Keywords
water intensity, agriculture, hydrology, modelling, database
Start Date
1-7-2012 12:00 AM
Abstract
Efficient water management strategies based on knowledge about how agricultural and hydrological processes affect local and regional water flows are needed to deal with changes in water availability due to global change. Transparent and flexible tools that can predict the effect of farm systems on these water flows are required. Such a new modelling tool is being built based on the database platform MongoDB. It will be able to calculate the influence of natural processes and of management decisions on the water use intensity in a variety of farm systems for the production of food and biomass for energy. Instead of treating the farm scale as a “black box”, the tool models the local agriculture and hydrologic processes, allowing the calculation of water-based indicators for various scenarios. Such forward-looking environmental indicators can function as early-warning signals, and support early intervention in the processes by enabling resource efficient process changes to be identified. The introduced software “ATB Modelling Database” is flexible enough to allow the addition of new processes and datasets as the database is expanded to reflect the diversity of the worldwide farming processes.
Modelling water use intensity at farm scale – an interdisciplinary study of agriculture and hydrology (AgroHyd)
Efficient water management strategies based on knowledge about how agricultural and hydrological processes affect local and regional water flows are needed to deal with changes in water availability due to global change. Transparent and flexible tools that can predict the effect of farm systems on these water flows are required. Such a new modelling tool is being built based on the database platform MongoDB. It will be able to calculate the influence of natural processes and of management decisions on the water use intensity in a variety of farm systems for the production of food and biomass for energy. Instead of treating the farm scale as a “black box”, the tool models the local agriculture and hydrologic processes, allowing the calculation of water-based indicators for various scenarios. Such forward-looking environmental indicators can function as early-warning signals, and support early intervention in the processes by enabling resource efficient process changes to be identified. The introduced software “ATB Modelling Database” is flexible enough to allow the addition of new processes and datasets as the database is expanded to reflect the diversity of the worldwide farming processes.
