Arkansas Discovery Farms: documenting water quality benefits of on-farm conservation management and empowering farmers

Arkansas Discovery Farms (ADFs) are private farms that collaborate with on-farm research, verification, and demonstration of farming's impact on the environment. We have nine ADFs representing livestock (broiler poultry and pasture grazed beef and sheep) and row crop agriculture (corn, cotton, rice, soybean, and wheat), where we collect water use and water quality data as a function of conservation management, using autosamplers equipped with edge-of-field H-flumes or weir flow structures, which measure and collect surface runoff. On the poultry farms, we are monitoring nutrient and sediment runoff originating immediately near poultry houses due to concerns with spillage of litter during bird removal and house clean out, as well as dust from tunnel ventilation. On a nearby farm we are assessing the impact of rotational grazing on water quality, soil organic matter, and soil health metrics. On the row crop farms we are assessing the impacts of conservation tillage and cover crops on soybean–corn rotations and cotton on nutrient and sediment runoff and the benefits of water harvesting and reuse of water conservation and quality. The information in this paper while preliminary, demonstrates how a state-wide on-farm demonstration program operates. Elevated nutrient and sediment runoff from around poultry production areas are decreased three-fold by directing runoff into ponds or through grassed waterways. While conservation tillage and cover crops do decrease nutrient and sediment runoff, no significant difference between conventional and conservation operations is yet to be realized. Importantly, ADF empowers farmers to proactively address environmental concerns. This paper discusses the development, guidance, principals, and goals of ADF and contrasts this with other farm monitoring projects, where the sources of nutrient impairment are the subject of ongoing litigation. Monitoring in divisive and transparent situations presents unique challenges with data ownership and release of findings, which can hinder productive outcomes of such monitoring.