IDEAS home Printed from https://ideas.repec.org/a/eee/agiwat/v271y2022ics0378377422003390.html
   My bibliography  Save this article

Satellite remote sensing of crop water use across the Missouri River Basin for 1986–2018 period

Author

Listed:
  • Bawa, Arun
  • Senay, Gabriel B.
  • Kumar, Sandeep

Abstract

Understanding historical crop water use (CWU) dynamics is important to improve land and water management. In this study, well-validated (coefficient of determination = 0.91, percent bias = 4%, and percent root mean square error = 11.8%) Landsat-based actual evapotranspiration (ETa) time-series estimations were used to (1) assess summer season CWU (CWU-Su) dynamics, (2) investigate CWU-Su trends over the study period (1986–2018; 33 years) at the regional- and pixel-scales, and (3) attribute CWU-Su driving factors across Missouri River Basin. Spatial variability of the ETa estimations along with the observed bimodal probability density distribution of ETa highlighted a strong relation between land cover and water uses across the basin. The bimodal distribution of ETa also indicated the presence of two major landcovers in the basin. The drier foothill regions in northwestern Missouri River Basin, dominated by grassland/shrubland, showed lower ETa (< 500 mm/year), whereas cropland dominated regions in lower semi-humid basin and forested subbasins exhibited higher ETa (> 600 mm/year). The CWU-Su anomalies revealed the vulnerability of the basin to year-to-year weather conditions. The CWU-Su trend analysis revealed a significant positive trend (p < 0.1) at the regional-scale affecting 30% of basin’s cropland pixels. The cropland pixels under positive CWU-Su trend were found to be clustered in the eastern and central Missouri River Basin as a result of the combined effect of increased crop production area, increased crop yields, crop practice shifts to higher biomass crops, and increased irrigated land. The effect of improved irrigation and water management practices on reducing CWU-Su was observed in western Missouri River Basin, which had a stable major crop throughout the study period. Overall, the study highlights the usefulness of Landsat imagery and remote sensing-based ETa modeling approaches in generating historical time-series ETa maps over a wide range of elevation, vegetation, and climate.

Suggested Citation

  • Bawa, Arun & Senay, Gabriel B. & Kumar, Sandeep, 2022. "Satellite remote sensing of crop water use across the Missouri River Basin for 1986–2018 period," Agricultural Water Management, Elsevier, vol. 271(C).
  • Handle: RePEc:eee:agiwat:v:271:y:2022:i:c:s0378377422003390
    DOI: 10.1016/j.agwat.2022.107792
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378377422003390
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.agwat.2022.107792?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. Deines, Jillian M. & Schipanski, Meagan E. & Golden, Bill & Zipper, Samuel C. & Nozari, Soheil & Rottler, Caitlin & Guerrero, Bridget & Sharda, Vaishali, 2020. "Transitions from irrigated to dryland agriculture in the Ogallala Aquifer: Land use suitability and regional economic impacts," Agricultural Water Management, Elsevier, vol. 233(C).
    2. Allen, Richard G. & Pereira, Luis S. & Howell, Terry A. & Jensen, Marvin E., 2011. "Evapotranspiration information reporting: I. Factors governing measurement accuracy," Agricultural Water Management, Elsevier, vol. 98(6), pages 899-920, April.
    3. Velpuri, Naga Manohar & Senay, G. B. & Schauer, M. & Garcia, C. A. & Singh, R. K. & Friedrichs, M. & Kagone, S. & Haynes, J. & Conlon, T., 2020. "Evaluation of hydrologic impact of an irrigation curtailment program using Landsat satellite data," Papers published in Journals (Open Access), International Water Management Institute, pages 34(8):1697-.
    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. Sharofiddinov, Husniddin & Islam, Moinul & Kotani, Koji, 2024. "How does the number of water users in a land reform matter for water availability in agriculture?," Agricultural Water Management, Elsevier, vol. 293(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. Feng, Yu & Gong, Daozhi & Mei, Xurong & Hao, Weiping & Tang, Dahua & Cui, Ningbo, 2017. "Energy balance and partitioning in partial plastic mulched and non-mulched maize fields on the Loess Plateau of China," Agricultural Water Management, Elsevier, vol. 191(C), pages 193-206.
    2. Kelly, T.D. & Foster, T. & Schultz, David M., 2023. "Assessing the value of adapting irrigation strategies within the season," Agricultural Water Management, Elsevier, vol. 275(C).
    3. Darouich, Hanaa & Karfoul, Razan & Ramos, Tiago B. & Moustafa, Ali & Shaheen, Baraa & Pereira, Luis S., 2021. "Crop water requirements and crop coefficients for jute mallow (Corchorus olitorius L.) using the SIMDualKc model and assessing irrigation strategies for the Syrian Akkar region," Agricultural Water Management, Elsevier, vol. 255(C).
    4. Escarabajal-Henarejos, D. & Fernández-Pacheco, D.G. & Molina-Martínez, J.M. & Martínez-Molina, L. & Ruiz-Canales, A., 2015. "Selection of device to determine temperature gradients for estimating evapotranspiration using energy balance method," Agricultural Water Management, Elsevier, vol. 151(C), pages 136-147.
    5. Gao, Yang & Yang, Linlin & Shen, Xiaojun & Li, Xinqiang & Sun, Jingsheng & Duan, Aiwang & Wu, Laosheng, 2014. "Winter wheat with subsurface drip irrigation (SDI): Crop coefficients, water-use estimates, and effects of SDI on grain yield and water use efficiency," Agricultural Water Management, Elsevier, vol. 146(C), pages 1-10.
    6. Yang, Yanmin & Yang, Yonghui & Han, Shumin & Li, Huilong & Wang, Lu & Ma, Qingtao & Ma, Lexin & Wang, Linna & Hou, Zhenjun & Chen, Li & Liu, De Li, 2023. "Comparison of water-saving potential of fallow and crop change with high water-use winter-wheat – summer-maize rotation," Agricultural Water Management, Elsevier, vol. 289(C).
    7. Jovanovic, N. & Pereira, L.S. & Paredes, P. & Pôças, I. & Cantore, V. & Todorovic, M., 2020. "A review of strategies, methods and technologies to reduce non-beneficial consumptive water use on farms considering the FAO56 methods," Agricultural Water Management, Elsevier, vol. 239(C).
    8. Fuentes, Sigfredo & Ortega-Farías, Samuel & Carrasco-Benavides, Marcos & Tongson, Eden & Gonzalez Viejo, Claudia, 2024. "Actual evapotranspiration and energy balance estimation from vineyards using micro-meteorological data and machine learning modeling," Agricultural Water Management, Elsevier, vol. 297(C).
    9. Wallander, Steven & Hrozencik, Aaron & Aillery, Marcel, 2022. "Irrigation Organizations: Drought Planning and Response," Economic Brief 327233, United States Department of Agriculture, Economic Research Service.
    10. Shahadha, Saadi Sattar & Wendroth, Ole & Zhu, Junfeng & Walton, Jason, 2019. "Can measured soil hydraulic properties simulate field water dynamics and crop production?," Agricultural Water Management, Elsevier, vol. 223(C), pages 1-1.
    11. Xinxin Fu & Xiaofeng Wang & Jitao Zhou & Jiahao Ma, 2021. "Optimizing the Production-Living-Ecological Space for Reducing the Ecosystem Services Deficit," Land, MDPI, vol. 10(10), pages 1-17, September.
    12. Wang, Weishu & Rong, Yao & Dai, Xiaoqin & Zhang, Chenglong & Wang, Chaozi & Huo, Zailin, 2024. "Variation and attribution of energy distribution for salinized sunflower farmland in arid area," Agricultural Water Management, Elsevier, vol. 297(C).
    13. Escarabajal-Henarejos, D. & Molina-Martínez, J.M. & Fernández-Pacheco, D.G. & Cavas-Martínez, F. & García-Mateos, G., 2015. "Digital photography applied to irrigation management of Little Gem lettuce," Agricultural Water Management, Elsevier, vol. 151(C), pages 148-157.
    14. Zhao, Nana & Liu, Yu & Cai, Jiabing & Paredes, Paula & Rosa, Ricardo D. & Pereira, Luis S., 2013. "Dual crop coefficient modelling applied to the winter wheat–summer maize crop sequence in North China Plain: Basal crop coefficients and soil evaporation component," Agricultural Water Management, Elsevier, vol. 117(C), pages 93-105.
    15. Hu, Xinyu & Zhao, Jinfeng & Sun, Shikun & Jia, Chengru & Zhang, Fuyao & Ma, Yizhe & Wang, Kaixuan & Wang, Yubao, 2023. "Evaluation of the temporal reconstruction methods for MODIS-based continuous daily actual evapotranspiration estimation," Agricultural Water Management, Elsevier, vol. 275(C).
    16. Elfarkh, Jamal & Simonneaux, Vincent & Jarlan, Lionel & Ezzahar, Jamal & Boulet, Gilles & Chakir, Adnane & Er-Raki, Salah, 2022. "Evapotranspiration estimates in a traditional irrigated area in semi-arid Mediterranean. Comparison of four remote sensing-based models," Agricultural Water Management, Elsevier, vol. 270(C).
    17. Segovia-Cardozo, Daniel Alberto & Rodríguez-Sinobas, Leonor & Zubelzu, Sergio, 2019. "Water use efficiency of corn among the irrigation districts across the Duero river basin (Spain): Estimation of local crop coefficients by satellite images," Agricultural Water Management, Elsevier, vol. 212(C), pages 241-251.
    18. Muniandy, Josilva M. & Yusop, Zulkifli & Askari, Muhamad, 2016. "Evaluation of reference evapotranspiration models and determination of crop coefficient for Momordica charantia and Capsicum annuum," Agricultural Water Management, Elsevier, vol. 169(C), pages 77-89.
    19. Feng, Jiaojiao & Wang, Weizhen & Xu, Feinan & Wang, Shengtang, 2024. "Evaluating the ability of deep learning on actual daily evapotranspiration estimation over the heterogeneous surfaces," Agricultural Water Management, Elsevier, vol. 291(C).
    20. Kukal, M.S. & Irmak, S., 2020. "Impact of irrigation on interannual variability in United States agricultural productivity," Agricultural Water Management, Elsevier, vol. 234(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:271:y:2022:i:c:s0378377422003390. 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.