Have we adequately identified threats to our water supplies and set the right management targets?
Agricultural impacts on water quality focus mostly on excess nutrients and sediments. However, other constituents or parameters of concern related to land and water management may emerge as more critical threats to regional water supplies. Research is essential to identifying these threats and characterizing risk.
How can we optimize practice designs?
Many studies have contributed significantly to advanced engineering and integration of in-field, edge-of-field and edge-of-stream agricultural practices. Historically, however, management recommendations have focused on costs and yields related to average field conditions. In addition to novel engineering designs, collaborative research is needed to tease out underlying drivers affecting practice performance and quantify outcomes related to a broader range of stakeholder concerns.
How can we improve trade-off analyses and decision support?
There is increasing evidence that the Pareto principle applies in agriculture: roughly 80 percent of the threats to our water supplies come from 20 percent of our working lands. Importantly, these high-impact areas may shift with climate change. Thus, models are essential to identifying the small portion of land areas that have a disproportionate impact on regional water resources or have an exceptional capacity to provide a range of ecosystem services affected by water management. Further, fully integrated biophysical, socio-economic models can transform stakeholder decision-support by providing a more holistic basis for assessing cost-effectiveness related to farm operations.
How can we engage farmers and emplace enough practices to achieve our goal?
The recent U.S. Agricultural Census indicates that farmers have applied best management practices to less than five percent of our agricultural lands. Such limited adoption poses a significant risk to our achieving our water security goal. There is a critical need to understand why farmers have not adopted these advanced recommendations and develop more effective incentive programs accordingly.
Are we achieving the expected outcomes?
Advances in continuous monitoring equipment and remote sensing technology present exciting opportunities to characterize current field conditions. More importantly, however, these technologies present exceptional opportunities to improve our decision-support tools’ accuracy and precision if used as part of a research program purposely designed to support model development. Model-based research is essential to improving credibility with stakeholders, thus improving resource management.