Evaluation of Rainfall-Runoff Erosivity Factor for Cameron Highland, Pahang, Malaysia

Sholagberu, Abdulkadir Taofeeq; Mustafa, Muhammad Raza Ul; Yusof, Khamaruzaman Wan; Ahmad, Mustafa Hashim

doi:10.12911/22998993/63338

“…The 20 equation was modified because the original Loureiro and Coutinho (2001) equation was developed in Portugal, and the aim of Shamshad et al (2008) was to modify it to suit the climatic conditions of tropical Malaysia. Similarly, Sholagberu et al (2016) used 23 years of daily rainfall data to create a regression equation relating annual rainfall and the R-factor for the highlands of Malaysia. These equations that use monthly or annual rainfall are valuable in study areas that do not have longterm detailed rainfall data, but have a similar climate.…”

Section: Rainfall Erosivity Factor (R)mentioning

confidence: 99%

A review of the (Revised) Universal Soil Loss Equation (R/USLE): with a view to increasing its global applicability and improving soil loss estimates

Benavidez¹,

Jackson²,

Maxwell³

et al. 2018

Preprint

View full text Add to dashboard Cite

Abstract. Soil erosion is a major problem around the world because of its effects on soil productivity, nutrient loss, siltation in water bodies, and degradation of water quality. By understanding the driving forces behind soil erosion, we can more easily identify erosion-prone areas within a landscape and use land management and other strategies to effectively manage the problem. Soil erosion models have been used to assist in this task. One of the most commonly used soil erosion models is 10 the Universal Soil Loss Equation (USLE) and its family of models: the Revised Universal Soil Loss Equation (RUSLE), the Revised Universal Soil Loss Equation version 2 (RUSLE2), and the Modified Universal Soil Loss Equation (MUSLE). This paper reviewed the different components of USLE and RUSLE etc., and analysed how different studies around the world have adapted the equations to local conditions. We compiled these studies and equations to serve as a reference for other researchers working with R/USLE and related approaches. We investigate some of the limitations of R/USLE, such as issues 15 in data-sparse regions, its inability to account for soil loss from gully erosion or mass wasting events, and that it does not predict sediment pathways from hillslopes to water bodies. These limitations point to several future directions for R/USLE studies: incorporating soil loss from other types of soil erosion, estimating soil loss at sub-annual temporal scales, and using consistent units for future literature. These recommendations help to improve the applicability of the R/USLE in a range of geoclimatic regions with varying data availability, and at finer spatial and temporal scales for scenario analysis. 20

show abstract

“…Rainfall erosivity factor (R): Rainfall erosivity is the erosive force of rainfall [Essel, 2016] and is defined as the aggressiveness of rainfall to induce erosion of soils [Sholagberu, 2016]. This factor is of paramount importance in its effect on soil erosion due to the ability of rain to dissolve, loosen, or wear away soil by the force of raindrops or runoff [Essel, 2016;Okorafor, 2017;Sholagberu, 2016].…”

Section: Methodsmentioning

confidence: 99%

“…This factor is of paramount importance in its effect on soil erosion due to the ability of rain to dissolve, loosen, or wear away soil by the force of raindrops or runoff [Essel, 2016;Okorafor, 2017;Sholagberu, 2016]. It is thus used to quantify the effect of raindrop and induced runoff on bare soil [Efthimiou, 2014].…”

Section: Methodsmentioning

confidence: 99%

“…It is thus used to quantify the effect of raindrop and induced runoff on bare soil [Efthimiou, 2014]. It was calculated using the daily rainfall values summarized as monthly and annual rainfall based on similar approaches used or reported by [Efthimiou, 2014;Okorafor, 2017;Rahaman, 2015;Sholagberu, 2016;Ufoegbune, 2011]. A rainfall erosivity index was calculated from the summaries using the modified Fournier index [Essel, 2016] and the resulting values were used to prepare a map.…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Assessing the Threat of Erosion to Nature-Based Interventions for Stormwater Management and Flood Control in the Greater Accra Metropolitan Area, Ghana

Asiedu¹

2018

View full text Add to dashboard Cite

Perennial flooding has become a major feature in urban areas in developing economies generating research interest towards finding alternative approaches to stormwater management which could complement the existing systems and help address the challenge of flooding. One of such alternative approaches is nature-based stormwater management and flood control, the implementation of which could be affected by soil erosion. This paper, as part of a wider research, was developed to determine the extent of the threat of soil erosion to stormwater management in an urban area on the example of Greater Accra Metropolitan Area, Accra Ghana as the focus of the research. Landsat 8 images (2014) were used in the research to prepare the Landcover maps. Daily rainfall data from 6 raingauge stations from 1972 to 2014 were utilized to prepare the rainfall erosivity factor maps, whereas DEM was used to prepare the slope and slope length (SL) factor maps. The land cover map with an overall accuracy of 73.6 and Kappa 0.7122 was combined with literature sources to prepare the vegetative cover factor map, and conservation practice factor map. A soil series map, prepared and updated with literature sources and data from the Harmonized World Soil Database on physical parameters, was used to calculate the soil erodibility factor (K factor) for each soil series. These were integrated into RUSLE model as 30 m raster maps to generate a soil loss map at tons/ha/yr. The results produced rainfall erosivity index values based on the modified Fournier index ranging between 0.058 and 23.197 which is classified as low. Low soil erodibility factor (K) ranging between 2.9×10 -5 and 8.5×10 -2 t ha/MJ mm indicated low susceptibility to erosion, SL factor value showing areas of low to almost flat relief with a few isolated areas of moderate slope length were generated. A soil loss of 69,5918 tons/ha/yr classified the soils as having high potential soil loss. The results showed a very low soil loss threat of 0-5.1853 tons/Ha/yr for more than 90% of the study area. Targeted intervention for source areas with high potential soil loss will contain any threat of erosion and sediment yield to the implementation of an infiltration-based stormwater management and flood control system.

show abstract

“…Tables 8 and 9 give a broad overview of C factors for different cover types and common crops. Wischmeier and Smith (1987) also in- : angle of slope m: dependent on the slope -0.5 if slope > 5 % -0.4 if slope is between 3.5 % and 4.5 % -0.3 if slope is between 1 % and 3 % -0.2 if slope is less than 1 % Thailand (Eiumnoh, 2000;Merritt et al, 2004); Vanuatu (Dumas and Fossey, 2009) (Schmitt, 2009); China (Li et al, 2014); Thailand (Nontananandh and Changnoi, 2012); Turkey (Ozsoy et al, 2012) 3 David (1988), based on work by Madarcos (1985) and Smith and Whitt (1947) Philippines, but based on work from the USA Slope rise in percent…”

Section: Cover and Management Factor (C)mentioning

confidence: 99%

A review of the (Revised) Universal Soil Loss Equation ((R)USLE): with a view to increasing its global applicability and improving soil loss estimates

Benavidez

¹

,

Jackson

²

,

Maxwell

³

et al. 2018

Hydrol. Earth Syst. Sci.

View full text Add to dashboard Cite

Abstract. Soil erosion is a major problem around the world because of its effects on soil productivity, nutrient loss, siltation in water bodies, and degradation of water quality. By understanding the driving forces behind soil erosion, we can more easily identify erosion-prone areas within a landscape to address the problem strategically. Soil erosion models have been used to assist in this task. One of the most commonly used soil erosion models is the Universal Soil Loss Equation (USLE) and its family of models: the Revised Universal Soil Loss Equation (RUSLE), the Revised Universal Soil Loss Equation version 2 (RUSLE2), and the Modified Universal Soil Loss Equation (MUSLE). This paper reviews the different sub-factors of USLE and RUSLE, and analyses how different studies around the world have adapted the equations to local conditions. We compiled these studies and equations to serve as a reference for other researchers working with (R)USLE and related approaches. Within each sub-factor section, the strengths and limitations of the different equations are discussed, and guidance is given as to which equations may be most appropriate for particular climate types, spatial resolution, and temporal scale. We investigate some of the limitations of existing (R)USLE formulations, such as uncertainty issues given the simple empirical nature of the model and many of its sub-components; uncertainty issues around data availability; and its inability to account for soil loss from gully erosion, mass wasting events, or predicting potential sediment yields to streams. Recommendations on how to overcome some of the uncertainties associated with the model are given. Several key future directions to refine it are outlined: e.g. incorporating soil loss from other types of soil erosion, estimating soil loss at sub-annual temporal scales, and compiling consistent units for the future literature to reduce confusion and errors caused by mismatching units. The potential of combining (R)USLE with the Compound Topographic Index (CTI) and sediment delivery ratio (SDR) to account for gully erosion and sediment yield to streams respectively is discussed. Overall, the aim of this paper is to review the (R)USLE and its sub-factors, and to elucidate the caveats, limitations, and recommendations for future applications of these soil erosion models. We hope these recommendations will help researchers more robustly apply (R)USLE in a range of geoclimatic regions with varying data availability, and modelling different land cover scenarios at finer spatial and temporal scales (e.g. at the field scale with different cropping options).

show abstract

Evaluation of Rainfall-Runoff Erosivity Factor for Cameron Highland, Pahang, Malaysia

Cited by 29 publications

References 26 publications

A review of the (Revised) Universal Soil Loss Equation (R/USLE): with a view to increasing its global applicability and improving soil loss estimates

A review of the (Revised) Universal Soil Loss Equation (R/USLE): with a view to increasing its global applicability and improving soil loss estimates

Assessing the Threat of Erosion to Nature-Based Interventions for Stormwater Management and Flood Control in the Greater Accra Metropolitan Area, Ghana

A review of the (Revised) Universal Soil Loss Equation ((R)USLE): with a view to increasing its global applicability and improving soil loss estimates

Contact Info

Product

Resources

About