MULTIVARIATE MODELS FOR PREDICTING RAINFALL EROSIVITY FROM ANNUAL RAINFALL AND GEOGRAPHICAL COORDINATES IN A REGION WITH A NON- UNIFORM PLUVIAL REGIME

Keya & Karim

doi:10.36103/ijas.v51i5.1133

Abstract

Soil erosion by water is a major land degradation problem because it threatens the farmer’s livelihood and ecosystem's integrity. Rainfall erosivity is one of the major controlling factors inducing this process. One obstacle of estimating the R-factor is the lack of detailed rainfall intensity data worldwide. To overcome the problem of data scarceness for individual analysis of storm events for developing the country with a non-uniform pluvial regime like the upper part of Iraq, multivariate models were derived for estimating annual rainfall erosivity. They were based on annual rainfall data and geographical coordinates of a group of meteorological stations distributed over the study area. A host of statistical indices were selected to evaluate adequately the model's performance. Further, the models were cross-validated using k-fold procedure and unseen data. Subsequently, four linear models were proposed for estimating the annual erosivity for the study area. Good correspondence was found between the measured and predicted values. Among the proposed models, the model with the combination of annual rainfall, latitude and longitude outperformed the remaining proposed ones. After calculating the annual, the ArcMap software ver. 10.2 was applied to map the spatial variability of the R-factor over the study region.

Highlights

Natural resources degradation is a challenging problem worldwide and in Iraq (15)
General aspects of annual rainfall and annual erosivity The average annual rainfall in the study area varied from 120.4 to1048.0 mm, with a high coefficient of variability (35.7%), indicating high spatial variability of rainfall in the study region
This result is concordant with the finding of Jawad et al (16), who observed a significant fluctuation of precipitation from its average value

Summary

INTRODUCTION

Natural resources degradation is a challenging problem worldwide and in Iraq (15). Rainfall erosivity is one of the major controlling factors inducing water erosion, which defined as the product of the total storm kinetic energy and maximum 30-minute rainfall intensity (28). This study was conducted with the main objective of deriving a multivariate model to estimate rainfall erosivity factor for the upper part of Iraq from annual rainfall data and some other predictors and creating a rainfall erosivity map based on the calculation of annual R. The data set consists receives rainfall less than 250 mm while the of rainfall records during 2000 -2018 at 25 rain semi-wet zone receives 900-1000 mm and gauges located in the study region and its over. Mapping the spatial variability of the RFactor After calculating the R-values at annual Rfactor, the ArcMap software ver. 10.2 was applied to map the spatial variability of the Rfactor over the region using Kriging interpolation method

RESULTS AND DISCUSSION

11 Multiple linear

Conclusions