Projections of future scenarios are scarce in developing countries where human activities are increasing and impacting land uses. We present a research based on the assessment of the baseline trends of normalized difference vegetation index (NDVI), precipitation, and temperature data for the Khuzestan Province, Iran, from 1984 to 2015 compiled from ground-based and remotely sensed sources. To achieve this goal, the Sen’s slope estimator, the Mann-Kendall test, and Pearson’s correlation test were used. After that, future trends in precipitation and temperature were estimated using the Canadian Earth System Model (CanESM2) model and were then used to estimate the NDVI trend for two future periods: from 2016 to 2046 and from 2046 to 2075. Our results showed that during the baseline period, precipitation decreased at all stations: 33.3% displayed a significant trend and the others were insignificant ones. Over the same period, the temperature increased at 66.7% of stations while NDVI decreased at all stations. The NDVI–precipitation relationship was positive while NDVI–temperature showed an inverse trend. During the first of the possible future periods and under the RCP2.6, RCP4.5, and RCP8.5 scenarios, NDVI and precipitation decreased, and temperatures significantly increased. In addition, the same trends were observed during the second future period; most of these were statistically significant. We conclude that much assessments are valuable and integral components of effective ecosystem planning and decisions.
In recent decades population increasing and development of agriculture and also being mountainous and climatic characteristics of Sefieddasht plain and also nonuniform distribution of rainfall in study area have led to irregular use of groundwater resources in study area. This issue has led to critical condition of groundwater resources in Sefieddasht plain. This research was carried out to determine the suitable areas for artificial recharge in Sefieddasht plain. Four factors namely, alluvial quality, alluvial thickness, slope, and infiltration rate parameters were explored and maps produced and classified using GIS. Fuzzy logic model was used to determine the suitable areas for artificial recharge. Finally land use maps were used as a filter. Based on results 4.12% of region was recognized as suitable area for artificial recharge.
The aim of this study was to investigate the effects of climate change on the climate condition of outdoor tourists in Hormozgan province, Iran, through Outdoor Tourism Climate Index (OTCI). For this purpose, the data pertaining to 7 weather stations as well as 2 global climate models (GCMs) under 2.6 and 8.5 Representative Concentration Pathways (RCP) were applied. GCMs were statistically downscaled by the change factor (CF) approach. The findings illuminated that, based on OTCI, December, January, February, and March were regarded as the optimal months for the outdoor tourism activities. Nevertheless, for the concerned months, the range of OTCI score in twenty-first century is changing from 2 to − 12 regarding the base period (1980–2010). Mostly, the changes in OTCI score is predicted to occur at March, April, May, October, and November, whereas June would record the least. Moreover, Hajiabad and Kish stations in the North and South of the under-study area would encounter the most and least changes, respectively, in the future.
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