Rivers are an important source of water for the economy. However, in dry periods continuous abstraction could function as a catalyst for low-flow events and, hence, run counter to hydrological-ecological requirements and lead to imbalances in competing use demands. In the absence of hydro-economic incentive systems, there is no economic motivation for water users to refrain from this procedure. Using a hydro-economic model approach, this article examines the hydrological and economic implications of dynamic water abstraction charges in response to low-flow conditions. The developed approach combines hydrodynamic river modeling with an abstraction cost model. This requires hydrological input data, such as flow rates, but also economic inputs, such as withdrawal quantities and charge rates. The cost rates are linked to discharge conditions, which allows a dynamic simulation of the cost structure at different flow rates. As a result, the simulated abstraction costs per flow range and a failure day risk are obtained. By simulating different scenarios, the study indicates that dynamic pricing mechanisms can provide flow-dependent economic signals relevant for sustainable water resource management under scarcity conditions. The approach was tested using the discharges of the middle Elbe between 1990 and 2022. The simulated application examples showed that dynamic abstraction charges lead to cost differences of up to 14 to 17 percent compared to fixed charges. For an exemplary extractor with an approved extraction rate of 3,500 m 3 /h, additional costs from cost dynamization amount to approximately EUR 200,000 per year in years with consistently low, but not extremely low, discharge volumes. Furthermore, it was found that the specified minimum flow rate was not met on up to 162 days in 2018, a year characterized by extremely low water levels. The findings highlight the potential of adaptive abstraction charges as a policy instrument to reflect hydrological scarcity in economic terms. However, as the model does not explicitly represent behavioral responses, the results should be interpreted as changes in cost signals rather than realized changes in water use. Furthermore, as part of a comprehensive low-flow risk approach, it can help decision-makers to understand hydro-economic interactions and develop strategies for sustainable water management.
Folkens et al. (Wed,) studied this question.