فصلنامه حفاظت منابع آب و خاک
سال سیزدهم شماره 4 (پیاپی 52، تابستان 1403)

Due to the limitation of water resources, proper use of water is necessary, and the use of appropriate irrigation methods in fields is an appropriate strategies to use water. Water stress can affect crop yield in the field. Therefore, the correct method of irrigation and management of water consumption is one of the basic issues in farms. The deficit irrigation strategy with the water requirement supply approach can be considered as a practical and efficient technique to ensure more crop yield, without compromising the physiological processes and yield. Therefore, the scope of this research is to estimate the amount of water consumed and the amount of evapotranspiration of the bean plant with the aim of evaluating the field conditions and comparing it with Tafteh, Pasquale and Raes methods.

The present study aims to determine the amount of water use and evapotranspiration of bean using Tafteh, Pasquale and Raes methods and based on the inverse solution of the yield production function in Markazi Province and at the Khomin Bean National Research Station at an altitude of 1930 meters above sea level with a length of 49 degrees and 57 minutes of latitude and 33 degrees and 39 minutes of latitude were implemented in 2016 and 2017. In this experiment, the irrigation treatment including furrow and drip-tape as the main factor and, the values of water requirement including 100, 75 and 55% of water requirement as a sub-factor and in the form of split plots in the form of randomized complete blocks design were done in three replications. Cultivated variety was of native type and its planting time was on the 10th and 9th of June respectively in the first and second year. Drip irrigation tapes were placed on the stacks and irrigation was carried out in the same way until the seedling was fully established in the stage of emergence of the third three leaves.

The highest seed yield with an average of 2683 kg/ha was obtained in the furrow irrigation method and by providing 100% of the water requirement. In evaluating evapotranspiration, the root mean square error (RMSE) in Tafteh, Pasquale and Raes methods were 0.160, 117.8 and 0.185 mm respectively and the root mean square normal error (RMSEn) were 0.448, 0.330 and 0.518 percent respectively. The index of agreement or compatibility (d) in Tafteh, Pasquale and Raes methods were 0.295, 0.600 and 0.081% respectively. In the investigation of irrigation water amounts, the root mean square error (RMSE) in Tafteh, Pasquale and Raes methods was 156.7, 117.5, and 181.3 mm, respectively, and the root mean square normal error (RMSEn) was 0.446, 0.335 and 0.516 percent respectively. The index of agreement or compatibility (d) in Tafteh, Pasquale and Raes methods were 0.324, 0.602 and 0.118% respectively.

In general and according to the statistical results, Tafteh, Pasquale and Raes methods had an acceptable estimate of the amount of irrigation water and the amount of evapotranspiration in the furrow and drip conditions under different amounts of water requirement. Therefore, they can be used as appropriate tool in the estimation of water use in the studied area.

In the last few decades, due to the growth of industries, drastic changes have occurred in the climate of the planet, and its average temperature has increased significantly. Land use changes and climate have had a great impact on discharge and sediment production in watershed. The increase in the production of sediments has many harmful environmental and constructional effects; among these effects we can mention the reduction of the useful depth of the dam and consequently the reduction of the life of the dam. The purpose of this study is to investigate the process of sedimentation along the Mubarakabad River (Emamzadeh Ebrahim watershed) and the effect of time on the increase in the sedimentation depth of the Lasak dam reservoir located in Guilan province using the HEC-RAS model in different states for the time range of 1997 to 2071.

Mubarakabad River is one of the main branches of Pasikhan River, which is the most important river supplying water to Anzali wetland. This watershed has various uses, including forest, degraded pasture, medium pasture and good quality pasture, residential, paddy field, etc. To carry out this study, land use changes in the years 1997, 2007, 2020, 2040 and 2071 were used. In order to measure the runoff, sediment and flow rate in the coming years (2022 and 2071) with the help of the LARS-WG statistical model in two scenarios (RCP 4.5 and RCP 8.5) and SWAT tool was investigated. To implement the HEC-RAS model, three models of surface reduction were used: Borland and Miller's method, Moody's surface reduction method and surface increase method. The input variables of the model are loaded in three sections: topographic map, discharge information, discharge-sediment, and sediment grading. The model was calibrated using discharge and sediment data during the study period. In this study, changes in sedimentation along the Mubarakabad River from upstream to the construction site of Lasak Dam were investigated. Also, the sedimentation depth of the dam reservoir was investigated in different years using the HEC-RAS model.

The simulation results of this study showed that with passing of time, the percentage of residential areas will increase significantly and the area of pastures located in the southern part of the basin will decrease. Currently, in this basin, the total area of 1.87 km2 has been allocated to the residential sector, which includes several villages. While in 2071, this amount will reach 21.45 km2. Also, pastures with dense coverage in this basin in 1997 were equal to 99.65 km2, and in 2071 this amount will decrease to 4.82 km2. The results of this study showed that from the source to the construction site of the dam, sediment deposition has increased due to the reduction of the slope, and the largest amount of sediments have accumulated in the reservoir of the dam. It was also observed that with passing time, the depth of sediments behind the dam reservoir has increased significantly, which reduces the efficiency of the dam. The results of this study showed that there is an increasing trend in the sedimentation depth of the reservoir, so that its maximum value was obtained in 2071, equivalent to 39.1 meters from the height of the dam intake. The results of this study show that in the years 2071 and 2040, 2.02 and 1.92 million tons of sediment will settle in the Lasak dam reservoir, respectively.

According to the results obtained from the HEC-RAS model simulation in the Emamzadeh Ebrahim watershed, it can be seen that if detailed and executive planning is not done in this area, land use change will occur severely. This change of uses causes the increase of soil erosion and production of sediment in the watershed, in other words, this change of uses can be considered as an alarm for the destruction of Anzali Wetland. In general, due to the conditions of the watershed and its high erosion upstream, the life of the Lasak dam will not be long, and its construction will reduce the water rights of the Anzali wetland and lead this international wetland to complete destruction at a faster rate.

Due to the population growth and the increase in global demand for food security, the correct use of water and soil resources, especially in arid and semi-arid regions, is necessary and inevitable. Providing water sources in agricultural and garden lands by clay irrigation method has been customary in arid and semi-arid regions of Iran for a long time. However, the development of this method has not received much attention due to the invasion of the roots into the clay nozzles and the clogging of the pores caused by the growth of algae, fungi, and bacteria. One of the main goals of this article is to provide a practical solution to combat root invasion towards the wall of clay subsurface irrigation nozzles (porous clay capsules). This research seeks to investigate the effect of copper oxide added to the porous clay capsule wall in inhibiting root invasion.

This research aims to reduce the density and distribution of roots in the vicinity of porous clay capsules, by investigating the effect of copper oxide on the wall of the clay nozzle as an inhibitor of root movement in the form of a completely randomized design with 4 treatments with zero concentrations (control). 1000ppm, 5000ppm and 10000ppm copper) in 3 replications in the research greenhouse of Tarbiat Modares University in 1401 on sweet pepper variety 302. In this experiment, the volume, length and dry weight of root, fresh weight of leaf and stem, dry weight of leaf and stem and ratio of dry weight of leaf/root were measured at the end of vegetative growth stage of the bell pepper plant.

The results showed that copper levels did not have a significant effect on the volume and length of the bell pepper plant's root, but it had a significant effect on the dry weight of the root. The highest root dry weight (3.27 grams) was obtained at the probability level of 5% corresponding to the level of 10000 ppm of copper sulfate. Also, the results of the investigation of the root distribution system showed that the distribution of the root distribution in the control treatment was the same in all directions, while in the 10000 ppm copper sulfate treatment, this distribution was severely limited around the wall of the clay nozzles, so that the most the root accumulation around the nozzles was related to the control treatment and the lowest root accumulation was visible in the 10000 ppm treatment. The results showed that the highest development of the root system around the nozzles was related to the control treatment and the lowest was observed in the 10000 ppm treatment in the control treatment, the porous clay capsule were heavily invaded by plant roots and the roots completely surrounded the porous clay capsules. Therefore, adding copper sulfate to the wall of the porous clay capsule and fixing it in its pores as copper oxide has had positive effects in inhibiting the invasion of plant roots into clay nozzles.

The purpose of this research is to model scenarios for the protection of underground water resources in South Khorasan province in drought conditions.

In this regard, this problem was followed using the system dynamics approach and the behavior of the reference variable "Volume of underground water resources of South Khorasan Province" was simulated against different scenarios during the years 2013 to 2014 through the use of Vensim software. The required information was collected by referring to relevant organizations such as South Khorasan Regional Water Organization, South Khorasan Agricultural Jihad Organization and Iran Statistics Center, and the input data of the model was called into the model in the form of an Excel file.

The results of the research showed that applying the control scenario of water resources exploitation in normal drought conditions and drought with low intensity is useful, but applying this scenario in drought conditions of more than 20% will have negative effects on the economic indicators of the agricultural sector. Also, the fourth scenario of the cultivation pattern (emphasis on strategic crops) along with the fifth scenario of the cultivation pattern (drought-resistant crops) have brought the least pressure on underground water resources. Nevertheless, considering that cultivation pattern No. 4 has created the least added value, it cannot be an efficient pattern.

According to the results of the research, if the severity of droughts increases in the coming years, but the current agricultural conditions of South Khorasan province continue in terms of cropping patterns, droughts will not have an effect on economic indicators, because in these conditions, farmers By breaking the ground and extracting more from underground water sources, they will compensate for the lack of rainfall and will show the negative effects of drought on the stock of underground water resources. Considering the effect of the cultivation pattern on underground water resources and economic indicators, it is necessary to think of measures to change the cultivation pattern.

In recent decade, biochar application as a soil amendment has received attention from many researchers around the world. With respect to report of different impacts of biochars on soil properties and crop type the use of biochar in soil as an amendment must be scientifically and practically studied in relation to the type of soil, type of biochar and type of plant to investigate and determine its positive or negative effects. The aim of this study was to investigate the effect of biochar derived from pistachio waste and date palm leaves on some physical properties and water repellency of soil.

For this purpose, two types of soil (i.e. sand and sandy loam) were combined with two types of biochar, date palm leaf biochar (DPLB) and pistachio harvesting waste biochar (PHWB), at 4 application levels (1, 2, 3, and 5% by weight), also the treatment without biochar application was considered as a control. These biochars were mixed with soil and after a two-month incubation period, then physical properties of soil such as bulk density, specific surface area, hygroscopic moisture, water repellency, and dispersible clay were measured and the obtained results were statistically analyzed.

The results showed that the application of biochars generally decreased the bulk density (BD) and increased the specific surface area (SSA) and hygroscopic moisture content (HMC) in the both soils. Although the application of DPLB caused decrease in dispersible clay (DC) of the soils but PHWB increased this parameter compared to the control. Application of 5% DPLB in both soils reduced DC by 60% but on the other hand, PHWB increased DC by 43% and 114% in sandy soil and sandy loam soil, respectively. In general, the low levels of biochar application (1% level) caused a significant decrease in the water repellency of sandy loam soil compared to the control, and increasing the levels of biochar application, resulted in an increase in soil hydrophobicity. The effect of DPLB application in sandy loam soil on water repellency was not significant, and the application of PHWB had a different effect on water repellency of sandy soil. Increasing levels of PHWB caused a significant decrease in water repellency of sandy soil, so that the application of 5% of PHWB reduced this index by 31% in this soil. It seems that PHWB has increased the SSA of sandy soil and on the other hand, the greater tendency of this biochar to absorb water on the surface (increased HWC), has increased the tendency of sandy soil to suck the water, so decreased the water repellency of this soil.

In general, the effects of the studied biochars on the physical properties of the both soils were positive, and the reduction of the BD and DC also the increasing of the SSA and HWC could be considered as an increasing in the soil quality, but this doesn't mean that the application of biochars can have positive effects on plant growth in the soil, because the aspects of the impact of these amendments on other soil properties (i.e. chemical properties) should also be considered. So, considering that the effect of biochar can be greatly influenced by the combination of biochar properties and soil conditions, effective use of biochar in agricultural soils requires prior evaluation of the biochar effect based on soil and plant conditions.

Groundwater is one of the main sources of sustainable development in human societies, and due to the supply of water needed by the drinking, agriculture, and industry sectors, their pollution will have destructive effects. In addition, the fuel transmission network is of great importance due to the storage and transportation of petroleum products. The importance of this system increases in various aspects during events such as earthquakes. Pollution of underground water sources due to leakage from the fuel transmission system is one of the secondary effects of the earthquake and leaves an adverse effect on the environment and human health. This research is focused on evaluating the vulnerability of groundwater due to the failure of the urban fuel transmission network against the occurrence of an earthquake, which was conducted in the form of case studies on the fuel transmission network of Tehran city and the Tehran-Karaj plain aquifer.

In this research, a unified model for seismic damage analysis and risk assessment under conditions of uncertainty in the fuel transmission network of Tehran city has been defined and implemented. In this model, the consequences of damage to the fuel transmission network under three earthquake scenarios (magnitude 5, 6, 7 on the Richter scale) have been evaluated on the pollution of underground water in Tehran. In addition, strategic strategies have been presented in order to reduce the effects of groundwater pollution caused by earthquakes. The proposed model uses a multi-layer perception artificial neural network (ANN). Also, the DRASTIC model has been used to evaluate groundwater pollution based on fuel leakage from the damaged fuel transmission network. In these studies, strategic planning has been done based on the use of robust decision-making techniques and the degree of robustness in order to reduce the probable effects of groundwater pollution by using the theory of minimum-maximum regret.

Results:

 The results of this research showed that the developed artificial neural network model has a high ability to assess damage(failure-leakage) in the pipeline of the fuel transmission network so that the root-mean-square error (RMSE) and the correlation coefficient R are equal to 0.029 and 0.98 respectively. Based on the results, the amount of damage to the pipeline in the first scenario (Mw=5) is equal to 15 leaks and 2 failures, in the second scenario (Mw=6), it is equal to 25 leaks and 7 failures and in the third scenario (Mw=7) the number of leaks was 27 and 9 failures. According to the results obtained from aquifer pollution under three earthquake scenarios, it is clear that in the scenario of an earthquake with Mw=5, 30% of the aquifer has medium pollution potential and 55% of the potential of low pollution, in the scenario of an earthquake with Mw=6, 45% The aquifer has medium pollution potential and 18% has low pollution potential, and in the earthquake scenario with Mw=7, 55% of the aquifer has medium pollution potential and 22% has low pollution potential. In line with the strategic planning of aquifer pollution reduction, different strategies were evaluated against different scenarios with the minimum-maximum regret criterion. Finally, three strategies were presented to reduce the pollution of underground water resources. According to the results, the use of the strategy (insulation of the environment around the pipeline) led to a 70% reduction in groundwater pollution, and the use of the strategy (implementation of an intelligent seismic system to cut off the fluid flow in the event of an earthquake), which was known as a robust strategy, led to aquifer pollution has been reduced by 75%.

Based on obtained results from the performance evaluation of the model developed in this research, it was found that the presented model had an acceptable performance in predicting the seismic vulnerability of the fuel transmission pipeline and assessing the pollution of the aquifer. This model has the ability to be implemented in different urban areas and to evaluate the performance of the fuel transmission system under different earthquake scenarios, as well as to evaluate groundwater pollution. Also, based on the results of the strategic management of groundwater pollution control, implementing an intelligent seismic system to cut off the fluid flow in the event of an earthquake can be used as a comprehensive solution to reduce environmental damage to groundwater resources specifically in the seismic regions.

Using the values analyzed by the wavelet function can increase the accuracy of the simulations. Considering the climatic changes and the increase of extreme values in recent years, in this study, we made an effort that the effect of signal processing under the name of wavelet transformation in improving the performance of random forest model in simulating monthly river flow in Siminehrood and Mahabadchai sub-basins in the south of Lake Urmia has been discussed and investigated in the period of 1971-2019.

In this study, the accuracy of the random forest model has been investigated in two steps of training and testing. At first, the random forest model was evaluated in two phases of training and testing in rainfall-runoff simulation in the south of Lake Urmia basin. Nash-Sutcliffe statistics and root mean square error were used to evaluate the performance and error rate of the studied models, respectively. In the next step, after investigating the performance of the random forest model, the time series of rainfall and river flow in the studied basins were analyzed using the wavelet function. In this regard, two analysis levels (level 1 and 2) and two Haar and Daubechies wavelet functions were used. Finally, using the random forest model, rainfall-runoff simulation based on the wavelet theory was done under the name of W-RF model.

Results and Dissection: 

At First, the random forest model was investigated in two phases of training and testing, and the simulation results of the river flow values showed that the simulated values were within the 95% confidence interval, and the error rate of the river flow simulation using the RMSE statistic is 3.22 and 8.91 cubic meters per second in the test phase for Mahabadchai and Siminehrood sub-basins, respectively. In order to investigate the effect of time series analysis on the performance of the RF model, wavelet theory and Haar and Daubechies 4 wavelet functions were used in decomposition levels 1 and 2. By estimating the accuracy and performance of the hybrid W-RF model in 4 input patterns, the best pattern was selected based on the RMSE and NSE model evaluation criteria. The research results showed that for the Haar wavelet function in level 1 decomposition has better performance and error rate than level 2 type in both sub-basins. In this study, the Daubechies wavelet at level 1 in the test phase has provided the best performance and the lowest error rate in the simulation of the river flow values in the studied sub-basins and has been able to reduce the error rate in the two sub-basins of Mahabadchai and Siminehrood respectively by about 89 and 80 percent compared to the random forest model.

Finally, by comparing the RF and W-RF models, the simulation results of river flow in the two studied sub-basins showed that the integrated W-RF model was able to reduce the error rate in the two sub-basins of Mahabadchai and Siminehrood to reduce by 89 and 80% respectively. Considering the increase in simulation complexity with the involvement of wavelet theory, the error recovery rate and model performance are acceptable. The integrated W-RF model in this study provides reliable results for the simulation of river flow data in order to support decision-making and risk analysis in the exploitation of downstream reservoirs and the management of water resources in sub-basins. The obtained results can be used in the design of water resources systems.

Grass is one of the most important cover plants in most green spaces, and considering that Iran is considered one of the dry and semi-arid regions of the world, water and soil salinity affects the growth of plants, as a result, using salt-resistant grass is one of the solutions to create green space in these areas. Therefore, the purpose of this research is to investigate the salinity tolerance of sport turfgrass caused by sodium chloride and potassium chloride salts.

In April, sports grass seeds were planted in an area located in Karaj province in the form of a r randomized complete block design with three replications in plots of 2 m2 (1 x 2 m2) and were cultivated with a density of 40 g m-2. The experimental treatments included sodium chloride and potassium chloride salts with concentrations of zero, 25, 50 and 75 mg l-1. After about 5 weeks of planting the seeds, salt stress was applied for one month through irrigation with salts twice a week and each time with 12 liter of salt solution and then sampling was done to evaluate fresh and dry weight of shoots and roots, total chlorophyll, proline, protein and activity of superoxide dismutase and peroxidase enzymes.

Data analysis showed that the treatments had a significant effect on the assessed traits. The highest fresh and dry weight of shoots (3.85-4.87 g) and roots (1.46-23.2 g) and total chlorophyll (16.96 mg g-1) were observed in the control, while the highest protein (3.73 μg mg-1) and activity of superoxide dismutase (4.62 enzyme units g-1) and peroxidase (4.12 enzyme units g-1) in 75 mg l-1 sodium chloride treatment and the highest proline content (12/ 8 mg g-1) was observed in 75 mg l-1 potassium chloride treatment, also the lowest fresh and dry weight of aerial parts (2.12-3.08 g) and total chlorophyll (12.53 mg g-1) in 75 mg l-1 potassium chloride treatment and the lowest fresh and dry weight of roots (0.59-0.96 g) were obtained in 75 mg l-1 sodium chloride treatment, and the lowest content of proline (4.48 mg g-1), protein (2.48 μg mg-1) and the activities of superoxide dismutase (3.00 enzyme units g-1) and peroxidase (2.93 enzyme units g-1) were in the control.

According to the obtained results, sport turfgrass was able to tolerate stress conditions in 25 and 50 mg l-1 salt stress to some extent by increasing compounds such as proline, protein and antioxidant enzyme activity, but increasing the concentration of salts used, especially potassium chloride salt (75 mg l-1) had the greatest effect in reducing the vegetative traits and increasing the enzyme activity of sport turfgrass.

Rainfall is one of the complex natural phenomena and one of the most crucial component of the water cycle, playing a significant role in assessing the climatic characteristics of each region. Understanding the amount and trends of rainfall changes is essential for effective management and more precise planning in agricultural, economic, and social sectors, as well as for studies related to runoff, droughts, groundwater status, and floods. Additionally, rainfall prediction in urban areas has a significant impact on traffic control, sewage flow, and construction activities.

The objective of this study is to compare the accuracy of classification models, including Chi-squared Automatic Interaction Detector (CHAID), C5 decision tree, Naive Bayes (NB), Quest tree, and Random Forest, k-Nearest Neighbors (KNN), Support Vector Machine (SVM), and Artificial Neural Network (ANN) in predicting rainfall occurrence using 50 years of data from the synoptic station at Hamedan Airport. In this study, 80% of the data is used for training the models, and 20% for model validation and the results obtained from the model executions are compared using metrics such as confusion matrix, Receiver Operating Characteristic (ROC) curve, and the Area Under the Curve (AUC) index. To create the classification variable for rainfall and non-rainfall data, based on rainfall data, the days of the year are categorized into two classes: days with rainfall (y) and days without rainfall (n). Data preprocessing is performed using Automatic Data Preprocessing (ADP). Then, Principal Component Analysis (PCA) is employed to reduce the dimensions of the variables.

In this study, the PCA method reduces the dimensions of the variables to 5. Also, approximately 80% of the available data corresponds to rainless days, while 20% corresponds to rainy days. The research results indicated that the KNN model with an accuracy of 91.9% for training data and the SVM model with 89.13% for test data exhibit the best performance among the data mining models. The AUC index for the KNN model is 0.967 for training data and 0.935 for test data, while for the SVM algorithm, it is 0.967 for training data and 0.935 for test data. According to the ROC curve for Hamedan rainfall data, the KNN model outperforms other models. Considering the sensitivity index in the confusion matrix, the KNN and SVM models perform better in predicting non-rainfall occurrence for training data. In terms of the precipitation occurrence prediction, the RT and KNN models show better results according to the specificity index.

The results demonstrated that for the RT, C5, ANN, SVM, BN, KNN, CHAID, QUEST, accuracy metrics was obtained 86.82%, 89.78%, 89.55%, 89.96%, 88.06%, 91.9%, 88.29%, 87.46%, 91.9%, respectively for training data. Moreover, for test data, the accuracy metrics for this model was obtained 83.82%, 87.9%, 88.12%, 89.13%, 87.12%, 89.13%, 87.12%, 88.19%, 86.93%, 86.76%, respectively. The AUC index in the training data for RT, C5, ANN, SVM, BN, KNN, CHAID QUEST models was 0.94%, 0.99%, 0.94%, 0.94%, 0.93%, 0.97%, 0.93%, 0.89%, respectively. In addition, for the test data, this metric was evaluated 0.89%, 0.89%, 0.93%, 0.94%, 0.92%, 0.90%, 0.92%, 0.88% respectively. As observed, considering accuracy metric and AUC index for training data KNN model and for test data SVM model were more sufficient in rainfall prediction.

In this study, the flood zoning in the Karun River in the area between Zaras Castle and Jafarabad has been determined. For this purpose, using the topographic map and satellite images, the exact course of the river was determined and the initial processing was done on its information. Then flood zoning was obtained with return periods of 500 years, 200 years, 100 years, 50 years, 25 years, 10 years, 2 years.

In this research, flood zoning of Karun river, which is one of the main and permanent rivers of Khuzestan province. was investigated in the area from Zaras Castle to Jafar Abad. The aim of the current research is to zonate the risk of flooding occurrence and identify the villages at risk of flooding, through the preparation of the river boundary map for the return period of 500 years, 200 years, 100 years, 50 years, 25 years, 10 years, 2 years in the Karun river using the Hec-RAS model in the ARC-GIS environment. In this research, the discharges of this river are based on the probability of its occurrence using Johnson sb statistical distribution was calculated.

In this research, in addition to calculating flood depth and flow velocity parameters, factors such as shear stress and flow strength for different return periods were calculated and investigate. Shear stress and flow strength are effective parameters in the flood risk, so it is important to investigate them.

In this research, flood inundation risk zoning was done and the villages at risk of flooding were identified by preparing a map of the River boundary for the return period of 500 years, 200 years, 100 years, 50 years, 25 years, 10 years, 2 years, and Discharges of this river were calculated based on the probability of its occurrence using the statistical distribution of Johnson sb. Among the 10 villages located along the Karun river, Jafarabad villages, Hasht Lak Kanaar, Zaras Qala, Lali New Road bridge are the most vulnerable areas, which regardless of the rules of construction and non-observance of the river boundary are built in its main bed. Factors such as the change of land use and the transformation of floodplains into agricultural and garden lands, disregarding the river boundary and encroaching on the floodplain of the river have increased the potential of flood risk and as a result the villages are more vulnerable, especially in the flood zone with a return period of 500 years.