@article{watkins_poole_youssef_moursi_vann_heiniger_2024, title={E FFECTS OF SHALLOW SURFACE DRAINAGE DITCHES W ITH CONTROLLED SUBSURFACE DRAINAGE M ANAGEMENT ON CROP YIELDS IN NORTH CAROLINA}, volume={67}, ISSN={["2769-3287"]}, DOI={10.13031/ja.15537}, abstractNote={Highlights Shallow surface ditches with controlled subsurface drainage (SD) increased corn and soybean yields in eight of nine growing seasons compared to conventional drainage. The SD system increased corn yields on average by 0.4 Mg/ha, or 4% (0.7 Mg/ha, or 6.6%, excluding 2016). The SD system increased soybean yields on average by 0.5 Mg/ha, or 14.3%. Abstract. Agricultural drainage in the coastal areas of North Carolina (NC) is commonly achieved through large trapezoidal-shaped ditches. The coastal region of NC has limited topographic relief (slopes < 1%) with poorly drained soils that can cause substantial issues with surface water ponding during high-intensity or long-duration precipitation events without some form of surface drainage. Installation of large free flowing surface ditches (FD) with field crowning improves the drainage intensity but can create negative consequences such as over drainage and side slope scouring within the ditch. Large open ditches remove tillable land from production and serve as a primary transport pathway for pollutants. An alternative drainage design (SD) has been implemented that decreases the size of the surface ditches, limiting their drainage effect to only surface water and potentially improving equipment trafficability. The smaller ditches, installed with precision grade equipment, are placed on a grade sufficient to direct surface flow while keeping soil movement to a minimum. Lateral subsurface drainage tiles are installed to provide subsurface drainage and are connected to a main tile line operated with an outlet control structure for controlled drainage (CD). This study evaluates the crop yield and water table effects of the SD system compared to FD over nine crop seasons from 2014-2022. The SD treatment increased yield in eight of the nine crop seasons overall, four of five corn (Zea mays L.) crops, and all four soybean (Glycine max L.) crops. Overall, SD increased corn yields by 0.4 Mg/ha or 4% (0.7 Mg/ha or 6.6% with the exclusion of 2016) and soybean yields by 0.5 Mg/ha (14.3%). The effects of SD on crop yield and water table show that the system can be utilized to improve crop health and provide better management of cropland for producers. Keywords: Corn Yield, Drainage Water Management, Soybean Yield, Surface Drainage, Water Table.}, number={2}, journal={JOURNAL OF THE ASABE}, author={Watkins, Mitchell L. and Poole, Chad and Youssef, Mohamed A. and Moursi, Hossam and Vann, Rachel and Heiniger, Ron}, year={2024}, pages={349–361} }
 @article{moursi_youssef_poole_2024, title={THE EFFECT OF DRAINAGE AND SUBIRRIGATION FROM A SMALL DRAINAGE WATER RECYCLING RESERVOIR ON CORN AND SOYBEAN YIELDS IN EASTERN NORTH CAROLINA}, volume={67}, ISSN={["2769-3287"]}, DOI={10.13031/ja.15536}, abstractNote={Highlights The Drainage Water Recycling (DWR) reservoir stored enough water to meet irrigation demand in three of four growing seasons. Subirrigation raised the groundwater table by an average of 15 cm. On average, DWR increased corn and soybean yields by 0.52 Mg ha -1 (8%) and 0.45 Mg ha -1 (17%), respectively. Subirrigation from the small size DWR reservoir did not protect corn from extended dry conditions during the growing season. Nutrients recycled back to the field via supplemental irrigation were not large enough to reduce fertilizer application rate. Abstract. Drainage water recycling (DWR) has been proposed as a source of supplemental irrigation to increase crop production resilience to extended and more frequent dry periods during the crop growing season; however, the system’s potential benefits have not been adequately quantified. The main objective of this study was to assess the performance of a DWR system for providing water for supplemental irrigation to corn and soybean at a research site in eastern North Carolina and quantify corn and soybean yield responses during 4 growing seasons (2018-2021) with varying weather conditions. Two treatments were implemented at the study site: DWR and the control (CT) treatment. The CT treatment was a 11.23 ha non-irrigated field that was primarily drained by a surface drainage system. The DWR treatment (11.48 ha) had a subsurface drainage system that provided drainage during the wet periods and subirrigation during the dry periods of the growing season. A small size reservoir (5,458 m3) was used to collect surface runoff and subsurface drainage and subirrigate the DWR treatment. Results showed that the DWR reservoir stored enough water to meet irrigation requirements in 3 of the four growing seasons and provided 5 to 73 mm of irrigation to the DWR treatment. Subirrigation raised the groundwater table by an average of 15 cm, which helped increase the upward movement of soil water to the root zone and meet crop evapotranspiration demand. DWR increased corn yields by 0.13 and 0.91 Mg ha-1 (1% and 79%) and soybean yields by 0.31 and 0.59 Mg ha-1 (9% and 30%). Subirrigation, which is generally less efficient than overhead irrigation methods, did not optimize the use of the limited water stored in the small reservoir and could not provide enough protection to corn against prolonged dry conditions in the 2019 growing season. The amount of nutrients recycled back to the field through subirrigation was not large enough to help reduce fertilizer application rate. Overall, the results demonstrated that DWR is a promising practice for increasing the resilience of crop production in the southeastern U.S. to the uncertainty in precipitation, which is expected to intensify by climate change. Monitoring the performance of DWR for longer periods with varying factors of weather, soil, and system design and management would help guide the design and management of the system to optimize the performance and minimize the implementation cost. Keywords: Drainage water management, Drainage water reuse, Irrigation reservoir, On-farm water storage, Subsurface drainage, Supplemental irrigation.}, number={1}, journal={JOURNAL OF THE ASABE}, author={Moursi, Hossam and Youssef, Mohamed A. and Poole, Chad}, year={2024}, pages={13–25} }
 @article{moursi_youssef_poole_castro-bolinaga_chescheir_richardson_2023, title={Drainage water recycling reduced nitrogen, phosphorus, and sediment losses from a drained agricultural field in eastern North Carolina, USA}, volume={279}, ISSN={["1873-2283"]}, DOI={10.1016/j.agwat.2023.108179}, abstractNote={An experimental study was conducted to evaluate the effect of drainage water recycling (DWR) on reducing nitrogen (N), phosphorus (P), and sediment losses from agricultural fields to downstream surface water bodies. The two-year study (May 2019-April 2021) was conducted at an agricultural field in eastern North Carolina, U.S.A. A reservoir existed at the site was used to store subsurface drainage and surface runoff water during wet periods and provide supplemental irrigation during dry periods of the crop growing season. On average, the reservoir retained 14% of received inflow, with a higher flow reduction in the dry year (2019–2020; 29%) than the wet year (2020–2021; 8%). The hydraulic retention time (HRT) for the reservoir was 33.8 days for the dry year and 12.4 days for the wet year. The reservoir significantly reduced the loadings of N by 47%, P by 30% and sediment by 87%. Nitrogen load reduction was primarily driven by nitrate assimilation, the dominant form of N in the reservoir. Phosphorus load reduction was attributed to Orthophosphate assimilation as the reservoir released more particulate P than received. Reductions in both water flow and species concentration contributed to nutrient load reductions. Results suggested the removal efficiency of the reservoir would be highest during the summer and early fall months when the reservoir has a smaller water volume (due to irrigation), longer HRT, and warmer temperature. This study clearly demonstrated the potential of DWR for significantly reducing N, P, and sediment losses from agricultural land to receiving surface water. Further research is needed to investigate the physical, chemical, and biological processes that occur in the storage reservoir and affect the fate and transport of nutrients and sediment. The understanding of these processes will enable optimizing the treatment efficiency of DWR, which maximizes the system's benefits and reduces construction cost.}, journal={AGRICULTURAL WATER MANAGEMENT}, author={Moursi, Hossam and Youssef, Mohamed A. and Poole, Chad A. and Castro-Bolinaga, Celso F. and Chescheir, George M. and Richardson, Robert J.}, year={2023}, month={Apr} }
 @article{moursi_youssef_chescheir_2022, title={Development and application of DRAINMOD model for simulating crop yield and water conservation benefits of drainage water recycling}, volume={266}, ISSN={["1873-2283"]}, DOI={10.1016/j.agwat.2022.107592}, abstractNote={Drainage water recycling (DWR) is an emerging practice that has the potential to increase crop yield and improve water quality. DWR involves capturing and storing subsurface drainage water and surface runoff in ponds or reservoirs, and using this water for supplemental irrigation during dry periods of the growing season. The main objective of this study was to enhance DRAINMOD model to simulate the hydrology and crop yield of DWR systems. The expanded model; named DRAINMOD-DWR, has a new module that conducts a water balance of the storage reservoir and simulates the interaction between the reservoir and the field, irrigated from and/or draining into the reservoir. The model predicts the long-term performance of DWR as affected by weather conditions, soil type, crop rotation, reservoir size, and irrigation and drainage management. Three performance metrics were defined based on model predictions to quantify irrigation, crop yield, and water capture benefits of DWR. To demonstrate the new features of the model, uncalibrated DRAINMOD-DWR was applied to a hypothetical DWR system with continuous corn using a 50-yr (1970–2019) weather record in Eastern North Carolina, U.S. Different reservoir sizes were simulated to demonstrate how the model can predict the effect of storage capacity on the system’s performance. The model predicted that a 3.0-m deep reservoir with a surface area of 4% of the field area would optimize corn yield for the simulated conditions. The model application clearly demonstrated the DRAINMOD-DWR model’s capability of optimizing the DWR system design to avoid under-sizing or over-sizing the storage reservoir, which reduces system’s performance and increases implementation cost. Research is needed to test DRAINMOD-DWR using field measured data, and to develop routines for simulating the fate and transport of nutrients and sediment in the storage reservoir, which would enable the model to predict the water quality benefits of DWR.}, journal={AGRICULTURAL WATER MANAGEMENT}, author={Moursi, Hossam and Youssef, Mohamed A. and Chescheir, George M.}, year={2022}, month={May} }
 @article{moursi_kim_kaluarachchi_2017, title={A probabilistic assessment of agricultural water scarcity in a semi-arid and snowmelt-dominated river basin under climate change}, volume={193}, ISSN={["1873-2283"]}, DOI={10.1016/j.agwat.2017.08.010}, abstractNote={Water resources planning and management is crucial and challenging in semi-arid regions to minimize water scarcity. Potential impacts due to climate change are a concern to water managers and stakeholders in semi-arid river basins with limited water availability. This study provides a probabilistic assessment of climate change impacts on water scarcity in the Sevier River Basin of Utah, which has a snowmelt-driven water supply and high agricultural water demands, using a decision-scaling framework. The methodology consists of a bottom-up approach that uses climate response functions, together with projections from 31 general circulation models (GCMs), to assess vulnerability to water scarcity for 2000–2099. Water scarcity is defined using an index comparing water availability to crop water demand predicted by the AquaCrop model from the Food and Agriculture Organization. Results showed that off-season precipitation is the most sensitive factor affecting water scarcity in the basin, followed by precipitation and temperature during the growing seasons. The GCM projections of temperature and precipitation suggest an increasing availability of water for agriculture in the basin. Still, a considerable risk probability of agricultural water shortage was found in years 2025 through 2049 with the emission scenario RCP4.5, suggesting the need for adaptation and mitigation strategies. The bottom-up decision scaling approach used here with a wide range of GCMs was practical to explore climate risk to agricultural water scarcity given the simplicity and minimal computational requirement.}, journal={AGRICULTURAL WATER MANAGEMENT}, author={Moursi, Hossam and Kim, Daeha and Kaluarachchi, Jagath J.}, year={2017}, month={Nov}, pages={142–152} }