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Economic policies for managing agricultural water use are often complicated by the challenge of using water prices as an efficient economic tool when other non-economic concerns are involved in the decision-making process. This study aims to analyse the impact of water pricing policies on preserving agricultural water resources in Iran. This study applies a system dynamics approach to simulate the system performance and behaviour of stakeholders and the economic implications. Our finding shows that water pricing policies will likely fail due to low water price elasticity and if there are lack of institutional and physical infrastructure, alternative professions, manufacturing technology, education, and training opportunities. The results also illustrate how agricultural water price increase (AWPI) fails to reduce water consumption in the absence of an adequate institutional arrangement. Also, it shows how the lack of advanced institutional infrastructure in the presence of physical infrastructure enhances pervasive overuse and destructive competition among stakeholders by increasing the area under cultivation. In the discussion, the paper portrays a way out of the decision-making body by following AWPI effects on water conservation in the agricultural sector as the most significant water consumer. It investigates the absence and subsequent presence of specific institutional conditions and evaluates training and enhancing farmers' skills and alternative career source with higher income and technology as the architecture of good environmental governance. Finally, it concludes that a series of inclusive measures must be considered to increase the elasticity of the water price. These measures must stimulate farmers towards pursuing the goals of global sustainable development and enhancing social welfare. [ABSTRACT FROM AUTHOR]

This paper reports a realistic analysis of a region using Grounded Theory (GT) to provide a sustainable model for family farming systems based on the intercropping system in rural communities of Iran. Furthermore, the fuzzy analytic hierarchy process (FAHP) was applied to assign weights to the criteria and sub-criteria of intercropping and monocropping systems. According to the model, the main phenomenon was "sustainability in the family farming system based on intercropping". In this model, the causal factors were found to include behavioral and attitudinal motivators. Micro- and macro-factors were identified as the interfering factors in family farming systems based on intercropping. Social factors, economic components, and environmental potentials were the contextual factors of this system. Finally, the consequences included the conceptual development and evolution of sustainability, socioeconomic transformation, and ecological-environmental transformation. The results of FAHP showed that the environmental criterion was ranked the first among all criteria underpinning the sustainability of the intercropping system. [ABSTRACT FROM AUTHOR]

This paper reports a realistic analysis of a region using Grounded Theory (GT) to provide a sustainable model for family farming systems based on the intercropping system in rural communities of Iran. Furthermore, the fuzzy analytic hierarchy process (FAHP) was applied to assign weights to the criteria and sub-criteria of intercropping and monocropping systems. According to the model, the main phenomenon was "sustainability in the family farming system based on intercropping". In this model, the causal factors were found to include behavioral and attitudinal motivators. Micro- and macro-factors were identified as the interfering factors in family farming systems based on intercropping. Social factors, economic components, and environmental potentials were the contextual factors of this system. Finally, the consequences included the conceptual development and evolution of sustainability, socioeconomic transformation, and ecological-environmental transformation. The results of FAHP showed that the environmental criterion was ranked the first among all criteria underpinning the sustainability of the intercropping system. [ABSTRACT FROM AUTHOR]

Economic policies for managing agricultural water use are often complicated by the challenge of using water prices as an efficient economic tool when other non-economic concerns are involved in the decision-making process. This study aims to analyse the impact of water pricing policies on preserving agricultural water resources in Iran. This study applies a system dynamics approach to simulate the system performance and behaviour of stakeholders and the economic implications. Our finding shows that water pricing policies will likely fail due to low water price elasticity and if there are lack of institutional and physical infrastructure, alternative professions, manufacturing technology, education, and training opportunities. The results also illustrate how agricultural water price increase (AWPI) fails to reduce water consumption in the absence of an adequate institutional arrangement. Also, it shows how the lack of advanced institutional infrastructure in the presence of physical infrastructure enhances pervasive overuse and destructive competition among stakeholders by increasing the area under cultivation. In the discussion, the paper portrays a way out of the decision-making body by following AWPI effects on water conservation in the agricultural sector as the most significant water consumer. It investigates the absence and subsequent presence of specific institutional conditions and evaluates training and enhancing farmers' skills and alternative career source with higher income and technology as the architecture of good environmental governance. Finally, it concludes that a series of inclusive measures must be considered to increase the elasticity of the water price. These measures must stimulate farmers towards pursuing the goals of global sustainable development and enhancing social welfare. [ABSTRACT FROM AUTHOR]

Monitoring spatial and temporal trends of water use is of utmost importance to ensure water and food security in river basins that are challenged by water scarcity and climate change induced abnormal weather patterns. To quantify water consumption by the agriculture sector, continuous monitoring is required over different spatial scales ranging from field (< 1 ha) to basin. The demand driven requirement of covering large areas yet providing spatially distributed information makes the use of in-situ measurement devices unfeasible. Earth observation satellites and remote sensing techniques offer an effective alternative in estimating the consumptive use of water (Actual EvapoTranspiration (ETa) fluxes) by using periodic observations from the visible and infrared spectral region. Optical satellite data, however, is often hindered by noises due to cloud cover, cloud shadow, aerosols and other satellite related issues such as Scan Line Corrector (SLC) failure in Landsat 7 breaking the continuity of temporal observations. These gaps have to be statistically filled in order to compute aggregated seasonal and annual estimates of ETa. In this paper, we introduce an approach to develop a gap-filled multi-year monthly ETa maps at medium spatial resolution of 30 m. The method includes two major steps: (i) estimation of ETa using the python based implementation of surface energy balance model called PySEBAL and (ii) temporal interpolation using Locally Weighted Regression (LWR) model followed by spline based spatial interpolation to fill the gaps over time and space. The approach is applied to a large endorheic Lake Urmia Basin (LUB) basin with a surface area of ~ 52,970 km2 in Iran for the years 2013–2015 using Landsat 7 and 8 satellite data. The results show that the implemented gap filling approach could reconstruct the monthly ETa dynamics over different agriculture land use types, while retaining the high spatial variability. A comparison with a similar dataset from FAO WaPOR reported a very high correlation with R2 of 0.93. The study demonstrates the applicability of this approach to a larger basin which is extendible and reproducible to other geographical areas. [ABSTRACT FROM AUTHOR]

Despite the high cost and low efficiency, compressed air is mostly used in underground mining for ore extraction, hoisting, and mineral processing operations. Failures of compressed air systems not only threaten the health and safety of workers but also contribute to inefficient control of airflow and stopped all equipment that operates by compressed air. In such uncertain conditions, mine managers are faced with the big challenge to supply enough compressed air, and therefore, the reliability evaluation of these systems is essential. This paper aims to analyze the reliability of the compressed air system using the Markov modeling approach as a case study, Qaleh-Zari Copper Mine, Iran. To achieve this, the state space diagram was constructed considering all relevant states for all compressors in the main compressor house of the mine. The failure and repair rate of all main and reserve compressors were calculated for all possible transitions between states to obtain the probability of being of the system in each of the states. Moreover, the probability of failure at any time period was considered to study the reliability behavior. The results of this study show that there is 31.5% probability that the compressed air supplying system is in operating condition with two main and one standby compressors. The system probability that two main compressors are remain in the operation without failure for one months is 92.32%. Furthermore, the lifetime of the system is estimated 33 months when at least one main compressor is active. [ABSTRACT FROM AUTHOR]

It is interesting to note that the country of Iran is essential in terms of energy production and consumption, and the economy of Iran is mainly dependent on energy revenues. Therefore, thermal and hydropower plants consume water to produce various energy carriers. Considering that Iran is suffering from water stress, the nexus of water and energy becomes very important. This paper frames a comprehensive structure for Iran's energy subsystem within the Water, Energy, and Food (WEF) nexus system. The energy subsystem's supply and demand side in the proposed framework are formulated using data and physic-based equations. The presented framework addresses most interactions between WEF subsystems in a dynamic and adaptive setting. It is shown that through analysis of binding interactions between WEF, different management scenarios can boost the flexibility of the supply and demand side of the energy subsystem. In addition, by incorporating this framework, the water subsystem will manage the allocated and consumed water on the supply side and arrive at the most desirable outcome for the water sector. Also, the optimal cropping pattern could be evaluated based on energy consumption. [ABSTRACT FROM AUTHOR]

Due to the severe effects of climate change on the agricultural sector, urgent action is required on the part of farmers and is, indeed, critical to reducing climate change impacts. However, reports globally revealed farmers' engagement in climate change adaptation is still insufficient, ambivalent, and inconsistent and farmers do not consider adaptation to be urgent. Researchers have argued that this issue is rooted in psychological biases beside other factors. Therefore, the aim of this study is to evaluate how psychological distance determines climate change beliefs, risk perception and adaptation strategies among Iranian farmers. A cross-sectional paper-based survey was conducted in the Dasht-e Azadegan county of Khuzestan province in southwest Iran. The study sample consisted of 250 farmers selected through a multi-stage random sampling process. An expert panel review and a pilot study were conducted to confirm convergent validity and reliability of the scales. The results confirm that all four dimensions of psychological distance influence water management adaptation strategies and non-farm activities. Moreover, all psychological dimensions, except the temporal dimension, affect adaptation in farming management. Thus, making climate change more proximal to decision makers could be a strategic way of encouraging individuals to take adaptive actions. This study emphasizes that concepts of psychological distance can be applied to help organizations (e.g., agriculture extension services) to understand farmers' risk perceptions and responses to climate change impacts and improve risk communication to better engage farmers in climate action. [ABSTRACT FROM AUTHOR]

Water as a main driver for sustainable development (SD) should be optimally allocated to different users to support economic, social, and environmental functions. Traditional approaches are not able to account for all the mentioned functions simultaneously, therefore a change in the allocation approaches is necessary. This paper proposes a new framework for inter-sectoral water allocation called "water-constrained green development" (WCGD) to better meet the SD goals. The framework optimally allocates economically-allocable water (EAW), which is the total available water resources left after subtracting the amount of water required for drinking, sanitation, and environment (DSE), to different job classes. It was tested in Sistan Region- a low-developed area in southeast of Iran- which stands on agriculture. In the recent years, because of water crisis, intensity of dust problem, lack of sustained occupation, and immigration, the region's rate of population growth has been negative. Also, due to decrease of Helmand River inflow, Hamoun wetland, being the major source of food and shelter for the Sistan's residents, has been degraded. Therefore, Sistan Region needs to take a new development route. The shares of occupation and gross domestic product (GDP) in the agricultural sector of Sistan are respectively 29.1 and 14.8%, whereas they are on average 1 and 7% in Iran. Application of the proposed framework in Sistan Region under three scenarios of available EAW resources showed that the optimal reallocation of water among 15 job classes can improve job availability and GDP of the region currently suffering from poor economy and employment conditions. Based on the optimal job pattern obtained, the share of GDP of Sistan's agricultural sector drops to 7.1% while the shares of industrial and service sectors increase respectively from 9.7 and 75.4% to 13.7 and 79.2%, which are close to those of the country averages. Also, under the WCGD-based optimal solution, 68, 14, and 18% of people will respectively be employed in service, industry, and agriculture sectors. Additionally, the total available jobs and GDP will increase by 8.9 and 51.1%, respectively, leading to improved socio-economic well-being of the region's people and protection of its environmental resources. [ABSTRACT FROM AUTHOR]

Crash severity models play a crucial role in evaluating the influencing factors in the severity of traffic crashes. In this study, Extremely Randomised Tree (ERT) is used as a machine learning technique to analyse the severity of crashes. The crash data in the province of Khorasan Razavi, Iran, for a period of 5 years from 2013 to 2017, is used for crash severity model development. The dataset includes traffic-related variables, vehicle specifications, vehicle movement, land use characteristics, temporal characteristics, and environmental variables. In this paper, Feature Importance Analysis (FIA), Partial Dependence Plots (PDP), and Individual Conditional Expectation (ICE) plots are utilised to analyse and interpret the results. According to the results, the involvement of vulnerable road users such as motorcyclists and pedestrians alongside traffic-related variables are among the most significant variables in crash severity. Results show that the presence of motorcycles can increase the probability of injury crashes by around 30% and almost double the probability of fatal crashes. Analysing the interaction of PDPs shows that driving speeds above 60 km/h in residential areas raises the probability of injury crashes by about 10%. In addition, at speeds higher than 70 km/h, the presence of pedestrians approximately increases the probability of fatal crashes by 6%. [ABSTRACT FROM AUTHOR]

This paper is devoted to a phenomenological study of the earthquakes in central Alborz, Iran. Using three observational quantities, namely the weight function, the quality factor, and the velocity model in this region, we develop a modified dissipative sandpile model which captures the main features of the system, especially the average activity field over the region of study. The model is based on external stimuli, the location of which is chosen (I) randomly, (II) on the faults, (III) on the low active points, (IV) on the moderately active points, and (V) on the highly active points in the region. We uncover some universal behaviors depending slightly on the method of external stimuli. A multi-fractal detrended fluctuation analysis is exploited to extract the spectrum of the Hurst exponent of the time series obtained by each of these schemes. Although the average Hurst exponent depends slightly on the method of stimuli, we numerically show that in all cases it is lower than 0.5, reflecting the anti-correlated nature of the system. The lowest average Hurst exponent is found to be associated with the case (V), in such a way that the more active the stimulated sites are, the lower the average Hurst exponent is obtained, i.e. the large earthquakes are more anticorrelated. Moreover, we find that the activity field achieved in this study provide information about the depth and topography of the basement, and also the area that can potentially be the location of the future large events. We successfully determine a high activity zone on the Mosha Fault, where the mainshock occurred on May 7th, 2020 (M W 4.9). [ABSTRACT FROM AUTHOR]

An amendment to this paper has been published and can be accessed via a link at the top of the paper. [ABSTRACT FROM AUTHOR]

This study was conducted to evaluate the properties of lightweight sandwich panels made from low diameter bamboo particles, Phyllostachys Bambusides collected from Gilan province, Iran, as core layer, combined with thin wall bamboo strips as faces. The effects of three individual variables such as density of core layer (350–550 kg/m3), resin consumption in core layer (7.5–9.5%) and resin consumption in faces (175–275 g/m2) on some important physical, mechanical and thermos-acoustic properties of the panels were investigated. Response surface methodology was used to statistically analyse the results and optimization process. The average values for the mechanical properties of the sandwich panels were obtained as 17.16 MPa, 5669 MPa, 0.02 MPa, 17.60 MPa, 1.83 MPa, 0.03 MPa, and 913.3 MPA for modulus of rupture, modulus of elasticity, internal bonding, compression strength parallel to face grain, compression strength perpendicular to face grain, shear strength, and screw holding, respectively. Finally, thermal conductivity and noise reduction coefficient of the panels were respectively gained as 0.01 W/mk and 0.31. The results of technical and thermo- acoustic properties of the panels showed that the light weight sandwich panels from bamboo residues would be a suitable and sustainable alternative as an insulation material for sustainable and green construction. [ABSTRACT FROM AUTHOR]