Publications
NIBIOs employees contribute to several hundred scientific articles and research reports every year. You can browse or search in our collection which contains references and links to these publications as well as other research and dissemination activities. The collection is continously updated with new and historical material.
2019
Authors
Endre Hansen Fønhus Mikael Bruce TalbotAbstract
No abstract has been registered
Abstract
Preferential flow may become significant in partially frozen soils because infiltration can occur through large, initially air-filled pores surrounded by a soil matrix with limited infiltration capacity. The objectives of this study were to develop and evaluate a dual-permeability approach for simulating water flow and heat transport in macroporous soils undergoing freezing and thawing. This was achieved by introducing physically based equations for soil freezing and thawing into the dual-permeability model MACRO. Richards’ equation and the heat flow equation were loosely coupled using the generalized Clapeyron equation for the soil micropore domain. Freezing and thawing of macropore water is governed by a first-order equation for energy transfer between the micropore and macropore domains. We assumed that macropore water was unaffected by capillary forces, so that water in macropores freezes at 0°C. The performance of the model was evaluated for four test cases: (i) redistribution of water in the micropore domain during freezing, (ii) a comparison between the first-order energy transfer approach and the heat conduction equation, (iii) infiltration and water flow in frozen soil with an initially air-filled macropore domain, and (iv) thawing from the soil surface during constant-rate rainfall. Results show that the model behaves in accordance with the current understanding of water flow and heat transport in frozen macroporous soil. To improve modeling of water and heat flow in frozen soils, attention should now be focused on providing experimental data suitable for evaluating models that account for macropore flow.
Authors
Jihong Liu ClarkeAbstract
No abstract has been registered
Authors
Masoud Mahdianpari Mahdi Motagh Vahid Akbari Fariba Mohammadimanesh Bahram SalehiAbstract
Synthetic Aperture Radar (SAR) data have gained interest for a variety of remote sensing applications, given the capability of SAR sensors to operate independent of solar radiation and day/night conditions. However, the radiometric quality of SAR images is hindered by speckle noise, which affects further image processing and interpretation. As such, speckle reduction is a crucial pre-processing step in many remote sensing studies based on SAR imagery. This study proposes a new adaptive de-speckling method based on a Gaussian Markov Random Field (GMRF) model. The proposed method integrates both pixel-wised and contextual information using a weighted summation technique. As a by-product of the proposed method, a de-speckled pseudo-span image, which is obtained from the least-squares analysis of the de-speckled multi-polarization channels, is also produced. Experimental results from the medium resolution, fully polarimetric L-band ALOS PALSAR data demonstrate the effectiveness of the proposed algorithm compared to other well-known de-speckling approaches. The de-speckled images produced by the proposed method maintainthe mean value of the original image in homogenous areas, while preserving the edges of features in heterogeneous regions. In particular, the equivalent number of look (ENL) achieved using the proposed method improves by about 15% and 47% compared to the NL-SAR and SARBM3D de-speckling approaches, respectively. Other evaluation indices, such as the mean and variance of the ratio image also reveal the superiority of the proposed method relative to other de-speckling approaches examined in this study.
Authors
Patrick J. Drohan Marianne Bechmann Anthony Buda Faruk Djodjic Donnacha Doody Jonathon M. Duncan Antti Iho Phil Jordan Peter J. Kleinman Richard McDowell Per-Erik Mellander Ian A. Thomas Paul J. A. WithersAbstract
The evolution of phosphorus (P) management decision support tools (DSTs) and systems (DSS), in support of food and environmental security has been most strongly affected in developed regions by national strategies (i) to optimize levels of plant available P in agricultural soils, and (ii) to mitigate P runoff to water bodies. In the United States, Western Europe, and New Zealand, combinations of regulatory and voluntary strategies, sometimes backed by economic incentives, have often been driven by reactive legislation to protect water bodies. Farmer‐specific DSSs, either based on modeling of P transfer source and transport mechanisms, or when coupled with farm‐specific information or local knowledge, have typically guided best practices, education, and implementation, yet applying DSSs in data poor catchments and/or where user adoption is poor hampers the effectiveness of these systems. Recent developments focused on integrated digital mapping of hydrologically sensitive areas and critical source areas, sometimes using real‐time data and weather forecasting, have rapidly advanced runoff modeling and education. Advances in technology related to monitoring, imaging, sensors, remote sensing, and analytical instrumentation will facilitate the development of DSSs that can predict heterogeneity over wider geographical areas. However, significant challenges remain in developing DSSs that incorporate “big data” in a format that is acceptable to users, and that adequately accounts for catchment variability, farming systems, and farmer behavior. Future efforts will undoubtedly focus on improving efficiency and conserving phosphate rock reserves in the face of future scarcity or prohibitive cost. Most importantly, the principles reviewed here are critical for sustainable agriculture.
Authors
Stig A. BorgvangAbstract
No abstract has been registered
Authors
Svenja B. KroegerAbstract
No abstract has been registered
Abstract
No abstract has been registered
Authors
Nick Hodgetts Marta Cálix Eve Englefield Nicholas Fettes M. García Criado Lea Patin Ana Nieto Ariel Bergamini Irene Bisang Elvira Baisheva Patrizio Campisi A Cogoni Tomas Hallingbäck Nadya A. Konstantinova Neil Lochhart Marko Sabovljevic Norbert Schnyder Christian Schröck Cecília Sérgio Manuela Sim-Sim Jaroslav Vrba Catarina C. Ferreira Olga M. Afonina T.L. Blockeel Hans Blom Steffen Caspari Rosalina Gabriel Cesar Garcia Ricardo Garilleti J González Mancebo Irina Goldberg Lars Hedenäs David T. Holyoak Vincent Hugonnot Sanna Huttunen Mikhail S. Ignatov Elena A. Ignatova Marta Infante Riikka Juutinen Thomas Kiebacher Heribert Köckinger Jan Kucera Niklas Lönnell Michael Lüth Anabela Martins Oleg Maslovsky Beata Papp Ron Porley Gordon Rothero Lars Söderström Sorin Ştefǎnuţ Kimmo Syrjänen Alain Untereiner Jíri Vána Alain Vanderpoorten Kai Vellak Michele Aleffi J. W. Bates Neil Bell Montserrat Brugués Nils Cronberg Jo Denyer J.G. Duckett Heinjo During Johannes Enroth Vladimir E. Fedosov Kjell Ivar Flatberg Anna Ganeva Piotr Gorski Urban Gunnarsson Kristian Hassel Helena Hespanhol Mark O. Hill Rory Hodd Kristoffer Hylander Nele Ingerpuu Sanna Laaka-Lindberg Francisco Lara Vicente Mazimpaka Anna Mežaka Frank Müller Jose David Orgaz Jairo Patiño Sharon Pilkington Felisa Puche Rosa Maria Ros Fred Rumsey José Gabriel Segarra-Moragues Ana Séneca Adam Stebel Risto Virtanen Henrik Weibull Jo Wilbraham Jan ZarnowiecAbstract
No abstract has been registered
Authors
Sigrid Bratlie Kristin Halvorsen Bjørn Kåre Myskja Hilde Mellegård Cathrine Bjorvatn Petter Frost Gunnar Harald Heiene Bjørn Morten Hofmann Arne Holst-Jensen Torolf Holst-Larsen Raino Sverre Malnes Benedicte Paus Bente Sandvig Sonja Irene Sjøli Birgit Skarstein May Britt Thorseth Nils Vagstad Dag Inge Våge Ole Johan BorgeAbstract
No abstract has been registered