Hughes-Lomelin et al. (2026) Integrated modeling of surface water and groundwater systems: a multivariate stochastic perspective

Identification

• Journal: Frontiers in Water
• Year: 2026
• Date: 2026-09-24
• Authors: Roxana Nicte-Há Hughes-Lomelin, Joel Hernandez-Bedolla, Claudia Lizeth Garcia-Perez, Mario Alberto Hernández-Hernández, Sonia Tatiana Sánchez-Quispe
• DOI: 10.3389/frwa.2026.1915442

Research Groups

• Hydraulics Department, Universidad Michoacana de San Nicolás de Hidalgo, Morelia, Mexico
• Institute of Geophysics, Universidad Nacional Autónoma de México, Mexico City, Mexico
• Technical University of Valencia

Short Summary

This study presents an integrated modeling framework that combines stochastic rainfall generation, monthly evapotranspiration estimation (MASHWIN), and the coupling of the rainfall–runoff model HBV with the groundwater-flow model MODFLOW. The proposed approach generates 100 alternative meteorological realizations and propagates their effects sequentially from climate forcing to runoff and recharge and, finally, to groundwater-level responses.

Objective

• Investigate how stochastic variability in precipitation and evapotranspiration influences recharge estimates derived from a rainfall–runoff model.
• Evaluate the extent to which variability in recharge affects groundwater level responses.
• Assess whether stochastic climate series can serve as a reliable substitute for observed data in groundwater modeling applications, especially under data-scarce conditions.

Study Configuration

• Spatial Scale: Aguascalientes Valley aquifer (3,129 km²)
• Temporal Scale: 29-year simulation period from 1985 to 2014

Methodology and Data

• Models used:
  • MASHWIN (multisite multivariate stochastic model) for generating synthetic precipitation and evapotranspiration series.
  • HBV (rainfall–runoff model) for estimating infiltration-derived recharge.
  • MODFLOW (groundwater-flow model) for simulating groundwater heads and uncertainty under multiple stochastic climate scenarios.
• Data sources:
  • Meteorological data from Mexican National Meteorological Service (SMN).
  • Hydrometric data from National Water Commission (CONAGUA).
  • Hydrogeological variables from regional studies.

Main Results

• The multisite multivariate stochastic model generated 100 synthetic series, each with a length matching the historical series (29 years).
• Precipitation and evapotranspiration series were parameterized monthly using logarithmic normalization and included a 5-year warming period.
• The generated series are presented in Figures 4 and 5, showing that precipitation in the study area reflected the highest values in the generated series but was adjusted to align with the average historical period.

Contributions

• This study addresses the gap in explicit propagation of multivariate climate variability through rainfall runoff and distributed groundwater flow models.
• The proposed methodology generates 100 alternative meteorological realizations and propagates their effects sequentially from climate forcing to runoff and recharge and, finally, to groundwater-level responses.
• This structure provides a quantitative assessment of how climatic variability propagates through the hydrological system and contributes to groundwater uncertainty in data-constrained semi-arid aquifers.

Funding

• This research was funded by [insert funding projects, programs, and reference codes].

Citation

@article{HughesLomelin2026Integrated,
  author = {Hughes-Lomelin, Roxana Nicte-Há and Hernandez-Bedolla, Joel and Garcia-Perez, Claudia Lizeth and Hernández-Hernández, Mario Alberto and Sánchez-Quispe, Sonia Tatiana},
  title = {Integrated modeling of surface water and groundwater systems: a multivariate stochastic perspective},
  journal = {Frontiers in Water},
  year = {2026},
  doi = {10.3389/frwa.2026.1915442},
  url = {https://doi.org/10.3389/frwa.2026.1915442}
}