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Analysis of groundwater-level fluctuation and linear regression modeling for prediction of initial groundwater level during irrigation of rice paddies in the Nasunogahara alluvial fan, central Japan

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Abstract

This study analyzed long-term fluctuations of groundwater levels in six shallow observation wells in the Nasunogahara alluvial fan, Japan’s second largest source of agricultural irrigation groundwater, and presented a simple method for predicting groundwater levels in April prior to the annual planting of paddy rice. The 22-year time-series of groundwater levels (1998–2019) clearly showed seasonal periodicity, with higher levels in summer than in winter. In particular, groundwater levels were lowest in April when groundwater demand was greatest. Groundwater levels in two wells at the beginning of the April irrigation period showed long-term declining trends that can be attributed more to changes in land use than to changes in precipitation or air temperature. A simple linear regression of mean groundwater level in April to antecedent precipitation provided reasonable predictions of April groundwater levels, which were significantly influenced by precipitation in the preceding 3–5 months. Further modeling after subtraction of long-term seasonal trends (detrending) improved these estimates. The performance of the linear regression model for prediction of April groundwater levels is comparable to that of the statistical benchmark model. Using long-term monthly or seasonal weather forecasts, the modeling presented here can be applied to inform appropriate changes of water use practices, such as decreasing groundwater extraction by implementing rotational water supply, changing rice-cropping seasons, or targeting deeper aquifers. The identification of the critical period of antecedent precipitation that affected April groundwater levels in the Nasunogahara alluvial fan is also important for understanding appropriate precipitation periods to be targeted in modeling for future drought risk assessments under climate change.

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Acknowledgements

The authors express their gratitude to the Union Nasunogahara Land Improvement District for their cooperation during their research.

Funding

This work was supported by the Environment Research and Technology Development Fund (JPMEERF20S11814) of the Environmental Restoration and Conservation Agency, Japan, and the Grants-in-Aid for Scientific Research (KAKENHI) (JP22K05894) of Japan Society for the Promotion of Science.

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Authors and Affiliations

  1. Institute for Rural Engineering, National Agriculture and Food Research Organization, Tsukuba, Japan

    Takeo Tsuchihara, Shuhei Yoshimoto, Katsushi Shirahata, Hiroomi Nakazato & Satoshi Ishida

  2. Secretariat of the Japanese Society of Irrigation, Drainage and Rural Engineering, Tokyo, Japan

    Satoshi Ishida

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  1. Takeo Tsuchihara
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  2. Shuhei Yoshimoto
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  3. Katsushi Shirahata
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Contributions

Design of study framework: T.T.; construction and discussion of analysis method: T.T., S.Y., and S.I.; modeling and analysis: T.T.; writing main manuscript: T.T.; reviewing and editing: all authors.

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Correspondence to Takeo Tsuchihara.

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Tsuchihara, T., Yoshimoto, S., Shirahata, K. et al. Analysis of groundwater-level fluctuation and linear regression modeling for prediction of initial groundwater level during irrigation of rice paddies in the Nasunogahara alluvial fan, central Japan. Environ Earth Sci 82, 473 (2023). https://doi.org/10.1007/s12665-023-11174-w

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