Alpine Catchment Areas Research Articles

Estimating Regional Snow Line Elevation Using Public Webcam Images

Snow cover is of high relevance for the Earth’s climate system, and its variability plays a key role in alpine hydrology, ecology, and socioeconomic systems. Measurements obtained by optical satellite remote sensing are an essential source for quantifying snow cover variability from a local to global scale. However, the temporal resolution of such measurements is often affected by persistent cloud coverage, limiting the application of high resolution snow cover mapping. In this study, we derive the regional snow line elevation in an alpine catchment area using public webcams. We compare our results to the snow line information derived from the Moderate-Resolution Imaging Spectroradiometer (MODIS) and Sentinel-2 snow cover products and find our results to be in good agreement therewith. Between October 2017 and the end of June 2018, snow lines derived from webcams lie on average 55.8 m below and 33.7 m above MODIS snow lines using a normalized-difference snow index (NDSI) of 0.4 and 0.1, respectively, and are on average 53.1 m below snow lines derived from Sentinel-2. We further analyze the superior temporal resolution of webcam-based snow cover information and demonstrate its effectiveness in filling temporal gaps in satellite-based measurements caused by cloud cover. Our findings show the ability of webcam-based snow line elevation retrieval to complement and improve satellite-based measurements.

Extremely high flow within the Alpine catchments in the Rila Mountain

The study of high flow characteristics within the Alpine catchments represents one of the most challenging tasks for the modern hydrological science, because of high vulnerability response of these areas to the global and regional climate changes, including to the proven positive air temperature trends. The current picture of the hydro-climatic processes in the Rila Mountain – the highest mount within the Balkan Peninsula, is not exception. Study area covers eight Alpine catchment areas, located above 1600 m sea level in the Rila Mountain. The aim of this research is to perform a spatio-temporal analysis of the extremely high streamflow characteristics within the researched drainage basins. Study period includes six years in the beginning of the XXІ century: there are very dry (2001), very wet (2005) and four normal water years. The analysis is based of Threshold level method (TLM) with fixed constant threshold value: 5th percentile of all discharge daily data for the given term. Results obtained show the number of extremely high streamflow events ranges from 6 to 26 – for the catchments of the Stara River at Kostenets and the Blagoevgradska Bistritsa River at Bistritsa, respectively. The maximal duration of these events varies from 15 (for the Mesta River at Yakoruda) do 39 days (the Stara River at Kostenets), but the oneweek extremely high flow periods are most typical here (a frecquency to 88% of all cases). The temporal analysis shows a concentration of studied hydrological events during the spring season (in the months of April, May and June), when occurs also a high streamflow phase, due to the snow melting and rainfalls. An exception of this statement is the wettest year in Bulgaria from the beginning of this century – 2005. Then because of heavy prolonged rainfalls during the months of July, August and September, were detected sharp peaks of the hydrographs. Present work establishes some spatial differences of extremely high flow characteristics (time of occurring, duration, frequency) in study area due to the slopes exposition peculiarities. Results obtained supplement previous scientific works and give new information about the risk hydrological processes within the mountainous catchment areas in Bulgaria.

Analysis of flood‐reduction capacity of hydropower schemes in an Alpine catchment area by semidistributed conceptual modelling

AbstractThe simulation of run‐off in Alpine catchment areas is essential for the optimal operation of high head storage hydropower plants (HPPs) under normal flow conditions, but also in case of flood events. A conceptual semidistributed numerical approach is presented, combining hydrologic modelling and operation of hydraulic works. Spatial rainfall and temperature distributions were taken into account for simulating the dominant hydrologic processes, such as glacier melt, snowpack constitution and melt, soil infiltration and run‐off. The object‐oriented modelling tool allowed run‐off generation, simulation of the operating mode of complex HPP and its impact on the downstream river network for different scenarios. The paper briefly presents the hydrologic model and then the application for the upper Aare catchment in Switzerland, where about half of the area is operated by the Oberhasli hydropower scheme. The development, calibration and validation of the hydrologic model are discussed. Finally, the retention effect of the existing reservoirs and their management, including preventive turbine operations, on flood routing in the Aare River upstream of Lake Brienz is presented for the 2005 historical flood event.

High abundance of genetic Bacteroidetes markers for total fecal pollution in pristine alpine soils suggests lack in specificity for feces

Two frequently applied genetic Bacteroidetes markers for total fecal pollution (AllBac and BacUni) were found in high numbers in pristine soil samples of two alpine catchment areas casting doubt on their value as fecal indicators. This finding underlines the necessity to evaluate assays locally and against non-intestinal samples before application.

Potentials and limitations of modelling spatio‐temporal patterns of soil moisture in a high mountain catchment using WaSiM‐ETH

AbstractSoil moisture is a highly dynamic ecological variable. This dynamic is especially distinct in high mountains areas, where topography, snow cover, micro‐climate, vegetation, soil properties and land cover vary across short distances. For such areas, soil moisture modelling on a fine scale is therefore particularly challenging. We evaluated the distributed, physically based model WaSiM‐ETH with regard to its ability to model soil moisture in high mountain catchments, including spatio‐temporal patterns. The study was performed in the alpine catchment area of the Lötschen valley (160 km2) in Switzerland, an area ranging from 600 to 4000 m a.s.l. The model was run for the period of 2003–2007 with high temporal (hourly) and spatial (50 m) resolution. Extensive TDR‐ and FD‐measurements conducted in 2006 and 2007 enabled the validation of the simulated soil moisture. A local sensitivity analysis indicated a dependence of soil moisture on skeleton fraction and temperature. The validation results showed that WaSiM‐ETH is able to simulate absolute soil moisture variability across different altitudes and land cover types with only a moderate accuracy (R = 0·47), whereas the soil moisture dynamic is reproduced well (R = 0·69, IoA = 0·66). High spatial variability of skeleton fraction and coarse meteorological data are the main causes for the limitation in soil moisture modelling. Nevertheless, analysing the spatio‐temporal patterns of soil moisture revealed a clear seasonal pattern that is in line with literature. We found soil moisture to be determined by liquid precipitation, snow‐melt and evapotranspiration. Greatest efforts should be laid on the exact determination of fine‐scale meteorological data and spatial skeleton estimation to improve soil moisture modelling in high mountain areas in the future. Copyright © 2010 John Wiley & Sons, Ltd.

Simulation and analysis of runoff from a partly glaciated meso‐scale catchment area in Patagonia using an artificial neural network

AbstractIn this study, a model based on an artificial neural network (ANN) was developed to forecast the runoff of a meso‐scale, partly glaciated (40%), Alpine catchment area in the southernmost Andes in Patagonia, Chile. The study area is located in a maritime climate with a mean annual air temperature of + 5·7 °C and about 5500 mm of precipitation per year at sea level.The multilayer feed‐forward network is designed to make use of the Levenberg‐Marquardt algorithm to increase the speed of computation (convergence). Using climate data recorded at an automatic weather station nearby as well as water level records measured simultaneously, the ANN model was trained and verified using independent training and validation datasets. Parameters and the corresponding time lags were determined by statistical methods such as partial, cross‐ and autocorrelation. The results of the simulation confirm that the proposed model was able to identify the underlying non‐linear relationships between the input parameters and the observed discharge. The correlation during validation shows a significant correlation coefficient of 0·98, and an RMSE of 0·02 m respectively. However, it is almost impossible to decipher the internal behaviour of ANN due to its black‐box character. Nevertheless, valuable insights were gained in the complex input–output relationships, and the occurrence of dependencies between different input variables were detected using global sensitivity analysis (GSA). The results of the GSA were compared with those of multiple linear regression (MLR). While the performance of the ANN is much better than the MLR, both models return similar results in terms of the dependency of the discharge upon input variables. It was found that despite the large proportion of glaciated surface area within the catchment, discharge is mainly controlled by precipitation (49%). Furthermore, the runoff is slightly influenced by temperature (19%), global radiation (15%) and wind speed (16%).While the ANN proves to be a very efficient tool for simulating runoff in glacerized, Alpine catchments from meteorological data, the GSA method, as outlined and used in this paper, offers a useful approach of analysing ANN output. Copyright © 2008 John Wiley & Sons, Ltd.

A quantitative real-time PCR assay for the highly sensitive and specific detection of human faecal influence in spring water from a large alpine catchment area

The aim of the study was the development of a sensitive human-specific quantitative real-time PCR assay for microbial faecal source tracking (MST) in alpine spring water. The assay detects human-specific faecal DNA markers (BacH) from 16S rRNA gene sequences from the phylum Bacteroidetes using TaqMan minor groove binder probes. The qualitative and quantitative detection limits of the PCR assay were 6 and 30 marker copies, respectively. Specificity was proved by testing 41 human faeces and waste water samples and excluding cross-amplification from 302 animal faecal samples from Eastern Austria. Marker concentrations in human faecal material were in the range from 6.6 x 10(9) to 9.1 x 10(10) marker equivalents per gram. The method was sensitive enough to detect a few 100 pg of faeces in faecal suspensions. The assay was applied on water samples from an alpine karstic spring catchment area and the results reflected the expected levels of human faecal influence. The method exhibited sufficient sensitivity to allow quantitative source tracking of human faecal impact in the investigated karstic spring water. The developed method constitutes the first quantitative human-specific MST tool sensitive enough for investigations in ground and spring water.

The value of historical documents for hazard zone mapping

Abstract. The assessment of historical data of small mountain torrents in Alpine catchment areas has shown a significant difference between the results of a regular hazard zone mapping and a thorough historical analysis. The Gemsbach in the Ostrach valley near Hinterstein (Municipality of Hindelang, southern Bavaria/Germany) serves, among others, as an example. A "traditional" hazard zone for the Gemsbach has been mapped in the 1990s. The oldest event included in the analysis was the flood of 1954. But historical data collected and analysed by the HANG-project shows flood-prone areas around the Gemsbach differing greatly in size and location from the one shown in the hazard zone maps. The inclusion of all data available for the Gemsbach area (15 events between 1671 and 1960 collected from four different archives) leads to a completely new picture of the regional hazardous activity and demands a re-structuring of the traditional way of hazard zone mapping.

Application of flow models in an alpine catchment area using tritium and deuterium data

Measurements of tritium and deuterium concentrations in precipitation and runoff were in addition to conventional investigation methods used to provide some further insight into the storage properties of Lainbach valley, a catchment area of 18.7 km 2 and 670 to 1801 m above sea level in the Bavarian Alps. The basin was modeled using different simple hydrological models. Information about mean transit times of subsurface water and storage volumes of basin reservoirs is derived from the application of specific flow models to the isotopic output data. Based on fitted mean transit times of 0.8 yr. for the upper subsurface reservoir and 7.5 yr. for the lower subsurface reservoir, storage volume equivalents were obtained of 0.6 and 1.9 m of water depth, respectively.