Assessment of temporal dynamics of snow cover and its validation with hydro-meteorological data in parts of Chenab Basin,western Himalayas

The present investigation was conducted to analyze the temporal patterns of snow cover area%(SCA%), air temperature, snowfall and river discharge in parts of Chenab basin, western Himalayas. The relationship of mean SCA% with mean air temperature and river discharge was also tested using Pearson's product-moment correlation at 95% confidence limit and further sensitivity analysis of river discharge to SCA and SCA to air temperature was performed. Moderate Resolution Imaging Spectroradiometer(MODIS) 8-day surface reflectance product MOD09A1 was used to delineate SCA during the period 2000–2013. Moreover, variation in the lowest elevation from where snow cover area starts(LESCA) was also analyzed and its relationship with mean air temperature was also studied. Non-parametric method, Mann-Kendall test was employed to determine the trend in the SCA%, air temperature, snowfall and river discharge. The investigation carried out for three meteorological stations i.e. Batote, Reasi and Tandi revealed significant findings. At Batote and Reasi, statistically significant decreasing trends were observed over the period 2000 to 2012, for maximum, minimum and mean air temperature. Mean minimum SCA% exhibited a significant upward trend during 2000–2013 which is corroborated by the significantly increasing trend of mean annual snowfall(Tandi station) from 2000 to 2010. Further, significant decreasing trend of river discharge for the winter season at Batote station from 2000 to 2011 and decreasing trends in the maximum, minimum and mean air temperature at Batote and Reasi stations are also consistent with the increasing trend of SCA%. At both Batote and Reasi stations, mean SCA% exhibited significant negative relationship with the mean air temperature. On the other hand, LESCA exhibited positive correlation with the mean air temperature except in a few months, where negative relationship was seen. Sensitivity analysis of river discharge to SCA exhibited very low values of sensitivity coefficient in most of the months, indicating less sensitivity of river discharge to SCA. On the other hand, sensitivity coefficient of SCA to air temperature exhibited comparatively higher values which indicate SCA is more sensitive to air temperature.     

Determining the causes for the dramatic recent fall of Lake Prespa (southwest Balkans)

Mediterranean lake–wetland systems are threatened by climate change and intensive human impacts. Individual lake responses to these threats are poorly known but urgently required to steer preservation strategies. The dramatic water-level fall (~8 m since 1987) of Lake Megali Prespa endangers this global biodiversity hotspot and the wider catchment’s water resources. Annual lake fluctuations are found to be strongly related to wet-season (Oct.–Apr.) precipitation variability, which is linked to the North Atlantic Oscillation. The lake primarily adjusts to sustained inflow changes through amending surface evaporation. Cumulative water abstraction since 1951 (~19 × 10⁶ m³/year: ~0.006% of lake volume) explains ~70% of the long-term decrease in surface evaporation; climate variability explains the remainder. Persistent low lake levels after 1995 are caused by water abstraction. Compared to 1952/53–1977/78, the period 1978/79–2003/04 experienced significant decreases in wet-season precipitation, snowfall and discharge; the number of very dry years increased.

EDITOR A. Castellarin; ASSOCIATE EDITOR D. Gerten     

Climate change impacts on surface water resources in the Rheraya catchment (High Atlas,Morocco)

This study aimed to quantify possible climate change impacts on runoff for the Rheraya catchment (225 km²) located in the High Atlas Mountains of Morocco, south of Marrakech city. Two monthly water balance models, including a snow module, were considered to reproduce the monthly surface runoff for the period 1989?2009. Additionally, an ensemble of five regional climate models from the Med-CORDEX initiative was considered to evaluate future changes in precipitation and temperature, according to the two emissions scenarios RCP4.5 and RCP8.5. The future projections for the period 2049?2065 under the two scenarios indicate higher temperatures (+1.4°C to +2.6°C) and a decrease in total precipitation (?22% to ?31%). The hydrological projections under these climate scenarios indicate a significant decrease in surface runoff (?19% to ?63%, depending on the scenario and hydrological model) mainly caused by a significant decline in snow amounts, related to reduced precipitation and increased temperature. Changes in potential evapotranspiration were not considered here, since its estimation over long periods remains a challenge in such data-sparse mountainous catchments. Further work is required to compare the results obtained with different downscaling methods and different hydrological model structures, to better reproduce the hydro-climatic behaviour of the catchment.

EDITOR M.C. Acreman

ASSOCIATE EDITOR R. Hirsch     

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.     

Exploitation of Landsat data for snow zonation mapping in the Hindukush,Karakoram and Himalaya (HKH) region of Pakistan

Abstract

In the Hindukush, Karakoram and Himalaya (HKH) region of Pakistan, many glaciological variables are still not known due to the remoteness and harsh weather conditions of the area. A remote sensing technique is therefore applied to map the snow zonation in the HKH region. Landsat 7 ETM+ data for the year 2003 are used in this study. Image classification and image processing techniques are applied to map, for the first time, the major snow zones in the HKH region. Six classes are identified: the results show that the area covered by the highest-altitude snow (Snow I), lower-altitude snow (Snow II), bare ice, debris-covered ice, wet snow and shadow is 21 529.42, 22 472.58, 8696.41, 8038.75, 12 159.37 and 7322.30 km², respectively. The study also indicates that the equilibrium line altitude (ELA) lies between 5000 and 5500 m above sea level, with an accumulation area ratio (AAR) of 0.60.

Citation Butt, M.J., 2013. Exploitation of Landsat data for snow zonation mapping in the Hindukush, Karakoram and Himalaya (HKH) region of Pakistan. Hydrological Sciences Journal, 58 (5), 1088–1096.     

Deriving snow‐cover depletion curves for different spatial scales from remote sensing and snow telemetry data

During the melting of a snowpack, snow water equivalent (SWE) can be correlated to snow‐covered area (SCA) once snow‐free areas appear, which is when SCA begins to decrease below 100%. This amount of SWE is called the threshold SWE. Daily SWE data from snow telemetry stations were related to SCA derived from moderate‐resolution imaging spectroradiometer images to produce snow‐cover depletion curves. The snow depletion curves were created for an 80 000 km² domain across southern Wyoming and northern Colorado encompassing 54 snow telemetry stations. Eight yearly snow depletion curves were compared, and it is shown that the slope of each is a function of the amount of snow received. Snow‐cover depletion curves were also derived for all the individual stations, for which the threshold SWE could be estimated from peak SWE and the topography around each station. A station's peak SWE was much more important than the main topographic variables that included location, elevation, slope, and modelled clear sky solar radiation. The threshold SWE mostly illustrated inter‐annual consistency. Copyright © 2015 John Wiley & Sons, Ltd.     

Electrical resistivity imaging and hydrochemical analysis for groundwater investigation in Kuala Langat,Malaysia

ABSTRACT

Integrated two-dimensional electrical resistivity imaging (ERI) and hydrochemical surveys were used to investigate the groundwater alluvial aquifer in Kuala Langat, Malaysia. The study in the Langat basin considered the thickness of the aquifer, the depth of the bedrock, the regions influenced by seawater intrusion, and the monitoring of water levels. The resistivity imaging results show that the upper layer consists of clay, while the second layer is an aquifer whose thickness varies mostly in the range of 10–30 m, and in some cases extends to 40 m. The bedrock depth varies from 30 to 65 m. The chemical analyses were carried out on groundwater samples from nine boreholes collected between 2008 and 2012. The analyses indicate that the total dissolved solids (TDS) exceed 1000 mg L^-1 near the coastal area and are often less than 500 mg L^-1 further inland. The ERI and hydrochemical analyses reveal that groundwater in the study area, especially towards the coast, is a mixture of brackish and fresh waters.

EDITOR D. Koutsoyiannis; ASSOCIATE EDITOR M.D. Fidelibus     

Snow model sensitivity analysis to understand spatial and temporal snow dynamics in a high‐elevation catchment

In this paper, we addressed a sensitivity analysis of the snow module of the GEOtop2.0 model at point and catchment scale in a small high‐elevation catchment in the Eastern Italian Alps (catchment size: 61 km²). Simulated snow depth and snow water equivalent at the point scale were compared with measured data at four locations from 2009 to 2013. At the catchment scale, simulated snow‐covered area (SCA) was compared with binary snow cover maps derived from moderate‐resolution imaging spectroradiometer (MODIS) and Landsat satellite imagery. Sensitivity analyses were used to assess the effect of different model parameterizations on model performance at both scales and the effect of different thresholds of simulated snow depth on the agreement with MODIS data. Our results at point scale indicated that modifying only the “snow correction factor” resulted in substantial improvements of the snow model and effectively compensated inaccurate winter precipitation by enhancing snow accumulation. SCA inaccuracies at catchment scale during accumulation and melt period were affected little by different snow depth thresholds when using calibrated winter precipitation from point scale. However, inaccuracies were strongly controlled by topographic characteristics and model parameterizations driving snow albedo (“snow ageing coefficient” and “extinction of snow albedo”) during accumulation and melt period. Although highest accuracies (overall accuracy = 1 in 86% of the catchment area) were observed during winter, lower accuracies (overall accuracy < 0.7) occurred during the early accumulation and melt period (in 29% and 23%, respectively), mostly present in areas with grassland and forest, slopes of 20–40°, areas exposed NW or areas with a topographic roughness index of ?0.25 to 0 m. These findings may give recommendations for defining more effective model parameterization strategies and guide future work, in which simulated and MODIS SCA may be combined to generate improved products for SCA monitoring in Alpine catchments.     

Evaluation of temporal consistency of snow depth drivers of a Rocky Mountain watershed in southern Alberta

Collecting spatially representative data over large areas is a challenge within snow monitoring frameworks. Identifying consistent trends in snow accumulation properties enables increased sampling efficiency by minimizing field collection time and/or remote sensing costs. Seasonal snowpack depth estimations during mid-winter and melt onset conditions were derived from airborne Lidar over the West Castle Watershed in the southern Canadian Rockies on three dates. Each dataset was divided into five sets of snow depth driver classes: elevation, aspect, topographic position index, canopy cover and slope. Datasets were quality controlled by eliminating snow depth values above the 99th percentile value, which had a negligible effect on average snow depths. Consistent trends were observed among driver classes with peak snow accumulation occurring within the treeline ecotone, north-facing aspects, open canopies, topographic depressions and areas with low slope angle. Although mid-winter class trends for each driver were similar and watershed-scale snow depth distributions were significantly correlated (0.76, p < .01), depth distributions within the same driver class of the three datasets were not correlated due to recent snowfall events, redistribution and settling processes. Trends in driver classes during late season melt onset were similar to mid-winter conditions but watershed scale distribution correlation results varied with seasonality (0.68 mid-winter 2014 and melt onset 2016; 0.65 mid-winter 2017 and melt onset 2016, p < .1). This is due to the differing stages of accumulation or ablation and the upward migration in the 0°C isotherm during spring, when snow depth can be declining in valley bottoms while still increasing at higher elevations. The observed consistency in depth driver controls can be used to guide future integrated snow monitoring frameworks.     

Assessment of reservoir sedimentation using remote sensing and recommendations for desilting Patratu Reservoir,India

ABSTRACT

This study describes the assessment of reservoir sedimentation of the Patratu Reservoir using Satellite Remote Sensing (SRS). The sedimentation assessment was carried out using satellite data and reservoir water level data from 2006 to 2012. Water spread area was analysed from satellite data. The Normalized Difference Water Index (NDWI) has been used to delineate open water features and to enhance the presence of water surface in satellite imagery of the Patratu Reservoir. Water spread area of the reservoir at a particular elevation on the date of the passing of the satellite was used to develop an elevation-area curve. For the present case, fluctuation of water level was found to vary from 387.096 to 406.152 m. The linear interpolation/extrapolation technique has been employed to assess the water spread area of Patratu Reservoir at different elevations. Further, these areas were used to compute the live storage capacity of the reservoir between two elevations by the Prismoidal formula. From the study, it was found that due to sedimentation, the live storage capacity of Patratu Reservoir has reduced from 101.95 to 89.96 hm³, thus showing capacity loss of 11.76% in a span of 44 years. To increase the live storage capacity of the reservoir it is proposed to adopt manual and mechanical digging combined with flushing for desilting of the deposited sediment.

EDITOR D. Koutsoyiannis ASSOCIATE EDITOR S. Kanae     

Evaluation of recent hydro-climatic changes in four tributaries of the Niger River Basin (West Africa)

West Africa experienced severe drought during the 1970s and 1980s, posing a threat to water resources. A wetter climate more recently suggests recovery from the drought. The Mann-Kendall trend and Theil-Sen’s slope estimator were applied to detect probable trends in weather elements in four sub-basins of the Niger River Basin between 1970 and 2010. The cross-entropy method was used to detect breakpoints in rainfall and runoff, Spearman’s rank test for correlation between the two, and cross-correlation analysis for possible lags. Results showed an overall increase in rainfall and runoff and a decrease in sunshine duration. Spearman’s coefficients suggest significant (5%) moderate to strong rainfall–runoff correlation for three sub-basins. A significant lower runoff was observed around 1979, with a rainfall break around 1992, indicating possible cessation of the drought. Temperatures increased significantly, at 0.02–0.05°C year^-1, with a negative wind speed trend for most stations. Half of the stations exhibited an increase in potential evapotranspiration.

EDITOR M.C. Acreman

ASSOCIATE EDITOR Not assigned     

Assessment of groundwater recharge influenced by floodwater spreading: an integrated approach with limited accessible data

To assess the response of groundwater to artificial recharge through floodwater spreading (FWS) a combination approach of water table fluctuations and water budget was used. In this process, water level data in six observation wells installed inside and around the site of the FWS systems together with the amount of rainfall and volume of floodwater diverted to the system were examined during the period 1993–2012. Specific yield was also determined based on measured soil hydraulic properties for three experimental wells hand drilled within the FWS systems. The observation wells located inside the FWS systems were less susceptible to drought and abstractions than the other wells in the area. The hydrograph of the wells inside the FWS showed a large disparity in rises (0.5–2.05 m) after the two major floods in 2004 and 2005 due to systems closure in 2004. The water budget calculated based on water table fluctuations for 2010/11 showed that the contribution of FWS systems to total recharge in the study area was about 57–61%.

EDITOR D. Koutsoyiannis

ASSOCIATE EDITOR S. Kanae     

Variation of hydrogeochemical characteristics of water in surface flows,shallow wells,and boreholes in the coastal city of Douala (Cameroon)

ABSTRACT

Groundwater is used by 3?million inhabitants in the coastal urban city of Douala, Cameroon, but comprehensive data are too sparse for it to be managed in a sustainable manner. Hence this study aimed to (1) assess the potability of the groundwater; (2) evaluate the spatial variation of groundwater composition; and (3) assess the interaction and recharge mechanisms of different water bodies. Hydrogeochemical tools and methods revealed the following results in the Wouri and Nkappa formations of the Douala basin, which is beneath Douala city: 30% of water samples from hand-dug wells in the shallow Pleistocene alluvium aquifer were saline and highly mineralized. However, water from boreholes in the deeper (49–92 m depth) Palaeocene aquifer was saline-free, less mineralized and potable. Water in the shallow aquifer (0.5–22 m depth) was of Na⁺-K⁺-Cl^?-NO₃^? type and not potable due to point source pollution, whereas Ca⁺-HCO₃^? unpolluted water dominates in the deeper aquifer. Water in the deep and shallow aquifers indicates the results of preferential flow pass and evaporative recharge, respectively. Possible hydrogeochemical processes include point source pollution, reverse ion exchange, remote recharge areas and mixing of waters with different chemical signatures.

EDITOR D. Koutsoyiannis ASSOCIATE EDITOR M.D. Fidelibus     

A hybrid factorial stepwise-cluster analysis method for streamflow simulation – a case study in northwestern China

ABSTRACT

In this study, a hybrid factorial stepwise-cluster analysis (HFSA) method is developed for modelling hydrological processes. The HFSA method employs a cluster tree to represent the complex nonlinear relationship between inputs (predictors) and outputs (predictands) in hydrological processes. A real case of streamflow simulation for the Kaidu River basin is applied to demonstrate the efficiency of the HFSA method. After training a total of 24?108 calibration samples, the cluster tree for daily streamflow is generated based on a stepwise-cluster analysis (SCA) approach and is then used to reproduce the daily streamflows for calibration (1995–2005) and validation (2008–2010) periods. The Nash-Sutcliffe coefficients for calibration and validation are 0.68 and 0.65, respectively, and the deviations of volume are 1.68% and 4.11%, respectively. Results show that: (i) the HFSA method can formulate a SCA-based hydrological modelling system for streamflow simulation with a satisfactory fitting; (ii) the variability and peak value of streamflow in the Kaidu River basin can be effectively captured by the SCA-based hydrological modelling system; (iii) results from 2⁶ factorial experiments indicate that not only are minimum temperature and precipitation key drivers of system performance, but also the interaction between precipitation and minimum temperature significantly impacts on the streamflow. The findings are useful in indicating that the streamflow of the study basin is a mixture of snowmelt and rainfall water.

EDITOR D. Koutsoyiannis; ASSOCIATE EDITOR G. Thirel     

Assessing drought threats to agricultural water supplies under climate change by combining the SWAT and MODSIM models for the Geum River basin,South Korea

ABSTRACT

The impacts of future climate change on the agricultural water supply capacities of irrigation facilities in the Geum River basin (9645.5 km²) of South Korea were investigated using an integrated modeling framework that included a water balance network model (MODSIM) and a watershed-scale hydrologic model (Soil and Water Assessment Tool, SWAT). The discharges and baseflows from upland drainage areas were estimated using SWAT, and the predicted flow was used to feed agricultural reservoirs and multipurpose dams in subwatersheds. Using a split sampling method, we calibrated the daily streamflows and dam inflows at three locations using data from 6 years, including 3 years of calibration data (2005–2007) followed by 3 years of validation data (2008–2010). In the MODSIM model, the entire basin was divided into 14 subwatersheds in which various agricultural irrigation facilities such as agricultural reservoirs, pumping stations, diversions, culverts and groundwater wells were defined as a network of hydraulic structures within each subwatershed. These hydraulic networks between subwatersheds were inter-connected to allow watershed-scale analysis and were further connected to municipal and industrial water supplies under various hydrologic conditions. Projected climate data from the HadGEM3-RA RCP 4.5 and 8.5 scenarios for the period of 2006–2099 were imported to SWAT to calculate the water yield, and the output was transferred to MODSIM in the form of time-series boundary conditions. The maximum shortage rate of agricultural water was estimated as 38.2% for the 2040s and 2080s under the RCP 4.5 scenario but was lower under the RCP 8.5 scenario (21.3% in the 2040s and 22.1% in the 2080s). Under the RCP 4.5 scenario, the projected shortage rate was higher than that during the measured baseline period (1982–2011) of 25.6% and the RCP historical period (1982–2005) of 30.1%. The future elevated drought levels are primarily attributed to the increasingly concentrated rainfall distribution throughout the year under a monsoonal climate, as projected by the IPCC climate scenarios.

EDITOR Z.W. Kundzewicz; ASSOCIATE EDITOR not assigned     

River temperature forecasting: case study for Little Southwest Miramichi River (New Brunswick,Canada)

River temperature models play an increasingly important role in the management of fisheries and aquatic resources. Among river temperature models, forecasting models remain relatively unused compared to water temperature simulation models. However, water temperature forecasting is extremely important for in-season management of fisheries, especially when short-term forecasts (a few days) are required. In this study, forecast and simulation models were applied to the Little Southwest Miramichi River (New Brunswick, Canada), where water temperatures can regularly exceed 25–29°C during summer, necessitating associated fisheries closures. Second- and third-order autoregressive models (AR2, AR3) were calibrated and validated using air temperature as the exogenous variable to predict minimum, mean and maximum daily water temperatures. These models were then used to predict river temperatures in forecast mode (1-, 2- and 3-day forecasts using real-time data) and in simulation mode (using only air temperature as input). The results showed that the models performed better when used to forecast rather than simulate water temperatures. The AR3 model slightly outperformed the AR2 in the forecasting mode, with root mean square errors (RMSE) generally between 0.87°C and 1.58°C. However, in the simulation mode, the AR2 slightly outperformed the AR3 model (1.25°C < RMSE < 1.90°C). One-day forecast models performed the best (RMSE ~ 1°C) and model performance decreased as time lag increased (RMSE close to 1.5°C after 3 days). The study showed that marked improvement in the modelling can be accomplished using forecasting models compared to water temperature simulations, especially for short-term forecasts.

EDITOR M.C. Acreman ASSOCIATE EDITOR S. Huang     

Spatial interpolation of snow water equivalency using surface observations and remotely sensed images of snow‐covered area

As demand for water continues to escalate in the western Unites States, so does the need for accurate monitoring of the snowpack in mountainous areas. In this study, we describe a simple methodology for generating gridded‐estimates of snow water equivalency (SWE) using both surface observations of SWE and remotely sensed estimates of snow‐covered area (SCA). Multiple regression was used to quantify the relationship between physiographic variables (elevation, slope, aspect, clear‐sky solar radiation, etc.) and SWE as measured at a number of sites in a mountainous basin in south‐central Idaho (Big Wood River Basin). The elevation of the snowline, obtained from the SCA estimates, was used to constrain the predicted SWE values. The results from the analysis are encouraging and compare well to those found in previous studies, which often utilized more sophisticated spatial interpolation techniques. Cross‐validation results indicate that the spatial interpolation method produces accurate SWE estimates [mean R² = 0·82, mean mean absolute error (MAE) = 4·34 cm, mean root mean squared error (RMSE) = 5·29 cm]. The basin examined in this study is typical of many mid‐elevation mountainous basins throughout the western United States, in terms of the distribution of topographic variables, as well as the number and characteristics of sites at which the necessary ground data are available. Thus, there is high potential for this methodology to be successfully applied to other mountainous basins. Copyright © 2010 John Wiley & Sons, Ltd.     

Impact of forest degradation on streamflow regime and runoff response to rainfall in the Garhwal Himalaya,Northwest India

Baseflows have declined for decades in the Lesser Himalaya but the causes are still debated. This paper compares variations in streamflow response over three years for two similar headwater catchments in northwest India with largely undisturbed (Arnigad) and highly degraded (Bansigad) oak forest. Hydrograph analysis suggested no catchment leakage, thereby allowing meaningful comparisons. The mean annual runoff coefficient for Arnigad was 54% (range 44–61%) against 62% (53–69%) at Bansigad. Despite greater total runoff Q_t (by 250 mm year^–1), baseflow at Bansigad ceased by March, but was perennial at Arnigad (making up 90% of Q_t vs. 51% at Bansigad). Arnigad storm flows, Q_s, were modest (8–11% of Q_t) and occurred mostly during monsoons (78–98%), while Q_s at Bansigad was 49% of Q_t and occurred also during post-monsoon seasons. Our results underscore the importance of maintaining soil water retention capacity after forest removal to maintain baseflow levels.

EDITOR D. Koutsoyiannis; ASSOCIATE EDITOR D. Gerten     

Energy fluxes and melt rate of a seasonal snow cover in the Moroccan High Atlas

ABSTRACT

In this study, we used an energy balance model and two simple methods based on readily available data to identify the processes driving the point-scale energy and mass balance of the snowpack. Data were provided from an experimental site located at 3200 m. All models were evaluated by comparing observed and modelled snow water equivalents. Performances are variable from one season to the next and the energy balance model gives better results (mean of root mean square error, RMSE = 25 mm and r² = 0.90) than the two simplified approaches (mean of RMSE = 54 mm and r² = 0.70). There are significant amounts of snow sublimation but they are highly variable from season to season, depending on wind conditions (between 7 and 20% of the total). While the main source of energy for melting is net radiation, the amount of heat brought by sensible heat flux is significant for two of the most windy snow seasons.

Editor Z.W. Kundzewicz Associate editor not assigned     

Assessment of hydrological extremes in the Kamo River Basin,Japan

A suite of extreme indices derived from daily precipitation and streamflow was analysed to assess changes in the hydrological extremes from 1951 to 2012 in the Kamo River Basin. The evaluated indices included annual maximum 1-day and 5-day precipitation (RX1day, RX5day), consecutive dry days (CDD), annual maximum 1-day and 5-day streamflow (SX1day, SX5day), and consecutive low-flow days (CDS). Sen’s slope estimator and two versions of the Mann-Kendall test were used to detect trends in the indices. Also, frequency distributions of the indices were analysed separately for two periods: 1951–1981 and 1982–2012. The results indicate that quantiles of the rainfall indices corresponding to the 100-year return period have decreased in recent years, and the streamflow indices had similar patterns. Although consecutive no rainfall days represented by 100-year CDD decreased, continuous low-flow days represented by 100-year CDS increased. This pattern change is likely associated with the increase in temperature during this period.

EDITOR D. Koutsoyiannis

ASSOCIATE EDITOR E. Gargouri