ندا جعفری

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.

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-, , 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. 

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. 

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.

The proceedings are accelerated, the litigants can access a website and fill out the forms Raise disputes related to arbitration procedures electronically and defend their claims. arbitration Online increases the speed and efficiency of arbitration. Document filing systems in databases It allows the parties to send many documents with considerable speed from any place geographically and at any distance without paying the lowest costs in virtual space. These issues It has caused the attention of various societies to the issue of online arbitration in legal systems. Although so far from arbitration There has been no mention of online in Iran's legal system, but the need to pay attention to it is felt more than ever can be Also, in French law, there is no supranational or EU-related instrument of online arbitration There is no set separately from offline arbitration. This issue is even resolved in relation to the setting 1 online disputes It is also true. Likewise, online arbitration is the same as normal arbitration It is adjusted. However, there are features for online arbitration that show this You must have distinct principles to set up a petition

Water is a treasure to be passed on to future generations, and it is now clear to the world that human well-being and industrial and agricultural development are all at stake unless the optimal use of water resources as well as integrated environmental planning and management become a key element of plans and investments. Water resources management is a set of various management measures, which is done to optimize the use of water resources and reduce economic, social and environmental damage. Sustainability assessment by indicators is useful for planning, management and educational purposes. Indicators should be easy to use, comprehensive and universal. They must also be accessible, understandable and valuable, revealing and comprehensive. Due to the importance of sustainable development, quantifying this concept of sustainable water resources management indicators is done by considering economic and social ecosystem considerations. The use of multi-criteria decision-making methods in water-related issues has been used by many researchers.

The purpose of this study is to investigate the stability of Gamasiab basin. The study area, Gamasiab catchment is one of the main sub-basins of Karkheh basin. Figure (1) shows the geographical location of the Gamasiab catchment. Figure (2) shows the algorithm of research steps. The studied indicators are as follows: Percentage of normal rainfall index (PNPI): Its basic concept is the ratio of actual rainfall to its normal amount over a period of time, expressed as a percentage and can be calculated on a scale (weekly, monthly, seasonal and annual). Equation (1) shows how to calculate this index. A standard precipitation index (SPI) was provided to monitor and determine droughts. This index is calculated in time scales of 48,24,18,12,9,6,6,3,1 months and one year (Equations 2 and 3). Surface water storage index (SWSI): The purpose of this index is to consider hydrological and meteorological characteristics as a single index (Equations 4 and 5). Standard runoff index (SRI): This index is obtained according to Equation (6). Available water index (WAI) This index includes surface water resources, groundwater and its difference from the needs of all household sectors of the agricultural industry (Equation 7). WEAP model: This model is flexible due to the data structure in a range of highly decomposed to highly aggregated modes. The input to the reservoir can be given to the model both through the hydrological model and as a time series . Integrated management of water resources and consumption was simulated in the WEAP model and its output was used in EXCEL software to calculate ASI, ESI, out-of-reach water supply reliability and fairness in water allocation. Figure (3) shows a schematic of the resources and uses of the Gamasiab catchment area. Reliability Index (REI) Reliability or reliability is the probability with which water allocated to the consumer meets its needs (Equations 8 and 9). Reversibility index (Res) The probability that a system will return to normal after a failure is called reversibility (Equation 10). Vulnerability index (Vul) The most widely used definition is the ratio of the total deficits to the number of steps in which the deficit occurred divided by the total need (Equation 11). Sustainability Index (SI) Sustainability Index Summarizes system performance metrics in an index to facilitate comparison and decision making between different water resources management and planning options (Equation 12). Environmental Indicators: The Agricultural Sustainability Index (ASI) is defined as the sum of the nominal ratio of agricultural demand in the time series. Environmental sustainability (ESI) is defined as the ratio of supply to demand in an environmental measure over time. The Wilcox Index The Wilcox diagram is based on the electrical conductivity (EC) values of water-soluble solutes in different classes. Schuler Index The Schuler Index divides water into six groups: good, acceptable, suitable, bad, drinkable in an emergency, and non-potable. Social indicators: Drinking water supply reliability index in the form of reliability of drinking water transmission links in which the amount of supply to demand is equal to 1. Justice in water allocation index (CV) This index shows the coefficient of variation of supply to demand ratio in all agricultural demands. Economic indicators: Profit to cost ratio (B / C) This index is obtained by dividing the profit on existing costs. The total value of production is obtained by subtracting the total costs of crop production from the gross value (the product of product yield per unit area multiplied by the unit price). Shannon entropy method was used to weight the indices, which can be calculated using relations 13 to 18. TOPSIS, CP and SAW multi-criteria decision-making methods were used to rank the indicators (relationships 19 to 32). Ranking options using different decision-making methods are different. Therefore, the Bordeaux counting method has been used for the final selection of the superior option. In this method, instead of using the evaluation values of each option, only their comparative rank, which is determined by using different methods, is used to minimize uncertainty in them (Equations 33 and 34).

In this study, multi-criteria decision making (MCDM) methods were used to rank the sub-basins of Songor, Sahneh, Kangavar, Harsin-Biston and intermediate in terms of economic, social, environmental and water resources criteria. The results of weighting the indicators by Shannon entropy method showed that the reliability index of drinking supply has the highest weight with 0.29. After that, out of reach water indices and WAI index with weights of 0.188 and 0.186, respectively, have the highest weights. The lowest weights among the indices are related to PNPI index with a value of 0.000053, followed by SWSI index with a value of 0.00018 and then the lowest weight is related to Schuler diagram index with a value of 0.00082. Finally, due to the ranking differences of the above methods, the Bordeaux counting group decision-making method was used for the final ranking. The results of this study using multi-criteria decision making methods including SAW, TOPSIS and CP decision making models showed that the most sustainable sub-basin in terms of economic, social, environmental and water resources for Gamasiab catchment in Kermanshah province is Harsin-Biston catchment (due to the usefulness of the calculated indicators),. The intermediate and Songhar sub-basins, respectively, have the ranks of 2 and 3 in terms of stability. The weakest sub-basins are Sahneh and Kangavar sub-basins in terms of criteria.

Determining water quality is of particular importance in water resources management. Today, due to the existence of numerous polluting sources of water resources, the chemical quality of water resources has been greatly reduced. The purpose of this study is to qualitatively classify the water resources of Gamasiab catchment area of Kermanshah province for drinking and agricultural uses and the quality of surface and groundwater resources. The qualitative data of five stations from 1358-97 and 5 wells were used. Qualitative data studied in this study are 10 parameters including: So4، cl، Hco3، ، ، TDS، EC ، pH and SAR. The results showed that according to the Wilcox diagram, all samples are in the C2S1 class range, which indicates good quality water for irrigation and agriculture. . According to the piper diagram, the facies is calcite water and fresh water type. River water is acceptable in terms of hardness and bicarbonate based on Schuler index in terms of hardness and in good range in terms of other parameters. The results of calculating WQI and GWQI indices show excellent water quality for surface and groundwater of this basin.

In the recent years, the failure of many bridges has reported due to local scour around abutment. Many studies have focused on reducing the scour with the help of structures reducing the destructive effects of flow. In this study, the scouring effect on two vertical wall abutments with different widths was investigated using clean water. Where the upstream face of the latter is protected with roughening elements as devices to intercept the down flow responsible for the formation of the principal vortex. Different sizes of the elements with thicknesses and protrusions equal to 0.025L, 0.05L, 0.1L, 0.2L and 0.3L (L is the length of the abutment) placed at different elevations on abutments were investigated. The optimum elevation of roughening elements obtained at 0.6L below the bed level. As the thickness and protrusion dimensions of the elements increases to 0.2L, scour depth around the abutment decreases, and after that increases if the element size become larger. In conclusion, the roughening elements with thickness and protrusion equal to 0.2L and placement of 0.6L below the sediment bed reduced the scour depth 30.4 and 32.8% at the small and large abutments, respectively.

As the international auditing standard no. 700 is revised and the International Auditing Standard 701 is set by the International Auditing Standards Board and both of them are executed since 15 December 2016, this research is aimed to examine the viewpoints of auditors on the current as well as the new audit report subject to recent changes in audit reports. This is a survey type research and data is collected through questionnaire. The statistical population includes audit managers and top level supervisors, partners in audit organizations and certified auditor members of the Auditing Organization and Certified Accounting Society. The statistical sample consists of 400 members of the statistical population that participated in the "Recent Changes in Auditing Reports" forum held in Feb-March 2018. From the 400 questionnaires distributed among the sample, 72 ones are considered as applicable. In order to analyze data, the one-sample t-test is applied. Research findings indicate that auditors have different opinions about advantages and disadvantages of the current audit report and believe in some necessary changes in the current report. Moreover, auditors confirm the new audit report and its partial and simultaneous execution in all economic units and accounting entities, as well as the disclosure of auditor tenure in the audit report. The research findings can convince standard setting authorities and Securities and Exchange organization to accept new auditing standards. Moreover, the research provides evidence of Iranian auditors' attitude toward new changes made in the auditing report