Evidence map›Paper›PMID 42894881›Full record

ArticleiScience2026

Aquifer-differentiated process-guided GRU for multi-timescale groundwater-level prediction.

Xiandong Xie, Baizhong Yan, Tian Wang, Chuanlong Han, Cong Wei, Yanliang Zhai, Jialong Lv, Mingrong Zhang

Abstract read
In one paragraph

Article in iScience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Xiandong XieHebei GEO University, Shijiazhuang 050031, China.
Baizhong YanHebei GEO University, Shijiazhuang 050031, China.
Tian WangHebei GEO University, Shijiazhuang 050031, China.
Chuanlong HanHebei GEO University, Shijiazhuang 050031, China.
Cong WeiHebei GEO University, Shijiazhuang 050031, China.
Yanliang ZhaiHebei Key Laboratory of Mountain Geological Environment, Chengde, China.
Jialong LvHebei GEO University, Shijiazhuang 050031, China.
Mingrong ZhangHebei GEO University, Shijiazhuang 050031, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Groundwater-level prediction supports water-resource management in overexploited aquifers, yet conventional data-driven models often struggle to represent pumping disturbances and contrasting shallow- and deep-aquifer responses. Using groundwater levels, meteorological variables, and agricultural pumping data from four shallow and four deep wells in Guantao County, North China Plain, we developed an aquifer-differentiated process-guided gated recurrent unit model for daily and dekadal (10-day) prediction. Compared with a conventional gated recurrent unit model, the process-guided model reduced group-mean root-mean-square error by 7.2% and 6.1% for shallow and deep wells at the daily scale and by 4.0% and 2.1% at the dekadal scale, respectively. Deep-well performance depended on the pumping-response window, with 60-day averaged pumping providing a stable configuration. These incremental gains show that incorporating pumping disturbances and aquifer-specific response differences as process guidance can improve groundwater-level representation and provide a modeling approach for groundwater management in agricultural abstraction areas.

Indexed as

groundwater-level predictionGRUmulti-timescale predictionprocess-guidedsustainable groundwater management

Identifiers

PMID42894881
PMCPMC13677239

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.