مجله ترویج و توسعه آبخیزداری
پیاپی 42 (پاییز 1402)

The natural abundance of phytoplankton in the Persian Gulf has changed, creating a constant threat to biodiversity. Monitoring and predicting the spatial-temporal behavior of this phenomenon is crucial to prevent negative social-economic consequences and environmental planning. On this basis, the current research aims to assess the spatial-temporal changes of chlorophyll and analyze its relationship with the sea surface temperature in the Persian Gulf. To this end, we estimated and analyzed changes in the concentration of chlorophyll as an organic compound produced by algae and plants using MODIS sensor images from 2000 to 2021 (monthly and seasonally). Spatial indices of the barycenter were also calculated in addition to accuracy assessment using error evaluation criteria. Global Moran and G-star (G*) statistics were used to identify the degree of spatial autocorrelation and the magnitude of spatial patterns. The results showed that the intensity of this phenomenon on average varies between 0.05 and 16.38 mg m-2. The northwest and southwest have the maximum values and the central parts of the Persian Gulf have the minimum values. The northern coast of the Persian Gulf is located in Iran, and the northern parts, i.e., areas with less population and industries, have a low amount of this phenomenon. The ellipse line shows three standard deviations in the northwest and southeast directions following the cities and industries. The time series of changes showed that as the temperature decreases in the cold season, especially in January, the concentration increases, and as the temperature of the water surface increases in the hot season the amount of chlorophyll in the water decrease. Statistical analysis of the spatial distribution also indicates a significant cluster spatial pattern. Slope changes verified that the southern regions of the Persian Gulf, especially in the countries of Bahrain, UAE, and Saudi Arabia, have the most positive slope of changes. In the main part of the area, including the northern part of the Persian Gulf, whose coastline is entirely owned by Iran, except for the northwest, which includes the Mahshahr port and Asaluyeh, the slope of changes has been very low or decreasing. This research could identify areas exposed to adverse changes in phytoplankton concentrations and can be used in environmental planning.

Long-term warming of the atmosphere, decrease in precipitation, drought and floods lead to the creation of climate change phenomena in natural and unnatural ecosystems. In addition, an increase in greenhouse gases, which cause the temperature to rise, also increases this phenomenon. Climate change affects different aspects of Mashhad city in terms of geographical location, tourism and tourism. In this study, using the CanESM2 model and the precipitation and temperature data of Mashhad station from 1961 to 2005, they were predicted in the near future from 2030 to 2060 and from 2070 to 2100 under RCP climate change scenarios. The results showed that the CanEMS2 model is in good agreement with the observational data and can be used to simulate the data in the future period. The simulation results show that the amount of precipitation will decrease in the near future, but not in the distant future. This parameter will also increase, but the temperature will increase in the future (near and far) and the phenomenon of global warming will increase. The results of this research can be used for environmental management and the services and industries that will lead to an increase in greenhouse gas emissions in Mashhad city can be used for proper policy and planning in order to reduce greenhouse gas emissions.

The crop water stress index based on canopy–air temperature differences (CWSIdT) is an appropriate index for monitoring the water status of croplands but is rarely used to evaluate the water status of forest ecosystems. However, CWSIdT is rarely used in forest ecosystems. Investigating the possibility of using the crop water stress index (CWSI) for planning the irrigation of four species of pasture trees, Prosopis cineraria (T1), Conocarpus (T2), Albezia lebbek (T3) and Ziziphus (T4), under four methods of surface irrigation, bubbler, pitcher, and waterboxx system, was selected. This research was conducted in the year 2021 in the experimental farm of the Faculty of Water and Environmental Engineering of Shahid Chamran University of Ahvaz and lasted for 9 months. The experiment was conducted as a factorial in the form of a randomized complete block design with 3 replications. The crown temperature, actual evaporation and transpiration and meteorological factors of the field were continuously and simultaneously measured during the period from the beginning of April to the end of December. Infrared thermometers was used to measure crown temperature and vapor pressure deficiency values for different irrigation treatments. The results showed that under well-watered conditions, canopy-air temperature difference and canopy surface transpiration rate are both controlled by the net radiation received by the canopy surface The highest and lowest calculated CWSI values were related to waterboxx and Pitcher irrigation with values of 1.01 and 0.81, respectively, which were related to Ziziphus and Konocarpus trees. Statistical analysis showed that the effect of irrigation method on plant water stress index values in spring and autumn seasons was significant at the level of 5% and the average values of plant water stress index increased with water consumption reductions of 87 and 59% in waterbox and pitcher irrigation systems, respectively. However, there was no significant difference observed in the summer season. Also, the effect of tree type on the CWSIdT index during the period was important at a 1% level. In addition, the difference in vegetation and air temperature were used as a determining factor to determine irrigation time, which can be used to estimate pasture tree water stress.

In the last decade, the migration of rural villagers and residents has made it clear that some villages are empty. In this context, the continued migration of rural residents to urban areas requires a review of lifestyles and incomes in the area, in order to be aware of the construction. Access to environmental problems and sustainable development depends on an understanding of the natural, social, cultural and economic development of a village and a careful planning and strategy in the field. In order to achieve the best strategic strengths, weaknesses, and threats the village was identified and characterized. In order to identify and characterize the best strategic strengths, weaknesses, threats and opportunities in rural areas. SWOT and ANP models were then used to assess the most appropriate strategies in decision-making and evaluation of the potential. The model results showed that aggressive competitive strategy is the best strategy. Based on the results obtained using the best network analysis processes to improve the lives of villagers and the potential new applications of public facilities such as greenhouse cultivation in the region. The SWOT model of strategy formation of cooperatives and the efforts and participation of locals in the production and sales strategies of government grants and self-educated class of his employment and occupation job with a score of 20 as the priorities of the Executive. Because many rural development activities in Iran are related to climate, the ANP models should consider the interactions among the factors considered in deciding the performance.

Analyzing changes in land use/cover and identifying their drivers is essential for developing sustainable land management approaches that restore ecosystem resources and services. This research analyzes land use/land cover changes in the Fandoghlo region in Ardabil province in the last two decades based on Landsat 8 (OLI/TIRS L1TP) satellite images and investigates governance and socio-economic drivers based on household surveys and key informants interviews. The results recorded a negative net change in forest (187.5 ha) and rangeland (662.5 ha) ecosystems and a positive net change in agriculture (587.1 ha) and man-made (267.6 ha). Analysis of the 20-year (2003-2023) change detection matrix showed that about 26% of the study area experienced a transition. Based on the results of the investigation of 11 governance and socio-economic drivers, the observed change in ecosystems caused by the expansion of agriculture (91%), poverty (71%), livestock pressure (68%), weak law enforcement (65%), wood smuggling (62%), increasing demand for firewood (60%), population growth (44%), fires (41%), incompatible forms of tourism (40%), distance to the road (36%), and mining (11%). These socio-economic drivers have a significant impact on the availability of ecosystem services, community welfare, biodiversity, and climate. Therefore, this study recommends coordinated efforts by stakeholders to develop participatory ecosystem management and public awareness on the coexistence of nature conservation and sustainable livelihoods. In order to protect ecosystems in this region, it is crucial to empower local communities, understand the dynamics of agricultural lands, and manage the causes and consequences of recent demographic changes.

This research was conducted in Ardabil plain with the aim of investigating the quantitative and sustainable status of different sources of water supply for potato, wheat, barley and alfalfa crops. Using CROPWAT software, the water requirement of these products as the main crops of the plain was determined. Various components of the virtual water footprint, including VWFblue, VWFgreen, VWFgrey, as well as water stress indices from the perspective of production (WSI) and water consumption (CWSI) were calculated. The results showed that potatoes with an annual consumption of approximately 84 million m3 (66%) have the largest share in the virtual water footprint index (VWF) of Ardabil Plain. In addition, barley, alfalfa and wheat products have a virtual water footprint (VWF) of 21, 12.2, and 11 million m2 respectively. The WSIgreen, WSIblue, and WSIgrey indices were calculated with values of 0.5, 6.4, and -0.1, respectively, and moderate water and severe water shortages, respectively. Considering the limitations of water resources in the Ardabil Plain, it is necessary to improve the productivity of regional agricultural water from a production point of view and to prioritize the development and protection of water resources to ensure the quantity and quality of the water needed.

The greatest depth of precipitation possible for a given duration is called probable maximum precipitation denoted by PMP. Probable maximum precipitation is generally evaluated using two meteorological and statistical methods. In this research, the Hershfield's statistical methods and conventional torque method were used to evaluate probable maximum precipitation of Bakhtegan Watershed. In Hershfield's equation, the frequency factor was considered to be constant at 15. Since this factor might not be consistent to all the stations in different climatic conditions, then, in this study, the frequency factor in Bakhtegan Watershed was obtained based on the maximum precipitation of 24h, at 35 meteorological stations in three statistical Hershfield's methods І , Hershfield's ІІ, Hershfield's ІІ with eliminated outlier data. Afterwards, the probable maximum precipitation of 24h in Watershed's stations were analyzed and calculated for all three methods. In this study, the conventional torque method was also used for 17 stations having more than 30 years of precipitation statistics. In this method, after performing data homogeneity test (Mann-Kendall) and removing outlier data, maximum precipitation amount was performed for normal distribution, two-parameter lognormal, three-parameter lognormal, Pearson type-III, Log-Pearson type-III and Gumbel was using SMADA software; and the best frequency distribution was obtained using RMSE test for each station. Using RRMSE test for all stations, it is found that Gumbel distribution was the most appropriate one; by the use of Gumbel distribution, 24-h PMP with various return period is obtained for each station. In addition, for each approaches, a maximum 24-h PMP watershed precipitation was plotted to show the spatial distribution.