Remote Sensing (RS)
Heshmat Karami; Hadi Abdolazimi
Abstract
Extended AbstractIntroductionWetlands are considered valuable resources of the environment. Despite the importance of wetlands, they are currently threatened by intensive water harvesting for irrigation, industrial development, deforestation, construction of dam reservoirs, and changing rainfall patterns. ...
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Extended AbstractIntroductionWetlands are considered valuable resources of the environment. Despite the importance of wetlands, they are currently threatened by intensive water harvesting for irrigation, industrial development, deforestation, construction of dam reservoirs, and changing rainfall patterns. Monitoring can determine the changes in the location, extent, and quality of the wetland and therefore plays an important role in the maintenance and protection of the wetland. Ecosystem monitoring with remote sensing methods offers the advantage of difference, frequent and uniform coverage of large areas. The study of effective parameters or up-to-date maps that show spatial and temporal changes in the sub-basin of Horul Azim Wetland is not available. Therefore, considering that currently, this wetland is struggling with various problems to continue its survival, the purpose of this research is to use Google Earth Engine and satellite data to study the process of wetland changes.Materials & MethodsThis study was done on the platform of Google Earth Engine open source system. In this study, the data of water area, vegetation cover, precipitation, evaporation, and surface temperature were coded in the Google Earth Engine system in a standard way and their time series was obtained. Also, the NASA GRACE data analysis tool (DAT) was used for time series of groundwater levels. In this research, the Mann-Kendall test and Spearman's correlation were used in order to evaluate the changes in different parameters. In this research, the period from 2000 to 2022 was considered to investigate the trend of the data according to the available time range of the data. Finally, to check the fact that the changes in the zones were affected by floods, the data of the Global Surface Water of Water Occurrence (GSWE) probe was used.Results, discussion, and conclusion The results of the analysis graph of the water area data trend showed that from 2007 to 2019 the water area trend is increasing, with 2007 being the minimum year and 2019 being the maximum year, and the reason for this was the 90% water withdrawal of the Hor al-Azim wetland in the Iranian part. Also, the reason for the increase in the water area in 2017 is heavy rains that lead to floods and overflowing of the Karkheh dam in the sub-basin of the Hor al-Azim wetland. In 2017 and 2020, 2021, the water area shows a significant increase, which is due to the change in climatic behavior and the occurrence of floods in these years. Finally, the trend of the blue zone will be downward until July 2022. The results of a careful analysis of the data trend by the Mann-Kendall test showed that the trend of the available time period was observed. Kendall's tau value also confirms the increasing trend. It seems that the increasing trend of the water area in the years 2019 to 2021 in this study using the Google Earth Engine system is the result of the floods of the last few years, that Considering only this parameter and these data leads to errors in the study and investigation of the condition of Hor-al Azim wetland. No significant trend was observed in the time series of vegetation cover, but according to the positive Mann-Kendall vegetation cover statistic, one of the causes of the non-significant decrease in the groundwater level could be the increase of pastures and agricultural lands. Kendall's tau value for the surface temperature also showed a negative value (-0.24). According to this result and the sensitivity of the evaporation parameter to temperature, we can point to the role of this parameter in reducing evaporation in the sub-basin of the Hor al-Azim wetland. The northwest and southeast regions have the highest temperature up to a part of the central region of the sub-basin. The western part, which includes the border of the Hor al-Azim wetland, has the lowest temperature, and most of the central part has the lowest temperature, one of the causes of which can be the presence of vegetation and the development of agricultural lands. The time series graph of precipitation showed that the parameter of precipitation in the years 2017 to 2020 had an upward trend, which led to recent floods in the studied area. The results of the Mann-Kendall test for the general trend of evaporation and transpiration parameters, ground surface temperature, and precipitation in the sub-basin of the Hor al-Azim wetland did not show a significant trend. Using the Global Surface Water Explorer (GSWE) data, the occurrence of water, the intensity of water changes, and the seasonal change of water on the wetland were studied for the period of 1984-2021. The study of this dataset confirmed the human interference (creating the Karkheh Dam and draining its lake) and the occurrence and effects of the flood on the sub-basin of the Hor-al Azim wetland. The results of Spearman's correlation test also showed that climate changes such as changes in precipitation patterns and human activities can become factors that affect the surface of the water body of Hor al-Azim Wetland. The results of this research can be used in the management of Hor al-Azim wetland and wetlands with similar conditions.
Mahdi Sedaghat; Hamid Nazaripour
Abstract
Extended Abstract Introduction Soil moisture is considered to be a key parameter in meteorology, hydrology, and agriculture, and the estimation of its temporal-spatial distribution contributes to understanding the relations between precipitation, evaporation, water cycle, and etc. Soil moisture reduction ...
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Extended Abstract Introduction Soil moisture is considered to be a key parameter in meteorology, hydrology, and agriculture, and the estimation of its temporal-spatial distribution contributes to understanding the relations between precipitation, evaporation, water cycle, and etc. Soil moisture reduction results in the creation of centers susceptible to dust storms. With socio-economic impacts ranging from urban to intercontinental and from a few minutes to several decades, this can challenge regional development. The first estimate of potential dust sources is derived from the soil properties. With the reduction of surface soil moisture and the wind speedcrossing a certain threshold level, wind erosion process can cause the formation of dust storms. Field studies have proved that increasing the moisture content in soil from zero to about 3%, reduces the dust concentrationsignificantly. To understand the climatology of dust and develop related numerical predictive methods, continuous recording of dust storms is essential, which requires effective and continuous monitoring of the variations in surface soil moisture. Remote sensing technology is an effective method for calculating soil moisture. This technology was first used for the estimation of energy flux and surface soil moisture in the 1970s. To extract the surface soil moisture content, some remote sensing methods use surface radiation temperature and some others apply water transfer (soil/vegetation/air) (SVAT) model. Various indices have been developed for soil moisture monitoring, such as soil moisture (SM), soil water index (SWI), Temperature-Vegetation-Dryness Index (TVDI), Soil Moisture Index (SMI) and Perpendicular Soil Moisture Index (PSMI), all of which combine vegetation and surface temperature variables. Materials and Methods Soil moisture is considered to be a significant parameter in the exchange of mass and energy between the Earth surface and the atmosphere. Lack of soil moisture or decreased moisture in soil is considered to be a factoraccelerating the process of dust storm formation. During the previous decades, water stresses on the ecosystem of Hour-al-Azim have transformed this wetland into one of the main dust centers in the southwest Iran. Hour-al-Azim is one of the largest wetlands in southwestern Iran. This wetland is shared between in Iran and Iraq. It is located between N 30° 58´- N31° 50´ and E 47° 20´- 47° 55´. The Iranian part of this wetland encompassed an area of 64,100 ha in the 1970s, while in the 2000s, the area has decreased to only 29,000 ha. The present study aims to monitor the spatial-temporal variability of soil moisture in Hour-al-Azim wetland and to investigate the relation between these changes and dust storms in the southwest Iran. To reach this end, we used 8-day images obtained from the Aqua satellite in the period of 2003 to 2017 and also annual frequency of dust storms with a visibility of less than 1000 m in the period of1987–2017. A database consisting of 189 images of the red band, near-infrared band, and ground surface temperature (LST) was created, which contained 4 images per year (one image per season). The resolution of the red / near-infrared band data and daily LST values were 231.65 and 926.62 meters, respectively. Then, soil adjusted vegetation indices (SAVI) and perpendicular soil moisture index (PSMI) were extracted. SAVI index is used to reduce the effect of background soil on vegetation cover in semi-arid and arid environments with less than 30% vegetation cover.Compared to NDVI, SAVIwith L = 0.5reduces the effect of soil changes on green plants. In the next step, a trapezoidal method was used to calculate the PSMI index. In order to investigate changes in the soil moisture content of the Hour-al-Azim wetland, three time series obtained from regional mean of SAVI, LST and PSMI remote sensing indices and a time series consisting of the number of days with dust storms observed in the 9 stations were evaluated using simple linear regression test. Results and discussion Extracting Soil Adjusted Vegetation Index indicated that in the study period, the highest values of this index was observed with a regional mean of 0.15 on 4/7/2014 and the lowest values was observed with a regional mean of 0.08 on 1/1/2005. Land Surface Temperature survey showed that during the study period, the highest values of this index was observed with a regional mean of 54.42 ° C on 7/4/2010 and the lowest values was observed with a regional mean of 17.28 ° C on 1/1/2007. The regional mean of Perpendicular Soil Moisture Index indicates that despite winter is considered to bethe wettest season of the region, PSMI index with a regional mean of 0.2 has experienced the driest soil moisture conditionsat the beginning of winter (1/1/2016),while it had experienced the wettest soil moisture conditionsin the same season on 1/1/2009 with a regionalaverage of 0.13. Conclusion Finding of the present study indicate an increasing trend in the range of remote sensing indicators. The range of SAVI index is increasing, which means that the density of vegetation in the Wetland is decreasing. Perpendicular Soil Moisture Index values also show an increasing trend, indicating a decrease in soil moisture content. As a result of the decrease in soil moisture, the vegetation density also has decreased and the land surface temperature has increased. Results of statistical tests indicate the role of changes in environmental conditions of Hour-al-Azim wetland in the frequency of dust storms. Using findings of the present study, or studies such as Kim et al. (2017), it is possible to take advantage of soil moisture variations for the prediction of dust generation, its emission, and spread level.
