Journal of Range and Watershed Managment
Year:2012 | Volume:65 | Issue:2|Papers Count:11

Iran is located in dry belt of the earth and always involved with drought in different sections. Drought has already caused many losses to natural plant cover, agriculture and human society. For drought monitoring, we can use some drought indecies. In this research, the Standard Index of Annual Precipitation)SIAP), Sandardized Precipitation Index (SPI) and Palmer Drought Severity Index (PDSI) were used for assessment of drought effects on rangeland plant production. The research area is located in Qom province that contains eight rangeland sites. Plant production and soil factors were measured in rangeland readiness period from 1997-1998 to 2005-2006 annualy. Regression techniques were used between drought indices and total production and also production of different vegetation forms in seven time scales (early March to late July (growth season) and early February to late July (growth season and the previous month), March to June, March to May, March to April and March (start of growth season). The best drought index was then selected based on the highest correlation coefficient and lowest standard error. The result showed that the best drought indices in Qom rangelands are SPI-3, PDSI, SPI-24 and SPI-6, respectively. Also the most significant time step was resulted growth season and specially early stage of growth season.

Assessment process of vegetation cover by remote-sensing images should be based on understanding of the vegetation indices. Vegetation indices are widely used for assessing and monitoring ecological variables such as vegetation cover, above-ground biomass and leaf area index. The aim of the present research was to study of the ASTER data capabilities to estimate the vegetation cover percentage on Ghareh Aghaj Watershed as well as selecting proper vegetation indices for vegetation cover procurement. Various preprocessing, including image rectification was applied with geo-referencing of the image to a registered image with RMSE of 0.5 pixel. The atmospheric and topographic corrections were applied using subtraction of dark object's method and the Lambert method accordingly. Image processing, including vegetation indices and supervised classification were employed to produce the vegetation cover map. Field data collection was started on June 2008 on 8962.25 ha and prolonged about two months. Various vegetation types were sampled using the stratified random sampling method. Sixty random sampling points were selected, and the vegetation cover percentage was estimated with estimation of checking method. Digital data and the Indices maps were used as independent data and the field data as dependent variables. The resulted models were processed on, and the resulted images were categorized in five classes. Finally, the produced maps were controlled for their accuracy. The results confirmed that the NDVI vegetation indices were significantly correlated with field cover data (P£0.01), the strongest relationships explaining relatively 78% of the variance in the field measurements (R2=0.38). Other vegetation indices were not significantly related to vegetation cover percentage of the field data. The total validity and the Kappa coefficient for this map are 68.5% and 72.4%. On these sites, the R square was exceeded to 85%. Most of the produced maps had higher accuracies with NDVI indices, and their Kappa was very high. During the growing seasons, the most rangeland products changes, belongs to class 5 and 2 in the NDVI and SAVI indices map. The outcoming results of this study prove that the ASTER data estimates the plant production very well. Through this tool, one can monitor the hay production that is very useful for resources management as well as decision making for logic rangeland utilization. Generally introduced indices, provided accurate quantitative estimation of the parameters. Therefore, it is possible to estimate cover and production as important factors for rangeland monitoring using ASTER data.

Carbon sequestration potential of three species including Agropyron elengatum, Stipa barbata and Artemisia aucheri was evaluated in parts of a semi-arid rangeland in this study. After determination and selecting key areas as study sites, sampling from vegetation and soil, based on randomized systematic method, was done and 90 plant and 45 soil samples were taken, respectively. Shooting and rooting organs of the species were separated from each other after transfer to the laboratory and carbon sequestration coefficient of plant organs was determined with combustion method.Then carbon sequestration coefficient of different species, organs and soil under these species were analyzed. The results showed that carbon sequestration rate between studied three species, had significantly statistical difference (p<%5) while Artemisia aucheri had the highest carbon sequestration rate in the region. Also carbon sequestration between organs (roots, stems and leaves) of three species showed significantly statistical difference (p<%5). Investigation of soil carbon storage showed that Artemisia aucher stores 29.445 t/ha carbon in the soil which is higher than other studied species.

Proper judgment on rangeland state needs appropriate sampling plan and accurately estimation of plant characteristics. Sample shape and size are critical issues in vegetation measurement. Thus, decision on appropriate quadrate shape that enables us to determine several parameters accurately and timely would increase sampling efficiency. Several criterias including accuracy, perimeter/area ratio, spent time for measurement, usability and ease of use as well as three variance and or covariance dependent criterias were used to decide on proper plot size to determine multi-variables of rangelands, i.e. different life forms composition, sand and gravels, litter and bare soil coverage. Different quadrate sizes including 1×1, 1×2, 1.4×1.4, 0.4×4, 2×2, 2.8×2.8 and 4×4m were established along a 640 m long transect within a homogeneous vegetation type. Within each quadrate, species canopy cover, litter, sand and gravel coverage in addition to spent time for measurement were estimated and recorded. Life forms composition in each plot was calculated by summing each life form species. An Analytical Hierarchical Process (AHP) was performed to find out appropriate sampling quadrate from aforementioned quadrate sizes. Moreover, 5 repeats of nested quadrates from 25×25 cm to 16×16 m were established to determine sampling minimal area. Efficacy of minimal area method with this multi criteria method that synchronously incorporated a number of criteria was compared. Results showed that accuracy of multi-variable estimation raises with increasing sampling quadrate size (area) until reaches a 4 square meter quadrate (2×2 m) but after that more or less stabilized. Also, on a constant sample size (area), efficiency of square plots is higher than rectangles for estimation of objective variables. AHP results showed that based on accuracy, time, perimeter/area ratio, and usability and ease of application criteria a 4 square meter (i.e., 2×2 m) plot is the most appropriate alternative for synchronic measurement of multi-variables. Repeated nested plots showed at least a 32×32 m plot for minimal area that is not applicable in practice. We can conclude that 1) minimal area that is estimated using nested plots are not necessarily the most appropriate minimal quadrate size in heterogeneous vegetations for multi-variable measurement, and 2) by considering multi criteria and choosing the best option (alternative) from different quadrates, researcher will increase sampling efficiency.

For planning the grazing of rangeland according to difference in body weight and different energy requirements should determine forage requirement of animal unit. In the other hand, daily need of animal in rangeland depends on the quantity and quality of intake forage composition. For this purpose selected part of the rangeland of Fereidunshahr in Isfahan province was classified to vegetation types. In each type of all plant species about 500 grams at flowering stage were collected. Nitrogen (N) and acid detergent fiber (ADF) were measured through chemical analysis. Crude protein, ADF, dry matter digestibility and metabolizable energy either 3 replicates were assessed in the laboratory as indicators of forage quality. The Lori sheep race is user dominant Animal unit. In order to determine the animal unit body weight, from 3 existing herds within 11 unit management with dominant Animal from this race, 10 three and 10 four Dry adult ewes(main structure of the herd), 5 three and 5 four years old rams and 6 month old lambs randomly selected and were weighed in two period. Weighing operation performance once before grazing beginning (first may) and once after the end of grazing season (first September). In conclusion 45 kg body weight as animal unit was calculated and livestock rations of animal requirement in maintenance condition and grazing in rangeland (0.7 times of keeping in a stable) calculated using the MAFF equation. The result showed that animal requirement based on forage quality at flowering stage was 1.09 kg that for grazing session (30% reduction of forage quality) is 1/58 kg in day. Because there are difference in structure of vegetation types and metabolism energy so a permanent quantity of dry forage cannot specify as basic of computation the daily need.

More than 30% of Iran's land is formed from mountainous areas. So each year, landslides cause damages to structures, residential areas and forests, creating sedimentation, muddy floods and finally deposit the sediments in reservoir dams. Therefore, for preventing of this damages and expressing the sensitivity rate of hillslopes, landslide hazard zonation is considered in prone areas. The purpose of this study is to determine the optimal structure of artificial neural network with different numbers of input factors for the landslide hazard zonation in the Haraz Watershed. First, the number of optimal epochs was determined to prevent network overlearning with trial and error method. Then, 14 neurons were determined in the hidden layer. Finally, the number of neurons was changed from 1 to 9 in the input layer. According to the obtained results, with increasing the number of neurons in the input layer, efficiency of Artificial Neural Network improved for landslide susceptibility mapping. In this research, nine neurons in the input layer, 14 neurons in the hidden layer and one neuron in the output layer were selected as the optimal structure. Root Mean Square Error and Descriptive Coefficient (R2) were equal to 0.051 and 0.962, respectively and the accuracy of landslide hazard zonation map was equal to 92.3%. Meanwhile, the results showed that about 35.14, 26.73, 14.59, 9.88, and 13.63 percent of all studied areas are located in stable, low, moderate, high and extremely hazardous areas, respectively.

Plant cover is one of the most important factors affecting infiltration rate of water into the soil and decreasing runoff. Distribution of plants in arid and semi-arid areas is almost patchy and form different patterns. One of the fascinating patterns is ring-shaped growth pattern. Ring patterns of varying size are formed by clonally reproducing grasses, sedges and even shrubs growing in resource-limited (water and nutrient) environments. Study on the role of ring pattern in infiltration rate is lacking. In this study infiltration rate was compared between ring patterns formed by Iris songarica and Scripoides holoschoenus and soil without plant cover (bare soil). Infiltration rate was measured by double ring in different time interval until infiltration was constant. Infiltration models efficiency were analyzed by calculation Nash-Sutcliffe coefficient. Result from paired T test analysis showed that infiltration rate was significantly different between two plants and also with bare soil (p<0.01). The results showed the cumulative infiltration rate for Iris, Scripoides and bare soil were 56.5±2.8, 89.5±5.4 and 42.7±1.3mm, respectively. On the other hand, infiltration rate for Iris, Scripoides and bare soil were 39.6±2.0, 54±2.7 and 27.6±1.4 mm/hr, respectively. The root system and dead parts of plants in center of the rings were responsible for high infiltration rate in two plants. It is concluded that formation of ring is an adaptive characteristic of plant to use rainfall in one hand and in another hand it would increase groundwater level. Nash Sutcliffe ranges showed Green-Ampt and Horton models are in acceptable levels of performance for predicting infiltration rate of vegetal ring patterns and bare soil.

The term hydrological drought is applied to represent low water levels in streams, reservoirs and lakes as well as a low groundwater level. Base flow index (BFI) as one of low flow indices gives the ratio of base flow to total flow and investigates basin’s ability to store and release of water in drought periods. The objectives of this study were to determine BFI and to validate this index in drought studies of Sefidrood Drainage Basin. To view of this, first three homogenous regions were identified based on the threshold level using cluster analysis. Then, daily BFI was calculated in 28 gauging stations of the homogenous regions. The results showed that the regional mean of BFI with value of 0.65 (SD=0.19) is stable during long-period data. BFI ranged between 0.17 and 0.86 and also based on the 25, 50 and 75 percentiles, river flow regime in the study area is divided into four categories that show more than 50 percent of the catchments in the study area have low or unstable regime. So it would be hard that the catchments able to provide river flow during drought periods. Therefore the results of this study can be used in assessment of groundwater recharge, water supply system, irrigation management, and hydrological drought monitoring as well as regional modeling of water resources storage and hydrological drought in ungauged areas.

The research was carried out to find the effects of Haloxylon aphyllum plantation on soil properties in Abardej region of Varamin located in Tehran province. For this purpose, field survey was performed in planted site with saxaul and adjacent control site (without vegetation). Soil sampling was done based on randomized-systematic method. Three linear transects with a distance of 100 m from each other were considered and soil samples were taken from 0-20 and 20-80 cm depths along the transects crossing H. aphyllum individuals. Five H. aphyllum individuals were determined along each transect, so that a total number of 30 samples were gathered from the planted site. Also, 30 samples were taken from the control site. Soil texture, pH, EC, lime, gypsum, organic matter, K, Na, Ca, Mg, Cl and HCO3 were determined at the laboratory. T test was used to analyze the data and the results showed that although Haloxylon planting has had some effects on soil characteristics but appropirate management in establishment period of the mentioned plant could be resulted in positive changes in the soil. Subsequently, H. aphyllum will act as a pioneer plant in desert regions to provide better condition for presence of some other suitable plants.