WATERSHED ENGINEERING AND MANAGEMENT
Year:2017 | Volume:8 | Issue:4 |Papers Count:10

In this study, SWAT model was used for simulating soil erosion and sediment transport in Gharesou Watershed, Golestan Province and for identifying and prioritizing critical areas of soil erosion. After model calibration, validation and uncertainty analysis using semi-automatic SUFI-2 method, the outputs of the calibrated model were used for assessing spatial pattern of soil erosion and sediment. For this purpose, four indices including: load per unit area index, concentration index, load index and total index were defined and analyzed based on the model outputs. The results indicated that, despite lack and uncertainty of available data, SWAT model performance in simulating soil erosion and sediment transport in Gharesou watershed is quite acceptable. During calibration, the simulated monthly sediment loads matched the observed values with a Nash-Sutcliffe coefficient of 0. 24 and PBIAS of-17%. The values for validation period were 0. 2 and-12. 1% respectively, indicating the model’ s weakness in simulating sediment dynamics and its capability in predicting average sediment load. Assessing spatial pattern of erosion and sediment indices showed that, in general, critical sub-watersheds based on load per unit area index are located in upstream areas of watershed while sensitive sub-watersheds in terms of sediment concentration are situated in the middle part of the watershed, and sensitive sub-watersheds with respect to sediment load are in downstream. Suitable conservation practices were recommended for each zone based on their ecohydrological conditions. The outputs of this study can help experts and managers in planning of management practices for the watershed.

Most of drought assessment systems are largely based on rainfall data. Although the short period of data, poor quality of rainfall measurement network and low-dense distribution of stations reduce the ability of detecting drought spatial patterns. Therefore, it is obligatory to detect climate data sources, which would get rid of this problem, then to be used as an alternative option. Accordingly, in this study for monitoring drought in West Frontier Basin (including the Ilam, Kermanshah, Kurdistan and Lorestan provinces), using meteorological data (including 30 climatology and synoptic stations), to assess monthly data satellite TRMM (3B43). Drought indicators using SPI index for time scales of three, six, nine and 12 months in the period of 12 years (2000-2012) were calculated. After evaluating the accuracy and validating of monthly data from satellite images, estimation value of the drought on the determined time scales was done by use of TRMM dataset. The estimated value of the drought (SPI) across the study area using TRMM satellite images and maps of rainfall of ground-stations was calculated in MATLAB software after that for all the pixels continuously SPI value was calculated. The results indicate that, the SPI index from satellite images and ground stations are closely related. According to the statistics of weather and precipitation, year 2008 was introduced as the low rainfall year, besides the results of the study showed that the SPI value of the basin, in 2008 was lowest that determined it as the dry year.

In general, the protection and utilization of surface water in arid regions, done by different methods such as Flood water spreading that undoubtedly will affect on sustainable development of groundwater resources. In order to provide, suitable, executive and manageable solution, Continuous monitoring is essential for such projects. For this reason the effect of Dehender Flood spreading on downstream unconfined aquifer was evaluated. For this purpose, the location of flood spreading and hydrogeological conditions of downstream aquifer determined by data and information that are Gathered from Hormozgan regional water authority along with field observations. Then 7 Observation wells were chosen. Finally, the effect of flood water spreading on water table surface groundwater changes was investigated by using underground water balance equation and unit hydrograph befor and after the construction of flood spreading system. The results of this evaluation showed that the average level of the water from sea level at the central of the plain(are not affected by flood water spreading) and near flood spreading (are affected by flood water spreading respectively) befor and after the construction of flood spreading system are: 213. 4, 209. 5 and 254, 251 meter of the sea level. As a result we can state that flood water spreading play an important role in sustainable development of ground water resources.

Two factors of cost and time are related directly to the accurate estimate of runoff in the watersheds. More detailed information on the status of rainfall runoff also facilitate decisions on future programs for watershed managers, a step towards the preservation of natural resources for sustainable development. In this study, in order to achieve optimal amount of runoff in the Shafaroud watershed, first significant rainfall data of four stations during 1998 to 2011 were collected and combined with other maps of the study area, such as DEM, land use and soil as input data in the form of SWAT model was software. After running the model, the SUFI-2 and GLUE algorithms in SWAT-CUP program used to evaluate the data uncertainty and the most accurate simulation. The first three years (1998-2000) of rainfall data for warm-up and the next 7 years (2001-2007) for the calibration and final 4 years (2008-2011) were used for the validation. Finally, with multiple simulations, the uncertainty of the parameters assessed with P-factor, R-factor, and NS coefficients. The results indicated in runoff simulation, the SUFI2 algorithm ( =0. 85, NS=0. 74) is more accurate than GLUE algorithm ( =0. 82, NS=0. 71).

Estimation of Base Flow Index (BFI), has always been one of the most important issues in hydrology. Base flow separation process, often is done using daily stream flow data. Lack of full coverage of daily data for the whole country, may lead to some errors for estimating the base flow and its index. In this research, base flow index in some catchments of Karkhe basin based on daily and monthly stream flow data and using six algorithms were extracted. Three based on recursive digital filter (One-parameter, two parameter and Lynie & Hollick algorithms), and the others on simple smoothing including, Local minimum, Fixed interval and sliding interval methods. Results were analyzed using different statistical methods such as standard deviation, mean absolute error, relative error and other descriptive methods. The results showed that minimum relative error of monthly data compared to daily data was related to two parameter algorithm with 2. 45% and the maximum was related to Lynie & Hollick algorithm with 84. 19 percent. In overall conclusion, two parameter algorithms because of low relative error, minimum Mean Absolute and Root Mean Square Error was recognized as a suitable method for the extraction of base flow using monthly data in the absence of appropriate data daily.

Climate is a complex system that changing mostly due to increased greenhouse gases and global warming, leading to intensification of change in climatic factors such as precipitation amount and intensity of extreme precipitation events. In effect of climate change in the future, change amount and volume of the soil erosion is expected which the most important sensitive factor will be the rain fall erosivity. The aim of this study was to determine the effect of climate change on rainfall erosivity factor. For this purpose the HadCM3 model from A1B scenario was used and downscaling with LARS-WG model was used. So monitoring of rainfall erosivity factor for three periods of 2011-2030, 2045-2065, and 2080-2099 in north of Iran was simulated. Results show that rainfall erosivity factor in Sangdeh, Babol, Korkorsar, Anzali, Behshar and Gorgan stations will be increasing during the 2011-2030 period but for stations in Babolsar, Hashtpar, Rasht and Gorgan in the period 2045-2065 and 2080-2099 decreased. According of calculations, maximum changes of the rainfall erosivity factor in future will be occurring during the 2011-2030 and it’ s minimum will be occurring period the 2080-2099. So largest rainfall erosivity factor was simulated about 42. 6 MJ mm ha-1 h-1 for Hashtpar station during the 2011 to 2030 period. The obtained results show that the erosivity factor increase will be during the current century in the north of Iran.

Predicting the temperature and precipitation changes is necessary for assessing the change in the future and to mitigate the harmful impacts of climate change on water resources and agriculture, environmental, economic and social issues. Accordingly atmospheric general circulation models (GCMs) have been developed for simulation of climatic parameters. In this research, output data of HadCM3 general circulation model (with three climate change scenarios A1B, A2 and B1) were downscaled using LARS-WG Statistical Model in selected stations of the Urmia Lake Basin and Results has been evaluated and analyzed from three selected synoptic stations, including Saghez, Tabriz and Urmia stations in the base period (1961-1990) and the 2050 (2046-2065) for three variables minimum temperature, maximum temperature and precipitation. In LARS-WG model analysis, evaluation of the amount of MSE, RMSE, MAE indexes were done and correlation coefficients were determined. The conclusion can be presented herein that: the model was fit for the region. The overall results for 20 years of 2050s, indicate a decrease of 12. 1 percent in precipitation and also 1. 3 Celsius degrees would be increased in temperature compared to the base period. In the study area, the highest maximum temperature increase would be in Tabriz synoptic stations and the highest minimum temperature and highest decries precipitation would occur in Urmia station. The results of this study would help enormous the policymakers and planners for water resources in the future.

In this study, changes of aridity index (AI), reference evapotranspiration (ET0) and precipitation were investigated in six stations located in the west and northwest of Iran over 1966-2010, 2011-2040, 2041-2070 and 2071-2100 periods. The outputs of HadCM3 under A2 and B2 emission scenarios were downscaled using statistical downscaling approach by Statistical downscaling model (SDSM). Mann-Kendall trend test was applied to assess the significance of trends of aridity index, reference evapotranspiration and precipitation in 1966-2010. The results of Mann-Kendall test revealed that there was a significant decreasing trend in AI and precipitation at the level of 95% over 1966-2010 in most of the surveyed stations. The negative trends of AI during winter, spring, summer and autumn were significant at five, four, zero and two of six surveyed stations, respectively. This indicates that reduced wintertime aridity index plays an important role in downward trend of annual aridity index in the studied area. The results also showed that AI, averaged across all stations, would decline by 8. 0, 14. 7 and 34. 3% under A2 and 12. 6, 12. 5 and 20. 1% under B2 over the early, middle and late 21st century relative to the baseline period (1966-2010), respectively, indicating a drier climate in northwest and west of country over the 21st century. On seasonal scale, the greatest decrease of AI is expected in summertime under A2 and springtime under B2 over the 21st century. AI, averaged over all stations, will most likely approach 0. 2 indicating a severe reduction of aridity index in the studied area under A2. In some regions such as Tabriz, increased ET0 and decline of precipitation will cause a shift from semi-arid to arid climatic condition over the 21st century.

In this research, the target area were regionlized into few distinctive homoginious sub-regions by applying principal component alalysis to the SPI time series at 3-, 6-and 12-months time scales and the resultant PC scores were considered as the regional SPI time series for drought forecasting using time series modellingineach identified sub-region. The probability of occurences of dry, normal and wet events were also predicted for all the considered stations using Markov chain model and the results were spatially mapped and analysed. The expected drught numebr and drught length of the prediceted drought events were also estimated and mapped to spatially display their results in order to ease their spatial variability comparrison. Furthermore, different time series models were fitted to the Regional SPI series (PC scores) to identify the best fitted model for each region in order to use for drought forcasting. The result shows that the ARMA is the best fitted model for SPI time series at 3-and 6-months time scales while for the 12-months time scales the SARIMA model is the best fitted model. Using the identified models the magnitude of the SPI was forcasted for the leading times. The result shows that the time series models can favorably forcast SPI values for three months ahead, wherease the predicted results for more than three months ahead is not reasonably accurate.

Laboratory plots and rainfall simulators are useful tools for erosion studies, but transferring soil and consequent preparation steps which leads to damage soil structure, are among the disadvantages of laboratorial soil erosion studies yet. In other words, soil preparation steps can cause considerable errors in the results of runoff and erosion in laboratorial conditions. On the other hand, measuring splash erosion, as the first ability to detach and move the soil particles, is very important in soil erosion studies. Knowing the uncertainties of splash results due to soil preparation methods is therefore essential to improve the accuracy of laboratory results. The present study has been therefore conducted to measure and compare the amount of splash in a sandy-clay-loam soil in both undisturbed and disturbed conditions in a hillslope in the southern part of Alborz Mountains under three rainfall intensities of 40, 60 and 80 mm h-1. The results showed that disturbing soil in erosion laboratory studies could significantly increase the upslope, downslope, gross splash (p<0. 01) and net splash (p<0. 05). The effects of soil disturbance on the ratio between upslope and downslope splash was not significant. According to the results, the increasing rates of upslope, downslope, gross and net splash due to soil disturbance were 216, 241, 234 and 257%, respectively.