مجله تحقیقات منابع آب ایران
سال نوزدهم شماره 2 (پیاپی 65، تابستان 1402)

Evaporation is one of the main sources of water loss. Various methods were introduced to estimate evaporation and evaluating their performances in saline water bodies is of great significant. Accordingly, the aim of this study was to use the remote sensing images in evaporation estimation models applied to a saline water body and evaluate the results. Accordingly, using Moderate Resolution Imaging Spectroradiometer (MODIS) images and meteorological data, evaporation from the Urmia Lake was calculated by employing FAO56-PM, Priestley-Taylor, Kimberly-Penman, Hargreaves-Samani, and METRIC methods and the spatial distribution of evaporation was mapped. The result of this research showed that the evaporation is not evenly distributed over the selected saline water surface and considering a constant value of albedo for the whole surface would result in an error in the evaporation estimation. The obtained result indicated that combined methods give more reliable results compared to the other methods since they consider all effective parameters.

Water quality management in inland lakes requires continuous monitoring of chlorophyll-a (Chl-a) concentration and trophic state. As a critical variable of eutrophication, concentration of Chl-a in the northern part of the Lake Urmia was modeled using Multiple Linear Regression (MLR) and Artificial Neural Networks (ANN) models developed based on Landsat-8 and Sentinel-2 satellite images. Based on Landsat-8 images both models (ANNLandsat-8, MLRLandsat-8) accurately estimated Chl-a concentration in the north of Lake Urmia, while models based on Sentinel-2 images (MLRSentinel-2 and ANNSentinel-2) showed poor performances. Moreover, the ANN models performed slightly better than MLR models based on both Landsat-8 and Sentinel-2 images. According to the better performance, the optimum ANNlandsat-8 model (with a hidden layer) was used to analyze the spatiotemporal variation of Chl-a concentration and the trophic state index (TSI). In the northern part of the Lake Urmia, analysis of the spatial pattern of Chl-a concentration showed an increase towards the central deeper parts and a decrease towards the causeway. Furthermore, the average concentration of Chl-a and TSI in the northern section of the lake increased significantly from February to July followed by a drop between July to September and then a rise between September and October. Based on the optimum ANNLandsat-8 model, northern Lake Urmia experienced acute mesotrophic conditions in February and September of 2016, and mild eutrophic conditions in July, August, and October.

Lakes play an important role in the hydrological cycle and predicting the water level in them can provide vital information for the future management of lakes and their ecosystems. To this aim, in this research two models were developed and run for 1-, 2- and 3-month water level forcasts for the Lake Urmia in north-west of Iran; the tree post-pruning using the REPT method and the combined REPT model with the ROF-REPT. The water level time series data from 2001 to 2020 were divided into two categories for model building (from 2001 to 2014) and for model validation (from 2015 to 2020). Different input scenarios were developed and evaluated to find the most effective input scenario of climate variables. Finally, the developed models were evaluated through visual and quantitative criteria. The results showed that the combined ROF-REPT model has a higher performance than the single REPT model for all forecasts of 1-, 2- and 3-months. Nash-Sutcliffe Efficiency was obtained between 0.45 and 0.87 for single models and between 0.53 and 0.95 for combined models. Also, it was shown that the developed models are able to predict the water level up to 3 months ahead.

In recent years, due to drought, population growth, and the decline in groundwater reserves, the water poverty became an essential measure to consider. The main objective of this study is to quantitatively and qualitatively assess the of groundwater resources poverty based on two innovative effective and data-mining mathematical-analytical methods considering the six factors of capacity, environment, infrastructure and access, water resources, management and climate (57 variables) in the West Azerbaijan province for the period of 1390-1398 (2011-2019). The value of comprehensive water poverty index was obtained as 53.03 and 53.67 in two effective and data-mining mathematical-analytical models, respectively. The results showed that for the models the factors of water resources, management and climate cause relative unsustainability in groundwater resources systems. The comprehensive water poverty index has increased from 2012 to 2018, while the value of this index has reached a relatively stable status after the implementation of plans and projects related to groundwater resources management. The years 2011, 2013, and 2017 are respectively the milestones for the change of the status of the comprehensive water poverty index from very low to low, low to medium, and medium to high. As one of the unique innovations of the current research, considering the climate factor along with the extreme climatology phenomena in measuring comprehensive water poverty can play a key role in decision making and formulating management plans in water sector. Also, the development of a data-mining model which reduces the number of variables included in the measurement of the water poverty index, can effectively reduce the time, cost and resources used for the water projects. Finally, investigating the effect of the two sub-projects related to the Groundwater reclamation and balancing plan i.e. 1) equipping wells with smart measuring tools, and 2) culture and information project, on the water poverty index showed that the mentioned projects in some cases require management reforms that should be taken into consideration by the managers and the policy makers.

Determining the contribution of each of the effective processes to river flow plays an important role in how accurate these processes are estimated via hydrological modeling. Although water balance provides an overview of the volumetric changes of its components, the origin of the outflows and their temporal changes require utilization of approaches based on water tracking. In this study, we developed a three-dimensional physical and integrated hydrological model and coupled it to a water tracking model (ParFlow-CLM-EcoSLIM) to determine the contribution of rainfall, snowmelt, and groundwater to streamflow and evapotranspiration. Also, the distribution of the travel time of outfluxes has been simulated and studied. To demonstrate the applicability of the developed models, we chose the Godarchay basin, located in the southwest of Lake Urmia, as the study area. The results showed that snowmelt is the main source of river discharge and evapotranspiration in the region, such that the average contribution of snowmelt, rainfall and groundwater to the runoff production during a water year, is equal to 56%, 5% and 39%, respectively. Also, about 55% of the incoming snow during a water year is stored in the soil after the process of melting and infiltration, and is then removed from the system in the following years; while only 22% of new rain is stored in the system and 78% of it leaves the system in the same year.

Controlling water consumption in agricultural sector requires an appropriate understanding of the interplay between water resources, water consumption and agricultural economy. This study aimed to develop two hydrological and agro-economic models in the Mahabad study area (located in south of the Lake Urmia) in order to investigate the effects of climate change on the volume of water entering the Mahabad dam, explore long-term changes in gross irrigation needs, and study the impact of the crop pattern change on the gross irrigation need and the agricultural economy of the region. The results showed that if the agricultural water consumptions are controlled up to the year 1419 (Persian Calendar), the increase in the volume of water entering the Mahabad Dam under the climate change scenarios A1B and B1 can reduce the current withdrawal from surface and groundwater sources. It would also promote the possibility of release from the Mahabad Dam to partially provide the environmental flow of Lake Urmia. We further found that the net value of the crop production in the past years was much lower for wheat and barley compared to other crops, which explains the lack of economic justification for the cultivation of these two crops. The amount of production and the net value of sugar beet production showed a significant growing trend, which is in a clear contradiction to the policies of reducing agricultural water consumption by 40%. In case of increasing the cultivated area of water-rich crops in the region, the greatest stress on groundwater resources will be under the climate change scenario A2.

In this research, a new framework of socio-hydrological modeling framework has been developed in order to evaluate the performance of human-water systems. For this purpose, a comprehensive hydrological model has been developed by combining SWAT and MODFLOW models to simulate surface and underground water resources. Then by using Value-Belief-Norm Theory, the effective factors in the water consumption behavior of farmers are identified. Finally, by combining the SWAT-MODFLOW model and the Agent-Based Model based on the theory of VBN, the behavioral pattern of farmers in choosing the type of cultivation and irrigation method has been evaluated. The theoretical framework of the VBN theory and the behavioral rules of agents in ABM are designed based on the data collected from Mahabad plain farmers through field questionnaires. Afterward, an analysis and investigation were conducted on the response of the socio-hydrology model that was developed, utilizing climate change data from the 6th IPCC report and the ACCESS-CM2 model, for the planning horizon. The results showed that those farmers who are below the poverty threshold try to improve their unfavorable economic situation by choosing profitable crops for farming. Therefore, if no fundamental change is made in management policies in the future, the climate change will reduce the profit within the agricultural sector and the pattern of cultivation will change towards crops with high profits and yet high water consumptions. If the management methods remain unchanged in the future, the yield of the crops, the income of the farmers in the region, and at the same time the inflow to Lake Urmia from the Mahabad River will decrease significantly. Therefore, it is recommended to adjust the management policies as a way to deal with the effects of the climate change. In general, the results of the present research can be considered for future planning and policies and for estimating how changes in economic and psychological factors for farmers affect the restoration of Lake Urmia.

In the past years the climate change has altered the behavior of river flow and led to more frequent extreme hydrological events such as flash floods with high sediments. This has made it very important to know the different characteristics of river sediments when planning for and designing water structures. In this study, a new Standardized Sediment Index (SSI) was developed and different characteristics of sediment, including probability density function (PDF), magnitude, intensity, etc., were determined for the western of Lake Urmia basin using a Monte Carlo simulation process. For this purpose, first, the sediment data was determined according to different models of rating curve, and then the synthetic data series of sediment (1000 series) were generated using a suitable stochastic model and were used to determine different characteristics of sediment. The results showed that in most stations, the method of estimating the rating relationship according to the innovative method of this study, i.e. using the flow discharge index method to classify the relationship between flow and sediment, has the higher performance compared to other methods proposed in different studies. Also, the PDF of sediment data completely follows the normal distribution, as expected from a normalized natural process, and has a systematic behavior with skewness data. Finally, the results of this study are a comprehensive guide for accurate and real inference of river sediment phenomenon according to the SSI index and can significantly reduce the damages caused by sediments.

One of the important consequences of the climate change on extreme floods is the change in their frequency, timing and magnitude. In this research, the seasonality of flood in the Urmia Lake basin was analyzed based on the extreme flood data from 14 stations. This work was done in the statistical period of 2003-2019 using the new method of circular statistics. The uniformity of occurrence time of extreme floods (OTEF) was examined by Rayleigh-test and Kuiper-test, in three significance levels of 0.1, 0.05 and 0.01. The slope of the trend lines for the OTEF were estimated using the modified Sen’s estimator. The results of the Kuiper test indicated that there is no uniformity in the OTEF. It was found that there are two distinct flood seasons in the region including a) late March to mid-May (S1) and b) mid-September to early December (S2). The mean of seasonal strength index of events was equal to r̅=0.695. By dividing the year into above mentioned seasons, this index was obtained as 0.9 for the first season and 0.78 for the second season. The two eastern and western parts of the Urmia Lake had same seasonality strength in S1. However, in S2 the seasonality of the western part of the lake was stronger than the eastern part. In S1, on average, the OTEF in 40% of the stations had a negative trend while for the rest it showed a positive trend. For S2 the stations with negative and positive trends were respectively 11% and 78% of the total.

To study effects of the Lake Urmia’s causeway opening configurations at different water levels on the hydrodynamics and water quality of the lake, a three-dimensional biophysical model of the Lake has been developed based on FVCOM. The causeway opening configurations, proposed by the Urmia Lake Restoration Program, include the current situation of the causeway of the lake, without the causeway, without any opening, and a modified causeway with an additional 500-meter opening.The results of this research for the water level of 1274.1 m (the desirable restoration level which is called the ecological level) showed that in the absence of the causeway and in the case of adding an additional opening of 500-meter to the present causeway, the salinity difference between the north and south parts will be reduced respectively by 11 and 19 P.S.U. due to the flow exchange between these two parts. The closure of the causeway opening or reducing the flow exchange between the northern and southern parts will cause a decrease in dissolved oxygen (DO) and a doubling of chlorophyll-a in the northern part of the lake. At the water level of 1270.7 m (the existing water level), changing the causeway opening has no significant effect on the concentration of dissolved oxygen and the lake is always experiencing the low-oxygen condition. At the water level of 1272 m (the restoration level most likely to be achieved), changing the causeway opening increased the growth of phytoplankton, especially in the northern part, which can cause eutrophication of the lake. This study highlights that in addition to increasing the water level and reducing salinity, water quality indicators should also be addressed in the main objectives of Lake Urmia restoration plan.

Considering the critical situation of the Urmia Lake and the decision made by the government on its restoration, attention should be given to the effects of over-exploitation of the ground water resources in the plains upstream the lake plays a critical role in recharging and restoring the lake. In various areas of Iran, over-extraction of ground water resources for agricultural purposes caused land subsidence. Similarly in the plains around Lake Urmia, the agricultural development and pressure on ground water resources caused the subsidence of a significant area in the region. In this study, a subsidence map of the Urmia Lake’s surrounding areas was assessed by applying combined various geodetic observations. Results showed that there are 13 subsidence areas around Urmia Lake. The maximum rate of subsidence in these areas is 18.9 cm/yr and unfortunately 70 percent of the perimeter of the lake is subsiding. The area of subsidence is about 4000 square kilometers. Considering the subsidence hazards to water and soil resources of the region, ground water resource management, optimal cultivation pattern performance and modern irrgation methods should be accounted for urgently.