Gorgan University Of Agricultural Sciences Journal of Water and Soil Conservation 2322-2069 27 3 2020 08 22 Forecasting the groundwater monitoring network using hybrid time series models(Case study:Nalochay) Forecasting the groundwater monitoring network using hybrid time series models(Case study:Nalochay) 85 103 5136 10.22069/jwsc.2020.17149.3264 FA Abbas Khashei-Siuki Ali Shahidi Associate Professor of water engineering Deot. Yousef Ramezani Assistant Professor of Water engineering Dept. Mohammad Nazeri Tahrudi Ph.D. student. water engineering Dept. University of Birjand Journal Article 2019 10 18 Background and objectives: 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. Materials and Methods: 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. Results: 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. Conclusion: 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. Background and objectives: 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. Materials and Methods: 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. Results: 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. Conclusion: 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.

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