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Cd (54-125%)> Zn (35-73%)> Cu (13-87%)>Pb (6-32%). These patterns can be due to the quality and quantity of the used wastewater and impact of the used wastewater with its receiving soils. Similar to the available fraction, there was an increasing trend in the total fraction of metals in the order of Cd> Zn>Pb> Ni> Cu following wastewater irrigation. In this context, the mean content of total Zn, Cu, Cd, Pb, and Ni in wastewater-irrigated soils was as 51-157%, 10-32%, 243-310, 11-203%, and 13-126% higher than those of control soil, respectively. In spite of such enrichment, only the Cd values exceeded the maximum acceptable limits. The AP index is an appropriate index to compare the mobility potential and the toxicity of heavy metals in soil. In this study, the highest rate of this index among the heavy metals was related to Cd and its lowest level was related to Pb, which showed more toxicity and more mobility of Cd compared with other elements. The average of single-factor pollution index of five elements was observed in sequence Cd> Zn> Ni>Pb> Cu that the element of Cd had the highest class of PI (class 4). The highest and lowest of NPI values of five elements were observed in profiles 4 and 2, respectively. Also, the greatest effect of the five elements of this study is on the elements of Cd and Zn in the generation of this level of contamination. The pollution index of the five studied elements in irrigated soils with treated wastewater was similar to the NPI, its maximum was observed in profile 4 and Cd showed the highest effect on increasing the value of this index.
Conclusions: The results of this study showed that irrigation with sewage significantly increased the available fraction of the metals in the order of Ni (78.9-141.8%)> Cd (54.4-125%)> Zn (35.7-73.3%>Cu (13-87%)>Pb (6-32.3%) compared to the control. However, with the exception of cadmium, the available fraction of other elements was within the permissible limit. Compared to the control, in the majority of studied soils, the total fraction of the metals (with the exception of copper) was significantly increased and the lowest and highest increase associated with Cu (10-32%) and Cd (2 - 3 times). Also, the results of pollutant indices showed that the majority of the studied soils were in the low to high contamination and Cd was known as the major metal affecting the indices yield.]]>
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10%) and good (>20%) amounts in all stations and temporal scales. Among other stations, Mazar Shrif showed the best conformity between AgMERRA and observed data, while Kabul station had the weakest, probably due to complex topographic situation of the Kabul airport station. The amounts of R2 for predicting temperature (Tmax and Tmin) were more than 0.86 in daily, 14-days and monthly temporal scales. The lowest amount of the coefficient of determination was obtained at Qandahar station for Tmean in daily temporal scale (R2=0.8) and the highest amount obtained for daily Tmax at Mazar Sharif station (R2=0.947). R2 for daily PRCP were inadequate, but increasing to adequate amounts in 14-days and monthly temporal scales. The highest spatiotemporal amount of Tmax,Tmin and Tmean was obtained in daily scale and the lowest amount was obtained for Tmean (1.8 and 0.9, respectively). The Index of agreement (d), also had adequate amounts for 14-days and monthly PRCP (>0.87). The amount of MBE for precipitation in Herat, Mazar Sharif and Kabul stations were negative, while it was positive in Qandahar station with a hot and dry climate. AgMERRA could show a good compliance with changes of observed seasonal patterns, however, some amount of over and under-estimates are obvious especially for Kabul station. This compliance with in-situ observed patterns was acceptable for daily temporal scale, although AgMERRA was unable to predict some of the fluctuations in probability distribution composition (with the range of 1 °C), especially fot Tmax and Tmin, but fot Tmean the fluctuations simulated well.
Conclusion: According to the results of the study, AgMERRA showed an acceptable potency to simulate the in-situ meteorological data in four major studied stations of Afghanistan. According to the stochastic nature of PRCP, the variable showed the weakest results in daily temporal scale but acceptable in 14-days and monthly. Given the weak coverage of in-situ meteorological data of Afghanistan, AgMERRA could be a valid dataset for producing well scaled spatiotemporal data series to be used in agroclimatic, CC and crop growth modeling studies.]]>
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