Universal Power Law for Relationship between Rainfall Kinetic Energy and Rainfall Intensity

Shin, Seung Sook; Park, Sang Deog; Choi, Byoung Koo

doi:10.1155/2016/2494681

Cited by 22 publications

(12 citation statements)

References 51 publications

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“…Grounds without canopy cover are affected by the raindrops falling directly onto the bare soil (direct throughfall). The kinetic energy density of direct throughfall (U DT ; J m −2 mm −1 ) is estimated from the universal power law equation suggested by Shin et al [45] for a given rainfall intensity (RI; mm h −1 ):…”

Section: Sediment Delivery To Surface Runoffmentioning

confidence: 99%

Daily Based Morgan–Morgan–Finney (DMMF) Model: A Spatially Distributed Conceptual Soil Erosion Model to Simulate Complex Soil Surface Configurations

Choi

Arnhold

Huwe

et al. 2017

Water

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Abstract:In this paper, we present the Daily based Morgan-Morgan-Finney model. The main processes in this model are based on the Morgan-Morgan-Finney soil erosion model, and it is suitable for estimating surface runoff and sediment redistribution patterns in seasonal climate regions with complex surface configurations. We achieved temporal flexibility by utilizing daily time steps, which is suitable for regions with concentrated seasonal rainfall. We introduce the proportion of impervious surface cover as a parameter to reflect its impacts on soil erosion through blocking water infiltration and protecting the soil from detachment. Also, several equations and sequences of sub-processes are modified from the previous model to better represent physical processes. From the sensitivity analysis using the Sobol' method, the DMMF model shows the rational response to the input parameters which is consistent with the result from the previous versions. To evaluate the model performance, we applied the model to two potato fields in South Korea that had complex surface configurations using plastic covered ridges at various temporal periods during the monsoon season. Our new model shows acceptable performance for runoff and the sediment loss estimation (NSE ≥ 0.63, |PBIAS| ≤ 17.00, and RSR ≤ 0.57). Our findings demonstrate that the DMMF model is able to predict the surface runoff and sediment redistribution patterns for cropland with complex surface configurations.

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Section: Sediment Delivery To Surface Runoffmentioning

confidence: 99%

Daily Based Morgan–Morgan–Finney (DMMF) Model: A Spatially Distributed Conceptual Soil Erosion Model to Simulate Complex Soil Surface Configurations

Choi

Arnhold

Huwe

et al. 2017

Water

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“…To estimate the combined effect of rainfall duration and intensity on the soil surface (i.e., the destruction of clods and particle displacement), cumulative kinetic energy was chosen as an indicator. To estimate the kinetic energy KE p (J·m −2 ) applied during each measurement phase, time-specific rainfall kinetic energy KE t (J·m −2 ·h −1 ) was first estimated using the universal power law proposed by [ 26 ], for each 5 min measuring time-step. KE p was then estimated as the sum of KE t for each measurement time step during a phase.…”

Section: Methodsmentioning

confidence: 99%

Towards Mapping of Soil Crust Using Multispectral Imaging

Crucil

Oost

2021

Sensors

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Soil crusts and surface roughness are properties which are highly dynamic in both space and time that change in response to biotic processes, meteorological conditions and farming operations. These factors, however, are difficult to quantify and are usually described using simplified expert-based classes. This hampers a clear identification of the controlling factors and their relation to soil erosion and sediment generation processes. The availability of new small portable multispectral cameras offers the potential to study soil surface dynamics at a high spatial and temporal resolution. The objective of this study was to analyse the relationship between soil crusting, represented by cumulative rainfall kinetic energy, and soil surface reflectance, as derived from vis-NIR multispectral imaging. We designed a series of rainfall-soil surface experiments to disentangle the effects of soil crusting on spectral reflectance factors from those related to surface micro-scale roughness. Partial least squared regression (PLSR) models were developed to predict both kinetic energy and roughness from multispectral images. We evaluated different roughness removal methods which were based on the transformation of reflectance through standard normal variate (SNV) and roughness thresholding using high resolution digital elevation models. Furthermore, we assigned the light scattering effect related to roughness in the multispectral spatial domain by calculating the inter-quantile range of the reflectance values in a kernel. Our experiments and workflow demonstrate that it is possible to model crust development, using rainfall kinetic energy as a proxy, from vis-NIR based multispectral imaging.

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“…Several models of KE-I relationships including linear [3,4], exponential [5][6][7][8], logarithmic [9,10] and power law [11][12][13][14] have been found to fit the empirical data the best. The large variation in the KE-I relationships established in the literature is caused by the use of different measurement methods, limited sampling, errors introduced during interpretation of data and rainfall patterns [15].…”

Section: Introductionmentioning

confidence: 99%

Impact of Disdrometer Types on Rainfall Erosivity Estimation

Johannsen

Zambon

Strauß³

et al. 2020

Water

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Soil erosion by water is affected by the rainfall erosivity, which controls the initial detachment and mobilization of soil particles. Rainfall erosivity is expressed through the rainfall intensity (I) and the rainfall kinetic energy (KE). KE–I relationships are an important tool for rainfall erosivity estimation, when direct measurement of KE is not possible. However, the rainfall erosivity estimation varies depending on the chosen KE–I relationship, as the development of KE–I relationships is affected by the measurement method, geographical rainfall patterns and data handling. This study investigated how the development of KE–I relationships and rainfall erosivity estimation is affected by the use of different disdrometer types. Rainfall data were collected in 1-min intervals from six optical disdrometers at three measurement sites in Austria, one site in Czech Republic and one site in New Zealand. The disdrometers included two disdrometers of each of the following types: the PWS100 Present Weather Sensor from Campbell Scientific, the Laser Precipitation Monitor from Thies Clima and the first generation Parsivel from OTT Hydromet. The fit of KE–I relationships from the literature varied among disdrometers and sites. Drop size and velocity distributions and developed KE–I relationships were device-specific and showed similarities for disdrometers of the same type across measurement sites. This hindered direct comparison of results from different types of disdrometers, even when placed at the same site. Thus, to discern spatial differences in rainfall characteristics the same type of measurement instrument should be used.

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Universal Power Law for Relationship between Rainfall Kinetic Energy and Rainfall Intensity

Cited by 22 publications

References 51 publications

Daily Based Morgan–Morgan–Finney (DMMF) Model: A Spatially Distributed Conceptual Soil Erosion Model to Simulate Complex Soil Surface Configurations

Daily Based Morgan–Morgan–Finney (DMMF) Model: A Spatially Distributed Conceptual Soil Erosion Model to Simulate Complex Soil Surface Configurations

Towards Mapping of Soil Crust Using Multispectral Imaging

Impact of Disdrometer Types on Rainfall Erosivity Estimation

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