Liang-Jun Zhu (朱良君)

• (We are hiring!) Our research group is looking for postdoc and guest graduate/undergraduate students in the field of geospatial intelligent Analysis and computing. The work involves research and system implementation of intelligent geographic computing services and parallel geographic computing under the framework of cloud-native environment. Interested? Contact us immediatedly!

• (2023-05-26) The follow-up study of the methodology paper in WRR, the design and evaluation study of a web-based participatory watershed planning system, titled From scenario to roadmap: Design and evaluation of a web-based participatory watershed planning system for optimizing multistage implementation plans of management practices under stepwise investment has been acceped by Journal of Environmental Management.

• (2023-05-23) The postdoctoral work of Dr. Shen Shen, whom I co-supervised with Prof. Qin, titled Optimizing the implementation plan of watershed best management practices with time-varying effectiveness under stepwise investment, has been accepted by Water Resources Research. Based on our work on spatial optimization of BMP scenarios[1, 2], considering the critical realistic factor that a BMP scenario cannot be implemented at a time and investments often restrict this, this study proposes a new simulation-optimization framework for the implementation plan of BMPs by using net present value to calculate the economic costs of BMP scenarios, and the time-varying effectiveness of BMPs to evaluate the environmental effectiveness of multistage BMP scenarios. The proposed framework was implemented based on the SEIMS framework and demonstrated in an agricultural watershed case study. The proposed novel idea of extending the spatial optimization of BMPs to the spatio-temporal level by considering the stepwise investment is of great significance to BMP scenario analysis.

• (2023-02-24) The undergraduate thesis work of Tong Wu, whom I co-supervised with Prof. Qin, titled Identification of watershed priority management areas based on landscape positions: An implementation using SWAT+ has been published in the Journal of Hydrology. This work builds upon the fundamental idea we proposed in 2018 of optimizing watershed BMPs based on slope position units. It clarified the concept of priority management areas (PMA) in a watershed and proposed that landscape position units are more suitable to be used as PMA identification units than subbasin units. The work summarizes and improves a framework for identifying PMAs using spatial units with upstream and downstream relationships as identification units. The framework is implemented using the SWAT+ model and an improved Markov chain-based surrogate model for pollutant source apportionment.

More news…