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Efficient water resource management in glacier- and snow-dominated basins requires accurate estimates of the snow water equivalent (SWE) in late winter and spring and melt onset timing and intensity. To understand the high spatio-temporal variability of snow and glacier ablation, a spatially distributed energy balance model combining satellite-based retrievals of albedo and snow cover was applied. Incoming short-wave energy, contributing to daily estimates of melt energy, was constrained by remotely sensed surface albedo for snow-covered surfaces. Fractional snow cover was used for non-glaciated areas, as it provides estimates of snow cover for each pixel to better constrain snow melt. Thus, available daily estimates of melt energy in a given area were the product of the possible melt energy and the fractional snow cover of the area or pixel for non-glaciated areas. This provided daily estimates of melt water to determine seasonal snow and glacier ablation in Iceland for the period 2000–2019. Observations from snow pits on land and glacier summer mass balance were used for evaluation, and observations from land and glacier-based automatic weather stations were used to evaluate model inputs for the energy balance model. The results show that the interannual SWE variability was generally high both for seasonal snow and glaciers. For seasonal snow, the largest SWE (>1000 mm) was found in mountainous and alpine areas close to the coast, notably in the East- and Westfjords, Tröllaskaga, and in the vicinity of glacier margins. Lower SWE values were observed in the central highlands, flatter inland areas, and at lower elevations. For glaciers, more SWE (glacier ablation) was associated with lower glacier elevations while less melt was observed at higher elevations. For the impurity-rich bare-ice areas that are exposed annually, observed SWE was more than 3000 mm. [ABSTRACT FROM AUTHOR]

During the melt season, absorbed solar energy, modulated at the surface by albedo, is one of the main governing factors controlling surface melt variability for glaciers in Iceland. An energy balance model was applied with the possibility of utilizing spatiotemporal Moderate Resolution Imaging Spectroradiometer (MODIS) satellite-derived daily surface albedo driven by high-resolution climate forcing data to reconstruct the surface energy balance (SEB) for all Icelandic glaciers for the period 2000–2021. The SEB was reconstructed from April through September for 2000–2021 at a daily time step with a 500 m spatial resolution. Validation was performed using observations from various glaciers spanning distinct locations and elevations with good visual and statistical agreement. The results show that spatiotemporal patterns for the melt season have high annual and interannual variability for Icelandic glaciers. The variability was influenced by high climate variability, deposition of light-absorbing particles (LAPs) from volcanic eruptions and dust hotspots in pro-glacial areas close to the glaciers. Impacts of LAPs can lead to significant melt enhancement due to lowering of albedo and increased short-wave radiative energy forced at the surface. Large impacts on the SEB were observed for years with high LAP deposits, such as the volcanic eruption years of 2004, 2010 and 2011 and the sand- and dust-rich year of 2019. The impacts of volcanic eruptions and other LAP events were estimated using historical mean albedo under the same climatology forcing to provide estimations of melt energy enhancements. The impact of LAPs was often significant even though the glaciers were far away from the eruption location. On average, the melt enhancements due to LAPs were ∼27 % in 2010, ∼16 % in 2011 and ∼14 % in 2019 for Vatnajökull, Hofsjökull and Langjökull. [ABSTRACT FROM AUTHOR]

During the melt season, absorbed solar energy, modulated at the surface by albedo, is one of the main governing factors controlling surface-melt variability for glaciers in Iceland. An energy balance model was developed with the possibility to utilize spatio-temporal MODIS satellite-derived daily surface albedo driven by high-resolution climate forcing data to reconstruct the surface energy balance (SEB) for all Icelandic glaciers for the period 2000–2021. The SEB was reconstructed from April through September for 2000–2021 at a daily timestep with a 500 m spatial resolution. Validation was performed using observations from various glaciers spanning distinct locations and elevations with good visual and statistical agreement. The results show that spatio-temporal patterns for the melt season have high annual and inter-annual variability for Icelandic glaciers. The variability was influenced by high climate variability, deposition of light-absorbing particles (LAPs) from volcanic eruptions and dust hotspots in pro-glacial areas close to the glaciers. Impacts of LAPs can lead to significant melt enhancement due to lowering of albedo and increased short-wave radiative energy forced at the surface. Large impacts on the SEB were observed for years with high LAPs deposits, such as volcanic eruption years in 2004, 2010 and 2011 and the sand and dust-rich year of 2019. The impacts of volcanic eruptions and other LAP events were estimated using historical mean albedo under the same climatology forcing to provide estimations of melt energy enhancements. The impact of LAPs was often significant even though the glaciers were far away from the eruption location. [ABSTRACT FROM AUTHOR]

The power‐law rating curve has been used extensively in hydraulic practice and hydrology. It is given by Q(h)=a(h−c)b, where Q is discharge, h is water elevation, a, b, and c are unknown parameters. We propose a novel extension of the power‐law rating curve, referred to as the generalized power‐law rating curve. It is constructed by linking the physics of open channel flow to a model of the form Q(h)=a(h−c)f(h). The function f(h) is referred to as the power‐law exponent and it depends on the water elevation. The proposed model and the power‐law model are fitted within the framework of Bayesian hierarchical models. By exploring the properties of the proposed rating curve and its power‐law exponent, we find that cross‐sectional shapes that are likely to be found in nature are such that the power‐law exponent f(h) will usually be in the interval [1.0,2.67]. This fact is utilized for the construction of prior densities for the model parameters. An efficient Markov chain Monte Carlo sampling scheme, that utilizes the lognormal distributional assumption at the data level and Gaussian assumption at the latent level, is proposed for the two models. The two statistical models were applied to four datasets. In the case of three datasets the generalized power‐law rating curve gave a better fit than the power‐law rating curve while in the fourth case the two models fitted equally well and the generalized power‐law rating curve mimicked the power‐law rating curve. We developed an R package, bdrc, for fitting the power‐law and generalized power‐law rating curve models. It is available on CRAN. [ABSTRACT FROM AUTHOR]

We studied the trends in climate change and snow cover in Iceland. Climate was classified based on the Köppen-Geiger (KG) classification system for 1950-2100 using the ensemble average of + NASA-NEX downscaled CMIP5 projections for RCP 4.5. Snow Cover Frequency (SCF) was calculated based on in MODIS10A1 snow product in days/year and SCF trends were calculated for 2001-2016. Trends in climate and snow cover changes were evaluated in 4 different elevation bands: Coastline (0-100 m.a.s.l.), Lowland (100-500 m.a.s.l.), Highland (500-1000 m.a.s.l.) and Mountains/Glaciers (1000+ m.a.s.l.). The results showed that in all elevations zones warmer climate classes have been replacing colder climates and polar tundra since 1950's, based on climate projections we expect these trends to continue throughout the present century. We observed that in large areas of the country a significant increase in SCF had occurred during the period 2001-2016. These changes were most pronounced in the highlands where SCF had increased by 3.5 days/year on average. The only locations where we observed increasing SCF was around the termini of the country's outlet glaciers. The results suggest that by the end of the present century polar tundra climate (ET) will have decreased from 20 % to 5 % coverage and cold climate with warm summers (Dfb), will extend around the island and spread into the highlands. [ABSTRACT FROM AUTHOR]

Information about natural background levels (NBLs) of chemicals in source waters allows water utilities to identify trends in drinking water contamination. We estimate NBLs for chemicals in source waters for Icelandic water utilities at both national levels with all data pooled, and according to geological regime. NBLs were derived by collecting samples from 79 aquifers considered largely unimpacted by human activities. The aquifers were categorized into four geological settings that are representative of the geology of Iceland. NBLs were calculated as 90%iles of all aquifers in each setting and in all pooled. There was a statistical difference between the geological settings in 11 parameters of 37 tested. The 90%ile for nitrate for all aquifers pooled was 1.36 mg/l, indicating little anthropogenic influence on water used for public water supply in Iceland. The results were compared to the chemical status of 60 European aquifers, collected for the European Union's Sixth Framework Program Background Criteria for the Identification of Groundwater Thresholds project, revealing lower dissolved solids concentration for Icelandic groundwater than that from other parts of Europe. The explanation is likely due to high permeability of young geology settings and low population density in Iceland whereas there is a long history of agriculture and industry in most European countries. [ABSTRACT FROM AUTHOR]