Climate Zoning Under Climate Change Scenarios In The Basin Of Lake Urmia And Vicinity Basins

A study of climate change scenarios is presented in this paper by projecting a set of recorded precipitation data into three future periods by statistical downscaling methods by employing LARS-WG using data from 7 synoptic stations. The study area covers the basin of Lake Urmia and its overlaps with two of its surrounding basins flowing to the Caspian Sea. The modelling is at two stages: Downscaling comprises: (i) use large-scale GCM models to provide climate variables (predictors); and (ii) downscale them to the local climatic variables for correlating with the observed timeseries (e.g. rainfall) for the period of T0: 1961-2001 - 40 years; Projecting comprises the derivation of precipitation values during the time periods of ; T1: 2011-2030), T2: 2046-2065 and T3: 2080-2099 at synoptic stations using three of standard scenarios: A1B, A2 and B1. These values are then used to map the climate zoning, which show: (i) climates at T1 are still similar to T0 and if any difference, precipitation increases; but changes are likely at T2 and T3 periods; (ii) the climate is moving toward a peakier regime at the northern region but drier towards the central region; and (iii) precipitation is likely to decrease in some of the zones. Thus, the results underpin the need for more responsive policymaking and should this not be realised in the next 5 to 10 years, the future seems bleak, as the loss of Lake Urmia and the depletion of aquifers are likely to be permanent, inflicting immigration from the region.

Linking Spatial–Temporal Changes of Vegetation Cover with Hydroclimatological Variables in Terrestrial Environments with a Focus on the Lake Urmia Basin

Investigation of vegetation cover is crucial to the study of terrestrial ecological environments as it has a close relationship with hydroclimatological variables and plays a dominant role in preserving the characteristics of a region. In Iran, the current study selected the watersheds of two rivers, Nazloo-Chay and Aji-Chay, to systematically investigate the implications and causes of vegetation cover variations under changing environments. These two rivers are among the essential inflows to Lake Urmia, the second largest saline lake on Earth, and are located on the west and east sides of the lake, respectively. There has been a debate between the people living in the rivers’ watersheds about who is responsible for the decline in the level of Lake Urmia—does responsibility fall with those on the east side or with those on the west side? In this study, the normalized difference vegetation index (NDVI) was used as a remotely sensed index to study spatial–temporal pattern changes in vegetation. Moreover, the temperature, precipitation, and streamflow time series were gathered using ground measurements to explore the causes and implications of changing vegetation cover. Discrete wavelet transform was applied to separate the different components of the time series. The Mann–Kendall (MK) test was applied to the time series on monthly, seasonal, and annual time scales. The connections and relationship between the NDVI time series and temperature, precipitation, and streamflow time series and any underlying causes were investigated using wavelet transform coherence (WTC). Land use maps were generated for different years using a support vector machine (SVM) in the final stage. The results indicated that the most dominant monthly, seasonal, and annual hydrological periodicities across the watersheds are 8 months, 6 months, and 2 years, respectively. The increasing vegetation cover during stable hydro-environmental periods revealed unusual conditions in the Aji-Chay watershed and reflected agricultural expansion. The WTC graphs indicated sudden changes in mutual periodicities and time-lags with different patterns between variables, which indicates the increasing anthropogenic activities in both watersheds. However, this was more dominant in the Aji-Chay watershed. The land use maps and investigation of the averaged NDVI maps also denoted that the areas of cultivated land have increased by 30% in the Aji-Chay watershed, and crop types have been changed to the crops with a higher demand for water in both watersheds.