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Showing 2 results for Spatiotemporal Variations

Behrooz Mohseni, Kaka Shahedi, Seyyed Mohsen Manavi, Narjes Mahmoodi-Vanolya,
Volume 9, Issue 2 (9-2022)
Abstract

The sedimentation, sediment transport, erosion and sedimentation problems are important discussions in the planning of wisdom and macro watershed strategies and management of watershed basins. The sediment collection in lower areas causes regional damage, the destruction of the pathway of the waterways, the flow of water pollution, the accumulation of streams of sediment and reducing the capacity of reservoirs of dams and environmental bottlenecks. The sediment resulting from the watersheds erosion, in addition to soil loss and its degradation results in a decrease in water quality and endangers the useful life of dams due to the accumulation of deposits in their reservoirs. In this research, Spatiotemporal variations of suspended sediment load were investigated at three hydrometric stations of Sefidchah, Gelevard and Ablou located on the main channel of the Nakaroud Basin using sediment rating curves and linear regression model through applying MINITAB and EXCEL softwares. In order to determine the best model, determination coefficient (R2) was used. The results of this study showed that in seasonal variations of spring season in all three stations with a determination coefficient of at least 82% and a maximum of 89% as the most suitable model for estimating suspended sediment load among the models studied. In spatial studies, the Ablou station located at the outlet of the watershed has the highest determination coefficient (0.934) between sediment discharge and streamflow discharge.
 
Dr Masoud Moradi, Dr Mohammad Hosein Gholizadeh, Mr Meysam Rahmani,
Volume 10, Issue 2 (9-2023)
Abstract

Investigation of the Temporal and Spatial Variation of Maximum Soil Temperature in Iran

Extended Abstract
Introduction
The study of soil temperature in different depths of soil is important in climatology, hydrology, agrometeorology and water resource management. Different depths has a different temporal and spatial soil temperature variation. It represents the regional ground temperature regime. Furthermore, due to its rapid response to environmental changes, soil temperature is one of the most important indicators of climate change. The increase in soil temperature because of global warming can promotes disasters such as drought by increasing the water demand of agricultural products during the plant growth period. The increase in soil temperature also have a various consequences, include increasing evaporation from the soil surface, soil salinity in susceptible areas, which can lead to a decrease in soil yield and failure in plant growth. Therefore, knowledge of soil temperature changes in different environments is very important in climate studies. The aim of the current research is to analyze the spatial and temporal variations of soil temperature at different depths from five to 30cm of the ground and to investigate the existence of any kind of increasing or decreasing trend at different climates of Iran.
Methodology
Hourly soil temperature data (depths of 5, 10, 20 and 30 cm) were used in this research for the period of 1998-2017. The soil depth temperature is measured three times a day at 6:30 am, 12:30 pm, and 6:30 pm local time (3, 9, and 3 p.m. UTC). These data have been received for 150 synoptic stations of Iran on a daily basis from the Iran Meteorological Organization (IRIMO). IRIMO monitored the quality of soil temperature for data entry, data recording, and data reformatting errors. Data availability, discrepancies, errors, and outliers were identified during the second stage.
At the first step, temporal coefficient of variation were calculated for available soil temperature time series from five to 30 cm depths of each station. For this purpose, the average of three daily measurements of soil temperature was calculated and then the temporal coefficient of variation was obtained. In the next step, trend analysis of soil temperature has been investigated using the non-parametric Mann-Kendal test. The trend slope was calculated using Sen’s slope for each station in seasonal time scale. Trend analysis has been done for all three observations of the day.
Results and Discussion
The studied stations show significant spatial patterns in the temporal variability of soil temperature. In all four investigated depths, from five to 30 cm, the northwest parts of Iran, and some parts of Zagros and Alborz mountain ranges have high temporal coefficient of variation. In contrast, the stations located on the southern coasts and southern islands had the lowest temporal variability. In warm and cold seasons (summer and late autumn to mid-winter), the spatial changes of soil temperature at different depths are lower than spring and early autumn. However, in the warm period of the year, the soil temperature experiences lower spatial variations at different depths. Spring and autumn seasons, as the transition period from cold to warm and warm to cold seasons, show the most spatial temperature variations in Iran. Detected trends do not have significant differences among the three observations of the day. Soil temperature Trend analysis at different depths showed positive values for two seasons of summer and winter over most of the stations throughout Iran. Extreme trends are more frequent in the summertime of Zagros and Alborz mountainous regions, while in the winter season the stations located at the southern latitudes of Iran have experienced the most positive trends. In the summer season, higher trends with 99% confidence are more frequent in the mountainous areas. These positive trends in soil temperature have occurred in all studied depths. The negative trend at different depths is a distinct feature of the autumn season, which is significantly more prevalent than other seasons throughout Iran. The analysis of soil temperature trends in different depths shows that values above 1 degree Celsius often occur in 5 to 20 cm deeps. The increasing trend of soil temperature in winter shows a greater spatial expansion, which is indicate increasing annual minimum soil temperatures and the increasing trend of Iran's soil temperature.
Keywords: Soil Temperature, Spatiotemporal Variations, Man-Kendal Test, Sen's Slope, Iran

 

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