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Publication Date: 2025
Land Use Policy (0264-8377) 148
Land use change is an effective factor in climate change and global warming, which contributes to the carbon cycle, radiant energy balance, and dust production. Urmia Lake basin water balance in the Northwestern part of Iran is in a critical condition due to land use change, drought, and climate change. This process has led to the lake water area reduction and pronounced dust production. The satellite images indicate that from 1984 to 2017, 1433 Km2 rangelands and water area of the Urmia Lake basin decreased by more than 2906 Km2. The area of human settlement increased by 550 Km2, irrigated farmland and orchards, 804 Km2, and salty marsh, 3428 Km2. The outputs of the WetSpass hydrological model reveal the highest coefficient of evapotranspiration and interception variation in the East of Urmia Lake basin. The effects of these changes are observed in reduced soil moisture, increased salty marsh, and soft sediments as potential dust resources. During the study period, the frequency of dust days in the North and East of the lake increased 2.5-fold, while in the Southern and Western parts increased 6-fold. The results of the Pettitt Test indicate that these changes began to appear in 2007. The regression and correlation test confirm that salt marshes and soft sediments account for up to 75 %, and the decrease in the area of Urmia Lake for more than 64 % of the dust changes. The results of the assessments indicate the contribution of footprint in the destruction of the natural environment and the water balance of the lake basin. Revision of water resources management and environmental water rights of the lake, changes in the development strategy from agriculture to non-agriculture development based on lower water demand, and reduction of storage dams are among the recommended strategies to address this problem. © 2024 Elsevier Ltd
Publication Date: 2025
Remote Sensing Applications: Society and Environment (23529385) 37
The areal extent of coastal wetlands is declining rapidly worldwide, and scientists and land managers need land cover maps that show the magnitude and severity of changes over time to assess impacts and develop effective conservation strategies. Within the United States (US), widely-used, continental-scale wetland land cover data products are either static in time (The National Wetlands Inventory) or have a course temporal resolution and do not distinguish between different types of change (the NOAA Coastal Change Analysis Program, C-CAP). This study presents a new coastal wetland geospatial data product that leverages the Landsat database and maps annual land cover across the US Atlantic and Gulf Coasts from 1985 to 2022. The algorithm was trained on the existing US wetland inventories to make the final maps compatible with products that are used in operational management. A multi-stage classification approach was designed that uses the Continuous Change Detection and Classification (CCDC) algorithm to characterize time series of remote sensing reflectance with fitted harmonic functions and identify when changes likely occurred. The fitted time series models are then input into a random forest classifier to make a class prediction. An annual-scale random forest classification is performed in parallel, and results from both algorithms are combined and analysed to detect both gradual and abrupt changes and to identify transitional time series segments. A time series smoothing procedure is subsequently applied to ensure class transitions are logical and consistent and extract a summative change characterization map that shows the severity and spatial density of change. The final maps distinguish between four homogenous classes and six mixed classes, representing areas that are transitioning between classes and where the boundaries between classes are unstable. The algorithm uses data and tools within the Google Earth Engine platform, making it accessible and scalable. The average overall accuracy is 93.7%, and the average class omission and commission errors are 6.7% and 6.4%, respectively. A variety of change detection comparisons were performed, using the existing wetland inventory that employed a fundamentally different change detection approach, and a more comparable annual-scale, Landsatderived product that estimated changes across the Northeastern Atlantic Coast. These comparisons show that the new products’ severe change magnitude matches that of the existing US inventory and the moderate change magnitude matches that of the Northeastern Coast product. The 2019 Wetland Status and Trends Report estimated that net loss rates in emergent wetlands from 2010 to 2019 amount to 1.7%, and the new maps show an equivalent loss rate of 1.6%, again showing close agreement. © 2024 The Authors
Publication Date: 2022
Paddy and Water Environment (16112490) 20(2)pp. 241-253
In this study, the effect of climate change on planting date and growth duration of rainfed wheat in the west and northwest parts of Iran has been investigated. The occurrence of climate change in the region was first evaluated for the base period (1992–2018) using two nonparametric tests of Mann–Kendall and Sen's slope estimator. Then, the climatic parameters of maximum temperature, minimum temperature and precipitation were simulated under RCP4.5 scenario for the period 2019–2039 based on downscaled output data of the Community Climate System Model (CCSM4) using LARS WG software. The growth period was obtained using a linear multiple regression model, which was selected based on R-square and accounted for 87% of its total variation. The results predicted that the average annual temperature will increase by 2 °C, while the average annual precipitation will increase by 30% by the end of 2039. Planting dates were determined based on two indices combining temperature and precipitation for the base and future periods. The results showed that climate change effects at the 2039 horizon will shorten by 18 days the wheat growth period and the appropriate planting time for rainfed wheat will be reduced by 2–19 days. © 2021, The International Society of Paddy and Water Environment Engineering.
Publication Date: 2021
Environmental Processes (21987505) 8(3)pp. 1027-1045
This paper aims to find the possible relationships between winter precipitation (December, January, February; DJF) in Iran with three oceanic sources through the correlation wavelet analysis by applying the continuous wavelet transform (CWT), the cross–wavelet transform (XWT), and the wavelet transform coherence (WTC). The sources in the North Atlantic Ocean (30°W-70°W, 10°N-30°N), the South Pacific Ocean (80°W-120°W, 20°S-40°S) and the Indian Ocean (50°E-100°E, 10°S-40°S) were selected using Pearson correlation coefficient (PCC > 0.5) that can represent the possible relationships between Iran’s winter precipitations with the oceanic sea surface temperature (SST) anomaly. The monthly gridded precipitation and SST data with a 2.5° × 2.5° resolution were evaluated from 1984 to 2019 to achieve this goal. The XWT results of precipitation and SST anomaly showed that the 8–16 months period is the most effective and predominant period between the South Pacific Ocean and 81% of all the precipitation zones. WTC results for the North Atlantic Ocean and 72% of all the precipitation zones showed periods of 4–8 (36%) and 16–32 (36%) months as the dominant duration. Despite the proximity of the Indian Ocean to the precipitation zones, there is no significant causal relationship between them, based on the XWT results. However, due to Madden–Julian oscillation (MJO), the 4–8 months period (45%) was seen between the Indian Ocean and some precipitation zones, based on WTC results. © 2021, The Author(s), under exclusive licence to Springer Nature Switzerland AG.
Publication Date: 2020
Theoretical and Applied Climatology (14344483) 142(3-4)pp. 1359-1367
Countries located in arid and semi-arid regions of the world, such as Iran, with highly dependent economy to agriculture, are more vulnerable to climate change. Six agro-climatic indices have been used, which include the length of the growing season and the frost-free season, dates of the occurrence of the last frost in spring and the first frost in autumn, and annual sum of the growing degree-days (GDD) for two temperature thresholds. To explore variabilities of the indices in the future, outputs of three regional climate models (RCMs) have been analyzed based on two Representative Concentration Pathway (RCP4.5 and RCP8.5) scenarios for the South Asia CORDEX region, with the horizontal resolution of 0.44°. Differences between the historical and future simulated agro-climatic indices have been calculated, in which the former is obtained from historical outputs of three models for the period 1961–1990, while the latter is based on future simulations during the period 2061–2090 applying RCP4.5 and RCP8.5 scenarios. Both RCP scenarios indicate an increase in the number of frost-free days (maximum 40 and 70 frost-free days according to the RCP4.5 and RCP8.5 scenarios, respectively), with higher changes in mountainous regions. Our results indicate that shorter frost days will be more common in northwestern and western Iran in the future period. The highest increase in annual sum of the GDD will be in southern and central Iran, but the lowest increase will be in northwestern Iran. © 2020, Springer-Verlag GmbH Austria, part of Springer Nature.
Publication Date: 2020
Arabian Journal of Geosciences (discontinued) (18667538) 13(4)
Water level reduction of Urmia Lake Basin is the main problem in northwest of Iran during 2001–2017. Climate change and human activity have affected the water resources in this basin. In addition, continuing downward trend of water level in the Urmia Lake leads to hazard such as dust storm, lake drying, subsidence in plains, population immigration, and reduced production efficiency. Finding the causes of water level change is one of the challenges as to the unsustainability of the lake. Climate change, drought, dam construction, well drilling, land use change, land cover change, and the pattern of cultivations are inflectional here. The results of the Man-Kendall test indicate that the annual temperature (Z = 2.3, 95%) and frequency of droughts increased, and annual precipitation (Z = − 2.5, 95%) decreased. The results indicate that groundwater extraction increased from 374 to 2263.4 mcm, and the volume of dams increased from 198 to 1758 mcm (1961–2017). Surface water is reduced due to decreasing rainfall, increasing temperature, and drought frequency in the last decade. The comparison of these parameters with each other indicates high contribution of climate change and human activity in water level reduction of the subject lake. Restoration and sustainability of this lake are very important to the water management resources of Urmia Lake Basin. © 2020, Saudi Society for Geosciences.
Publication Date: 2017
Chinese Geographical Science (10020063) 27(5)pp. 800-809
Clouds can influence climate through many complex interactions within the hydrological cycle. Due to the important effects of cloud cover on climate, it is essential to study its variability over certain geographical areas. This study provides a spatial and temporal distribution of sky conditions, cloudy, partly cloudy, and clear days, in Iran. Cloud fraction parameters were calculated based on the cloud product (collection 6_L2) obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors on board the Terra (MOD06) and Aqua (MYD06) satellites. The cloud products were collected daily from January 1, 2003 to December 31, 2014 (12 years) with a spatial resolution of 5 km × 5 km. First, the cloud fraction data were converted into a regular geographic coordinate network over Iran. Then, the estimations from both sensors were analyzed. Results revealed that the maximum annual frequency of cloudy days occurs along the southern shores of the Caspian Sea, while the minimum annual frequency occurs in southeast Iran. On average, the annual number of cloudy and clear-sky days was 88 and 256 d from MODIS Terra, as compared to 96 and 244 d from MODIS Aqua. Generally, cloudy and partly cloudy days decrease from north to south, and MODIS Aqua overestimates the cloudy and partly cloudy days compared to MODIS Terra. © 2017, Science Press, Northeast Institute of Geography and Agricultural Ecology, CAS and Springer-Verlag GmbH Germany.
Publication Date: 2015
Theoretical and Applied Climatology (14344483) 120(1-2)pp. 367-376
This study compares the precipitation regimes by using harmonic analysis during the last four decades (1965–2004). We used the measured precipitation data from 428 rain-gauge sites and weather stations distributed across Iran by applying 15 × 15 km spatial grids to generate the interpolated data. Data validations were carried out by statistical tests. In this study, first three harmonics of precipitation variances were evaluated. Variability of precipitation regime was explored by using three harmonic analysis methods. In addition, the effect of geographical factors (GF) (site elevation, latitude, and longitude) affecting the precipitation regime (P) was verified by multivariate regression method. The resulted regression equation between P and GF for spring showed the highest correlation coefficient (r = 0.79). For other seasons, r was lower than for spring and varied between 0.26 (summer) to 0.58 (autumn). Analysis of the first harmonic proved that the main precipitation regime in Iran tends to concentrate in one specific season (winter) as a result of large-scale Mediterranean systems passing over the country. In other words, the first harmonic is able to explain most of the precipitation variations which are caused by large-scale atmospheric circulation. For all the three harmonics, variances of precipitation were mainly a function of the geographical factors. This effect was more evident in the third harmonic; in such a way that increasing the latitudes caused higher precipitation variance. This means that the precipitation regime in northern sites is more sensitive to the local factors than those of southern sites. The results of this research can be used for reliable estimation of precipitation in ungauged sites. © 2014, Springer-Verlag Wien.
Publication Date: 2013
Mausam (02529416) 64(3)pp. 539-546
Mediterranean cyclones, especially east cyclones of this sea, play a very important role in precipitation events of cold season in Iran. In the other hand formation of surface trough over the Red Sea makes possible the displacement of humidity from tropical area to extra-tropical area. To determine the role of Red Sea trough in supplying humidity sources of EM cyclones, surface data of geopotential height, specific humidity and Vertical and Horizontal component of wind in limited 5 through 65 degrees of north latitude and 0 through 80 degrees of east longitude were used. During the study 56 cyclones formed over the east of Mediterranean recognized which were simultaneous to the Red Sea troughs events. Convergence maps of moisture flux of 10 cases of simultaneous cyclones with Red sea trough which were strong, were drawn. Verification of convergence maps of moisture flux of selected cases show some required humidity for EM cyclones are initiated from Arabian Sea and then to some extent are reinforced over Persian Gulf and Gulf of Aden and then by passing over Red Sea enter to the south east of Mediterranean Sea. Actually Red Sea has not an important role in the humidity source of these cyclones and acts as a pass way for displacement of humidity of tropical area to extra-tropical area and injects the required humidity into the EM cyclones. To determine the regions and the amount of suction in the high levels, composite maps of ageostrophic divergence and jet streams of polar front were used.
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