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Soil aggregates refers to groups of soil particles which attach to each other stronger than neighbour particles. Aggregate stability shows the capability and strength of soil aggregates to tolerate breakup when disruptive stresses and destructive forces via mechanical agricultural operation such as tillage and water or wind erosion are applied. Wet aggregate stability shows how well a soil can withstand raindrop impact and water erosion, while size distribution of dry aggregates can be used to predict resistance to abrasion and wind erosion. Aggregate stability changes can act as the first indicators of recovery or degradation of soils. Aggregate stability is an indicator of organic matter content, biological activity, and nutrient cycling in soil. Generally, in small aggregates (< 0.25 mm), the particles are bound by older and more stable forms of organic matter. Microbial decomposition of fresh organic matter releases products (that are less stable) that bind small aggregates into large aggregates (> 2-5 mm). Although, there is not a unique acceptable methodology that serves and applies the entire world up to now, aggregate stability has been introduced as a soil physical quality indicator. Difficulties remain when comparison of aggregate stability from different methodologies are done. The objective of the present study was to assess appropriate and satisfactory aggregate stability tests that enable to distinguish the soil physical quality condition of both arid and moist medium textured soils. A total of 120 soil samples which contained 60 wetland samples from Guilan province with a very humid climate, average annual rainfall of 1285 mm, and average annual temperature of 16°C, and 60 samples from Fars province with dry climate, average rainfall of 225 mm, and the average annual temperature of 27°C were provided. Soil sampling was performed from surface layer (0-20 cm). Each 10 soil samples with similar texture were mixed and one soil sample for each texture was finally obtained. After air drying and sieving, soil texture and organic carbon were determined by pipette and oxidation methods, respectively. Also, undisturbed samples were taken using metal cylinders from surface layer of 5-15 cm for determination of soil saturation coefficient, soil moisture curve, and soil bulk density. Also, in order to determine the aggregate stability, Kemper and Rosenau, de Leenheer and de Boodt, as well as Le Bissonnais were used. Among different tested methods, wet sieving using the well known fast wetting methods of Kemper & Rosenau and of Le Bissonnais presented similar results in both climates. The mean weight diameter value of both methods for assessing aggregate stability can be considered as a dependable indicator of soil structure status for comparing soils. These aggregate stability tests were in correspondence with only one out of the eight soil physical quality indicators when the entire soils were used. It was concluded that the aggregate stability should be used judiciously and in accordance with other indicators for an overall assessing of the soil physical quality condition. The great differences in the estimation of aggregate stability between KRSW and LB2 with other methods confirm that aggregate stability increases with increasing soil moisture content. This involves reducing the amount of air condensed, which results in the reduction of compressive forces on the aggregates during rapid wetting. But the lack of similarity between the KRSW and LB2 methods in terms of MWD suggests that the results of these two methods are not comparable to dry and wet soils. The difference in aggregate size distribution from all three treatments of LB method was higher in dry areas than wet areas. Only dry soils based on LB (LB1 and LB3 treatments based on MWD) (P <0.05) are comparable. In dry soils, the LB3 method is very efficient. This method involves the use of ethanol that protects the aggregate structure against dryness stresses. The lack of similarity between the MWD and other soil quality indicators describes the complexity of the soil structure, which is dependent on the location. It seems that SOC can be considered as an indicator with high correlation with the aggregate sustainability index of LB and KRFW methods, at least in the studied medium-textured soils. Since only a soil quality index (SOC) had a similar trend to the sustainability index derived from these two methods (LB1 and KRFW), it can be concluded that aggregate stability should be judged and recognized correctly, along with other used soil physical indicators for a general assessment of the conditions. In case of arid land soils, efficiency of pre-wetted methods of Kemper and Rosenau and of Le Bissonnais as well as pre-wetted Le Bissonnais with mechanical slaking and shaking were similar. If a simple and rapid analysis of the structure status is needed, single tests such as fast wetted Kemper and Rosenau and Le Bissonnais can be used.

Objective and Plants such as rice need to provide their nutrient elements by using fertilizers for much more production in surface unit. For this purpose, it is essential to recognize macro-elements amount in soils and prepare their ideal maps. Soil CEC is a vital indicator of soil fertility quality and pollutant sequestration capacity as well as characteristics of N, P, K as macro-elements. This research was conducted with the aim of estimating and mapping the desired properties in order to obtain the results and maps that could be used in optimum management of fertilizer use and control of groundwater contaminants. The study area with an area of about 40,000 hectares is one of the central areas of Guilan province. 247 soil samples were collected from depth 0-30cm. The values of CEC, total nitrogen, phosphorus and potassium in soil samples and their descriptive statistics were determined. The normal distribution of data was analyzed using Kolmogrov-Smirnov test. Data that did not have normal distribution was converted to normal with appropriate transformations. Before the use of interpolation method, trend and anisotropy analysis were performed. Semi-variograms were calculated using ordinary Kriging and maps were plotted. The amount of K and P varied from 78 to 269.5 mgkg-1 and from 2.3 to 56 mgkg-1, respectively. The average contents of K and P were 192.03 and 16.51 mgkg-1, respectively. The amount of total N changed from 0.02% to 0.8%, which its average was 0.26%. Also, the content of CEC varied from 10.6 to 47.1 cmolckg-1 and its average was 26.72 cmolckg-1. The fitted model was based on semi-variograms of total nitrogen was exponential and those of phosphorus, potassium, and CEC were spherical. Determination coefficient (R2) of models had high value and the nugget effect/threshold is less than 25%. These characteristics showed that semi-variograms of properties had strong spatial structure. After specifying the semi-variograms, a map of their values was prepared using ordinary Kriging. Evaluation criteria values R2, RMSE and MAE derived for K 0.79, 27.84 and 0.106, P 0.73, 8.17 and 4.63, total nitrogen 0.72, 0.059 and 0.025 and CEC 0.76, 4.06 and 3.09. Criteria values R2, RMSE and MAE showed that accuracy of prepared maps was ideal. With attention to interpolation maps, spatial distribution of K was good in western, north-western, and central area of studied region. K deficiency was concentrated in southern and north-eastern areas. The amounts of P and total N were suitable in central and northern areas which their deficiencies were observed in southern area. With regard to soil nitrogen and P maps, usage of more than optimum limit of nitrate and phosphorus fertilizers causes ground waters pollution. Potash fertilizers application in land with high CEC results its fixation, too. Precise attention to CEC map and on-time fertilizer application can solve this problem. Therefore, accurate notice to different amounts of these parameters in maps, critical and optimum limits can well manage fertilizers application, prevents additional costs to farmer and pollution of ground water resources. Since the investigation of N, P, K, and CEC is important for determination of soil fertility quality, so, the maps of spatial distribution of mentioned parameters were prepared via determination of experimental semi-variogram with strong spatial structure using kriging. The criteria of R2, RMSE and MAE showed that maps accuracy was acceptable. Spatial distribution of K was good in western, north-western, and central area of studied region. K deficiency was almost concentrated in southern and north-eastern areas. The contents of P and total N were suitable in central and northern areas which their deficiencies were observed in southern area