Optimizing the configuration of streamflow stations based on coverage maximization: A case study of the Jinsha River Basin

Abstract

Streamflow stations are typical hydrometric stations that serve as the basic components of hydrological monitoring networks. To effectively obtain information for predicting the magnitude and frequency of future floods and droughts, an optimal configuration of streamflow stations should be established to maximize the sensing capability with limited resources. In this paper, we propose a method to site streamflow stations in space to maximize the total area for streamflow monitoring. Considering the special regulations for deploying streamflow stations, a modified maximal covering location problem (MCLP) model is introduced. The effective coverage range of a streamflow station is determined based on the minimum density required and the site-specific terrain slope. The candidate sites are assumed to be continuously distributed along a river, and the river network is abstracted as a series of line-based river segments. The covering priority for each segment can be determined by the river length, the drainage area, or the level of flooding risk. The hydrometric network intersection point set (HNIPS) is proposed to identify finite candidate sites along a river. By narrowing the continuous search space to a discrete point set, this siting problem is solved using the MCLP-based model and HNIPS. The Jinsha River Basin is selected as a study area to test the proposed streamflow station siting method. Results show that the proposed method is effective in prescribing the optimal configuration of streamflow stations and the model solution achieves better coverage than that of the real-world deployment. The applicability of the proposed optimal siting method using HNIPS is analyzed. The criteria for candidate site selection and impacts of different weighting schemes applied to river segments are also discussed.