JWSS - Journal of Water and Soil Science

Two field experiments were conducted in 1996 at the experimental station, College of Agriculture, Shiraz University at Badjgah. Fourteen cultivars consisting of eight hybrids and six open pollinated cultivars were grown in two randomized complete block designs with four replications.

 The well-watered experiment received water when evaporation reached 65±5 mm from class A evaporation pan.

The water-limited experiment was irrigated in terms of 125±5mm evaporation from class A evaporation pan. Days to flowering, days to physiological maturity, head diameter, stem diameter, number of leaves per plant, plant height, number of filled seeds per head, 1000 seed weight, kernel percentage, unfilled seed percentage, seed yield, oil percentage, oil yield and harvest index were measured.

Most of the traits including seed yield and oil yield showed considerable genotypic and phenotypic variations. Highly significant differences were observed among cultivars. In normal and water stress conditions, the highest seed yield were obtained by Louc and Armavirsky cultivars, respectively. Water stress significantly decreased yield and its components. Furthermore, days to physiological maturity reduced in response to water deficit. However, oil percentage did not differ significantly. Drought resistance indexes were calculated in order to evaluate the response of each cultivar to water deficit. No association was found between yield potential and the stress susceptibility index, suggesting that drought resistance and high yield potential may be combined to improve sunflower cultivars. In addition, it was revealed that selection for height mean productivity and stress tolerance index will improve yield and drought tolerance simultaneously. Among cultivars that were used in this study, Armavirsky, besides having a relatively higher yield, was also drought tolerant.

Topography and land use are among the most important factors affecting the soil formation. Chemical forms of Fe and magnetic susceptibility (χ) are widely used for the evaluation of soil development. This study was conducted in order to determine the effect of these factors on χ. A toposequence was selected in Madvan Plain, Northern Yasouj. Nine soil profiles (paddy and dryland soils) were dug and sampled from diagnostic horizons. Magnetic susceptibility was measured by Bartington Dual Frequency, MS2 Meter at frequencies of 0.46 and 4.6 KHz. Results indicated that less amounts of χ, frequency dependence of χ (χfd%) and CBD extractable Fe (Fed) (3.1, 2.6 and 2.7 times, respectively), and more quantities of oxalate extractable Fe (Feo) and Feo/Fed ratio (5 and 7.2 times, respectively) were measured in paddy soils. The highest value of χ was observed in pedons located on plateau and piedmont plains, and the lowest belonged to those located on river terraces with aquic conditions. Compared to paddy soils, χ enhancement at soil surface was greater (17%) in dryland soils. A positive correlation existed between χ and some soil characteristics such as Fed, clay content and χfd%.

The objective of the current research was to prioritize effective factors in landslide occurrence and its susceptibility zonation using Shannon’s entropy index in North of Tehran metropolitan. To this end, 528 landslide locations were identified using satellite images such as Geoeye (2011-2012), SPOT-5 (2010), and field surveys, and then landslide inventory map was created for the study area in ArcGIS environment. Data layers such as slope degree, slope aspect, plan curvature, altitude, lithology, land use, distance of road, distance of fault, distance of drainage, drainage density, road density, sediment transport index (STI), stream power index (SPI), topographic wetness index (TWI), normalized difference vegetation index (NDVI), surface area ratio (SAR) and topographic position index (TPI) were created and the mentioned maps were digitized in GIS environment. Prioritization of effective factors by Shannon’s entropy index showed that the layers such as land use, lithology, slope degree, stream power index, and NDVI had the most effect on landslide occurrence. However, factors of topographic position index and plan curvature had the least effect. Also, landslide susceptibility zoning by the mentioned model and its accuracy assessment using relative operating characteristics (ROC) curve and 30 percent of landslide locations showed an accuracy of 82.83% with a standard error of 0.0233 in the study area.

Accelerated soil erosion in Iran causes on-site and off-site effects and identifying of sediment sources and determination of their contribution in sediment yield is necessary for effective sediment control strategies in river basin. In spite of increasing sediment fingerprinting studies uncertainty associated with magnetic susceptibility properties has not been fully incorporated in models yet. The objective of this study is determination of the relative contribution of sediment sources using magnetic susceptibility properties (High frequency, Low frequency and Frequency dependence) incorporated in uncertainty mixing model. For this purpose, 25 bed sediment samples were collected from the outlet of drainage basin and outlet of sub-basins and their magnetic susceptibility was measured and calculated. The results of Kruskal–Wallis test and discriminant function analysis showed that magnetic susceptibility properties can be used as optimum set of tracers in the uncertainty mixing model. The results of Bayesian mixing model indicated that mean (uncertainty range) relative contribution of Sparan, Joyband and Boyoukchay are 92 (83.9-94.8), 2.8 (0.2-10.7), 5.7 (0.2- 10.5) percent, respectively. According to these results, the highest amount of sediment yield is related to Sparan sub-basin and these results could be used in soil conservation and management planning.

Landslide susceptibility mapping is essential for land use planning and decision-making especially in the mountainous areas. The main objective of present research is to produce landslide hazard zonation at Sarkhoun basin in Karoon basin using two statistical models such as an index of Shannon’s entropy and weight of evidence and to assess the obtained results. At the first stage, landslide locations were identified in the study area by interpretation of aerial photographs, image sattellites, and from field investigations and then landslide inventory map was created for study area. The landslide conditioning factors such as slope degree, slope aspect, altitude, lithology, land use,distance of road, distance of fault, distance of drainage, topographic wetness index (TWI), Convergence Index, and precipitation were extracted from the spatial database and they were digitized in GIS environment. With integrated variables, landslides were calculated in each variable class and ‎weighted in index of entropy and weight of evidence model. In the last, landslide hazard zonation map ‎were obtained with both of models. The results of landslide susceptibility mapps of both statistical models were indicated more than 70 percent the occurred landslides were located in very high and high zones that about half of the basin area (over 45 percent) constitute. Also, the results of both models together were revealed that land use, has the greatest impact on the occurred landslides. Resolution of the zones, based on the seed cell area index (SCAI) and frequency ratio (FR) were evaluated suitable for both statistical models. Finally, the ROC (receiver operating characteristic) curves for landslide susceptibility maps were drawn and the areas under the curve (AUC) were calculated. The verification results of both models were evaluated very well and showed that the index of entropy model (AUC=89%) performed slightly better than weight of evidence model (AUC=82%).