Incorporating water quality responses into the framework of best management practices optimization

Lei, Chen; Wei, Guoyuan; Shen, Zhenyao

doi:10.1016/j.jhydrol.2016.08.038

Cited by 26 publications

(8 citation statements)

References 39 publications

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“…The SCS-CN model (Woodward et al, 2002) was selected on the basis of its simplicity and success in simulating hydrological processes (Mishra & Singh, 2003;Mishra & Singh, 2012;Zhang & Pan, 2014;Chen et al, 2016). Although Caviedes-Voullième et al (2012) found that the SCS-CN methods might be unsuitable for shallow-water based hydrological simulation.…”

Section: Surface Runoff Derived From a Hydrological Modelmentioning

confidence: 99%

Integrated remote sensing imagery and two-dimensional hydraulic modeling approach for impact evaluation of flood on crop yields

Chen

Liang

Liu

et al. 2017

Journal of Hydrology

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Section: Surface Runoff Derived From a Hydrological Modelmentioning

confidence: 99%

Integrated remote sensing imagery and two-dimensional hydraulic modeling approach for impact evaluation of flood on crop yields

Chen

Liang

Liu

et al. 2017

Journal of Hydrology

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“…More importantly, it dramatically impacts the water bodies that directly or indirectly receive those pollutants (Wu et al, 2023). These areas are common priority areas for implementing BMPs to control eco-environmental problems, including nonpoint source pollution and soil erosion (Chen et al, 2016;White et al, 2009;Rana & Suryanarayana, 2020). Therefore, after PMAs are identified and prioritized, the implementation order of suitable BMPs in the PMAs can be designed accordingly (Jang et al, 2013;Shen et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

“…The second type of optimization method is an intelligent optimization algorithm-based method that simplifies, formulates, and solves the complex optimization problem of selecting and locating BMPs by incorporating watershed modeling (Chen et al, 2016;Srivastava et al, 2002;Veith et al, 2003;Zhu et al, 2021). The optimization problem formulation comprises objectives, geographic decision variables, and constraining conditions Zhu et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Optimizing the Implementation Plan of Watershed Best Management Practices with Time-varying Effectiveness under Stepwise Investment

Shen

Qin

Zhu

et al. 2023

Preprint

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Optimizing the spatial configuration of diverse best management practices (BMPs) can provide valuable decision-making support for comprehensive watershed management. Most existing methods focus on selecting BMP types and locations but neglect their implementation time or order in management scenarios, which are often investment-restricted. This study proposes a new simulation-optimization framework for determining the implementation plan of BMPs by using the net present value to calculate the economic costs of BMP scenarios and the time-varying effectiveness of BMPs to evaluate the environmental effectiveness of BMP scenarios. The proposed framework was implemented based on a Spatially Explicit Integrated Modeling System and demonstrated in an agricultural watershed case study. This case study optimized the implementation time of four erosion control BMPs in a specific spatial configuration scenario under a 5-year stepwise investment process. The proposed method could effectively provide more feasible BMP scenarios with a lower overall investment burden with only a slight loss of environmental effectiveness. Time-varying BMP effectiveness data should be gathered and incorporated into watershed modeling and scenario optimization to better depict the environmental improvement effects of BMPs over time. The proposed framework was sufficiently flexible to be applied to other technical implementations and extensible to more actual application cases with sufficient BMP data. Overall, this study demonstrated the basic idea of extending the spatial optimization of BMPs to a spatiotemporal level by considering stepwise investment, emphasizing the value of integrating physical geographic processes and anthropogenic influences.

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“…The Soil and Water Assessment Tool (SWAT), a semi-distributed hydrologic model, is mainly used to simulate the impact of agricultural management on water quantity and quality in a watershed [19]. SWAT has been applied for hydrologic assessment [20,21,22,23], the evaluation of impacts of climate and land use change on streamflow [24,25] and water quality [26], modeling of ecosystem services [27,28], and best management practices (BMP) assessment [29,30]. In previous studies, surface runoff was found to be affected by landscape configuration and structure [31].…”

Section: Introductionmentioning

confidence: 99%

Integrating Landscape Metrics and Hydrologic Modeling to Assess the Impact of Natural Disturbances on Ecohydrological Processes in the Chenyulan Watershed, Taiwan

Chiang

Chuang

Han

2019

IJERPH

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The Chenyulan watershed, located in the central mountain area of Taiwan, has been suffering from earthquakes, typhoons, and heavy rainfalls in recent decades. These sequential natural disturbances have a cumulative impact on the watershed, leading to more fragile and fragmented land cover and loss of capacity of soil water conservation. In this study, the Soil and Water Assessment Tool (SWAT) and a landscape metrics tool (FRAGSTATS) were used to assess the direct impact (e.g., by annual rainfall) and indirect impact (e.g., by landscape configuration and composition) of natural disturbances on the ecohydrological processes of the Chenyulan watershed. Six SPOT satellite images from 2008 to 2013 were analyzed by using the nearest feature line embedding (NFLE) approach and reclassified into six land cover types: forest, cultivated land, grassland, river, landslide, and built-up. Forest was found to have the largest patch size, indicating that it is more resilient to disturbances, while agricultural land tended to expand from the river side toward the hill. Two land cover change scenarios were compared in the SWAT model. The results showed that there was no significant difference in simulated streamflow during 2004–2015 and sediment loading during 2004–2009; however, the model performed better for sediment loading during 2010–2015 with dynamic land cover change (coefficient of determination (R2) = 0.66, Nash-Sutcliffe efficiency coefficient (NSE) = 0.62, percent bias (PBIAS) = 10.5%, root mean square error observation standard deviation ratio (RSR) = 0.62) than with constant land cover (R2 = 0.61, NSE = 0.54, PBIAS = −17.3%, RSR = 0.68), indicating that long-term land cover change should be considered in hydrologic modeling. Changes in landslides during 2008–2013 were found to significantly affect ecohydrological processes, especially after 2011. In general, annual precipitation plays a dominant role, and landscape composition had by far the strongest influence on water yield and sediment yield compared to landscape configuration. The results can be useful for understanding the effects of land cover change on ecohydrological processes in the Chenyulan watershed and the potential impact of ecohydrological changes on the environment and public health.

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Incorporating water quality responses into the framework of best management practices optimization

Cited by 26 publications

References 39 publications

Integrated remote sensing imagery and two-dimensional hydraulic modeling approach for impact evaluation of flood on crop yields

Integrated remote sensing imagery and two-dimensional hydraulic modeling approach for impact evaluation of flood on crop yields

Optimizing the Implementation Plan of Watershed Best Management Practices with Time-varying Effectiveness under Stepwise Investment

Integrating Landscape Metrics and Hydrologic Modeling to Assess the Impact of Natural Disturbances on Ecohydrological Processes in the Chenyulan Watershed, Taiwan

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