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

In this study, entropy theory and the modified Mann-Kendall test were used to monitoring the quality and quantity of groundwater in the Dez Plain regarding temporal and spatial changes, as well as the excess and deficiency of stations in the aquifer. The values of groundwater level (28 stations), electrical conductivity and chlorine (30 stations) in the period of 1999-2019 were investigated in this study. The results of the analysis of trend changes show major increasing trend in qualitative values (80% of stations) and major decreasing trend in groundwater level values (53 percent of stations). The multivariable regression model has an average error of 0.10 mg/liter in the simulation of chlorine values, 15 μm/cm for the simulation of electrical conductivity values, and 0.49 m in the simulation of groundwater level values. By examining the entropy theory, the values of the information transfer index indicated the average conditions of the groundwater level and relatively excess conditions of qualitative values in terms of information transfer in the region. The transmission of chlorine information in the southwest of the aquifer and the transmission of groundwater level information in the southeast of the aquifer are in a state of deficiency. According to the existing conditions regarding the quantitative monitoring and electrical conductivity monitoring of the groundwater, the Dez aquifer is in a good condition and the distribution of the stations is also suitable, but regarding the optimal monitoring of the aquifer in terms of transmission of chlorine information, the need for a station in the southeast of the aquifer is felt. By ranking the stations using net exchange information, the best stations were introduced in terms of quantitative and qualitative values.

The quality monitoring of groundwater networks is of great importance due to its importance in different sectors of agriculture, drinking, industry, etc., and the necessity of its periodic use leads to the recognition of quality changes of water resources in different periods. In this study, the entropy theory based on random forest was used to quality monitoring of electrical conductivity (EC) and total dissolved solids (TDS) in the groundwater of 12 wells in the Tasouj plain located in south of Lake Urmia from 2002 through 2019. In order to investigate the interaction of wells in the aquifer area, the conventional method (multivariate regression) and the random forest algorithm were used. By comparing the performance of the two mentioned models in simulating EC and TDS values in a 12-variable mode, the results showed that the random forest model has a better performance and a lower error rate than the multi-variable regression model. On average, the random forest algorithm reduced the error rate by 40% and 56% in simulation EC and TDS values, respectively, in the studied aquifer. The ranking results of the studied wells showed that the Qara Tape well has the highest rank and the Amestjan well has the least important rank among the studied wells, which indicates the importance of the information extracted from the Qara Tape well. According to the zoning of the information transformation index in the aquifer area, the results showed that there is no limitation in monitoring of EC values in the aquifer, and the scattering of the wells is the best. There is no shortage of wells in terms of exchange of salinity information in the study area. Regarding the TDS values, a lack of wells was observed in the central areas and the eastern and western border areas.

Rainfall data are required for planning, designing, developing and managing water resources projects as well as hydrological studies. Some previous studies have suggested increasing the density of the rain gauge network to reduce the estimation error. However, more operational stations require more installation costs and monitoring. Some common techniques including statistical methods, spatial interpolation, information-based theory and combination are used to evaluate and design the network. Chaharmahal va Bakhtiari province is a mountainous region; hence, a denser rainfall network is expected in this mountainous environment. The aim of this study was to evaluate the condition of rain gauge stations in Chaharmahal va Bakhtiari province using two approaches, i.e. geostatistical methods and entropy theory.
The main required data set for this study is a time series of rainfall data. These data were collected on a daily scale from the Regional Water Company of Chaharmahal va Bakhtiari. After performing statistical tests, the annual data series was prepared for 46 rain gauge stations. A statistical period of 2000 to 2016 was used. The homogeneity of data was investigated by double mass test and histogram drawing methods using Excel and SPSS software, and the existence of trend in the time series of data was investigated by applying a Spearman test. Then, the adequacy of rain gauges in the gauging network was investigated. Annual rainfall interpolation maps and their standard error maps were prepared using the kriging method. Contribution of each station in reducing or increasing the error in the rain gauge network was investigated by removing each station in a cross validation procedure. The efficiency of the rain gauge network was evaluated using the concept of discrete entropy and the values of entropy indices. The value of keeping the rain gauge stations was determined using the net exchange information index.
There was no homogeneity problem and significant trend in the data series. Considering the permissible error percentage of 5%, there is a need to add 15 new rain gauge stations to the network. To apply the geostatistical method, we applied it once without deleting any station; then, the kriging interpolation error was calculated for the precipitation data. Then, only one station was removed at each stage, and both the error and the contribution of each station in increasing or decreasing the error compared to the case without Station deletion were obtained. The results indicated that Ab-Turki, Shahrekord, Borujen and Barez stations were more important than other stations. Two stations namely Chaman-Goli and Ben stations can also be considered as the influential stations in error due to the density of stations in the region and error maps. Similarly, the results of the entropy theory method were found effective in evaluating the design of the rain gauge network. The highest value of H(x) was observed in the data of Armand station (3.26) and the lowest value was observed in Abbasabad station (2.28). Since H(x) shows the uncertainty of measuring data, the maximum and minimum uncertainty were found for Armand and Abbasabad sites, respectively. Based on the Net Exchange Information Index, Bardeh, Bareh Mardeh and Dezkabad stations were ranked 1 to 3, respectively, indicating that they transmit and receive more information than other stations. On the other hand, a number of stations including Dorak anari, Abtorki and Chelo stations had the lowest values.
Due to the vast extent of the area and also considering the permissible error percentage of 5%, the number of the stations in this area was found to be insufficient. Thus, although calculating the kriging error maps showed that some stations do not have a significant share in increasing the error, removing the stations is not recommendable. Regarding the new stations, new 15 rain gauge stations are needed to check out the error maps. According to the field observations, the higher priority should be given to the northwestern area (which had the largest interpolation error) in the first place. For the regions with lower error, such as northeast, east, southeast, west and southwest that do not have rain gauge stations, additional rain gauge stations should be constructed.

Designing of water quantity and quality monitoring system has been raised as one of the most complex issues in the field of water resources and the environment. The siutable quality of groundwatertable information recorded in the groundwater networks plays an important role in the sustainable design of water projects. In order to create an efficient and efficient network, groundwater networks should be periodically evaluated according to the needs and plans of the forward water resources The study area is the Nazlouchai catchment area located in west of Urmia Lake.

In this research, entropy theory was used to monitoring the quantity water level in the two historical statistical periods (2001-2016) and updated (2016-2021). The updated statistical period was developed using hybrid time series models (CARMA-ARCH). After initial data analysis and changes in the time series, the data were simulated to create the interaction of piezometers with multivariate regression. After confirming the accuracy of the multivariate regression model, entropy indicators were calculated and zoned on the Nazlouchai plain. After evaluating the groundwater network monitoring during the statistical period of 2001-2016, the Nazlochai plain groundwater network monitoring was updated for the statistical period of 2016-2021.

The results of evaluation of the CARMA-ARCH hybrid model accuracy indicate the ability of the hybrid model to simulate and predict the annual values of groundwater level in the study area. The performance factor of the model also confirmed this. The results of the evaluation of the groundwater network monitoring in Nazlouchai plain showed that more than 99% of the studied area is located in the surplus and relatively surplus situation in terms of the number of piezometers. The status of the plain in the statistical period of 2011-2016 is good and the transmission of information between the piezometers is complete. During the statistical period of 2016-2021, groundwater level changes in the study area have been reduced, which has affected the network's groundwater monitoring. So that the areas with excess wells has been reduced to moderate monitoring areas. In general, the results of the research indicate the necessity of using the groundwater monitoring network and it is recommended that this monitoring be carried out annually for different plains of Iran. Also, the results showed that with decreasing groundwater level in the studied area, information transfer between wells is also reduced.

The results show that there is no complete transfer of information between the piezometers in the study area during the statistical period of 2016-2021.

Designing of water quantity and quality monitoring system has been raised as one of the most complex issues in the field of water resources and the environment. Designing of these systems used to achieve qualitative and quantitative information, while their design process requires basic information. The study area in this research is Urmia Lake basin that located in the North West of Iran. Entropy literally means disorder. In this study used entropy theory to rain gaging monitoring in period of 1984-2011. Also The modified Mann - Kendal test was used to study the trend of the studied parameters The results of the study of the trend of precipitation values of Urmia Lake basin at annual scale showed that rainfall changes in this basin have been decreasing in the annual scale. In order to study and monitoring the rain gauge network using Entropy theory, two methods of support vector regression and kriging were used to estimate precipitation values. Results indicated that the accuracy of the regression model was higher than the Kriging model. The results of the evaluation of the entropy index at the aquifer showed that only 1.4% of the studied basin had a severe shortage of information that required the construction of a new station in the area. However, since more than 90 percent of the basin area is in terms of data transmission in excess and relatively excessive condition, the study area is relatively good at its monitoring. In general, the results indicated that the accuracy of the optimized method of support vector regression was used to estimate the annual rainfall in the Urmia Lake basin. The results of the stations' ranking in the study area showed that the stations of Jharabad, Badamlou and Orban received ratings ranging from 1 to 3, which indicates the transfer and reception of more information than other stations.