Significance of using dynamic land-use data and its threshold in hydrology and water quality simulation models

Liu, Ruimin; Jiao, Lijun; Li, Lin; Wang, Yifan; Cao, Leiping

doi:10.1007/s10661-022-09761-8

Cited by 4 publications

(3 citation statements)

References 49 publications

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“…Different processes need to be balanced and interlinked in complex models in arbitrary ways which have only scarcely been subjected to rigorous tests. For example, numerous models have been set up and run to study the effects of land use on hydrological processes (cf., [ [92] , [93] , [94] ]), while Lischeid et al [ 95 ] found only minor effects of differences between various land use classes on groundwater head dynamics in a 20,000 km 2 region. This clearly contradicts the usual expectations and demonstrates the complexity of real-world ecosystems and the importance of empirical testing and verification, rather than relying solely on models.…”

Section: Shortcomings Of Current Research and Experimental Approachesmentioning

confidence: 99%

Sustainable transformation of agriculture requires landscape experiments

Pereponova,

Grahmann,

Lischeid

et al. 2023

Heliyon

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Section: Shortcomings Of Current Research and Experimental Approachesmentioning

confidence: 99%

Sustainable transformation of agriculture requires landscape experiments

Pereponova,

Grahmann,

Lischeid

et al. 2023

Heliyon

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“…This parameterization method may not fully consider the differences of different terrains, land use types, and soil properties in the basin, resulting in limited accuracy of the simulation results. In addition, the SWAT model simulates hydrological processes at the basin scale, and cannot capture details such as small-scale geomorphological features, land use changes, and local water resource management measures, which may lead to insufficient understanding of sediment production and transport processes, especially in basins with complex landforms and human activities [29,30].…”

Section: Simulation Of Runoff and St In Watershed Based On Swat Modelmentioning

confidence: 99%

Analysis of Spatial and Temporal Characteristics of Runoff Erosion Power in Fujiang River Basin Based on the SWAT Model

Jiang,

Mo,

et al. 2023

Sustainability

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As an erosion dynamic index considering the three elements of flood, runoff erosion power (REP) can better reflect the influence of precipitation, underlying surface, and other factors on the erosion and sediment transport (ST) of flood events. Therefore, it is of great significance to study the variation characteristics of the REP and its relationship with ST in the basin for soil erosion control. In this paper, the Fujiang River Basin (FRB) was selected to analyze the characteristics of runoff and ST at four hydrological stations in the basin from 2009 to 2018, including Santai, Jiangyou, Shehong, and Xiaoheba. Combined with the concept of the REP, six kinds of water–sediment relationship were compared and analyzed. Furthermore, by constructing the SWAT model, the spatial distribution characteristics of runoff, ST, and REP in the FRB were analyzed in depth, and the spatial scale effect of the REP in the basin was explored. The conclusions are as follows: (1) The power function relationship between REP and sediment transport modulus (STM) is better than the other five kinds of water–sediment relationship. (2) Based on the SWAT model, the evaluation indexes of the monthly runoff and ST of the four hydrological stations are credible, good, and excellent in the rating period (RP) and the validation period (VP). (3) The annual REP in the main stream from upstream to downstream is mostly a single change trend, while in each primary tributary, the overall value is larger than that of the main stream and the interannual difference is obvious. The average annual REP generally shows the distribution characteristics of ‘large at the junction of the upper and middle reaches and small in the rest of the area’. With the increase in the control area, the multi-year average REP has a decreasing trend, especially when the catchment area above the sub-watershed is >7318 km2; the change of the multi-year average REP is single and obviously slows down, with an average value of 23.8 mm·m3·s−1·km−2.

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“…Among the published studies, several have reported that aquatic systems may undergo sudden changes in water quality and/or ecosystem health in response to changes in their surrounding landscapes (Dodds et al, 2010;Capon et al, 2015;Tayyebi et al, 2015;D'Amario et al, 2019;Chen & Olden, 2020;Liu et al, 2021;Wang et al, 2022;Zhong et al, 2022;Xu et al, 2023a). However, as not all ecosystems experience nonlinear responses to external perturbations, it is also possible to identify regulatory thresholds that reflect balanced trade-offs between environmental protection and socioeconomic development (Antoniuk, 2006;Johnson, 2013;Guntenspergen & Gross, 2014;Kelly et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

Estimating Thresholds of Natural Vegetation for the Protection of Water Quality in South African Catchments

Locke

2024

Preprint

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Many of South Africa’s water quality problems are directly attributable to the negative impacts of anthropogenic land use transformations, including urban and agricultural expansion. To mitigate these impacts, the preservation of an adequate amount of natural vegetation within catchment areas is an important management strategy. However, it is unclear how much natural vegetation cover is required to provide adequate levels of protection, nor at which scale(s) this strategy would be most effective. Accordingly, regression analysis was used to model relationships between water quality (measured using Nemerow’s Pollution Index) and metrics of natural vegetation at multiple scales across a sample of sub-catchments located within South Africa’s Eastern and Western Cape provinces. With conspicuous outliers removed, the models were able to explain between 69 and 82% of variation in the sample. Moreover, a statistically significant, nonlinear, and inverse relationship was found between proportions of natural vegetation cover and pollution levels. This relationship was strongest when measured (1) across the whole catchment and (2) within a 200 m riparian buffer zone. The models further indicated that approximately 80 to 90% natural vegetation cover was necessary at these scales to maintain water quality at ecologically acceptable levels. Additional nonlinear thresholds estimated using breakpoint analysis suggested that if proportions of natural vegetation fall below 45% (across the whole catchment) and 60% (within a 200 m riparian buffer zone) a dramatic increase in pollution levels can be expected.

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Significance of using dynamic land-use data and its threshold in hydrology and water quality simulation models

Cited by 4 publications

References 49 publications

Sustainable transformation of agriculture requires landscape experiments

Sustainable transformation of agriculture requires landscape experiments

Analysis of Spatial and Temporal Characteristics of Runoff Erosion Power in Fujiang River Basin Based on the SWAT Model

Estimating Thresholds of Natural Vegetation for the Protection of Water Quality in South African Catchments

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