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Introduction The study of surface water quality control in water resources and environment management programs is very important. Surface water is one of the most important water sources that have crucial impact on agricultural, industrial, drinking and electricity production activities. Due to insufficient water sources with good quality and the increase in population growth rate and as a result of the increase in demand, the study of water quality parameters is very important. The Water Quality Index (WQI) serves as a prominent indicator in classifying surface water quality. Moreover, in recent years, the TOPSIS method has gained traction for evaluating water quality. This approach, known for its simplicity, is increasingly utilized in prioritizing river water and assessing its quality. Through this index, various components of water quality are condensed into a single numerical value, effectively expressing overall water quality. To ascertain the weight index, Shannon's entropy method was employed. Furthermore, to assess water suitability for drinking, agriculture, and industrial purposes, Schuler, Wilcox, and Piper diagrams were utilized. These diagrams provide valuable insights into the quality of water, aiding in decision-making processes regarding its utilization across different sectors. Therefore, the results of this study also confirmed the effectiveness of the TOPSIS method in identifying contaminated stations. Materials and Methods This research focuses on evaluating the water quality of three stations within the Aji Chai river watershed on an annual basis. These stations are identified as Arzanag, Akhola, and Markid. The assessment spans the years 2003 to 2021 and aims to classify water quality for both drinking and agricultural purposes. Utilizing the standards set forth by the World Health Organization, the surface water quality index of the Aji Chai basin is investigated to ascertain its suitability for drinking purposes. Shannon's entropy theory was used to prevent expert judgments in determining the weight of each parameter. TOPSIS method was used to classify eleven qualities including TDS, EC, pH, HCO3-, Cl-, SO42-, Ca2+, Mg2+, Na+, K+ and TH. In all the three stations water quality were ranked, based on TOPSIS numerical values. Also, in order to check the quality of drinking, agricultural and industrial water, Schuler, Wilcox and Piper diagrams were used. Results and Discussion The initial findings from the %RE error analysis revealed that throughout the entire statistical period (2003 -2021), the %RE values were consistently close to zero, with the majority being positive. This suggests that the total number of cations surpasses the total number. In terms of the Shannon water quality index, the results indicate that Markid station exhibited the highest index value at 945.92, while Arzanag station displayed the lowest value at 127.365 among the surveyed stations. The results of the water quality index showed that Arzanag and Akhola stations are in an average condition (100 < EWQI < 150) and Markid station is in a very poor condition (EWQI > 200). According to Schuler's diagram, it was found that the water of Arzanag station is in the average level in terms of water quality, which is in a good position in terms of quality compared to the other two stations, while the water of Akhola station is in a good position. In the range of poor quality, Markid water was undrinkable, which ranked worst among the three stations. According to the Wilcox diagram, it was found that the water quality of Markid is very poor, which is even outside the boundary of the Wilcox diagram, while the water of Arzanag station was ranked 1st in terms of quality. Arzanag water is in C4S2 class in terms of quality. Finally, the water class of Akhola station was placed in the C4S4 class (in the Wilcox chart), which shows very low water quality. According to the TOPSIS method, the first priority in terms of water quality pollution belonged to Markid station. Two other stations, including Akhola and Arzanag, were ranked second and third in this respect. Therefore, the most important station in this basin is Markid station. Conclusion The results of Shannon water quality index showed that among the stations, the highest index value is related to Markid station with a value of 945.92 and the lowest one is related to Arzanag station with a value of 127.365. According to Schoeller diagram, it was found that the water quality of Arzanag station is average, compared to the other two stations, it was in the right place and the water of Akhola station was in the range of poor quality. The quality of Markid water was found to be undrinkable, which was the worst one among all the three stations. The range of TOPSIS values in different stations is between 0.054 and 0.894, which belonged to the Arzanag and Markid stations, respective ly. According to the results of the Arzanag station, the best water quality condition and the Markid station were assigned the worst water quality condition among all the three stations. [ABSTRACT FROM AUTHOR]

Background and Objectives One of the main elements of hydrological cycle is evapotranspiration. Accurate estimate of this element is so crucial in agricultural water management. The reference crop potential evapotranspiration (ET0) is defined as the rate of evapotranspiration from a clipped green grass with a height of 8-12 cm, well irrigated and without nutrition deficiency in a given time (mainly day). In such conditions the hypothetical effective grass leaf area index is 2.88 m²m-2 (Allen et al. 1998). The aim of this study is to find the most suitable method among the three empirical ET0 models that needs less meteorological parameters in Urmia Lake basin. For this purpose, daily climatic data of the nine weather stations selected across the Urmia Lake basin were used. Methodology The study area is the Urmia Lake basin located in north west part of Iran with an area of about 52000 square km. This basin faced with water deficiencies problem in recent years that led to shrinkage the water surface of the lake dramatically. The water in the lake is hypersaline and was found as the second saline lake after the Dead Sea in middle east. The three candidate models used here are the Turk, Doorenbos and Pruitt (DP), and Blaney-Criddle (BC) models. Their accuracies were evaluated with the FAO-56 Penman-Monteith (FAO56PM) model (Allen et al. 1998). The main reason in selecting the FAO56PM method as a bench mark to evaluate other three methods is that this approach is physically based and explicitly incorporates both physiological and aerodynamic parameters (Sentelhaset al. 2010). Also, this method was used as the bench mark method in previous published papers (Allen et al. 1998, Sentelhaset al. 2010, Tabari 2010). Data in daily scale were collected from Islamic Republic of Iran Meteorological Organization (IRIMO). The data are the wind speed in 10 m height (U10), maximum air temperature (Tmax), minimum air temperature (Tmin), relative humidity (RH) and actual sunshine hours (n). The U10 converted to the two m height wind speed (U2) using the equation presented in Nandagiri and kovoor (2005). The mean daily air temperature (Tmean) evaluated using the arithmetic mean of Tmax and Tmin. All the equations used in estimation of other parameters are included in the work of Dinpashoh et al. (2011). The quality of data inspected visually and few missing values constructed using the most suitable method for each of the climatic parameters (Hasanpour Kashani and Dinpashoh. 2012). The performances of the candidate models wereevaluated. using the three criteria which are the coefficient of determination (R²), root mean square error (RMSE), and mean absolute error (MAE). Findings Results showed that the medians of R² obtained for the stations in the two models namely Turk and BC were equal to 0.9, but it was about 0.75 in the case of DP model. The median of RMSE obtained for Turk model was about 2 (mm day-1), however, it was about 2.2 and 3.5 (mm day-1) for the BC and DP models, respectively. The median of MAE for the selected stations was less than 1 (mm day-1) obtained for Turk, however, it was 1.9 and 2.5 (mm day-1) in the case of BC and DP, respectively. Both the two empirical models namely Turk and BC had similar performances which can be used as the alternative method to FAO54PM in Urmia Lake basin. In order to solve the water crisis in Urmia Lake basin it can be suggest to modification of crop pattern, i.e. cultivation of those crops that need less water, improving water efficiency by using modern systems such as drip irrigation, sprinkler irrigation and so on. Restriction of digging new deep wells in this basin is recommended for sustainable water use. Finally, some serious and quick works should be done in this basin to restrict pollution of both surface and groundwater. It can be claimed that the findings of this study can help water authority managers in better management of water resources across the basin. Conclusion In this research potential reference crop evapotranspiration estimated in the nine stations selected in (and/or the adjacent borders of) Urmia Lake basin. Three candidate models namely Turk, Doorenbos and Pruitt (DP), and Blaney-Criddle (BC) models compared with the FAO56PM output in this study. Based on the two performance criteria namely R²and RMSE it can be concluded that the Turk model having the R²equal to 0.9 and RMSE equal to 2 (mm day-1) is the preferable one among the others for the region under study. It can be suggested that this conclusion is valid when the candidate empirical models limited to the aforementioned three models. It is recommended to use other empirical models for better estimation of ET0 in the Urmia Lake basin. It can be claimed that the findings of this study can help water authority managers in better management of water resources across the basin. [ABSTRACT FROM AUTHOR]

Reference evapotranspiration (RET) plays a critical role in irrigation planning and is needed for the determination of water demands of crops. Thus, in the present study, trends in RET were identified over Bikaner located in the Thar Desert (Rajasthan) in India using the non-parametric Mann-Kendall (MK) test. First, RET values were estimated through the Penman-Monteith method for different time scales using meteorological data for 39 years from 1967 to 2005. Second, the effect of significant lag-1 serial correlation was removed from the time series of RET by pre-whitening. Third, trends were investigated using the MK test. RET was found to decrease significantly at Bikaner during annual, pre-monsoon, monsoon and post-monsoon time scales. On probing the causal meteorological parameters responsible for the observed RET trends in the Thar Desert, it was witnessed that wind speed dynamically influenced the observed RET changes at the annual time scale and all the four seasons over the Thar Desert. The maximum temperature, followed by relative humidity, influenced the RET trends at annual and seasonal (winter, pre-monsoon and monsoon) time scales. The calm atmosphere witnessed over this arid site substantiates RET decreases over this Thar Desert site. The results of this study support that the evapotranspiration decreases over Bikaner are controlled mainly by trends in the aerodynamic component, i.e. by the effects of significant wind speed decreases on RET, than the changes in the radiative component over the arid site located in the Thar Desert. [ABSTRACT FROM AUTHOR]

The aim of this research is to allocate the river's self-purification (acceptance capacity of pollution) fairly between the beneficiaries (pollutant sources) using bankruptcy theory. For this purpose, four bankruptcy rules (CAE, CEL, P, and TAL) were called using the link of the water quality simulation model (QULA2Kw) to an evolutionary optimization algorithm (multi-objective imperialist competition algorithm (MOICA)). The objective functions were reducing polluters' wastewater treatment costs and preventing biochemical oxygen demand (BOD) violations of the standard level along the river. The applicability of the approach is demonstrated by the case study that was carried out on the Dez River in Iran. According to the results, the CEL scenario is the most effective method for the Dez River when taking into account the most optimal state for both objective functions (selecting the best compromise solution from the Pareto front). This is because it has the lowest violation value of the standard level for BOD along the river when compared to other scenarios. Alternatively, when considering Solution 20, which focuses on the maximum cost of treating the polluters while staying within the acceptable level of pollution in the river, the results indicated that the CEA rule emerged as the most favorable option. This is due to its lower treatment cost (156.9 (1000$)) and higher pollution discharge to the river (681.91 g/s)., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Evaporation, as the main source of water loss from closed lakes, makes a significant contribution to the water balance equation of the lake and can lead to changes in the chemical composition thereof. The objective of the study was to develop an equation for estimation of evaporation from the water surface with different depths and concentrations. To that end, 48 barrels were used to model evaporation at 6 different depths and 8 different concentrations of salinity. The experiments have been conducted in the same meteorological condition for all the barrels near the Urmia Lake. Data were collected in March 1, 2019, to Aug 31, 2019. Different equations fitted to data for each concentrations of salinity separately with different depths, and the equations with the least errors were selected. A model was then developed for the estimation of evaporation, considering the effect of salinity and depth, and the results were compared with daily measurements. The results were evaluated using the root mean square error (RMSE), correlation coefficient (CC), and Nash-Sutcliffe efficiency coefficient (NS). The results indicated that evaporation (Horizontal row) from water surface with high concentrations of salinity to low concentrations of salinity in different depths had an incremental trend. However, it can be seen in the vertical row that evaporation increased from low depth to high depth, and then decreased at a certain depth (120 cm) while the maximum evaporation rate belonged to 90-cm barrels for each concentration of salinity (in the vertical and horizontal row). At the end, the comparison of evaporation computed from the model and measured data showed that the model estimated evaporation at different depths and concentrations of salinity satisfactorily.

This study examined the sensitivity of reference crop evapotranspiration (ET 0 ) to climatic variables in a humid region in Iran. ET 0 was estimated using the FAO-56 Penman-Monteith (PMF-56), Blaney-Criddle (BC), and Hargreaves-Samani (HG) methods. Sensitivity analysis was performed by two distinct methods which were (i) changing the value of a certain climatic parameter in a range between ± 20% of its long-term mean with an increment of 5%, and calculating the percentage of change in ET 0 , while the other parameter values were kept constant; and (ii) calculating the sensitivity coefficients (SCs) for each of the climatic variables. For each of the climatic parameters, the Iso-SC maps were plotted using the Arc-GIS software. Results indicated that the most sensitive parameter for ET 0 was the maximum air temperature (T max ) by PMF-56 and HG methods. Increasing T max up to 20% led to an increase in ET 0 between 8.5 and 15%, at the selected stations by PMF-56. In contrast, the less sensitive parameter for ET 0 was the minimum air temperature (T min ) for PMF-56 and T mean for HG. For PMF-56, increasing the minimum relative humidity (RH min ) to 20% led to a decrease in ET 0 in the range between 0.5 and 5%. The highest values of SC in the cases of T max and T min were found to be equal to 0.8 and 0.53, respectively. Similarly, the SC in the case of RH min varied between - 0.29 and - 0.0038. This range for wind speed was between 0.06 and 0.22 and in the case of sunshine hours it was between 0.272 and 0.385. These findings would be useful in the scientific management of water resources in the region.

Runoff prediction, as a nonlinear and complex process, is essential for designing canals, water management and planning, flood control and predicting soil erosion. There are a number of techniques for runoff prediction based on the hydro-meteorological and geomorphological variables. In recent years, several soft computing techniques have been developed to predict runoff. There are some challenging issues in runoff modeling including the selection of appropriate inputs and determination of the optimum length of training and testing data sets. In this study, the gamma test (GT), forward selection and factor analysis were used to determine the best input combination. In addition, GT was applied to determine the optimum length of training and testing data sets. Results showed the input combination based on the GT method with five variables has better performance than other combinations. For modeling, among four techniques: artificial neural networks, local linear regression, an adaptive neural-based fuzzy inference system and support vector machine (SVM), results indicated the performance of the SVM model is better than other techniques for runoff prediction in the Amameh watershed.