Journal of Spatial Analysis

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Groundwater resources are important sources for the supply of water in agriculture, industry and drinking in Ardabil plain, therefore underground water resources planning and sustainable management of these resources are important. The purpose of this study is grading the villages in the plain of Ardabil in underground water crisis and changes during the years 1360-1391. The information obtained from 39 wells, piezometers in plain of Ardabil. Using simple techniques and fuzzy cumulative weighting and interpolation methods, the piezometers interpolation of shallow water table and how it changes during the period is showd.

Introduction
     Groundwater is one of the main sources of drinking water supply for many people around the world, especially in rural areas. Groundwater can be contaminated by natural or human activities are numerous. All activities including residential, municipal, commercial, industrial and agriculture can affect groundwater quality. Groundwater contamination can result, such as the loss of a source of water supply, high cost of clearing the high cost of alternative water supply or cause potential health problems. Given the importance of determining the results of the plains of the country, the aim of this study was to determine changes in aquifer storage of Ardabil using statistics and analysis on multi-criteria decision-making and evaluation of groundwater is a crisis situation.

Data and Methods

     In this study, the data of piezometers wells in of Ardabil plain scattered through the city of Ardabil Regional Water Authority have been prepared. Also, the surface layers and point to the plains of Ardabil, political divisions and the location of wells, piezometers villages for final maps have been used. The data of deep wells, as well as cultivation of four major product with a high water requirement of wheat, barley, potatoes and forage to determine the relationship between ground water and water harvesting has been a drop in water table.

The study area

     Plain study area is located in the north-west of Iran in Ardabil province (Figure 2 and Figure 3).  The average height is about 1360 meters above sea level  It covers an area of approximately 820 square kilometers and is located in the Gharasoo watershed.

• Inverse Distance Weight;
• Global Polynomial Interpolation;
• Local Polynomial Interpolation;
• Radial Basis Functions;
• Straight Ranking;
• Fuzzy Normalized;
• Fuzzy multi-criteria decision-making;
• FSAW.

   The first step is to evaluate each process and required hydrological data collection, and the coordinatingits location. The geostatistical methods of IDW, GPI, LPI, and RBF in the ArcGIS software were used for  interpolating all existing data and a drop in water table in the area of standards for grades 10 class (raster) within restricted fields of Ardebil were determined.

    Finally, using simple collective weight, weight-bearing layers and layers of loss data water table for the years 60 and 90 is obtained. To get the final map of water table drops, the two layers are deducted and the final map of Ardabil plain water table drop that phase is obtained.

     Analysis showed the reduction of water table almost 47 percent in 1391 compared to 1360. As can be seen in Figures 12 and 13, maximum of 45 meters water table wells, piezometers in 1360 to more than 70 m in 1390 has come to reveal the deterioration of the aquifer Ardabil.

    Pholadloo_e_Shomali district with the highest concentration of deep wells in the near future to continue the removal of existing deep wells, groundwater resources will go into sharp decline.

    Sharghi Village goes to the crisis and in the meantime, the central Vilkij district includes the eastern part of the plain, the drop in water table aquifer at greatest risk to the two villages in East and Central Vilkij.

• Due to the limitations of traditional agricultural development potential ground water;
• Increase the efficiency of irrigation, changing crop patterns of water needed to fill low-power consumption;
• Efficient use of water resources and prevent unauthorized digging deep wells to exploit the nutritional front, especially in the East and Southeast plains.

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Assessing the Homogeneity of Temperature and Precipitation Data in Iran with Climatic Approach
 
Extended Abstract:
Qualitative evaluation and validation of atmospheric parameters such as precipitation and temperature are the most important condition for statistical analysis in climatic and hydrological researches. In addition, the meteorological and climatological data have a crucial role in transportation, agriculture, urbanization and health services.  Therefore, it is clear that using wrong data source for atmospheric investigations is the first hazard in natural hazards analysis. This study aimed to investigate the homogenization of minimum and maximum temperatures and precipitation data for 36 weather stations over different climatic classes in Iran. The Standard Normal Homogeneity Test (SNHT), (Alexanderson and Moberg, 1997), Pettit test (Pettit, 1979), Cumulative Deviation test (Buishand, 1982) and Worsley’s Likelihood Ratio test (Worsley, 1979) were carried out to study homogenization of minimum and maximum temperatures and precipitation data (1966-2015). The results revealed that 91.5 % and 88.5 % of minimum and maximum temperatures data, respectively, were in non-homogenized category. Although, Isfahan, Saghez and Gorgan for minimum temperature and Bandar-e Anzali, Sharekord, Kashan and Saghez for maximum temperature showed a homogenized condition with 5 % level of significance. The results showed most of the weather stations (28 out of 36 stations) had homogenized precipitation data. Even though, seven stations including Birjandd, Kerman, Kermanshah, Saghez, Sanandaj and Tabriz had homogenized precipitation data. The Urmia weather station was in doubtful class. That is precipitation data of Urmia weather station were homogenized by two tests results and were non-homogenized with other two tests of homogenization. The spatial distribution of trend variations of minimum temperature average was between -2.8 to 2.8 degree Celsius over the country. Moreover, maximum and minimum variations of minimum temperature occurred in northeast and northwest of the country, respectively. There were a significantly increasing trend (p<0.01) in most of the regions. The results also indicated that the significant variations happened for maximum temperature in most of the weather stations, mainly in northern half of the country. The minimum temperature jump was mostly found in 1985, 1994 and 1998 years during the study period (1966-2015). The maximum variations of minimum temperature were in Mashhad, Shahroud, Ahvaz, Yazd and Semnan weather stations with 2.8, 2.3, 2.2, 2 and 2 degrees Celsius, respectively, jump for above mentioned years during 1966-2015. In addition, the minimum change in minimum temperature was occurred in Birjand, Urmia and Bandar Abbas with a jump of 0.6 degrees Celsius. It should be mentioned that, unlike other stations, the Khorramabad (Lorestan Province) and Fasa (Fars Province) had a decreasing trend for minimum temperature. It changed from 10.3 to 8.3 and from 11.8 to 10.2 degrees Celsius in Khorramabad and Fasa, respectively. The results showed that the commencement of maximum temperature jump for most of the weather stations happened in 1998 with 1.1 degrees’ Celsius change. According to our study, a remarkable decrease in precipitation data was occurred in west and northwest of the country. There was a depletion of 80 to 150 millimeters from 1998 in Tabriz, Sanandaj, Saghez and Kermanshah weather stations during study period (1966-2015). Besides, 25 to 45 millimeters reduction in precipitation was found in south and southeast of the Country which has arid climate including Birjand (South Khorasan Province), Zabol (Sistan and Baluchestan Province) and Kerman. It was revealed that the variations of minimum temperature were larger than maximum temperature which was in agreement with results obtained by Rafati and Karimi, 2018. The results showed that the start of increasing maximum temperature in most of the weather stations was in 1998. It could be due to increasing the global temperature which is in accordance with results found by Steirou and Koutsoyiannis, 2012. The results revealed that about 80 % of precipitation data of weather stations were homogenized. These results were in agreement with results obtained by Hosseinzadeh Talaee et al., 2013. The results indicated that tests of homogenization for minimum and maximum temperatures and precipitation data could use in different climate over the country. Therefore, it could not allocate a single test to a particular climate type. In conclusion, it should be noted that before any analysis pertaining to environmental hazards, the calibration and maintenance of the weather instruments should be carried out periodically. In addition, the metadata and station history for relocation of the weather station should be checked. The relocation can create great changes in meteorological parameters due to elevation, latitude, longitude and land use/land cover differences between two sites.
 
Key Words: Homogeneity tests, Climate Data, Weather Station, Metadata
 
 
 

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Today, the impact of climate is considered on the life, health, comfort, activity and behavior in a form of the branch of science   such as human biology. Due to difference of frequency people with each other, the sensibility of every one from weather can be different from the other one that's why the climate can’t be totally undesirable or the climate can be totally desirable for all the people, so we can say that all of climatic elements are affected on human comfort but the effect of some of them is quite cleared and the effect of the others is mild and sometimes invisible. The greatest effect on comfort and discomfort can be included temperature, humidity and solar radiation. The aim of this research is to investigate and determine    the area risk of climatic comfort. For this purpose, the temperature, precipitation and humidity data have been extracted for Khuzestan province form Esfarazi database. In this approach, first different properties of the temperature, precipitation and humidity for the area with climatic discomfort   have discussed   based on the conditional probability distribution. This study has been identified the areas of climatic comfort in Khuestan province using multivariate analysis (Cluster analysis and Discriminant analysis) and spatial autocorrelation pattern (Hot Spot index and Moran index) with an emphasis on architecture. The results showed that the risk area of climate comfort is included mostly  of  the western parts of  Khuzestan province namely the border areas with Iraq and some parts of  southern  of  province .On the other hand ,trend analysis the  range of this area to climatic discomfort indicated that it has increased significantly  in  recent periods .The results also  showed that  the local distribution of   precipitation  in all periods in the areas of climatic discomfort  has  been   a high  the coefficient of  variations.

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 Relationship between hydrogeomorphic features and suspended sediment load under Kashfarud basins
 
Introduction
As a stressful stimulus, river sediment is the most significant threat to aquatic ecosystems. To prevent or minimize the damage, three stages of the erosion process should be investigated (Naseri et al., 2019: 83). Determining the amount of sediment transported by rivers is important from different aspects. Sediment carried by water flows is considered a factor effective in shaping the geometric structure and geomorphic characteristics of rivers (Tashekabood et al., 2019: 282).
Data and methodology
To estimate the amount of annual suspended sediments, the flow and sediment statistics of hydrometric stations (8 stations) and meteorological stations (13 stations) were employed (Figure 2). The research statistical period is 25 years (1993-2017). The altitude, area, and perimeter of the basins were obtained from topographic maps with a scale of 1.25000. To investigate the correlation between independent and dependent variables, the normality tests of Shapiro-Wilk and Kolmogorov-Smirnov were performed in SPSS16 software. To extract the geomorphic features of the basins, the digital elevation model was used. Then, ground surface corrections and pretreatments such as removal of hydrological pits were performed and ground drainage pattern was determined.
Stepwise multivariate regression
In the present study, stepwise multivariate regression was used to reduce the number of independent variables and determine the effective factors in the sedimentation of the basin. This method investigates the effect of several independent variables on a dependent variable (Zare Chahuki: 2010). In stepwise multivariate regression, the independent variable that has no more significant effect on the dependent variable is removed from the analysis, hence excluded from the equation. The general form of the stepwise regression equation is:
Equation 1                                                                            Y= a + B1X1 + B2X2 + …… + BnXn + e
Data description and interpretation
The principal component analysis method was used to determine the most effective characteristics of sediments as well as their grouping. In principal component analysis, variables that have a high correlation and are distributed in a multidimensional space are reduced to a set of non-correlated components, each of which is a linear combination of the main variables. The obtained non-correlated components are called principal components (PCs). Prior to component analysis, the KMO coefficient was used to ensure the appropriateness of the data for principal component analysis. This coefficient fluctuates in the range of zero and one and if its value is less than 0.5, the data will not be suitable for principal component analysis and if the values of this coefficient are between 0.5-0.69, The proportionality of the data is moderate and if the value of this coefficient is more than 0.7, the data will be quite suitable for performing principal component analysis.
Regression analysis results
In this study, the sediment weight of the basin was considered as a dependent variable and other parameters as independent variables. The variables of slope, precipitation, basin length, Elongation Ratio (R), circularity coefficient, and unevenness of the basin have a higher correlation with the amount of sediment production in the basin than other variables.
An eigenvalue was used to determine the number of factors. The minimum eigenvalue for the selection of final factors is 1, and factors with an eigenvalue bigger than 1 are considered final factors. The results showed that the three factors of circularity coefficient, compactness coefficient, and basin form coefficient have an eigenvalue bigger than 1.
Conclusion
The results showed that geomorphic parameters have a high correlation with the amount of annual sediment. The results showed that seven factors of slope, precipitation, basin length, elongation ratio, circularity coefficient, unevenness coefficient, and form ratio of the basin were the most important in estimating the amount of suspended sediment based on the principal components analysis method. The average of special sediment varies from 134 tons per year in Dehbar basin to 16 tons per year in Kardeh basin and also the average annual sediment varies from 261.6 tons per year in Golmakan basin to 156.7 tons per year in Shandiz basin. Evaluation of Bartlett's test of sphericity tests and KMO values is 0.9. Therefore, the data is suitable for factor analysis. The percentage of variance explained by each factor indicates that the circularity coefficient with 50.71% of the variance explains all the research variables. In total, three factors of circularity coefficient, compactness coefficient, and form ratio of the basin could explain 82.6% of the variance of all research variables. Therefore, the results are consistent with Lu et al. (1991), Sarangi et al. (2005), Tamene et al. (2006), Zhang et al. (2015), Salim (2014), and Ares et al. (2016).
Khorram Dareh sub-basin with heavy rainfall (504 mm) has the lowest specific sediment, which is due to the geological structure of the region. Based on the calculated indicators, most of the studied sub-basins are elongated. The form ratio of the basin is less indicative of the elongation of the basin. The highest branching ratio of the basins is in the vicinity of faults. Also, high circularity values indicate points prone to sedimentation. River sections up to degree 3 are located in more subdued areas and have a steeper slope. Golmakan, Khorram Darreh, Zashk, and Dehbar sub-basins have a high potential for sedimentation. Regression equations of sediment measurement curves are usually used in sediment load estimates. The most important reason is the ease of application of these equations. According to the research results, it can be concluded that the integrated use of principal component analysis, cluster analysis, and multivariate stepwise regression has a suitable and acceptable efficiency in estimating suspended sediments. Testing the regression model concerning different climatic and hydrological regimes of Iran’s watersheds to achieve an efficient pattern of using these equations can be fruitful in estimating sediment load in different regions.
 
Keywords: Hydrogeomorphic, Sediment erosion, Kashfarud basin, Stepwise multivariate regression

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Determination of flood-prone areas using Sentinel-1 Radar images
(Case study: Flood on March 2019, Kashkan River, Lorestan Province)

Introduction
Although natural hazards occur in all parts of the world, their incidence is higher in Asia than in any other part of the world. Natural phenomena are considered as natural hazards when they cause damage or financial losses to human beings. Iran is also one of the high-risk countries in terms of floods. Until 2002, about 467 floods have been recorded by the country's hydrometric stations. In addition to natural factors such as rainfall, researchers consider human impacts such as destruction of vegetation cover, soil destruction, inefficient management, destruction of pastures and forests, and encroachment on the river are the most important factors for the occurrence and damage of floods in the country. One of the most efficient and emerging tools in flood surveys is the use of radar images. SAR images and flood maps produced by radar images provide researchers valuable and reliable information. Moreover, maps obtained from SAR images help officials to manage the crisis and take preventive measures against floods. The Sentinel-1 satellite is part of the Copernicus program, launched by the European Space Agency, and is widely used in mapping flood-prone areas. The contribution of Sentinel-1 to the application of flood mapping arises from the sensitivity of the backscatter signal to open water. This study aims to determine high-risk and flood-prone areas along the Kashkan River using Sentinel-1 radar images.
Data and Methods
 The study area includes a part of the Kashkan river from Mamolan city to the connection point of this river to Seymareh river, after Pol-dokhtar city. The average annual discharge of the Kashkan river is 33.2 cubic meters per second based on the data of the Pole-Kashkan Station. The length of the river in the study area is about 100 km. To investigate flood-prone areas, we applied pre-processing and image-processing steps to each flood event including SAR images belonging to March 25^th, 2019, March 31^st 2019, and April 2^nd, 2019. SAR images were acquired from ESA Copernicus Open Access Hub. climatic data was downloaded from power.larc.nasa.gov. To create meander cross-sections, the Digital Elevation Model of the studied area was utilized. Cross-sections were created using QGIS software. Pre-processing steps include: applying orbit data, removing SAR thermal noise, calibration of SAR images, de-speckling and topographic correction. In image processing, we applied the Otsu thresholding method to distinguish water pixels from land pixels. In thresholding methods, the histogram of each image is divided into two parts according to the amount of gray composition. The higher the amount of gray (i.e., the pixel tends to be darker), the more pixels represent water, and conversely, the lighter-toned pixels (i.e., pixels that tend to whiten) represent land. The Otsu thresholding method is a commonly used method for water detection in SAR images. It uses an image histogram to determine the correct threshold. The most important feature of the Otsu method is that it is capable of determining the threshold automatically. The Otsu algorithm was applied to all images using MATLAB.
Results
According to the flood maps, on March 25th, 6.51 percent of the study area was flooded, while on March 31th, only 3.96 percent was flooded. This is mainly due to less precipitation on the 31st. On March 25^th the average daily precipitation was 47.46 mm while on 31^st of March the average daily precipitation was 31.64 mm. On April 2nd, however, there was no rainfall, on the day before more than 63 mm of precipitation has occurred. This massive amount of precipitation on the previous day has led to more than 25km2 being flooded in the studied area.
Conclusion
Results showed that meanders and their surrounding areas are the most dangerous sections in terms of flooding. The meander's dynamic and the river's hydrologic processes are essential factors affecting flooding in those sections. Generally, various factors affect flooding and the damage caused by it. This study aimed to determine flooded and flood-prone areas (according to flooded areas in previous events) using new methods in a short time and with high accuracy to use this tool for more accurate zoning and efficient planning in the future. The results showed that radar images are practical, robust, and reliable tools for determining flooded areas, especially for rapid and near-real-time studies of flood events.
Keywords: Floods, Radar images, Sentinel-1Satelitte, Kashkan river



 

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