Spatial optimization of watershed best management practice scenarios based on boundary-adaptive configuration units

Liang-Jun Zhu, Cheng-Zhi Qin*, and A-Xing Zhu



Spatial optimization of watershed best management practice (BMP) scenarios based on watershed modeling is an effective decision support tool for watershed management. Existing spatial optimization methods of BMP scenarios commonly utilized boundary-fixed spatial units for configuring BMPs which entirely ignores a dimension of solution space constructed by adjusting the boundaries of configuration units. In this paper, we proposed a new approach to the spatial optimization of BMP scenarios based on boundary-adaptive configuration units.

The proposed optimization approach adopts slope positions (e.g., ridge [or summit], backslope, and valley; which are basic landform units along hillslope inherently related to physical hillslope processes) as BMP configuration units and dynamically adjusts their boundaries by using the quantitative information on their spatial gradation (i.e., fuzzy slope positions) during the optimization.

Experimental results showed that the proposed optimization approach based on boundary-adaptive slope position units can significantly enlarge the search space for optimal solutions and obtain optimal BMP scenarios with better cost-effectiveness and higher optimization efficiency.

The proposed optimization approach provides a new framework for spatial optimization of BMP scenarios, in which other watershed models, intelligent optimization algorithms, and BMP configuration units available for boundary adjustment can be alternatively applied to BMP scenario optimization in a boundary-adaptive manner.

This study also exemplifies the potential of transforming the qualitative, vague, and empirical geographical knowledge (that on slope position units related to physical hillslope processes and BMPs) to the quantitative, explicit, automated geospatial algorithms for effectively resolving environmental management problems in a more geographical meaningful way.

Software availablility


  • New optimization framework of watershed best management practice scenarios in a unit-boundary adaptive manner, 10th iEMSs Conference (Online), Sep. 14–18, 2020. Brussels. Download PPT (alternative download link).

Review history

  • Submission: 2020-2-1

  • Awaiting Editor Assignment: 2020-2-1, ADM: Brian, Jayne (Associate Editor)

  • Awaiting Reviewer Selection: 2020-2-10, ADM: Malanson, George (Managing Editor)

  • Awaiting Reviewer Assignment: 2020-2-15, then changed to awaiting reviewer selection again, and then awaiting reviewer assignment (2020-3-5)

  • Awaiting Reviewer Scores: 2020-3-11

  • Awaiting Final Decision: 2020-4-13

  • Minor revision: 2020-4-15

    • Reviewer #1: I like this contribution, and congratulate the authors for a thoughtful, insightful and substantive piece of work. I must confess, up-front, that this paper is not in my direct area of expertise, so I am unable to address any issues for technical aspects of this paper, but the rationale for the work is clear, and the specific contribution of the study is well validated. The paper is clear and well written. The structure works well, with clear articulation of extensions to previous methodological approaches (i.e. building upon Qin et al., 2018). I applaud the effective documentation of the case study – it works well, amply justifying the approach and substantiating the contribution of the paper. Ultimately, I completely agree with the premise of this paper – we need more flexible approaches to boundary identification and mapping to inform management applications (including use of optimization procedures). I have just one suggestion. In order to promote uptake of this work, capturing a wider readership and potential citations, I wonder if the generic nature of the approach could be expressed explicitly. This could simply take the form of an additional sentence or two early in the introduction, broadening the scope for the issues addressed in this study. Associated with this point, I have a minor gripe at the end of the discussion, as I expected to see more substantive contextualization of findings of this work, relating the contribution more effectively to the international literature (and associated implications). If this issue was addressed, and a sentence to this effect was included within the abstract, I sense that there may be wider uptake of this paper. I always appreciate it when I can glean the core contribution from papers that are outside my core area of expertise.

    • Reviewer #2: The manuscript is very interesting. I think it is in the scope of Progress in Physical Geography. My comments: (1) “Boundary-adaptive configuration units” is actually according to slope positions in this paper, and BMP configuration units and dynamically adjusts their boundaries by using the quantitative information on their spatial gradation. Is it right the boundary-adaptive configuration units were for slope positions, not for BMPs? (2) BMPs are management plans directly implemented by farmers or the government. It doesn't mean very much by fluctuating management practices in reality. The authors need to justify that the given work is practically useful in the real world. (3) The methods may be suitable for BMPs practices of soil erosion control. Could it be used to TN and TP control? Do explain.

  • Submit the revision and Awaiting Admin Processing and then Awaiting Reviewer Selection (ADM: Brian, Jayne): 2020-5-12

  • Accepted: 2020-6-3 (after status update requirement at 2020-6-2)

    • Awaiting Copy Editor Checklist: 2020-6-3

    • Beginning copyediting by journal production: 2020-6-16

    • Page proofs: 2020-7-10

    • Revised proof for review: 2020-7-24

    • Published online: 2020-7-28

    • Published in Volume 45 Issue 2: 2021-4-8


Zhu, L.J., Qin, C.Z., and Zhu, A.X., 2021. Spatial optimization of watershed best management practice scenarios based on boundary-adaptive configuration units, Progress in Physical Geography: Earth and Environment, 45(2):207–227. doi:10.1177/0309133320939002

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