Estimating Rainfall Interception of Vegetation Canopy from MODIS Imageries in Southern China

Wu, Jianping; Liu, Liyang; Sun, Changzheng; Su, Yongxian; Wang, Changjian; Yang, Ji; Liao, Jiayuan; He, Xiaolei; Li, Qian; Zhang, Chaoqun; Zhang, Hongou

doi:10.3390/rs11212468

Cited by 19 publications

(15 citation statements)

References 63 publications

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“…Different root architectures have different water absorption, water holding capacity, and the ability to improve matric suction, so the rainfall threshold is different. The rainfall interception by vegetation canopies plays an important role in slope stabilization, which is related to the vegetation coverage [52]. The interception is not involved in this paper, and further research in this area should be strengthened in the future.…”

Section: Discussionmentioning

confidence: 99%

Effect of Vegetation Roots on the Threshold of Slope Instability Induced by Rainfall and Runoff

2021

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Although vegetation is increasingly used to mitigate landslide risks, how vegetation roots affect the landslide threshold of slope has rarely been explored, particularly in the case of lateral runoff. In this study, we established a two-dimensional saturated-unsaturated infiltration equation considering the hydraulic effects of vegetation roots. The analytical solution for the shallow unsaturated two-dimensional coupled infiltration of vegetated slope (VS) was obtained by a Fourier transform technique. The numerical method was used to evaluate the stability of VS caused by four root architectures, the rainfall amount, and the rainfall duration. Subsequently, the transformation law in runoff, vegetation evaporation, and landslide threshold was analyzed. The results indicate that the factor of safety (FOS) increases with increasing drying time and decreases with increasing depth; the minimum FOS is at the junction of the root-rootless zone. Runoff and vegetation evaporation are favorable for the shallow stability of VS. The time of the safe area is 35 h for rainfall amount 500 m in the uniformly root clay slope. Moreover, four landslide threshold curves that reflected the root architecture, rainfall amount, and rainfall duration are developed, which are more realistic than those created using one-dimensional instability modeling.

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Section: Discussionmentioning

confidence: 99%

Effect of Vegetation Roots on the Threshold of Slope Instability Induced by Rainfall and Runoff

2021

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Section: Study Area and Datamentioning

confidence: 99%

“…Estimates of LAI are expected to be useful for constraining simulated interception depths (annual means, seasonal distributions and even time series values). The major uncertainties are expected to be in the conversion of LAI into depths of interception for a given climate regime (De Groen & Savenije, 2006; Návar, 2020; Wu et al, 2019). The LAI data (Mao & Yan, 2019) used in the study are long‐term (1981–2015) monthly means (https://daac.ornl.gov/VEGETATION/guides/Mean_Seasonal_LAI.html, accessed during July 2020).…”

Section: Study Area and Datamentioning

confidence: 99%

Unpacking some of the linkages between uncertainties in observational data and the simulation of different hydrological processes using the Pitman model in the data scarce Zambezi River basin

Hughes

Farinosi

2021

Hydrological Processes

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The main objective of this study was to use an uncertainty version of a widely used monthly time step, semi-distributed model (the Pitman model) to explore the equifinalities in the way in which the main hydrological processes are simulated and any identifiable linkages with uncertainties in the available observational data. The study area is the Zambezi River basin and 17 gauged sub-basins have been included in the analyses. Unfortunately, it is not generally possible to quantify some of the observational uncertainties in such a data scarce area and mostly we are limited to identifying where these data are clearly deficient (i.e., erroneous or non-representative). The overall conclusion is that the equifinalities in the model are hugely dominant in terms of the uncertainties in the relative occurrence of different runoff generating processes, although water use uncertainties in the semi-arid parts of the basin can contribute to these uncertainties. The identification of landscape features that suggest the occurrence of saturation excess surface runoff provides some information to constrain the model. Improved independent estimates of groundwater recharge is also identified as a key source of observational data that would help a great deal in constraining the model parameter space and therefore reducing some of the model equifinality.

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“…Estimates of LAI are expected to be useful for constraining simulated interception depths (annual means, seasonal distributions and even time series values). The major uncertainties are not expected to be in the conversion of LAI into depths of interception for a given climate regime (De Groen and Savenije, 2006;Wu et al, 2019;Navar, 2020). The LAI data (Mao and Yan, 2019) used in the study are long-term (1981 to 2015) monthly means (https://daac.ornl.gov/VEGETATION/guides/Mean Seasonal LAI.html, accessed during July 2020) and the seasonal range for all sub-basins used in this study (plotted against their aridity index), as well as some sample seasonal distributions are given in Figure 3.…”

Section: Water Use Functionsmentioning

confidence: 99%

Unpacking some of the linkages between uncertainties in observational data and the simulation of different hydrological processes using the Pitman model in the data scarce Zambezi River basin.

Hughes

Farinosi

2020

Preprint

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The main objective of this study was to use an uncertainty version of a widely used monthly time step, semi-distributed model (the Pitman model) to explore the equifinalities in the way in which the main hydrological processes are simulated and any identifiable linkages with uncertainties in the available observational data. The study area is the Zambezi River basin and 18 gauged sub-basins have been included in the analyses. Unfortunately, it is not generally possible to quantify some of the observational uncertainties in such a data scarce area and mostly we are limited to identifying where these data are clearly deficient (i.e. erroneous or non-representative). The overall conclusion is that the equifinalities in the model are hugely dominant in terms of the uncertainties in the relative occurrence of different runoff generating processes, although water use uncertainties in the semi-arid parts of the basin can contribute to these uncertainties. The identification of landscape features that suggest the occurrence of saturation excess surface runoff provides some information to constrain the model. Improved independent estimates of groundwater recharge is also identified as a key source of observational data that would help a great deal in constraining the model parameter space and therefore reducing some of the model equifinality.Unpacking some of the linkages between uncertainties in observational data and the simulation of different hydrological processes using the Pitman model in the data scarce Zambezi River basin.

show abstract

Estimating Rainfall Interception of Vegetation Canopy from MODIS Imageries in Southern China

Cited by 19 publications

References 63 publications

Effect of Vegetation Roots on the Threshold of Slope Instability Induced by Rainfall and Runoff

Effect of Vegetation Roots on the Threshold of Slope Instability Induced by Rainfall and Runoff

Unpacking some of the linkages between uncertainties in observational data and the simulation of different hydrological processes using the Pitman model in the data scarce Zambezi River basin

Unpacking some of the linkages between uncertainties in observational data and the simulation of different hydrological processes using the Pitman model in the data scarce Zambezi River basin.

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