Modelling the non‐linear hydrological behaviour of a small Mediterranean forested catchment

A progressive perceptual understanding approach was used to identify a model structure able to represent the non‐linear behaviour of the hydrological cycle in a small intermittent Mediterranean stream. The initial lumped model structure consisting of a series of four connected water tanks (LU3) progressed to a model with five tanks (LU4), and finally to a semidistributed model structure (SD4) in which spatial variability of the evapotranspiration according to the vegetation cover and to the local aspect was considered. In the final model structure, which gave the best fit (Nash–Sutcliffe efficiency index = 0·78), an additional tank representing the riparian zone was included (SD4‐R). Results showed that the abrupt changes of the riparian water table during summer and the formation of a perched water table during the transition from dry to wet conditions were the main mechanisms leading to the non‐linear hydrological behaviour. The transpiration process from the saturated zone and the spatial variability of evapotranspiration resulted in key factors successfully representing the annual water balance. The spatial and temporal validations carried out for each of the four model structures considered in this study supported the hypothesis adopted during the calibration process. Copyright © 2008 John Wiley & Sons, Ltd.     

Understanding the hydrological system dynamics of a glaciated alpine catchment in the Himalayan region using the J2000 hydrological model

This paper provides the results of hydrological modelling in a mesoscale glaciated alpine catchment of the Himalayan region. In the context of global climate change, the hydrological regime of an alpine mountain is likely to be affected, which might produce serious implications for downstream water availability. The main objective of this study was to understand the hydrological system dynamics of a glaciated catchment, the Dudh Kosi River basin, in Nepal, using the J2000 hydrological model and thereby understand how the rise in air temperature will affect the hydrological processes. The model is able to reproduce the overall hydrological dynamics quite well with an efficiency result of Nash–Sutcliffe (0.85), logarithm Nash–Sutcliffe (0.93) and coefficient of determination (0.85) for the study period. The average contribution from glacier areas to total streamflow is estimated to be 17%, and snowmelt (other than from glacier areas) accounts for another 17%. This indicates the significance of the snow and glacier runoff in the Himalayan region. The hypothetical rise in temperature scenarios at a rate of +2 and +4 °C indicated that the snowmelt process might be largely affected. An increase in snowmelt volume is noted during the premonsoon period, whereas the contribution during the monsoon season is significantly decreased. This occurs mainly because the rise in temperature will shift the snowline up to areas of higher altitude and thereby reduce the snow storage capacity of the basin. This indicates that the region is particularly vulnerable to global climate change and the associated risk of decreasing water availability to downstream areas. Under the assumed warming scenarios, it is likely that in the future, the river might shift from a ‘melt‐dominated river’ to a ‘rain‐dominated river’. The J2000 model should be considered a promising tool to better understand the hydrological dynamics in alpine mountain catchments of the Himalayan region. This understanding will be quite useful for further analysis of ‘what‐if scenarios’ in the context of global climate and land‐use changes and ultimately for sustainable Integrated Water Resources Management in the Himalayan region. Copyright © 2012 John Wiley & Sons, Ltd.     

Simulation of probability distributions commonly used in hydrological frequency analysis

Random variable simulation has been applied to many applications in hydrological modelling, flood risk analysis, environmental impact assessment, etc. However, computer codes for simulation of distributions commonly used in hydrological frequency analysis are not available in most software libraries. This paper presents a frequency‐factor‐based method for random number generation of five distributions (normal, log–normal, extreme‐value type I, Pearson type III and log‐Pearson type III) commonly used in hydrological frequency analysis. The proposed method is shown to produce random numbers of desired distributions through three means of validation: (1) graphical comparison of cumulative distribution functions (CDFs) and empirical CDFs derived from generated data; (2) properties of estimated parameters; (3) type I error of goodness‐of‐fit test. An advantage of the method is that it does not require CDF inversion, and frequency factors of the five commonly used distributions involves only the standard normal deviate. Copyright © 2006 John Wiley & Sons, Ltd.     

Parameter estimation in semi‐distributed hydrological catchment modelling using a multi‐criteria objective function

Output generated by hydrologic simulation models is traditionally calibrated and validated using split‐samples of observed time series of total water flow, measured at the drainage outlet of the river basin. Although this approach might yield an optimal set of model parameters, capable of reproducing the total flow, it has been observed that the flow components making up the total flow are often poorly reproduced. Previous research suggests that notwithstanding the underlying physical processes are often poorly mimicked through calibration of a set of parameters hydrologic models most of the time acceptably estimates the total flow. The objective of this study was to calibrate and validate a computer‐based hydrologic model with respect to the total and slow flow. The quick flow component used in this study was taken as the difference between the total and slow flow. Model calibrations were pursued on the basis of comparing the simulated output with the observed total and slow flow using qualitative (graphical) assessments and quantitative (statistical) indicators. The study was conducted using the Soil and Water Assessment Tool (SWAT) model and a 10‐year historical record (1986–1995) of the daily flow components of the Grote Nete River basin (Belgium). The data of the period 1986–1989 were used for model calibration and data of the period 1990–1995 for model validation. The predicted daily average total flow matched the observed values with a Nash–Sutcliff coefficient of 0·67 during calibration and 0·66 during validation. The Nash–Sutcliff coefficient for slow flow was 0·72 during calibration and 0·61 during validation. Analysis of high and low flows indicated that the model is unbiased. A sensitivity analysis revealed that for the modelling of the daily total flow, accurate estimation of all 10 calibration parameters in the SWAT model is justified, while for the slow flow processes only 4 out of the set of 10 parameters were identified as most sensitive. Copyright © 2007 John Wiley & Sons, Ltd.     

Effects of area under‐estimations of sloped mountain terrain on simulated hydrological behaviour: a case study using the ACRU model

Sloped areas calculated from a GIS raster file, such as a digital elevation model, are smaller than the true surface area, because they are projected to a planimetric plane. In mountainous regions this sloped area under‐estimation (SAUE) can have significant consequences on hydrological calculations. A sensitivity analysis is conducted, using the ACRU agro‐hydrological modelling system in a small watershed in Glacier National Park, Montana, USA, to investigate the sensitivity of the SAUE on key elements of the hydrological cycle, including precipitation depth, April snow depth, August soil moisture deficit, actual evapotranspiration depth, and runoff depth. The sensitivity analysis is based on 224 unique combinations of slope, soil and land cover types, elevation with associated precipitation depths, and north and south facing radiation regimes. Results revealed an increasing influence of the SAUE on all hydrological processes with increasing slope steepness. Distinct differences and magnitudes between different land cover types, different elevations, and, in particular, different exposition were quantified. Actual evapotranspiration increases with SAUE, while runoff decreases. April soil water is simulated to decrease with an increase in SAUE. Finally, a comparison of a streamflow simulation of a small and steep alpine watershed with and without consideration of the SAUE is carried out. The sloped area of the small watershed is under‐estimated by 20·9%, and the difference in simulated runoff is 12·3%. When the SAUE was not considered, runoff was simulated to be higher, the associated coefficient of determination was slightly lower, and the slope of the regression line was flatter. Copyright © 2010 John Wiley & Sons, Ltd.     

Temporal sampling strategies and uncertainty in calibrating a conceptual hydrological model for a small boreal catchment

How much data is needed for calibration of a hydrological catchment model? In this paper we address this question by evaluating the information contained in different subsets of discharge and groundwater time series for multi‐objective calibration of a conceptual hydrological model within the framework of an uncertainty analysis. The study site was a 5·6‐km² catchment within the Forsmark research site in central Sweden along the Baltic coast. Daily time series data were available for discharge and several groundwater wells within the catchment for a continuous 1065‐day period. The hydrological model was a site‐specific modification of the conceptual HBV model. The uncertainty analyses were based on a selective Monte Carlo procedure. Thirteen subsets of the complete time series data were investigated with the idea that these represent realistic intermittent sampling strategies. Data subsets included split‐samples and various combinations of weekly, monthly, and quarterly fixed interval subsets, as well as a 53‐day ‘informed observer’ subset that utilized once per month samples except during March and April—the months containing large and often dominant snow melt events—when sampling was once per week. Several of these subsets, including that of the informed observer, provided very similar constraints on model calibration and parameter identification as the full data record, in terms of credibility bands on simulated time series, posterior parameter distributions, and performance indices calculated to the full dataset. This result suggests that hydrological sampling designs can, at least in some cases, be optimized. Copyright © 2009 John Wiley & Sons, Ltd.     

Global sensitivity analyses for a complex hydrological model applied in an Alpine watershed

The increasing complexity of hydrological models results in a large number of parameters to be estimated. In order to better understand how these complex models work, efficient screening methods are required in order to identify the most important parameters. This is of particular importance for models that are used within an operational real‐time forecasting chain such as HQsim. The objectives of this investigation are to (i) identify the most sensitive parameters of the complex HQsim model applied in the Alpine Lech catchment and (ii) compare model parameter sensitivity rankings attained from three global sensitivity analysis techniques. The techniques presented are the (i) regional sensitivity analysis, (ii) Morris analysis and (iii) state‐dependent parameter modelling. The results indicate that parameters affecting snow melt as well as processes in the unsaturated soil zone reveal high significance in the analysed catchment. The snow melt parameters show clear temporal patterns in the sensitivity whereas most of the parameters affecting processes in the unsaturated soil zone do not vary in importance across the year. Overall, the maximum degree day factor (meltfunc_max) has been identified to play a key role within the HQsim model. Although the parameter sensitivity rankings are equivalent between methods for a number of parameters, for several key parameters differing results were obtained. An uncertainty analysis demonstrates that a parameter ranking attained from only one method is subjected to large uncertainty. Copyright © 2012 John Wiley & Sons, Ltd.     

Internal testing of a numerical model of hillslope–channel coupling using laboratory flume experiments

The numerical model COUP 2D simulates the hydrological coupling between hillslopes and the river channel during a rainfall event. In order to test the numerical model, a 1:100 scaled laboratory flume which was modified to incorporate lateral hillslope elements, was used to run a series of experiments in which hillslope angle, channel angle, hillslope discharge and channel discharge were the varying parameters. Overall, there were 18 different experimental configurations with three replicates carried out for each condition, leading to a total of 54 experiments. These conditions were then used to parameterize and run COUP 2D. Internal model outputs of flow depth and flow velocity at four cross‐sections in the channel were compared to the measurements made in the physical model for the same parameter conditions. Statistical comparisons of the measured and modelled data were carried out for each experiment and across all experiments, using two goodness‐of‐fit measures—root mean square error and Nash–Sutcliffe coefficient of efficiency—in order to assess the performance of the model over an entire simulation as well as over all the simulations. The main effects on the goodness‐of‐fit measures for flow depth of each experimental variable, as well as the interactions between variables, were evaluated using statistical modelling. The results show that the model captures flow‐depth variations in response to changing channel and hillslope parameters. Statistical modelling suggests that the main effects on model error are cross‐section position, channel angle and channel discharge. Significant interactions also occur between all the channel variables and between the channel variables and hillslope discharge. The results of the testing procedure have significant implications for the consideration of different model components and for the interaction between data‐ and model evaluation. Copyright © 2007 John Wiley & Sons, Ltd.     

Perspectives in using a remotely sensed dryness index in distributed hydrological models at the river‐basin scale

In a previous study a spatially distributed hydrological model, based on the MIKE SHE code, was constructed and validated for the 375 000 km² Senegal River basin in West Africa. The model was constructed using spatial data on topography, soil types and vegetation characteristics together with time‐series of precipitation from 112 stations in the basin. The model was calibrated and validated based on river discharge data from nine stations in the basin for 11 years. Calibration and validation results suggested that the spatial resolution of the input data in parts of the area was not sufficient for a satisfactory evaluation of the modelling performance. The study further examined the spatial patterns in the model input and output, and it was found that particularly the spatial resolution of the precipitation input had a major impact on the model response. In an attempt to improve the model performance, this study examines a remotely sensed dryness index for its relationship to simulated soil moisture and evaporation for six days in the wet season 1990. The index is derived from observations of surface temperature and vegetation index as measured by the NOAA Advanced Very High Resolution Radiometer (AVHRR) sensor. The correlation results between the index and the simulation results are of mixed quality. A sensitivity analysis, conducted on both estimates, reveals significant uncertainties in both. The study suggests that the remotely sensed dryness index with its current use of NOAA AVHRR data does not offer information that leads to a better calibration or validation of the simulation model in a spatial sense. The method potentially may become more suitable with the use of the upcoming high‐resolution temporal Meteosat Second Generation data. Copyright © 2002 John Wiley & Sons, Ltd.     

Assessing the performance of a physically based hydrological model using a proxy‐catchment approach in an agricultural environment

Physically based models are useful frameworks for testing intervention strategies designed to reduce elevated sediment loads in agricultural catchments. Evaluating the success of these strategies depends on model accuracy, generally established by a calibration and evaluation process. In this contribution, the physically based SHETRAN model was assessed in two similar U.K. agricultural catchments. The model was calibrated on the Blackwater catchment (18 km²) and evaluated in the adjacent Kit Brook catchment (22 km²) using 4 years of 15 min discharge and suspended sediment flux data. Model sensitivity to changes in single and multiple combinations of parameters and sensitivity to changes in digital elevation model resolution were assessed. Model flow performance was reasonably accurate with a Nash–Sutcliffe efficiency coefficient of 0.78 in Blackwater and 0.60 in Kit Brook. In terms of event prediction, the mean of the absolute percentage of difference (μAbs_diff) between measured and simulated flow volume (Qv), peak discharge (Qp), sediment yield (Sy), and peak sediment flux (Sp) showed larger values in Kit Brook (48% [Qv], 66% [Qp], 298% [Sy], and 438% [Sp]) compared with the Blackwater catchment (30% [Qv], 41% [Qp], 106% [Sy], and 86% [Sp]). Results indicate that SHETRAN can produce reasonable flow prediction but performs less well in estimation of sediment flux, despite reasonably similar hydrosedimentary behaviour between catchments. The sensitivity index showed flow volume sensitive to saturated hydraulic conductivity and peak discharge to the Strickler coefficient; sediment yield was sensitive to the overland flow erodibility coefficient and peak sediment flux to raindrop/leaf soil erodibility coefficient. The multiparameter sensitivity analysis showed that different combinations of parameters produced similar model responses. Model sensitivity to grid resolution presented similar flow volumes for different digital elevation model resolutions, whereas event peak and duration (for both flow and sediment flux) were highly sensitive to changes in grid size.     

Spatial and temporal variability of the hydrological response in a small Mediterranean research catchment (Vallcebre,Eastern Pyrenees)

This paper analyses the spatial and temporal variability of the hydrological response in a small Mediterranean catchment (Cal Rodó). The first part of the analysis focuses on the rainfall–runoff relationship at seasonal and monthly scale, using an 8‐year data set. Then, using storm‐flow volume and coefficient, the temporal variability of the rainfall–runoff relationship and its relationship with several hydrological variables are analysed at the event scale from hydrographs observed over a 3‐year period. Finally, the spatial non‐linearity of the hydrological response is examined by comparing the Cal Rodó hydrological response with the Can Vila sub‐catchment response at the event scale. Results show that, on a seasonal and monthly scale, there is no simple relationship between rainfall and runoff depths, and that evapotranspiration is a factor that introduced some non‐linearity in the rainfall–runoff relationship. The analysis of monthly values also reveals the existence of a threshold in the relationship between rainfall and runoff depths, denoting a more contrasted hydrological response than the one usually observed in humid catchments. At the event scale, the storm‐flow coefficient has a clear seasonal pattern with an alternance between a wet period, when the catchment is hydrologically responsive, and a dry summer period, when the catchment is much less reactive to any rainfall. The relationship between the storm‐flow coefficient and rainfall depth, rainfall maximum intensity and base‐flow shows that observed correlations are the same as those observed for humid conditions, even if correlation coefficients are notably lower. Comparison with the Can Vila sub‐catchment highlights the spatial heterogeneity of the rainfall‐runoff relationship at the small catchment scale. Although interpretation in terms of runoff processes remains delicate, heterogeneities between the two catchments seem to be related to changes in the ratio between infiltration excess and saturation processes in runoff formation. Copyright © 2007 John Wiley & Sons, Ltd.     

Multicriteria sensitivity analysis as a diagnostic tool for understanding model behaviour and characterizing model uncertainty

Complex hydrological models are being increasingly used nowadays for many purposes such as studying the impact of climate and land‐use change on water resources. However, building a high‐fidelity model, particularly at large scales, remains a challenging task, due to complexities in model functioning and behaviour and uncertainties in model structure, parameterization, and data. Global sensitivity analysis (GSA), which characterizes how the variation in the model response is attributed to variations in its input factors (e.g., parameters and forcing data), provides an opportunity to enhance the development and application of these complex models. In this paper, we advocate using GSA as an integral part of the modelling process by discussing its capabilities as a tool for diagnosing model structure and detecting potential defects, identifying influential factors, characterizing uncertainty, and selecting calibration parameters. Accordingly, we conduct a comprehensive GSA of a complex land surface–hydrology model, Modélisation Environmentale–Surface et Hydrologie (MESH), which combines the Canadian land surface scheme with a hydrological routing component, WATROUTE. Various GSA experiments are carried out using a new technique, called Variogram Analysis of Response Surfaces, for alternative hydroclimatic conditions in Canada using multiple criteria, various model configurations, and a full set of model parameters. Results from this study reveal that, in addition to different hydroclimatic conditions and SA criteria, model configurations can also have a major impact on the assessment of sensitivity. GSA can identify aspects of the model internal functioning that are counter‐intuitive and thus help the modeller to diagnose possible model deficiencies and make recommendations for improving development and application of the model. As a specific outcome of this work, a list of the most influential parameters for the MESH model is developed. This list, along with some specific recommendations, is expected to assist the wide community of MESH and Canadian land surface scheme users, to enhance their modelling applications.     

Classifying the flow regimes of Mediterranean streams using multivariate analysis

Rivers in the Mediterranean region often exhibit an intermittent character. An understanding and classification of the flow regimes of these rivers is needed, as flow patterns control both physicochemical and biological processes. This paper reports an attempt to classify flow regimes in Mediterranean rivers based on hydrological variables extracted from discharge time series. Long‐term discharge records from 60 rivers within the Mediterranean region were analysed in order to classify the streams into different flow regime groups. Hydrological indices (HIs) were derived for each stream and principal component analysis (PCA) and then applied to these indices to identify subsets of HIs describing the major sources of variations, while simultaneously minimizing redundancy. PCA was performed for two groups of streams (perennial and temporary) and for all streams combined. The results show that whereas perennial streams are mainly described by high‐flow indices, temporary streams are described by duration, variability and predictability indices. Agglomerative cluster analysis based on HIs identified six groups of rivers classified according to differences in intermittency and variability. A methodology allowing such a classification for ungauged catchments was also tested. Broad‐scale catchment characteristics based on digital elevation, climate, soil and land use data were derived for each long‐term station where these data were available. By using stepwise multiple regression analysis, statistically significant relationships were fitted, linking the three selected hydrological variables (mean annual number of zero‐flow days, predictability and flashiness) to the catchment characteristics. The method provides a means of simplifying the complexity of river systems and is thus useful for river basin management. Copyright © 2015 John Wiley & Sons, Ltd.     

Hydrological response of a Brazilian semi‐arid catchment to different land use and climate change scenarios: a modelling study

Brazilian semi‐arid regions are characterized by water scarcity, vulnerability to desertification, and climate variability. The investigation of hydrological processes in this region is of major interest not only for water planning strategies but also to address the possible impact of future climate and land‐use changes on water resources. A hydrological distributed catchment‐scale model (DiCaSM) has been applied to simulate hydrological processes in a small representative catchment of the Brazilian northeast semi‐arid region, and also to investigate the impact of climate and land‐use changes, as well as changes associated with biofuel/energy crops production. The catchment is part of the Brazilian network for semi‐arid hydrology, established by the Brazilian Federal Government. Estimating and modelling streamflow (STF) and recharge in semi‐arid areas is a challenging task, mainly because of limitation in in situ measurements, and also due to the local nature of some processes. Direct recharge measurements are very difficult in semi‐arid catchments and contain a high level of uncertainty. The latter is usually addressed by short‐ and long‐time‐scale calibration and validation at catchment scale, as well as by examining the model sensitivity to the physical parameters responsible for the recharge. The DiCaSM model was run from 2000 to 2008, and streamflow was successfully simulated, with a Nash–Sutcliffe (NS) efficiency coefficient of 0·73, and R² of 0·79. On the basis of a range of climate change scenarios for the region, the DiCaSM model forecasted a reduction by 35%, 68%, and 77%, in groundwater recharge (GWR), and by 34%, 65%, and 72%, in streamflow, for the time spans 2010–2039, 2040–2069, and 2070–2099, respectively, could take place for a dry future climate scenario. These reductions would produce severe impact on water availability in the region. Introducing castor beans to the catchment would increase the GWR and streamflow, mainly if the caatinga areas would be converted into castor beans production. Changing an area of 1000 ha from caatinga to castor beans would increase the GWR by 46% and streamflow by 3%. If the same area of pasture is converted into castor beans, there would be an increase in GWR and streamflow by 24% and 5%, respectively. Such results are expected to contribute towards environmental policies for north‐east Brazil (NEB), and to biofuel production perspectives in the region. Copyright © 2010 John Wiley & Sons, Ltd.     

Meta‐analysis of flow modeling performances—to build a matching system between catchment complexity and model types

Hydrological models play a significant role in modelling river flow for decision making support in water resource management. In the past decades, many researchers have made a great deal of efforts in calibrating and validating various models, with each study being focused on one or two models. As a result, there is a lack of comparative analysis on the performance of those models to guide hydrologists to choose appropriate models for the individual climate and physical conditions. This paper describes a two‐level meta‐analysis to develop a matching system between catchment complexity (based on catchment significant features (CSFs)) and model types. The intention is to use the available CSF information for choosing the most suitable model type for a given catchment. In this study, the CSFs include the elements of climate, soil type, land cover and catchment scale. Specific choices of model types in small and medium catchments are further explored with all CSF information obtained. In particular, it is interesting to find that semi‐distributed models are the most suitable model type for catchments with the area over 3000 km², regardless of other CSFs. The potential methodology for expanding the matching system between catchment complexity and model complexity is discussed. Copyright © 2014 John Wiley & Sons, Ltd.     

Simulating the water budget of a Prairie Potholes complex from LiDAR and hydrological models in North Dakota,USA

Abstract

Hydrological processes of the wetland complex in the Prairie Pothole Region (PPR) are difficult to model, partly due to a lack of wetland morphology data. We used Light Detection And Ranging (LiDAR) data sets to derive wetland features; we then modelled rainfall, snowfall, snowmelt, runoff, evaporation, the “fill-and-spill” mechanism, shallow groundwater loss, and the effect of wet and dry conditions. For large wetlands with a volume greater than thousands of cubic metres (e.g. about 3000 m³), the modelled water volume agreed fairly well with observations; however, it did not succeed for small wetlands (e.g. volume less than 450 m³). Despite the failure for small wetlands, the modelled water area of the wetland complex coincided well with interpretation of aerial photographs, showing a linear regression with R² of around 0.80 and a mean average error of around 0.55 km². The next step is to improve the water budget modelling for small wetlands.

Editor Z.W. Kundzewicz; Associate editor X. Chen

Citation Huang, S.L., Young, C., Abdul-Aziz, O.I., Dahal, D., Feng, M., and Liu, S.G., 2013. Simulating the water budget of a Prairie Potholes complex from LiDAR and hydrological models in North Dakota, USA. Hydrological Sciences Journal, 58 (7), 1434–1444.     

Diagnostic evaluation of multiple hypotheses of hydrological behaviour in a limits‐of‐acceptability framework for 24 UK catchments

Testing competing conceptual model hypotheses in hydrology is complicated by uncertainties from a wide range of sources, which result in multiple simulations that explain catchment behaviour. In this study, the limits of acceptability uncertainty analysis approach used to discriminate between 78 competing hypotheses in the Framework for Understanding Structural Errors for 24 catchments in the UK. During model evaluation, we test the model's ability to represent observed catchment dynamics and processes by defining key hydrologic signatures and time step‐based metrics from the observed discharge time series. We explicitly account for uncertainty in the evaluation data by constructing uncertainty bounds from errors in the stage‐discharge rating curve relationship. Our study revealed large differences in model performance both between catchments and depending on the type of diagnostic used to constrain the simulations. Model performance varied with catchment characteristics and was best in wet catchments with a simple rainfall‐runoff relationship. The analysis showed that the value of different diagnostics in constraining catchment response and discriminating between competing conceptual hypotheses varies according to catchment characteristics. The information content held within water balance signatures was found to better capture catchment dynamics in chalk catchments, where catchment behaviour is predominantly controlled by seasonal and annual changes in rainfall, whereas the information content in the flow‐duration curve and time‐step performance metrics was able to better capture the dynamics of rainfall‐driven catchments. We also investigate the effect of model structure on model performance and demonstrate its (in)significance in reproducing catchment dynamics for different catchments. Copyright © 2013 John Wiley & Sons, Ltd.     

Evaluating explicit and implicit routing for watershed hydro‐ecological models of forest hydrology at the small catchment scale

This paper explores the behaviour and sensitivity of a watershed model used for simulating lateral soil water redistribution and runoff production. In applications such as modelling the effects of land‐use change in small headwater catchments, interactions between soil moisture, runoff and ecological processes are important. Because climate, soil and canopy characteristics are spatially variable, both the pattern of soil moisture and the associated outflow must be represented in modelling these processes. This study compares implicit and explicit routing approaches to modelling the evolution of soil moisture pattern and spatially variable runoff production. It also addresses the implications of using different landscape partitioning strategies. This study presents the results of calibration and application of these different routing and landscape partitioning approaches on a 60 ha forested watershed in Western Oregon. For comparison, the different approaches are incorporated into a physically based hydro‐ecological model, RHESSys, and the resulting simulated soil moisture, runoff production and sensitivity to unbiased error are examined. Results illustrate that both routing approaches can be calibrated to achieve a reasonable fit between observed and modelled outflow. Calibrated values for effective watershed hydraulic conductivity are higher for the explicit routing approach, which illustrates differences between the two routing approaches in their representation of internal watershed dynamics. The explicit approach illustrates a seasonal shift in drainage organization from watershed to more local control as climate goes from a winter wet to a summer dry period. Assumptions used in the implicit approach maintain the same pattern of drainage organization throughout the season. The implicit approach is also more sensitive to random error in soil and topographic input information, particularly during wetter periods. Comparison between the two routing approaches illustrates the advantage of the explicit routing approach, although the loss of computational efficiency associated with the explicit routing approach is noted. To compare different strategies for partitioning the landscape, the use of a non‐grid‐based method of partitioning is introduced and shown to be comparable to grid‐based partitioning in terms of simulated soil moisture and runoff production. Copyright © 2001 John Wiley & Sons, Ltd.     

The impact of different spatial land cover data sets on the outputs of a hydrological model - a modelling exercise in the Ucker catchment, North-East Germany

The spatial distribution of forests, meadows, arable land, water bodies and settlements in a catchment influences the spatial and temporal dynamics of evapotranspiration, surface runoff, soil moisture and ground water recharge. Four digital data sets from different sources were available for land cover distribution to be applied in a regional case study in the Ucker catchment with an area of about 2415 km². The first data set was obtained from the German digital topographic data set “Atkis” and the second one from the federal German biotope mapping procedure “Biotoptypenkartierung”. In addition, Corine land cover data and a land cover obtained from a supervised, multitemporal classification of three Landsat-TM5-scenes from the year 2000 were used in our study. These data sets differ in spatial resolution and in information content and this leads to different areal proportions of the main land cover classes forests, meadows, arable land, water bodies and settlements. This has to be considered as an uncertainty in the land cover data. In our case study, we analyzed how and to which extent this uncertainty influences the outputs of a hydrological catchment model such as evapotranspiration and discharge. For the time period 1996-2001, meteorological time series were obtained from four meteorological stations and five additional precipitation stations. Measured daily discharge rates were available from two gauges located in the catchment. In the different land cover data sets, the proportions of arable land ranged from 52.7% to 61.7% of the catchment area and for forests from 19.5% to 24.6%. These different proportions showed only minor impacts with small differences below ±10 mm y⁻¹ on the simulated annual rates of evapotranspiration and ground water recharge. In contrast, the simulated surface runoff rates showed a strong correlation to the amount of the settlement areas in the catchment. The highest proportion of settlements with 4.9% of the catchment area in comparison to the lowest proportion of 2.9% leads to an increase in the simulated surface runoff of 70%.