جستجوی مقالات مرتبط با کلیدواژه « Pre » در نشریات گروه « آب و خاک »

Dynamic Programing models are appropriate tools for deriving optimal operation policies of reservoirs, especially during the water scarcity situation. In this paper, the performances of a variety of these models including deterministic Dynamic Programming (DP), Stochastic Dynamic Programming with inflow classification (SDP_Class), Stochastic Dynamic Programming based on inflow scenarios (SDP_Scenario) and Sampling Stochastic Dynamic Programming (SSDP) were evaluated and compared for Zayandeh-Rood multi-purpose system. For this aim, beside the complete supply of domestic, industrial and environmental demands, optimal operation policies considering constant agricultural demand and then both agricultural and hydropower ones were derived. Finally the performance of optimization models was evaluated and compared based on simulation models, computational load of optimization models as well as some efficiency criterion such as temporal and volumetric reliability, maximum and average shortage. Results showed that stochastic models like SDP and SSDP performed better than DP models, considerably. This superiority was considerable, especially during extreme water shortage conditions. Despite the SSDP preference its computational load as well as its execution time were higher than others. In order to alleviate this problem, pre-allocation and vectorization techniques were applied and they had a significant effect on the run-time reduction of all models, particularly on SSDP.

Trend analysis conducted on stream-flow measured at hydrometric stations across the central part of Karkheh River watershed in monthly, seasonal and annual time scales using statistical methods. The data used were the monthly discharge time series of 11 selected hydrometric stations over a 40 year period (1969 to 2009). The slope of the trend line of discharge time series was estimated using the Theil-Sen approach (TSA) and the effect of the significant autocorrelation coefficient was removed using trend-free pre-whitening (TFPW), pre-whitening (PW) and variance correction approach (VCA) methods, and the discharge time series were pre-whitened. Then, the trend of original and pre-whitened data were analyzed using the Mann–Kendall (MK) test. The ability of TFPW, PW and VCA methods for removing the effect of the autocorrelation coefficient were evaluated. The results showed that the TFPW is the best method for removing the effect of serial correlation from discharge time series. So, trend analysis of monthly, seasonal and annual discharge time series was conducted by using the MK-TFPW method. The results show that at annual time scale, more than 70 percentages of considered stations have experienced a significant decreasing trend at the 5% level.Trend analysis conducted on stream-flow measured at hydrometric stations across the central part of Karkheh River watershed in monthly, seasonal and annual time scales using statistical methods. The data used were the monthly discharge time series of 11 selected hydrometric stations over a 40 year period (1969 to 2009). The slope of the trend line of discharge time series was estimated using the Theil-Sen approach (TSA) and the effect of the significant autocorrelation coefficient was removed using trend-free pre-whitening (TFPW), pre-whitening (PW) and variance correction approach (VCA) methods, and the discharge time series were pre-whitened. Then, the trend of original and pre-whitened data were analyzed using the Mann–Kendall (MK) test. The ability of TFPW, PW and VCA methods for removing the effect of the autocorrelation coefficient were evaluated. The results showed that the TFPW is the best method for removing the effect of serial correlation from discharge time series. So, trend analysis of monthly, seasonal and annual discharge time series was conducted by using the MK-TFPW method. The results show that at annual time scale, more than 70 percentages of considered stations have experienced a significant decreasing trend at the 5% level.Trend analysis conducted on stream-flow measured at hydrometric stations across the central part of Karkheh River watershed in monthly, seasonal and annual time scales using statistical methods. The data used were the monthly discharge time series of 11 selected hydrometric stations over a 40 year period (1969 to 2009). The slope of the trend line of discharge time series was estimated using the Theil-Sen approach (TSA) and the effect of the significant autocorrelation coefficient was removed using trend-free pre-whitening (TFPW), pre-whitening (PW) and variance correction approach (VCA) methods, and the discharge time series were pre-whitened. Then, the trend of original and pre-whitened data were analyzed using the Mann–Kendall (MK) test. The ability of TFPW, PW and VCA methods for removing the effect of the autocorrelation coefficient were evaluated. The results showed that the TFPW is the best method for removing the effect of serial correlation from discharge time series. So, trend analysis of monthly, seasonal and annual discharge time series was conducted by using the MK-TFPW method. The results show that at annual time scale, more than 70 percentages of considered stations have experienced a significant decreasing trend at the 5% level.Trend analysis conducted on stream-flow measured at hydrometric stations across the central part of Karkheh River watershed in monthly, seasonal and annual time scales using statistical methods. The data used were the monthly discharge time series of 11 selected hydrometric stations over a 40 year period (1969 to 2009). The slope of the trend line of discharge time series was estimated using the Theil-Sen approach (TSA) and the effect of the significant autocorrelation coefficient was removed using trend-free pre-whitening (TFPW), pre-whitening (PW) and variance correction approach (VCA) methods, and the discharge time series were pre-whitened. Then, the trend of original and pre-whitened data were analyzed using the Mann–Kendall (MK) test. The ability of TFPW, PW and VCA methods for removing the effect of the autocorrelation coefficient were evaluated. The results showed that the TFPW is the best method for removing the effect of serial correlation from discharge time series. So, trend analysis of monthly, seasonal and annual discharge time series was conducted by using the MK-TFPW method. The results show that at annual time scale, more than 70 percentages of considered stations have experienced a significant decreasing trend at the 5% level.

Flood irrigation after planting induces wetting and drying cycles in arable soils. For this reason, the effect of this process on load-bearing capacity (pre-compaction stress; pc) of a fine textured soil (silty clay) was studied. In this research, large air-dry disturbed soil specimens were prepared and some of them were exposed to five wetting and drying cycles. Next, the large soil specimens with/without wetting and drying cycles were compressed under three preloads (0, 100 or 200 kPa) and then the centre section of the preloaded soil specimen was firstly submitted to a plate sinkage test (PST). Then immediately one cylindrical sample was cored for confined compression test (CCT). The results showed that for reconstructed soil samples without wetting-drying cycles, the predicted σ pc using PST didnt significantly differ from the applied preload. Therefore, the PST can be used to determine the load-support capacity of the tilled soils. In PST, with an increase in soil water content from 0.9PL to 1.1PL, the amount of over-prediction in σ pc decreased. However, wetting-drying process significantly increased over-prediction in σ pc at the same water content. Hence, soil compressibility does not simply depend on the actual soil water content but also on the previous history of water content changes (i.e., wetting-drying cycles).

Wetting and drying induce stresses in soil which changes the physical structure of the soil. For this reason، the effect of this process on evaluating the methods for estimating the threshold of compactibility (load-bearing capacity، pre-compaction stress) of a coarse textured soil (sandy loam) collected from the fields of the Sugarecane and By-product Development Co. in Ahvaz province was studied. In this research، the plate sinkage test (PST) and confined compression test (CCT) methods were evaluated. Large air-dry disturbed soil samples were prepared and some of them were exposed to five wetting and drying cycles. After that، the large soil samples with/without wetting and drying cycles were compressed under three loads (0، 100 or 200 kPa) and then the centre section of the preloaded soil samples was firstly submitted to PST. Then immediately one cylindrical sample was cored for CCT. The results showed that for the soil samples without wetting and drying process، there was no significant difference between the applied load and the estimated values using PST method. However، for the soil samples under wetting and drying process، the obtained values were significantly greater than the applied loads. Therefore، for tilled soil، PST can be used as a quick method to determine the compression parameters of the soil in laboratory or in the field.