2018
Authors
Holger Lange Sebastian Sippel Britta Aufgebauer Michael Hauhs Christina Bogner Henning MeesenburgAbstract
No abstract has been registered
Authors
Inge Stupak Tat Smith Nicholas Clarke Teodorita Al-Seadi Lina Beniušienė Niclas Scott Bentsen Quentin Cheung Virginia Dale Jinke van Dam Rocio Diaz-Chavez Uwe Fritsche Martyn Futter Jianbang Gan Kaija Hakala Thomas Horschig Martin Junginger Yoko Kitigawa Brian Kittler Keith Kline Charles Lalonde Søren Larsen Dagnija Lazdina Thuy P. T. Mai-Moulin Maha Mansoor Edmund Mupondwa Shyam Nair Nathaniel Newlands Liviu Nichiforel Marjo Palviainen John Stanturf Kay Schaubach Johanny Arilexis Perez Sierra Vita Tilvikiene Brian Titus Daniela Thrän Sergio Ugarte Liisa Ukonmaanaho Iveta Varnagyrite-Kabasinkiene Maria WellischAbstract
No abstract has been registered
Abstract
We investigated whether diversification and/or structural change would improve Norwegian agriculture. Using a flexible technology approach to account for different technologies, we assessed economies of scope and scale of dairy and cropping farms, including regional differences. We fitted translog cost functions to farm-level panel data for the period 1991–2014. We found both economies of scope and scale on the farms. Dairy farms have an economic incentive to integrate dairying with cropping in all regions of Norway, and vice versa. Thus, policy makers should eschew interventions that inhibit diversification or structural change and that increase the costs of food production.
Abstract
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Abstract
In recent years, rising competition for water coupled with new environmental regulations has exerted pressure on water allocations for turfgrass irrigation. In this article, we reviewed published scientific and industry evidence on the agronomic and environmental impacts of turfgrass irrigation using a robust systematic review methodology. Our focus was on the links between (i) irrigation management (amount and frequency), (ii) agronomic responses to irrigation (turf quality, growth rates and rooting) and (iii) environmental impacts (nitrogen leaching). Based on an initial screening of 653 studies and data extracted from 83 papers, our results show that in most cases, under moderate levels of deficit irrigation (50%–60% of actual evapotranspiration), turf quality can be maintained at an acceptable level but with lower water consumption compared to irrigating back to field capacity. Irrigation beyond field capacity was found to increase the risk of nutrient leaching. However, evidence also showed that the concentration and total loss of urn:x-wiley:09312250:media:jac12265:jac12265-math-0001 in leachate were influenced more by nitrogen (N) rates, soil characteristics, turfgrass species and turfgrass growth rates than by irrigation practices. Our analyses suggest that turfgrass irrigation should be scheduled to apply water at moderate levels of deficit irrigation, sufficient to maintain turfgrass quality but limited to promote a deep and extensive rooting system. The findings provide new insights and valuable evidence for both scientists and practitioners involved in turfgrass research and management.
Abstract
The present work focuses on an assessment of the applicability of groundwater table (GWT) measures in the modelling of soil water retention characteristics (SWRC) using artificial neural network (ANN) methods. Model development, testing, validation and verification were performed using data collected across two decades from soil profiles at full-scale research objects located in Southwest Poland. A positive effect was observed between the initial GWT position data and the accuracy of soil water reserve estimation. On the other hand, no significant effects were observed following the implementation of GWT fluctuation data over the entire growing season. The ANN tests that used data of either soil water content or GWT position gave analogous results. This revealed that the easily obtained data (temperature, precipitation and GWT position) are the most accurate modelling parameters. These outcomes can be used to simplify modelling input data/parameters/variables in the practical implementation of the proposed SWRC modelling variants.
Authors
Rachel Cassidy Philip Jordan Marianne Bechmann Brian Kronvang Katarina Kyllmar Mairead ShoreAbstract
Achieving an operational compromise between spatial coverage and temporal resolution in national scale river water quality monitoring is a major challenge for regulatory authorities, particularly where chemical concentrations are hydrologically dependent. The efficacy of flow-weighted composite sampling (FWCS) approaches for total phosphorus (TP) sampling (n = 26–52 analysed samples per year), previously applied in monitoring programmes in Norway, Sweden and Denmark, and which account for low to high flow discharges, was assessed by repeated simulated sampling on high resolution TP data. These data were collected in three research catchments in Ireland over the period 2010–13 covering a base-flow index range of 0.38 to 0.69. Comparisons of load estimates were also made with discrete (set time interval) daily and sub-daily sampling approaches (n = 365 to >1200 analysed samples per year). For all years and all sites a proxy of the Norwegian sampling approach, which is based on re-forecasting discharge for each 2-week deployment, proved most stable (median TP load estimates of 87–98%). Danish and Swedish approaches, using long-term flow records to set a flow constant, were only slightly less effective (median load estimates of 64–102% and 80–96%, respectively). Though TP load estimates over repeated iterations were more accurate using the discrete approaches, particularly the 24/7 approach (one sample every 7 h in a 24 bottle sampler - median % load estimates of 93–100%), composite load estimates were more stable, due to the integration of multiple small samples (n = 100–588) over a deployment.
Authors
Francisco Javier Ancin Murguzur Aitor Barbero-Lopez Sari Kontunen-Soppela Antti HaapalaAbstract
No abstract has been registered
Abstract
No abstract has been registered
Authors
Astrid Johansen Anne Kjersti Bakken Anne Langerud Ragnhild Borchsenius Sverre Heggset Atle HaugnesAbstract
No abstract has been registered