Background and Objective: In water resources management and operation, especially for dam reservoirs, supplying the minimum water demand for protecting the life of the different plant and aquatic species is essential. Allocating the environmental flow for Mahabad River, as one of the most important rivers in the Urmia Lake basin, is very crucial. Therefore, the purpose of this study was to estimate the minimum environmental flow for Mahabad River using Eco-Hydrology methods. Method: In this study, the environmental flow for Mahabad River was estimated by five methods, namely Tenant, Tessman, Flow Duration Curve (FDC) Shifting, Desktop Reserve Model (DRM), and Flow Duration Curve Analysis (FDCA). Findings: According to the results obtained in this study, to protect Mahabad River in the acceptable minimum environmental condition, the FDC shifting model considering class B (35. 1% MAR (mean annual runoff), equivalent to 2. 75 m³ /s) and DRM considering class B/C (27. 24% MAR, equal to 2. 13 m³ /s) led to approximately similar and acceptable results. Discussion and Conclusion: Generally, the FDC shifting model and DRM that consider different hydrological classes are preferable to other methods, and these methods can be used to determine the environmental flow for Mahabad River.

The Chaloos river originates from Alborz mountain and enters into the Caspian Sea in Chaloos city. Five stations were chosen in different areas for the study during 1371 to 1372 (1992-93). Total variation range of hardness decreased 1 to 5 station, but measure NH4 and N03 increased. 45 genera belongs to 4 phyla of phytoplankton as follows: Chrysophyta, Chlorophyta, Euglenophyta and Cyanophyta. Zooplankton existing in this river belong to animal classes, which had more abundance in Sarcodina and Monogononta. The Benthos river establish Insecta larvae of Ephemeroptera, Coleoptera, Diptera, Plecoptera and Odonata (Orders). Chaloos fishes included to 4 families, 10 genera and 12 species. Cyprinidae consisted 66.7% or total fish and had maximum diversity at the various stations.

Introduction: Despite being helpful to explore and analyze large multidimensional datasets, visualization Techniques have been rarely considered in hydrology. One of the techniques is Pixel-Based (Raster-Based) graphs. Pixel-based graph is a graphing technique that maximizes displayed information using a pixel or raster-based approach. Materials and Methods: This study two types of raster-based graphs, including Raster-Hydrograph and Raster Hyetograph were evaluated, for Gamasiyab Karstic Spring located in Nahavand. The graphs were drawn by applying discharge and rainfall daily information of gamasiyab spring in 1969-2018. The MATLAB was employed to draw the graphs. To calculate the spring discharge, recorded data from Sang Sorakh and Variane Canal station were used. The data gathered for Sang Sorakh and Variane were recorded from 1969 and 2005, respectively. Thus, the spring discharge was the summation of both stations. The maximum, minimum and average discharge was, respectively, 37. 97, 0. 3 and 4 m3/s. It is important to note that the basin area is about 60 Km2. Results and Discussion: By applying the graphs, six different phenomena were investigated: 1. Snowmelt: According to the raster hydrograph of the Gamasiyab spring, snowmelt occurs in the first 200 to 300 days of year (e. g. early April to late July). According to this graph, during the recent years, snowmelt period shortened. As of 2004, that the number of snowmelt days showed a considerable reduction as compared to the previous years. This issue has become more intense for the years after 2013 indicating a change in the spring discharge regime. 2. Drought: According to the raster hydrograph of the Gamasiyab spring, droughts were observed in 1998 and 1999. 3. Storm Flow: According to the raster hydrograph of the Gamasiyab spring, a storm flow was observed in the middle of April, 1986. Storm flows were also observed in late February of 1986 and 2005, and the late March of 2016. 4. Dry Year: Dry Year is a year that the discharge is less than the average. 2008 and 2009 were the examples of dry years. In addition, 2014 was one-year low water. 5. Dry Month: Determine dry months are used for baseflow separation. In dry months, discharge is due to baseflow, and rainfall and snowmelt play a very small role in the discharge. 6. Monthly changes: Monthly changes happen when rapid changes in discharge are observed from one month to another. For example, the discharge regime suddenly changes from a dry to wet condition. According to the raster hydrograph of the Gamasiyab spring, the monthly changes in April and May, 2014 were observed. It was observed that the rainfall was almost equal to 0 in June to September. In the other words, rainfall period is from early November to early June. Maximum rainfall is in April and May. Better results can be achieved by using both Raster Hydrograph and Raster Hyetograph. Discharge of Gamasiyab spring is affected by snowmelt and groundwater flow since late May to late September, and rainfall has no effect on spring discharge in this period. According to these graphs, it can be also concluded that springtime rainfall was impacted with one-month lag time. According to raster hydrograph, the minimum discharge occurs in October, however, the area receives rainfall during October based on raster Hyetograph. Therefore, the discharge increase in the November can be attributed to the precipitation falling during October. Conclusion: Main benefits of this graphs are: 1. a way to view large datasets. 2. Quickly review and interpret. 3. Develop new types of products. 4. Cost and time efficiency. This method is able to show systematic error, missing data, outliers, comparison different places, potential new products. Results show that the snowmelt period in Gamasiyab spring decreased from 1969 to 2018. This period shortened from 100 to 30 days per year. The year of 2008 was the driest year during the statistical period of the spring, and a drought was also observed in 1998. According to raster hydrograph, the driest month was found to be October. Determining this month is very useful for base flow separation. One can conclude that these graphs including large amount of information, accelerate the processes of scanning and interpretation.

This paper provides an overview of the hydrology and water use in the Zayandeh Rud basin based on the data available over the 11- year's period 1988-1998. The inflows into Chadegan reservoir, the releases from the reservoir, and the extractions along the river for irrigation and other purposes are considered, and a rapid water balance of the basin is performed. Inflows to the Chadegan reservoir, which serves to collect and regulate the runoff from the upper catchments of the basin to better meet the downstream water requirements for irrigation, urban and industrial uses, follow a regular pattern with moderate variability. But the limited year-to-year storage in the reservoir makes the basin vulnerable to prolonged periods of drought. Water releases from the Chadegan reservoir also show a predictable pattern, with the only deviations occurring during flood events. There is a high reliability of meeting the water requirements during periods of peak demand. But releases during the winter months, at the end of the irrigation season, are lower and more variable. This results in low discharges in the Zayandeh Rud and reduced water quality, especially in the lower reaches of the river. A simple water-balance approach was used to estimate the proportion of return flows in the basin. An average annual value of 30% was obtained, with the magnitude of return flows being particularly important in the lower reaches of the basin. But more investigation, especially including groundwater and water quality aspects, needs to be carried out before a definitive value can be advanced. Given the limited supply of fresh water in the Zayandeh Rud basin, further water resources development and water management improvements can only be envisaged in there is scope for real water savings in the basin. This can be assessed if a basin-wide approach, leading to a good understanding of water use (and reuse) at the farm, system and basin levels, is adopted.

Current statistical methods may be unable to accurately predict recurrence intervals of rare, large magnitude floods. The usual procedure involves extrapolation from gauged hydrological records documenting 30–40 year records of observed (normally small) floods to the estimation of the quantifies and recurrence intervals of very large, rare floods. This Conventional approaches become less reliable as recurrence intervals exceed the length of the data base. If anything that happened in the past can happen at any instant with the same likelihood, then history provides no meaningful information and conventional method of addressing flood risk assessment can be improved by including information on past floods. Past flood information can be obtained from palaeoflood and from historical information. Documentary records can provide a catalogue of the largest flood events that curried during periods of settlement, while palaeoflood investigations using palaeostage geological indicators can document the magnitudes of the largest floods over well defined periods of time (usually from decades to millennia), and provide evidence of all other events below or above specified flow stages or thresholds. For historical flood data, human observation is required, but the modern hydrological procedures employed at gauging stations do not apply. Both sources are types of non-systematic information and use the same statistical analysis approach. palaeoflood and historical flood data provide a feasible solution for assessing and mapping flood risks, and planning flood-prone zones. These improved flood-potential estimates using palaeoflood and historical flood data also have significant beneficial economic and environmental implications, related to floodplain planning, management design of hydraulic structures, management of critical water-resources and environmental conservation issues....

Estimation methods of parameters of fuzzy least-squares regression have very sensitivity to unusual data (e.g. outliers). In the presence of outliers, most of the existing estimation methods of parameters of this kind of models using least-squares approach provide unexpected and unreliable estimators with amounts of errors. Therefore, in this paper a robust least trimmed squares fuzzy regression model is described for modeling for crisp input-fuzzy output variables. In this approach, the constructed target function in model parameter estimation problem in such a way which minimizes the sum of the h smallest squared residuals. This method has an algorithm that estimates the optimal values of the parameters based on different selected combinations of h good observations of the data set of size n. Therefore, this method has the ability of reducing the effects of such a data in estimation of the parameters of the model. Finally, the investigated fuzzy regression model is applied and studied to modeling real-world data set in hydrology which sometimes contains outlier points. In this regard, a comparison study between the proposed method and ordinary least squares fuzzy regression method is considered. The comparison results of the applied study reveal that for this particular data set the proposed method performs better fitting than the well-known ordinary fuzzy least-squares regression model. Also the proposed method identified the points that have bad effect on estimation problem of the parameters.

Introduction: Agricultural development upstream of Tashk and Bakhtegan lakes along with droughts of the 2000s, has led to a sharp decline in the water surface of the lakes. This study demonstrates the potential of social-hydrology modeling to describe coupled human-water systems with simple concepts and relationships. Methods: The focus of this study is on the development of a Sociohydrological conceptual model in order to simulate the interactions between community response and hydrology in the TashkBakhtegan basin. For the social submodel, the variables of community sensitivity and behavioral response are used, and for the hydrological submodel, the developed water balance model for the arid and semi-arid basins is used. Due to the vastness of the basin and the various features in different regions, it has been hypothesized that changes in human preferences and community sensitivities for upstream and downstream residents of the basin may be different. The time range of this research is from 1996 to 2013. Findings: The selection of factors affecting the community sensitivity was an acceptable choice, because of considering the average error less than 10% in the simulation of cultivated areas. The results of hydrological submodel by considering two soil layers with the the calculated cultivated area as an input, showed the acceptable accuracy of the model in the ability to simulate streamflow in the Tashk-Bakhtegan basin. Conclusion: The results showed that in the basin upstream areas, which has more rainfall and water resources, the community's perception of the threat to their quality of life is low and the priority of its residents is tendency to use more water and land resources. But in the downstream areas, with environmental issues and scarcity of water resources, people with a high sense of threat to their quality of life have shifted their priority to less use of water and land resources.