Next Article in Journal
Equity Evaluation of Street-Level Greenery Based on Green View Index from Street View Images: A Case Study of Hangzhou, China
Previous Article in Journal
Spatial Drivers of Urban Industrial Agglomeration Using Street View Imagery and Remote Sensing: A Case Study of Shanghai
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

Blue–Green Infrastructure Network Planning in Urban Small Watersheds Based on Water Balance

Department of Landscape Architecture, School of Architecture, Southeast University, Nanjing 210000, China
*
Author to whom correspondence should be addressed.
Land 2025, 14(8), 1652; https://doi.org/10.3390/land14081652
Submission received: 24 June 2025 / Revised: 29 July 2025 / Accepted: 7 August 2025 / Published: 15 August 2025
(This article belongs to the Section Urban Contexts and Urban-Rural Interactions)

Abstract

The rapid expansion of urbanization and inadequate planning have triggered a water balance crisis in many cities, manifesting as both the need for artificial lake supplementation and frequent urban flooding. Using the Xuanwu Lake watershed in Nanjing as a case study, this research aims to optimize the Blue–Green Infrastructure (BGI) network to maximize rainfall utilization within the watershed. The ultimate goal is to restore natural water balance processes and reduce reliance on artificial supplementation while mitigating urban flood risks. First, the Soil Conservation Service Curve Number (SCS–CN) model is employed to estimate the maximum potential of natural convergent flow within the watershed. Second, drawing on landscape connectivity theory, a multi-level BGI network optimization model is developed by integrating the Minimum Cumulative Resistance (MCR) model and the gravity model, incorporating both hydrological connectivity and flood safety considerations. Third, a water balance model based on the Storm Water Management Model (SWMM) framework and empirical formulas is constructed and coupled with the network optimization model to simulate and evaluate water budget performance under optimized scenarios. The results indicate that the optimized scheme can reduce artificial supplementation to Xuanwu Lake by 62.2% in June, while also ensuring effective supplementation throughout the year. Annual runoff entering the lake reaches 13.25 million cubic meters, meeting approximately 13% of the current annual supplementation demand. Moreover, under a 100-year return period flood scenario, the optimized network reduces total watershed flood volume by 35% compared to pre-optimization conditions, with flood-prone units experiencing reductions exceeding 50%. These findings underscore the optimized BGI network scheme’s capacity to reallocate rainwater resources efficiently, promoting a transition in urban water governance from an “engineering-dominated” approach to an “ecology-oriented and self-regulating” paradigm.
Keywords: water balance; urban small watershed; blue–green infrastructure; network optimization water balance; urban small watershed; blue–green infrastructure; network optimization

Share and Cite

MDPI and ACS Style

Chen, X.; Wang, X. Blue–Green Infrastructure Network Planning in Urban Small Watersheds Based on Water Balance. Land 2025, 14, 1652. https://doi.org/10.3390/land14081652

AMA Style

Chen X, Wang X. Blue–Green Infrastructure Network Planning in Urban Small Watersheds Based on Water Balance. Land. 2025; 14(8):1652. https://doi.org/10.3390/land14081652

Chicago/Turabian Style

Chen, Xin, and Xiaojun Wang. 2025. "Blue–Green Infrastructure Network Planning in Urban Small Watersheds Based on Water Balance" Land 14, no. 8: 1652. https://doi.org/10.3390/land14081652

APA Style

Chen, X., & Wang, X. (2025). Blue–Green Infrastructure Network Planning in Urban Small Watersheds Based on Water Balance. Land, 14(8), 1652. https://doi.org/10.3390/land14081652

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop