IDEAS home Printed from https://ideas.repec.org/a/eee/agiwat/v242y2020ics0378377420307721.html
   My bibliography  Save this article

DRAINMOD Simulation of macropore flow at subsurface drained agricultural fields: Model modification and field testing

Author

Listed:
  • Askar, Manal H
  • Youssef, Mohamed A
  • Chescheir, George M
  • Negm, Lamyaa M
  • King, Kevin W
  • Hesterberg, Dean L
  • Amoozegar, Aziz
  • Skaggs, R. Wayne

Abstract

Macropores are critical pathways through which water and pollutants can bypass the soil matrix and be rapidly transported to subsurface drains and freshwater bodies. We modified the DRAINMOD model to simulate macropore flow using a simple approach as part of developing the DRAINMOD-P model to simulate phosphorus dynamics in artificially drained agricultural lands. The Hagen-Poiseuille’s law was used to estimate the flow capacity of macropores. When ponding depths on the soil surface are greater than Kirkham’s depth, water is assumed to flow through macropores directly to tile drains without interaction with the soil matrix. In the modified model, macropore size is adjusted based on wet or dry conditions while connectivity is altered by tillage. The model was tested using a 4-year data set from a subsurface drained field in northwest Ohio. The soils at the field are classified as very poorly drained and are prone to desiccation cracking. The modified model predicted the daily and monthly subsurface drainage with average Nash-Sutcliffe efficiency (NSE) values of 0.48 and 0.59, respectively. The cumulative drainage over the 4-year simulation period was under-predicted by 8%. The new macropore component was able to capture about 75% of 60 peak drainage flow events. However, surface runoff was over-predicted for the entire study period. Annual water budgets using measured data (precipitation, subsurface drainage, and surface runoff) and model predictions (evapotranspiration, vertical seepage, and change in storage) were not balanced with an average annual imbalance of 6.4 cm. The lack of closure in the water balance suggests that errors may have occurred in field measurements, particularly, surface runoff. Overall, incorporating macropore flow into DRAINMOD improved predictions of daily drainage peaks and enabled the model to predict subsurface drainage flux contributed by macropore flow, which is critical for expanding DRAINMOD to simulate phosphorus transport in subsurface drained agricultural land.

Suggested Citation

  • Askar, Manal H & Youssef, Mohamed A & Chescheir, George M & Negm, Lamyaa M & King, Kevin W & Hesterberg, Dean L & Amoozegar, Aziz & Skaggs, R. Wayne, 2020. "DRAINMOD Simulation of macropore flow at subsurface drained agricultural fields: Model modification and field testing," Agricultural Water Management, Elsevier, vol. 242(C).
    • Handle: RePEc:eee:agiwat:v:242:y:2020:i:c:s0378377420307721
    DOI: 10.1016/j.agwat.2020.106401
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378377420307721
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.agwat.2020.106401?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Youssef, Mohamed A. & Abdelbaki, Ahmed M. & Negm, Lamyaa M. & Skaggs, R.Wayne & Thorp, Kelly R. & Jaynes, Dan B., 2018. "DRAINMOD-simulated performance of controlled drainage across the U.S. Midwest," Agricultural Water Management, Elsevier, vol. 197(C), pages 54-66.
    2. Larsson, Martin H. & Persson, Kristian & Ulén, Barbro & Lindsjö, Anders & Jarvis, Nicholas J., 2007. "A dual porosity model to quantify phosphorus losses from macroporous soils," Ecological Modelling, Elsevier, vol. 205(1), pages 123-134.
    3. Eastman, M. & Gollamudi, A. & Stämpfli, N. & Madramootoo, C.A. & Sarangi, A., 2010. "Comparative evaluation of phosphorus losses from subsurface and naturally drained agricultural fields in the Pike River watershed of Quebec, Canada," Agricultural Water Management, Elsevier, vol. 97(5), pages 596-604, May.
    4. Negm, Lamyaa M. & Youssef, Mohamed A. & Jaynes, Dan B., 2017. "Evaluation of DRAINMOD-DSSAT simulated effects of controlled drainage on crop yield, water balance, and water quality for a corn-soybean cropping system in central Iowa," Agricultural Water Management, Elsevier, vol. 187(C), pages 57-68.
    5. Negm, L.M. & Youssef, M.A. & Chescheir, G.M. & Skaggs, R.W., 2016. "DRAINMOD-based tools for quantifying reductions in annual drainage flow and nitrate losses resulting from drainage water management on croplands in eastern North Carolina," Agricultural Water Management, Elsevier, vol. 166(C), pages 86-100.
    6. Wang, X. & Mosley, C.T. & Frankenberger, J.R. & Kladivko, E.J., 2006. "Subsurface drain flow and crop yield predictions for different drain spacings using DRAINMOD," Agricultural Water Management, Elsevier, vol. 79(2), pages 113-136, January.
    7. Gunn, Kpoti M. & Baule, William J. & Frankenberger, Jane R. & Gamble, Debra L. & Allred, Barry J. & Andresen, Jeff A. & Brown, Larry C., 2018. "Modeled climate change impacts on subirrigated maize relative yield in northwest Ohio," Agricultural Water Management, Elsevier, vol. 206(C), pages 56-66.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Liu, Yi & Zeng, Wenzhi & Ao, Chang & Lei, Guoqing & Wu, Jingwei & Huang, Jiesheng & Gaiser, Thomas & Srivastava, Amit Kumar, 2022. "Optimization of winter irrigation management for salinized farmland using a coupled model of soil water flow and crop growth," Agricultural Water Management, Elsevier, vol. 270(C).
    2. Rares Halbac-Cotoara-Zamfir & Asdrubal Jesus Farias-Ramirez & Jarbas Honorio de Miranda & Maria Alejandra Moreno-Pizani & Sergio Nascimento Duarte & Franklin Javier Paredes-Trejo & Luca Salvati & Cris, 2022. "Simulation of Subsurface Drainage in the Sugarcane Crop under Different Spacing and Drain Depths," Land, MDPI, vol. 11(5), pages 1-20, April.
    3. Moursi, Hossam & Youssef, Mohamed A. & Chescheir, George M., 2022. "Development and application of DRAINMOD model for simulating crop yield and water conservation benefits of drainage water recycling," Agricultural Water Management, Elsevier, vol. 266(C).
    4. Eva Hyánková & Michal Kriška Dunajský & Ondřej Zedník & Ondřej Chaloupka & Miroslava Pumprlová Němcová, 2021. "Irrigation with Treated Wastewater as an Alternative Nutrient Source (for Crop): Numerical Simulation," Agriculture, MDPI, vol. 11(10), pages 1-20, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Singh, Shailendra & Bhattarai, Rabin & Negm, Lamyaa M. & Youssef, Mohamed A. & Pittelkow, Cameron M., 2020. "Evaluation of nitrogen loss reduction strategies using DRAINMOD-DSSAT in east-central Illinois," Agricultural Water Management, Elsevier, vol. 240(C).
    2. Ghane, Ehsan & Askar, Manal H. & Skaggs, R. Wayne, 2021. "Design drainage rates to optimize crop production for subsurface-drained fields," Agricultural Water Management, Elsevier, vol. 257(C).
    3. Youngseok Song & Moojong Park, 2021. "A Study on the Development of Reduction Facilities’ Management Standards for Agricultural Drainage for Disaster Reduction," Sustainability, MDPI, vol. 13(17), pages 1-15, August.
    4. Wen, Yeqiang & Shang, Songhao & Rahman, Khalil Ur & Xia, Yuhong & Ren, Dongyang, 2020. "A semi-distributed drainage model for monthly drainage water and salinity simulation in a large irrigation district in arid region," Agricultural Water Management, Elsevier, vol. 230(C).
    5. Youssef, Mohamed A. & Liu, Yu & Chescheir, George M. & Skaggs, R. Wayne & Negm, Lamyaa M., 2021. "DRAINMOD modeling framework for simulating controlled drainage effect on lateral seepage from artificially drained fields," Agricultural Water Management, Elsevier, vol. 254(C).
    6. Turunen, M. & Warsta, L. & Paasonen-Kivekäs, M. & Nurminen, J. & Myllys, M. & Alakukku, L. & Äijö, H. & Puustinen, M. & Koivusalo, H., 2013. "Modeling water balance and effects of different subsurface drainage methods on water outflow components in a clayey agricultural field in boreal conditions," Agricultural Water Management, Elsevier, vol. 121(C), pages 135-148.
    7. Dou, Xu & Shi, Haibin & Li, Ruiping & Miao, Qingfeng & Yan, Jianwen & Tian, Feng & Wang, Bo, 2022. "Simulation and evaluation of soil water and salt transport under controlled subsurface drainage using HYDRUS-2D model," Agricultural Water Management, Elsevier, vol. 273(C).
    8. Xu Dou & Haibin Shi & Ruiping Li & Qingfeng Miao & Feng Tian & Dandan Yu & Liying Zhou & Bo Wang, 2021. "Effects of Controlled Drainage on the Content Change and Migration of Moisture, Nutrients, and Salts in Soil and the Yield of Oilseed Sunflower in the Hetao Irrigation District," Sustainability, MDPI, vol. 13(17), pages 1-19, September.
    9. Revuelta-Acosta, J.D. & Flanagan, D.C. & Engel, B.A. & King, K.W., 2021. "Improvement of the Water Erosion Prediction Project (WEPP) model for quantifying field scale subsurface drainage discharge," Agricultural Water Management, Elsevier, vol. 244(C).
    10. Ghane, Ehsan & Askar, Manal H., 2021. "Predicting the effect of drain depth on profitability and hydrology of subsurface drainage systems across the eastern USA," Agricultural Water Management, Elsevier, vol. 258(C).
    11. Mariusz Sojka & Michał Kozłowski & Rafał Stasik & Michał Napierała & Barbara Kęsicka & Rafał Wróżyński & Joanna Jaskuła & Daniel Liberacki & Jerzy Bykowski, 2019. "Sustainable Water Management in Agriculture—The Impact of Drainage Water Management on Groundwater Table Dynamics and Subsurface Outflow," Sustainability, MDPI, vol. 11(15), pages 1-18, August.
    12. Liu, Yu & Youssef, Mohamed A. & Chescheir, George M. & Appelboom, Timothy W. & Poole, Chad A. & Arellano, Consuelo & Skaggs, R. Wayne, 2019. "Effect of controlled drainage on nitrogen fate and transport for a subsurface drained grass field receiving liquid swine lagoon effluent," Agricultural Water Management, Elsevier, vol. 217(C), pages 440-451.
    13. Yasir Abduljaleel & Ahmed Awad & Nadhir Al-Ansari & Ali Salem & Abdelazim Negm & Mohamed Elsayed Gabr, 2023. "Assessment of Subsurface Drainage Strategies Using DRAINMOD Model for Sustainable Agriculture: A Review," Sustainability, MDPI, vol. 15(2), pages 1-19, January.
    14. El-Ghannam, Mohamed K. & Aiad, Mahmoud. A. & Abdallah, Ahmed M., 2021. "Irrigation efficiency, drain outflow and yield responses to drain depth in the Nile delta clay soil, Egypt," Agricultural Water Management, Elsevier, vol. 246(C).
    15. Rares Halbac-Cotoara-Zamfir & Asdrubal Jesus Farias-Ramirez & Jarbas Honorio de Miranda & Maria Alejandra Moreno-Pizani & Sergio Nascimento Duarte & Franklin Javier Paredes-Trejo & Luca Salvati & Cris, 2022. "Simulation of Subsurface Drainage in the Sugarcane Crop under Different Spacing and Drain Depths," Land, MDPI, vol. 11(5), pages 1-20, April.
    16. Negm, L.M. & Youssef, M.A. & Skaggs, R.W. & Chescheir, G.M. & Jones, J., 2014. "DRAINMOD–DSSAT model for simulating hydrology, soil carbon and nitrogen dynamics, and crop growth for drained crop land," Agricultural Water Management, Elsevier, vol. 137(C), pages 30-45.
    17. Sidemo-Holm, William & Smith, Henrik G. & Brady, Mark V., 2018. "Improving agricultural pollution abatement through result-based payment schemes," Land Use Policy, Elsevier, vol. 77(C), pages 209-219.
    18. Feng Tian & Haibin Shi & Qingfeng Miao & Ruiping Li & Jie Duan & Xu Dou & Weiying Feng, 2023. "Soil Water and Salt Transport in Severe Saline–Alkali Soil after Ditching under Subsurface Pipe Drainage Conditions," Agriculture, MDPI, vol. 13(12), pages 1-20, November.
    19. Ramesh P. Rudra & Balew A. Mekonnen & Rituraj Shukla & Narayan Kumar Shrestha & Pradeep K. Goel & Prasad Daggupati & Asim Biswas, 2020. "Currents Status, Challenges, and Future Directions in Identifying Critical Source Areas for Non-Point Source Pollution in Canadian Conditions," Agriculture, MDPI, vol. 10(10), pages 1-25, October.
    20. Feng, Genxiang & Zhu, Chengli & Wu, Qingfeng & Wang, Ce & Zhang, Zhanyu & Mwiya, Richwell Mubita & Zhang, Li, 2021. "Evaluating the impacts of saline water irrigation on soil water-salt and summer maize yield in subsurface drainage condition using coupled HYDRUS and EPIC model," Agricultural Water Management, Elsevier, vol. 258(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:agiwat:v:242:y:2020:i:c:s0378377420307721. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/agwat .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.