Agricultural Meteorology
Firooz Abdolalizadeh; Ali Mohammadkhorshiddoust
Abstract
IntroductionHeavy rains often occur in small areas, but they may be the result of large-scale systems and their energy and moisture are provided from distant areas (Mohamadei et al., 2010). Therefore, identification of synoptic systems is of great importance in order to predict precipitation. Although ...
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IntroductionHeavy rains often occur in small areas, but they may be the result of large-scale systems and their energy and moisture are provided from distant areas (Mohamadei et al., 2010). Therefore, identification of synoptic systems is of great importance in order to predict precipitation. Although rain has many positive effects on human life, heavy rain can cause one of the most dangerous and damaging natural disasters, namely floods. Every year, floods cause many human and financial losses in different regions of the world. Floods are more effective in vulnerable areas and cause the loss of human lives, damage to property and products, disruption of transportation and services, and other economic losses (Kheradmand et al., 2018). In March 2019, heavy rains occurred in Golestan province, which caused flooding in parts of this province, especially in the cities of Gonbad-Kavus and Aqqala. Most of this heavy rain and flood occurred in the Gorgan River basin. According to meteorological reports, the rain started from the night of 03.17.2019 and continued until 03.21.2019, although the heaviest rainfall occurred from the 03.18.2019. The volume of the flood was so great that the dams on the Gorgan River could not accommodate it. According to the reports of the regional water company of Golestan province, the flood entered the Bostan dam at 1 am on 03/19/2019, and after passing through it, entered the Vashmgir dam at 6 am, and then on 03.21.2019 entered the city of Aqqala. The damage of this flood was estimated at about 4800 billion Tomans, which includes damage to 17800 residential units, damage to farms, transportation infrastructure, 40% reduction in tourism, damage to industrial units, unemployment of about 3000 people, and damage to the nomads of the province. (Islamic Republic News Agency, 04.09.2019). Considering the heavy damage caused by the mentioned heavy rain and flood in Golestan province, it is necessary to identify and analyze the causes of its occurrence in order to plan and take the necessary measures to prepare and deal with such incidents.Materials and MethodsThe study area is Gorganrood watershed, most of this area is located in Golestan province. Golestan province is one of the northern provinces of the country and is located in the southeast of Caspian sea. In this research, in order to identify and analyze the heavy rain that occurred in Golestan province in March 2019, which led to severe flooding, several types of data were used (data from meteorological stations, NCEP/NCAR reanalyzed data, MODIS satellite images, GPM precipitation products). First, using the rainfall data of the synoptic stations located in the Gorgan River watershed, the time of heavy rainfall was identified, and then using the data of the aforementioned stations and several stations outside the basin, a rainfall zoning map was prepared. MODIS satellite images were also used to check the position of precipitation system and cloudiness of region. Using GPM satellite rainfall products called IMERG, which were extracted on a half-hourly basis, as well as the main synop reports of meteorological stations, which are reported on a six-hourly basis, the intensity of rainfall was investigated. In addition, the physical conditions of the basin were investigated using the topography and slope map of the basin prepared from the DEM layer of the region. In the following, using the reanalyzed data of the NCEP/NCAR database (National Center for Environmental Prediction - National Center for Atmospheric Research of the United States), synoptic maps including maps of land surface pressure, geopotential height of the upper atmosphere, Omega (indicates the speed of vertical movements of the atmosphere), wind direction and speed, moisture flux convergence function, frontal function, specific humidity, atmospheric precipitable water and Hoff-Müller diagram were drawn to identify the synoptic and dynamic factors of the mentioned precipitations.Results and DiscussionThe results of the present research in the analysis of flood factors can be summarized as follows:Survey of the topography and slope of the Gorganrood basin revealed that the physical conditions of the basin are such that the potential for flooding is high.The amount of rainfall in 24, 6 and a half hour intervals in the study area were investigated and it was shown that the rainfall occurred on March 17, 18 and 19, especially on March 18, in terms of the intensity of rainfall were very intense.Investigation of the state of the middle troposphere showed that the formation of the Rossby wave and the meridional expansion of one of its troughs, along with the creation of a positive vorticity that dominated the studied area on the seventeenth of March, are the main factors in the creation of a baroclinic atmosphere and the dynamic ascent of air.Investigation of the synoptic-dynamic conditions of the lower levels of the troposphere showed that in the lower levels of the low-altitude synoptic system with closed meters, at the same time as the deep trough reigns over the region, it has been formed and strengthened during peak rainfall times and has led to a strong rise of air.Investigating the state of atmospheric humidity in the study area and identifying sources of moisture supply using special humidity maps, moisture flux convergence function and atmospheric flow paths were carried out.Investigating the omega variable in the vertical profile of the atmosphere using the Hoff-Mueller diagram showed that during the times of precipitation events, upward movements prevailed in all levels of the troposphere, especially during the peak of precipitation, the upward movements became more intense in the lower levels.Identifying the type of clouds using MODIS products showed that during heavy rains, especially on March 18, deep convective clouds with a high density of water were formed in the region, which extended up to a height of 300 hectopascals and were very thick.
M. Mahmoodi; M. Honarmand; F. Naseri; S. Mohammadi
Abstract
Introduction: Runoff estimation is one of the main concerns of hydrologists and plays a key role in various engineering calculations and designs. Many factors such as climate, topography, soil properties, land cover, etc, are involved in producing surface runoff. Land use and land cover changes have ...
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Introduction: Runoff estimation is one of the main concerns of hydrologists and plays a key role in various engineering calculations and designs. Many factors such as climate, topography, soil properties, land cover, etc, are involved in producing surface runoff. Land use and land cover changes have a direct impact on the hydrological cycle in the ecosystem. The most common model of surface runoff estimation is the curve number model developed by the US Soil Conservation Service (SCS-CN). Accurate estimation of its important parameters increases its precision and performance. Land use is one of the most important parameters of this model.Remote sensing (RS) and geographic information system (GIS) technologies are used in order to increase its speed and accuracy of estimation. One of the problems that have occurred in the Kashaf-Rood Basin is the extensive land use changes that may cause changes in peak discharge and surface runoff volume. In this study, due to the great importance and impact of land cover change on increasing flood risk, the effects of land use change over 28 years (from 1987 to 2015) on flood hydrograph characteristics were investigated.
Materials and Methods: The Kashaf-Rood basin is a part of the Ghara-Ghum basin. The total area of the basin is 16779 square kilometers with the highest and lowest elevation of 3235 and 378 meters above sea level, respectively . The length of the Kashaf-Rood River from the highest point to the outlet of the basin is about 374 km and its average and gross river slope are 0.0028 and 0.0043 m/m, respectively. The digital elevation model was used to calculate the topographical properties, hydrological properties and geometrical corrections required on satellite images. In this research, the data of the Global Digital Elevation Model (ASTER) with a spatial accuracy of 30 m was used. Also, the soil hydrologic group map prepared in Ghara-Ghum water resources balance studies was used. Since no land use change occurs in the short term and can be detected at long intervals, a 28-year interval was chosen for satellite imagery. In general, five images of Landsat satellite are needed for full coverage of the Kashaf-Rood Basin. For the oldest data, Landsat 5 images and for the latest data, Landsat 8 images were used. ERDAS IMAGINE 2014 software was used to digitally process satellite images. The images were classified in three methods: The Minimum distance, Mahalanobis distance and the Maximum Likelihood. In order to select the appropriate method, after applying different classification algorithms for the image of 2015, the accuracy of their classification was evaluated and, the image of 1987 was also classified based on the selected method. By combining soil hydrological group and land use map derived from Landsat satellite imagery using ArcGIS 10.3 software, the curve number maps for 1987 and 2015 were prepared. In the present study, the US soil conservation service standard curve number method (SCS-CN) was used to calculate the amount of rainfall and losses in the HEC-HMS model. For the calibration of the HEC-HMS model, four flood events at the bridge of Khatun Kashaf-Rood hydrometric station with relatively concomitant precipitation were selected. Three flood events were used for calibration and one flood event for validation.
Results and Discussion: The images were classified into three methods: The Minimum distance, Mahalanobis distance, and the Maximum Likelihood. Comparing the results of these three methods showed that their overall accuracy in evaluating and identifying land use was 78.5, 83.7 and 87.3, respectively. Thus, the maximum likelihood algorithm was used to classify the images and the image of the year 1987 was classified with this method. Ten land use classes were identified in the study area. The results showed that during the 28 years of study, the area of rocky lands and rangelands did not change. The highest percentage of change was due to water zones, poor rangelands and residential lands, which increased by 189, 143 and 50 percent, respectively. The highest amount of increase in the area occurred in the poor rangelands, which 1514 km2, and the highest decrease occurring in moderate rangelands which is 1278 km2. By combining soil hydrological group maps and land use maps in ArcGIS software and using standard tables, the curve number maps for 1987 and 2015 were prepared. The weighted average of the curve number in the mean moisture conditions for 1987 and 2015 was 77.5 and 78.4 units, respectively. After performing the calibration and validation steps, the HEC-HMS hydrological model was used to investigate the impact of land-use change on the flood hydrograph of the Kashaf-Rood River between 1987 and 2015. According to the results, in all four events which were studied, land-use changes have increased the peak of discharge and the flood volume over the 28 years of study. On average, the peak flood discharge in 2015 was 15.2% higher than the peak flood discharge in 1987, and similarly, the flood volume increased by 13.7% during the study period.
Conclusion: In conclusion, it can be derived that in recent decades, land-use changes which were caused by human interference, affected the flood characteristics and increased the risk of flooding in the Kashaf-Rood river. Therefore, land use must be managed and prevented further destruction of natural resources to prevent flooding in the area.
Khodayar Abdollahi; Somayeh Bayati
Abstract
Introduction: Curve number (CN) is a hydrologic parameter used to predict the direct runoff depth or the excessive rainfall that infiltrates into the soil. This parameter, which indicates surface water retention, is very important in the processes relating to flooding. Vegetation of the region is a major ...
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Introduction: Curve number (CN) is a hydrologic parameter used to predict the direct runoff depth or the excessive rainfall that infiltrates into the soil. This parameter, which indicates surface water retention, is very important in the processes relating to flooding. Vegetation of the region is a major factor affecting peak flow and flood volume. The peak flow is highly influenced by the land surface characteristics, for example at the time that vegetation coverage is naturally low or while vegetated areas are decreasing, the peak discharges increase as well. In this study, the flood hydrograph of Kareh-Bas Basin was simulated using the HEC-HMS model. The simulation was used to estimate the values of the annual curve number in the basin of interest.
Materials and Methods: Model data requirements for this study were temperature, precipitation, and evapotranspiration and discharge time series. The model was calibrated for the period 2000-2010. Then, the model was implemented independently for simulating of rainfall-runoff for each year without any change in the optimized parameters. The model was calibrated only by changing curve number. The average curve number of the basin for each year was computed using the weighted mean method. The MODIS leaf area index raster maps were downloaded from the Modis site. The maps were converted into ASCII format for spatial statistics and calculating the monthly spatial average. The correlation between the curve number and leaf area index was investigated by a nonlinear curve fitting. This lead to the development of a curve number as a function of the vegetation cover for each year. Finally, the accuracy of the developed relationship was investigated using the Nash-Sutcliffe efficiency coefficient by comparing the curve number obtained from the HEC-HMS model and the simulated values from the new relationship.
Results and Discussion: The obtained Nash-Sutcliff coefficient of 0.58 showed that the HEC-HMS model was capable to simulate the flood hydrograph with relatively good accuracy. The sub-basin spatial mean showed that the sub-basins 1 and 2 take the highest curve number values. This indicates that surface water retention in these sub-basins is less than the other sub-basins, which may lead to a sharper hydrological response or flood. In sub-basins 3 and 4, where vegetation density is higher thus land use acts as a predominant factor in hydrologicalbehavior of these sub-basins, the curve number was lower. The study shows the hydrological response depends on the temporal variation of the land cover, for instance in 2010, when the leaf area index increased by a factor of 1.4, the curve number has decreased to 47. As it is predictable with decreasing vegetation the peak discharge and flood volume was increasing. We found a direct nonlinear relationship between basin scale Leaf Area Index and Curve Number with a correlation coefficient of 0.7, indicating that the variation of the curve number is a function of the leaf area index. The developed model allows calculating curve number values based on the remotely sensed leaf area index. This relationship can be used as an auxiliary function for capturing the vegetation changes and dynamics. The accuracy of the derived equation was evaluated in terms of Nash-Sutcliffe's efficiency coefficient. A value of Nash-Sutcliff coefficient of 0.72 showed that this relationship is good enough for calculating basin or sub-basin curve number values capturing the dynamics of leaf area index.
Conclusions: The obtained Nash-Sutcliff efficiency coefficient from HEC-HMS showed that the model was able to simulate the flood hydrograph of Kareh-bas basin with relatively good accuracy. However, the visual interpretation shows there is a weakness in the simulation of the falling limb of the simulated hydrographs. This may be an indication that the drainage of stored water at the basin was not well-simulated by the model. In general, it can be said that peak discharge and flood volume were under-estimated. By increasing the curve number, the peak discharge values also were increasing. The pair data for spatially weighted values for curve number and averaged annual leaf area index showed that an increase in leaf area index leads to a lower value in obtained curve number. This may result in lower peak discharge and volume of the flood. Such relationships may be taken as a measure for flood control. Meanwhile remotely sensed leaf area index products may be considered as an opportunity to capture the dynamics of the land cover.
