Journal of Watershed Management Research

Extended Abstract
Introduction and Objective: Teleconnection patterns are one of the effective hydro-climatological factors in predicting precipitation, temperature and discharge on a large scale. Oppositely, comprehensive and integrated management of water resources requires that rainfall variables and consequently runoff flow can be predicted. From a dynamic and synoptic approach, teleconnection patterns can affect the precipitation pattern of different regions. The purpose of this study is to inspect the relationship between these indicators and autumn rainfall in the Caspian Sea basin and forecast it using various statistical models.
Material and Methods: Therefore, in this study, Caspian Sea sub-basins were selected and autumn rainfall in the 28-year period from 1987 to 2015 was calculated. Then the correlation of MEI, SOI, NCP, NAO, AO, CSST, P-SST and MSST indices with autumn rainfall in July, Aug, Sep, Oct, Nov, summer, Aug-Sep-Oct and Sep-Oct-Nov was calculated. And the most important ones that had the highest correlation were considered as inputs to different models. Finally, autumn rainfall forecasting was done using a statistical model and three artificial intelligence models with different structures.
Results: The study showed that various teleconnection patterns were effective depending on the type of sub-basin and time step. Prediction results showed that the difference between observational and modeled data in the training period was small and increased somewhat in the test period and reached about -25.7 to 47.6 mm in the whole sub-basins. Thoughtfulness of the type of analytical model showed that both SVR and MLP models had higher accuracy than GRNN and MLR models, so that the Root Mean Square Error by SVR model in Aras, Atrak, Haraz-Sefidrood, Qarahsu-Gorgan, Serazod-Haraz, and Haraz-Qarahsu sub-basins. 6.18, 7.34, 35.44, 18.25, 19.58, 17.68 and 47.22 mm, respectively, and the coefficient of determination will be 0.94, 0.91, 0.92, 0.84, 0.88, 0.88 and 0.87, respectively.
Conclusion: Therefore, the results show a strong relationship between teleconnection indices with autumn rainfall in the study basin. These include NAO, SOI, AO and Caspian and Mediterranean Sea surface temperatures at different time delays. With these results, steps can be taken to more accurately predict and manage the water resources of the Caspian Sea basin.
 

 Extended Abstract
Introduction and Objective: The snow variable plays an important role in hydrological cycles and is an essential component of the climate system. Is one of the basic applications in the field of water resources management, especially in areas where snowfall has a large share of precipitation. Therefore, the main purpose of this study is to investigate the trend of these changes in the watershed of the northern slope of the Alborz Mountain range in Mazandaran province in abnormal climatic conditions in the last decade.
materials and methods: First, MODIS sensor data was received daily from NASA's National Snow and Ice Database (NSIDC) with a 500*500 m embedding capacity. The received images are related to the period 2000-2018. To process the images, pre-processing operations were first performed on them in the ENVI 5.3 software environment. The NDSI index was used to estimate the snow cover. Mann-Kendall test and age line slope estimator method were used to study the trend of snow cover changes. Pearson correlation coefficient was also used to investigate the correlation between snow cover level and climatic parameters.
Results: Examination of the trend of snow cover level seasonally and annually showed that snow cover in winter has decreased by about -50.41 square kilometers per year. From the elevation standpoint, snow cover is regressing, as its trend is decreasing across all elevation levels, especially at altitudes of 1600 to 2500 meters. The result of this study shows that there is a negative correlation between snow cover and net radiation and a positive correlation with soil moisture at a 95% confidence level. A comparison of the correlation between snow cover status and time and different elevation classes with temperature and precipitation shows that in most cases negative snow cover anomalies are associated with positive temperature and negative rainfall anomaly, which is significant at 95% level. While acknowledging the decline of snow stocks on the northern slope and the increasing increase in freezing temperatures, the management of downstream basin water resources should be reconsidered.
Conclusion: In general, the results show that the trend of snow cover seasonally and annually has a decreasing trend. It can also be concluded that the trend of snow cover of different altitudes in the northern slopes of Central Alborz has decreased and receded. The greatest effect of temperature increase is observed in spring. This is because the energy required to melt snow is usually provided by short-wave radiation in early spring, and as the intensity of the net radiation current increases due to the increase in short-wave input radiation and the whiteness occurs due to the decrease in height and snow-covered range, the snow melting rate increases. Therefore, with increasing temperature and changing climatic conditions, winter precipitation, which will turn into snow accumulation, has decreased and can affect the runoff caused by these precipitations in spring.

Extended Abstract
Introduction and Objective: Water management in water basins is difficult due to the lack of data collection stations. Today, rainfall-runoff simulations with different models will help manage existing water resources. Therefore, using hydrological models that allow the identification and management of the basin with minimal data can be a suitable method.
Material and Methods: In this study, in order to simulate runoff caused by rainfall and to investigate the mechanism of runoff formation and outflow in the catchment area of the Shahid Rajaei Dam, located in Sari, the HBV-light model with existing data from 1981 to 2015 was used. Its performance was also evaluated under climate change conditions with two scenarios of RCP2.6 and RCP8.5 in the two time periods of near future (2016-2040) and distant future (2041-2065).
Results: The results showed that the increase in temperature in the two scenarios of RCP2.6 and RCP8.5 by 11.5 and 13.9% in the near future and 13.9 and 24.2% in the distant future, respectively. Rainfall in the two climate scenarios RCP2.6 and RCP8.5 will also decrease by about 58% in the distant and near future. The output results of the model showed that the effect of climate scenarios on peak discharges will increase in the near future (2016-2040) and decrease in the distant future (2041-2065). The difference between the mean peak discharges in the future time window compared to the base period was significant at the 95% confidence level (Kruskal-Walli’s test). RCP2.6 and RCP8.5 will increase by 36% and 28% in the near future and decrease by 12% and 3% in the near future, respectively. These changes in peak discharges will increase the probability of occurrence of extreme phenomena (severe peak discharges) due to changes in the statistical distribution.
Conclusion: In general, these results indicate that the management, operation and maintenance of water resources accumulated at the site of the Shahid Rajaei Dam will face serious challenges. Therefore, it is suggested to apply advanced leading scenarios in catchment management while examining more closely and comparing with the results of other hydrological models.