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NIBIOs ansatte publiserer flere hundre vitenskapelige artikler og forskningsrapporter hvert år. Her finner du referanser og lenker til publikasjoner og andre forsknings- og formidlingsaktiviteter. Samlingen oppdateres løpende med både nytt og historisk materiale. For mer informasjon om NIBIOs publikasjoner, besøk NIBIOs bibliotek.

2018

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Sammendrag

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.

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Climate change adversely affects the determinants of agriculture. Adaptation serves as an important strategy to reduce the adverse effects of climate change (variability) and vulnerability of the people. Adaptation through an innovation programme was implemented for 4 years during 2012–2016 to improve the adaptive capacity in agriculture and the water sectors through capacity building and implementation in the Krishna River Basin, India. Primary data were collected from 178 farm households of the Nagarjuna Sagar Project command area covering both adopters and non‐adopters of water‐saving interventions from the study area. The double difference method was used to analyse the impact of adaptation through capacity building and implementation. The water‐saving interventions include alternate wetting and drying (AWD) in rice, a modified system of rice intensification (MSRI) and direct seeding of rice (DSR). The capacity building and water saving increased crop yields by 0.96, 0.93 and 0.77 t ha−1 through AWD, MSRI and DSR respectively. The three practices have increased farmers’ income and decreased the cost of cultivation in DSR by Rs.11 000 (US$169) ha−1. The methods can be more focused in canal commands on a larger scale for equal distribution of water to all the head, middle and tail‐end regions.

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Sammendrag

Climate change characterized by global warming has become a hotspot of research in recent years for water resources, agriculture,ecology and other disciplines. In India, studies have shown an increasing trend in surface temperature, with decreasing trends inrainfall. Farmers are also more affected by the climate variability which has a serious influence on their production and income.The climate change and adaptation (ClimaAdapt) programme was implemented from 2012 to 2016 to build farm-level capacitiesand enhance the adaptive capacity of the agricultural and water sectors in the Krishna basin of Andhra Pradesh and Telanganastates. Water-saving interventions such as direct seeded rice, a modified system of rice intensification and alternate wetting anddrying (AWD) of rice were implemented in a cluster approach and enhanced water productivity. The training and implementationprogrammes increased the adaptation and awareness of farmers. Water measurements were carried out by usingflumes andultrasonic sensors. The area under direct seeded rice has increased to 64% in the study district and 77% of the trained farmersare adopting the practice. Capacity building, implementation and science–policy linkages are the key pillars of the programmeto improve the adaptive capacity and scaling-up of water management practices.

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Sammendrag

From 2017, the Norwegian River Monitoring Programme (Elveovervåkingsprogrammet) replaced the former RID programme “Riverine inputs and direct discharges to Norwegian coastal waters” which had run continuously since 1990. The present report provides the current (2017) status and long-term (1990-2017) water quality trends in the 20 rivers included in the main programme.