approaches have focused on peak discharges and have often neglected other hydrograph characteristics such as hydrograph volume and shape. Synthetic design hydrograph estimation procedures overcome this deficiency by jointly considering peak discharge, hydrograph volume, and shape. Such procedures have recently been extended to allow for the consideration of process variability within a catchment by a flood-type specific construction of design hydrographs. However, they depend on observed runoff time series and are not directly applicable in ungauged catchments where such series are not available. To obtain reliable flood estimates, there is a need for an approach that allows for the consideration of process variability in the construction of synthetic design hydrographs in ungauged catchments. In this study, we therefore propose an approach that combines a bivariate index flood approach with event-type specific synthetic design hydrograph construction. First, regions of similar flood reactivity are delineated and a classification rule that enables the assignment of ungauged catchments to one of these reactivity regions is established. Second, event-type specific synthetic design hydrographs are constructed using the pooled data divided by event type from the corresponding reactivity region in a bivariate index flood procedure. The approach was tested and validated on a dataset of 163 Swiss catchments. The results indicated that 1) random forest is a suitable classification model for the assignment of an ungauged catchment to one of the reactivity regions, 2) the combination of a bivariate index flood approach and event-type specific synthetic design hydrograph construction enables the consideration of event types in ungauged catchments, and 3) the use of probabilistic class memberships in regional synthetic design hydrograph construction helps to alleviate the problem of misclassification. Event-type specific synthetic design hydrograph sets enable the inclusion of process variability into design flood estimation and can be used as a compromise between single best estimate synthetic design hydrographs and continuous simulation studies.
Climate impact studies regarding floods usually focus on peak discharges and a bivariate assessment of peak discharges and hydrograph volumes is not commonly included. A joint consideration of peak discharges and hydrograph volumes, however, is crucial when assessing flood risks for current and future climate conditions. Here, we present a methodology to develop synthetic design hydrographs for future climate conditions that jointly consider peak discharges and hydrograph volumes. First, change factors are derived based on a regional climate model and are applied to observed precipitation and temperature time series. Second, the modified time series are fed into a calibrated hydrological model to simulate runoff time series for future conditions. Third, these time series are used to construct synthetic design hydrographs. The bivariate flood frequency analysis used in the construction of synthetic design hydrographs takes into account the dependence between peak discharges and hydrograph volumes, and represents the shape of the hydrograph. The latter is modeled using a probability density function while the dependence between the design variables peak discharge and hydrograph volume is modeled using a copula. We applied this approach to a set of eight mountainous catchments in Switzerland to construct catchment-specific and season-specific design hydrographs for a control and three scenario climates. Our work demonstrates that projected climate changes have an impact not only on peak discharges but also on hydrograph volumes and on hydrograph shapes both at an annual and at a seasonal scale. These changes are not necessarily proportional which implies that climate impact assessments on future floods should consider more flood characteristics than just flood peaks.
The higher mid-latitudes of the Northern Hemisphere are particularly sensitive to climate change as small differences in temperature determine frozen ground status, precipitation phase, and the magnitude and timing of snow accumulation and melt. An international inter-catchment comparison program, North-Watch, seeks to improve our understanding of the sensitivity of northern catchments to climate change by examining their hydrological and biogeochemical responses. The catchments are located in Sweden (Krycklan), Scotland (Mharcaidh, Girnock and Strontian), the United States (Sleepers River, Hubbard Brook and HJ Andrews) and Canada (Catamaran, Dorset and Wolf Creek). This briefing presents the initial stage of the North-Watch program, which focuses on how these catchments collect, store and release water and identify 'types' of hydro-climatic catchment response. At most sites, a 10-year data of daily precipitation, discharge and temperature were compiled and evaporation and storage were calculated. Inter-annual and seasonal patterns of hydrological processes were assessed via normalized fluxes and standard flow metrics. At the annual-scale, relations between temperature, precipitation and discharge were compared, highlighting the role of seasonality, wetness and snow/frozen ground. The seasonal pattern and synchronicity of fluxes at the monthly scale provided insight into system memory and the role of storage. We identified types of catchments that rapidly translate precipitation into runoff and others that more readily store water for delayed release. Synchronicity and variance of rainfall-runoff patterns were characterized by the coefficient of variation (cv) of monthly fluxes and correlation coefficients. Principal component analysis (PCA) revealed clustering among like catchments in terms of functioning, largely controlled by two components that (i) reflect temperature and precipitation gradients and the correlation of monthly precipitation and discharge and (ii) the seasonality of precipitation and storage. By advancing the ecological concepts of resistance and resilience for catchment functioning, results provided a conceptual framework for understanding susceptibility to hydrological change across northern catchments. Copyright (C) 2010 John Wiley & Sons, Ltd.
Chemical weathering of rocks or sediments is extremely important for the generation of soils, for the evolution of landscape, and as a main source of inorganic nutrients for plant growth and therefore for life. Temporal trends in weathering mechanisms, plant succession and nutrients availability in cold environments can be successfully studied in soil chronosequences along a glacier forefield. In the present paper, this was carried out in the pro-glacial area of Morteratsch. Different forms of phosphorous in the soil, stream and spring water chemistry were investigated. Apatite constitutes the main source of P, but it occurs only as a minor accessory mineral phase in the granitic/gneiss parent material. The identification of apatite was performed using SEM-EDX and cathodoluminescence. Water chemistry data indicated some calcite dissolution at the earliest phase of exposure, pyrite and - on older surfaces increasingly - feldspar weathering. Apatite also seemed to contribute to Ca which is leached from the soils. The concentrations of dissolved P in the stream and spring waters were, however, extremely low (only a few μg P/l). In the topsoil, the total stocks of P showed a slight decrease with time. Losses were rather difficult to detect even though the water fluxes through the soils and discharges are relatively high. Soil organic P is almost identical to the EDTA-extractable fraction. In an 11.5. ky-old soil outside the glacier forefield the concentration and proportions of organic P, EDTA-extractable P and inorganic P forms did not differ that much from the oldest soils (max. 150. years) of the glacier forefield. In the bulk soil, about 78% of total P was transformed into an organic form (40% already after 150. years) and, in the fine earth, about 81% (40-70% after about 150. years of soil evolution). Thus the P transformation reactions are shown to be very rapid, occur predominantly in the early phase of soil formation, and could be best described by an exponential decay model. © 2012 Elsevier B.V.
Post-processing the output of different rainfall-runoff models allows one to pool strengths of each model to produce more reliable predictions. As a new approach in the frame of the "Prediction in Ungauged Basins" initiative, this study investigates the geographical transferability of different parameter sets and data-fusion methods which were applied to 5 different rainfall-runoff models for a low-land catchment in Central Sweden. After usual calibration, we adopted a proxy-basin validation approach between two similar but non-nested sub-catchments in order to simulate ungauged conditions. Many model combinations outperformed the best single model predictions with improvements of efficiencies from 0.70 for the best single model predictions to 0.77 for the best ensemble predictions. However no "best" data-fusion method could be determined as similar performances were obtained with different merging schemes. In general, poorer model performance, i.e. lower efficiency, was less likely to occur for ensembles which included more individual models.
Model predictions of biogeochemical fluxes at the landscape scale are highly uncertain, both with respect to stochastic (parameter) and structural uncertainty. In this study 5 different models (LASCAM, LASCAM-S, a selfdeveloped tool, SWAT and HBV-N-D) designed to simulate hydrological fluxes as well as mobilisation and transport of one or several nitrogen species were applied to the mesoscale River Fyris catchment in mid-eastern Sweden. Hydrological calibration against 5 years of recorded daily discharge at two stations gave highly variable results with Nash-Sutcliffe Efficiency (NSE) ranging between 0.48 and 0.83. Using the calibrated hydrological parameter sets, the parameter uncertainty linked to the nitrogen parameters was explored in order to cover the range of possible predictions of exported loads for 3 nitrogen species: nitrate (NO3), ammonium (NH4) and total nitrogen (Tot-N). For each model and each nitrogen species, predictions were ranked in two different ways according to the performance indicated by two different goodness-of-fit measures: the coefficient of determination R2 and the root mean square error RMSE. A total of 2160 deterministic Single Model Ensembles (SME) was generated using an increasing number of members (from the 2 best to the 10 best single predictions). Finally the best SME for each model, nitrogen species and discharge station were selected and merged into 330 different Multi-Model Ensembles (MME). The evolution of changes in R2 and RMSE was used as a performance descriptor of the ensemble procedure. In each studied case, numerous ensemble merging schemes were identified which outperformed any of their members. Improvement rates were generally higher when worse members were introduced. The highest improvements were achieved for the nitrogen SMEs compiled with multiple linear regression models with R2 selected members, which resulted in the RMSE decreasing by up to 90%. © Author(s) 2010.
The assessment of snow, glacier, and rainfall runoff contribution to discharge in mountain streams is of major importance for an adequate water resource management. Such contributions can be estimated via hydrological models, provided that the modeling adequately accounts for snow and glacier melt, as well as rainfall runoff. We present a multiple data set calibration approach to estimate runoff composition using hydrological models with three levels of complexity. For this purpose, the code of the conceptual runoff model HBV-light was enhanced to allow calibration and validation of simulations against glacier mass balances, satellite-derived snow cover area and measured discharge. Three levels of complexity of the model were applied to glacierized catchments in Switzerland, ranging from 39 to 103 km(2). The results indicate that all three observational data sets are reproduced adequately by the model, allowing an accurate estimation of the runoff composition in the three mountain streams. However, calibration against only runoff leads to unrealistic snow and glacier melt rates. Based on these results, we recommend using all three observational data sets in order to constrain model parameters and compute snow, glacier, and rain contributions. Finally, based on the comparison of model performance of different complexities, we postulate that the availability and use of different data sets to calibrate hydrological models might be more important than model complexity to achieve realistic estimations of runoff composition.
Mountainous headwaters consist of different landscape units including forests, meadows and wetlands. In these headwaters it is unclear which landscape units contribute what percentage to baseflow. In this study, we analysed spatiotemporal differences in baseflow isotope and hydrochemistry to identify catchment-scale runoff contribution. Three baseflow snapshot sampling campaigns were performed in the Swiss pre-alpine headwater catchment of the Zckentobel (4.25 km(2)) and six of its adjacent subcatchments. The spatial and temporal variability of delta H-2, Ca, DOC, AT, pH, SO4, Mg and H4SiO4 of streamflow, groundwater and spring water samples was analysed and related to catchment area and wetland percentage using bivariate and multivariate methods. Our study found that in the six subcatchments, with variable arrangements of landscape units, the inter-and intra catchment variability of isotopic and hydrochemical compositions was small and generally not significant. Stream samples were distinctly different from shallow groundwater. An upper spring zone located near the water divide above 1,400m and a larger wetland were identified by their distinct spatial isotopic and hydrochemical composition. The upstream wetland percentage was not correlated to the hydrochemical streamflow composition, suggesting that wetlands were less connected and act as passive features with a negligible contribution to baseflow runoff. The isotopic and hydrochemical composition of baseflow changed slightly from the upper spring zone towards the subcatchment outlets and corresponded to the signature of deep groundwater. Our results confirm the need and benefits of spatially distributed snapshot sampling to derive process understanding of heterogeneous headwaters during baseflow.
Precipitation and catchment characteristics of mountainous headwaters can vary largely within short distances. It remains unclear how these two factors determine the contribution of event water and pre-event water to stormflow. We investigated this in five neighboring headwaters with high annual precipitation amounts (> 2,000 mm y(-1)) in a steep pre-alpine region in Switzerland. Rainfall and streamwater of 13 different rainstorms were sampled (P: 5 mm intervals, Q: 12 to 51 samples per events) to perform a two-component isotope hydrograph separation. Pre-event water contributions based on delta O-18 or delta H-2 computation were similar. The pre-event water contributions of headwaters depended largely on rainfall (amount and intensity) and varied more between events than between catchments, despite clear differences in land cover between the catchments. Furthermore, antecedent wetness was not found to control pre-event water contribution. With increasing rainfall amount, the proportion of rainfall in runoff increased and changed from pre-event to event water dominated. The variable rainfall amount and small active storage (organic soil horizon, 20-50 cm) resulted in a threshold in the upper soil horizon with subsequently more variable pre-event water contribution. Our results show the necessity of sampling in different headwaters and events to better understand controlling factors in runoff generation.
Isotope hydrograph separation (IHS) is a valuable tool to study runoff generation processes. To perform an IHS, samples of baseflow (pre-event water) and streamflow are taken at the catchment outlet. For rainfall (event water) either a bulk sample is collected or it is sampled sequentially during the event. For small headwater catchment studies, event water samples are usually taken at only one sampling location in or near the catchment because the spatial variability in the isotopic composition of rainfall is assumed to be small. However, few studies have tested this assumption. In this study, we investigated the spatiotemporal variability in the isotopic composition of rainfall and its effects on IHS results using detailed measurements from a small pre-alpine headwater catchment in Switzerland. Rainfall was sampled sequentially at eight locations across the 4.3 km(2) Zwackentobel catchment and stream water was collected in three subcatchments (0.15, 0.23, and 0.70 km(2)) during ten events. The spatial variability in rainfall amount, average and maximum rainfall intensity and the isotopic composition of rainfall was different for each event. There was no significant relation between the isotopic composition of rainfall and total rainfall amount, rainfall intensity or elevation. For eight of the ten studied events the temporal variability in the isotopic composition of rainfall was larger than the spatial variability in the rainfall isotopic composition. The isotope hydrograph separation results, using only one rain sampler, varied considerably depending on which rain sampler was used to represent the isotopic composition of event water. The calculated minimum pre-event water contributions differed up to 60%. The differences were particularly large for events with a large spatial variability in the isotopic composition of rainfall and a small difference between the event and pre-event water isotopic composition. Our results demonstrate that even in small catchments the spatial variability in the rainfall isotopic composition can be significant and has to be considered for IHS studies. Using data from only one rain sampler can result in significant errors in the estimated pre-event water contributions to streamflow.
Forty-five years (1960-2004) of hydrological data from 12 watersheds in the Abbay Basin, Ethiopia, were tested for possible trends over the entire time series and differences in medians (step-wise changes) between three sub-periods. The classification of the sub-periods was based on the major political changes in 1975 and 1991. Variables investigated were rainfall (P), total flow (Q(t)), high flow (Q(h)), low flow (Q(1)), low flow index (LFI) and run-off coefficient (C). Data were checked for outliers, errors and homogeneity. Trend was tested after serial and cross-correlation tests. The data for each variable were serially uncorrelated from 1 to 10 lag years. There were five globally significant trends out of 50 test cases and 36 significant step-wise changes out of 180 tests. The majority of the significant changes were watershed specific. Run-off coefficient was the single variable showing a consistently increasing trend and stood for ca. 25 % of the total significant trends and step-wise changes. Half of these changes occurred after 1991. We concluded that despite the land use policy changes in 1975 and 1991, as well as the long-term soil degradation, the hydrological regime was quite stable over the 45-year period, with the exception of an increase in the run-off coefficient in the latter part of the run-off record in some watersheds.
Land cover changes can have significant impacts on hydrological regime. The objective of this study was to detect possible hydrological changes of four watersheds in the Blue Nile Basin using a model-based method for hydrological change detection. The four watersheds, Birr, Upper-Didesa, Gilgel Abbay, and Koga range in size from 260 to 1800 km(2). The changes were assessed based on model parameters, model residuals, and in the overall function of the watersheds in transferring rainfall into runoff. The entire time series (1960-2004) was divided into three periods based on political and land management policy changes. A conceptual rainfall-runoff model, the HBV (Hydrologiska Byrans Vattenbalansavdelning) model, was used for the analysis, and suitable parameter sets for each period were found based on a Monte Carlo approach. The values of six out of nine parameters changed significantly between the periods. Model residuals also showed significant changes between the three periods in three of the four watersheds. On the other hand, the overall functioning of the watersheds in processing rainfall to runoff changed little. So even though the individual parameters and model residuals were changing, the integrated functioning of the watersheds showed minimal changes. This study demonstrated the value of using different approaches for detecting hydrological change and highlighted the sensitivity of the outcome to the applied modeling and statistical methods.
Flood early warning systems play a major role in the disaster risk reduction paradigm as cost-effective methods to mitigate flood disaster damage. The connections and feedbacks between the hydrological and social spheres of early warning systems are increasingly being considered as key aspects for successful flood mitigation. The behavior of the public and first responders during flood situations, determined by their preparedness, is heavily influenced by many behavioral traits such as perceived benefits, risk awareness, or even denial. In this study, we use the recency of flood experiences as a proxy for social preparedness to assess its impact on the efficiency of flood early warning systems through a simple stylized model and implemented this model using a simple mathematical description. The main findings, which are based on synthetic data, point to the importance of social preparedness for flood loss mitigation, especially in circumstances where the technical forecasting and warning capabilities are limited. Furthermore, we found that efforts to promote and preserve social preparedness may help to reduce disaster-induced losses by almost one half. The findings provide important insights into the role of social preparedness that may help guide decision-making in the field of flood early warning systems.
Data availability is important for virtually any purpose in hydrology. While some parts of the world continue to be under-monitored, other areas are experiencing an increased availability of high-resolution data. The use of the highest available resolution has always been preferred and many efforts have been made to maximize the information content of data and thus improve its predictive power and reduce the costs of maintenance of hydrometric sensor networks. In the light of ever-increasing data resolution, however, it is important to assess the added value of using the highest resolution available. In this study we present an assessment of the relative importance of hydro-meteorological data resolution for hydrological modelling. We used a case study with high-resolution data availability to investigate the influence of using models calibrated with different levels of spatially aggregated meteorological input data to estimate streamflow for different periods and at different locations. We found site specific variations, but model parameterizations calibrated using sub-catchment specific meteorological input data tended to produce better streamflow estimates, with model efficiency values being up to 0.35 efficiency units higher than those calibrated with catchment averaged meteorological data. We also found that basin characteristics other than catchment area have little effect on the performance of model parameterizations applied in different locations than the calibration site. Finally, we found that using an increased number of discharge data locations has a larger impact on model calibration efficiency than using spatially specific meteorological data. The results of this study contribute to improve the knowledge on assessing data needs for water management in terms of adequate data type and level of spatial aggregation.
Accurate estimation of precipitation and its spatial variability is crucial for reliable discharge simulations. Although radar and satellite based techniques are becoming increasingly widespread, quantitative precipitation estimates based on point rain gauge measurement interpolation are, and will continue to be in the foreseeable future, widely used. However, the ability to infer spatially distributed data from point measurements is strongly dependent on the number, location and reliability of measurement stations.
In this study we quantitatively investigated the effect of rain gauge network configurations on the spatial interpolation by using the operational hydrometeorological sensor network in the Thur river basin in north-eastern Switzerland as a test case. Spatial precipitation based on a combination of radar and rain gauge data provided by MeteoSwiss was assumed to represent the true precipitation values against which the precipitation interpolation from the sensor network was evaluated. The performance using scenarios with both increased and decreased station density were explored. The catchment-average interpolation error indices significantly improve up to a density of 24 rain gauges per 1000 km2, beyond which improvements were negligible. However, a reduced rain gauge density in the higher parts of the catchment resulted in a noticeable decline of the performance indices. An evaluation based on precipitation intensity thresholds indicated a decreasing performance for higher precipitation intensities. The results of this study emphasise the benefits of dense and adequately distributed rain gauge networks.
Groundwater flowing from hillslopes through riparian (near-stream) soils often undergoes chemical transformations that can substantially influence stream water chemistry. We used landscape analysis to predict total organic carbon (TOC) concentration profiles and groundwater levels measured in the riparian zone (RZ) of a 67 km2 catchment in Sweden. TOC exported laterally from 13 riparian soil profiles was then estimated based on the riparian flow-concentration integration model (RIM). Much of the observed spatial variability of riparian TOC concentrations in this system could be predicted from groundwater levels and the topographic wetness index (TWI). Organic riparian peat soils in forested areas emerged as hotspots exporting large amounts of TOC. These TOC fluxes were subject to considerable temporal variations caused by a combination of variable flow conditions and changing soil water TOC concentrations. Mineral riparian gley soils, on the other hand, were related to rather small TOC export rates and were characterized by relatively time-invariant TOC concentration profiles. Organic and mineral soils in RZs constitute a heterogeneous landscape mosaic that potentially controls much of the spatial variability of stream water TOC. We developed an empirical regression model based on the TWI to move beyond the plot scale and to predict spatially variable riparian TOC concentration profiles for RZs underlain by glacial till.
Topography is an important control on hydrological processes. One approach to quantify this control is the topographic ln(a/tanbeta) index. This index has become widely used in hydrology, but it utilizes a relatively small portion of the information contained in a digital elevation model (DEM). One potentially important feature not considered in the implementation of the ln(a/tanb) index is the enhancement or impedance of local drainage by downslope topography. This effect could be important in some terrain for controlling hydraulic gradients. We propose a new way of estimating the hydraulic gradient by calculating how far downhill (L-d, [m]) a parcel of water must move in order to lose a certain amount of potential energy (d, [m]). Expressed as a gradient, tanalpha(d) = d/ L-d, values tend to be lower on concave slope profiles and higher on convex slope profiles compared with the local gradient, tanbeta. We argue that the parameter d controls the deviation of hydraulic gradient from surface slope. While we determine this subjectively, landscape relief, DEM resolution, and soil transmissivity should be considered at the selection of d. We found the downslope index values to be less affected by changes in DEM resolution than local slope. Three applications are presented where the new index is shown to be useful for hydrological, geomorphological, and biogeochemical applications.
It is expected that an increasing proportion of the precipitation will fall as rain in alpine catchments in the future. Consequently, snow storage is expected to decrease, which, together with changes in snowmelt rates and timing, might cause reductions in spring and summer low flows. The objectives of this study were (1) to simulate the effect of changing snow storage on low flows during the warm seasons and (2) to relate drought sensitivity to the simulated snow storage changes at different elevations. The Swiss Climate Change Scenarios 2011 data set was used to derive future changes in air temperature and precipitation. A typical bucket-type catchment model, HBV-light, was applied to 14 mountain catchments in Switzerland to simulate streamflow and snow in the reference period and three future periods. The largest relative decrease in annual maximum SWE was simulated for elevations below 2,200 m a.s.l. (60-75% for the period 2070-2099) and the snowmelt season shifted by up to 4 weeks earlier. The relative decrease in spring and summer minimum runoff that was caused by the relative decrease in maximum SWE (i.e., elasticity), reached 40-90% in most of catchments for the reference period and decreased for the future periods. This decreasing elasticity indicated that the effect of snow on summer low flows is reduced in the future. The fraction of snowmelt runoff in summer decreased by more than 50% at the highest elevations and almost disappeared at the lowest elevations. This might have large implications on water availability during the summer.
Winter snow accumulation obviously has an effect on the following catchment runoff. The question is, however, how long this effect lasts and how important it is compared to rainfall inputs. Here we investigate the relative importance of snow accumulation on one critical aspect of runoff, namely the summer low flow. This is especially relevant as the expected increase of air temperature might result in decreased snow storage. A decrease of snow will affect soil and ground-water storages during spring and might cause low streamflow values in the subsequent warm season. To understand these potential climate change impacts, a better evaluation of the effects of inter-annual variations in snow accumulation on summer low flow under current conditions is central. The objective in this study was (1) to quantify how long snowmelt affects runoff after melt-out and (2) to estimate the sensitivity of catchments with different elevation ranges to changes in snowpack. To find suitable predictors of summer low flow we used long time series from 14 Alpine and pre-Alpine catchments in Switzerland and computed different variables quantifying winter and spring snow conditions. In general, the results indicated that maximum winter snow water equivalent (SWE) influenced summer low flow, but could expectedly only partly explain the observed inter-annual variations. On average, a decrease of maximum SWE by 10% caused a decrease of minimum discharge in July by 6-9% in catchments higher than 2000 ma.s.l. This effect was smaller in middle-and lower-elevation catchments with a decrease of minimum discharge by 2-5% per 10% decrease of maxi-mum SWE. For higher-and middle-elevation catchments and years with below-average SWE maximum, the minimum discharge in July decreased to 70-90% of its normal level. Additionally, a reduction in SWE resulted in earlier low-flow occurrence in some cases. One other important factor was the precipitation between maximum SWE and summer low flow. When only dry preceding conditions in this period were considered, the importance of maximum SWE as a predictor of low flows increased. We assessed the sensitivity of individual catchments to the change of maximum SWE using the non-parametric Theil-Sen approach as well as an elasticity index. Both sensitivity indicators increased with increasing mean catchment elevation, indicating a higher sensitivity of summer low flow to snow accumulation in Alpine catchments compared to lower-elevation pre-Alpine catchments.
Streamflow recession analysis provides valuable insights into catchment functioning that can be related to runoff generation, storage retention and baseflow dynamics. As an integrated characteristic, recession analysis is particularly useful in catchment comparison studies to help explain drivers of spatial and temporal variability in hydrological behavior. Here, five years of hourly streamflow data from 14, partly nested, catchments within a 68 km(2) boreal forest landscape in Northern Sweden were used to explore spatiotemporal variation in hydrological processes through recession analysis. The aim of this study was to better understand spatial variation in runoff generation and storage-discharge dynamics across the landscape, as well as the relation to landscape properties. Due to high collinearity between variables, partial least square regression was used to quantify the associations between recession characteristics and catchment properties, as well as to identify key variables controlling recession behavior. We analyzed recession characteristics using both an aggregated approach including all recession data and individual recession events. The analyses based on individual recession events, indicated that catchment topography, quantified by indices such as mean slope or elevation above the stream network, is a primary control on the recession behavior during relatively high flows, whereas catchment area gains importance when flows are relatively low. The proportion of sediment and deep soils also controlled recession behavior. Furthermore, we found that recession characteristics are influenced by both evapotranspiration (ET) and proxies of antecedent catchment storage, but that the patterns were different depending on catchment properties. ET was less influential in catchments with deeper soils and larger catchment area. Shifts in recession rates were primarily related to variation in storage, with faster streamflow recessions occurring during periods with low storage. The results demonstrate the influence of catchment properties on recession behavior, and we found great value in analyzing individual recession events for an increased understanding of spatial and temporal recession characteristics. When recession properties were lumped together, the relationships to catchment characteristics were obscured. This indicates the value of more detailed analyses, at least under the strongly seasonal hydroclimatic conditions of this site.
Nearby catchments in the same landscape are often assumed to have similar specific discharge (runoff per unit catchment area). Five years of streamflow from 14 nested catchments in a 68km(2) landscape was used to test this assumption, with the hypothesis that the spatial variability in specific discharge is smaller than the uncertainties in the measurement. The median spatial variability of specific discharge, defined as subcatchment deviation from the catchment outlet, was 33% at the daily scale. This declined to 24% at a monthly scale and 19% at an annual scale. These specific discharge differences are on the same order of magnitude as predicted for major land-use conversions or a century of climate change. Spatial variability remained when considering uncertainties in specific discharge, and systematic seasonal patterns in specific discharge variation further provide confidence that these differences are more than just errors in the analysis of catchment area, rainfall variability or gauging. Assuming similar specific discharge in nearby catchments can thus lead to spurious conclusions about the effects of disturbance on hydrological and biogeochemical processes.
Isotope hydrograph separation is a powerful tool to investigate catchment functioning. In most hydrograph separation studies, a pre-event baseflow sample is used to represent the pre-event water, and thus, baseflow is assumed to be a mixture of all the water that is stored in the catchment. However, baseflow may not be representative of all water stored in the catchment because some sources may not contribute to baseflow. This is problematic when the isotopic composition of the sources is highly variable. We quantified the effects of spatial variability in the shallow groundwater isotopic composition on pre-event water characterization and hydrograph separation results. We compared the composition of groundwater sampled at 38 wells in a 0.2 km(2)pre-alpine catchment with stream water sampled before, during, and after three rainfall events. We estimated the number of groundwater samples needed to characterize the average groundwater composition in the catchment and its spatial variability and compared the results of two-component hydrograph separations for different ways to characterize the pre-event water. We found that differences in the calculated pre-event water fractions and uncertainties were large and depended on which and how many samples were used to characterize the pre-event water composition. Analyses based on a limited number of groundwater samples likely underestimate the real uncertainty and can give a false impression of accuracy. Our results highlight the importance of representing the variability in the pre-event water composition when applying hydrograph separation analyses. We therefore recommend sampling pre-event water at multiple locations or estimating the variability based on literature values.
Hydrological modelling of glacierized catchments is challenging because internal inconsistencies might be hidden due to ice melt which represents an additional source of water. This is even more significant if there are no data available to evaluate model simulations, as is often the case in remote areas. On the other hand, these glacierized catchments are important source regions for water, and detailed knowledge of water availability is a prerequisite for good resource management strategies. An important question is how useful a limited amount of data might be for model applications. Therefore, in this study the predictive power of limited discharge measurements, mass balance observations and the combination of both was analyzed by means of Monte Carlo analyses with multi-criteria model performance evaluation. Ensembles of 100 parameter sets were selected by evaluating the simulations based on a limited number of discharge measurements, glacier mass balance, and the combination of discharge and mass balance observations. Then the ensemble simulation of runoff was evaluated for the entire runoff series. The result indicated that a single annual glacier mass balance observation contained useful information to constrain hydrological models. Combining mass balance observations with a few discharge data improved the internal consistency and significantly reduced the uncertainties compared to parameter set selections based on discharge measurements alone. To obtain good ensemble predictions, information on discharge was required for at least 3 days during the melting season. This demonstrated that the timing of runoff measurements is important for the information contained in these data. (C) 2010 Elsevier B.V. All rights reserved.
Freshwater ecosystems in the mid- to upper-latitudes of the northern hemisphere are particularly vulnerable to the impact of climate change as slight changes in air temperature can alter the form, timing, and magnitude of precipitation and consequent influence of snowmelt on streamflow dynamics. Here, we examine the effects of hydro-climate, flow regime, and hydrochemistry on Plecoptera (stonefly) alpha (alpha) diversity and distribution in northern freshwater ecosystems. We characterized the hydroclimatic regime of seven catchments spanning a climatic gradient across the northern temperate region and compared them with estimates of Plecoptera genera richness. By a space-for-time substitution, we assessed how warmer temperatures and altered flow regimes may influence Plecoptera alpha diversity and composition at the genus level. Our results show wide hydroclimatic variability among sites, including differences in temporal streamflow dynamics and temperature response. Principal component analysis showed that Plecoptera genera richness was positively correlated with catchment relief (m), mean and median annual air temperature (A degrees C), and streamflow. These results provide a preliminary insight into how hydroclimatic change, particularly in terms of increased air temperature and altered streamflow regimes, may create future conditions more favorable to some Plecopteras in northern catchments.
There is no scientific consensus about how dissolved organic carbon (DOC) in surface waters is regulated. Here we combine recent literature data from 49 catchments with detailed stream and catchment process information from nine well established research catchments at mid- to high latitudes to examine the question of how climate controls stream water DOC. We show for the first time that mean annual temperature (MAT) in the range from -3 degrees to +10 degrees C has a strong control over the regional stream water DOC concentration in catchments, with highest concentrations in areas ranging between 0 degrees and +3 degrees C MAT. Although relatively large deviations from this model occur for individual streams, catchment topography appears to explain much of this divergence. These findings suggest that the long-term trajectory of stream water DOC response to climate change may be more predictable than previously thought. Citation: Laudon, H., J. Buttle, S. K. Carey, J. McDonnell, K. McGuire, J. Seibert, J. Shanley, C. Soulsby, and D. Tetzlaff (2012), Cross-regional prediction of long-term trajectory of stream water DOC response to climate change, Geophys. Res. Lett., 39, L18404, doi: 10.1029/2012GL053033.
Evaporation of water intercepted by vegetation represents an important (sometimes major) part of evapotranspiration in temperate regions. Interception evaporation is an important process where insufficient measurement techniques hamper progress in knowledge and modeling. An ideal technique to study the interception evaporation process should monitor intercepted mass (and its vertical distribution) and interception loss with high accuracy (0.1 mm) and time resolution (1 min), and give correct area estimates. The method should be inexpensive, require minor supervision during extended periods, and work in dense forests. Net precipitation techniques, in which interception evaporation is determined from the difference between gross precipitation (measured with funnels) and throughfall (measured with funnels, troughs, or plastic sheet net-rainfall gauges) fulfill many of the requirements but usually have a too-low accuracy and time resolution for process studies. Precipitation measurements are normally affected by distortion of the wind field around gauges as well as by adhesive and evaporative losses. Throughfall measurements with precipitation funnels, troughs, or plastic sheet net-rainfall gauges, manually emptied or combined with tipping buckets, usually have too-low accuracy and time resolution for process studies and are impaired by adhesive losses. A new loadcell-based system to determine interception evaporation from gross and net precipitation is presented. A weighing gauge with minimal wind loss is used for precipitation, and weighing troughs are used for throughfall measurements. The weighing troughs minimize adhesive-loss errors and react instantaneously. Preliminary results with the method confirm that it can be used for process studies with a high accuracy (0.1 mm) and a high time resolution (1 min).
The riparian zone is a narrow corridor where hillslopes (and their associated hydrobiogeochemical processes) interface with the river system. As such, the riparian zone serves as the last piece of landscape with which water interacts as it transitions from being water flowing primarily through the landscape (i.e., shallow groundwater) to water flowing primarily on the landscape (i.e., stream water). This study investigates the spatiotemporal variability in riparian-zone soil water total organic carbon (TOC) and its relation to the shallow groundwater table using observations from the recently instrumented riparian observatory in the Krycklan catchment study area located in boreal northern Sweden. In general, there is a decrease in TOC concentration with depth down through the soil profile. The rate of this decrease was variable among the six monthly samplings used in this study. The spatial variability of soil water TOC in the riparian zone was connected to the spatial variability of the shallow groundwater levels. This demonstrated the importance of the temporal variation of flow pathways and the mixing of waters from different sources of TOC moving into and through the riparian zone. The coupled variation of the hydrologic and biogeochemical systems raised questions about the ability of simple lumped approaches to accurately predict how in-stream TOC concentrations will change with climate and/or land use. The integrated sampling approach in the riparian observatory covers both hydrologic and biogeochemical aspects of soil water TOC and provides a basis for development and testing of distributed, physically based transport models.
Interpolation of point measurements using geostatistical techniques such as kriging can be used to estimate values at non-sampled locations in space. Traditional geostatistics are based on the spatial autocorrelation concept that nearby things are more related than distant things. In this study, additional information was used to modify the traditional Euclidean concept of distance into an adjusted distance metric that incorporates similarity in terms of quantifiable landscape characteristics such as topography or land use. This new approach was tested by interpolating soil moisture content, pH and carbon-tonitrogen (C:N) ratio measured in both the mineral and the organic soil layers at a field site in central Sweden. Semivariograms were created using both the traditional distance metrics and the proposed adjusted distance metrics to carry out ordinary kriging (OK) interpolations between sampling points. In addition, kriging with external drift (KED) was used to interpolate soil properties to evaluate the ability of the adjusted distance metric to incorporate secondary data into interpolations. The new adjusted distance metric typically lowered the nugget associated with the semivariogram, thereby better representing small-scale variability in the measured data compared to semivariograms based on the traditional distance metric. The pattern of the resulting kriging interpolations using KED and OK based on the adjusted distance metric were similar because they represented secondary data and, thus, enhanced small-scale variability compared to traditional distance OK. This created interpolations that agreed better with what is expected for the real-world spatial variation of the measured properties. Based on cross-validation error, OK interpolations using the adjusted distance metric better fit observed data than either OK interpolations using traditional distance or KED. © 2010 Taylor & Francis.
Catchment-scale transit times for water are increasingly being recognized as an important control on geochemical processes. In this study, snowmelt water mean transit times (MTTs) were estimated for the 15 Krycklan research catchments in northern boreal Sweden. The snowmelt water MTTs were assumed to be representative of the catchment-scale hydrologic response during the spring thaw period and, as such, may be considered to be a component of the catchment's overall MTT. These snowmelt water MTTs were empirically related to catchment characteristics and landscape structure represented by using different indices of soil cover, topography and catchment similarity. Mire wetlands were shown to be significantly correlated to snowmelt MTTs for the studied catchments. In these wetlands, shallow ice layers form that have been shown to serve as impervious boundaries to vertical infiltration during snowmelt periods and, thus, alter the flow pathways of water in the landscape. Using a simple thought experiment, we could estimate the potential effect of thawing of ice layers on snowmelt hydrologic response using the empirical relationship between landscape structure (represented using a catchment-scale Pe number) and hydrologic response. The result of this thought experiment was that there could be a potential increase of 20-45% in catchment snowmelt water MTTs for the Krycklan experimental catchments. It is therefore possible that climatic changes present competing influences on the hydrologic response of northern boreal catchments that need to be considered. For example, MTTs may tend to decrease during some times of the year due to an acceleration in the hydrologic cycle, while they tend to increase MTTs during other times of the year due to shifts in hydrologic flow pathways. The balance between the competing influences on a catchment's MTT has consequences on climatic feedbacks as it could influence hydrological and biogeochemical cycles at the catchment scale for northern latitude boreal catchments. Copyright (C) 2010 John Wiley & Sons, Ltd.
Specific discharge variations within a mesoscale catchment were studied on the basis of three synoptic sampling campaigns. These were conducted during stable flow conditions within the Krycklan catchment study area in northern Sweden. During each campaign, about 80 individual locations were measured for discharge draining from catchment areas ranging between 0.12 and 67 km(2). These discharge samplings allowed for the comparison between years within a given season (September 2005 versus September 2008) and between seasons within a given year (May 2008 versus September 2008) of specific discharge across this boreal landscape. There was considerable variability in specific discharge across this landscape. The ratio of the interquartile range (IQR) defined as the difference between the 75th and 25th percentiles of the specific discharges to the median of the specific discharges ranged from 37% to 43%. Factor analysis was used to explore potential relations between landscape characteristics and the specific discharge observed for 55 of the individual locations that were measured in all three synoptic sampling campaigns. Percentage wet area (i.e., wetlands, mires, and lakes) and elevation were found to be directly related to the specific discharge during the drier September 2008 sampling while potential annual evaporation was found to be inversely related. There was less of a relationship determined during the wetter post spring flood May 2008 sampling and the late summer rewetted September 2005 sampling. These results indicate the ability of forests to "dry out" parts of the catchment over the summer months while wetlands "keep wet" other parts. To demonstrate the biogeochemical implications of such spatiotemporal variations in specific discharge, we estimate dissolved organic carbon (DOC) exports with available data for the May 2008 and September 2008 samplings using both the spatially variable observed specific discharges and the spatially constant catchment average values. The average absolute difference in DOC export for the various subcatchments between using a variable and using a constant specific discharge was 28% for the May 2008 sampling and 20% for the September 2008 sampling.
Accurate stream discharge measurements are important for many hydrological studies. In remote locations, however, it is often difficult to obtain stream flow information because of the difficulty in making the discharge measurements necessary to define stage-discharge relationships (rating curves). This study investigates the feasibility of defining rating curves by using a fluid mechanics-based model constrained with topographic data from an airborne LiDAR scanning. The study was carried out for an 8m-wide channel in the boreal landscape of northern Sweden. LiDAR data were used to define channel geometry above a low flow water surface along the 90-m surveyed reach. The channel topography below the water surface was estimated using the simple assumption of a flat streambed. The roughness for the modelled reach was back calculated from a single measurment of discharge. The topographic and roughness information was then used to model a rating curve. To isolate the potential influence of the flat bed assumption, a hybrid model rating curve was developed on the basis of data combined from the LiDAR scan and a detailed ground survey. Whereas this hybrid model rating curve was in agreement with the direct measurements of discharge, the LiDAR model rating curve was equally in agreement with the medium and high flow measurements based on confidence intervals calculated from the direct measurements. The discrepancy between the LiDAR model rating curve and the low flow measurements was likely due to reduced roughness associated with unresolved submerged bed topography. Scanning during periods of low flow can help minimize this deficiency. These results suggest that combined ground surveys and LiDAR scans or multifrequency LiDAR scans that see below the water surface (bathymetric LiDAR) could be useful in generating data needed to run such a fluid mechanics-based model. This opens a realm of possibility to remotely sense and monitor stream flows in channels in remote locations.
Studies on hydrology, biogeochemistry, or mineral weathering often rely on assumptions about flow paths, water storage dynamics, and transit times. Testing these assumptions requires detailed hydrometric data that are usually unavailable at the catchment scale. Hillslope studies provide an alternative for obtaining a better understanding, but even on such well‐defined and delimited scales, it is rare to have a comprehensive set of hydrometric observations from the water divide down to the stream that can constrain efforts to quantify water storage, movement, and turnover time. Here, we quantified water storage with daily resolution in a hillslope during the course of almost an entire year using hydrological measurements at the study site and an extended version of the vertical equilibrium model. We used an exponential function to simulate the relationship between hillslope discharge and water table; this was used to derive transmissivity profiles along the hillslope and map mean pore water velocities in the saturated zone. Based on the transmissivity profiles, the soil layer transmitting 99% of lateral flow to the stream had a depth that ranged from 8.9 m at the water divide to under 1 m closer to the stream. During the study period, the total storage of this layer varied from 1189 to 1485 mm, resulting in a turnover time of 2172 days. From the pore water velocities, we mapped the time it would take a water particle situated at any point of the saturated zone anywhere along the hillslope to exit as runoff. Our calculations point to the strengths as well as limitations of simple hydrometric data for inferring hydrological properties and water travel times in the subsurface.
In recent decades considerable progress has been made in climate model development. Following the massive increase in computational power, models became more sophisticated. At the same time also simple conceptual models have advanced. In this study we validate and compare three hydrological models of different complexity to investigate whether their performance varies accordingly. For this purpose we use runoff and also soil moisture measurements, which allow a truly independent validation, from several sites across Switzerland. The models are calibrated in similar ways with the same runoff data. Our results show that the more complex models HBV and PREVAH outperform the simple water balance model (SWBM) in case of runoff but not for soil moisture. Furthermore the most sophisticated PREVAH model shows an added value compared to the HBV model only in case of soil moisture. Focusing on extreme events we find generally improved performance of the SWBM during drought conditions and degraded agreement with observations during wet extremes. For the more complex models we find the opposite behavior, probably because they were primarily developed for prediction of runoff extremes. As expected given their complexity, HBV and PREVAH have more problems with over-fitting. All models show a tendency towards better performance in lower altitudes as opposed to (pre-) alpine sites. The results vary considerably across the investigated sites. In contrast, the different metrics we consider to estimate the agreement between models and observations lead to similar conclusions, indicating that the performance of the considered models is similar at different time scales as well as for anomalies and long-term means. We conclude that added complexity does not necessarily lead to improved performance of hydrological models, and that performance can vary greatly depending on the considered hydrological variable (e.g. runoff vs. soil moisture) or hydrological conditions (floods vs. droughts). (C) 2015 The Authors. Published by Elsevier B.V.
Ecologically relevant streamflow characteristics (SFCs) of ungauged catchments are often estimated from simulated runoff of hydrologic models that were originally calibrated on gauged catchments. However, SFC estimates of the gauged donor catchments and subsequently the ungauged catchments can be substantially uncertain when models are calibrated using traditional approaches based on optimization of statistical performance metrics (e.g., Nash-Sutcliffe model efficiency). An improved calibration strategy for gauged catchments is therefore crucial to help reduce the uncertainties of estimated SFCs for ungauged catchments. The aim of this study was to improve SFC estimates from modeled runoff time series in gauged catchments by explicitly including one or several SFCs in the calibration process. Different types of objective functions were defined consisting of the Nash-Sutcliffe model efficiency, single SFCs, or combinations thereof. We calibrated a bucket-type runoff model (HBV-Hydrologiska Byrans Vattenavdelning-model) for 25 catchments in the Tennessee River basin and evaluated the proposed calibration approach on 13 ecologically relevant SFCs representing major flow regime components and different flow conditions. While the model generally tended to underestimate the tested SFCs related to mean and high-flow conditions, SFCs related to low flow were generally overestimated. The highest estimation accuracies were achieved by a SFC-specific model calibration. Estimates of SFCs not included in the calibration process were of similar quality when comparing a multi-SFC calibration approach to a traditional model efficiency calibration. For practical applications, this implies that SFCs should preferably be estimated from targeted runoff model calibration, and modeled estimates need to be carefully interpreted.
Applications of runoff models usually rely on long and continuous runoff time series for model calibration. However, many catchments around the world are ungauged and estimating runoff for these catchments is challenging. One approach is to perform a few runoff measurements in a previously fully ungauged catchment and to constrain a runoff model by these measurements. In this study we investigated the value of such individual runoff measurements when taken at strategic points in time for applying a bucket-type runoff model (HBV) in ungauged catchments. Based on the assumption that a limited number of runoff measurements can be taken, we sought the optimal sampling strategy (i.e. when to measure the streamflow) to obtain the most informative data for constraining the runoff model. We used twenty gauged catchments across the eastern US, made the assumption that these catchments were ungauged, and applied different runoff sampling strategies. All tested strategies consisted of twelve runoff measurements within one year and ranged from simply using monthly flow maxima to a more complex selection of observation times. In each case the twelve runoff measurements were used to select 100 best parameter sets using a Monte Carlo calibration approach. Runoff simulations using these 'informed' parameter sets were then evaluated for an independent validation period in terms of the Nash-Sutcliffe efficiency of the hydrograph and the mean absolute relative error of the flow-duration curve. Model performance measures were normalized by relating them to an upper and a lower benchmark representing a well-informed and an uninformed model calibration. The hydrographs were best simulated with strategies including high runoff magnitudes as opposed to the flow-duration curves that were generally better estimated with strategies that captured low and mean flows. The choice of a sampling strategy covering the full range of runoff magnitudes enabled hydrograph and flow-duration curve simulations close to a well-informed model calibration. The differences among such strategies covering the full range of runoff magnitudes were small indicating that the exact choice of a strategy might be less crucial. Our study corroborates the information value of a small number of strategically selected runoff measurements for simulating runoff with a bucket-type runoff model in almost ungauged catchments.