IDEAS home Printed from https://ideas.repec.org/a/eee/agiwat/v206y2018icp217-228.html
   My bibliography  Save this article

Evaluating evapotranspiration estimation methods in APEX model for dryland cropping systems in a semi-arid region

Author

Listed:
  • Tadesse, Haile K.
  • Moriasi, Daniel N.
  • Gowda, Prasanna H.
  • Marek, Gary
  • Steiner, Jean L.
  • Brauer, David
  • Talebizadeh, Mansour
  • Nelson, Amanda
  • Starks, Patrick

Abstract

Evapotranspiration (ET), is a major component of the hydrologic budget and therefore it requires accurate estimation. The Agricultural Policy/Environmental eXtender (APEX), a hydrologic and water quality model developed for evaluating the effect of agricultural production management practices on the environment. It has five different methods to simulate ET. The objectives of this study were to: determine the impact of using different ET methods in APEX on sensitive ET parameters in semi-arid environments, determine reasonable range of values for sensitive parameters, and compare performance of these methods using multiple criteria. ET and crop yield data measured in the Lysimeter fields located in the USDA-ARS Conservation and Production Research Laboratory, Bushland, Texas were used to calibrate and validate the model. Results indicated that selection of statistical model performance measure and ET method affects the number of sensitive parameters and parameter rank. The number of sensitive parameters remained relatively stable among ET simulation methods but there was large variability in parameter sensitivity ranks. It is also important that users carefully choose appropriate statistical measure to use depending on the goals of their study. With the exception of maximum rainfall intercept, exponent coefficient rainfall, SCS index coefficient, rain intercept coefficient, and root growth soil strength, all methods had similar ranges of values for the sensitive parameters. In general there were no large differences in the performance of ET methods. However, Penman-Monteith method simulated ET relatively better than the other methods, which may be explained by the fact that it is a physically-based method with many weather variables whose data was available for the study area. However, the study findings indicate that the other ET methods can provide satisfactory results in regions with limited weather data.

Suggested Citation

  • Tadesse, Haile K. & Moriasi, Daniel N. & Gowda, Prasanna H. & Marek, Gary & Steiner, Jean L. & Brauer, David & Talebizadeh, Mansour & Nelson, Amanda & Starks, Patrick, 2018. "Evaluating evapotranspiration estimation methods in APEX model for dryland cropping systems in a semi-arid region," Agricultural Water Management, Elsevier, vol. 206(C), pages 217-228.
  • Handle: RePEc:eee:agiwat:v:206:y:2018:i:c:p:217-228
    DOI: 10.1016/j.agwat.2018.04.007
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378377418303482
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.agwat.2018.04.007?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. Sentelhas, Paulo C. & Gillespie, Terry J. & Santos, Eduardo A., 2010. "Evaluation of FAO Penman-Monteith and alternative methods for estimating reference evapotranspiration with missing data in Southern Ontario, Canada," Agricultural Water Management, Elsevier, vol. 97(5), pages 635-644, May.
    2. Moriasi, Daniel N. & King, Kevin W. & Bosch, David D. & Bjorneberg, Dave L. & Teet, Stephen & Guzman, Jorge A. & Williams, Mark R., 2016. "Framework to parameterize and validate APEX to support deployment of the nutrient tracking tool," Agricultural Water Management, Elsevier, vol. 177(C), pages 146-164.
    3. Pandeya, B. & Mulligan, M., 2013. "Modelling crop evapotranspiration and potential impacts on future water availability in the Indo-Gangetic Basin," Agricultural Water Management, Elsevier, vol. 129(C), pages 163-172.
    4. Aouissi, Jalel & Benabdallah, Sihem & Lili Chabaâne, Zohra & Cudennec, Christophe, 2016. "Evaluation of potential evapotranspiration assessment methods for hydrological modelling with SWAT—Application in data-scarce rural Tunisia," Agricultural Water Management, Elsevier, vol. 174(C), pages 39-51.
    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. Luo, Yao & Wang, Hongya, 2019. "Modeling the impacts of agricultural management strategies on crop yields and sediment yields using APEX in Guizhou Plateau, southwest China," Agricultural Water Management, Elsevier, vol. 216(C), pages 325-338.
    2. Edward Osei & Syed H. Jafri & Philip W. Gassman & Ali Saleh, 2023. "Simulated Ecosystem and Farm-Level Economic Impacts of Conservation Tillage in a Northeastern Iowa County," Agriculture, MDPI, vol. 13(4), pages 1-22, April.
    3. Dong, Shide & Wang, Guangmei & Kang, Yaohu & Ma, Qian & Wan, Shuqin, 2022. "Soil water and salinity dynamics under the improved drip-irrigation scheduling for ecological restoration in the saline area of Yellow River basin," Agricultural Water Management, Elsevier, vol. 264(C).
    4. Edward Osei & Syed H. Jafri & Ali Saleh & Philip W. Gassman & Oscar Gallego, 2023. "Simulated Climate Change Impacts on Corn and Soybean Yields in Buchanan County, Iowa," Agriculture, MDPI, vol. 13(2), pages 1-21, January.
    5. Zhao, Jie & Zhang, Xuepeng & Yang, Yadong & Zang, Huadong & Yan, Peng & Meki, Manyowa N. & Doro, Luca & Sui, Peng & Jeong, Jaehak & Zeng, Zhaohai, 2021. "Alternative cropping systems for groundwater irrigation sustainability in the North China Plain," Agricultural Water Management, Elsevier, vol. 250(C).

    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. Cunha, Angélica Carvalho & Filho, Luís Roberto Almeida Gabriel & Tanaka, Adriana Aki & Goes, Bruno Cesar & Putti, Fernando Ferrari, 2021. "Influence Of The Estimated Global Solar Radiation On The Reference Evapotranspiration Obtained Through The Penman-Monteith Fao 56 Method," Agricultural Water Management, Elsevier, vol. 243(C).
    2. Gonçalo C. Rodrigues & Ricardo P. Braga, 2021. "Estimation of Reference Evapotranspiration during the Irrigation Season Using Nine Temperature-Based Methods in a Hot-Summer Mediterranean Climate," Agriculture, MDPI, vol. 11(2), pages 1-13, February.
    3. Choudhury, B.U. & Singh, Anil Kumar & Pradhan, S., 2013. "Estimation of crop coefficients of dry-seeded irrigated rice–wheat rotation on raised beds by field water balance method in the Indo-Gangetic plains, India," Agricultural Water Management, Elsevier, vol. 123(C), pages 20-31.
    4. Houshang Ghamarnia & Vahid Rezvani & Erfan Khodaei & Hossein Mirzaei, 2012. "Time and Place Calibration of the Hargreaves Equation for Estimating Monthly Reference Evapotranspiration under Different Climatic Conditions," Journal of Agricultural Science, Canadian Center of Science and Education, vol. 4(3), pages 111-111, January.
    5. Yin, Juan & Deng, Zhen & Ines, Amor V.M. & Wu, Junbin & Rasu, Eeswaran, 2020. "Forecast of short-term daily reference evapotranspiration under limited meteorological variables using a hybrid bi-directional long short-term memory model (Bi-LSTM)," Agricultural Water Management, Elsevier, vol. 242(C).
    6. Ippolito, Matteo & De Caro, Dario & Cannarozzo, Marcella & Provenzano, Giuseppe & Ciraolo, Giuseppe, 2024. "Evaluation of daily crop reference evapotranspiration and sensitivity analysis of FAO Penman-Monteith equation using ERA5-Land reanalysis database in Sicily, Italy," Agricultural Water Management, Elsevier, vol. 295(C).
    7. Sangchul Lee & Junyu Qi & Hyunglok Kim & Gregory W. McCarty & Glenn E. Moglen & Martha Anderson & Xuesong Zhang & Ling Du, 2021. "Utility of Remotely Sensed Evapotranspiration Products to Assess an Improved Model Structure," Sustainability, MDPI, vol. 13(4), pages 1-18, February.
    8. Paredes, Paula & Trigo, Isabel & de Bruin, Henk & Simões, Nuno & Pereira, Luis S., 2021. "Daily grass reference evapotranspiration with Meteosat Second Generation shortwave radiation and reference ET products," Agricultural Water Management, Elsevier, vol. 248(C).
    9. Aouissi, Jalel & Benabdallah, Sihem & Lili Chabaâne, Zohra & Cudennec, Christophe, 2016. "Evaluation of potential evapotranspiration assessment methods for hydrological modelling with SWAT—Application in data-scarce rural Tunisia," Agricultural Water Management, Elsevier, vol. 174(C), pages 39-51.
    10. Yan, Shicheng & Wu, Lifeng & Fan, Junliang & Zhang, Fucang & Zou, Yufeng & Wu, You, 2021. "A novel hybrid WOA-XGB model for estimating daily reference evapotranspiration using local and external meteorological data: Applications in arid and humid regions of China," Agricultural Water Management, Elsevier, vol. 244(C).
    11. Peddinti, Srinivasa Rao & Kambhammettu, BVN P, 2019. "Dynamics of crop coefficients for citrus orchards of central India using water balance and eddy covariance flux partition techniques," Agricultural Water Management, Elsevier, vol. 212(C), pages 68-77.
    12. Babak Farjad & Anil Gupta & Danielle J. Marceau, 2016. "Annual and Seasonal Variations of Hydrological Processes Under Climate Change Scenarios in Two Sub-Catchments of a Complex Watershed," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(8), pages 2851-2865, June.
    13. Amanda M. Nelson & Nicolas E. Quintana Ashwell & Christopher D. Delhom & Drew M. Gholson, 2022. "Leveraging Big Data to Preserve the Mississippi River Valley Alluvial Aquifer: A Blueprint for the National Center for Alluvial Aquifer Research," Land, MDPI, vol. 11(11), pages 1-17, October.
    14. Tewekel Melese Gemechu & Hongling Zhao & Shanshan Bao & Cidan Yangzong & Yingying Liu & Fengping Li & Hongyan Li, 2021. "Estimation of Hydrological Components under Current and Future Climate Scenarios in Guder Catchment, Upper Abbay Basin, Ethiopia, Using the SWAT," Sustainability, MDPI, vol. 13(17), pages 1-19, August.
    15. Xiang, Keyu & Li, Yi & Horton, Robert & Feng, Hao, 2020. "Similarity and difference of potential evapotranspiration and reference crop evapotranspiration – a review," Agricultural Water Management, Elsevier, vol. 232(C).
    16. Nam, Won-Ho & Hong, Eun-Mi & Choi, Jin-Yong, 2015. "Has climate change already affected the spatial distribution and temporal trends of reference evapotranspiration in South Korea?," Agricultural Water Management, Elsevier, vol. 150(C), pages 129-138.
    17. Sharma, Harmandeep & Shukla, Manoj K. & Bosland, Paul W. & Steiner, Robert, 2017. "Soil moisture sensor calibration, actual evapotranspiration, and crop coefficients for drip irrigated greenhouse chile peppers," Agricultural Water Management, Elsevier, vol. 179(C), pages 81-91.
    18. Berti, Antonio & Tardivo, Gianmarco & Chiaudani, Alessandro & Rech, Francesco & Borin, Maurizio, 2014. "Assessing reference evapotranspiration by the Hargreaves method in north-eastern Italy," Agricultural Water Management, Elsevier, vol. 140(C), pages 20-25.
    19. Valle Júnior, Luiz C.G. & Ventura, Thiago M. & Gomes, Raphael S.R. & de S. Nogueira, José & de A. Lobo, Francisco & Vourlitis, George L. & Rodrigues, Thiago R., 2020. "Comparative assessment of modelled and empirical reference evapotranspiration methods for a brazilian savanna," Agricultural Water Management, Elsevier, vol. 232(C).
    20. Shih-Lun Fang & Yi-Shan Lin & Sheng-Chih Chang & Yi-Lung Chang & Bing-Yun Tsai & Bo-Jein Kuo, 2024. "Using Artificial Intelligence Algorithms to Estimate and Short-Term Forecast the Daily Reference Evapotranspiration with Limited Meteorological Variables," Agriculture, MDPI, vol. 14(4), pages 1-20, March.

    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:206:y:2018:i:c:p:217-228. 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.