Simulating rainfall is one of the valuable methods of measuring hydrological data and soil erosion processes. Rapid evaluation, high repeatability, and low cost are the reasons of using rain simulators. In this study, a rain simulator was constructed in dimensions of 3.0 × 3.0 × 3.0 m and it was protected on three sides by a plastic cover. An inclined table was used to create slopping surfaces of 5, 10, and 15%. Microplots were used in the dimensions of 0.2 × 0.4 × 1.0 m to collect and measure direct runoff in a bucket outside the device. Nozzles were calibrated to produce two different rainfall intensities 10 and 20 mmh−1 using sprinkler Model 5B at 8 and 12 psi, respectively. Furthermore, three different soil types, namely, clay loam (CL), silty clay (SC) loam, and SC were examined. In general, it was observed that with increasing the rainfall intensity and slope, the rate of runoff and sedimentation increase. SC soil at 15% slop offered the highest performance under the intensity of 20 mmh−1. SC and the CL soils produced the highest and lowest runoff coefficients, respectively. The CL soil produced the highest soil loss (1 kgm2 at 15% and I = 20 mmh−1). Further, it was concluded that a significant change (an average increase of 53%) in soil loss can be achieved as the rainfall intensity increased from 10 to 20 mmh−1.

This study aimed to determine the best fit probability distribution of annual maximum rainfall using data from nine stations within Erbil province using different statistical analyses. Nine commonly used probability distribution functions, namely Normal, Lognormal (LN), one-parameter gamma (1P-G), 2P-G, 3P-G, Log Pearson, Weibull, Pareto, and Beta, were assessed. On the basis of maximum overall score, obtained by adding individual point scores from three selected goodness-of-fit tests, the best fit probability distribution was identified. Results showed that the 2P-G distribution and LN distribution were the best fit probability distribution functions for annual rainfall for the region. The analysis of annual rainfall records in Erbil city spanning from 1964 to 2013, covering three periods, also revealed significant temporal changes in the shape and scale parameter patterns of the fitted gamma distribution. Based on the reliable annual rainfall data in the region, the shape and scale parameters were then regionalized, hence it is possible to find the parameter values for any desired location within the study area. The Mann–Kendall test results indicated that there was a decreasing trend in rainfall over most of the study area in recent decades.

The measurement of soil hydraulic properties is tedious, time-consuming, and costly. An alternative approach is to formulate models that utilize the physical and chemical properties of the soil as input variables to predict soil saturated hydraulic conductivity (Ks). However, the previous studies have not paid attention to the calcium carbonate content in their models; it can lead to reducing the size and number of the pores in the soil which, in turn, can lead to reduction Ks . Here we evaluated the ability of the Soil, Plant, Atmosphere, and Water (SPAW) model to predict Ks under different states of compaction for calcareous soils with wide-ranging textures sampled along a precipitation gradient in northwestern Iraqi Kurdistan. The results revealed that the best match occurred under loose to normal state of compaction for these soils. Among the soil properties, sand content was high significantly correlated with Ks followed by CaCO3, clay, organic matter content, silt and Electrical conductivity. A pedotransfer function (PTF) was proposed using these data and its results were compared to these from the SPAW model. Root mean square error (RMSE) and coefficient of variation (CV) for the comparison between measured Ks values and those predicted by the SPAW model were very high 2.7×10-4 cm s−1 and 166% respectively, that due to the values of Ks predicted by the SPAW model are overestimated for calcareous soils, for these reasons the accuracy of the SPAW model was improved via calibration. The RMSE and CV of the calibrated SPAW model were dropped to 9.8×10-5 cm s−1 and 61.2%, respectively. Additionally, the accuracy of our best PTF that constructed from sand, clay, and CaCO3 was slightly higher than the calibrated SPAW model. Therefore, it is recommended to use the calibrated SPAW model for predicting Ks in calcareous soils.

Availability of improved tillage and herbicides during the last decades has enhanced the acceptance of conservation tillage. The main constrain to this type of tillage, particularly, zero tillage is high level of crop residue, which reduces seeding quality, soil temperature, etc. Accordingly, a study was initiated by equipping row cleaners with no-till system under wheat cultivation. For this purpose, a field experiment was laid in a split-split plot design with three types of row cleaners, three sub-treatments of travelling speed, and two sub- sub treatments of tillage depth. The results indicated that the soil temperature was highly affected by percent of residue left. Measurement of penetration resistance indicated that hard pan was not a potential limiting factor for the crop root development. The soil water was increased by 8.83%, 15.33% and 12.54% under no-till without row cleaner (M1), no-till with narrow row cleaner (M2) and no-till with wide row cleaner (M3) respectively compared to that under conventional tillage (CT). The percentage of soil loss reduction under M1, M2 and M3 were 53.11%, 59.62% and 50.51% compared to that under CT. The water losses were also reduced by 46.19%, 48.65% and 46.86% under these treatments as compared with CT.

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