Responses of flood peaks to land use and landscape patterns under extreme rainstorms in small catchments - A case study of the rainstorm of Typhoon Lekima in Shandong, China

Yuanhao, Liu; Han, Jianqiao; Jiao, Juying; Liu, Baoyuan; Ge, Wenyan; Qing-bin, Pan; Wang, Fei

doi:10.1016/j.iswcr.2021.07.005

Cited by 24 publications

(13 citation statements)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…1b), the land use types in the above regions are mainly forest land, and the area covers 51.04% of the total area of the watershed. The output flow accounts for 54.21% of the total output of the basin, which is the key area for water conservation [34]. The water intake of the Shanxi…”

Section: Spatial Distribution Of Water Resources and Identification O...mentioning

confidence: 99%

Daily-Scale Runoff Simulation of Shanxi Drinking Water Based on SWAT Model, Using Separation Dry and Wet Season Calibration Method

Liu¹,

Fang²,

Zhou³

et al. 2023

Pol. J. Environ. Stud.

View full text Add to dashboard Cite

In this study, by establishing a daily scale SWAT model with dry and wet seasons separated in the study area, the sensitivity and uncertainty of parameters in the typhoon-affected area are discussed. At the same time quantitative analysis of the temporal and spatial characteristics of water resources. The results show that 1) the sensitivity parameters in the dry and wet seasons are very different. The most sensitive parameters are ALPHA_BF.gw and CN_2.mgt, but the least sensitive parameters are SURLAG.bsn and GWQMN.gw, respectively. This is obviously related to the meteorological conditions of the two periods. 2) Uncertainty analysis shows that the uncertainty of model parameters is mainly caused by extreme daily runoff parameters. 3) Except that the NSE and R 2 of the wet season model are slightly lower than 0.7, the NSE and R 2 of the dry season are higher than 0.73, and the PBIAS in both periods is within 10%. This shows that the application of separate calibration methods improves the accuracy of the model. 4) The correlation between wet season precipitation and runoff is higher than 0.98. The average wet season runoff for many years accounts for 81.44% of the annual runoff, which is the main period of runoff generation. The key source area of runoff is 51.04% of the total area of the river basin, and the runoff flow accounts for 54.21% of the total runoff of the land. It should be protected.

show abstract

Section: Spatial Distribution Of Water Resources and Identification O...mentioning

confidence: 99%

Daily-Scale Runoff Simulation of Shanxi Drinking Water Based on SWAT Model, Using Separation Dry and Wet Season Calibration Method

Liu¹,

Fang²,

Zhou³

et al. 2023

Pol. J. Environ. Stud.

View full text Add to dashboard Cite

show abstract

“…The method involves constructing envelopes based on historical flood data and using them to estimate the likelihood of future floods exceeding a certain discharge threshold. This early work laid the foundation for using envelopes in flood prediction, which has since been refined and expanded upon by many researchers in the field of hydrology (Boughton et al, 1987;Hu et al, 2019;Lam et al, 2017;Lian et al, 2017;Liu et al, 2022;Stevens, 1936).…”

Section: Rel Ated Work Smentioning

confidence: 99%

“…One of the earliest references in the literature that describes this purpose is a article published by J. C. Stevens in 1916 (Stevens, 1916), which describes a method of predicting floods using envelopes, defined as “the limits of flood discharge for different periods at a given point on a stream.” The method involves constructing envelopes based on historical flood data and using them to estimate the likelihood of future floods exceeding a certain discharge threshold. This early work laid the foundation for using envelopes in flood prediction, which has since been refined and expanded upon by many researchers in the field of hydrology (Boughton et al., 1987; Hu et al., 2019; Lam et al., 2017; Lian et al., 2017; Liu et al., 2022; Stevens, 1936).…”

Section: Related Workmentioning

confidence: 99%

Analyzing the spatial interactions between rainfall levels and flooding prediction in São Paulo

Billa,

Santos,

Negri

2023

Transactions in GIS

View full text Add to dashboard Cite

Rainfall is one of the primary triggers for many geological and hydrological natural disasters. While the geological events are related to mass movements in land collapse due to waterlogging, the hydrological ones are usually assigned to runoff or flooding. Studies in the literature propose predicting mass movement events as a function of accumulated rainfall levels recorded at distinct periods. According to these approaches, a two‐dimensional rainfall levels feature space is segmented into the occurrence and non‐occurrence decision regions by an empirical critical curve (CC). Although this scheme may easily be extended to other purposes and applications, studies in the literature need to discuss its use for flooding prediction. In light of this motivation, the present study is unfolded in (1) verifying that defining CCs in the rainfall levels feature space is a practical approach for flooding prediction and (2) analyzing how geospatial components interact with rainfall levels and flooding prediction. A database containing the rainfall levels recorded for flooding and non‐flooding events in São Paulo city, Brazil, regarding the period 2015–2016, was considered in this study. The results indicate good accuracy for flooding prediction using only partial rain, which can be improved by adding physical characteristics of the flooding locations, demonstrating a direct correlation with spatial interactions, and rainfall levels.

show abstract

“…Although multiple disciplines have explored spatial factors relating to UGS and flood mitigation, these perspectives are disconnected and inconsistent, limiting a comprehensive understanding of the role of spatial factors. For example, some studies indicate that smaller and dispersed patches may have more runoff reduction (Liu et al, 2022; Yang and Lee, 2021a), while others indicate the positive impact of larger connected UGS on runoff reduction in an urban watershed (Li et al, 2020). To gain a comprehensive understanding of the expansive research field of flood regulation, we seek to highlight the role of spatial factors of UGS in this study.…”

Section: Introductionmentioning

confidence: 99%

How do spatial factors of green spaces contribute to flood regulation in urban areas? A systematic mapping approach

Asl

Pearsall

2023

Progress in Physical Geography: Earth and Environment

View full text Add to dashboard Cite

Flooding is increasing in urban areas around the world, leading to loss of life and property damage, and cities are using urban green spaces (UGS) for flood regulation. The spatial attributes of UGS have an important role in controlling and regulating urban flooding, and there is a need for a systematic map on how spatial factors of UGS, such as shape, size, location, or connectivity, impact flooding in urban areas. The objectives of this study are to analyze and synthesize published material to evaluate the impacts of the spatial dimensions of UGS on flood regulation and to identify knowledge gaps and future research directions. Pertinent literature was reviewed and synthesized using the systematic mapping method. The results of this study show that previous research on spatial configuration have examined how variables such as slope, DEM, green space coverage, and landscape shape index impact runoff reduction. Slope was found to be an important, but not determining factor in flood regulation. There is a need for further research on how the geographic context of urban regions, including climatic conditions and land use changes, impacts UGS functionality. Additionally, there is a need for further research on how the spatial configuration of UGS impacts flood vulnerability and intensity, two under-addressed yet important topics in urban flooding.

show abstract

Responses of flood peaks to land use and landscape patterns under extreme rainstorms in small catchments - A case study of the rainstorm of Typhoon Lekima in Shandong, China

Cited by 24 publications

References 40 publications

Daily-Scale Runoff Simulation of Shanxi Drinking Water Based on SWAT Model, Using Separation Dry and Wet Season Calibration Method

Daily-Scale Runoff Simulation of Shanxi Drinking Water Based on SWAT Model, Using Separation Dry and Wet Season Calibration Method

Analyzing the spatial interactions between rainfall levels and flooding prediction in São Paulo

How do spatial factors of green spaces contribute to flood regulation in urban areas? A systematic mapping approach

Contact Info

Product

Resources

About