New Research Shows Good Farming Practices Reducing Nutrient Losses on Dairy Farms
Analysis of decades of research has revealed the good farming pracrtice plays a critical role in reducing nutrient losses to improve freshwater outcomes.
The pilot programme, led by Professor Derrick Moot from Lincoln University, is one of multiple pieces of work being performed as part of the Hill Country Futures Partnership, a five-year project co-funded by Beef + Lamb New Zealand, the Ministry of Business, Innovation and Employment (MBIE), PGG Wrightson Seeds and Seed Force New Zealand.
The $8.1 million programme is focused on future proofing the profitability, sustainability and wellbeing of New Zealand’s hill country farmers, their farm systems, the environment and rural communities.
Moot says the decades of data, which comes from Lincoln’s Mt Grand Station near Lake Hāwea will be compared to data from NIWA’S Virtual Climate Station Network (VCSN).
The VCSN data estimates rainfall, air and vapour pressure, relative humidity, solar radiator, wind speed, soil moisture and evapotranspiration – processes by which water moves from the Earth’s surface into the atmosphere.
“Lincoln has had weather stations at Mt Grand for 25 years, recording temperature and rainfall at three different altitudes. It is easy to predict what is happening on flat land but most of New Zealand is hill country and there is lots of local change, through aspect and altitude or north or south facing slopes,” he says.
“NIWA gets its information from weather stations but also has a virtual network with the climate for the whole of New Zealand. What we want to see is how well the predictions from that match the data from our weather stations.
“Stations at the bottom of the valley do not pick up the difference between sunny and shady slopes so we are trying to quantify the difference in temperature and moisture across different altitudes and aspects and ultimately to help farmers plan better.”
“We are looking to see how big the difference is and how much of a difference it makes, and whether we could use NIWA’s virtual network,” says Moot.
“This is just a pilot, not a solution, but we have the opportunity to do this with the dataset we have available.”
