This study focuses on the design, implementation and performance evaluation of a new irrigation and open-channel module into the well-known Topkapi distributed model. The Topkapi was implemented through the PyTopkapi library. The research framework encompasses the integration of an irrigation simulation module alongside a sophisticated kinematic wave model, designed to emulate the intricate dynamics of surface flow transport in irrigation channels, thereby enriching the structural composition of the overall model. The performance of the improved model was tested in the Achibueno River basin (Chile) strategically positioned in the southern reaches of the Maule region, encompassing a substantial land expanse of 1578 km 2 with a very important agricultural activity and a subsequent important presence of open-channels for its water distribution network. The dataset utilized for this comprehensive assessment spans a temporal continuum from 1979 to 2005 and has been meticulously curated from the historical archives of the CR2 institution. The evaluation of model performance is executed through the application of the Nash and Nash-ln coefficients, enabling a nuanced understanding of the model’s proficiency. Two distinct scenarios are meticulously considered throughout the assessment: one wherein the irrigation module is absent from the model configuration, and another wherein the irrigation module is integrated into the model’s structural framework. The findings emanating from our results underscore a discernible augmentation in the operational efficiency of PyTopkapi to the extent of approximately 17% when the irrigation module is applied (NSE moving from 0.63 to 0.74 for the calibration period and 0.54 to 0.64 for the validation period). This heightened efficiency manifests notably during the transport of flow through channels, where the kinematic wave model plays a pivotal role in orchestrating the dynamics of surface water movement.

We inter-compare four hydrological models in terms of their surface water response simulations and their ability to capture the particular features of humid Mediterranean climates. We selected the Maule River basin (central Chile), in particular the Longaví basin as the paradigm of humid Mediterranean climate to run the study. The area is under intensive irrigated agricultural exploitation, which jeopardizes groundwater recharge and may be further pressurized by precipitation changes due to global warming. The Longaví basin in the south of the Maule, was studied and its hydrological cycle was simulated using four simulation tools: GR4J, HBV-light, HEC-HMS and WEAP, hence including lumped as well as a semi-distributed approaches. For model performance assessment, the Longaví was sub-divided into three zones with comparable characteristics in terms of climate, physical soil properties and altitude classes. Daily hydro-meteorological forcing time series were provided by official institutions of Chile for the 1979 to 2015 period. The individual model efficiency was evaluated through usual deterministic performance indicators. The models exhibit different strengths in terms of hydrologic response simulations. The results obtained with GR4J, HEC-HMS and WEAP perform better during southern hemisphere Winter between June and October, while HBV-light produces stronger results during the November to May Summer season. The more heavily parameterized WEAP model tends to better represent the stream flow variability observed during the rainy season with respect to the dry season.

We inter-compare four hydrological models in terms of their surface water response simulations and their ability to capture the particular features of humid Mediterranean climates. We selected the Maule River basin (central Chile), in particular the Longaví basin as the paradigm of humid Mediterranean climate to run the study. The area is under intensive irrigated agricultural exploitation, which jeopardizes groundwater recharge and may be further pressurized by precipitation changes due to global warming. The Longaví in the south of the Maule, was studied using four simulation tools: HBV-light, GR4J, HEC-HMS and WEAP, hence including conceptual as well as a semi-distributed approaches. For model performance assessment, the Longaví was sub-divided into three zones with comparable characteristics in terms of climate, physical soil properties and altitude classes. Daily hydro-meteorological forcing time series were provided by official institutions of Chile for the 1979 to 2015 period. The individual model efficiency was evaluated through usual deterministic performance indicators. The models exhibit different strengths in terms of hydrologic response simulations. The results obtained with GR4J, HEC-HMS and WEAP perform better during southern hemisphere Winter between June and October, while HBV-light produces stronger results during the November to May Summer season. The more heavily parameterized WEAP model tends to better represent the stream flow variability observed during the rainy season with respect to the dry season. The actual irrigation water demand for the selected study region is matter of further research and will be acknowledged in a sequel paper.