Prediction of Temperature Using SDSM Multiple Linear Models (Case Study: Hoor al-Azim and Miangaran Wetlands)

Introduction: One of the consequences of the climate change in Khuzestan Province is thedrying up of a large part of the wetlands of this province, including Miangaran and Hoor al-Azim, which has caused dust storms in recent years. In this regard, this research aims to predictclimate changes in the area of Miangaran and Hoor al-Azim wetlands by using the SDSMstatistical microscale model based on HadCM3 B2 and A2 climate scenarios. Considering thespecific conditions of the region and the fact that few studies have been done regardingtemperature change in these areas, knowing the state of temperature change can help bettermanagement of resources, especially water resources management.Material and Methods: These parameters include the average sea level pressure, thegeopotential height of the surface of 850 hectopascals and the average temperature at a heightof two meters. For this purpose, by using the daily data of average temperature, minimum andmaximum temperature in the synoptic stations of Izeh and Bostan as the closest stations to Hooral-Azim and Miangaran wetlands in the periods of 2010-2039, 2040-2069 and 2070-2099,predictions were made and then a comparison was made with the base period (1961-1990). Theselected predictors in climate parameters were chosen using NCEP observational large-scaleparameters and SDSM software. These parameters included average sea level pressure, surfacegeopotential height of 850 hectopascals, and average temperature of two meters above thesurface. Also, with scenarios A2 and B2 until the year 2099, the prediction of the return periodof extreme climatic events in the HadCM3 model was done.Results and Discussion: The results of the simulation of the HadCM3 model along withobservational data from the Izeh station, modeled annual average temperature data was 18.47°Cand for the Bostan station, modeled annual data average temperature was 19.10°C. Both stationshad a higher average temperature in the base period, and the maximum temperature in theMiangaran wetland was much higher than Hoor al-Azim wetland in the base period. The resultsshowed that in both stations in scenario A2, the average temperature had significant cycles withreturn periods of 1.2 years and the lowest significant cycles for the two stations were in returnperiods of 2.3 and 1.3 years, respectively. In scenario B2, the average temperature in twostations has significant cycles with return periods of 7.5 years and the lowest significant cyclewith a return period of 1.2 years. The results of examining the cycles in the studied areasindicate that in the A2 scenario, certain climatic conditions in the area have short-term returnperiods. One year was obtained in both scenarios, which indicates a wider range of the returnperiod and a higher probability of extreme temperature events in the B2 scenario. In thecomparison of the two stations, it can be seen that in scenario A2, the average temperature ofthe Miangaran wetland is 1.02 °C and the Hoor al-Azim wetland is 1.08 °C.Conclusion: The results of the data analysis in the future observation and simulation periodswith scenarios B2 and A2 showed an increase in the mean, minimum, and maximum averagetemperature in the future simulation periods compared to the base period in Izeh and Bostanstations. In Bostan station, the average minimum and maximum annual temperature alsoincreased in the third period compared to the base period. In both scenarios, due to the increasein temperature, the drying process of both wetlands will continue

Assessment of Two Soil Fertility Indexes to Evaluate Paddy Fields for Rice Cultivation

Assessing soil fertility is essential to help identify strategies with less environmental impact in order to achieve more sustainable agricultural systems. The main objective of this research was to assess two soil fertility evaluation approaches in paddy fields for rice cultivation, in order to develop a user-friendly and credible soil fertility index (SFI). The Square-Root method was used as a parametric approach, while the Joint Fuzzy Membership functions as a fuzzy method with adapted criteria definition tables, were used to compute SFI. Results indicated that both of the methods determined the major soil limiting factors for rice cultivation clearly, and soil fertility maps established using GIS (Geographic Information System) could be helpful for decision makers. The coefficients of determination (R2) for the linear regression between the two SFI values and rice yields were relatively high (0.63 and 0.61, respectively). Additionally, the two SFI were significantly correlated to each other (r = 0.68, p < 0.05). The study results demonstrated that both of the methods provide reliable and valuable information. Compared to the fuzzy method, the procedure of the parametric method is easier but may be expensive and time-consuming. However, the fuzzy method, with carefully chosen indicators, can adequately evaluate soil fertility and provide useful information for decision making

Point estimation of water retention in smectitic soils

Soil hydraulic properties are needed for the modelling of water and substance movement in unsaturated soils. Their direct measurements are difficult, time consuming and expensive. Therefore, these properties need to be estimated using indirect methods. The objective of this study is to evaluate the effect of microaggregates on the estimation of soil water retention. In this study, 74 disturbed and undisturbed soil samples were taken from Guilan province, northern Iran. Bulk density; water content at matric suctions of 5, 25, 33, 100 and 1500 kPa; and microaggregate-size distribution (MASD) were measured. The fractal parameters of the MASD were calculated and used to estimate water content. Estimation of water contents at different matric suctions was improved significantly by adding the fractal parameters of the MASD to the pedotransfer functions. The most improvement occurred for θ1500 prediction with relative improvements of 12·5% and 45·2% for training and testing, respectively. It can be due to the influence of soil microstructure on water retention at high matric suctions. Smectite clay with high specific surface area affects soil structure and microaggregates and, consequently, water retention. Using the MASD would be useful in the estimation of soil water content in smectitic soils. </jats:p