Effects of performing an R-factor analysis of observed variables based on population models comprising R- and Q-factors were investigated. Although R-factor analysis of data based on a population model comprising R- a...Effects of performing an R-factor analysis of observed variables based on population models comprising R- and Q-factors were investigated. Although R-factor analysis of data based on a population model comprising R- and Q-factors is possible, this may lead to model error. Accordingly, loading estimates resulting from R-factor analysis of sample data drawn from a population based on a combination of R- and Q-factors will be biased. It was shown in a simulation study that a large amount of Q-factor variance induces an increase in the variation of R-factor loading estimates beyond the chance level. Tests of the multivariate kurtosis of observed variables are proposed as an indicator of possible Q-factor variance in observed variables as a prerequisite for R-factor analysis.展开更多
In most TVD schemes, the r-factors were proposed according to the cell-centered（CC） finite volume method（FVM） framework for the numerical approximation to the convective term. However, it is questionable whether t...In most TVD schemes, the r-factors were proposed according to the cell-centered（CC） finite volume method（FVM） framework for the numerical approximation to the convective term. However, it is questionable whether those r-factors would be appropriate and effective for the vertex-centered（VC） FVM. In the paper, we collected five kinds of r-factor formulae and found out that only three of those, respectively by Bruner（1996）, Darwish and Moukalled（2003） and Cassuli and Zanolli（2005） can be formally extended to a context of the VC FVM. Numerical tests indicate that the TVD schemes and r-factors, after being extended and introduced to a context of the VC FVM, maintained their similar characteristics as in a context of the CC FVM. However, when the gradient-based r-factors and the SUPERBEE scheme were applied simultaneously, non-physical oscillations near the sharp step would appear. In the transient case, the oscillations were weaker in a context of the VC FVM than those in a context of the CC FVM, while the effect was reversed in the steady case. To eliminate disadvantages in the gradient-based r-factor formula, a new modification method by limiting values on the virtual node, namely Фu in the paper, was validated by the tests to effectively dissipate spurious oscillations.展开更多
One of the most commonly used equations to estimate soil erosion is the revised universal soil loss equation (RUSLE). Based on the early approach developed by the Soil Conservation Service of USA, the rainfall erosivi...One of the most commonly used equations to estimate soil erosion is the revised universal soil loss equation (RUSLE). Based on the early approach developed by the Soil Conservation Service of USA, the rainfall erosivity factor (R-factor) in the RUSLE equation requires sub-daily rainfall data, which is usually not available. Other empirical equations estimate R-factor based on available rainfall data like annual and monthly rainfall data. In arid regions such as the Arabian Peninsula, several studies estimated the R-factor based on these empirical equations without calibration. We propose in this paper to assess the applicability of some of these empirical equations against R-factor values calculated using as a reference the RUSLE approach. For this data, data from 104 stations with sub-daily rainfall was collected. The reference R-factor w<span><span><span style="font-family:;" "="">as</span></span></span><span><span><span style="font-family:;" "=""> calculated for the 104 stations. The results of seven empirical equations were tested against the reference R-factor. Most of the tested equations significantly underestimated the R-factor. Furthermore, the obtained RMSE and MAE values were almost as high as the average R-factor, with MAPE exceeding 100%. Therefore, it is recommended not to apply these equations in arid regions. A recalibration of the form of equation that gave the best results, gave a</span></span></span><span><span><span style="font-family:;" "="">n</span></span></span><span><span><span style="font-family:;" "=""> RMSE of 280 (Mj<span style="color:#4F4F4F;font-family:-apple-system, "font-size:16px;white-space:normal;background-color:#F7F7F7;">·</span>mm/(ha<span style="color:#4F4F4F;font-family:-apple-system, "font-size:16px;white-space:normal;background-color:#F7F7F7;">·</span>hr)) and the MAPE dropped to 47.6%.</span></span></span>展开更多
The prevalence of unwholesome land use practices and population pressure exacerbates soil loss which is worsening the problem of sedimentation of the Kubanni dam. This study was conducted at the Kubanni drainage basin...The prevalence of unwholesome land use practices and population pressure exacerbates soil loss which is worsening the problem of sedimentation of the Kubanni dam. This study was conducted at the Kubanni drainage basin covering a spatial area of 56.7 Km2 in Samaru, Zaria, Nigeria to estimate annual soil loss using the RUSLE model. Satellite images of Landsat OLI for December 2014, 2016, 2018, February, July and November 2022;soil data, rainfall data from 2010 to 2022, and DEM of 30-meter resolution were utilized for the study. All factors of the RUSLE model were calculated for the basin using assembled data. The erosivity (R-factor) was discovered to be 553.437 MJ∙mm∙ha−1∙h−1∙yr−1. The average erodibility (K-factor) value was 0.1 Mg∙h∙h∙ha−1∙MJ−1∙mm−1∙yr−1. The Slope Length and Steepness factor (LS-factor) in the basin ranged between 0% and 13.47%. The Crop Management Factor (C-factor) values were obtained from a rescaling of the NDVI values derived for the study area and ranged from 0.26 to 0.55. Support practice (P-factors) were computed from the prevalent tillage practice in the basin and ranged from 0.27 to 0.40. The soil loss amount for the Kubanni basin was found to be 28441.482 tons∙ha−1∙yr−1, while the annual soil loss for the entire Kubanni drainage basin was found to be 49780.257 tons∙yr−1. The study has demonstrated the viability of coupling RUSLE model and Remote Sensing and Geographic Information System (GIS) techniques for the estimation of soil loss in the Kubanni drainage basin.展开更多
Temporal changes in rainfall erosivity can be expected to occur with changing climate and because rainfall amounts areknown to bein pait of afunction of elevation erosivity can be expected to be influenced by elevatio...Temporal changes in rainfall erosivity can be expected to occur with changing climate and because rainfall amounts areknown to bein pait of afunction of elevation erosivity can be expected to be influenced by elevation as well.This is particularly truein mountainous regions such as are found over much of the westem United Stafes.The objective of this study was to identify temporal and elevation trends in rainfall erosivity on a 149km^(2)(58 miles)watershed in a semi-arid region of southeastem Arizona Data from 84 rain gages forthe years 19602012 at elevations ranging from 1231 to 1644 m(40385394 ft)were used in the analyses.The average annual erosivity over the watershed as a whole was 1104 MJ mm ha^(-1)h^(-1)yr^(-1)(65 hundreds of foot ton inch acrei h^(-1)yr^(-1)),and ranged from approximately 950 to 1225 MJ mm ha^(-1)h^(-1)yr^(-1)(56-72 hundreds of foot ton inch acre^(-1)h^(-1)yr^(-1)),with a statistical trend showing greater erosivity af the higher elevations No statistically significant temporal changes in annual or summer erosivities were found.This result stands in contrast to fecent modeling studies of runoff and erosion in the area based on downscaled GCM information that project significant levels of erosivity changes over coming decades.These results are consistent with known orographic rainfall effects,but contrast with recent studies that presented projections of significant trends of increasing erosivity in the future based on downscaled GCM outputs for the area The results illustiate the need for testing and developing improved techniques to evaluate future erosion scenarios for purposes of making targeted soil conservation decisions Production and Hosting by Elsevier B.V on behalf of International Research and Training Center on Erosion and Sedimentation and China Water and Power Press This is anopen access article under theCCBY-NC-ND licens(http://creativecommons.org/licenses/by-ncnd/4.0/).展开更多
文摘Effects of performing an R-factor analysis of observed variables based on population models comprising R- and Q-factors were investigated. Although R-factor analysis of data based on a population model comprising R- and Q-factors is possible, this may lead to model error. Accordingly, loading estimates resulting from R-factor analysis of sample data drawn from a population based on a combination of R- and Q-factors will be biased. It was shown in a simulation study that a large amount of Q-factor variance induces an increase in the variation of R-factor loading estimates beyond the chance level. Tests of the multivariate kurtosis of observed variables are proposed as an indicator of possible Q-factor variance in observed variables as a prerequisite for R-factor analysis.
基金financially supported by the National Natural Science Foundation of China(Grant Nos.41306078 and 41301414)the National Engineering Research Center for Inland Waterway Regulation and Key Laboratory of Hydraulic and Waterway Engineering of the Ministry of Education Program(Grant No.SLK2016B03)the Key Laboratory of the Inland Waterway Regulation of the Ministry of Transportation Program(Grant No.NHHD-201514)
文摘In most TVD schemes, the r-factors were proposed according to the cell-centered（CC） finite volume method（FVM） framework for the numerical approximation to the convective term. However, it is questionable whether those r-factors would be appropriate and effective for the vertex-centered（VC） FVM. In the paper, we collected five kinds of r-factor formulae and found out that only three of those, respectively by Bruner（1996）, Darwish and Moukalled（2003） and Cassuli and Zanolli（2005） can be formally extended to a context of the VC FVM. Numerical tests indicate that the TVD schemes and r-factors, after being extended and introduced to a context of the VC FVM, maintained their similar characteristics as in a context of the CC FVM. However, when the gradient-based r-factors and the SUPERBEE scheme were applied simultaneously, non-physical oscillations near the sharp step would appear. In the transient case, the oscillations were weaker in a context of the VC FVM than those in a context of the CC FVM, while the effect was reversed in the steady case. To eliminate disadvantages in the gradient-based r-factor formula, a new modification method by limiting values on the virtual node, namely Фu in the paper, was validated by the tests to effectively dissipate spurious oscillations.
文摘One of the most commonly used equations to estimate soil erosion is the revised universal soil loss equation (RUSLE). Based on the early approach developed by the Soil Conservation Service of USA, the rainfall erosivity factor (R-factor) in the RUSLE equation requires sub-daily rainfall data, which is usually not available. Other empirical equations estimate R-factor based on available rainfall data like annual and monthly rainfall data. In arid regions such as the Arabian Peninsula, several studies estimated the R-factor based on these empirical equations without calibration. We propose in this paper to assess the applicability of some of these empirical equations against R-factor values calculated using as a reference the RUSLE approach. For this data, data from 104 stations with sub-daily rainfall was collected. The reference R-factor w<span><span><span style="font-family:;" "="">as</span></span></span><span><span><span style="font-family:;" "=""> calculated for the 104 stations. The results of seven empirical equations were tested against the reference R-factor. Most of the tested equations significantly underestimated the R-factor. Furthermore, the obtained RMSE and MAE values were almost as high as the average R-factor, with MAPE exceeding 100%. Therefore, it is recommended not to apply these equations in arid regions. A recalibration of the form of equation that gave the best results, gave a</span></span></span><span><span><span style="font-family:;" "="">n</span></span></span><span><span><span style="font-family:;" "=""> RMSE of 280 (Mj<span style="color:#4F4F4F;font-family:-apple-system, "font-size:16px;white-space:normal;background-color:#F7F7F7;">·</span>mm/(ha<span style="color:#4F4F4F;font-family:-apple-system, "font-size:16px;white-space:normal;background-color:#F7F7F7;">·</span>hr)) and the MAPE dropped to 47.6%.</span></span></span>
文摘The prevalence of unwholesome land use practices and population pressure exacerbates soil loss which is worsening the problem of sedimentation of the Kubanni dam. This study was conducted at the Kubanni drainage basin covering a spatial area of 56.7 Km2 in Samaru, Zaria, Nigeria to estimate annual soil loss using the RUSLE model. Satellite images of Landsat OLI for December 2014, 2016, 2018, February, July and November 2022;soil data, rainfall data from 2010 to 2022, and DEM of 30-meter resolution were utilized for the study. All factors of the RUSLE model were calculated for the basin using assembled data. The erosivity (R-factor) was discovered to be 553.437 MJ∙mm∙ha−1∙h−1∙yr−1. The average erodibility (K-factor) value was 0.1 Mg∙h∙h∙ha−1∙MJ−1∙mm−1∙yr−1. The Slope Length and Steepness factor (LS-factor) in the basin ranged between 0% and 13.47%. The Crop Management Factor (C-factor) values were obtained from a rescaling of the NDVI values derived for the study area and ranged from 0.26 to 0.55. Support practice (P-factors) were computed from the prevalent tillage practice in the basin and ranged from 0.27 to 0.40. The soil loss amount for the Kubanni basin was found to be 28441.482 tons∙ha−1∙yr−1, while the annual soil loss for the entire Kubanni drainage basin was found to be 49780.257 tons∙yr−1. The study has demonstrated the viability of coupling RUSLE model and Remote Sensing and Geographic Information System (GIS) techniques for the estimation of soil loss in the Kubanni drainage basin.
文摘Temporal changes in rainfall erosivity can be expected to occur with changing climate and because rainfall amounts areknown to bein pait of afunction of elevation erosivity can be expected to be influenced by elevation as well.This is particularly truein mountainous regions such as are found over much of the westem United Stafes.The objective of this study was to identify temporal and elevation trends in rainfall erosivity on a 149km^(2)(58 miles)watershed in a semi-arid region of southeastem Arizona Data from 84 rain gages forthe years 19602012 at elevations ranging from 1231 to 1644 m(40385394 ft)were used in the analyses.The average annual erosivity over the watershed as a whole was 1104 MJ mm ha^(-1)h^(-1)yr^(-1)(65 hundreds of foot ton inch acrei h^(-1)yr^(-1)),and ranged from approximately 950 to 1225 MJ mm ha^(-1)h^(-1)yr^(-1)(56-72 hundreds of foot ton inch acre^(-1)h^(-1)yr^(-1)),with a statistical trend showing greater erosivity af the higher elevations No statistically significant temporal changes in annual or summer erosivities were found.This result stands in contrast to fecent modeling studies of runoff and erosion in the area based on downscaled GCM information that project significant levels of erosivity changes over coming decades.These results are consistent with known orographic rainfall effects,but contrast with recent studies that presented projections of significant trends of increasing erosivity in the future based on downscaled GCM outputs for the area The results illustiate the need for testing and developing improved techniques to evaluate future erosion scenarios for purposes of making targeted soil conservation decisions Production and Hosting by Elsevier B.V on behalf of International Research and Training Center on Erosion and Sedimentation and China Water and Power Press This is anopen access article under theCCBY-NC-ND licens(http://creativecommons.org/licenses/by-ncnd/4.0/).
