Description: Das Projekt "Snow distribution dynamics under forest canopy" wird vom Umweltbundesamt gefördert und von Eidgenössische Forschungsanstalt für Wald, Schnee und Landschaft, Eidgenössisches Institut für Schnee- und Lawinenforschung durchgeführt. Forested headwaters that are snowmelt dominated produce 60Prozent of the freshwater runoff of the world. Forested areas also act as vast storage units and within the northern hemisphere and can house 17Prozent of total terrestrial water storage in the form of snow and ice during the winter season. However, the state of forest structures within these zones are continually changing due to effects from climate change, land use management as well as a variety of natural disturbances which creates uncertainty regarding the fate of this major water cycle component. The necessity to fully understand the interplay between forest structures and snow is augmented by alarmingly high global water withdrawal predictions ranging from an 18-50Prozent increase for just 13 years from now in 2025. Arriving at accurate estimations of snowmelt and runoff rate variations from forested areas is of great importance to hydrologic forecasters throughout the world, but in spite of this and the recognized impacts of these areas, many forest snow processes are still poorly understood. With the emerging need to understand and quantify snow-vegetation interactions, a significant number of land surface models have included forest canopy representations and their effect on seasonal snow. The model inter-comparison initiative SnowMIP2 constituted the first comprehensive assessment of the capabilities of these models to reproduce snow cover dynamics under canopy and revealed important shortcomings. Enhancing the consistency of model simulations between locations, years and differing forested and open areas needs to be addressed as this deficiency limits the applicability of current models used for water resources monitoring as well as impact studies in forested areas. Specifically, traditional forest snow melt models typically utilize site-based representations of the canopy. But unless the field area has homogenous canopy coverage, a simplified representation of canopy structure can hamper the ability of current land surface models to accurately quantify the effect of forest canopy on snow accumulation and melt. Recent advances in high resolution availability of LiDAR data will allow us to investigate and create new parameters of canopy characteristics over varying scales in order to more accurately represent the natural heterogeneity of forest systems. These characteristics will be integrated with field based ground penetrating radar (GPR) measurements of snow distribution to arrive at improved predictions of snow cover dynamics under heterogeneous canopy. The development of improved canopy structure descriptors will also reduce the reliance on site specific calibration and allow for more accurate data transference and upscaling to larger scale model applications. (...)
SupportProgram
Origin: /Bund/UBA/UFORDAT
Tags: Vegetation ? Waldbaum ? Kalibrierung ? Lidar ? Regenwasserabfluss ? Radar ? Wasserverfügbarkeit ? Fernerkundungsdaten ? Schneeschmelze ? Süßwasser ? Prognose ? Waldboden ? Winter ? Geoinformation ? Waldfläche ? Messdaten ? Flächennutzung ? Freifläche ? Einzugsgebiet ? Jahreszeit ? Landschaftsstruktur ? Monitoring ? Schnee ? Simulation ? Abflussmodell ? Wasserkreislauf ? Bilanz ? Modellierung ? Daten ? Digitales Landschaftsmodell ? Klimafolgen ? Studie ? Baumbestand ? Wasserressourcen ? Wald ? Physikalischer Vorgang ? Datenerhebung ? Standortbedingung ? GPR ? snow accumulation and melt ? snowpack mass balance ? water resources research ? Waldstruktur ? forest canopy structure ? forest snow hydrology ? Wechselwirkung ? ground penetrating radar ? Bodenbedeckung [Abdeckung] ? Schneeverteilung ?
License: cc-by-nc-nd/4.0
Language: Englisch/English
Time ranges: 2013-04-01 - 2016-03-31
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