Analysis of Hydrology Cycle in the Urmia Lake Basin with the WetSpass-M Model

Lake Urmia is the largest interior lake in Iran. This lake, as an effective ecosystem unit in northwest of Iran, highly contribute in the ecology of the region. The water level of Lake Urmia has dropped between 6 and 7.40 meters that has reduced the area of water zone. This reduction has leaded to increase in salty marsh, since1995. By May 2017, the water level was 3.11 m lower than the ecological balance. Expansion of salt marshes is due to successive droughts and an increase in water harvesting from the surface and ground water sources. This phenomenon can promote dust and salt storm occurrence, and lead to the death of the lake ecosystem, compulsory migration and population health threats of more than 10 million people. In order to optimal long-term planning and management of the available water resources, a better understanding of the temporal and spatial variations of water balance components (especially actual evapotranspiration, surface runoff, and groundwater recharge) is essential. A review of various research findings around the world shows that the WetSpass-M model is a suitable model for the spatial simulation of surface runoff, actual evapotranspiration and groundwater recharge in basins. The main aim of this paper was to analyze spatial distribution of annual components of hydrology cycle in the basin of Lake Urmia, using WetSpass-M model during 25 years (1992-2017). The method adopted in this study was analytic. Climatic, hydrological and land use data were applied in this analysis. Climatic and hydrological data were provided from meteorological stations, hydrometric station information and observed wells respectively. In this study, the satellite images and field studies were applied to determine land use. These images were downloaded from the site of EarthExplorer. The original Wet Spass-M model is a quasi-steady state spatially distributed water balance model scripted in Avenue and used to predict hydrological processes at seasonal and annual time steps. Since the model is a distributed one, the water balance computation is performed at a raster-cell level. Individual raster water balance in this model was obtained by summing up independent water balances for the vegetated, bare soil, open- water, and impervious fraction of each raster cell. The total water balance of the given area was thus calculated as the summation of the water balance of each raster cell. Precipitation was taken as the starting point for the computation of the water balance by each of the above mentioned components of a raster cell. The rest of the processes (interception, runoff, evapotranspiration and recharge) follow in an orderly manner. To validate the results of Wet Spass-M model, the coefficients of Nash-Sutcliffe Efficiency and RMSE-Observations Standard Deviation Ratio were used. The basin of Lake Urmia has been affected by many climate and human changes that have caused Lake Urmia Crisis. During the study period, runoff declined but temperature and evaporation increased. Land use has also changed widely. These changes included dry farming and rangelands convert to settlement and increase in area of irrigated farming. About 3043 km2 of lake area has been reduced and added to salt marsh. The average depth of ground water has decreased by 7.4 meters. The analysis of simulation results indicated that Wets pass-M model works properly to simulate hydrological water budget components in the Urmia Lake Basin. According to the results, in 1992, the highest runoff occurred in the western part of the basin with the highest rainfall, and all groundwater in the southern and western parts of the basin was well recharge. In the year 2017 most of the runoff and groundwater recharge was confined to the southwestern part of the basin. In 2017, Lake Urmia experienced higher evapotranspiration than the year 1992. In 1992, 58.42% of the basin precipitation was spent on evapotranspiration, 7.20% for surface runoff, 31.18% for groundwater recharge and 3.2% for interception. In the year 2017, these changed to 55.49, 1.55, 39.77 and 3.19%, respectively. Among the simulated components during the study period, the runoff has the highest coefficient of variation and the lowest groundwater recharge. Also during the 25-year statistical period, eastern parts of Urmia Lake (including: Ajab Shir, Azarshahr, Maragheh and Shiramin) had the highest coefficient of variation in all studied components. The southwestern parts of the basin were in better condition.