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Coupled hydro-economic models are increasingly used to analyse how land-use decisions, water availability, and policy interventions interact in agricultural catchments. However, most existing couplings remain ad hoc and weakly reproducible, largely because hydrological and microeconomic models operate on fundamentally different spatial representations. Distributed and semi-distributed hydrological models require spatially explicit land-use representations (e.g. HRUs, grids, or sub-basins), whereas microeconomic models typically allocate land and water over aggregated administrative units or representative agents. As a result, land-use change is often imposed through static scenario maps or one-way translations, preventing fully operational two-way feedback between hydrology and economic decision-making.We introduce the hydro-economic land-use interoperability method (HILAM), a spatial template designed to enable consistent, bidirectional coupling between distributed or semi-distributed hydrological models and microeconomic land-allocation models. HILAM is not tied to any specific economic or hydrological model: any land-use allocation model and any spatially explicit hydrological model can be plugged into the framework. HILAM uses a semi-distributed spatial layer that links detailed land-use, soil, and climate data into common spatial units. These units allow crop shares from the economic model to be passed to the hydrological model and hydrological outputs to be returned to the same locations, enabling spatially explicit two-way feedback.As an illustration of the economic component, we use a positive mathematical programming (PMP) model, representing one member of a broader class of mathematical programming approaches (e.g. linear programming, multi-attribute models, PMP) that can be coupled through HILAM. PMP provides a microeconomic characterisation of farmers’ production choices under binding resource constraints, reproducing observed land-use allocations as the outcome of constrained optimisation while allowing consistent responses to changes in prices, yields, and water availability for irrigation.As an illustration of the hydrological component, we use the Soil and Water Assessment Tool (SWAT) as one example of a semi-distributed, process-based hydrological model that can be coupled through HILAM. SWAT translates land-use configurations into water flows, soil moisture dynamics, irrigation requirements, and crop water stress, ensuring that economic decisions are grounded in physically meaningful hydrological constraints. Through HILAM, these outputs are returned to the economic model at consistent spatial units, closing the hydro-economic feedback loop. A key innovation of HILAM is that the spatial template explicitly controls the level of spatial detail, allowing modellers to regulate complexity, uncertainty, and computational cost in a transparent and reproducible manner, providing an intermediate alternative between fully gridded simulations and highly aggregated representations.We demonstrate HILAM through a case study that couples SWAT with a PMP land-use model in an intensively irrigated aquifer system in central Spain. The coupled framework enables continuous feedback between crop choice, irrigation water availability, crop yields, and hydrological responses over multi-year simulations. Results show that spatially explicit hydro-economic coupling produces substantially different projections of water use, crop distribution, and aquifer stress than conventional aggregated approaches, highlighting the importance of spatial interoperability for water governance and climate-adaptation analysis.