Sensitivity Analysis of the Surface Runoff Coefficient of HiPIMS in Simulating Flood Processes in a Large Basin

Wang, Yueling; Yang, Xiaoliu

doi:10.3390/w10030253

Cited by 8 publications

(7 citation statements)

References 27 publications

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“…Previous studies investigated the potential of integrating hydraulic roughness in the form of Manning's n and remote sensing data to quantify river discharge [17,22,23]. However, commonly they assigned the Manning's roughness coefficient based on land-cover/land-use class types interpreted from remote sensing [24][25][26]. Due to the high influence of vegetation on runoff generation, various remote sensing methods were developed to estimate hydraulic roughness over humid environments using remote sensing, such as using multispectral-based vegetation indices or light detection and ranging (LiDAR) [17,27].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Manning’s n Roughness Coefficient in Arid Environments by Using SAR Backscatter

et al. 2018

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The prediction of arid region flash floods (magnitude and frequency) is essential to ensure the safety of human life and infrastructures and is commonly based on hydrological models. Traditionally, catchment characteristics are extracted using point-based measurements. A considerable improvement of point-based observations is offered by remote sensing technologies, which enables the determination of continuous spatial hydrological parameters and variables, such as surface roughness, which significantly influence runoff velocity and depth. Hydrological models commonly express the surface roughness using Manning’s roughness coefficient (n) as a key variable. The objectives were thus to determine surface roughness by exploiting a new high spatial resolution spaceborne synthetic aperture radar (SAR) technology and to examine the correlation between radar backscatter and Manning’s roughness coefficient in an arid environment. A very strong correlation (R2 = 0.97) was found between the constellation of small satellites for Mediterranean basin observation (COSMO)-SkyMed SAR backscatter and surface roughness. The results of this research demonstrate the feasibility of using an X-band spaceborne sensor with high spatial resolution for the evaluation of surface roughness in flat arid environments. The innovative method proposed to evaluate Manning’s n roughness coefficient in arid environments with sparse vegetation cover using radar backscatter may lead to improvements in the performance of hydrological models.

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Section: Introductionmentioning

confidence: 99%

Evaluation of Manning’s n Roughness Coefficient in Arid Environments by Using SAR Backscatter

et al. 2018

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“…The models responded differently to extremely high and extremely low flows. Therefore, the responses of the models to different conditions [39][40][41] We also plotted flow duration curves (FDCs) in Figure 4 to evaluate the agreement between observations and simulations. Both the XAJ and SWAT models overestimated extreme high flows (<1% exceedance) during calibration and validation periods, and it was further obvious in the SWAT model.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…The models responded differently to extremely high and extremely low flows. Therefore, the responses of the models to different conditions [39][40][41] need further study. Table 5 summarizes the statistical performance measures for runoff, peak flow and occurrence time of peak flow.…”

Section: Simulation Resultsmentioning

confidence: 99%

Development and Integration of Sub-Daily Flood Modelling Capability within the SWAT Model and a Comparison with XAJ Model

Shi

et al. 2018

Water

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To date, floods have become one of the most severe natural disasters on Earth. Flood forecasting with hydrological models is an important non-engineering measure for flood control and disaster reduction. The Xin’anjiang (XAJ) model is the most widely used hydrological model in China for flood forecasting, while the Soil and Water Assessment Tool (SWAT) model is widely applied for daily and monthly simulation and has shown its potential for flood simulation. The objective of this paper is to evaluate the performance of the SWAT model in simulating floods at a sub-daily time-scale in a slightly larger basin and compare that with the XAJ model. Taking Qilijie Basin (southeast of China) as a study area, this paper developed the XAJ model and SWAT model at a sub-daily time-scale. The results showed that the XAJ model had a better performance than the sub-daily SWAT model regarding relative runoff error (RRE) but the SWAT model performed well according to relative peak discharge error (RPE) and error of occurrence time of peak flow (PTE). The SWAT model performed unsatisfactorily in simulating low flows due to the daily calculation of base flow but behaved quite well in simulating high flows. We also evaluated the effect of spatial scale on the SWAT model. The results showed that the SWAT model had a good applicability at different spatial scales. In conclusion, the sub-daily SWAT model is a promising tool for flood simulation though more improvements remain to be studied further.

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“…where ∆t is the duration when the flow of the i-th grid reaches the outlet of the corresponding sub-basin (the value is an integer) (s); L is the ground flow length (m); n is the roughness (the values of different land use types are derived from some references and are shown in Table 4 [37,38]); i c is the net rain intensity (m/s); and S l is the slope. According to the above formula, the surface runoff in each period through the outlets of the sub-basin was calculated as follows:…”

Section: Water Quantity Modulementioning

confidence: 99%

A Combination Model for Quantifying Non-Point Source Pollution Based on Land Use Type in a Typical Urbanized Area

Wang

Rao

Yang

et al. 2020

Water

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Water pollution poses threats to urban environments and subsequently impacts the ecological health and sustainable development of urban areas. Identifying the spatiotemporal variation in non-point sources (NPS) pollution is a prerequisite for improving water quality. This paper aimed to assess the NPS pollution load and then recognized the spatiotemporal characteristics of the pollution sources in a typical urbanized area. A combination model based on land use type was used to simulate the NPS pollution load. The results showed the following: (1) ponds and farmlands had higher pollution production intensities than other land use types, but the intensity and magnitude of pollution emissions were generally greater in urban areas; (2) monthly and annual total nitrogen (TN) and total phosphorus (TP) emissions had the same pattern as rainfall, and TN and TP emissions accounted for 56.2% and 58.0%, respectively, of the total in summer; (3) TN pollution was more serious than TP pollution in the study area, especially in farmlands; (4) urban runoff (UR) and livestock and poultry breeding (LPB) were the main sources of NPS, TN and TP emissions in the study area. If these NPS pollutants cannot be removed from this area, a large amount of freshwater is needed to dilute the current rivers to meet the requirement of the fourth category of China national environmental quality standards for surface water. This problem is serious in the control of polluted rivers in many cities throughout China.

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Sensitivity Analysis of the Surface Runoff Coefficient of HiPIMS in Simulating Flood Processes in a Large Basin

Cited by 8 publications

References 27 publications

Evaluation of Manning’s n Roughness Coefficient in Arid Environments by Using SAR Backscatter

Evaluation of Manning’s n Roughness Coefficient in Arid Environments by Using SAR Backscatter

Development and Integration of Sub-Daily Flood Modelling Capability within the SWAT Model and a Comparison with XAJ Model

A Combination Model for Quantifying Non-Point Source Pollution Based on Land Use Type in a Typical Urbanized Area

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