Search

Developing drainage water management (DWM) systems in the Midwest to reduce nitrogen (N) transport to the northern Gulf of Mexico hypoxic zone requires understanding of the long-term performance of these systems. Few studies have evaluated long-term impacts of DWM, and the simulation of controlled drainage (CD) with the Root Zone Water Quality Model (RZWQM) is limited, while shallow drainage (SD) has not been examined. We tested RZWQM using nine years (2007-2015) of field data from southeast Iowa for CD, SD, conventional drainage (DD), and undrained (ND) systems and simulated the long-term (1971-2015) impacts. RZWQM accurately simulated N loss in subsurface drainage, and the simulations agreed with field data that CD and SD substantially reduced N loss to drainage. As indicated by the field data, the SD N concentration was predicted to be greater than DD and CD, likely due to reduced time of travel to shallower drains. The long-term simulations show that CD and SD reduced annual N lost via tile drainage by 26% and 40%, respectively. Annual reductions in N lost via tile drainage ranged from 28% in the driest years to 22% in the wettest years for CD and from 56% in the driest years to 35% in the wettest years for SD. Considering spring N loading for the purpose of addressing hypoxia in the Gulf of Mexico, CD was found to be less effective than SD, and in many years CD exported more N in the spring than DD. Spring N loading (April through June) was indicated by the EPA Science Advisory Board to have the greatest impact on hypoxia in the northern Gulf of Mexico. Therefore, improvement of CD systems within the months of April through June to reduce N loss via drainage across the upper Midwest landscape may be required. Limited research in the upper Midwest has addressed spring N loading under controlled drainage systems (CD). This research will help model developers, model users, and agricultural scientists more clearly understand N transport under different systems, including CD, SD, and ND, which will aid in developing the design and management of drainage systems to reduce N transport from tile-drained agriculture to surface waters. Keywords: Agricultural simulation model, Drainage water management, Nonpoint-source pollution, Northern Gulf of Mexico hypoxic zone, Nutrient reduction, Subsurface drainage.

In Iowa, producers achieve an adequate growing season for high yielding corn (Zea mays L.) by beginning field activities in a timely fashion. Subsurface drainage allows for early field activities by improving trafficability and decreasing excess water stress to crops on poorly drained soils. Drainage water management practices reduce drainage volumes and nitrate (NO3) loss by maintaining the water table closer to the ground surface when compared to conventional drainage systems. The objective of this study was to determine the effect of shallow, controlled, conventional, and no drainage on depth to water table, volumetric water content, and soil temperature during a 51-day period, from mid-April through May, to evaluate if drainage water management practices delay planting. At the Iowa State University Southeast Research Farm near Crawfordsville, Iowa, we evaluated eight large-scale research plots with two replicates for each of the four drainage treatments over the 51-day planting period during 2012 to 2015. Each plot was planted half to soybeans (Glycine max [L.] Merr.) and the other half to corn, and the halves rotated every year in accordance with a typical corn–soybean rotation. Conventional and controlled drainage significantly lowered (p

Subsurface drainage improves row crop production but also short circuits nitrate-nitrogen (NO3-N) pathways in the soil with significant losses to surface waters. The objective of this study was to evaluate the effect of shallow, controlled, conventional, and undrained drainage treatments on depth to water table, drainage volume and NO3-N loads, soil water content and storage in the soil profile, and crop yields. This research was conducted at the Iowa State University Southeast Research Farm near Crawfordsville, Iowa, from 2007 to 2015. We report on years five through nine here. The site consisted of eight large field plots with each of the four drainage treatments replicated twice. One-half of each plot was planted with corn (Zea mays L.) and the other half with soybeans (Glycine max [L.] Merr.). The corn and soybean halves were rotated every year in accordance with a typical corn–soybean rotation. The undrained treatment had a shallower water table than the other treatments and had a significantly higher number of days during the growing season when the water table was within 30 cm (12 in) of the ground surface than the other treatments. However, there was no difference in soil water contents in the top 80 cm (31.5 in) of the soil profile during the growing season between drainage treatments. Over the five-year study, controlled and shallow drainage reduced annual subsurface flows by 60% and 58%, respectively, while also reducing NO3-N loads by 61% and 49%, respectively, as compared to the conventional drainage design. Crop yields were similar along the drainage designs but significantly lower in the undrained treatment. This study highlights the effectiveness of shallow and controlled drainage to reduce NO3-N loads.

Soil microbial communities are structured by biogeochemical processes that occur at many different spatial scales, which makes soil sampling difficult. Because soil microbial communities are important in nutrient cycling and soil fertility, it is important to understand how microbial communities function within the heterogeneous soil landscape. In this study, a self-organizing map was used to determine whether landscape data can be used to characterize the distribution of microbial biomass and activity in order to provide an improved understanding of soil microbial community function. Points within a row crop field in south-central Iowa were clustered via a self-organizing map using six landscape properties into three separate landscape clusters. Twelve sampling locations per cluster were chosen for a total of 36 locations. After the soil samples were collected, the samples were then analysed for various metabolic indicators, such as nitrogen and carbon mineralization, extractable organic carbon, microbial biomass, etc. It was found that sampling locations located in the potholes and toe slope positions had significantly greater microbial biomass nitrogen and carbon, total carbon, total nitrogen and extractable organic carbon than the other two landscape position clusters, while locations located on the upslope did not differ significantly from the other landscape clusters. However, factors such as nitrate, ammonia, and nitrogen and carbon mineralization did not differ significantly across the landscape. Overall, this research demonstrates the effectiveness of a terrain-based clustering method for guiding soil sampling of microbial communities.