Initial findings from agricultural water quality monitoring at the edge-of-field in Arkansas

Authors: Reba, Michele; ARYAL, NIROJ - North Carolina Agricultural And Technical State University; TEAGUE, TINA - University Of Arkansas; Massey, Joseph

Submitted to: Journal of Soil and Water Conservation
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/20/2019
Publication Date: 6/1/2020
Citation: Reba, M.L., Aryal, N., Teague, T.G., Massey, J. 2020. Initial findings from agricultural water quality monitoring at the edge-of-field in Arkansas. Journal of Soil and Water Conservation. https://doi.org/10.2489/jswc.75.3.291.
DOI: https://doi.org/10.2489/jswc.75.3.291

Interpretive Summary: With farm-scale knowledge of how production practices affect water quality, land managers and agricultural producers can make more informed decisions on implementing soil and water conservation practices that sustain productivity and protect water resources. To expand understanding of these relationships as well as to provide baseline water quality data, edge-of-field water quality monitoring studies were carried out in nine commercial, rice, cotton and soybean fields in northeast Arkansas over multiple seasons. These year-round measurements generated 23 site-years of data on sediment, nutrient concentrations, and loads with various soils and crop rotation regimes. The results indicate that the non-growing season losses were statistically higher than those measured during the growing season, lending support to the need for off-season practices such as winter cover crops. Lower concentrations and loads of nutrients and sediment were observed in rice fields compared to measurements made in the cotton and soybean systems. These findings will help inform regional budgets of nutrients and sediment loss, as well as assist land managers and conservationists in directing resources more effectively. These data also will support modelers in their efforts to calibrate, verify, validate, and estimate uncertainty for simulations of nutrients and sediment loss.

Technical Abstract: With farm-scale knowledge of how production practices affect water quality, land managers and agricultural producers can make more informed decisions on implementing soil and water conservation practices that sustain productivity and protect water resources. The Lower Mississippi River Basin is a major agricultural production region for rice, cotton, corn, and soybean; however, there is limited knowledge on how agronomic practices in those cropping systems affect water quality. In addition, modelled contributions from agricultural commercial fertilizer to the hypoxic zone in the northern Gulf of Mexico are high. To expand understanding of these relationships as well as to provide baseline water quality data, edge-of-field water quality monitoring studies were carried out in nine commercial, rice, cotton, and soybean fields in northeast Arkansas over multiple seasons. These year-round monitoring activities generated 23 site-years of data on sediment and nutrient concentrations and loads with various soils and crop rotation regimes. Discharge from runoff, nitrite-N, nitrate-N, total nitrogen, soluble phosphorus, total phosphorus and suspended sediment concentration on a per-event basis were measured. The results indicate that the non-growing season losses were statistically higher than those measured during the growing season, lending support to the need for off-season practices such as winter cover crops. Lower concentrations and loads of nutrients and sediment were observed in rice fields compared to measurements made in the cotton and soybean systems. These differences are likely due to soil type, but also are related to the water management system of flooded rice fields compared to furrow irrigated row-crops. These findings will help inform regional budgets of nutrients and sediment loss, as well as assist land managers and conservationists in directing resources more effectively. This data also will support modelers in their efforts to calibrate, verify, validate, and estimate uncertainty for simulations of nutrients and sediment loss.