جستجوی مقالات مرتبط با کلیدواژه « فضای فیزیوگرافی » در نشریات گروه « آبخیزداری، بیابان، محیط زیست، مرتع »

Regional analysis is the stability method to improve estimates of flood frequency, which has become one of the dynamic sectors in hydrology and the new theories are testing, constantly. Application of geostatistical method is an innovation in this field for regional flood analysis.This technique is based on the interpolation of hydrological variables in the physiographical space instead of using common geographical space. However, the hydrological, climatological and physiographical information of 38 river basin information of watersheds inside of Mazandaran province were obtained and Canonical Kriging method was used for regional flood analysis whit return periods of 10, 20, 50 and 100 years. The Canonical Correlation Analysis was used to design physiographic space by the geomorphoclimatical variables affecting the flood. The Gaussian model had the best fit to semi-variogram model in all return periods and the geostatistical method of Ordinary Kriging was used for regionalization. Results evaluated using Jack Knife mutual procedure and the five statistical indexes. The performance of NASH was obtained over than 0.9 in all of return periods, which implies the accurate and acceptable predictions of flood in ungauged basins. The other indicators led to satisfying results, too. According to the results of relative statistical indicators accuracy regional estimates improves as long as return periods increase. These results showed that application of Canonical Kriging method is effective and practical approach for regional flood analysis.

Advances in tools and spatial and temporal techniques, have provided new approaches in regional flood analysis and parameters estimation. Application of interpolation techniques based on physiographical attributes, seems to be new in many hydrological aspects. However, the hydrological, climatological and physiographical information of 38 river basin information of watersheds inside of Mazandaran province were obtained and regional flood estimates basis the main and specific quantiles discharge and several of return periods were estimated using physiographical space based interpolation technique. The Multivariate Principal Component Analysis was used to design physiographic space using the six geomorphoclimatical variables affecting the flood. The exponential model had the best fit to smi-varigram model in all return periods and the ordinary kriging, simple kriging and IDW methods were used for interpolation. Results evaluated using Jack knife mutual procedure and the four statistical indexes including BIASr, RMSE, RMSEr, and NASH. Results improved dramatically, when the data of 7 stations eliminated due to having the largest value of RMSEr and BIASr. Accordingly, in the first case the NASH values increased from 0.4 to 0.6 up to 0.5 to 0.8, respectively. Moreover, the three other indexes led to satisfying results, too. This implies that the proposed approach has the efficiency to estimate discharge in ungauged watersheds. Results of the interpolation indicated that the ordinary kriging and IDW have similar performances and their performances are better than simple kriging.

The physiographical and climatological attributes of basins and maximum annual flood statistics were obtained from 38 hydrometric stations of Mazandaran province with minimum and maximum statistical periods of 13 and 56 years. The first، homogenous regions based on neighborhood approach were determined using canonical kriging method. The Canonical Correlation Analysis was used to design physiographic space using the six physiographic variables affecting the flood and two hydrological variables. The Gaussian model had the best fit to semi-variogram model in 10، 20، 50 and 100 year return periods، and regional estimates obtained using ordinary Kriging technique based on physiography space. The accuracy of results was evaluated using L-moments method for regional flood frequency analysis. In this method، Ward hierarchical clustering has been used to the determination of homogeneous regions. Homogeneity areas were adjusted by using homogenous and discordancy tests. Using goodness-of-fit Z DIST the Generalized Logistic distribution was selected for all clusters as the best regional distribution and regional estimates obtained by parameters selected distribution. Finally، performance methods evaluated using Jack Knife procedure and the five statistical indexes BIAS، BIASr، RMSE، RMSEr and NASH. Both methods give the same and desirable performance based on NASH، however results of other indexes showed that canonical kriging method provide better performance than linear moments. Increasing the return periods will improve the estimation، but the L-moments offers better performance for short return periods.