Milad Soltani; Adel Soltani; Mahin Kalehhouei; Karim Solaimani
Abstract
Introduction
Drought is a serious danger with very extensive impacts on the soil, economy, and the threat to the livelihood and health of local communities. This disaster as an unpleasant climatic phenomenon that directly affects the communities through restrictions on access to water resources, causes ...
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Introduction
Drought is a serious danger with very extensive impacts on the soil, economy, and the threat to the livelihood and health of local communities. This disaster as an unpleasant climatic phenomenon that directly affects the communities through restrictions on access to water resources, causes high economic, social and environmental costs. Meteorological drought indicators are calculated directly from meteorological events such as precipitation, and in the absence of these data, drought monitoring will not be useful. Due to the fact that meteorological drought indicators are only valid for a single location and do not have the required spatial resolution and are also dependent on weather station information, and these stations are often distributed distantly, the reliability of these indicators has been questioned. Given the characteristics of satellite data such as spatial and temporal resolution, extensive coverage of studied areas, and direct investigation of vegetation status by satellite indices, many studies have been carried out for drought modeling using this technology and these indicators. Over the past four decades, far-reaching drought monitoring tools have been widely developed and drought monitoring models are widely proposed, which are generally based on vegetation indices, surface temperature, humidity and reflection in the visible and infrared regions. These include leaf water content index, vegetation cover index and temperature - drought - vegetation index. Therefore, remote sensing techniques can be a useful tool in drought monitoring. The purpose of this study is to monitor drought and vegetation health in the city of Kermanshah using LANDSAT satellite imagery. For this purpose, first, by examining the rain-gauging and synoptic data of existing stations and using the standard precipitation index model, the driest year and one wet year were selected as the sample. In this study, two years of 2015 and 2016 were selected as the dry and wet years and then, the vegetation cover of the region was compared with the Landsat images. To use these images, it is first necessary to make sure that there is no geometric error. For this purpose, the road vector layer was used, which was revealed that the images have geometric errors. Images with less than a half-pixel error were corrected geometrically using 21 and 24 auxiliary points. The adaptation of the vector layers with the roads existing in the image indicated the accuracy of the correction. At the next stage, the driest year and one wet year were selected as samples by examining the rain-gauging and synoptic data of the existing stations and by using the standardized model of rainfall index. At the next stage, the Temperature Condition Indices and Vegetation Health Index (VHI) were compared in two wet and drought periods were studied in order to determine the differences of these indices during a dry year and a year with high precipitation. For this purpose, each of the aforementioned indices was built using the LANDSAT-8 imagery, and the stages of building these indices were subsequently presented. The required pre-processing and processing as well as the geometric and radiometric corrections were first performed on the satellite images. Then, temperature condition indices, vegetation status index and vegetation health index were prepared for drought monitoring. Considering that, the meteorological drought indices are only valid for a single location and lack the required spatial resolution and are also dependent on the information of the meteorological stations, and these stations are often distributed far apart from each other, the reliability of these indexes has been questioned. Satellite data characteristics like high spatial and temporal resolution, extensive coverage of the study areas, and direct survey of the vegetation status by the satellite indexes have led to a large number of studies on drought modeling using this technology, and the confirmation of the use of these indices. The aim of this study is to determine the moisture, heat and health of the vegetation using the LANDST images. Thus, the results of the study in the next stage indicated that the LANDSAT images and the built indices have the required capabilities to monitor drought. The results of this research can be a proper option for decision-makers to effectively supervise, examine and resolve the drought conditions and double the necessity of profile definition. Supplementary studies are suggested for spatial drought monitoring by satellite imagery through ground measurements of the quantitative changes in the coverage and temperature of the earth’s surface. There are limitations in the use of NDVI and satellite thermal bands. These include weather and cloud conditions that should be considered. Using maps obtained from the drought monitoring and evaluating indices can help improve drought management programs and play a significant role in reducing the effects of drought. Using vegetation health status index, it was determined that the vegetation status has had a lot of changes during drought compared to the wet period, hydrological drought has had a major share in the destruction of vegetation and drying of the lakes and, consequently, the abandonment of agricultural lands and the lack of access to alternative water resources, as well as the lack of groundwater resources or the lack of alternative surface water resources have intensified, and it seems that, this part of Iran will face numerous problems if the drought continues in the coming years and the appropriate methods are not used to deal with it. Also, given that the water resources of the region are going to decrease in the coming decades, the necessity of using comprehensive water management methods in all sectors, including the reserve, transfer and distribution sectors seems very essential and inevitable. Finally, it is expected that the trend of destruction of vegetation decreases in the future by applying proper management practices, sustainable water distribution, regional negotiations, methodical agriculture as well as the establishment of optimal hydrological conditions.
Yaghoub Niazi; Ali Talebi; Mohammad Hossein Mokhtari; Majid Vazifedoust
Abstract
Extended abstract
Introduction
Droughts are long-term phenomena that affect vast areas, causing significant economic damages andlosses in human lives. Droughts are the most costly natural disaster in the world, and affect more people than any other natural disaster. Therefore, it is important to develop ...
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Extended abstract
Introduction
Droughts are long-term phenomena that affect vast areas, causing significant economic damages andlosses in human lives. Droughts are the most costly natural disaster in the world, and affect more people than any other natural disaster. Therefore, it is important to develop early warning systems to mitigate the effects of drought. The easiest way to monitor drought is to use drought indices that calculate drought severity, duration and actual range for each drought type. Several drought indices have been developed based on different variables and parametersto assess drought types. Soil moisture is a significant hydrological variable related to flood and drought and plays an important role in the process of converting precipitation into runoff andstorage of groundwater. Due to the difficulty, cost and time required for the field measurements of soil moisture, this parameter has not been widely used in drought indexes. Recent developments of global databases, based on satellite estimates, as well as rapid progress in hardware and software for modeling complex processes governing the water balance at the ground surface, have led to many efforts to deploy this new tool to reduce the limitations in this field. In this research, a new drought index based on soil moisture, derived from the land surface models of Global Land Data Assimilation System (GLDAS-SMDI) has been provided to monitor the evolution of drought severity.Thisindex is based on the fact that soil moisture is a determinant factor in most of complex environmental processes and has an important role in the occurrence of drought.
Materials and Methods
The central Iran is located between 27N-37N latitudes and 48E-61E longitudes with an area of about 837,184 km2. There are 50 synoptic stations within the area. In the present study, soil moisture derived from Global Land Data Assimilation System using the GLDAS-SMDI index was used to prepare the spatial distribution map of drought in central Iran over the period of 2001-2004. The accuracy of the GLDAS-SMDI index based on satellite data was carried out using the evaluation criteria of R and RMSE compared with drought spatial distribution map derived from the SPI index based on monthly precipitationdata of 50 synoptic stations.
Results and Discussion
In this study, the drought spatial distribution index of Soil Moisture based on the Global Land Data Assimilation System (GLDAS-SMDI) and SPI was obtained based on the monthly precipitation data from 50 synoptic stations over the period of 2001-2004. The results of the statistical criteria of the moisture drought spatial distribution mapcompatibility assessment based on GLDAS data with corresponding pixels on the drought spatial distribution map based on the precipitation data of thesynoptic stations showed that the drought severity map has had a high precision and good conformity with the land data (R=0.65, RMSE=0.22) based on GLDAS data.The highest correlation coefficient (0.74) was in 2004 and the lowest (0.45) in 2003.
The lowest and the highest mean errors in 2004 and 2001were 0.19 and 0.26, respectively,.The highest droughtseverity based on the GLDAS-SMDI index occurred in the Central Iran region at Iranshahr, Kahnuj, Bam, Baft and Birjandstationsduring the studied period.
Conclusion
Droughts are hydro-meteorological anomalies characterized by prolonged shortage in regional water supply and can cause temporary difficulties (even failures) in water reservoirs. Today, most of the severe droughts are breaking out in terms of frequency, magnitude and duration due to constantly increasing water consumption, causing serious social, economic and environmental problems worldwide. Therefore, in order to deal with frequent droughts, great efforts have been made to estimate a more accurate assessment for better decision-making in order to prevent and mitigate drought losses. The most successful efforts among these methods might be the development and the use of various objective indices. In this research, the monthlymoisture data of the Global Land Data Assimilation System was evaluated to estimate the drought severity index based on soil moisture. The evaluation was performed using the coefficient of determination (R2) and Root Mean Square Error (RMSE). This analysis has demonstrated that the GLDAS products have very good compatibility with the land data over the selected area of Central Iran on monthly timescales and a 0.25° spatial scale. As a result, it can be said that the GLDAS data has a good potential for useful application of hydrological simulation and the calculation of water balance sheet, in the regions with low observations and low quality station. Therefore, it can be concluded that the soil moisture output of Global Land Data Assimilation System can be used for rapid and low cost estimation of drought severity based on soil moisture, which is a major factor in many complex environmental processes and has an important role in the occurrence ofdrought. In order to increase the spatial accuracy of drought intensity maps, it is recommended that the satellite data be combined with the values of ground stations.
