M. Golestani, H. Pakniyat,
Volume 11, Issue 41 (fall 2007)
Abstract
To investigate genetic variation, and identification of tolerant genotypes according to quantitative indices of drought tolerance, 8 sesame genotypes were tested in a randomized complete block design with three replications under optimum and limited irrigation at the Research Station of College of Agriculture, Shiraz University. Based on the potential yield and yield under stress, quantitative indices of drought tolerance such as mean productivity (MP), geometric mean productivity (GMP), harmonic mean (HM), stress tolerance index (STI), stress susceptibility index (SSI) and tolerance index (TOL) were determined. The result of analysis of variance exhibited highly significant differences among the genotypes for all the indices measured, and yield under optimum and limited irrigation, indicating the existence of genetic variation among genotypes, and thus the possibility of selecting drought tolerant genotypes. Mean comparison displayed that the highest potential yield, stress yield, MP, GMP, HM and STI were related to the genotype number 5. Correlation analysis between indices, mean potential and stress yields indicated that every four indices are suitable for screening the genotypes. Based on these indices and higher yields under optimum and limited irrigation the best drought tolerant genotypes were identified to be genotypes number 4 and 5. Multivariate biplot indicated that the genotypes number 4 and 5 were located next to the vectors of drought tolerance indices, including MP, GMP, HM and STI. Cluster analysis showed genetic distance among genotypes. As a result, genotypes number 4 and 5 were identified as drought tolerant and genotypes number 1, 2 and 3 as susceptible to drought.
M. Golestani, S. F. Mousavi, H. Karami,
Volume 29, Issue 3 (Fall 2025)
Abstract
Groundwater is a vital resource for meeting drinking, agricultural, and industrial needs in arid and semi-arid regions of Iran. In this study, quantitative and qualitative changes in groundwater in the Garmsar Plain were modeled using GIS, MODFLOW, and MT3DMS software during the period 2011-2013. Spatial and climatic data were comprehensively processed and prepared in the GIS environment, and groundwater flow was simulated using the MODFLOW model, and water quality changes were analyzed using the MT3DMS model. After validation with field data from 2012 to 2013, the model showed acceptable accuracy with statistical indicators of mean absolute error (MAE) in the range of 0.4 to 0.5 meters and root mean square error (RMSE) between 0.5 and 0.6 meters. The modeling results showed that a 15% increase in water withdrawal led to a decrease in the water table of up to 8 meters, a constant withdrawal led to a decrease of 7 meters, and a 15% decrease in withdrawal led to a decrease of 5 meters in the water table. From a quality perspective, the decrease in withdrawal improved the quality of irrigation water but increased the concentration of some pollutants, which requires the development of effective management strategies to protect groundwater resources. The findings of this study illustrate the importance of sustainable exploitation and smart management of groundwater resources in the Garmsar Plain.
