IDEAS home Printed from https://ideas.repec.org/a/eee/agiwat/v252y2021ics037837742100161x.html
   My bibliography  Save this article

Large-scale monitoring of soil moisture using Temperature Vegetation Quantitative Index (TVQI) and exponential filtering: A case study in Beijing

Author

Listed:
  • Zhao, Ziyang
  • Wang, Hongrui
  • Qin, Daoqing
  • Wang, Cheng

Abstract

In this study, to understand the variation trend of soil moisture in Beijing, surface soil moisture retrieval, deep soil moisture estimation and spatiotemporal distribution characteristics from 2013 to 2014 were analyzed. The results showed that the Temperature Vegetation Quantitative Index (TVQI), which was modified from the TVDI by the quantitative dry edge and wet edge, is effective for predicting surface soil moisture. The coefficient of determination (R2), root man squared error (RMSE), and Nash-Sutcliffe efficiency coefficient (NSE) of the TVQI increased by 0.2, 0.3%, and 4.6, respectively, compared to those of the TVDI. Moreover, the TVQI is closely related to cumulative precipitation within 1 month, as the correlation is the highest in this time interval. The accuracy of surface soil moisture retrieval was good, with relative error (RE), R2, and NSE values of 6%, 0.9 and 0.7, respectively. The deep soil moisture estimations performed well at both 20 cm and 40 cm, with an average R2 above 0.9, an average RE below 0.1 and an average NSE above 0.7. However, the prediction accuracy decreased as the soil depth increased. Topt, the best characteristic time length of the exponential filter, was significantly related to the soil bulk density, while the precipitation meteorological condition had little effect. Moreover, the average Topt of all stations can be used instead of the Topt of each station. Beijing, the study area, is dry throughout the year, with soil moisture reaching a minimum in May and a maximum in July. The changes in soil moisture at 10 cm, 20 cm and 40 cm were consistent, and soil moisture increased with soil depth. Furthermore, the variation trends of soil moisture were high in the east and low in the west. Not only is this study important for understanding soil moisture variation trends; it also provides a preliminary reference for water management in Beijing.

Suggested Citation

  • Zhao, Ziyang & Wang, Hongrui & Qin, Daoqing & Wang, Cheng, 2021. "Large-scale monitoring of soil moisture using Temperature Vegetation Quantitative Index (TVQI) and exponential filtering: A case study in Beijing," Agricultural Water Management, Elsevier, vol. 252(C).
    • Handle: RePEc:eee:agiwat:v:252:y:2021:i:c:s037837742100161x
    DOI: 10.1016/j.agwat.2021.106896
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S037837742100161X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.agwat.2021.106896?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. Zhang, Biao & Fu, Zetian & Wang, Jieqiong & Zhang, Lingxian, 2019. "Farmers’ adoption of water-saving irrigation technology alleviates water scarcity in metropolis suburbs: A case study of Beijing, China," Agricultural Water Management, Elsevier, vol. 212(C), pages 349-357.
    2. Zhao, Ziyang & Wang, Hongrui & Wang, Cheng & Li, Wangcheng & Chen, Hao & Deng, Caiyun, 2020. "Changes in reference evapotranspiration over Northwest China from 1957 to 2018: Variation characteristics, cause analysis and relationships with atmospheric circulation," Agricultural Water Management, Elsevier, vol. 231(C).
    Full references (including those not matched with items on IDEAS)

    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. Bopp, Carlos & Jara-Rojas, Roberto & Bravo-Ureta, Boris & Engler, Alejandra, 2022. "Irrigation water use, shadow values and productivity: Evidence from stochastic production frontiers in vineyards," Agricultural Water Management, Elsevier, vol. 271(C).
    2. Wu, Hao & Xu, Min & Peng, Zhuoyue & Chen, Xiaoping, 2022. "Quantifying the potential impacts of meltwater on cotton yields in the Tarim River Basin, Central Asia," Agricultural Water Management, Elsevier, vol. 269(C).
    3. Mattoussi, Wided & Mattoussi, Foued & Larnaout, Afrah, 2023. "Optimal subsidization for the adoption of new irrigation technologies," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 1126-1141.
    4. Gonzalo Villa‐Cox & Francesco Cavazza & Cristian Jordan & Mijail Arias‐Hidalgo & Paúl Herrera & Ramon Espinel & Davide Viaggi & Stijn Speelman, 2021. "Understanding constraints on private irrigation adoption decisions under uncertainty in data constrained settings: A novel empirical approach tested on Ecuadorian Cocoa cultivations," Agricultural Economics, International Association of Agricultural Economists, vol. 52(6), pages 985-999, November.
    5. Qiu, Xin & Jin, Jianjun & He, Rui & Mao, Jiansu, 2022. "The deviation between the willingness and behavior of farmers to adopt electricity-saving tricycles and its influencing factors in Dazu District of China," Energy Policy, Elsevier, vol. 167(C).
    6. Rouzaneh, Davoud & Yazdanpanah, Masoud & Jahromi, Arman Bakhshi, 2021. "Evaluating micro-irrigation system performance through assessment of farmers' satisfaction: implications for adoption, longevity, and water use efficiency," Agricultural Water Management, Elsevier, vol. 246(C).
    7. Diana Martínez-Arteaga & Nolver Atanacio Arias Arias & Aquiles E. Darghan & Dursun Barrios, 2023. "Identification of Influential Factors in the Adoption of Irrigation Technologies through Neural Network Analysis: A Case Study with Oil Palm Growers," Agriculture, MDPI, vol. 13(4), pages 1-13, April.
    8. Masoud Yazdanpanah & Kurt Klein & Tahereh Zobeidi & Stefan Sieber & Katharina Löhr, 2022. "Why Have Economic Incentives Failed to Convince Farmers to Adopt Drip Irrigation in Southwestern Iran?," Sustainability, MDPI, vol. 14(4), pages 1-15, February.
    9. Li, Pei & Ren, Li, 2023. "Evaluating the differences in irrigation methods for winter wheat under limited irrigation quotas in the water-food-economy nexus in the North China Plain," Agricultural Water Management, Elsevier, vol. 289(C).
    10. Tanko, Mohammed, 2022. "Nexus of risk preference, culture and religion in the adoption of improved rice varieties: Evidence from Northern Ghana," Land Use Policy, Elsevier, vol. 115(C).
    11. Zhai, Yijie & Bai, Yueyang & Wu, Zhen & Hong, Jinglan & Shen, Xiaoxu & Xie, Fei & Li, Xiangzhi, 2022. "Grain self-sufficiency versus environmental stress: An integration of system dynamics and life cycle assessment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
    12. Rui Yang & Qijie Gao, 2021. "Water-Saving Irrigation Promotion and Food Security: A Study for China," Sustainability, MDPI, vol. 13(21), pages 1-14, November.
    13. Xinyue Qu & Wenfeng Zhou & Jia He & Dingde Xu, 2023. "Land Certification, Adjustment Experience, and Green Production Technology Acceptance of Farmers: Evidence from Sichuan Province, China," Land, MDPI, vol. 12(4), pages 1-20, April.
    14. Bola Amoke Awotide & Adebayo Ogunniyi & Kehinde Oluseyi Olagunju & Lateef Olalekan Bello & Amadou Youssouf Coulibaly & Alexander Nimo Wiredu & Bourémo Kone & Aly Ahamadou & Victor Manyong & Tahirou Ab, 2022. "Evaluating the Heterogeneous Impacts of Adoption of Climate-Smart Agricultural Technologies on Rural Households’ Welfare in Mali," Agriculture, MDPI, vol. 12(11), pages 1-16, November.
    15. Jordán, Cristian & Speelman, Stijn, 2020. "On-farm adoption of irrigation technologies in two irrigated valleys in Central Chile: The effect of relative abundance of water resources," Agricultural Water Management, Elsevier, vol. 236(C).
    16. Hu, Xuhua & Chen, Mengting & Liu, Dong & Li, Dan & Jin, Li & Liu, Shaohui & Cui, Yuanlai & Dong, Bin & Khan, Shahbaz & Luo, Yufeng, 2021. "Reference evapotranspiration change in Heilongjiang Province, China from 1951 to 2018: The role of climate change and rice area expansion," Agricultural Water Management, Elsevier, vol. 253(C).
    17. Cai, Jinyang & Chen, Yiming & Hu, Ruifa & Wu, Mingyin & Shen, Zhiyang, 2022. "Discovering the impact of farmer field schools on the adoption of environmental-friendly technology," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    18. Li, Bo & Ding, Junqi & Wang, Jieqiong & Zhang, Biao & Zhang, Lingxian, 2021. "Key factors affecting the adoption willingness, behavior, and willingness-behavior consistency of farmers regarding photovoltaic agriculture in China," Energy Policy, Elsevier, vol. 149(C).
    19. Dependra Bhatta & Krishna P. Paudel & Kai Liu, 2023. "Factors influencing water conservation practices adoptions by Nepali farmers," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(10), pages 10879-10901, October.
    20. Zihan Liu & Dong Jing & Yu Han & Jingxin Yu & Tiangang Lu & Lili Zhangzhong, 2022. "Spatiotemporal Distribution Characteristics and Influencing Factors Analysis of Reference Evapotranspiration in Beijing–Tianjin–Hebei Region from 1990 to 2019 under Climate Change," Sustainability, MDPI, vol. 14(10), pages 1-22, May.

    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:252:y:2021:i:c:s037837742100161x. 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.