مجله سامانه های سطوح آبگیر باران
سال هشتم شماره 3 (پیاپی 26، پاییز 1399)

Rainfall-runoff from urban areas is one of the available water resources, which is wasted due to lack of attention and proper management. Besides, urban runoff excess of drains capacity causing many problems including inundation and urban environmental pollution. Therefore, harvesting this runoff can provide a part of the required water in urban areas, and also reduce flood and urban inundation, thus rainwater harvesting systems can play an important role in this regard. The purpose of this study is identification areas with inundation potential for urban runoff harvesting using the support vector machine model. For this purpose, 46 flood points were collected in Imam Ali (AS) town in Mashhad, and 32 points were randomly selected for the model training plus 14 points for the model validation. The predicting variables such as elevation, slope, drainage density, distance from drainage channels, and land use were used to implement the support vector machine model. The results showed that high and very high potential classes for runoff collection include 11.63% and 4.49% of the total area, respectively. The central and north-eastern parts have more potential for urban runoff harvesting, while the western, eastern, and southern regions have the lowest potential for runoff harvesting. Also, the evaluation performance of the support vector machine model was 87.8% in the training stage and 80% in the validation stage, which indicates that the performance of the model is "very good".

Rain simulators are suitable tools for research related to the process of erosion and runoff. However, it is possible to use these simulators on other topics as well. For example, in designing the rainwater catchment systems such as micro-catchments for planting trees on slopes, curve pits in pastures, and determining the size of the water collection pond, knowledge of runoff coefficient and volume of collected water are essential. For this purpose, in a national study, several tons of soil from four selected rainfed lands including Faraghi (Golestan province), Sararoud (Kermanshah province), Kouheen (Qazvin province), and Sarab neniz (Kohgilouyeh and Boyer-Ahmad province) were transferred to the Rainfall Simulation and Erosion Laboratory of the Soil Conservation and Watershed Management Research Institute and after preparation by standard methods, the soils were subjected to a heavy rainfall of 64 mm per hour on three slopes of 6, 12 and 25% for 30 minutes. Such rainfall is unlikely to occur and can be used to design rainwater catchment systems. Outlet flow during the experiment was measured at intervals of 1 to 3 minutes (17 times in total) and the total runoff volume, and then the runoff coefficient and soil infiltration capacity were calculated according to the rainfall volume. In addition, soil infiltration capacity was calculated about 3 to 6 cm per hour. The runoff coefficient of these soils (except Sararoud soil with high infiltration) was calculated between 50 to 90%. According to the characteristics of the soil, soil structure, specific weight, and the amount of organic matter are the factors that determine the infiltration capacity. The volume of runoff (except Sararoud soil) in the most severe events was estimated between 15 to 30 liters per square meter, which is used in the design of the rainwater catchment systems. For soil with high infiltration, it is recommended to compact the soil or use other methods to reduce the infiltration and increase the runoff coefficient.

Although flood maps based on the deterministic approach play an important role in minimizing flood losses, there is considerable uncertainty in calculating the level of water inundation. Roughness is a key parameter in water surface elevation. Since roughness is not easily measurable and is estimated based on experimental and laboratory methods, it introduces a significant degree of uncertainty into the model. Therefore, in this paper, a probabilistic framework based on the Monte Carlo simulation approach is used to analyze the uncertainty of the roughness coefficient using the HEC-RAS model. In this framework, a computational module in Visual Basic language was introduced to communicate with the HECRASController to automatically run 84,000 Monte Carlo simulations within 7.5 km of the Karde River. In each performance, 1000 Monte Carlo simulations were performed in 84 separate cross-sections based on the Manning roughness probability distribution and the results of roughness uncertainty at water elevation were presented at 99%, 95%, 50%, 5%, and 1% confidence levels. The results indicate a significant effect of roughness on the water surface elevation uncertainty at 90% confidence level so that changes in water surface elevation in many cross-sections reach more than 1 meter. Comparing the cross-sections with the minimum and maximum uncertainty bands, show that the cross-sections with higher lateral gradients have more uncertainty and the V-shaped cross-sections with the lower lateral gradients have fewer uncertainty bands. Also, the results of sensitivity analysis to select the optimal number of simulations indicate that the bandwidth of uncertainty is not affected by the number of simulations of more than 1000 runs. The presented results based on the deterministic approach and increasing the reliability and improving the performance of the model based on the uncertainty of roughness in the Karde River can be used in the design of rainwater catchment.

Excessive use of water and soil resources, especially in arid and semi-arid regions, increases soil erosion, destructive storms, the occurrence of dust, and desertification. Therefore, to prevent environmental problems in these areas, it is necessary to efficiently manage water and soil resources in arid and semi-arid regions. Rainwater catchment systems are one of the management and operational methods, which can be used in arid and semi-arid areas. This study investigates the effect of rainwater catchment systems on vegetation characteristics of the Tasuki region of Sistan. In this research, the ​​rainwater catchment area was selected as the study area, and the adjacent area was selected as the control treatment. Due to the distribution of plant species in the ​​rainwater catchment area, the size of the plots was selected in a way to have more accuracy for plant cover and shrub species evaluation. For this purpose, two linear transects each with a length of 250 meters was placed in each research unit, then every 50 meters, a 3 × 3-meter plot was arranged, and a 1 × 1-meter plot was placed inside them to measure the canopy percentage, forage production amount, litter percentage, number of rootstocks and bare soil surface. Forage was harvested by hand and after drying, was weighed with a digital scale with an accuracy of 0.01 g. The outcomes were analyzed using SPSS statistical software. The results showed that Alhagi camelorum, Aeluropus littoralis, Tamarix stricta, Haloxylon aphylum, Hammada salicornica species have grown in the study area, but only Hammada salicornica distributed in the control area. Statistical analysis showed that all the characteristics of the control treatment and rainwater catchment area were significantly different at the one percent significance level, which indicates the proper performance of this system in improving vegetation cover of the area.

Today, the world is facing several problems, including population growth, urbanization, food demand increasing, depletion of water resources, and environmental degradation. "Urban agriculture" as part of urban activities is an opportunity to make positive changes in the world food system and produce quality food. Urban agriculture is a new solution to deal with environmental, social, and economic problems. It is obvious that with the expansion of cities and the growth of the urban population, the demand for food will increase. Agriculture has always been the main supplier of human food and creates food security for society. In addition to its advantages and disadvantages, urban agriculture also has its challenges. Cities are the main centers for achieving the goals of sustainable development, and therefore the production of quality food in the smallest place and in the shortest time is very important. By producing food on rooftops, backyards, and suitable urban areas and by applying proper management, the food needs of citizens can be answered and the quality of the urban environment can be maintained. It also provides an opportunity for low-income citizens to achieve food security by creating jobs and reducing household food costs. The present study is based on a descriptive and review method using library studies.

Studying climate change and its effect on the intensity and frequency of drought can help the proper use of water resources and adaptation to the destructive effects of the drought phenomenon in the future decades. In recent decades, rising global temperatures have disturbed the planetchr('39')s climate balance and caused widespread climate change in most parts of the world. This research tries to assess climate change in 2021-2050 and its impact on drought in the Latian dam. For this purpose, after assessing the efficiency of the SDSM model in simulation of the base period (1992-2019), the downscaling output of the HadGEM model under RCP4.5, and RCP8.5 scenarios was performed to estimate maximum and minimum temperature and precipitation based on Standardized Precipitation Evapotranspiration Index. The outcomes show an increase of 0.85 to 1.54°C in the average monthly temperature under the RCP8.5 scenario and an increase of 0.25 to 1.45°C under the RCP4.5 scenario. Furthermore, the results show a decrease of 31 to 100 mm in average annual precipitation. The highest decrease in precipitation is in February. Also, the annual analysis of the SPEI showed that 65% of the years are normal, therefore, the Latian dam will not face an increase in the frequency of drought in the period 2021-2050, but it is expected that precipitation events mostly will occur in the warm season.