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Climate change is having tangible impacts on storm dust events in many parts of the world. Although it is complicated and difficult to distinguish between changes caused by natural and anthropogenic factors, in recent years severe droughts in Iran have led to reduced soil moisture contents and vegetation canopies with the result that local and regional storm dust events have become more frequent. Against this background, this study is assessing the importance of land use types comprising rangelands and both rainfed and irrigated cropping as sources of storm dust in Kermanshah city, Iran, using colour indices and a composite fingerprinting procedure. Colour indices as tracers were measured on 57 samples collected to characterise the potential storm dust sources and eight target storm dust samples fractionated into two particulate size fractions. Composite fingerprints were selected using statistical analysis and a Bayesian un-mixing model was employed to apportion storm dust source contributions. For the, The 28th IUGG General Assembly (IUGG2023) (Berlin 2023)

The identification of the spatial distribution of soil trace-elements and the contribution of different sources to the sediment yield is necessary for a better watershed and river water quality management. Until now, less attention has been paid to comprehensive assessments of sediment sources and soil trace-elements with respect to the suspended sediment production. The present study aimed at modelling the spatial distribution of soil trace-elements, quantifying the sediment sources apportionment and relating the landforms to polluted soils. Different techniques and approaches such as the Nemerow pollution index, machine learning algorithms (Random Forest (RF), generalised boosting methods (GBM), generalised linear models (GLM) and sediment fingerprinting were applied to the Kan watershed. A total of 79 soil samples having different Nemerow index values were considered for spatial modelling. Using statistical methods (Range test, Kruskal-Wallis and discrimination function analysis), an optimal set of tracers was selected. An unmixing model was applied to calculate the relative contribution of landforms for eight rainfall events. The results of the soil trace-element mapping showed that RF had the best performance with an accuracy of 83%. The evaluation of polluted soil areas showed that the landforms 'steep hills' and 'valley' contributed the most with 51% and 27% in the riparian zone, respectively. In addition, these landforms give a high contribution to sediment production in late-winter-spring events (29%) with a GOF (goodness of fit) of 0.65. The landform 'plain' had the highest contribution (28%) in sediment yield with a GOF of 0.72 in early-winter events. This means that the valley and steep hill landforms accelerate the transport of trace-elements across the watershed. Interestingly, the contribution of landforms varies during the year. Overall, the new proposed approach enables to better trace the origin of suspended sediments and trace-elements discharge into the river environment.

The main objective of this study was to investigate the effect of forest road construction on the Soil Organic Carbon Stock (SOCS) in Ziarat Catchment. Therefore, soil samples were collected from five land use types including road construction, cultivated area, channel bank, pasture and forest land and soil organic carbon concentration and bulk density were measured in the samples and SOCS were calculated. The results showed that the forest road construction reduce SOCS. SOC stock was greatest in the forest land use and the total SOC stock under different land uses varied in order forest, pasture, cultivate, channel bank and road construction with 143, 136, 128, 36 and 29 Mg ha −1 , respectively (p< 0.001). Therefore, these results can be useful as a scientific basis for selecting the proper soil erosion control methods as a simple and low-cost approach to mitigate the SOC loss.

Assessment of drought is one of the most important steps in risk management of drought analysis. Drought is mostly the result of a decrease in precipitation in comparison with the mean value and would affect the quantities of soil moisture and water resources. The basis of drought indices is often based on measuring the deviation of precipitation values from long-term mean, during a specific period of time. The standard precipitation index (SPI) can be used for indicating the associated temporal and spatial variations. The aim of this research is the assessment of the characteristics such as intensity, frequency and duration of meteorological drought using SPI with 1, 3, 6, 12 and 24 months time scales in West Azarbaijan Province, Iran. The indices have been computed in various time scales for 38 gauging stations with 32 years record period in the study area and evaluated for the recent drought during 1998-2001. The results indicate that with an increase in return period and time scale, the duration of drought will be increased. Frequency of drought, with an increase in scale, will also be decreased linearly, but their durations show an increase. This index having temporal and spatial variations and is attributed as a suitable tool for analyzing drought for different hydrological purposes.@JASEMKeywords: Meteorological Drought, Standardized Precipitation Index, Drought Management, West Azarbaijan ProvinceJ. Appl. Sci. Environ. Manage. Dec, 2011, Vol. 15 (4) 589 - 596

The objective of this study was to better understand the functional links between soil quality, erosion, geomorphology and land-use. This was done for the Kan catchment of the Tehran province, central Iran. Soil quality was assessed by using the integrated quality index (IQI) and the Nemoro quality index (NQI): this enabled the total and minimum datasets (TDS) to be obtained by using the principal component analysis. Soil erosion was calculated using the revised universal soil loss equation (RUSLE) model using the InVEST software. The calculated erosion rates are very high (on average 7 t ha−1 yr−1) in the region due to the variety of topography, steep slopes and lack of suitable vegetation. The variety of topography and steep slopes are a caused by the high uplift rates. Consequently, the modelled actual erosion rates are in the same order of magnitude as measured, long-term denudation rates (10Be). The erosion rates in the rangeland were higher than in agriculture land and built-up areas and exhibit a positive correlation with elevation and slope angle. The integrated soil quality index produced more plausible results than the NQI. According to the IQI, the soils in the study area mostly have a moderate to low quality. The statistical analyses showed that organic matter and sand play a more important role on the soil quality than all the other soil characteristics. Slope and elevation seem to significantly influence the soil quality. We demonstrated that soil quality can be evaluated precisely enough by using the minimum dataset (which reduces costs and time) and that it is dependent only on a few soil parameters. Soil quality and erosion rates vary strongly in areas having a rough and steep topography and the effect of land-use is partially overshadowed.