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Summary: Hillslope hydrological response to precipitation is extremely complex and poorly modeled. One possible approach for reducing the complexity of hillslope response and its mathematical parameterization is to look for macroscale hydrological behavior. Hillslope threshold response to storm precipitation is one such macroscale behavior observed at field sites across the globe. Nevertheless, the relative controls on the precipitation–discharge threshold poorly known. This paper presents a combined model development, calibration and testing experiment study to investigate the primary controls on the observed precipitation–discharge threshold relationship. We focus on the dominant hydrological processes revealed in part one of this two-part paper and with our new numerical model, replicate the threshold response seen in the discharge record and other hydrometric and tracer data available at the site. We then present a series of virtual experiments designed to probe the controls on the threshold response. We show that the threshold behavior is due to a combination of environmental (storm spacing and potential evapotranspiration) and geologic (bedrock permeability and bedrock topography) factors. The predicted precipitation–discharge threshold subsumes the complexity of plot-scale soil water response. We then demonstrate its use for prediction of whole-catchment storm discharge at other first order catchments at Maimai and the HJ Andrews Experimental Forest in Oregon. [ABSTRACT FROM AUTHOR]

An integrated groundwater/surface water hydrological model with a 1 km2 grid has been constructed for Denmark covering 43,000 km2. The model is composed of a relatively simple root zone component for estimating the net precipitation, a comprehensive three-dimensional groundwater component for estimating recharge to and hydraulic heads in different geological layers, and a river component for streamflow routing and calculating stream–aquifer interaction. The model was constructed on the basis of the MIKE SHE code and by utilising comprehensive national databases on geology, soil, topography, river systems, climate and hydrology. The present paper describes the modelling process for the 7330 km2 island of Sjælland with emphasis on the problems experienced in combining the classical paradigms of groundwater modelling, such as inverse modelling of steady-state conditions, and catchment modelling, focussing on dynamic conditions and discharge simulation. Three model versions with different assumptions on input data and parameter values were required until the performance of the final, according to pre-defined accuracy criteria, model was evaluated as being satisfactory. The paper highlights the methodological issues related to establishment of performance criteria, parameterisation and assessment of parameter values from field data, calibration and validation test schemes. Most of the parameter values were assessed directly from field data, while about 10 ‘free’ parameters were subject to calibration using a combination of inverse steady-state groundwater modelling and manual trial-and-error dynamic groundwater/surface water modelling. Emphasising the importance of tests against independent data, the validation schemes included combinations of split-sample tests (another period) and proxy-basin tests (another area). [Copyright &y& Elsevier]

Extreme precipitation can cause flooding and may result in great economic losses and deaths. The return level is a commonly used measure of extreme precipitation events and is required for hydrological engineer designs, including those of sewerage systems, dams, reservoirs and bridges. In this paper, we propose a two-step method to estimate the return level and its uncertainty for a study region. In the first step, we use the generalized extreme value distribution, the L-moment method and the stationary bootstrap to estimate the return level and its uncertainty at the site with observations. In the second step, a spatial model incorporating the heterogeneous measurement errors and covariates is trained to estimate return levels at sites with no observations and to improve the estimates at sites with limited information. The proposed method is applied to the daily rainfall data from 273 weather stations in the Haihe river basin of North China. We compare the proposed method with two alternatives: the first one is based on the ordinary Kriging method without measurement error, and the second one smooths the estimated location and scale parameters of the generalized extreme value distribution by the universal Kriging method. Results show that the proposed method outperforms its counterparts. We also propose a novel approach to assess the two-step method by comparing it with the at-site estimation method with a series of reduced length of observations. Estimates of the 2-, 5-, 10-, 20-, 50- and 100-year return level maps and the corresponding uncertainties are provided for the Haihe river basin, and a comparison with those released by the Hydrology Bureau of Ministry of Water Resources of China is made. [ABSTRACT FROM AUTHOR]

The allocation of the water resources of Southeastern United States have given rise to inter-state political conflicts for decades. The limited water resource are not only required to satisfy the demand of rapidly growing urban areas, but also the power industry, recreational needs and the environment. Although water resource variability has been attributed to various teleconnections, knowledge of long-term water resource availability is limited. In this paper historical (1952–2014) precipitation and streamflow data from 18 basins in southeast United States are analyzed for long-term changes in the hydroclimatology, possibly brought by urbanization, climate change and/or changed precipitation patterns. A Pettitt test indicates a change in the precipitation-runoff relationship in the late 1990s. After the shift, basin records indicate decreased precipitation storage and consequently increased streamflow. [ABSTRACT FROM AUTHOR]

Despite the tremendous improvement made in numerical weather and climate models over the recent years, the forecasts generated by those models still cannot be used directly for hydrological forecasting. A post-processor like the Ensemble Pre-Processor (EPP) developed by U.S. National Weather Service must be used to remove various biases and to extract useful predictive information from those forecasts. In this paper, we investigate how different designs of canonical events in the EPP can help post-process precipitation forecasts from the Global Ensemble Forecast System (GEFS) and Climate Forecast System Version 2 (CFSv2). The use of canonical events allow those products to be linked seamlessly and then the post-processed ensemble precipitation forecasts can be generated using the Schaake Shuffle procedure. We used the post-processed ensemble precipitation forecasts to drive a distributed hydrological model to obtain ensemble streamflow forecasts and evaluated those forecasts against the observed streamflow. We found that the careful design of canonical events can help extract more useful information, especially when up-to-date observed precipitation is used to setup the canonical events. We also found that streamflow forecasts using post-processed precipitation forecasts have longer lead times and higher accuracy than streamflow forecasts made by traditional Extend Streamflow Prediction (ESP) and the forecasts based on original GEFS and CFSv2 precipitation forecasts. [ABSTRACT FROM AUTHOR]

Summary The multisensor Quantitative Precipitation Estimates (MQPEs) created by the US National Weather Service (NWS) are subject to a non-stationary bias. This paper quantifies the impacts of climatological adjustment of MQPEs alone, as well as the compound impacts of adjustment and model calibration, on the accuracy of simulated flood peak magnitude and that in detecting flood events. Our investigation is based on 19 watersheds in the mid-Atlantic region of US, which are grouped into small (<500 km 2 ) and large (>500 km 2 ) watersheds. NWS archival MQPEs over 1997–2013 for this region are adjusted to match concurrent gauge-based monthly precipitation accumulations. Then raw and adjusted MQPEs serve as inputs to the NWS distributed hydrologic model-threshold frequency framework (DHM-TF). Two experiments via DHM-TF are performed. The first one examines the impacts of adjustment alone through uncalibrated model simulations, whereas the second one focuses on the compound effects of adjustment and calibration on the detection of flood events. Uncalibrated model simulations show broad underestimation of flood peaks for small watersheds and overestimation those for large watersheds. Prior to calibration, adjustment alone tends to reduce the magnitude of simulated flood peaks for small and large basins alike, with 95% of all watersheds experienced decline over 2004–2013. A consequence is that a majority of small watersheds experience no improvement, or deterioration in bias (0% of basins experiencing improvement). By contrast, most (73%) of larger ones exhibit improved bias. Outcomes of the detection experiment show that the role of adjustment is not diminished by calibration for small watersheds, with only 25% of which exhibiting reduced bias after adjustment with calibrated parameters. Furthermore, it is shown that calibration is relatively effective in reducing false alarms (e.g., false alarm rate is down from 0.28 to 0.19 after calibration for small watersheds with calibrated parameters); but its impacts on detection rate are mixed. As an example, the detection rate of 2-Y events in fact declines for small watersheds after calibration is performed (from 0.4 to 0.28, and from 0.28 to 0.19 with raw and adjusted MQPE, respectively). These mixed outcomes underscore the complex interplays between errors in MQPEs, conditional bias in the reference gauge-based analysis, and structural deficiencies of the hydrologic model. [ABSTRACT FROM AUTHOR]

Summary: Zekai Sen provides several comments on our paper (Chang, C.L., Lo, S.L., Yu, S.L., 2005. Applying fuzzy theory and genetic algorithm to interpolate precipitation. J. Hydrol. 314, 92–104). More discussions could create different opinions and ideas, and they are all very significant for the development of methodology or study application. However, Sen has some misunderstanding on our paper. The following discussions follow the order of Sen’s comments. [Copyright &y& Elsevier]

Summary This paper analyses and compares rainfall erosivity values that were computed with five different kinetic energy-intensity ( KE-I ) relationships using the 0.5-h and 1-h maximum rainfall intensities ( I 30 and I 60 , respectively). The KE-I relationships included three exponential equations (Brown and Foster, 1987 (BF); McGregor et al., 1995 (MG); van Dijk et al., 2002 (VD)), a logarithmic equation (Wischmeier and Smith, 1958 (WS)) and a linear equation (Hudson, 1961 (HU)). The KE-I relationships were used to compute rainfall erosivity from pluviographic records of 30 sites that are located in central Chile. A total of 415 years of data were used, and more than 18,000 storms were identified. The results showed that among the exponential equations, the MG relationship yielded erosivity results that were statistically identical to the VD and the BF relationships. However, when comparing the VD and the BF relationships, significant differences in erosivity were found, which showed that the exponential equation is highly sensitive to changes in its regression parameters and is therefore site-specific. Among all of the relationships, the WS logarithmic equation yielded the largest erosivity estimates; however, they were statistically equal to the estimates made with the MG and the VD relationships but were not statistically equal to estimates predicted by the BF relationship. In contrast, in comparison to the other equations, the HU linear relationship yielded significantly smaller erosivity values. Conversely, regardless of the KE-I relationship and the site, computing erosivity using I 60 provided erosivity estimates that are 10% smaller than those obtained using I 30 . The relative size of the erosivity estimates is due to the relative values of I 60 and I 30 ; on average I 60 was 10% smaller than I 30 at the study sites. Finally, because the rainfall erosivity estimates at the study sites were highly affected by the type of KE-I relationship, these results demonstrate that selecting an appropriate KE-I relationship is crucial for accurately estimating erosivity. These differences were augmented because of the typically low rainfall intensities at the study sites. Under this condition, the differences between the KE-I relationships were greatest. However, with higher rainfall intensities, all of the KE-I relationships provide similar kinetic energy estimates, which makes the selection of the KE-I relationship less important than the use of a reliable I 30 value for computing rainfall erosivity. [ABSTRACT FROM AUTHOR]

Summary A new technique for gauge-only precipitation analysis for improved estimation of heavy-to-extreme precipitation is described and evaluated. The technique is based on a novel extension of classical optimal linear estimation theory in which, in addition to error variance, Type-II conditional bias (CB) is explicitly minimized. When cast in the form of well-known kriging, the methodology yields a new kriging estimator, referred to as CB-penalized kriging (CBPK). CBPK, however, tends to yield negative estimates in areas of no or light precipitation. To address this, an extension of CBPK, referred to herein as extended conditional bias penalized kriging (ECBPK), has been developed which combines the CBPK estimate with a trivial estimate of zero precipitation. To evaluate ECBPK, we carried out real-world and synthetic experiments in which ECBPK and the gauge-only precipitation analysis procedure used in the NWS’s Multisensor Precipitation Estimator (MPE) were compared for estimation of point precipitation and mean areal precipitation (MAP), respectively. The results indicate that ECBPK improves hourly gauge-only estimation of heavy-to-extreme precipitation significantly. The improvement is particularly large for estimation of MAP for a range of combinations of basin size and rain gauge network density. This paper describes the technique, summarizes the results and shares ideas for future research. [ABSTRACT FROM AUTHOR]

Summary: This paper presents an assessment of the impacts of climate change on a series of indicators of hydrological regimes across the global domain, using a global hydrological model run with climate scenarios constructed using pattern-scaling from 21 CMIP3 (Coupled Model Intercomparison Project Phase 3) climate models. Changes are compared with natural variability, with a significant change being defined as greater than the standard deviation of the hydrological indicator in the absence of climate change. Under an SRES (Special Report on Emissions Scenarios) A1b emissions scenario, substantial proportions of the land surface (excluding Greenland and Antarctica) would experience significant changes in hydrological behaviour by 2050; under one climate model scenario (Hadley Centre HadCM3), average annual runoff increases significantly over 47% of the land surface and decreases over 36%; only 17% therefore sees no significant change. There is considerable variability between regions, depending largely on projected changes in precipitation. Uncertainty in projected river flow regimes is dominated by variation in the spatial patterns of climate change between climate models (hydrological model uncertainty is not included). There is, however, a strong degree of consistency in the overall magnitude and direction of change. More than two-thirds of climate models project a significant increase in average annual runoff across almost a quarter of the land surface, and a significant decrease over 14%, with considerably higher degrees of consistency in some regions. Most climate models project increases in runoff in Canada and high-latitude eastern Europe and Siberia, and decreases in runoff in central Europe, around the Mediterranean, the Mashriq, central America and Brasil. There is some evidence that project change in runoff at the regional scale is not linear with change in global average temperature change. The effects of uncertainty in the rate of future emissions is relatively small. [Copyright &y& Elsevier]

Summary: The Mekong River Basin in South East Asia has experienced in recent decades large inter-annual variations between large floods and severe droughts. The general perception is that climate variability has increased in the region. In this paper our aim was to examine the role of El Niño-Southern Oscillation (ENSO) on these recent climate variations. To achieve our aim, we analysed the influence of ENSO on precipitation (over period 1981–2005) and discharge (1910–2008) by using spatial GIS analyses and statistical methods, such as linear correlations, spectral analysis and stochastic regression models. We found that the Mekong’s hydrology was significantly influenced by ENSO, particularly in the decay year of ENSO events. The influence was strongest in the southern parts of the basin. The precipitation and discharge decreased (increased) during El Niño (La Niña) and the annual flood period was shorter (longer) during El Niño (La Niña). We found also decadal variations in the ENSO-discharge relationship. Our findings indicate high potential for developing prediction methods for ENSO induced hydrological anomalies. These findings may significantly improve the possibility of preparing for extreme hydrological events, either drought or exceptional floods, and thus potentially improve water resources management in the basin. [ABSTRACT FROM AUTHOR]

Summary: Many methods have been worked out to estimate precipitation rainfall from meteorological satellite radiances sensed by microwave (on-board low-orbiting satellites) and infrared (on-board geostationary satellites) sensors. Validation of such estimated precipitation products have become more and more important. This paper describes the validation study limited to the geographical area of Hungary of three satellite-based rain estimates for hydrology purposes. These estimates were recently developed in the frame of the Hydrology SAF project, launched by EUMETSAT (European Organization for the Exploitation of Meteorological Satellites) in 2005. While two of these products were estimated using microwave-based method, one of them was estimated using a combination of infrared (IR) and microwave (MW) radiances. The validation studies carried out at the Hungarian Meteorological Service covered statistical analyses of instantaneous values over monthly periods and case-by-case analyses. Statistics were evaluated for every month, and focus was given to the differences between summer and winter to depict the seasonal features of the rainfall estimates. All three products gave best results in summer months (probability of detection was between 0.5 and 0.7 compared to 0.1 and 0.2 in winter; and false alarm rate was 0.3–0.6 in summer compared to 0.8–0.9 in winter), due to the much easier detection of deep convective clouds by satellites. Correlation was between 0.2 and 0.4 in summer months for every product, whereas in the winter it was under 0.1. In case studies, the location of convective cells formed in the summer was reflected well by MW observation; the combined products showed overestimated area of low precipitation. Significant underestimation of heavy rainfall (mean error of −15 to 20mm/h) was found in the case of the infrared–microwave (IR–MW) mixed product. According to case studies, the MW-based retrievals overestimated high precipitation intensities of the convective cells. However, in the monthly statistics the mean error was negative (−5 to 10mm/h) which demonstrated that the overestimation was not systematic. Winter results revealed that light rainfall had low probability of detection both by MW and IR–MW combined measurements. However, the case study presented for a winter day showed for all the three products well detection of liquid precipitation. Overall results exposed more reliable detection of convective than stratiform precipitation. [Copyright &y& Elsevier]

Summary: The relationship between δ2H and δ18O in precipitation at a site, known as the local meteoric water line (LMWL), is normally defined using an ordinary least squares regression (OLSR) which gives equal weighting to all data points regardless of the precipitation amount they represent. However, smaller precipitation amounts are more likely to have a lower D-excess due to re-evaporation of raindrops below the cloud-base or biases in the sampling method. In this paper we present an equation for a precipitation amount weighted least squares regression (PWLSR) that will correct these biases for use in groundwater and surface hydrology applications. New LMWL equations are presented for Australian sites in the Global Network of Isotopes in Precipitation (GNIP), where the PWLSR consistently produces a LMWL with a larger gradient than the OLSR. Perth and Alice Springs exhibit the largest change in slope. This is consistent with the higher frequency of small monthly precipitation amounts with low D-excess values occurring at these sites in summer for Perth and throughout the year for Alice Springs. The PWLSR method was also applied to 288 stations in the GNIP data base (N >36) and the difference between the slopes of the LMWLs (Δa =slopePWLSR–slopeOLSR) calculated for these stations. The mean change in slope, Δa was 0.12 with 56% of sites showing an increase in slope or positive Δa value and 44% having a decrease in slope or negative Δa. Sites with Mediterranean climates showed the greatest increase in slope. The magnitude of the change in slope followed some general trends showing a positive correlation with average δ2H and δ18O composition and rainfall variability, and negative correlation with period of record (N). [ABSTRACT FROM AUTHOR]

Summary: This paper presents isotopic composition (δ18O, δ2H) of groundwater, lagoon water, and seawater collected in a coastal lagoon system in Southern Brazil as a tool to define groundwater sources within a permeable barrier that separates the lagoon from the ocean. The isotopic signature of the barrier groundwater differs both from the isotopic composition of lagoon water and seawater. The groundwater is significantly lighter, indicating that the major recharge source to the barrier is precipitation, rather than lagoon water. In the southern and central part of the barrier no interaction of groundwater with lagoon water was observed. In the northern part, however, lagoon water intrusion into the barrier was identified. This effect is apparently caused by different vegetation types on the barrier influencing subsurface hydrological processes. The central and the southern areas are characterised by natural dune vegetation (high infiltration, low evapotranspiration rates) whereas the northern part is covered by extensive pine tree plantations (low infiltration, high evapotranspiration rates). The presence of pine trees may enhance lagoon and seawater intrusion into the shallow aquifer and decrease fresh submarine groundwater discharge. [ABSTRACT FROM AUTHOR]

Summary: This paper provides a general overview of changes in flooding caused by climate change in Finland for the periods 2010–2039 and 2070–2099. Changes in flooding were evaluated at 67 sites in Finland with variable sizes of runoff areas using a conceptual hydrological model and 20 climate scenarios from both global and regional climate models with the delta change approach. Floods with a 100-year return period were estimated with frequency analysis using the Gumbel distribution. At four study sites depicting different watershed types and hydrology, the inundation areas of the 100-year floods were simulated with a 2D hydraulic model. The results demonstrate that the impacts of climate change are not uniform within Finland due to regional differences in climatic conditions and watershed properties. In snowmelt-flood dominated areas, annual floods decreased or remained unchanged due to decreasing snow accumulation. On the other hand, increased precipitation resulted in growing floods in major central lakes and their outflow rivers. The changes in flood inundation did not linearly follow the changes in 100-year discharges, due to varying characteristics of river channels and floodplains. The results highlight the importance of comprehensive climatological and hydrological knowledge and the use of several climate scenarios in estimation of climate change impacts on flooding. Generalisations based on only a few case studies, or large scale flood assessments using only a few climate scenarios should be avoided in countries with variable hydrological conditions. [ABSTRACT FROM AUTHOR]

Summary: Deriving high quality daily rainfall estimates are required not only for successful hydrological modelling but also for its application in ungauged basins. At present, there are two resources to estimate rainfall fields: raingauge stations and remote sensing devices (such as satellites and radar). The observations obtained from raingauges are accurate and reliable, but are usually limited to interpolate daily rainfall as input into hydrological models by spatial coverage. Hence, the areal precipitation estimates constructed solely by raingauges exhibit a great deal of uncertainty where the raingauge network is sparse, especially for local convective events. Satellite-based gridded precipitation estimates are produced at high temporal (3h) and reasonably high spatial resolution (0.25°×0.25°). However, the accuracy of these surfaces is lower than using ground based observations. The main aim of this paper is to present a novel method of generating a synthesis of a discrete set of point raingauge observations and a satellite derived rainfall product. This method stems from some ideas of data assimilation and focuses on the difference between gridded and point data. A nonparametric kernel smoothing method is employed in this merging strategy with emphasis on discontinuity correction and spatial interpolation adapting for sparse design. A cross-validation study was undertaken to blend observations from the Australian raingauge network and satellite derived TRMM Multisatellite Precipitation Analysis (TMPA) 3B42. In order to test the proposed method, several methods including ordinary kriging and cokriging were trialled. The comparison showed that the bias results produced by the proposed method were far superior to the other methods trialled and other error statistics such as root mean square error were comparable or better (although the kriging methods tended to perform better in densely gauged areas). In particular, the bias of the proposed method was reduced consistently over the whole country, whilst the kriging methods trialled produced relatively large biases across the country leading to near overall zero bias. In addition to improving quantitative efficiency, the estimated rainfall field showed good visual performance in the presence of sparse gauge stations. [Copyright &y& Elsevier]

Summary: Proglacial areas are expanding globally as a consequence of sustained glacier retreat, but there are very few studies focusing on their hydrology. This paper examines the surface and atmospheric water fluxes over a complete annual cycle in the proglacial area of the Svalbard glacier Finsterwalderbreen (77N), through a combination of field measurements, physical modelling and statistical estimation. Precipitation in winter (226mm) exceeded that in summer (29mm), and over the course of the annual cycle total precipitation exceeded total evaporation (141mm), although evaporative outputs from the proglacial area exceeded precipitation inputs during the dry summer. Runoff was highly irregular in time, with much of the total annual flow being concentrated into two relatively brief, early-to-mid summer intervals, the greater of which was characterised by the release of subglacially-stored water. Water fluxes were dominated by meltwater supply from the glacier: the total annual glacial runoff (7.38×107 m3) was an order-of-magnitude greater than the precipitation flux delivered directly to the proglacial area, and two orders-of-magnitude greater than evaporative losses from it. Outputs of meltwater from the proglacial area were not significantly different from inputs over the duration of the melt season, so surface water storage does not appear to be important in the studied catchment, despite episodes of flooding over shorter timescales. A synthesised description of the seasonal hydrological cycle in Finsterwalderbreen’s proglacial area is presented, which can be viewed as a set of hydrological boundary conditions for comparable high-latitude locations. Further study of these conditions is required, because the challenging nature of hydrometry in the high-latitudes has the potential to limit progress in understanding environmental change there. [Copyright &y& Elsevier]

Summary: An attempt was made to improve the application of a lumped parameter model in the unsaturated soils planted with different crops. A first step of such an improvement was shown in Stumpp et al. [Stumpp, C., Maloszewski, P., Stichler, W., Fank, J., 2009. Application of the environmental isotope δ18O to study the water flow in unsaturated soils planted with different crops: 1. Case study – Lysimeter station “Wagna”, Austria. Journal of Hydrology] where the tracer concentrations in the recharging water were weighted according to the precipitation rate and by separating the observation period to different vegetation sub periods. However, during strongly variable flow conditions this improvement was still not sufficient enough to yield adequate modelling results. Therefore, in the present paper we investigated the flow processes in a high sophisticated lysimeter setup. The lysimeter had a length of 2m and a surface area of 1m2 and was weighable which yielded water content as a function of time. This data enabled a further development of the lumped parameter approach to variable flow conditions. A new method was found to estimate the tracer concentration in the recharging water (input function) that takes the actual evapotranspiration rates into account which was indirectly determined from weighing the lysimeters’ mass. Thus, it was possible to use a lumped dispersion model with such a new estimated input function to investigate the δ18O transport in soils planted with crop rotation with relatively high accuracy. The results obtained with the lumped dispersion model were compared with more exact numerical transient flow modelling, which however requires more detailed soil hydraulic data. The results of both modelling approaches yielded similar system parameters. The lumped parameter approach resulted in water contents of 0.14–0.30cm3 cm−3 during the different vegetation periods and a mean value of 0.22cm3 cm−3 for the whole observation period. The transient flow modelling yielded a mean water content of 0.21cm3 cm−3. The dispersion parameter found in both models was in the same range. This study shows that a lumped dispersion model is applicable in the unsaturated zone even under strongly variable flow conditions having additional information about the water balance. [Copyright &y& Elsevier]

Abstract: End-member mixing analysis (EMMA) and isotopes of water (deuterium and oxygen-18) are used to describe hydrologic processes for six boreal forest catchments in the discontinuous permafrost of northern Alberta. The data presented in this paper represent pre-disturbance conditions during two average precipitation years for small basins where the impacts of clear cut harvesting will be evaluated in future work. Hydrologic patterns and soil water sources were different between the two streams draining sloped catchments and the four streams draining flat lowlands. In sloped catchments, snowmelt discharged rapidly prior to loss of soil frost. Snowmelt discharge initially contained between 70 and 90% water from mineral soils and peatlands. As melt progressed, soil water was replaced by surface or near-surface runoff comprising 50–80% of stream discharge. Surface storage of snowmelt in sloped catchments was minimal and summer stream discharge was dominated by rainfall routed through organic and mineral soils (34 and 46%, respectively). Surface runoff averaged 20% of total discharge throughout the summer but rose to 60% of discharge following large storms. In contrast, snowmelt was stored in lowland catchments; peak snowmelt discharge was 30–66% of summer peak discharge and was an equal mix of older groundwater and snowmelt. In lowland catchments, watertables and stream flow declined through the summer and summer discharge was increasingly dominated (>50%) by groundwater routed through organic soils. [Copyright &y& Elsevier]

This paper reports on the extension of a hydrometeorological model of glacierized basins to incorporate a detailed account of glacier mass balance. In this mass balance module a constant fraction of snow fall is redistributed within the basin from ice free areas to the glacier areas. In the particular basin discussed here solid precipitation on the glacier surface is increased by a factor of 2.15 over the basin mean of each 100 m altitude interval.The resulting mass balance parameters like mean annual specific balance, b(h), balance gradients, equilibrium line altitude and accumulation area ratio are within the range of records from other glaciers.The sensitivity of these quantities to meteorological input and model tuning parameters is evaluated, e.g. the sensitivity of mean specific mass balance to mean basin temperature is of the order of 800 mm/K. Emphasis is placed on the net accumulation outside the glacier areas in years with positive mass balance. [Copyright &y& Elsevier]

This paper examines the hydrologic model performance in three snowmelt-dominated basins in the western United States to dynamically- and statistically downscaled output from the National Centers for Environmental Prediction/National Center for Atmospheric Research Reanalysis (NCEP). Runoff produced using a distributed hydrologic model is compared using daily precipitation and maximum and minimum temperature timeseries derived from the following sources: (1) NCEP output (horizontal grid spacing of approximately 210 km); (2) dynamically downscaled (DDS) NCEP output using a Regional Climate Model (RegCM2, horizontal grid spacing of approximately 52 km); (3) statistically downscaled (SDS) NCEP output; (4) spatially averaged measured data used to calibrate the hydrologic model (Best-Sta) and (5) spatially averaged measured data derived from stations located within the area of the RegCM2 model output used for each basin, but excluding Best-Sta set (All-Sta).In all three basins the SDS-based simulations of daily runoff were as good as runoff produced using the Best-Sta timeseries. The NCEP, DDS, and All-Sta timeseries were able to capture the gross aspects of the seasonal cycles of precipitation and temperature. However, in all three basins, the NCEP-, DDS-, and All-Sta-based simulations of runoff showed little skill on a daily basis. When the precipitation and temperature biases were corrected in the NCEP, DDS, and All-Sta timeseries, the accuracy of the daily runoff simulations improved dramatically, but, with the exception of the bias-corrected All-Sta data set, these simulations were never as accurate as the SDS-based simulations. This need for a bias correction may be somewhat troubling, but in the case of the large station-timeseries (All-Sta), the bias correction did indeed ‘correct’ for the change in scale. It is unknown if bias corrections to model output will be valid in a future climate. Future work is warranted to identify the causes for (and removal of) systematic biases in DDS simulations, and improve DDS simulations of daily variability in local climate. Until then, SDS based simulations of runoff appear to be the safer downscaling choice. [Copyright &y& Elsevier]