Conditioning temperature‐index model parameters on synoptic weather types for glacier melt simulations

Temperature‐index models are widely favoured as a pragmatic means of simulating glacier melt because of their generally good performance, computational simplicity and limited demands for in situ data. However, their coefficients are normally treated as temporally stationary, unrealistically assuming a constancy of the prevailing weather. We address this simplification by prescribing model coefficients as a function of synoptic weather type, in a procedure that utilizes reanalysis data and preserves the minimal data requirements of temperature‐index models. Using a cross‐validation procedure at Vestari Hagafellsjökull, Iceland, and Storglaciären, Sweden, we demonstrate that applying transient model coefficients, for three temperature‐index models, results in statistically significant increases in the skill with which melt is modelled: Median simulation improvements in the Nash–Sutcliffe efficiency coefficient of 7.3 and 23.6% are achieved when hourly and daily melt totals are evaluated respectively. Our weather‐type modelling approach also yields insight to processes driving parameter variability, revealing dependence that is consistent with a priori considerations of the surface energy balance. We conclude that incorporating weather types into temperature‐index models holds promise for improving their performance, as well as enhancing understanding variability in coefficient values. Copyright © 2014 John Wiley & Sons, Ltd.     

Initial results from a distributed,physically based model of glacier hydrology

This paper describes the development and testing of a distributed, physically based model of glacier hydrology. The model is used to investigate the behaviour of the hydrological system of Haut Glacier d'Arolla, Valais, Switzerland. The model has an hourly time-step and three main components: a surface energy balance submodel, a surface flow routing submodel and a subglacial hydrology submodel. The energy balance submodel is used to calculate meltwater production over the entire glacier surface. The surface routing submodel routes meltwater over the glacier surface from where it is produced to where it either enters the subglacial hydrological system via moulins or runs off the glacier surface. The subglacial hydrology submodel calculates water flow in a network of conduits, which can evolve over the course of a melt season simulation in response to changing meltwater inputs. The main model inputs are a digital elevation model of the glacier surface and its surrounding topography, start-of-season snow depth distribution data and meteorological data. Model performance is evaluated by comparing predictions with field measurements of proglacial stream discharge, subglacial water pressure (measured in a borehole drilled to the glacier bed) and water velocities inferred from dye tracer tests. The model performs best in comparison with the measured proglacial stream discharges, but some of the substantial features of the other two records are also reproduced. In particular, the model results show the high amplitude water pressure cycles observed in the borehole in the mid-melt season and the complex velocity/discharge hysteresis cycles observed in dye tracer tests. The results show that to model outflow hydrographs from glacierized catchments effectively, it is necessary to simulate spatial and temporal variations in surface melt rates, the delaying effect of the surface snowpack and the configuration of the subglacial drainage system itself. The model's ability to predict detailed spatial and temporal patterns of subglacial water pressures and velocities should make it a valuable tool for aiding the understanding of glacier dynamics and hydrochemistry. © 1998 John Wiley & Sons, Ltd.     

Using high‐resolution isotope data and alternative calibration strategies for a tracer‐aided runoff model in a nested catchment

Testing hydrological models over different spatio‐temporal scales is important for both evaluating diagnostics and aiding process understanding. High‐frequency (6‐hr) stable isotope sampling of rainfall and runoff was undertaken during 3‐week periods in summer and winter within 12 months of daily sampling in a 3.2‐km² catchment in the Scottish Highlands. This was used to calibrate and test a tracer‐aided model to assess the (a) information content of high‐resolution data, (b) effect of different calibration strategies on simulations and inferred processes, and (c) model transferability to <1‐km² subcatchment. The 6‐hourly data were successfully incorporated without loss of model performance, improving the temporal resolution of the modelling, and making it more relevant to the time dynamics of the isotope and hydrometric response. However, this added little new information due to old‐water dominance and riparian mixing in this peatland catchment. Time variant results, from differential split sample testing, highlighted the importance of calibrating to a wide range of hydrological conditions. This also provided insights into the nonstationarity of catchment mixing processes, in relation to storage and water ages, which varied markedly depending on the calibration period. Application to the nested subcatchment produced equivalent parameterization and performance, highlighting similarity in dominant processes. The study highlighted the utility of high‐resolution data in combination with tracer‐aided models, applied at multiple spatial scales, as learning tools to enhance process understanding and evaluation of model behaviour across nonstationary conditions. This helps reveal more fully the catchment response in terms of the different mechanistic controls on both wave celerites and particle velocities.     

Hydrochemistry of meltwaters draining a polythermal‐based,high‐Arctic glacier,south Svalbard: II. Winter and early Spring

The hydrochemistry of naled and upwelling water sampled from the forefields of Finsterwalderbreen, Svalbard, during spring are used for the first time to infer the hydrology of overwinter meltwaters at a polythermal‐based glacier. Hydrochemical variations in naled are explained in terms of different water sources and their chemical alteration during freezing. Two water sources to naled are identified: surficially routed snowmelt and subglacial water. Naled that results from the freezing of the former is enriched in atmospherically derived ions such as Na⁺ and Cl⁻, and is believed to be formed during winter warm periods. Naled of subglacial origin contains relatively high proportions of crustally derived solute. It reflects the freezing of subglacial meltwaters that continue to issue from a subterranean upwellling during winter. An increasing dominance of SO²⁻₄ Mg²⁺, Na⁺ and Cl⁻ in subglacial naled with increasing distance from the upwelling reflects the progressive freezing of this water body and the associated removal of Ca²⁺ and HCO by calcite precipitation. These spatial trends are accentuated by the leaching of soluble ions from the naled close to its source by subsequent upwelling waters. The chemistry of spring upwelling waters, also of subglacial origin, strongly reflects this process. Meltwater produced by geothermal heating of glacier basal ice is believed to be the principal source of water to the subglacial drainage system during winter. Solute acquisition by this meltwater is limited by a scarcity of proton suppliers. Evolution of this dilute meltwater carries an imprint of ion exchange processes. Some stored subglacial water from the end of the previous ablation season may supplement the basal meltwater component in early winter. Copyright © 2000 John Wiley & Sons, Ltd.     

A temperature‐precipitation‐based model of thirty‐year mean snowpack accumulation and melt in Oregon,USA

High‐resolution, spatially extensive climate grids can be useful in regional hydrologic applications. However, in regions where precipitation is dominated by snow, snowmelt models are often used to account for timing and magnitude of water delivery. We developed an empirical, nonlinear model to estimate 30‐year means of monthly snowpack and snowmelt throughout Oregon. Precipitation and temperature for the period 1971–2000, derived from 400‐m resolution PRISM data, and potential evapotranspiration (estimated from temperature and day length) drive the model. The model was calibrated using mean monthly data from 45 SNOTEL sites and accurately estimated snowpack at 25 validation sites: R² = 0·76, Nash‐Sutcliffe Efficiency (NSE) = 0·80. Calibrating it with data from all 70 SNOTEL sites gave somewhat better results (R² = 0·84, NSE = 0·85). We separately applied the model to SNOTEL stations located < 200 and ≥ 200 km from the Oregon coast, since they have different climatic conditions. The model performed equally well for both areas. We used the model to modify moisture surplus (precipitation minus potential evapotranspiration) to account for snowpack accumulation and snowmelt. The resulting values accurately reflect the shape and magnitude of runoff at a snow‐dominated basin, with low winter values and a June peak. Our findings suggest that the model is robust with respect to different climatic conditions, and that it can be used to estimate potential runoff in snow‐dominated basins. The model may allow high‐resolution, regional hydrologic comparisons to be made across basins that are differentially affected by snowpack, and may prove useful for investigating regional hydrologic response to climate change. Published in 2011 by John Wiley & Sons, Ltd.     

Non‐stationary hydrological model parameters: a framework based on SOM‐B

The application of stationary parameters in conceptual hydrological models, even under changing boundary conditions, is a common yet unproven practice. This study investigates the impact of non‐stationary model parameters on model performance for different flow indices and time scales. Therefore, a Self‐Organizing Map based optimization approach, which links non‐stationary model parameters with climate indices, is presented and tested on seven meso‐scale catchments in northern Germany. The algorithm automatically groups sub‐periods with similar climate characteristics and allocates them to similar model parameter sets. The climate indices used for the classification of sub‐periods are based on (a) yearly means and (b) a moving average over the previous 61 days. Classification b supports the estimation of continuous non‐stationary parameters. The results show that (i) non‐stationary model parameters can improve the performance of hydrological models with an acceptable growth in parameter uncertainty; (ii) some model parameters are highly correlated to some climate indices; (iii) the model performance improves more for monthly means than yearly means; and (iv) in general low to medium flows improve more than high flows. It was further shown how the gained knowledge can be used to identify insufficiencies in the model structure. Copyright © 2015 John Wiley & Sons, Ltd.     

Sensitivity analysis of temperature‐index melt simulations to near‐surface lapse rates and degree‐day factors at Vestari‐Hagafellsjökull,Langjökull,Iceland

The performance of temperature‐index melt models is particularly affected by the choice of near‐surface lapse rate used to determine the sum of positive daily temperatures at different elevations, and by the choice of factor used to relate this sum to the rate of melting. Data from the Langjökull ice cap are used in this study to quantify the influence of lapse‐rate and degree‐day factor variation on temperature‐index melt simulations. The lapse rate was significantly lower during summer than in spring or autumn, as a result of diabatic cooling, reducing boundary‐layer sensitivity to free‐air temperature change. The summer lapse rate was also significantly lower than the saturated adiabatic lapse rate. A sensitivity of approximately 600 mm water equivalent (w.e.) cumulative June–August melt per 0.1 °C 100 m^–1 change in lapse rate was found across a 500‐m altitude range. The sensitivity to a 1‐mm w.e. °C^–1 day^–1 change in degree‐day factors varied more: from approximately 500 mm w.e. cumulative summer melt at low elevation to approximately 200 mm w.e. at high elevation, reflecting the decline in melt rates associated with the greater persistence of snow with increasing altitude. The determination of a degree‐day factor for snow is complicated by the densification of the ageing snowpack, but the application of a parameterization for near‐surface density on the basis of albedo helped account for the development of snow water equivalence. Lapse rate was parameterized as a function of standardized anomalies in 750 hPa reanalysis temperature and significantly improved the simulation of cumulative summer melt compared with models applying the saturated adiabatic lapse rate. Copyright © 2012 John Wiley & Sons, Ltd.     

Modelling discharge through artesian springs based on a high‐resolution piezometric network

Artesian springs are localized aquifer outlets that originate when pressurized ground water is allowed to rise to the surface. Computing artesian discharge directly is often subject to practical difficulties such as restricted accessibility, abundant vegetation or slow flow rates. These circumstances call for indirect approaches to quantify flow. This paper presents a method to estimate ground water discharge through an upwelling spring by means of a three‐layer steady‐state groundwater flow model. Model inputs include on‐site measurements of vertical sediment permeability, sediment temperatures and hydraulic gradients. About 70 spring bed piezometers were used to carry out permeability tests within the spring sediments, as well as to quantify the hydraulic head at different depths below the discharge point. Sediment temperatures were measured at different depths and correlated to permeabilities in order to demonstrate the potential of temperature as a substitute for cumbersome slug tests. Results show that the spatial distribution of discharge through the spring bottom is highly heterogeneous, as sediment permeability varies by several orders of magnitude within centimetres. Sensitivity analyses imply that geostatistical interpolation is irrelevant to the results if field datasets come from a sufficiently high resolution of piezometric records. Copyright © 2013 John Wiley & Sons, Ltd.     

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

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

Interannual variability in glacier contribution to runoff from a high‐elevation Andean catchment: understanding the role of debris cover in glacier hydrology

We present a field‐data rich modelling analysis to reconstruct the climatic forcing, glacier response, and runoff generation from a high‐elevation catchment in central Chile over the period 2000–2015 to provide insights into the differing contributions of debris‐covered and debris‐free glaciers under current and future changing climatic conditions. Model simulations with the physically based glacio‐hydrological model TOPKAPI‐ETH reveal a period of neutral or slightly positive mass balance between 2000 and 2010, followed by a transition to increasingly large annual mass losses, associated with a recent mega drought. Mass losses commence earlier, and are more severe, for a heavily debris‐covered glacier, most likely due to its strong dependence on snow avalanche accumulation, which has declined in recent years. Catchment runoff shows a marked decreasing trend over the study period, but with high interannual variability directly linked to winter snow accumulation, and high contribution from ice melt in dry periods and drought conditions. The study demonstrates the importance of incorporating local‐scale processes such as snow avalanche accumulation and spatially variable debris thickness, in understanding the responses of different glacier types to climate change. We highlight the increased dependency of runoff from high Andean catchments on the diminishing resource of glacier ice during dry years.     

Development of a soil moisture‐based distributed hydrologic model for determining hydrologically based critical source areas

A simple grid cell‐based distributed hydrologic model was developed to provide spatial information on hydrologic components for determining hydrologically based critical source areas. The model represents the critical process (soil moisture variation) to run‐off generation accounting for both local and global water balance. In this way, it simulates both infiltration excess run‐off and saturation excess run‐off. The model was tested by multisite and multivariable evaluation on the 50‐km² Little River Experimental Watershed I in Georgia, U.S. and 2 smaller nested subwatersheds. Water balance, hydrograph, and soil moisture were simulated and compared to observed data. For streamflow calibration, the daily Nash‐Sutcliffe coefficient was 0.78 at the watershed outlet and 0.56 and 0.75 at the 2 nested subwatersheds. For the validation period, the Nash‐Sutcliffe coefficients were 0.79 at the watershed outlet and 0.85 and 0.83 at the 2 subwatersheds. The per cent bias was less than 15% for all sites. For soil moisture, the model also predicted the rising and declining trends at 4 of the 5 measurement sites. The spatial distribution of surface run‐off simulated by the model was mainly controlled by local characteristics (precipitation, soil properties, and land cover) on dry days and by global watershed characteristics (relative position within the watershed and hydrologic connectivity) on wet days when saturation excess run‐off was simulated. The spatial details of run‐off generation and travel time along flow paths provided by the model are helpful for watershed managers to further identify critical source areas of non‐point source pollution and develop best management practices.     

Multi‐site calibration using a grid‐based event rainfall–runoff model: a case study of the upstream areas of the Nakdong River basin in Korea

Most runoff analyses using a grid‐based distributed model use one parameter group calibrated at the outlet of a watershed, instead of dividing the watershed into subwatersheds. Significant differences between the observed value and the simulation result of the subwatersheds can occur if just one parameter group is used in all subwatersheds that have different hydrological characteristics from each other. Therefore, to improve the simulation results of the subwatersheds within a watershed, a model calibrated at every subwatershed needs to be used to reflect the characteristics of each subwatershed. In this study, different parameter groups were set up for one or two sites using a distributed model, the GRM (Grid based Rainfall‐runoff Model), and the evaluations were based on the results of rainfall–runoff analysis, which uses a multi‐site calibration (MSC) technique to calibrate the model at the outlet of each site. The Hyangseok watershed in Naeseong River, which is a tributary of Nakdong River in Korea, was chosen as the study area. The watershed was divided into five subwatersheds each with a subwatershed outlet that was applied to the calibration sites . The MSC was applied for five cases. When a site was added for calibration in a watershed, the runoff simulation showed better results than the calibration of only one site at the most downstream area of the watershed. The MSC approach could improve the simulation results on the calibrated sites and even on the non‐calibrated sites, and the effect of MSC was improved when the calibrated site was closer to the runoff site. Copyright © 2014 John Wiley & Sons, Ltd.     

Seasonal evolution of meltwater generation,storage and discharge at a non‐temperate glacier in Svalbard

In glacierized catchments, meteorological inputs driving surface melting are translated into runoff outputs mediated by the glacier hydrological system: analysis of the relationship between meteorology and diurnal and seasonal patterns of runoff should reflect the functioning of that system, with the role of meltwater storage likely to be of particular importance. Daily meltwater storage is determined for a glacier at 78 °N in the Svalbard archipelago, by comparing inputs calculated from a surface energy balance model with measured outputs (proglacial discharge). Solar radiation, air temperature, wind speed and proglacial discharge are then analysed by regression and time‐series methods, in order to assess the meteorology–discharge relationship and its variation at diurnal and seasonal time‐scales. The recorded discharge time‐series can be divided into two contrasting intervals: up to early August, proglacial discharge was high and variable, mean hydrographs showed little indication of diurnal cycling, ARIMA models of discharge indicated a non‐seasonal, moving‐average generating process, and there was a net loss of meltwater from storage; from early August, proglacial discharge was low and relatively invariable, but with clearer diurnal cycles, regression models of discharge showed substantially improved correlations with air temperature and solar radiation, ARIMA models indicated a non‐seasonal, autoregressive generating process, and eventually a seasonal component, and there was a net gain in meltwater storage. The transition between the two periods is brief compared with the duration of the melt season. The runoff response to meteorology therefore lacks the strongly progressive element previously identified in mid‐latitude glacierized catchments. In particular, the glacier hydrological system only appears responsive to diurnal forcing following the depletion of the seasonal snowpack meltwater store. Copyright © 2001 John Wiley & Sons, Ltd.     

A distributed parameter model of a frame pin‐supported wall structure

Many reinforced‐concrete frames collapse via a soft‐story mechanism during severe earthquakes. Such collapses are mainly attributed to concentrated deformation in a soft story. Deformation control is thus important in preventing collapse. The frame pin‐supported wall structure is a type of rocking structure that releases constraints at the bottom of the wall. Previous research has obtained good results for the deformation control of this type of structure. However, the interior forces and strength demands of the pin‐supported wall have not been systematically explored. In this paper, a distributed parameter model is developed to investigate the strength demand of the wall in a frame pin‐supported wall structure. In the model, the pin‐supported wall is simplified as a bending beam and the frame is simplified as a shear beam. The two beams are joined by distributed shear connectors, so that the shear force can be transferred at any location on the interface. The model can be solved using differential equations based on equilibrium and compatibility. The accuracy of the model is verified using SAP2000 (Computers and Structures Inc., Berkeley, CA, USA). Displacement distribution of the structure and distributions of the moment and shear force within the pin‐supported wall are obtained for two typical external force profiles. It is found that the pin‐supported wall can effectively reduce the drift concentration factor. Distributions of the displacement, moment, and shear force are closely correlated with the relative stiffness of the wall and frame. Finally, recommendations on the stiffness and strength of a pin‐supported wall are made. Copyright © 2015 John Wiley & Sons, Ltd.     

Application of a data‐based mechanistic modelling (DBM) approach for predicting runoff generation in semi‐arid regions

This paper addresses the application of a data‐based mechanistic (DBM) modelling approach using transfer function models (TFMs) with non‐linear rainfall filtering to predict runoff generation from a semi‐arid catchment (795 km²) in Tanzania. With DBM modelling, time series of rainfall and streamflow were allowed to suggest an appropriate model structure compatible with the data available. The model structures were evaluated by looking at how well the model fitted the data, and how well the parameters of the model were estimated. The results indicated that a parallel model structure is appropriate with a proportion of the runoff being routed through a fast flow pathway and the remainder through a slow flow pathway. Finally, the study employed a Generalized Likelihood Uncertainty Estimation (GLUE) methodology to evaluate the parameter sensitivity and predictive uncertainty based on the feasible parameter ranges chosen from the initial analysis of recession curves and calibration of the TFM. Results showed that parameters that control the slow flow pathway are relatively more sensitive than those that control the fast flow pathway of the hydrograph. Within the GLUE framework, it was found that multiple acceptable parameter sets give a range of predictions. This was found to be an advantage, since it allows the possibility of assessing the uncertainty in predictions as conditioned on the calibration data and then using that uncertainty as part of the decision‐making process arising from any rainfall‐runoff modelling project. Copyright © 2001 John Wiley & Sons, Ltd.     

The effects of topographic depressions on multiscale overland flow connectivity: A high‐resolution spatiotemporal pattern analysis approach based on connectivity statistics

In watershed modelling, the traditional practice of arbitrarily filling topographic depressions in digital elevation models has raised concerns. Advanced high‐resolution remote sensing techniques, including airborne scanning laser altimetry, can identify naturally occurring depressions that impact overland flow. In this study, we used an ensemble physical and statistical modelling approach, including a 2D hydraulic model and two‐point connectivity statistics, to quantify the effects of depressions on high‐resolution overland flow patterns across spatial scales and their temporal variations in single storm events. Computations for both models were implemented using graphic processing unit‐accelerated computing. The changes in connectivity statistics for overland flow patterns between airborne scanning laser altimetry‐derived digital elevation models with (original) and without (filled) depressions were used to represent the shifts of overland flow response to depressions. The results show that depressions can either decrease or increase (to a lesser degree and shorter duration) the probability that any two points (grid locations) are hydraulically connected by overland flow pathways. We used macro‐connectivity states (Φ) as a watershed‐specific indicator to describe the spatiotemporal thresholds of connectivity variability caused by depressions. Four states of Φ are identified in a studied watershed, and each state represents different magnitudes of connectivity and connectivity changes (caused by depressions). The magnitude of connectivity variability corresponds to the states of Φ, which depend on the topological relationship between depressions, the rising/recession limb, and the total rainfall amount in a storm event. In addition, spatial distributions of connectivity variability correlate with the density of depression locations and their physical structures, which cause changes in streamflow discharge magnitude. Therefore, this study suggests that depressions are “nontrivial” in watershed modelling, and their impacts on overland flow should not be neglected. Connectivity statistics at different spatial scales and time points within a watershed provide new insights for characterizing the distributed and accumulated effects of depressions on overland flow.     

Do not only connect: a model of infiltration‐excess overland flow based on simulation

The paper focusses on connectivity in the context of infiltration‐excess overland flow and its integrated response as slope‐base overland flow hydrographs. Overland flow is simulated on a sloping surface with some minor topographic expression and spatially differing infiltration rates. In each cell of a 128 × 128 grid, water from upslope is combined with incident rainfall to generate local overland flow, which is stochastically routed downslope, partitioning the flow between downslope neighbours. Simulations show the evolution of connectivity during simple storms. As a first approximation, total storm runoff is similar everywhere, discharge increasing proportionally with drainage area. Moderate differences in plan topography appear to have only a second‐order impact on hydrograph form and runoff amount. Total storm response is expressed as total runoff, runoff coefficient or total volume infiltrated; each plotted against total storm rainfall, and allowing variations in average gradient, overland flow roughness, infiltration rate and storm duration. A one‐parameter algebraic expression is proposed that fits simulation results for total runoff, has appropriate asymptotic behaviour and responds rationally to the variables tested. Slope length is seen to influence connectivity, expressed as a scale distance that increases with storm magnitude and can be explicitly incorporated into the expression to indicate runoff response to simple events as a function of storm size, storm duration, slope length and gradient. The model has also been applied to a 10‐year rainfall record, using both hourly and daily time steps, and the implications explored for coarser scale models. Initial trails incorporating erosion continuously update topography and suggest that successive storms produce an initial increase in erosion as rilling develops, while runoff totals are only slightly modified. Other factors not yet considered include the dynamics of soil crusting and vegetation growth. Copyright © 2014 John Wiley & Sons, Ltd.     

Analysis of geomorphologic and hydrological characteristics in watershed saturated areas using topographic‐index threshold and geomorphology‐based runoff model

The objective of this paper is to investigate the variation of geomorphology and runoff characteristics in saturated areas under different partial contributing area (PCA) conditions. Geomorphologic information and hydrologic records from two mid‐size watersheds in northern Taiwan were selected for analysis. The PCA ratio in the watershed during a storm was assumed equal to the ratio of the surface‐flow volume to the direct runoff volume from measured hydrologic data. The extents of PCA regions were then determined by using a topographic‐index threshold. Consequently, the geomorphologic factors in saturated and unsaturated areas could be calculated using a digital elevation model, and these factors could then be linked to a geomorphology‐based IUH model for runoff simulation, which can consider both the surface‐ and subsurface‐flow processes in saturated and unsaturated areas, respectively. The results show that geomorphologic characteristics in the saturated areas vary significantly with different PCA ratios especially for higher order streams. A large PCA ratio results in a sharp hydrograph because the quick surface flow dominates the runoff process, whereas the hydrologic response in a low PCA case is dominated by the delayed subsurface flow. Copyright © 2007 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.