مجله تحقیقات منابع آب ایران
سال هجدهم شماره 4 (پیاپی 63، زمستان 1401)

Estimating the available water plays a vital role in planning water resources projects. The first step in assessing water availability is to calculate runoff in catchments. Moreover, it is necessary to study the effects of climate change on water components such as runoff since climate change directly affects the hydrological components and water resources. In this study, the status of the inflow to Tashk-Bakhtegan lakes as one of the most important lakes in the country was investigated. Because generation of runoff is a complex concept due to its nonlinear and multidimensional nature, various theoretical and physical models have been developed to predict runoff. The high dependence of these physical models on numerous parameters and maps, practically challenfged their efficiency in basins with limited observations. On the other hand, models based on artificial neural networks and fuzzy inference systems are considered applied tools that can help hydrologists in such circumstances. In this study, FFBPNN and ANFIS models and their combination with PSO and GA metaheuristic algorithms have been investigated in evaluating the runoff in historical conditions and under RCP and SSP climate change scenarios.  The obtained results showed that the FFBPNN and ANFIS models combined with the PSO algorithm (ANFIS_PSO) using precipitation, minimum temperature, and maximum temperature as inputs had better performance compared to other models with different inputs. The values of the correlation coefficient, root mean square error (m3/s), Nash-Sutcliffe coefficient and Kling Gupta were respectively 0.99, 2.07, 0.99 and 0.98 in the training period and 0.94, 3.61, 0.91 and 0.88 in the test period and 0.98, 94. 2, 0.97 and 0.98 in the training period and 0.93, 3.87, 0.85 and 0.88 in the test period. The results of this study can be used in investigating the effects of the above mentioned scenarios on important basins of the country and consequently in planning and managing water resources in the context of climate change.

In this study, long-term changes in the precipitation pattern and how they affect the future flood events were explored by collecting, completing and validating precipitation data in the Karkheh, Dez, Karun, and Great Karun Basins. Also, the depth and frequency of precipitation in the water year 2018-2019 have been carefully investigated. Finally, the quality of precipitation forecast and awareness by some official organizations has been discussed. The study area has a sufficient number and density of reliable meteorological stations. However, this does not hold for the synoptic stations in mountainous areas, such that only 4% of the stations have recorded data in more than 10% of the entire 30-year statistical period. The results showed that the climatic trend of the region is on average in the direction of decreasing precipitation amount. The investigation of rainfall pattern has revealed the continuation of high soil moisture due to the increase of low rainfall events in recent years, which can lead to enhanced probability of flood occurrence. The analysis of April 2019 precipitations showed that in the entire study area, the amount of precipitation was 24% to 108% higher than the last 10-year average. The return period of total precipitation in Ahvaz station in the water year 2018-2019 was 297 years, which is unprecedented. In addition, the forecasts of the Iran Meteorological Organization and the Water Research Institute for the flood of April 2019 in the Khuzestan province were significantly erronous compared to the observations.

Accurate estimation of the actual evapotranspiration (ETa) and analysis of its spatiotemporal variations is crucial for irrigation water management, particularly at local and daily scales. The Operational Simplified Surface Energy Balance (SSEBop) model is among the most efficient and practical single-source surface energy balance models based on remote sensing data. Nevertheless, limited studies are made to assess the performance of this model in Iran. In this study, a modified version of SSEBop (based on the use of local weather data, automatic calculation of daily reference evapotranspiration, and variable surface albedo) was introduced and its performance was examined over a 14-ha alfalfa farmland in East Isfahan. To this end, the model was calibrated and both the intermediate model outputs (e.g., surface temperature and albedo) and the estimated actual daily evapotranspirations were validated against the in-situ ETas obtained from a scintillometer and an adjacent automatic weather station. The results showed an acceptable performance (RMSE= 0.8 mm.day-1, r= 0.81) of the modified and locally calibrated SSEBop model for estimating daily ETa throughout the growth season. However, during and after harvesting, when the crop biomass was low (NDVI<0.4), the model failed. This study reveals the promising application of the SSEBop for operational irrigation management practices

Interactions and conflicts, or in general, the relationships between different stakeholders in a large-scale water resources scheme, are very important factors affecting the status of water systems. In this study, the conflict was studied, mapped, and rooted in a water system using the social network analysis approach, utility analysis, and conflict tree. After finding the major problems in a water system, influential stakeholders were first identified. Then, using the social network analysis method the relationships between these stakeholders were studied to estimate their conflicts. Next, by assessing the desirability of stakeholders, the ground of conflict emerging between them was investigated using desirability mapping. Using the output of the desirability analysis, social network analysis, and important problems recognition, the roots, core, and results of the conflict were presented using the conflict tree approach. The catchment area in the west of Tehran, namely the Kan River basin, has been studied using the mentioned method. The little interest of the municipal institution in utilizing groundwater resources, the problem of subsidence and the quality of water resources, coupled with the interest in expanding green spaces and urban development are among the challenge between the regional municipality and the regional water authority. The minor consideration for the management of illegal water extraction, return water, aquatic ecosystems, and water quality has been the cause of conflict between the agricultural institution and the regional water authority. It is also critical that the interest of the industrial sector is focused on development of industries and other interests are of less importance in this sector. The lack of interest in institutions such as the urban development stakeholder to consider the water cycle's importance in urban development is another challenging issue.

In arid and semi-arid regions, surface evaporation can be considered the main cause of water loss. Evaporation occurs at temperatures lower than the boiling point of water and it is an inevitable phenomenon and it plays an important role in the loss of water resources in countries according to their geographical and meteorological conditions. One of the main methods to reduce evaporation from the surface of open tanks, which is used in many hot and dry regions, is the use of physical and chemical coatings. In the current research, which was conducted with the aim of reducing the rate of evaporation from class A evaporation pans, it was tried for the first time to investigate the efficiency of three types of balls with monolayer composition of hexadecanol as an evaporation reducing coating. Three types of balls with a diameter of 7 cm made of propylene were used; balls with two holes, six holes, and no holes. In order to investigate the performance of these coatings in reducing the evaporation of class A pans, they were investigated for 2 months from 1400/6/1 to 1400/7/30 (two months). The measurement of evaporation has been repeated once every hour from 8:00 am to 5:00 pm and the resulted times series were analyzed statistically. The measured evaporation values were analyzed in SAS software and the comparison of averages was done at the 99% probability level based on Duncan's average comparison test. Results showed that the combination of hexadecanol monolayer and three ball samples had a significant difference at the 5% level in terms of changes in evaporation rate and temperature. The results of comparing the average effect of different coatings on the rate of evaporation showed that the control pan had the highest amount of evaporation among other pans, while the pans covered with the monolayer combination of hexadecanol and non-porous balls showed the lowest amount of evaporation. The comparison of average evaporation values in Duncan's test did not show any common letters which means that all pairs of coatings have a significant difference at the 5% level. The results showed that the combination of hexadecanol monolayer and non-porous balls with an efficiency of 86.7% contributed the most in reducing evaporation. While the combination of hexadecanol monolayer with two-hole and six-hole balls with efficiency of 59.6% and 56.7% were placed in the next priorities. Finally, the combination of hexadecanol monolayer and balls without holes were identified as the best evaporation reducing coating in the present study due to the appropriate surface roughness and the constant percentage of empty spaces over time.

Due to the increase in population and the uncertainty of safe water supply, the use of rainwater harvesting systems has gained popularity in recent years. This research has evaluated the technical and financial feasibility of these systems in the production of packaged water at Sari University of Agricultural Sciences and Natural Resources. In the first step, daily rainfall was predicted for the period of 2022-2047 using the historical data of Dashtnaz weather station in Sari and those of the GFDL-CM3 climate model. The daily Water balance modeling and financial indicators (IRR, NPV, and B/C) were used to analyze the technical and financial aspects of the systems with catchment levels of 200, 850, and 1700 m2. Findings showed that aiming at supplying the daily requirement drinking water of the university, increasing the daily treatment capacity of this system has no effect on its performance in this area. According to the financial index, storage tanks with volumes of 8, 20, and 40 m3 are suitable for systems with catchment levels of 200, 850, and 1700 square meters, respectivel The financial indicators (IRR, NPV and B/C) were respectively 45%, 917 million Rials and 1.2 for the catchment area of 200 m2, 103%, 4768 million Rials and 1.31 for the catchment area of 850 m2, and 117%, 8918 million Rials and 1.33 for the catchment area of 1700 m2

Considering the importance and status of monitoring the quality characteristics of water resources, it seems necessary to use technologies such as remote sensing that increase the speed and accuracy of water quality monitoring information. Turbidity is one of the key water quality characteristics which is one of the main sources of sediment in water bodies and directly affects issues such as sediment transport, aquatic life, and management of lakes and reservoirs. This makes water turbidity monitoring an important concern in the field of water resources management. Traditional and laboratory methods of monitoring are accurate but time-consuming and expensive. The use of scientific capabilities such as remote sensing can therefore be beneficial. In this research experimental methods and models developed based on neural network algorithms are used to estimate opacity parameter zoning maps. The main goal of this study is to investigate and compare different band combinations to estimate the turbidity parameter using the spectral data of Sentinel-2 and Landsat-8 satellite images. Considering the importance of the mentioned quality parameter and also the location of the study area, ground measurement of these parameters was a challenge; As a result, it is necessary and practical to use neural network and remote sensing capabilities for modeling. According to the investigations carried out in this study it can be concluded that due to the spectral data of Sentinel-2 and Landsat-8 satellite images, the zoning maps of water turbidity parameter can be estimated with good accuracy. Four different forms of band combinations (single bands, band ratio, spectral derivative ratio and normal difference index) have been used for which the detection coefficient value were 0.86, 0.83, 0.83 and 0.89 and the RMSE error were 3.26, 3.52, 3.43 and 2.79, respectively. Accordingly, each of the compounds is considered independently as the model input in the modeling process. The results showed that the band combination of the normalized difference index estimates much better results. However, considering the fact that the single band combinations also had good results with little difference from the normal difference index combinations’ derivative model and since it could reduce calculations, single band combinations can be used as best band combinations to estimate the water turbidity parameter in this study area.

Estimation of agricultural water consumption with unrealistic bases causes more aggravation of the current Iran water crisis. Accordingly using broader information, especially water budget components which received less attention, can be effective in enhancing such estimates. To this aim, this study developed a framework based on grouping of agricultural crops and the concept of "water footprint". The framework also includes an optimization module to examine consequences of the policies such as increasing self-sufficiency rates of agricultural crops under best optimum management on water budget. Accordingly, the consumption of agricultural sector for 2017 was estimated to be 64 BCM, which was associated with a negative balance of 5.5 BCM. Furthermore, the targets of the 6th national development plan (2016-2021) regarding three crop groups including oil seeds, sugar crops and maize were examined (target values were respectively about 3.2, 1.4 and 3.2 times of their productions in 2017). The results showed that by expansion of the cultivation area to achieve these targets, country’s negative water budget will increase to -12.5 BCM/yr. With the same assumption and a 30% reduction in vegetables and fruits, the negative budget would reduce to -10.5 and with the most optimum provincial crop patterns, it reaches -8.5 BCM/yr. What investigated here was an attempt for improving the estimation of agriculture water consumption, reducing related uncertainties and elucidating the alerting consequences of increasing self-sufficiency rates on the water balance. Nonetheless follow ups are needed to improve such methodologies.

Drought as a natural phenomenon is one of the most important challenges in water supply, especially in arid and semi-arid climates such as Iran. In this study, the hydrological drought has been investigated in the western sub-basins of Lake Urmia using the Surface Water Supply Index (SWSI) from Oct. 2009 to Sep. 2019. For this purpose, annual precipitation data, snow water equivalent, surface runoff, and reservoir storage (or changes in groundwater storage) have been used. The methodology of the study is based on the SWSI index, remote sensing using Google Earth Engine, determining the snow cover area using the NDSI index, and analyzing the drought trend using the Mann–Kendall trend test. The results showed that according to the weights of the components obtained by the Analytic Hierarchy Process (AHP), precipitation is the most important factor in the study area in hydrological droughts. Also, according to the SWSI index, during the 10 water year period, wet, extreme drought, and severe drought conditions have not occurred in the study area and generally, in 54% of the cases near-normal conditions, in 19% of the cases incipient drought conditions prevail and in the next ranks are abundant and moderate drought conditions with respectively 14% and 13% incidence. Also, the wettest water year was from Oct. 2018 to Sep. 2019 and the driest water years were from Oct. 2016 to Sep. 2017 and from Oct. 2011 to Sep. 2012. In addition, in all studied sub basins except Zolachay, the near-normal hydrological condition was the most common condition during the study period. Also, the results of Mann-Kendall non-parametric trend test showed that only in the Baranduzchay and Rashkan-Talkhab sub basins, the trend of hydrological drought time series has been increasing (increasing humidity).

Seasonal precipitation forecasting plays a pivotal role in water resource management and development of warning systems. This study evaluated the ensemble forecasts of three C3S models over the period 1993–2017 in Iran’s eight classified precipitation clusters for 1- to 3-month lead times. The quantile mapping (QM), the linear scaling (LS), and the gamma distribution mapping (GDM) for post-processing of precipitation forecasts, and the LS and variance scaling (VS) was used to post-process temperature forecasts. The results were then compared with the raw forecasts. It is indicated that the models performed best in western precipitation clusters, while in the northern humid cluster the models had negative skill scores. Almost all the post-processing methods were able to reduce the errors and improve the forecast accuracy in most groups. In general, after post-processing the ECMWF models had the best performance and the MF model had the worst performance. Among the precipitation post-processing methods, GDM and LS performed better, and the superiority of these methods is quite noticeable, especially in the rain-heavy groups of northern Iran (G6 and G8), which had poor raw forecasts. Regarding the post-processing of ensemble temperature forecasts, the performance of each LS and VS method is similar, they have a slight difference in increasing the accuracy of forecasts. Of course, overall, the VS method has worked a little better. The performance of post-processing methods is very effective in the cold months of the year (late autumn and winter) and slightly weaker in the hot months (summer).

This essay addresses the principal challenges in the Zayandeh Rud River and their underlying causes and highlights some strategies to alter current practices. The primary problem in this basin is the need for organizing and monitoring the water withdrawals. This issue has intertwined with determining the share and priority of water rights under different climate conditions. The persistence of these challenges implies that water scarcity and poor water governance are symptoms of a deeper problem related to the impacts of Iran's socio-political situation. Therefore, blaming the water governance system is a misguided approach. The most crucial strategy for transitioning to a new equilibrium state is maintaining a minimum but steady natural flow of the river through iterative and step-by-step processes. Regardless of its size, a flowing river can be seen as a symbol of transformation and the driving force behind building capacity for river management, monitoring, and enforcement of surface water and groundwater withdrawals.