Salam A. Abbas

Effective and balanced management of economic and environmental concerns in groundwater-irrigated basins is a world-wide challenge. Environmental flow modification is increasingly influenced by groundwater-supported irrigation in these heavily irrigated regions, yet the ability to rigorously quantify how groundwater-based irrigation influences ecological surface-water flows remains limited, leaving resource managers with difficult and opaque decisions regarding resource allocation. This work presents a generic and generalised framework to programmatically evaluate how groundwater use for irrigation has altered surface-water flow characteristics by using an integrated surface-subsurface modelling system paired with rigorous ensemble-based data assimilation. As an example, we demonstrate the mechanisms linking groundwater dynamics to environmental flow alteration in groundwater-dependent river systems, utilising the Mississippi Alluvial Plain (MAP), USA, as a representative study. Specifically, a coupled SWAT+gwflow model was applied across six HUC-8 watersheds and calibrated using an iterative ensemble smoother, incorporating both monthly streamflow and groundwater head observations. Model performance was evaluated using multiple hydrologic metrics and independent datasets, including streamflow, groundwater levels and basin-scale evapotranspiration. Environmental flow alteration was quantified using the IAHRIS framework under managed and naturalised conditions. Results reveal that while annual discharge volumes remain near stable, substantial degradation occurs in low-flow magnitude, duration and seasonal structure. Groundwater abstraction-induced baseflow reduction emerged as the primary driver of low-flow collapse, particularly during the irrigation season. The proposed framework provides a transferable, process-oriented methodology for diagnosing groundwater-driven environmental flow alteration in intensively irrigated basins and offers a robust basis for evaluating sustainable groundwater–surface water management strategies under increasing water demand.

Coupled surface-subsurface hydrologic models are used worldwide to study historical patterns of water storage and hydrologic behaviour, investigate the impact of management strategies on water resources, and quantify the impact of changing climate, population, and policies. This study presents a new hydrologic model to simulate surface and subsurface in a physically based spatially distributed manner by linking the popular SWAT+ and MODFLOW modelling codes. Within this new code, SWAT+ simulates processes in the landscape, soils, channels, and reservoirs, whereas MODFLOW simulation groundwater processes and interaction with land surface features (soil, channels, canals, reservoirs, tile drains). Geographic connections between SWAT+ objects and MODFLOW grid cells are established a priori using a GIS and then read into the code to be used throughout the simulation to map hydrologic fluxes (recharge, soil water transfer, groundwater-channel exchange, canal seepage, tile drainage outflow, groundwater-reservoir exchange, pumping for irrigation) on a daily time step. The use and general accuracy of the model is demonstrated for two study regions that are subject to irrigation management: the Arkansas River Basin in Colorado and the San Joaquin River Basin in California. An accompanying tutorial and example model data allow for easy use of the model to other study regions. As both SWAT+ and MODFLOW are widely used worldwide for watershed and groundwater modelling, we expect that this new tool can be an important asset in many water resources projects.

In hydrologic modeling, the value of the model parameters is often influenced by the rainfall patterns of the calibration period. However, modeling studies typically only use a single calibration period, with parameters constrained by the associated hydrologic conditions. In this paper, we explore the use of multiple, hydrologically disparate calibration periods and investigate their influence on parameter selection. Specifically, we present a dual calibration approach designed to predict different aspects of the hydrograph: one model scenario is calibrated to replicate wet period conditions to support peak flow conditions, while the other experiment is calibrated to dry periods to support evaluating ecological flows. We use a surface–subsurface hydrologic model (SWAT+, enhanced with new groundwater module gwflow) applied to the semiarid, snowmelt-dominant, intensively irrigated Cache la Poudre River Basin (4,824 km2) in Colorado for the 2000–2015 period. The model is tested against monthly streamflow. We conduct a global sensitivity analysis to explore the seasonal sensitivity of streamflow, high flow, and low flow during wet and dry seasons and to evaluate the watershed-average hydrologic fluxes for the wet- and dry-calibration experiments, highlighting the key differences between the two calibration experiments. Sensitivity analysis shows seasonal shifts in the relation between parameters and simulated streamflow: during wet periods, runoff lag time and aquifer specific yield control, while dry periods highlight hydraulic conductivity and percolation. The model effectively simulates high flows during wet periods but has difficulties in dry conditions, underscoring the complexities of successfully designing and deploying a single mode and calibration strategy across varying hydrologic regimes. Low-flow simulations during dry calibration exhibit reduced precision; however, wet testing enhances performance, illustrating the model’s ability to accurately represent low flows in wetter settings. This research highlights the intricacies of simulating the full range of flow dynamics in complex watersheds.