نشریه پژوهش های آبخیزداری
پیاپی 83 (تابستان 1388)

During the time، landcover and associated landuse patterns are changing very fast and the human factors play a major role in such drastic changes. Scientists have formerly attempted to identify the landuse altering processes and related environmental impacts. In the past decades، researchers have generally examined dissimilar sort of observations taking from the field operations and also arial photos for detection of different kind of changes which occurred by human actions or natural process. Nowadays، satellite images could be accurately processed، as an advanced technique in remote sensing، to determine the environment changes in a particular object of study between two or more time periods. In current study، it was primary viewed as an important process for monitoring of Qazvin Plain landuse changes and latest but very fast industrial and urban developments to provide quantitative analysis of the spatial variation of landcovers in the area of interest. Accordingly، some image processing techniques such as: A supervised classification and its different algorithms specifically: Maximum likelihood، methods were utilized to evaluate landuse changes in the study area. All these methods were performed using Landsat TM and ETM+ data for 1987 and 2002 to detect spatially physical extension of the industrial and residential areas. Overall results have indicated that about 19. 86 percent of landuse patterns have been changed through decreasing on pasture، dry-farming and orchard landuses in responding to the increasing of residential and industrial landcovers. In order to evaluate some associated environmental impacts in the region an arbitrary damage index was introduced and results were categorized into four different categories to inventor that the human processes at work can be more fully understood by applying new approached remote sensing technology. Final models indicate that more than 18 thousand hectares of landuse patterns could be recognized as destructive changes in the region.

Considering arid and semiarid climatic conditions in Iran، the runoff generated from rainfall is one of the main sources of water supply demands for agricultural، industrial and domestic uses. Depending upon watersheds’ characteristics and weather conditions، a substantial part of precipitation may be changed into runoff. The knowledge about the discharge and volume of the runoff generated by rainfalls، especially in unguaged catchments، plays an important role in water resources management planning. In the absence of sufficient data recorded from the real events، use of rainfall simulators in the field and laboratory may be recommended to simulate runoff generation process in different conditions of soils، vegetation cover، slope and rainfalls. In this research، a rainfall simulator was used to investigate the effect of vegetation cover density and soil moisture on runoff values. During this study، the rainfalls with intensities of 24. 5 and 32 mm/h on 145 experimental plots in Taleghan basin were generated and the respective amounts of runoff were measured. Based on the obtained results، correlation matrix confirmed the visual interpretation of the dissipation graphs achieved from the investigated independent and dependent variables. The vegetation cover density was found the most effective variable، affecting the runoff discharge in the two simulated rainfall intensities. Percentage of vegetation cover in rainfall intensities of 24. 5 and 32 mm/h was correlated with runoff value with the coefficients of -0. 903 and 0. 872، respectively at significant level of 0. 01. The two regression relations were also developed for predicting runoff values in different conditions in the range of investigated independent variables.

Instantaneous unit hydrograph is one of the methods that could be used for estimation of flood event hydrograph. In ungaged basins، its application needs estimation of storage coefficient (k) and number of reservoirs (n). In this research، in order to investigate relationship between IUH’s parameters and basin characteristics، at first hydrograph and hyetograph of 5-9 flood events from 6 basins with different climate collected and then IUH’s parameters calculated for each event using moment methods. Multiple regression analysis between IUH’s parameters، basin characteristics and some of rainfall and flow characteristics showed that area and excess rainfall and ratio of mean stream length to basin slope are effective in n and k and are significant in 95%. The mentioned relationship is of linear regression and could be applied in other basin with similar characteristics.

Regarding the value of potential evapotranspiration as an important factor in water resources studies and suitability techniques of geostatistical methods، the present study has been investigated. For this purpose، all stations existed in the Salt Lake watershed were considered، and 37 stations with data collection period longer than 15 years and suitable spatial distribution were selected for the analysis. Three methods of ordinary kriging، cokriging and moving average using inverse and linear distance with powers of 1 to 3 were then applied for analyzing annual and monthly evapotranspiration data by using GS+ geostatistical software. The results showed that all methods except moving average through linear application perform equally well owing to low mean absolute error and mean bias. The precise comparison of results also showed that the cokriging and weighing moving average through inverse distance with power of 2 are the best methods for the analysis of data belong to September and October، and June، respectively، while the kriging method is the best performed model for other months and annual evapotranspiration data. According to the results obtained through analysis of variogram model، spherical and exponential، and linear models are supposed as the best models for monthly and annual data analysis، respectively. The results of the analysis also showed that the optimal distance between meteorological stations is some 40 km in the study area.

Seed and productivity are two major factors to be considered when exotic species are going to be introduced. In a split plot The effect of seed source was investigated in laboratory on germination and vigour traits of Quercus brantii Lindl. acorn. The acorns were collected from 4 forest habitats (seed sources) in southern Zagros (provinces of Kohkilouyeh-Bouyer Ahmad، and Fars)، located in elevations of 850، 1100، 1500 and 2100 m a. s. l. and examined in incubator (25 c، 8 hours radiation) as completely randomized design with four replications. The results of the 30-day period revealed that seed source significantly affected germination and vigor characteristics of acorns (p > 0. 01)، whereas germination، germination rate، root length، vigor index، dry masses of root، shoot and plant were lower in high elevation seed source than in middle and low elevation ones. Correlation of seed origin with mean time of germination was significantly positive (p> 0. 01)، and with other seed traits was significantly negative (p > 0. 01). Since the germination، germination rate، shoot length and plant dry mass are considered as assessment criteria for seed vigor index، it can be suggested that low and middle elevation seed sources are more proper.

This study was carried out to investigate relationships between plant biodiversity and environmental factors in the plant communities of arid ecosystems in Zirkouh of Qaen. In this study، after reorganization of the plant communities، diversity، richness and evenness indices were determined in each community. Within each sample، one profile was dug and soil samples being taken at 0-20cm and 20-100cm depths. Physical-chemical characteristics were determined are texture، lime، organic matter، soil moisture content، saturation moisture، EC and pH. In total، 51 species representing 33 genera and 17 families were identified in this study. Phanerophytes (51. 9 %) were the most abundant life form. Pearson correlation analysis indicated that soil texture، slope، elevation and annual mean precipitation were the most important environmental factors that were positively correlated with species richness and diversity. Soil moisture content and EC were the main factors correlated with species diversity negatively. Species evenness was significant positively correlated with sand، slope and elevation.

In last decades، CO2 has become one of the most important glasshouse gases in which increased its concentrations in atmosphere and followed by global warming. The global warming may have negative impacts on the environment and natural ecosystems. Leniency of decreasing atmospheric carbon dioxide concentrations could be possible via carbon sequestration in biomass and soil organic matter of rangelands ecosystems in Iran and all around the world. Astragalus rangelands covering about 17 million hectare (10%) of Iran territory so could play much important role in carbon sequestration. In order to investigate the role and potential of Astragalus rangelands in carbon sequestration، a study was carried out in a key rangeland area covered by Astragalus brachycalex- Agropyron sp. in Gholestankoh of Khansar. The content of carbon in aboveground and underground biomass، litter carbon and soil organic carbon were determined. The results showed that the total carbon sequestration was 94. 90 ton/hectare and 94. 66 % of total carbon sequestration was soil organic carbon. The results of biomass carbon distribution showed that the carbon content in aerial biomass was higher than underground biomass. Correlation and stepwise regression analyses revealed that the content of carbon sequestration was positively related to Astragalus height and volume، aerial and underground biomass، total biomass، litter amount and soil organic carbon (SOC) content. It was concluded that the Astragalus rangelands have a tremendous potential to sequester carbon and the soil is the most important sink for organic carbon storage in Gholestankoh of Khansar rangeland.

One of the most important event in hydrology and flood management is a daily flow predication water different characteristic. There are several methods for estimating amount river discharge. One of these methods is nonlinear mathematic model of neural network. Artificial neural network is a useful technique which allows the user to detect nonlinear complex interaction between output and input data without considering natural phenomena. In addition، due to spiral changes in precipitation، complexity is great. Artificial neural network is a flexible method which helps us to distinguish nonlinear relationship between input and output data. The aim of this research was to investigate application of ANN in prediction of daily discharge. Then، estimated data of this method were compared with estimated data of regression method algorithm was used in ANN was Back Propagation and function was sigmoid results showed that estimation of ANN was accurate that regression method. Determination Coefficient between data estimated with ANN and observed data was 62. 94 percent and Residual Mean Square Error (RMSE) and Mean Absolute Error (MAE) of estimated data of this method were 11. 88، 3. 7 respectively. Thus، the neural network model is recommended because its structure is simple، the speed of presses is high and the required data are available.

Suspended sediment load constituted the principal part of sediment yield in rivers، and custom methods were estimating sediment yield less than real sediment. The purpose of this study was assistant accuracy and precision method customs for estimate sediment yield instudied watershed. In this basis، six different methods were used، that integrated of three rating curve linear، multilinear and mean value with two mean daily and duration flow in Ilam Dam watershed. For selecting the suitable model is used of mean absolute error (MAE) index، next the rating curve with minimum error in integrate with daily was selected as a suitable method. Such as at during 40 daily of concentration sediment flood and based flows were sampling and determination real sediment yield. In next stage real sediment with sediment estimate models were compared. The results conducted that، there were significant differences between methods sediment estimation. The rating curve by mean value in compound with daily flow discharge was selected as a suitable method. The method was able to estimate 56 percent of real sediment load، but by using of flood hydrograph sediment load increased to 83 percent. In order word، using of flood hydrograph in flood days، in compared with mean daily discharge، it was increased sediment up to 2. 73 times. Such as، 96 percent of sediment at duration flood and 4 percent at base flow were delivered. In the based، increase precision sediment hydrological models are important. To accomplish this، increase sampling of sediment at duration floods and use of flood hydrograph in estimate sediment yield are proposed.

Classification and provision of desertification intensity map، as an efficient tool، has an important role in evaluation of environmental capability and prevention of desertification and reclamation of degradation lands. So far، different models and methods have been proposed in local، national، and international scales، such as Medalus method، Iranian classification of desertification (ICD) and etc. Investigation of mentioned models shows that these models have some deficiencies such as exotic and qualitative indices and expertise mistake. Therefore، Taxonomy Model has developed as base of the desertification assessment model. The model has developed in connection with four principles: a) Natural resources evaluation and Comprehensive knowledge of effective desertification indices، b) determination of terrain mapping units (TMU)، c) Classification of criterion with uniform and similar scale and finally classification and provision of desertification intensity map. This paper investigates the abilities of Modify Numerical Taxonomy model (MNT) to assess lands sensitivity to desertification. and was applied in Khezr Abad region، with 78180 ha area. Results show that MNT model has high ability to assess desertification risk and provision of desertification intensity map. Weighted average of the quantitative value of desertification intensity was estimated at 0. 74 for all the study area (intense class of desertification risk). Investigation of weighted average of the quantitative values of human and natural desertification benchmarks shows prevailing of natural benchmarks over human factors، so that weighted average of natural benchmarks have been assessed at 0. 79 (very intense class of desertification risk) and weighted average of human benchmarks have been assessed at 0. 37 (moderate class of desertification).