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.     

Transferability of hydrological model parameter spaces in the estimation of runoff in ungauged catchments

Abstract

In this study, transferability options of the Hydrologiska Byråns Vattenbalansavdelning (HBV) hydrological model parameter (MP) spaces were investigated to estimate ungauged catchment runoff. Three approaches were applied in the study: MP space transfer from single, neighbouring and all potential donor catchments. The model performance was evaluated by a jackknife procedure, where one catchment at a time was treated as if ungauged, and behavioural MP sets from candidate donor catchments were used to estimate the “ungauged” runoff. The results showed that ungauged catchment runoff estimation could not be guaranteed by transferring MP sets from a single physiographically nearest donor catchment. Integrating MP sets typically from one to six donor catchments supplemented the lack of effective MP sets and improved the model performance at the ungauged catchments. In addition, the analysis results revealed that the model performance converged to an average performance when the MP sets of all potential donor catchments were integrated.     

Parameter and rating curve uncertainty propagation analysis of the SWAT model for two small Mediterranean catchments

Abstract

The SWAT model was tested to simulate the streamflow of two small Mediterranean catchments (the Vène and the Pallas) in southern France. Model calibration and prediction uncertainty were assessed simultaneously by using three different techniques (SUFI-2, GLUE and ParaSol). Initially, a sensitivity analysis was conducted using the LH-OAT method. Subsequent sensitive parameter calibration and SWAT prediction uncertainty were analysed by considering, firstly, deterministic discharge data (assuming no uncertainty in discharge data) and secondly, uncertainty in discharge data through the development of a methodology that accounts explicitly for error in the rating curve (the stage?discharge relationship). To efficiently compare the different uncertainty methods and the effect of the uncertainty of the rating curve on model prediction uncertainty, common criteria were set for the likelihood function, the threshold value and the number of simulations. The results show that model prediction uncertainty is not only case-study specific, but also depends on the selected uncertainty analysis technique. It was also found that the 95% model prediction uncertainty interval is wider and more successful at encompassing the observations when uncertainty in the discharge data is considered explicitly. The latter source of uncertainty adds additional uncertainty to the total model prediction uncertainty.

Editor D. Koutsoyiannis; Associate editor D. Gerten

Citation Sellami, H., La Jeunesse, I., Benabdallah, S., and Vanclooster, M., 2013. Parameter and rating curve uncertainty propagation analysis of the SWAT model for two small Mediterranean watersheds. Hydrological Sciences Journal, 58 (8), 1635?1657.     

Understanding coastal wetland hydrology with a new regional‐scale,process‐based hydrological model

Coastal wetlands represent an ecotone between ocean and terrestrial ecosystems, providing important services, including flood mitigation, fresh water supply, erosion control, carbon sequestration, and wildlife habitat. The environmental setting of a wetland and the hydrological connectivity between a wetland and adjacent terrestrial and aquatic systems together determine wetland hydrology. Yet little is known about regional‐scale hydrological interactions among uplands, coastal wetlands, and coastal processes, such as tides, sea level rise, and saltwater intrusion, which together control the dynamics of wetland hydrology. This study presents a new regional‐scale, physically based, distributed wetland hydrological model, PIHM‐Wetland, which integrates the surface and subsurface hydrology with coastal processes and accounts for the influence of wetland inundation on energy budgets and evapotranspiration (ET). The model was validated using in situ hydro‐meteorological measurements and Moderate Resolution Imaging Spectroradiometer (MODIS) ET data for a forested and herbaceous wetland in North Carolina, USA, which confirmed that the model accurately represents the major wetland hydrological behaviours. Modelling results indicate that topographic gradient is a primary control of groundwater flow direction in adjacent uplands. However, seasonal climate patterns become the dominant control of groundwater flow at lower coastal plain and land–ocean interface. We found that coastal processes largely influence groundwater table (GWT) dynamics in the coastal zone, 300 to 800 m from the coastline in our study area. Among all the coastal processes, tides are the dominant control on GWT variation. Because of inundation, forested and herbaceous wetlands absorb an additional 6% and 10%, respectively, of shortwave radiation annually, resulting in a significant increase in ET. Inundation alters ET partitioning through canopy evaporation, transpiration, and soil evaporation, the effect of which is stronger in cool seasons than in warm seasons. The PIHM‐Wetland model provides a new tool that improves the understanding of wetland hydrological processes on a regional scale. Insights from this modelling study provide benchmarks for future research on the effects of sea level rise and climate change on coastal wetland functions and services.     

A process‐based conversion model for caesium‐137 derived erosion rates on agricultural land: an integrated spatial approach

There is increasing recognition that ¹³⁷Cs data remain one of the few sources of spatially distributed information concerning soil erosion. However, many of the conversion models that have been used to convert ¹³⁷Cs data into soil redistribution rates failed to account for some of the key factors affecting the redistribution of ¹³⁷Cs in agricultural landscapes. The conversion model presented in this paper aims to overcome some of the limitations associated with existing models and therefore to provide more realistic estimates of soil erosion rates on agricultural land. The conversion model aims at coupling soil redistribution processes directly with ¹³⁷Cs redistribution. Emphasis is placed on the spatial representation of soil redistribution processes and the adequate simulation of tillage processes. The benefits of the presented model arise from the two‐dimensional spatial integration of mass balance models with soil erosion models. No a priori assumptions about the intensity of any soil redistribution process are necessary and the level of agreement between observed and simulated ¹³⁷Cs inventories enables us to evaluate the performance of the model. The spatial implementation and the use of fuzzy parameter sets also allow us to assess the uncertainties associated with soil erosion estimates. It was shown that an adequate simulation of tillage processes is necessary and that simplified tillage models may lead to erroneous estimates of soil redistribution. The model was successfully applied to a study site in the Belgian Loam Belt and the results indicated that tillage is the dominant process. Furthermore, the uncertainties associated with the estimation of water erosion rates were much higher than those associated with tillage, especially for depositional areas. Copyright © 2003 John Wiley & Sons, Ltd.     

Effects of land‐cover changes on the hydrological response of interior Columbia River basin forested catchments

The topographically explicit distributed hydrology–soil–vegetation model (DHSVM) is used to simulate hydrological effects of changes in land cover for four catchments, ranging from 27 to 1033 km², within the Columbia River basin. Surface fluxes (stream flow and evapotranspiration) and state variables (soil moisture and snow water equivalent) corresponding to historical (1900) and current (1990) vegetation are compared. In addition a sensitivity analysis, where the catchments are covered entirely by conifers at different maturity stages, was conducted. In general, lower leaf‐area index (LAI) resulted in higher snow water equivalent, more stream flow and less evapotranspiration. Comparisons with the macroscale variable infiltration capacity (VIC) model, which parameterizes, rather than explicitly represents, topographic effects, show that runoff predicted by DHSVM is more sensitive to land‐cover changes than is runoff predicted by VIC. This is explained by model differences in soil parameters and evapotranspiration calculations, and by the more explicit representation of saturation excess in DHSVM and its higher sensitivity to LAI changes in the calculation of evapotranspiration. Copyright © 2002 John Wiley & Sons, Ltd.     

Integrating glaciers raster‐based modelling in large catchments hydrological balance: the Rhone case study

A raster‐based glacier sub‐model was successfully introduced in the distributed hydrological model FEST‐WB to simulate the water balance and surface runoff of large Alpine catchments. The glacier model is based on temperature‐index approach for melt, on linear reservoir for melt water propagation into the ice and on mass balance for accumulation; the initialization of the volume of ice on the basin was based on a formulation depending on surface topography. The model was first tested on a sub‐basin of the Rhone basin (Switzerland), which is for 62% glaciated; the calibration and validation were based on comparison between simulated and observed discharge from 1999 to 2008. The model proved to be suitable to simulate the typical discharge seasonality of a heavily glaciated basin. The performance of the model was also tested by simulating discharge in the whole Swiss Rhone basin, in which glaciers contribution is not negligible, in fact, in summer, about the 40% of the discharge is due to glacier melt. The model allowed to take into account the volume of water coming from glaciers melt and its simple structure is suitable for analysis of the effects of climate change on hydrological regime of high mountain basins, with available meteorological forcing from current RCM. Copyright © 2012 John Wiley & Sons, Ltd.     

Process‐based hydrological modelling: The potential of a bottom‐up approach for runoff predictions in ungauged catchments

Conceptual rainfall–runoff models are a valuable tool for predictions in ungauged catchments. However, most of them rely on calibration to determine parameter values. Improving the representation of runoff processes in models is an attractive alternative to calibration. Such an approach requires a straightforward, a priori parameter allocation procedure applicable on a wide range of spatial scales. However, such a procedure has not been developed yet. In this paper, we introduce a process‐based runoff generation module (RGM‐PRO) as a spin‐off of the traditional runoff generation module of the PREVAH hydrological modelling system. RGM‐PRO is able to exploit information from maps of runoff types, which are developed on the basis of field investigations and expert knowledge. It is grid based, and within each grid cell, the process heterogeneity is considered to avoid information loss due to grid resolution. The new module is event based, and initial conditions are assimilated and downscaled from continuous simulations of PREVAH, which are also available for real‐time applications. Four parameter allocation strategies were developed, on the basis of the results of sprinkling experiments on 60‐m² hillslope plots at several grassland locations in Switzerland, and were tested on five catchments on the Swiss Plateau and Prealps. For the same catchments, simulation results obtained with the best parameter allocation strategy were compared with those obtained with different configurations of the traditional runoff generation module of PREVAH, which was also applied as an event‐based module here. These configurations include a version that avoids calibration, one that transfers calibrated parameters, and one that uses regionalised parameter values. RGM‐PRO simulated heavy events in a more realistic way than the uncalibrated traditional runoff generation module of PREVAH, and, in some instances, it even exceeded the performance of the calibrated traditional one. The use of information on the spatial distribution of runoff types additionally proved to be valuable as a regionalisation technique and showed advantages over the other regionalisation approaches, also in terms of robustness and transferability.     

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.     

Testing the applicability of a kinematic wave-based distributed hydrological model in two climatically contrasting catchments

Abstract

Steep mountainous areas account for 70% of all river catchments in Japan. To predict river discharge for the mountainous catchments, many studies have applied distributed hydrological models based on a kinematic wave approximation with surface and subsurface flow components (DHM-KWSS). These models reproduce observed river discharge of catchments in Japan well; however, the applicability of a DHM-KWSS to catchments with different geographical and climatic conditions has not been sufficiently examined. This research applied a DHM-KWSS to two river basins that have different climatic conditions from basins in Japan to examine the transferability of the DHM-KWSS model structure. Our results show that the DHM-KWSS model structure explained flow regimes for a wet river basin as well as a large flood event in an arid basin; however, it was unable to explain long-term flow regimes for the arid basin case study.     

Understanding the time‐varying importance of different uncertainty sources in hydrological modelling using global sensitivity analysis

Simulations from hydrological models are affected by potentially large uncertainties stemming from various sources, including model parameters and observational uncertainty in the input/output data. Understanding the relative importance of such sources of uncertainty is essential to support model calibration, validation and diagnostic evaluation and to prioritize efforts for uncertainty reduction. It can also support the identification of ‘disinformative data’ whose values are the consequence of measurement errors or inadequate observations. Sensitivity analysis (SA) provides the theoretical framework and the numerical tools to quantify the relative contribution of different sources of uncertainty to the variability of the model outputs. In traditional applications of global SA (GSA), model outputs are aggregations of the full set of a simulated variable. For example, many GSA applications use a performance metric (e.g. the root mean squared error) as model output that aggregates the distances of a simulated time series to available observations. This aggregation of propagated uncertainties prior to GSA may lead to a significant loss of information and may cover up local behaviour that could be of great interest. Time‐varying sensitivity analysis (TVSA), where the aggregation and SA are repeated at different time steps, is a viable option to reduce this loss of information. In this work, we use TVSA to address two questions: (1) Can we distinguish between the relative importance of parameter uncertainty versus data uncertainty in time? (2) Do these influences change in catchments with different characteristics? To our knowledge, the results present one of the first quantitative investigations on the relative importance of parameter and data uncertainty across time. We find that the approach is capable of separating influential periods across data and parameter uncertainties, while also highlighting significant differences between the catchments analysed. Copyright © 2016 The Authors. Hydrological Processes. Published by 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.     

Assessing the spatial and temporal variation of the rainwater harvesting potential (1971–2010) on the Chinese Loess Plateau using the VIC model

Rainwater harvesting could increase the resilience of ecosystems on the Loess Plateau and thus ensure the sustainability of livelihoods that depend on them. As such, it is a key component of strategies for adapting to global climate change. In this study, we used a new method to quantify the rainwater harvesting potential (RWHP) across the whole Loess Plateau and to characterize its spatial and temporal variation over the last four decades on the basis of the variable infiltration capacity model. It was found that that the mean RWHP of the study region was 731.10 × 10⁸ m³, and the average water layer thickness was 114.34 mm. There is considerable scope for rainwater harvesting across the Loess Plateau as a whole, to the extent that it could potentially provide enough water to implement the ‘Grain for Green’ Project. The annual average RWHP decreased slightly from 1971 to 2010, and Hurst exponent analysis indicated that this trend will exhibit long‐term persistence. The annual RWHP was highest in the southeast of the Loess Plateau and lowest in the northwest. Areas with high RWHP values tended to be clustered around the middle reach of the Yellow River. For most areas, there was no significant change between 1971 and 2010. Those areas for which there was a significant decrease in RWHP were primarily located around the upper–middle reaches of the Weihe River, the upper reach of Jinghe River, the eastern Guanzhong Plain, the Qinhe River watershed and the area around Dongsheng. Quantitative assessments of RWHP are likely to be useful for guiding the development and use of innovative rainwater harvesting technologies around the world and could help to relieve the problems caused by water shortages on the Loess Plateau while simultaneously eliminate the major cause of soil erosion. Copyright © 2012 John Wiley & Sons, Ltd.     

Coupling of a simultaneous heat and water model with a distributed hydrological model and evaluation of the combined model in a cold region watershed

Snow and frozen soil prevail in cold regions worldwide, and the integration of these processes is crucial in hydrological models. In this study, a combined model was developed by fully coupling a simultaneous heat and water model with a geomorphologically based distributed hydrological model. The combined model simulates vertical and lateral water transfer as well as vertical heat fluxes and is capable of representing the effects of frozen soil and snowmelt on hydrological processes in cold regions. This model was evaluated by using in situ observations in the Binggou watershed, an experimental watershed for cold region hydrology of the Watershed Allied Telemetry Experimental Research Project. Results showed that the model was able to predict soil freezing and thawing, unfrozen soil water content, and snow depth reasonably well. The simulated hydrograph was in good agreement with the in situ observation. The Nash–Sutcliffe coefficient of daily discharge was 0.744 for the entire simulation period, 0.472 from April to June, and 0.711 from June to November. This model can improve our understanding of hydrological processes in cold regions and assess the impacts of global warming on hydrological cycles and water resources. Copyright © 2012 John Wiley & Sons, Ltd.     

A simple rainfall–runoff model based on hydrological units applied to the Teba catchment (south‐east Spain)

A hydrological model (YWB, yearly water balance) has been developed to model the daily rainfall–runoff relationship of the 202 km² Teba river catchment, located in semi‐arid south‐eastern Spain. The period of available data (1976–1993) includes some very rainy years with intensive storms (responsible for flooding parts of the town of Malaga) and also some very dry years. The YWB model is in essence a simple tank model in which the catchment is subdivided into a limited number of meaningful hydrological units. Instead of generating per unit surface runoff resulting from infiltration excess, runoff has been made the result of storage excess. Actual evapotranspiration is obtained by means of curves, included in the software, representing the relationship between the ratio of actual to potential evapotranspiration as a function of soil moisture content for three soil texture classes. The total runoff generated is split between base flow and surface runoff according to a given baseflow index. The two components are routed separately and subsequently joined. A large number of sequential years can be processed, and the results of each year are summarized by a water balance table and a daily based rainfall runoff time series. An attempt has been made to restrict the amount of input data to the minimum. Interactive manual calibration is advocated in order to allow better incorporation of field evidence and the experience of the model user. Field observations allowed for an approximate calibration at the hydrological unit level. Copyright © 2001 John Wiley & Sons, Ltd.     

Use of multi‐platform,multi‐temporal remote‐sensing data for calibration of a distributed hydrological model: an application in the Arno basin,Italy

Images from satellite platforms are a valid aid in order to obtain distributed information about hydrological surface states and parameters needed in calibration and validation of the water balance and flood forecasting. Remotely sensed data are easily available on large areas and with a frequency compatible with land cover changes. In this paper, remotely sensed images from different types of sensor have been utilized as a support to the calibration of the distributed hydrological model MOBIDIC, currently used in the experimental system of flood forecasting of the Arno River Basin Authority. Six radar images from ERS‐2 synthetic aperture radar (SAR) sensors (three for summer 2002 and three for spring–summer 2003) have been utilized and a relationship between soil saturation indexes and backscatter coefficient from SAR images has been investigated. Analysis has been performed only on pixels with meagre or no vegetation cover, in order to legitimize the assumption that water content of the soil is the main variable that influences the backscatter coefficient. Such pixels have been obtained by considering vegetation indexes (NDVI) and land cover maps produced by optical sensors (Landsat‐ETM). In order to calibrate the soil moisture model based on information provided by SAR images, an optimization algorithm has been utilized to minimize the regression error between saturation indexes from model and SAR data and error between measured and modelled discharge flows. Utilizing this procedure, model parameters that rule soil moisture fluxes have been calibrated, obtaining not only a good match with remotely sensed data, but also an enhancement of model performance in flow prediction with respect to a previous calibration with river discharge data only. Copyright © 2006 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.     

Does the incorporation of process conceptualization and tracer data improve the structure and performance of a simple rainfall‐runoff model in a Scottish mesoscale catchment?

A geomorphological instantaneous unit hydrograph (GIUH) rainfall‐runoff model was applied in a 31 km² montane catchment in Scotland. Modelling was based on flow path length distributions derived from a digital terrain model (DTM). The model was applied in two ways; a single landscape unit response based on the DTM alone, and a two‐landscape unit response, which incorporated the distribution of saturated areas derived from field‐validated geographic information system (GIS) analysis based on a DTM and soil maps. This was to test the hypothesis that incorporation of process‐information would enhance the model performance. The model was applied with limited multiple event calibration to produce parameter sets which could be applied to a spectrum of events with contrasting characteristics and antecedent conditions. Gran alkalinity was used as a tracer to provide an additional objective measure for assessing model performance. The models captured the hydrological response dynamics of the catchment reasonably well. In general, the single landscape unit approach produced the best individual model performance statistics, though the two‐landscape unit approach provided a range of models, which bracketed the storm hydrograph response more realistically. There was a tendency to over‐predict the rising limb of the hydrograph, underestimate large storm event peaks and anticipate the hydrograph recession too rapidly. Most of these limitations could be explained by the simplistic assumptions embedded within the GIUH approach. The modelling also gave feasible predictions of stream water chemistry, though these could not be used as a basis for model rejection. Nevertheless, the study suggested that the approach has potential for prediction of hydrological response in ungauged montane headwater basins. Copyright © 2007 John Wiley & Sons, Ltd.     

Using targeted short‐term field investigations to calibrate and evaluate the structure of a hydrological model

This study combines the application of a hydrological model with the use of field data derived from short period measurement campaigns at two sites, one a low topography forested area and the other a steep grassland catchment. The main objective was to determine if the structure of the widely used Pitman model could be considered appropriate for simulating the field data. The model is typically applied at coarse spatial and temporal (1 month) scales, while the tests reported here use data from small catchments and are applied in a daily version of the model. The results demonstrate the importance of ensuring that field observations are measuring the same hydrological variables as the model simulations. At one study site, there was a mismatch in the soil moisture data that was corrected by incorporating a two‐layer soil algorithm into the model. The model results from both field sites identified the sensitivity of the model to assumptions about evaporative demands and indicate that the model structure is very sensitive to the potential evaporation inputs. The overall conclusion is that the model structure is generally appropriate for simulating the hydrological responses at the two sites, but that there remain some unresolved uncertainties about specific model components and the use of certain types of input data. The study lends support for the future development of a more complete daily version of this widely used model. Copyright © 2013 John Wiley & Sons, Ltd.     

On the role of spatial resolution on snow estimates using a process‐based snow model across a range of climatology and elevation

Hydrological processes in mountainous settings depend on snow distribution, whose prediction accuracy is a function of model spatial scale. Although model accuracy is expected to improve with finer spatial resolution, an increase in resolution comes with modelling costs related to increased computational time and greater input data and parameter information. This computational and data collection expense is still a limiting factor for many large watersheds. Thus, this work's main objective is to question which physical processes lead to loss in model accuracy with regard to input spatial resolution under different climatic conditions and elevation ranges. To address this objective, a spatially distributed snow model, iSnobal, was run with inputs distributed at 50‐m—our benchmark for comparison—and 100‐m resolutions and with aggregated (averaged from the fine to the large resolution) inputs from the 50‐m model to 100‐, 250‐, 500‐, and 750‐m resolution for wet, average, and dry years over the Upper Boise River Basin (6,963 km²), which spans four elevation bands: rain dominated, rain–snow transition, and snow dominated below treeline and above treeline. Residuals, defined as differences between values quantified with high resolution (>50 m) models minus the benchmark model (50 m), of simulated snow‐covered area (SCA) and snow water equivalent (SWE) were generally slight in the aggregated scenarios. This was due to transferring the effects of topography on meteorological variables from the 50‐m model to the coarser scales through aggregation. Residuals in SCA and SWE in the distributed 100‐m simulation were greater than those of the aggregated 750 m. Topographic features such as slope and aspect were simplified, and their gradient was reduced due to coarsening the topography from the 50‐ to 100‐m resolution. Therefore, solar radiation was overestimated, and snow drifting was modified and caused substantial SCA and SWE underestimation in the distributed 100‐m model relative to the 50‐m model. Large residuals were observed in the wet year and at the highest elevation band when and where snow mass was large. These results support that model accuracy is substantially reduced with model scales coarser than 50 m.