TY - JOUR A1 - Schattan, Paul A1 - Baroni, Gabriele A1 - Oswald, Sascha Eric A1 - Schoeber, Johannes A1 - Fey, Christine A1 - Kormann, Christoph A1 - Huttenlau, Matthias A1 - Achleitner, Stefan T1 - Continuous monitoring of snowpack dynamics in alpine terrain by aboveground neutron sensing JF - Water resources research N2 - The characteristics of an aboveground cosmic-ray neutron sensor (CRNS) are evaluated for monitoring a mountain snowpack in the Austrian Alps from March 2014 to June 2016. Neutron counts were compared to continuous point-scale snow depth (SD) and snow-water-equivalent (SWE) measurements from an automatic weather station with a maximum SWE of 600 mm (April 2014). Several spatially distributed Terrestrial Laser Scanning (TLS)-based SD and SWE maps were additionally used. A strong nonlinear correlation is found for both SD and SWE. The representative footprint of the CRNS is in the range of 230-270 m. In contrast to previous studies suggesting signal saturation at around 100 mm of SWE, no complete signal saturation was observed. These results imply that CRNS could be transferred into an unprecedented method for continuous detection of spatially averaged SD and SWE for alpine snowpacks, though with sensitivity decreasing with increasing SWE. While initially different functions were found for accumulation and melting season conditions, this could be resolved by accounting for a limited measurement depth. This depth limit is in the range of 200 mm of SWE for dense snowpacks with high liquid water contents and associated snow density values around 450 kg m(-3) and above. In contrast to prior studies with shallow snowpacks, interannual transferability of the results is very high regardless of presnowfall soil moisture conditions. This underlines the unexpectedly high potential of CRNS to close the gap between point-scale measurements, hydrological models, and remote sensing of the cryosphere in alpine terrain. KW - cosmic-ray neutron sensing KW - snow hydrology KW - continuous snowpack monitoring KW - alpine environment Y1 - 2017 U6 - https://doi.org/10.1002/2016WR020234 SN - 0043-1397 SN - 1944-7973 VL - 53 SP - 3615 EP - 3634 PB - American Geophysical Union CY - Washington ER - TY - THES A1 - Barbosa, Luís Romero T1 - Groundwater recharge in tropical wet regions via GIS-based and cosmic-ray neutron sensing T1 - Recarga de águas subterrâneas em regiões úmidas tropicais por métodos baseados em SIG e Detecção de Nêutrons de Raios Cósmicos T1 - Grundwasserneubildung in tropisch-feuchten Gebieten über GIS-basierte Methoden und Messung der Neutronen aus kosmischer Höhenstrahlung N2 - Studies on the unsustainable use of groundwater resources are still considered incipient since it is frequently a poorly understood and managed, devalued and inadequately protected natural resource. Groundwater Recharge (GWR) is one of the most challenging elements to estimate since it can rarely be measured directly and cannot easily be derived from existing data. To overcome these limitations, many hydro(geo)logists have combined different approaches to estimate large-scale GWR, namely: remote sensing products, such as IMERG product; Water Budget Equation, also in combination with hydrological models, and; Geographic Information System (GIS), using estimation formulas. For intermediary-scale GWR estimation, there exist: Non-invasive Cosmic-Ray Neutron Sensing (CRNS); wireless networks from local soil probes; and soil hydrological models, such as HYDRUS. Accordingly, this PhD thesis aims, on the one hand, to demonstrate a GIS-based model coupling for estimating the GWR distribution on a large scale in tropical wet basins. On the other hand, it aims to use the time series from CRNS and invasive soil moisture probes to inversely calibrate the soil hydraulic properties, and based on this, estimating the intermediary-scale GWR using a soil hydrological model. For such purpose, two tropical wet basins located in a complex sedimentary aquifer in the coastal Northeast region of Brazil were selected. These are the João Pessoa Case Study Area and the Guaraíra Experimental Basin. Several satellite products in the first area were used as input to the GIS-based water budget equation model for estimating the water balance components and GWR in 2016 and 2017. In addition, the point-scale measurement and CRNS data were used in the second area to determine the soil hydraulic properties, and to estimate the GWR in the 2017-2018 and 2018-2019 hydrological years. The resulting values of GWR on large- and intermediary-scale were then compared and validated by the estimates obtained by groundwater table fluctuations. The GWR rates for IMERG- and rain-gauge-based scenarios showed similar coefficients between 68% and 89%, similar mean errors between 30% and 34%, and slightly-different bias between -13% and 11%. The results of GWR rates for soil probes and CRNS soil moisture scenarios ranged from -5.87 to -61.81 cm yr-1, which corresponds to 5% and 38% of the precipitation. The calculations of the mean GWR rates on large-scale, based on remote sensing data, and on intermediary-scale, based on CRNS data, held similar results for the Podzol soil type, namely 17.87% and 17% of the precipitation. It is then concluded that the proposed methodologies allowed for estimating realistically the GWR over the study areas, which can be a ground-breaking step towards improving the water management and decision-making in the Northeast of Brazil. N2 - Studien über die nicht nachhaltige Nutzung von Grundwasserressourcen gelten nach wie vor als am Anfang, da es sich oft um eine schlecht verstandene und unkontrolliert genutzte, geringgeschätzte und unzureichend geschützte natürliche Ressource handelt. Die Grundwasserneubildung (GWR) ist eines der am schwierigsten abzuschätzenden Einflussgrößen, da sie selten direkt gemessen werden kann und nicht einfach aus vorhandenen Daten abzuleiten ist. Um diese Einschränkungen zu überwinden, haben viele Hydro(geo)logen verschiedene Ansätze kombiniert, um die GWR in großem Maßstab zu ermitteln, darunter sind: Fernerkundungsprodukte, wie das IMERG-Produkt; Wasserbilanz-Abschätzungen, auch in Kombination mit hydrologischen Modellen und; Geographische Informationssysteme (GIS) unter Nutzung von Abschätzungsformeln. Für die Ermittlung von GWR auf mittleren Flächenskalen existieren: Nicht-invasive Messung der Albedoneutronen an der Landoberfläche (CRNS); Drahtlosnetzwerke von lokalen Bodensonden, und bodenhydrologische Modelle, wie bspw. HYDRUS. In diesem Kontext zielt die Doktorarbeit zum einen darauf ab, eine GIS-basiert Modellkopplung zur Schätzung der GWR-Verteilung im großen Maßstab in tropisch-feuchte Einzugsgebiete aufzuzeigen. Zum anderen verwendet sie CRNS- und invasive Bodenfeuchtesonden-Zeitreihen zur inversen Kalibrierung der hydraulischen Bodeneigenschaften und darauf aufbauend zur Schätzung der GWR im mittleren Maßstab über ein bodenhydrologisches Modell. Zu diesem Zweck wurden zwei tropisch-feuchte Einzugsgebiete ausgewählt, die sich in einem komplexen Sedimentgrundwasserleiter der Küstenregion des Nordosten-Brasilien befinden. Dies sind das João Pessoa-Fallstudiengebiet und das Guaraíra-Flusseinzugsgebiet. Mehrere Satellitenprodukte wurden im ersten Gebiet als Eingangsdaten für das GIS-basierte Wasserbilanz-Modell zur Schätzung der Wasserhaushaltskomponenten und der GWR in den Jahren 2016 und 2017 verwendet. Daneben wurden im zweiten Gebiet die Punktmessungen- und CRNS-Daten verwendet, um über ein bodenhydrologisches HYDRUS-1D-Modell die hydraulischen Bodeneigenschaften zu ermitteln und die GWR in den hydrologischen Jahren 2017-2018 und 2018-2019 abzuschätzen. Die resultierenden GWR-Werte im großen und mittleren Maßstab wurden dann mit den gemessenen Schwankungen der Grundwasserstände verglichen und daran überprüft. Die GWR-Raten aus IMERG- und Niederschlagsmessern-basierten Szenarien zeigten ähnliche Korrelationen zwischen 68% und 89%, mittlere Fehler zwischen 30% und 34%, und leicht unterschiedliche Abweichungen zwischen -13% und 11%. Die berechneten GWR-Raten für Bodensonden- und CRNS-Bodenfeuchtewerte lagen im Bereich von 58,7 bis 618,1 mm im Jahr, was 5% bzw. 38% der Niederschlagsmengen entspricht. Die Berechnung der mittleren GWR-Raten auf großer Landschaftsskala, basierend auf Fernerkundungsdaten, und auf mittlerer Skala, basierend auf CRNS-Daten, ergaben für den Bodentyp Podsol ähnliche Ergebnisse, nämlich 17,87% bzw. 17% der Niederschläge. Daraus wurde der Schluss gezogen, dass die vorgeschlagenen Methoden eine realistische Schätzung der GWR in den Untersuchungsgebieten ermöglichen, was ein wegweisender Schritt zur Verbesserung des Wassermanagements und Nutzungsentscheidungen im Nordosten Brasiliens sein kann. N2 - Estudos sobre o uso insustentável dos recursos hídricos subterrâneos ainda são considerados incipientes, por se tratar de um recurso natural pouco compreendido e gerenciado, desvalorizado e mal protegido. A Recarga de Água Subterrânea (GWR) é um dos elementos mais desafiadores para estimar, pois raramente pode ser medido diretamente e não pode ser facilmente derivado dos dados existentes. Para superar essas limitações, muitos hidro(geo)logistas têm combinado diferentes abordagens para estimar a GWR em larga escala, a saber: produtos de sensoriamento remoto, como o produto IMERG; Equação do Balanço Hídrico, também em combinação com modelos hidrológicos no solo, e; Sistema de Informação Geográfica (GIS), com o uso de fórmulas de estimativa. Para as estimativas de GWR em escala intermediária, existem: Detecção Não-invasiva de Nêutrons de Raios Cósmicos (CRNS); redes sem fio a partir de sondas locais inseridos no solo; e modelos hidrológicos, como o HYDRUS. Neste contexto, a tese de doutorado visa, por um lado, demonstrar um acoplamento de modelo baseado em GIS para estimar a distribuição da GWR em larga escala em bacias tropicais úmidas. Por outro lado, visa utilizar as séries temporais de CRNS e de umidade do solo de sondas invasivas para calibrar inversamente as propriedades hidráulicas do solo, e com base nisso, estimar a GWR em escala intermediária usando um modelo hidrológico do solo. Para tanto, foram selecionadas duas bacias hidrográficas úmidas tropicais, localizadas em um aquífero sedimentar complexo na região costeira do Nordeste do Brasil. Estas são a Área de Estudo de Caso de João Pessoa e a Bacia Experimental do Guaraíra. Vários produtos de satélite foram usados na primeira área como entrada no modelo de balanço hídrico baseado em GIS para estimar os componentes do balanço hídrico e a GWR em 2016 e 2017. Além disso, as medições em escala pontual e os dados de CRNS foram usados na segunda área para determinar as propriedades hidráulicas do solo, e estimar GWR nos anos hidrológicos 2017-2018 e 2018-2019. Os valores resultantes de GWR em escala larga e intermediária foram então comparadas e validadas pelas estimativas obtidas pelas flutuações do lençol freático. As taxas de GWR para os cenários baseados no IMERG e em medidores de precipitação mostraram correlações semelhantes entre 68% e 89, erros médios semelhantes entre 30% e 34%, e viés ligeiramente diferentes entre -13% e 11%. Os resultados das taxas de GWR para os cenários de umidade do solo para sensores inseridos no solo e CRNS variaram de -5,87 a -61,81 cm ano-1, o que corresponde a 5% e 38% da precipitação. Os cálculos das taxas médias de GWR em grande escala, com base em dados de sensoriamento remoto, e em média escala, com base em dados de CRNS, apresentaram resultados semelhantes para o tipo de solo Espodossolo, a saber 17,87% e 17% da precipitação. Conclui-se então que as metodologias propostas permitiram estimar realisticamente a GWR nas áreas de estudo, o que pode ser um passo inovador no tocante ao aprimoramento do gerenciamento e tomada de decisão da água no Nordeste do Brasil. KW - groundwater recharge KW - remote sensing KW - cosmic-ray neutron sensing KW - soil hydraulic properties KW - northeast of Brazil KW - Grundwasserneubildung KW - Fernerkundungsprodukte KW - Neutronen aus kosmischer Höhenstrahlung KW - hydraulische Bodeneigenschaften KW - Nordostbrasilien KW - recarga de águas subterrâneas KW - sensoriamento remoto KW - detecção de nêutrons de raios cósmicos KW - propriedades hidráulicas do solo KW - nordeste do Brasil Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-460641 ER - TY - JOUR A1 - Schattan, Paul A1 - Köhli, Markus A1 - Schrön, Martin A1 - Baroni, Gabriele A1 - Oswald, Sascha Eric T1 - Sensing area-average snow water equivalent with cosmic-ray neutrons: the influence of fractional snow cover JF - Water resources research N2 - Cosmic-ray neutron sensing (CRNS) is a promising non-invasive technique to estimate snow water equivalent (SWE) over large areas. In contrast to preliminary studies focusing on shallow snow conditions (SWE <130 mm), more recently the method was shown experimentally to be sensitive also to deeper snowpacks providing the basis for its use at mountain experimental sites. However, hysteretic neutron response has been observed for complex snow cover including patchy snow-free areas. In the present study we aimed to understand and support the experimental findings using a comprehensive neutron modeling approach. Several simulations have been set up in order to disentangle the effect on the signal of different land surface characteristics and to reproduce multiple observations during periods of snow melt and accumulation. To represent the actual land surface heterogeneity and the complex snow cover, the model used data from terrestrial laser scanning. The results show that the model was able to accurately reproduce the CRNS signal and particularly the hysteresis effect during accumulation and melting periods. Moreover, the sensor footprint was found to be anisotropic and affected by the spatial distribution of liquid water and snow as well as by the topography of the nearby mountains. Under fully snow-covered conditions the CRNS is able to accurately estimate SWE without prior knowledge about snow density profiles or other spatial anomalies. These results provide new insights into the characteristics of the detected neutron signal in complex terrain and support the use of CRNS for long-term snow monitoring in high elevated mountain environments. KW - area-average snow monitoring KW - cosmic-ray neutron sensing KW - neutron simulations KW - spatial heterogeneity KW - fractional snow cover Y1 - 2019 U6 - https://doi.org/10.1029/2019WR025647 SN - 0043-1397 SN - 1944-7973 VL - 55 IS - 12 SP - 10796 EP - 10812 PB - American Geophysical Union CY - Washington ER -