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x> +0.5, and from among the 250 months examined the anomalies (at least 20 stations from 30 stations), 57 cases with anomalies among whole months were selected in the study period, and then by the Pearson correlation method, a relation was calculated between the 17 selected atmospheric-oceanic indicators and the air temperature. The indicators used in this study are the most important indicators introduced in international studies. Also, by using multivariate regression, optimal parameters and regression functions are presented in order to explain and predict the relationship between indices and temperature anomalies in the warm season in the whole of Iran.
3. Results and Discussion
The air temperature of Iran shows a significant relationship with the teleconnection indexes. According to the tests performed in selective stations, in general, NINO3, NINO1+2, NINO3.4, NINO4, GBI, CAR, PACEFIC WARM POOL and GLOBAL MEAN TEMP indexes were have a significant correlation in 90% confidence level. In terms of time in calculations with monthly synchronous steps at selected stations, the best indexes are GBI, NINO1 + 2, NINO3 and NINO3.4, with correlations of 0.8, -0.8, -0.57 and -0.4, respectively. In terms of a previous step, the GBI, NINO1+2 and NINO3 indexes had the highest correlation values of 0.8, -0.8 and -0.5, respectively. The temporal pattern of the impact of some indicators, such as NINO, which was mostly strong and inversely in the same month, was directly and significantly in the two and three months earlier. Based on the results obtained from the multivariate modeling, the correlation between the selected teleconnection indexes such as GLOBAL MEAN TEMP, GBI, NINO 1+2 with thermal anomalies in the warm season of Iran are 0.94; as the best temperature predictions, and at the same time a month earlier, the NINO3 index was added to the above-mentioned indexes. In general, the indexes of NINO3-4, NINO3, NINO1+2, NINO4, and GBI are the best atmospheric and oceanographic indicators that predict Iran's temperature anomalies.
4. Conclusion
According to numerical correlation analysis between the selective indexes and the temperature anomalies of the selective stations in the warm season in Iran showed that NINO3, NINO1 + 2, NINO3.4, NINO4, GBI and GLOBAL MEAN TEMPERATURE indexes are the most important oceanic-atmospheric predictors. Also, in this paper, linear regression functions for the relationship between indices and monthly temperature anomalies are presented, which can explain and predict the temperature changes in Iran. The correctness of these functions is confirmed by using the actual and modeled data (estimating R correlation values, RMSE and MBE values) with an acceptable error rate. It should be noted as long as the intervals of predicting are prolonged, apparently the importance of atmospheric indexes is reduced and contradictory the number and reliability of ocean indexes are increased. In total, using the above mentioned indices and using multivariate regression method in each step of time (simultaneously, one, two and three months earlier), the linear regression function for the relationship between indexes and monthly temperature anomalies of Iran has been presented, which by using it the Iran's temperature changes can be predicted finally. It should be noted that the functions obtained here are to predict the average temperature of selected stations in Iran, and therefore for each station the calculations must be made individually.]]>
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p. 85−107
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0.05) increased in the CSB+P and P treatments over time. CSB+P significantly reduced bulk density from 1.46 (1st yr) to 1.32 (3rd yr) enhancing soil moisture content. The crescent shaped bund was designed as the adaptive micro-catchment runoff harvesting system (MCRHS) and measured within treatments plots. This technique has a lower soil and embankment movement than earthy or stone dams which can be built perpendicularly in the flow of runoff. Besides, it is arranged in staggered rows along the natural contour of the land with the open end facing uphill. Consequently, these bunds slow down runoff enabling the harvested water to be used in an effective way. This is particularly useful in increasing the soil moisture, especially when precipitation is scarce.
4. Conclusion
It is concluded that CSB+P (first treatment) can be considered as the possible adaptation approach for combating Zagros forest mortality induced by drought stress and climate change. This technique is a possible measure for runoff harvesting and thereby enhancement of soil moisture during dry season. However, proper and holistic management of forests are needed to curtail forest dieback event. Furthermore, Zagros forest soil should be protected from disturbance factors in terms of tillage practice, machinery traffic, grazing, logging and charcoal extraction. In our experience, runoff harvesting through micro-catchment technique, forest preservation and sustaining SOC are crucial short term measures for combating forest mortality in Zagros regions.]]>
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p. 163−179
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p. 181−197
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