Han et al. (2025) Assessing the effects of controlled drainage on regional hydrological cycle and crop waterlogging and drought based on a coupled agro-hydrological model

Identification

• Journal: Agricultural Water Management
• Year: 2025
• Date: 2025-10-11
• Authors: Xudong Han, Xiugui Wang, Wenquan Gu, Yingzhi Qian, Youzhen Wang, Tao Shen, Rong Tang
• DOI: 10.1016/j.agwat.2025.109881

Research Groups

• State Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan, Hubei 430072, China
• Key Laboratory of Water Conservancy and Water Resources of Anhui Province, Anhui & Huaihe River Institute of Hydraulic Research, Bengbu, Anhui 233000, China
• College of Water Resources and Civil Engineering, Hunan Agricultural University, Changsha, Hunan 410128, China

Short Summary

This study developed a coupled agro-hydrological model to assess the regional impacts of controlled drainage (CD) on hydrological cycles and crop water stress in the Huaihe River Basin, China. The research quantified how CD regulates groundwater-soil water interactions and crop yields across different precipitation regimes, proposing precipitation-specific management schemes to mitigate waterlogging and drought.

Objective

• To develop a coupled agro-hydrological model integrating surface water, groundwater, and crop growth processes to evaluate the effects of controlled drainage (CD) on hydrological processes and crop performance.
• To identify dominant water stress factors and their spatiotemporal dynamics under CD.
• To quantify how CD regulates groundwater–soil water interactions and crop yields across different precipitation regimes.
• To propose precipitation-specific CD schemes for optimizing both water management and crop production.

Study Configuration

• Spatial Scale: Lixin Controlled Drainage Experiment Area (LCDA) in the central-northern Huaihe River Basin, China, covering 115.3 square kilometers. The area was horizontally discretized into 272 × 94 cells, each 100 meters × 100 meters, and vertically into two aquifer layers with thicknesses of 6 meters and 44 meters.
• Temporal Scale: Simulation period from June 1, 2006, to May 31, 2021 (15 years). Calibration period from June 1, 2019, to May 31, 2020. Validation period from June 1, 2020, to May 31, 2021.

Methodology and Data

• Models used:
  • DWSEM (Drought and waterlogging simulation and evaluation Model) - a coupled agro-hydrological model.
  • Modified EPIC model - for plant growth simulation.
  • MODFLOW - for three-dimensional groundwater flow.
  • SCS runoff curve method - for runoff calculation.
  • One-dimensional Saint-Venant equations - for main ditch flow routing.
  • Feddes model - for crop water stress determination.
  • Extended Fourier Amplitude Sensitivity Test (eFAST) method - for global sensitivity and uncertainty analysis.
  • Limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS-B) algorithm - for model calibration.
• Data sources:
  • Ditch water levels (DWL): Monitored by 6 HOBO U20L water level loggers.
  • Groundwater levels: Monitored by 51 Hobo loggers.
  • Crop yields (wheat and maize): Field observations (2019–2021) and Lixin Almanac statistics (2017–2021).
  • Hydrogeological conditions: Investigated by drilling 18 boreholes, providing soil parameters (saturated hydraulic conductivity, Van Genuchten parameters).
  • Meteorological data: Daily data from the China Meteorological Data Service Centre.
  • Digital Elevation Model (DEM): Sourced from NASA.
  • Land-use map: Derived from GF-1 satellite data (1 meter resolution).
  • Crop phenology: Field observations.

Main Results

• Parameter Sensitivity: Groundwater levels and ditch water levels are most sensitive to topsoil hydraulic parameters (soil porosity (n), van Genuchten parameter (α), saturated water content (θs), and saturated hydraulic conductivity (Ks) in the 0–0.2 meter layer), and n across 0–0.8 meter depth. Crop yields are primarily governed by physiological parameters (biomass-energy conversion factor (BE), potential heat units (PHU), maximum leaf area index (LAImax), base temperature (Tbase), and fraction of growing season when leaf area starts declining (DLAI)).
• Model Performance: The coupled model showed strong agreement with observations, with R² values exceeding 0.799 for ditch water levels, 0.831 for groundwater levels, 0.69 for maize yield, and 0.52 for wheat yield. Normalized Root Mean Squared Error (NRMSE) values were below 0.4% for ditch water levels, 1.2% for groundwater levels, 11.6% for maize yield, and 10.5% for wheat yield.
• Crop Water Stress: Precipitation dictates the dominant water stress. Waterlogging is the primary stress for maize, particularly during the jointing-tasseling stage. Drought mainly affects wheat, especially during the heading-milk maturity stage.
• Controlled Drainage (CD) Impacts: CD significantly influences groundwater table depth (GWT) and groundwater-to-soil recharge (GtoS), thereby altering crop water stress and yields.
  • Strong negative linear relationships were observed between net GtoS and GWT (|R|>0.9), and between crop yields and GWT (|R|>0.84).
  • For each 1 meter increase in GWT, average net GtoS decreases by 31 millimeters for maize and 25 millimeters for wheat.
  • An average maize yield increase of 425 kilograms per hectare was observed for each 1 meter increase in GWT, while wheat yield decreased by 174.1 kilograms per hectare for each 1 meter increase in GWT.
  • CD effects are amplified when precipitation deviates from critical thresholds, marking transitions between drought- and waterlogging-dominated regimes.
• Optimal CD Schemes: Precipitation thresholds for the transition from drought to waterlogging stress were established at 312–401 millimeters for maize and 354–434 millimeters for wheat, decreasing as ditch water level increases. Dynamically adjusted precipitation-specific CD schemes can increase maize yield by 57 kilograms per hectare and wheat yield by 212 kilograms per hectare compared to current constant schemes.

Contributions

• Developed a novel, flexible coupled agro-hydrological model (DWSEM integrated with modified EPIC and MODFLOW) that simultaneously simulates ditch convergence under controlled drainage, maintains water balance across modules, and accurately captures crop water stress and yield responses at a regional scale.
• Provided a robust, process-based framework for quantifying the influence of water management schemes on regional hydrology and crop waterlogging/drought, which is transferable to other crops, regions, and management practices.
• Identified critical crop growth stages and spatial hotspots prone to waterlogging and drought stresses for major crops in the study area.
• Mechanistically analyzed how controlled drainage regulates groundwater-soil water interactions and crop yield responses, establishing quantitative relationships between GWT, GtoS, and crop yields.
• Proposed precipitation-specific controlled drainage schemes, derived from systematic model applications, to optimize water management and crop production, offering valuable guidance for precision water regulation.
• Improved crop growth simulation by modifying the EPIC model's water stress factor with the Feddes model, leading to reduced RMSE for maize and wheat yields.

Funding

• Natural Science Foundation of China (Grants 52309059 and 51709204)
• Fundamental Research Funds for the Central Universities (2042025kf0065 and 20251404027)

Citation

@article{Han2025Assessing,
  author = {Han, Xudong and Zhu, Yan and Wang, Xiugui and Gu, Wenquan and Qian, Yingzhi and Wang, Youzhen and Shen, Tao and Tang, Rong},
  title = {Assessing the effects of controlled drainage on regional hydrological cycle and crop waterlogging and drought based on a coupled agro-hydrological model},
  journal = {Agricultural Water Management},
  year = {2025},
  doi = {10.1016/j.agwat.2025.109881},
  url = {https://doi.org/10.1016/j.agwat.2025.109881}
}