Resources Environment and Information Engineering

Providing fresh water suitable for drinking and farming and living organisms in the ecosystem is essential. To evaluate water quality, qualitative indicators are often employed for managing water resources and water quality protection and pollution abatement. This study evaluated the quality of Borkhar basin water resources using three different water quality indices, including National Institutes of Health Water Quality Index (NIHWQI) having nine parameters, the Oregon Water Quality Index (OWQI) having eight parameters, and the Canadian Water Quality Indices (CWQI) with 22 main parameters. Using data for a period of 30 years, NIHWQI, OWQI and CWQI were used. To analyze water quality of the entire basin for current and future time. Results showed that water quality of the basin was in a very moderate range according to NSFWQI, and was in a very bad range accordingly to OWQI. Water quality forecasts showed that future water quality would be bad, based on OWQI and moderate based on NSFWQI, whereas based on CWQI, it will be good for drinking, and bad for aquatic animals, recreation, irrigation, and livestock use.

Nowadays, one of the most significant problems is that to recognize how the severity of heavy precipitation and floods may alter in future time in comparison with the current period. The purpose of this research is to understand the impact of future climate change on storm water and probability of maximum flood for future time period. Zayandeh rud river basin in Iran is selected as a case study. Forecast of future climatic parameters based on temperature and precipitation of the upcoming period (2006-2040) is completed with using the HadCM3 model and based on RCP 2.6, 4.5, and 8.5 emission patterns. Also, climate change model is downscaled statistically with applying LARS-WG. In the next step, the probable of maximum precipitation is measured through synoptic method and then, in order to model maximum storm water under the climate change effects, the HEC-HMS for simulating rainfall-runoff model is used. Also, the Snowmelt Runoff Model (SRM) is applied to model snow melting. The results of this research indicate the maximum of probable precipitation in the basin for the period of 2006-2040 under the scenario RCP 2.6, can rise by 5% and by the scenarios of RCP 4.5 and RCP 8.5 can decrease by 5% and 10%, respectively in comparison with the current period 1970-2005.

Hydrologic classification is the method of scientifically arranging streams, rivers or catchments into groups with the most similarity of flow regime features and use it to recognize hydrologically homogenous areas. Previous homogeneous attempts were depended on  overabundance of hydrologic metrics that considers features of variability of flows that are supposed to be meaningful in modelling physical progressions in the basins. This research explains the techniques of hydrological homogeneity through comparing past and existing methods;  in addition it provides a practical framework for hydrological homogeneity that illustrates serious elements of the classification process.