JWSS - Journal of Water and Soil Science

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In this research, 5 percent of normal Precipitation Index (PNPI),Deciles of Precipitation(DPI),Rainfall Anomaly Index (RAI), Bahlme & Mooley Drought Index (BMDI) and standardized Precipitation Index (SPI) were used in order to investigate drought in Yazd synoptic station and 31 non synoptic stations all around this province. For this purpose, the present statistical errors were reconstructed via correlation between the stations, after raining data collection from the considered stations. Then, calculation of PNPI, DPI, RAI, BMDI and SPI indexes were calculated on monthly and annual scales. Situation of drought was determined based on the obtained values from calculation of each index according to tables related to the considered indexes in different classes of drought during the statistical period. Then indexes were compared to each other, considering drought given situation for each station. The difference and similarity of each index with other 4 indexes were calculated and investigated. Also after determination of drought situation in each station, given percentage of drought different situations via each Index was determined on annual scales, in 33 study stations. After passing the above mentioned stages, it was found that there was the highest percentage value of similarity between the two indexes RAI & DPI, as both indexes indicated similar situation of hard drought in the stations. These two indexes are considered most efficient to investigate aerology drought. But considering that static indexes are faced with problem on monthly scales and in stations located in drought regions, it is recommended to use‌ SPI & BMDI dynamic indexes whose similarity percentages are acceptable.

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The effects of soil intrinsic properties on soil structural stability were evaluated. Soil samples (33 series) with wide ranges of properties and structural stability were collected from Hamadan province. Two structural stability indices were used: mean weight diameter (MWD) using Yoder method and De Leenheer-De Boodt index (DDI). Wetting pre-treatments (fast wetting to saturation and slow wetting to a matric suction of 30 kPa) were applied before wetting. Linear and multiple regression relations of MWD and DDI with the soil intrinsic properties (organic matter, clay, fine clay, silt, sand, calcium carbonate, EC and pH) were assessed. Results showed that organic matter had the highest impact on the two mentioned indices. Following organic matter, clay, fine clay and calcium carbonate were ranked respectively one after another. Fast wetting caused a higher aggregate break-down, due to its destructive energy, air entrapment, and non-uniform swelling of the soil whereas slow wetting exhibited better differentiation of soils with low structural stability. The findings of this research demonstrated high agreement (R2>75%) between the MWD and DDI, recommended both to be used for evaluating of the aggregate stability in Hamedan province

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Precision farming aims to optimize field-level management by providing information on production rate, crop needs, nutrients, pest/disease control, environmental contamination, timing of field practices, soil organic matter and irrigation. Remote sensing and GIS have made huge impacts on agricultural industry by monitoring and managing agricultural lands. Using vegetation indices have been widely used for quantifying net annual production on different scales. The aim of this study was to find a rapid method with acceptable precision for the identification and classification of agricultural lands under cultivation (wheat and barley, alfalfa and potatoes). We used multi-temporal AWiFS data and applied Boolean logic and unsupervised classification. Results indicated that Boolean logic approach had a higher accuracy and precision in comparison to unsupervised classification, although it is more complicated and time consuming.

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Southern Oscillation Index (SOI) and Sea Surface Temperature (SST) patterns affect rainfall in many parts of the world. This study aimed to investigate the relationship between monthly and seasonal rainfall of Iran versus SOI and Pacific and Indian sea surface temperature. Monthly rainfall data, from 50 synoptic stations with at least 30 years of records up to the end of 2007, were used. Monthly and seasonal time series of each station were divided to several groups by four methods (Average SOI, SOI Phases, Indian SST Phases and Pacific SST Phases) using Rainman software and with regard to 0-3 months lead-time. Significant differences among rainfall groups in each method were assessed by the non-parametric Kruskal-Wallis and Kolmogorov-Smirnov tests, and the significant relationship was validated using Linear Error in Probability Space (LEPS) test. The results showed that SOI during summer (July-September) was related to autumn (October-December) and October rainfall in the west and northwest of Iran and the west Caspian Sea coast. The El Niño (negative) phase was associated with an increase in rainfall and the La Niña (positive) phase was associated with a decrease in rainfall in these regions. Average SOI is a useful index for rainfall forecasting in the above-mentioned areas. However, Indian and Pacific SST phases are not suggested for rainfall forecasting in Iran, duo to weak or non-persistence relationships. In conclusion, Iran rainfall is not limited to SOI, Pacific and Indian SST therefore, Rainman could not be used as an aid to water resources management over a year in Iran. It is suggested that we study the teleconnection between Iran rainfall and other ocean-atmospheric oscillations developing a model similar to Rainman in order to that we investigating the variation in Iran rainfall with aid of other effective ocean-atmospheric indicators

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Soil characteristics are the most powerful factors in desertification phenomenon. The purpose of this study was investigating soil characteristics as indices for evaluating desertification intensity. The most important indicators of the soil that affect desertification were selected in the present study. Soil samples were taken from Segzi desert vicinity located in the east of Isfahan city with surface area of 112,167 ha. Soil indices such as Soil texture, soil gypsum percentage, the content of HCO3-1, electrical conductivity (EC), pH, the percentage of the organic matter, the content of the soil sodium, chloral and sodium absorption ratio (SAR) were selected. All of these indices were calculated on the thirty four soil samples. After ensuring of the normality of the samples by Klomogrov-Smirnov test, the mentioned indices were imported into GIS for delineating soil characteristics maps. To delineate distribution maps of each soil indice, inverse distance weighting and ordinary and discrete Kriging methods were applied, and appropriate method was selected. Each layer was scored based on MEDALUS model, and the final characteristic maps were then generated using soil geometric mean indices. Results showed that the affected areas of the average, severe and very severe classes of desertification were calculated about 66000, 45650 and 517 ha, respectively. The results also revealed that the indices of the organic matter, soil gypsum percentage, electrical conductivity and SAR were the most influential indicators, which affected desertification in the study area.

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The geographical location of Isfahan province has led the province to be at risk of drought. One of the ways to mitigate drought is evaluation and monitoring of drought based on indices that can determine its intensity and permanence in each region. In this research, for drought and trend analysis standard precipitation index and Mann-Kendall test were used, respectively. Also, monthly precipitation time series of Isfahan province was applied to forecast drought from 1970 to 2009. For this purpose, Box and Jenkins modeling approach (1976) was used which has three main steps, namely model identification, parameter estimation, goodness of fit test or time independency and normal test of residual. The results showed that most of the stations in Isfahan province were faced with severe drought in the year 2000 and this situation was repeated one more time in 2008. Also, the results brought forth multiplicative models in all the stations. ARIMA (1,0,0) (0,1,1) showed the highest correlations between control and forecast data in Isfahan, Meime and Ardestan stations, and the model ARIMA (0,0,1) (0,1,1) displayed the highest correlation between control and forecasted data in Naein, Freydoonshahr, Khansar and Natanz. These models were selected as the best models through which the amount of precipitation was predicted till 2015. The trend of forecast data across Isfahan province showed that in most months the trend is not significant.

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Organic carbon pools and carbon lability directly affect soil biological, physical and chemical characteristics. Besides, capacity of self-organization of soil is related to the organic carbon pools. Sand size fraction (> 50 µm) organic matter is more labile than silt+clay size fraction organic matter. Assessment of this organic carbon variation can be a suitable index to determine soil quality. The aim of present study was to evaluate the impact of land use change on particle size fractions of organic carbon and carbon pool index. In September 2010, soil samples were collected from the three major land use types including wetlands around the lake, wetlands converted to wheat, and alfalfa cultivations. Soil samples were collected from the 0-30, 30-60 and 60-90-cm depths in each of land use. According to the results of particle size fractionation of organic carbon in 0-30-cm layer, the highest and lowest amounts of sand size fraction organic carbon were obtained in wetland (67.01 g.C.kg-1soil) and wheat land use (24.57 g.C.kg-1soil), respectively. Land use change from wetland to alfalfa and wheat caused a decrease of silt+clay size fraction organic carbon in 0-30-cm by 48.39 and 45.14 t.C.h^-1, respectively. In the 30-60-cm layer of cultivated land, soil organic carbon storage in silt+clay size particle was more than sand size fraction organic carbon. Results showed that carbon pool index in alfalfa, and wheat land was decreased by 50 and 60% compared to wetland, respectively. And carbon management index in alfalfa and wheat was declined by 44.90% and 66.70%, respectively.

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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.

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This study aimed to evaluate the performance of TM satellite data acquired in June 2009 to map soil salinity in southeast of Isfahan province. Ground salinity data (EC) was collected within 9 pixels, covering an area of approximately 8100 m2 using stratified random sampling technique at 53 sample sites. Spectral indices including TM bands, BI, SI1, SI2 and SI3, PC1, PC2, PC3 and also multiple linear regression modeling and maximum likelihood classification techniques were applied to the geometrically corrected image. Results of regression analysis showed that the TM band 4 had the strongest relationship with EC data (R2=0.48) and also the relationship of the modeling image using TM 3, TM 4, TM5 and PC3 was significant at the 99% confidence level. The accuracy assessment of the stratified TM4 and modeling image into five classes including 0-4, 4-20, 20-60, 60-100 and EC>100 ds/m indicated that there was more than 86% agreement with the field measurements of EC data. Therefore, it can be concluded that the discretely classified salinity maps have higher accuracy than regression methods for identifying broad areas of saline soils, and can be used as appropriate tools to manage and combat soil salinization.

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Management of organic and inorganic treatments may have positive or negative effects on soil quality, plant growth and human nutrition. The objectives of this study were to determine the effects of organic and inorganic zinc fertilizer application on soil quality indicators and wheat yield. This research was conducted at Agricultural Research Station Roudasht, Isfahan, Iran. Sewage sludge and cow manure (5 and 10 t/ha), ash rubber (1 t/ha), powder rubber (200 kg/ha), ZnSO4 (40 kg/ha) were applied and wheat was cultivated. Soil samples were collected at tilling and harvest stages. After taking samples and measurements of the soil parameters, we determined the critical limits for each category and class rating for the each soil parameters, and the soil quality index was calculated. The results showed sewage sludge and rubber ash were significantly effective in increasing soil bioavailable Zn compared to other treatments. Application of sewage sludge and cow manure at 10 ton/ha improved soil quality. The expanded soil quality index can help better understand the effect of fertilizers on soil. A positive and significant relationship between soil quality indicators and Zn uptake and wheat yields was also observed. Our results indicate that addition of 10 t/ha sewage sludge as fertilizer can significantly improve soil quality, supplying the necessary amount of Zn for wheat growth.

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Considering soil compaction problem in sugarcane fields due to using heavy harvester and haulout equipment under unsuitable moisture conditions, this research aims to assess soil compaction in sugarcane fields located in Da'balKhazaei Plantation unitofSugarcane Development and By-product Company, Ahvaz. Undisturbed soil samples from the furrow (wheel tracks) were collected for measuring soil water content and bulk density. Considering the changes in soil texture of sugarcane fields, for expressing the degree of soilcompactness, in addition to soil bulk density (BD), relative bulk density (BD divided by reference BD) was also determined. The change in soil mechanical resistance with depth was determined by a cone penetrometer. Results showed that most of soil BD values measured in the sugarcane fields were in the range of small root development scale (high limitation). Comparingthe calculated RBD values with optimum value (0.85), it was observed that most of the values were higher than the optimum values recommended for root growth. This shows excessivesoil compaction in the sugarcane fields. The values of cone indices measured in soil profiles indicated that most of the values were higher than either limiting (2 MPa) or critical (3 MPa) values for root growth. Therefore, for improving soil physical fertility and achieving sustainability in crop production, management of farm machinery traffic in sugarcane fields, especially at the harvest time, needs to be reconsidered.

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The Palmer Drought Severity Index (PDSI), which uses hydrometeorological variables to solve a simple water balance equation in the soil and considers the drought or wet conditions as dynamic phenomena, is used for the assessment of drought conditions in many parts of the world. The main goal of this study was to assess the PDSI based on its original assumptions, its regionalized status, using the outputs of already calibrated and validated SWAT model in central regions of Iran. The PDSI was assessed through five methods: 1) original Palmer Index without calibration in which the climate coefficients and the severity equation were derived for Kansas and central Iowa 2) original Palmer Index in which the coefficients of severity equations were adjusted 3) the Palmer Index with the calibration of equations in central areas of Iran 4) the Palmer Index using the soil moisture and potential evapotranspiration from SWAT model and 5) the Palmer Index using the soil moisture, potential evapotranspiration and runoff from SWAT model. The evaluation was conducted for 17 major basins covering the entire country with a monthly time step for the period 1990-2002. Then, using all five methods, the severity of the drought for 160 sub basins located in central Iran was calculated and evaluated. The results of this study indicated that method 4 provides more acceptable results. Also, the results of this research showed these methods clearly demonstrated (1992) as the wettest year and (2001) as the driest year. The approach used in this study is applicable to regional calibration of Palmer Index and the outputs of other hydrological models.

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The aim of this paper is to adapt a water quality index for individual samples and to compare the results with that of the original GIS-based approach. Thirteen water quality parameters observed in 97 wells from the Shahrekord aquifer were used. In GIS-based method, quality parameters maps are difference-normalized, ranked and GWQI map is drawn. In derived method, observations from individual wells were separately and similarly treated to obtain WQI for each well. Both GWQI maps displayed similar trends and were highly correlated (R=0.91). While the minimum and mean GWQI for both methods were identical (respectively 81 and 84) the derived method estimated the maximum GWQI slightly lower (7%) and showed up to 6% difference in water quality class coverage. Overall, the derived method GWQI is more correlated with observations and performs better than the GIS-based method, and therefore, can be used for determining the overall quality of individual water samples and without the requirement of samples being spatially distributed.

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Drought is an extended period of low precipitation which resulted in injuries to consumers of water and reducing their performance, especially in agriculture. Different indices have already been proposed for evaluating drought, based on one of the varieties of meteorological, hydrological and agricultural droughts, but no indices has been identified yet, encompassing all factors. This study has been carried out to assess existing indices for drought monitoring and proposing an integrated index including main factors of drought and is applied to the Zayandehrood river basin as study area, because of its sensitive situation in the central Iran plateau. An integrated index includes various drought factors such as meteorological, hydrological, agricultural, socio - economical and environmental factors. In designing of this integrated index, a combination of static and dynamic layers has been used. Static layers include land use, slope and soil type. Dynamic layers include precipitation, evaporation, temperature, surface water storage, groundwater levels position, and environmental needs. All these layers are analyzed in GIS software and drought zoning maps is prepared. Results showed that based on values of integrated index, water year 1371-72 was a wet year and water year 1378-79 was the most critical, in terms of drought.

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Drought is a climatic anomaly that associates with a significant decrease (lack) of precipitation and water resources availability, which spreads on vast temporal and spatial scales, and significantly affects various aspects of life and environment. One of the most common methods of drought assessing and monitoring is calculating drought indices (DIs). Drought areal and temporal extent and its severity are determined by these indices. In this study, an aggregate drought index (Hydro-Meteorological) has been developed for the assessment of hydrological and meteorological droughts in Sarbaz river basin located in southeastern of Iran. The Aggregate Drought Index (ADI) comprehensively considers all physical forms of drought (meteorological, hydrological, and agricultural) through selection of variables that are related to each drought type. In this case, monthly values of Stream flow Drought Index (SDI) and Standardized Precipitation Index (SPI) indicators were used for four similar reference periods with principle component analysis and aggregate hydro-meteorological index was defined based on its first component. The study time span was set between 1981-82 to 2010-11, which begins of October in Iran. Results based on the aggregate drought index (ADI) revealed that a long period of hydro-meteorological drought occurred from 1999-2000 to 2005/06 in southeast of Iran, in which, 2003/04 water year has been extremely a drought year. The ADI methodology provides a clear, objective approach for describing the intensity of drought. This index is appropriately able to represent the behavior of Hydro-Meteorological droughts and recommended as an integrated index for assessing and monitoring of regional droughts. Finally, different states of hydro-meteorological drought have been extracted based on conventional regional thresholds, and have been modeled by Markov chain. This made the estimation of drought state transition frequency possible, and made the prediction of next drought state time more real. State transition frequency matrices, are the main instruments for predicting drought states in real time. Results of validation tests and conforming the predicted results with real data indicate that predicting hydrological drought state transitions in the study area using Markov chain method is valid.

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Constant use of treated wastewater (TWW) for irrigation over long periods may cause buildup of heavy metals up to toxic levels for plants, animals, and entails environmental hazards in different aspects. The aim of this study was to assess the effect of using a deep emitter installation on lowering the potential heavy metal accumulation in soil and wheat grain, and health risk under drip irrigation with treated municipal wastewater. A field experiment was conducted according to a split block design with two treatments (fresh and wastewater) and three sub treatments (0, 15 and 30 cm depth of emitters) in four replicates in Esfahan, Iran. Soil samples were collected before planting (initial value) and after harvesting (final value) in each year. Elemental concentrations (Cu, Zn, Cd, Pb, Cr, and Ni) in soil and grain were determined using an atomic absorption spectrophotometer. A pollution load index (PLI) showed that there was not substantial buildup of heavy metals in the wastewater-irrigated soils compared to the freshwater-irrigated soils. Cu, Pb, Cr and Zn concentrations in wheat grain were within permissible EPA limits, but concentrations of Cr was above the safe limits of EPA. In addition, concentrations of Ni in wheat grain were several folds higher than EPA standards. A health risk index (HRI) which is usually adopted to assess the health risk to hazard materials in foods showed values higher than 1 for Cd and Cu, whereas children might also be exposed to health risk of Cd, Cu and Cr. Based on aforementioned results, it can be concluded that the depth of emitter in drip irrigation does not play a significant role in the accumulation of heavy metals from TWW in our sandy loam soil.

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The main purpose of this study is investigation of hydraulic properties in drip irrigation tape. In this study, 10 types of drip irrigation tape were tested, and the effect of 4 temperatures of water, 13, 23, 33 and 43 °C, was investigated according to the standard ISO 9261 and ISO IRISI. Initially all experiments were performed in standard temperature (23°C) in order to obtain qualitative evaluation indexes of tapes. The results obtained were as follows: According to the Cv, 8 models of tapes were ranked as good and 2 models as medium. According to the difference between the actual and nominal flow rates, 3 models were ranked as good, 3 models as medium, 3 models were acceptable and 2 models were unacceptable. According to the EU, 9 models were ranked as excellent and T3 was ranked as good. According to the UC, UC of all models was more than 70% and their flow rate variation follows normal distribution. According to q_var, flow rate changes in 3 models were acceptable, 2 models were ranked as good and 5 models were unacceptable.
 

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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%).

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Soil water repellency can affect several soil properties such as aggregate stability. Soil texture and organic matter are two main internal factors responsible for the variability of soil water repellency. Major sources of organic matter in soil include plant residues, and exudates of plant roots and soil microorganisms. Tall fescue (Festuca arundinacea Schreb.) as an important cool-season perennial forage grass is usually infected by a fungal endophyte (Epichloë coenophiala) which often enhances resistance to biotic and abiotic stresses as well as altering the litter decomposition rate and soil properties. In this study, the effects of endophyte-infected (E+) and endophyte-free (E−) tall fescue residues (in three different levels of 0, 1 and 2%) on soil organic carbon, basal microbial respiration, water-dispersible clay and water repellency index (determined by intrinsic sorptivity method) were investigated in four texturally-different soils in the laboratory. E+ and E− tall fescue residues were completely mixed with moist soil samples and then were incubated at 25 °C. During two months of incubation period, the amended soil samples were subjected to 10 wetting and drying cycles and then, the above-mentioned soil properties were measured. The results indicated that soil organic carbon and water-dispersible clay were greater, while basal soil respiration and repellency index were lower in fine-textured soils. Water repellency index was increased by production of hydrophobic substances (for the rate of 1%) and was reduced by induced greater soil porosity (for the rate of 2%). Presence of endophyte in plant residues had no significant effect on water sorptivity, ethanol sorptivity and water repellency index; nevertheless, E+ residues increased soil organic carbon and decreased water-dispersible clay significantly. Overall, it is concluded that tall fescue residues, especially those with E+, can improve soil physical quality due to improving soil organic carbon storage and water repellency index and decreasing water-dispersible clay (as an index for aggregate instability). These E+ species and the residues have great potential to be used in sustainable soil conservational managements.
 

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