جستجوی مقالات مرتبط با کلیدواژه « arid regions » در نشریات گروه « آب و خاک »

Droughts are natural events and could lead to declining surface water quality of regional basin. Understanding the complex impacts of drought may help authorities to monitor changes in different regional basin and to make appropriate decision on development of a river basin management plan. In this study 20 years annual precipitation time series from 1994-2013 from 7 synoptic weather stations located in the Halil-Rood basin were analysed using both Standard Precipitation Index (SPI) and Reconnaissance Drought Index (RDI) and then dry (-1.35 to -1.75) and wet years (1/7 to 2.45) were determined by model simulation studies. Several climate based drought indices and remotely sensed based drought indices were used for monitoring and evaluating of drought. The impact of drought on the water quality parameters in the study area was evaluated. Results showed that there was significant relationship between most of the examined water quality parameters (Ca2+, Mg2+, HCO3-, SO42+, Na+, total dissolved solids TDS, SAR) and drought, however there was no significant relationship between water pH and drought. The study indicated that focus on the drought indices might be helpful as a tool in improving surface water resources management under drought condition and may promote sustainable water resources utilization and management in the study area. Also, dividing the Halil-Rood basin into several homogeneous regions is recommended for future studies to prepare a better ground for studying the effect of drought on the quality of water at a regional scale.

Base of soil information for environmental modeling is soil survey and mapping as a way to determine soil distribution patterns, describe and display it to understood and interpreted for different users. Digital soil mapping creates link between classes or soil characteristics and environmental factors affected soil formation and development by using mathematical models which can provide more precise and accurate soil maps and reducing cost of soil survey and mapping projects. This study was done to mapping soil great groups and subgroups by using Random Forest technique in the Hirmand county lands in Sistan plain.
In this study 108 soil profiles were dug on about 60.000 hectares of Hirmand county lands. Sixteen environmental variables were used as estimator for soil mapping including land properties, salinity and vegetation index. After classification of soil profiles to great groups and subgroups, soil classes map provided by using random forest (RF) method. It should be mentioned 80 percent of data was used for model training and 20 percent for independent validation.
Pedological studies showed soils that formed in Sistan plain haven’t high development and most of them are Entisol and Aridisol. Most soil profiles classified as Torrifluvents on great groups and Typic Torrifluvents as subgroups. Also the result of RF showed the lowest estimation error of out of bag (OOB) samples in soil great groups and subgroups were 43.53 and 50.59 respectively. Independent validation results showed the best accuracy obtained for soil great groups and subgroups were 48 and 53 percent respectively. Grooves depth, convergence index, channel network between and salinity in soil great groups and grooves depth, elevation and catchment area in soil subgroups were the most important environmental variables to estimate soil classes.
The results showed most soils are young in the low relief lands in arid regions and these regions have also low soil diversity. Soil digital mapping and random forest technique could be useful for soil classes prediction and soil mapping in this kind of regions.

Climate change especially global warming is the most problem in the 21st century. So investigation variability trend this problem is very important in global, regional and local scale.Newadays numerous general circulation models(GCMs) have been designed to predicat future climat.An outstanding issu of output for regional and local applications is coarse spitial resoluation.To produce accurate predications of future climate variables at the regional and local scale various methods are suggested.Despit many studies this case, ufortunately,there is not a standard method for a specific rogion.Thus it is necessary that accurate predications of these methods are evaluated befor applaying in a certain region.One of th most widspread methods is Statistical DownScaling Model(SDSM).In this research efficiency of SDSM model is evaluated to simulate temperture indexes in Kerman station, instance arid and semi- arid regions.Hence, SDSM is calibrated and validated by using kerman station observ tempertur and national center enviromental predication data.We used mean absolute criterium to evaluate model.After obtaining confidence simulation accuracy. Temperture indexes (mean,absoluate maximmum and minimm temperture)are simulated by using two GCMs(CGCMand HadCM3 under A2 and B2 scenarios)until 2100-year.The result of this study is shown that SDSM model has suitably to simulate temperture indexes also using HadCM3 model data is beter than that of CGCM model. Increasing mean annual temperture on base HadCM3 model in (2010-2039),(2040-2069)and(2070-2100) periods relation to base period (1961-1990) is respectively 1.5,2.8 and 4.5 degree of centigrade in Kerman station.

Due to its continuation and extension in time and space، wind erosion has high destructive potential، especially in arid regions، and its damage to economic resources، especially soil and vegetation، is significant. Therefore، a comprehensive understanding of wind erosion formation، performance، affected areas، and overall effects is essential. The objective of the present study was to present a suitable method for providing wind erosion hazard zoning maps. At first، the role of six effective factors on wind erosion including height changes، geomorphology، stone sensitivity to erosion، soil types، diversity and density of vegetation cover and land use were studied according to the status of the study area. For this purpose، Numerical Taxonomy Method، a rating scale method، was used. In the context of this method، facies units were selected by geomorphological method. Then، erosion intensity and effective index were determined in every unit using Taxonomy Method. Finally، the zoning map was presented in GIS based on Arc View3. 2a. The results showed that sand dune units with plant coverage (SDPC)، bare clay grounds (BCG)، and clay grounds with plant coverage (CGPC)، with the greatest quantitative values of، respectively، 0. 76، 0. 76 and 0. 77 were prone to very intense wind erosion. In the meantime، the quantitative value of wind erosion risk for the entire region was estimated at 0. 52، which indicated high potential of the region for occurrence of wind erosion. Generally، based on the final layer، 15% of the area of Khezrabad basin is prone to high risk of very intense wind erosion and threatens70% of the region with intense wind erosion.

Application of sewage sludge has been considered as an organic fertilizer in arid and semi-arid regions of Iran. This study was conducted to investigate cumulative and residual effects of sewage sludge on soil inorganic fractions and their relation to phosphorus (P) availability. Two levels of application (50 and 100 Mg ha-1) and three consecutive times of sewage sludge application (1, 3 and 5 years) with a control treatment were studied in a randomized complete block split plot design with three replications. Composite soil samples were collected from 0-30 depth at the end of 5th year of application. Increasing the rate and application year of sewage sludge enhanced dicalcium phosphate (Ca2-P), octacalcium phosphate (Ca8-P), apatite (Ca10-P), aluminum phosphate (Al-P), iron phosphate (Fe-P) and available P but decreased occluded P (OC-P). Residual effect of sewage sludge application resulted in increased inorganic fractions in blocks treated for 1 year compared to control. Positive correlations were observed between inorganic P fractions and Olsen P, wheat yield and P uptake (except OC-P). We concluded that inorganic P fractions and P availability increased in sewage sludge amended soil.