Watershed Management Research
Year:2018 | Volume:31 | Issue:120 |Papers Count:7

Due to widespread and continuous drought in the Iranian Plateau and environmental problems in the neighboring countries during the recent decades, we should find a new approach to combat dust and other environmental problems in the southern cities in our country in the future. An approach in this field is an extension of green spaces in accordance with the bio-climatic and watershed properties, and current facilities in any area. Localizing urban green landscape is necessary for the urban sustainable development. Localization and development of the established green space was not desirable due to the expansion of cities, incorrect positioning and lack of attention to standards. In this article, we evaluate the status of the existing urban green space per capita based on the environmental and urban development. Through the combined hierarchical model and the GIS functions, and considering the proximity, we discussed the locations for establishment of the green space. We developed a green space map in terms of the appropriateness of the place for establishing a new green space based on the proximity criteria.

The amount of country's water erosion is estimated at a rate of 976 million t. yr-1 by Erosion Potential Method (EPM) based on the national erosion map prepared at the Soil Conservation and Watershed Management Research Institute. This map is suitable for identifying the most sensitive areas to erosion in each region, but the estimated values of the model need calibration, which was estimated based onthe observed sediment yield data of 276 watersheds. The minimum and maximum annual observed sediment yields were 4 and 5591 t. km-2, and estimated by the model was 31 and 2946 t. km-2, respectively. Correction ratio in the eight homogeneous regions was between 0. 57 to 1. 43 by dividing the median of the observed sediment yields to the corresponding estimates in the studied watersheds. These ratios then were used to improve the erosion values for homogeneous regions between 1063 and 130 t. km-2. yr-1, belonging to the Oman Sea (Region 8) and the internal desert (Region 6) basins, respectively. The annual erosion of the country was estimated to be million 895 t. yr-1. The(5. 5 t. ha-1. yr-1), with the highest and lowest contribution, respectively to the Region 8 (33%) and the Region 1 or Caspian Sea coastal basins (2. 5%). It was also found that the observed specific sediment yield had a positive correlation with an increasing area unlike the expectation, with its probable reasons have been explained in the paper.

Precipitation is the most important climatic factor, particularly in dry lands and its regime characteristics is affected by the change in climate. The precipitation regime is a result of physical, spatial and temporal interactions. The seasonality index (SI) specifies the distribution of monthly rainfall over the year and evaluates the seasonal variations of the rainfall regime. The present study was conducted to determine the precipitation regime and to detect the trend of precipitation SI at the central part of the Province of Ardabil. The rainfall data of 24 stations were collected for the 1989– 2012 period. Descriptive statistics of monthly precipitation data were presented both graphically and statistically, and the spatial-temporal variations were estimated using the SI and coefficient of variation (CV). The trend of precipitation SI at different rain gauge stations was determined using the Mann-Kendall test. The results showed that the highest CV belonged to the Sad-Ghorichay and Lay Stations (65 and 63%), and the lowest was related to the Shamsir Khani Station (36%). Based on the precipitation SI of monthly data, two main regimes were determined: a short dry-season (SI= 0. 2– 0. 3), and a wet-season having the SI value of 0. 6. The results of the Mann-Kendall test showed that most stations had either negative or positive trends in the precipitation SI. The increasing trend in the study area was more than the decreasing trend; only in some stations was the trend statistically significant. Also, assessing the CV of precipitation data showed that the uniformity of monthly precipitation values had decreased during the study period. Increasing the CV and precipitation SI indicate a change in precipitation regime; consequently, an increase in the severity of possible droughts in the study area.

Soil freezing depth is an important parameter in the management of soil water availability in agriculture and horticulture. The purpose of this study was to investigate the effect of global warming and climate change on the freezing depth by using different scenarios on the Malayer Plain, which is the center of grape and raisin production in the country. Daily minimum and maximum air temperatures, sunshine hours, and precipitation data were collected from the Malayer Synoptic Station from 1995 to 2013 and used to simulate the near future climate using the HADCM3 and LARS-WG models based on the optimistic, pessimistic, and moderate scenarios. Performances of these models were evaluated by comparing observation and simulation data using the R2, NSE, RMSE, and MAE indices. The results showed that these models have the necessary efficiency to predict the production of daily data in the region. The air freezing index was estimated by using the Norwegian, Finnish, and American methods based on the mean daily air temperature. Soil freezing depth was estimated by the McKeown and Standard model based on the soil texture at different depths and air temperatures. Annual precipitation, maximum and minimum temperatures will rise under the three scenarios A1B, A2, and B1. The air temperature will increase in winter more than the other seasons, while the absolute value of minimum temperature changes will be higher than that of the maximum temperature. The RSME and CRM indicators in the base and future periods indicate that the Norwegian method, and more, than that the Finnish method, are suitable for estimating the soil freezing depth (at the 5% level) in this semi-arid and mountainous Zagros Region. Application of this method overestimates a deepe freezing depth for the future. Due to the climate change, the depth of freezing will be reduced by the end of 2030 in this important agricultural plain.

The present research attempts to develop a new model. This model considers various indicators with different aspects or criteria of land degradation and desertification, namely natural and human, and trend of degradation for finding areas with higher rate of degradation, and measuring the probability of its occurrence of worse case in these areas. Two areas in the northeast (Masjed Soleiman) and southeast (Omidieh) of the Khuzestan Province were selected as the study areas. These two areas were selected because of their differences in the climatic conditions. The final land degradation risk map was produced by overlaying all three natural, human and trend of degradation types compared with the present state of degradation using the GIS software. Furthermore, the areas under risk were classified to subclasses with different levels of probability level to show a statistical picture of risk in the future. In this method the percentage of the risk probability is evaluated according to the trend and potential of degradation and the emphasis was on the trend of degradation against its potential. More over, the proposed model is named Risk Assessment of Land Degradation (RALDE). A comparison of risk assessment in both areas based on the weighted average indicates that the risk of degradation in the human, natural, trend, present state and finally in land degradation risk in the Omidieh zone (all factors with a weighted average of more than 2. 5) with an arid and warm climate is more hazardous than that of the Masjed Soleiman zone (only two factors natural & current status with a weighted average more than 2. 5) with a semi humid and moderate climate. This study indicated that the arid and warm climate of Khuzestan Province is more conducive to land degradation.

Water and soil are the most important natural resources of every country. As soil is a vital resource for food production and environmental regulation, its deterioration affects the human wellbeing. This research was carried out with the aim of assessing the effect of land use on runoff and sediment production in the Khangah Sorkh Watershed in Urmia. Two slopes of 13 – 0 and 25 – 13 percentage gradient were selected from the DEM map of the region considering the requirements for the setting of rainfall simulator. Also, by investigating the intensity-duration-frequency of the rainfall of the region, two intensities of 40 and 50 mm/h were selected, corresponding to the return periods of 50 and 100 years, respectively. Two cropped fields and two grass-covered rangeland were selected randomly and the rainfall simulation was conducted on each of them for 15 minutes per experiment using the factorial design. The results showed that there was no significant difference in runoff production in the grassland, but there was a significant difference in its sediment production. There was a significant difference between the different levels of slope gradient and the rainfall intensity in the runoff production in the cropland, but there was no significant difference in the sediment production. There was no interaction between the rainfall intensity and slope gradient in either of the land use systems at the 5% confidence level. However, both the volume of the runoff and the rate of erosion were higher for the cropland.

The conventional methods for actual evapotranspiration (ETa) estimating is not sufficiently accurate due to the point based nature of meteorological data and the difficulties related to the plant coefficient (Kc) estimation. The true rate of ET from a basin is an important factor of hydrological cycle and in the water balance equation and accounts for a huge part of out-flow of a basin or any other scale. In this study, the ET values were calculated in the region of Kelestan located in the northwest of Shiraz. The SEBS evapotranspiration model was applied and evaluated by using the Landsat 8 satellite images (nine images) and the meteorological data collected at the Kelestan Station for the period 2015– 2017. Results were compared to the FAO Penman-Monteith equation to verify the accuracy of this model in the region of Kelestan. The radiation sources required for the SEBS model were produced by the R. sun module in Grass-GIS. Other remote sensing data were calculated in the Ilwis software environment. The results of evapotranspiration obtained from the SEBS model in comparison with the mentioned equation showed a correlation coefficient of 0. 999, which is statistically significant. Variations of the ETa for different landuses were within a reasonable range. The production of reliable data from evapotranspiration is one of the prominent advantages of using this model for application in hydrologic research of the basin.