Omid Rahmati; Aliakbar Nazari Samani; Nariman Mahmoodi; bahram choubin
Abstract
One of the techniques to eliminate groundwater resources crisis is to carry out artificial recharge projects, which cause infiltration of water from the surface into the aquifer and balance of the water table. An appropriate site selection for artificial recharge is one of the most important steps in ...
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One of the techniques to eliminate groundwater resources crisis is to carry out artificial recharge projects, which cause infiltration of water from the surface into the aquifer and balance of the water table. An appropriate site selection for artificial recharge is one of the most important steps in implementation of these projects, itself. In this study, capability of gridding technique and AHP method was evaluated for zonation of artificial recharge potential. Accordingly, a grid, with cell size 0.1 km2, was defined for rangelands of Chamshor watershed and geological parameters, slope, thickness of unsaturated layer, electrical conductivity and transmissivity were selected for entry into the model. Finally, potential zonation map of artificial recharge project, using gridding technique, Analytical Hierarchy Process (AHP) and weighting linear combination methods were produced for implementation of artificial recharge. In order to assess the model, the project of artificial recharge in the study area was used which has had a successful performance on balancing the water table level, reducing destructive floods and increasing vegetation. Finally, the accuracy of the gridding technique and AHP method was 87.5 percent. In conclusion, the zonation of artificial recharge potential which was obtained by gridding technique and AHP method was reliable and it is recommended to be used in the site selection of flood spreading systems to be able to carry out artificial recharge projects.
bahram choubin; SHahram KHalighi Sigaroodi; Arash Malekian
Abstract
Predicting climate trends, especially forecasting rainfall, provides managers of different fields withsuitable tools so that considering these predictions; they can devise future-state policies. At thisstudy, after selecting the most effective climate indices applying PCA method, the effects of largescaleclimate ...
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Predicting climate trends, especially forecasting rainfall, provides managers of different fields withsuitable tools so that considering these predictions; they can devise future-state policies. At thisstudy, after selecting the most effective climate indices applying PCA method, the effects of largescaleclimate signals in seasonal rainfall of basin Maharlu - Bakhtegan were investigated bothsimultaneously and by delay through statistical methods (Pearson correlation and cross-correlationcoefficient) and by applying stepwise regression model, regression equation for forecasting rainfallwas offered. The results showed that in cross-correlation between the time series of SPI (dependentvariable) at time (t) and climate signals (independent variable) at time (t-k), only SOI indexconcurrently has a significant relationship with rainfall, whereas, most of indices turned significantwith standardized precipitation index with different lag times. In season to season study of thesignals with the standard precipitation index using Pearson's correlation coefficient it was found thatclimate signals of spring and summer are not significantly correlated with SPI. Representationcoefficients (R2) and standardized regression effect (Beta) in stepwise regression model showed thatsimultaneous and with season to season delays signals (for example: SPI index of autumn with fourprevious seasons indexes) at method Pearson correlation have higher relationship with seasonalstandardized precipitation index than the cross-correlation in time (t-k), (which signals of allseasons given is delay together with than SPI of all seasons) show.