نشریه پژوهش های آبخیزداری
پیاپی 139 (تابستان 1402)

Introduction and Objective:

Soil is a part of every ecosystem and one of the most valuable and important sources of food production in every country, which plays a significant role in the continuation of human life. Today, soil erosion is one of the most important threats to water and soil resources and has become one of the most important human environmental problems. Soil supports food security and environmental quality, both of which are essential for human life. The purpose of this research was to evaluate the performance of watershed management measures in the treated sub-watershed of Khamsan representative watershed. The lake of Gavshan Reservoir has receded at the maximum level to the outlet of the Khamsan watershed. This has caused soil erosion from this watershed to enter the Gavshan dam lake directly and with the shortest distance. Therefore, it is very important to evaluate the performance of the measures taken in this watershed, especially based on the distribution map of erosion and sedimentation.

Materials and Methods:

The first step of measuring soil erosion using cesium-137 is to select a control or reference area. Slope and land use maps were used to determine the final sampling points in this research. After measuring the activity of cesium-137 (becquerels per kilogram of soil), the presence of cesium-137 per square meter of soil sample is needed to calculate soil erosion. The activity of cesium-137 in reference points was compared with the activity of cesium-137 remaining in the research points. If the cesium-137 activity of the soil samples was lower than the activity in the reference profile, soil loss and erosion occurred. The increase in the activity of cesium-137 in the soil samples compared to the reference profile was indicative of soil transfer to the sampling point and considered as a sedimentation site.

Results  and Discussion:

The results of the comparison of the same points in the rangelands in both treated and control sub-watersheds showed that sedimentation conditions prevail over erosion. The amount of sedimentation in the rangelands with watershed management measures (contour trenching, seeding and exclosure) in the treated sub-watershed with a slope of 20-30% was more than the rangeland with the same characteristics in the control sub-watershed. In rangeland with watershed management measures, erosion conditions prevailed in the slope of more than 30-60%, but erosion in protected conditions was less compared to the same point in the control sub-watershed.

Conclusion and Suggestions:

The results of the amount of erosion and sedimentation in both treated and control sub-watersheds in rangeland with a slope of 20-30% showed that sedimentation conditions prevail. However, the amount of sediment deposition in the rangeland with watershed management measures in the treated sub-watershed showed an increase of 1445.65% compared to the rangeland without protective measures in the control sub-watershed, which indicates the positive effect of watershed management measures in the treated sub-watershed rangelands with a slope of 20-30%. This finding shows the special effect of contour trenching on increasing sediment trapping, reducing the volume and speed of runoff, and thus reducing the power of sediment transfer. Also, in the slope of 30-60%, although erosion conditions prevailed in both treated and control sub-watersheds, watershed management measures in rangeland in the treated sub-watershed showed a 28.57% reduction in soil erosion compared to the same point in the control sub-watershed. Considering the positive performance of watershed management measures, especially contour trenching, it is suggested to use these measures in other watersheds similar to Khamsan representative watershed.

The use of simulations combined with the drought index enhances forecast accuracy. The exploratory approach provides the scope for drought warning and the opportunity for financial support and insurance mechanisms for local communities. The most important part related to the reduction of the effects of drought is the improvement of the precision of forecasting systems.

In this research, the precision of the new Anfis Simulation combined with the meta-heuristics of ant colonies in drought prediction is compared to the normal ANFIS Simulation. Simulation performance is estimated using the Mean Squared Error, Mean Absolute Error and Coefficient of Determination.

Validation of the simulation in the three month profile shows that the Absolute Error Value and the Root Mean Square Error in the Zabol Station are lower by Anfis Simulation. This article examines the Compatible Adaptive Neuro Fuzzy Inference System (ANFIS) and ANFIS models with Ant Colony Optimization Algorithm (ANFIS-ACOR) for drought forecasting. Drought forecasting was done using monthly precipitation data from synoptic stations Zabol (1983-2020) and Zahak (1994-2020). The results showed (ANFIS-ACOR) improved the performance of the Adaptive Neuro Fuzzy Inference System. The model predictive correlation test (ANFIS-ACOR) values in the 3, 6, 9 and 12-month intervals are equal to 0.738, 0.854, 0.801 and 0.898 at the Zabol Station. As well 0.792, 0.804, 0.759 and 0.887 at Zahak Station, respectively. In addition, Anfis Simulation-ant colony has a higher coefficient of determination. Validation of the simulation related to the three-month profile of Anfis-ant Colony Simulation showed that the absolute error and the Root Mean Square Error are lower and the coefficient of determination is higher. In the Zahak Station, the Anfis Simulation is more accurate in the 3-month formation, but in the validation section, the Anfis-ant Colony Simulation is superior. Overall, in the three-month SPI profile, Aanfis Simulation training is more accurate, but Anfis Colony Simulation is superior in validation.

Conclusion and Suggestions :

Ant colony optimization as a function of the data population progressively brings the proposed solutions closer to the overall optimal solution. This problem increased the efficiency of the numerical calculation of the ant colony compared with the Anfis in predicting drought. Anfis Simulation in combination with ant colony provides efficiency for large-scale problems in a short time by auto-tuning. These features reduce the cost of calculating natural data with irregular geometric pattern or data recorded in high volume. Simulations which optimize will fail at the local optimum level. Anfis-Ant Colony Simulation evaluates simulation space for predicting droughts on a global scale. This research proposes to compare the Anfis Simulation with other numerical calculations and to choose the best simulation for the Zabol Watershed.

Droughts have a set of negative environmental, social and economic effects in a region or country. Using a monthly index and its analysis that, in addition to precipitation values, takes into account the effect of evaporation on the numerical value of the index, is very useful in determining drought parameters. Different indices are also a combination of variables with different marginal distributions, and for this purpose, their statistical analysis is difficult. Therefore, in order to determine the structure of dependence between two or more random variables, copula functions can be used, the distribution of margins is separated from the modeling of the structure of dependence between variables.

In this study, RDI index was used to determine the severity and duration of drought in 6 stations of North Khorasan province between 1988-2018 and Copula functions were used to analyze the severiy and duration. 26 different Copula functions were investigated using different statistical values. Also, two methods of local optimization and Monte Carlo Markov chain simulation with Bayesian estimator were used to numerically estimate the posterior distribution of selected Copula parameters. In order to evaluate the fit of different copulas, the common criteria were used for measuring the fit of different copulas including mean squared error, Bayesian information criterion, Akaike information and Nash-Sutcliffe efficiency criterion.

In all stations, the values of correlation coefficient with Pearson and Kendall tests were positive and had the same trend. The results of the Kolmogorov-Smirnov test at a significance level of five percent for choosing the optimal distribution showed that the generalized Pareto distribution was selected for the intensity and duration of Bojnord station and the exponential distribution for other stations was selected as the appropriate fitted distribution. The optimal function for Bojnord, Maneh and Semelghan stations was Burr function, Jajarm and Shirvan stations, Joe function, Farouj station, Galambos function and Esfarayen station, BB1 function. The results of the local optimization method are highly consistent with the Markov chain Monte-Carlo method. For the 100-year return period, the drought severity at bojnord station is 6.8, at esfarayen station, drought severity is 7.8, at faruj station, drought severity is 7.5, at jajarm station, drought severity is 7.8, at the station in manesemelghan, the drought severity was 8 and in shirvan station, the drought intensity was 2.8.

Conclusion and Suggestions :

The current study shows the high capability of copula functions in solving two-variable problems and recommends the use of all possible functions in choosing marginal distributions and copula in solving problems. Also, the high correspondence between the two methods of local optimization and Markov chain Monte Carlo for estimating the parameters of the functions is probably due to the short statistical period used. Investigating the capabilities of these functions in solving multivariate problems, implementing other Monte Carlo Markov chain estimators, and using longer data to compare different optimization algorithms are suggested in future researches.

Nowadays, it is necessary to use new methods to resolve the issue of soil erosion instead of traditional methods in order to achieve more accurate knowledge and appropriate planning. The cheapest and most appropriate way to conserve the soil is to use vegetation. Therefore, considering the high costs and adverse environmental effects of mechanical methods compared to biological methods of soil conservation, the present study aims to investigate the effect of planting two varieties of fodder vetch as a biological, economic and environmentally friendly solution to reduce runoff, sediment and improve soil properties.

This research was carried out using standard experimental plots with dimensions of 22 × 1.8 meters and a slope of 9%, so that totally nine experimental plots including three treatments and three replications were applied and executed in the form of a randomized complete block design. The three treatments studied in this experiment included Maragheh vetch, Golshan vetch and native wheat of the study region (control treatment), and the studied vetch varieties were planted simultaneously with wheat cultivation in the fall in two consecutive years, 2020 and 2021. Finally, the mean data of runoff, sedimentation and stability of soil aggregates were compared and statistically analyzed.

In general, the studied fodder plants had a significant effect on reducing the runoff and sediment generated from the experimental plots, which shows the importance and role of these plants for the purposes of soil and water conservation. In particular, Maragheh fodder vetch showed excellent performance in reducing runoff and sediment in the study area, therefore planting the mentioned varieties in order to conserve soil and water is prioritized in the study area. The stability of soil aggregates also did not show any significant difference in the studied treatments during the experimental period. Therefore, it can be concluded that the stability of soil aggregates will not change within two years, and more time is needed to observe the change in this soil characteristic.

Conclusion and Suggestions :

The results of this research revealed the significant effect of using forage plants, especially Maragheh and Golshan forage plants, on reducing runoff and sediment in line with the goals of soil and water protection. The use of fodder legumes compatible with the climatic conditions of each region that have suitable plant characteristics such as a strong and dense root and stem system as well as a suitable canopy in order to conserve soil and water and improving the livelihood of the residents of the region and also carrying out early irrigation and supplementary irrigation is recommended in the important stages of the plant growth under drought and low rainfall conditions. Also, conducting researches that investigate the effect of rainfall intensity, amount of rainfall, soil moisture, soil texture and chemical properties of soil on the effectiveness of dry fodder plants in water and soil conservation, as well as the relationship between different climatic, morphological and hydrological conditions of upstream and the effectiveness of dry land fodder plants in the qualitative and quantitative control of runoff, is suggested.

Resilience and vulnerability of Society plays an important role in facing natural hazards. Due to the dependence of the rural economy on agricultural activities, the impact radius of the drought phenomenon is higher in rural areas. The purpose of this research was to assess the resilience and vulnerability of rural households in Kavar city located in Fars province, against the effects of drought with the capital analysis approach including economic, social, environmental, human, physical and political capital.

In order to conduct this research, samples were collected in 44 villages of Kavar city that were directly affected by drought. The statistical population includes 198 people from the local elite, including villagers, the Islamic Council and local trustees. Using Cochran's method, 131 people were selected as a statistical sample. The tools used were questionnaires and interviews. The variables used in this research included 62 samples which were divided into six groups of social, economic, environmental, physical, human and political capital. The validity of the questionnaire was confirmed by a group of experts in natural resources and sociology. The reliability of the research questions was also obtained using Cronbach's alpha. In order to prioritize capitals in terms of importance in the process of resilience and vulnerability of rural settlements against drought, the data obtained from the questionnaires were weighted and prioritized using the AHP method.

According to the research results in the case study, the highest vulnerability and resilience were related to human capital and environmental capital, respectively. Also, the least vulnerability and resilience are related to economic capital and political capital, respectively. The vulnerability of all investigated funds was more than the statistical median of the sample, which shows that the target society has high vulnerability. The capacity of resilience in economic, physical and political capitals was lower than the statistical median of the sample and for social, environmental and human capitals it was more than the statistical median of the sample. The average of the total funds in the region shows that vulnerability is high and resilience is low in this region.

Conclusion and Suggestions :

The results of capital prioritization in terms of importance in the process of resilience and vulnerability of rural settlements against drought using the AHP method showed that environmental, social, human, physical, economic and political capitals in resilience and human, Political, environmental, physical, social and economic capital’s, have the highest to lowest priority in vulnerability. In addition, the results showed that the level of community preparedness is at a low level when drought occurs. The vulnerability index was 3.74 and the resilience index was 2.81, which show that vulnerability is high and resilience is low in this area. It is suggested that the prevailing approach be changed from a weak focus on reducing vulnerability to drought crisis to increasing resilience against this crisis. In this connection, planning should be done in order to strengthen resilience characteristics in societies exposed to drought crisis.

Introduction and goal:

The phenomenon of flood is one of the frequent hazards that have caused financial losses and many lives in Iran in the last decade. One of the three main natural hazards of Iran is the occurrence of floods, and it is safe to say that a large flood occurs at least once a year in some part of this country. Floods are considered as a great threat to human life by damaging or killing people and animals, especially buildings and houses, agricultural land and crop production, urban infrastructure, bridges and roads. Floods in Iran cause a lot of damage from an economic point of view; it causes destruction of the environment, natural and residential resources and loss of life. In the past years, about 70% of the annual credits of the plan to reduce the effects of natural disasters and the headquarters of unexpected events have been used to compensate for the damages caused by floods. In this research, by using flood location data and using machine learning models and random forest data mining and the weight of evidence and their combination, the spatial prediction of flood prone areas has been discussed.

In this research, combined models and 11 predicting variables of flood probability in Karkheh watershed located in Lorestan province have been used. These variables include maps of geomorphometric indicators, including topographic humidity index, relative slope position and topographic position index, hydrological maps including: drainage density and distance from the drainage network, for this purpose, first, data mining models for the initial analysis of the relationships between environmental variables and events Past risks are used and their results are used as input data for machine learning models. Flood data were randomly divided into two groups: training (70%) and validation (30%). Prediction accuracy was evaluated using operating characteristic curve (ROC) method.

According to the results of the random forest model, the accuracy was 0.904, the weight of evidence was 0.886, and the combined model of random forest - the weight of evidence was 0.978. Based on the combined model of random forest and the weight of evidence as the superior model, 20.49% of the surface has medium upward potential. Based on the random forest model, drainage density, distance from waterways, height and land use were the most important factors affecting flood potential.

Urban watersheds have become important due to the problems related to water resources management, including floods and pollution control. Therefore, the approach of engineers in recent years is toward computer software for estimating and simulating runoff. So far, many rainfall-runoff software with different capabilities and complexity have been developed and used for flood forecasting. The approach of the current research is to simulate the surface runoff and to identify the flood and critical nodes under the influence of climate change and to determine the efficiency of the surface drainage network in the west of six districts of Tehran municipality.

This research includes two parts of hydrology and water flow. In the hydrological department, after calculating the concentration time, in order to extract the rainfall intensity of the plan and to analyze the maximum rainfall for different durations of the base period (1980-2020), the near future period (2021-2050) and the far future (2051-2100) and preparing the IDF curve at different times and durations, based on the RCP2.6 and RCP8.5 scenarios, the Abkhezer-Qahraman method was used. In the water flow section, the assessment of the drainage network and flood control nodes in the western part of the six municipalities of Tehran in the base period (1980-2020) and under the influence of climate change (2021-2050), (2051-2100) in the RCP 2.6 and RCP8.5 scenarios for the period 25 and 50 year returns were made.

The results showed that the values ​​of rainfall intensity in the duration of rainfall and different return periods in all three scenarios have increased compared to the frequency intensity curve of the base period, and the maximum rainfall intensity has increased in the short-term time base, and with the passage of time, the maximum rainfall intensity has decreased. and IDF curves are affected by short-term rainfall. The results of the model calibration showed that there is a good agreement between the observed and simulated data in the simulation of water runoff in the five investigated rainfall events. The results of the sensitivity analysis showed that the impervious areas have the greatest impact on the change of peak water discharge. The results of the evaluation of flood nodes showed that, for example, the number of flood nodes in the base period (1980-2020) and under the influence of climate change in the RCP2.6 and RCP8.5 scenarios (2021-2050) for the 25-year return period are 7, 10, and 12, respectively. The number of flood nodes in the base period (1980-2020) and under the influence of climate change scenario RCP2.6 and RCP8.5 (2051-2100) for the return period of 50 years are 9, 14 and 17, respectively.

Conclusion and Suggestions :

The results of this research showed that the number of flood catchment nodes in the basin increased in the 25-year return period compared to the 50-year return period in each period. According to the identification of critical nodes in the research area, by applying modern methods of urban runoff control, such as creating permeable surfaces and gardens, absorption wells and reservoirs and storage ponds, the runoff can be controlled at the source to reduce the volume and peak water in the downstream, so that the probability of occurrence Minimize flooding and flooding. Since the percentage of impervious areas in the study area is high, it is recommended to increase the dimensions of the channels in terms of the passage of flood during rains and to have the ability to direct more amount of runoff and reduce the amount of peak flow of runoff in the location of super critical nodes.

Due to droughts occurred in recent years, available water resources in southern basins and watersheds of Iran especially those are in Hormozgan Province has been drastically decreased which may not only change their ecosystem but also make serious problem for the country’s food security.  In addition to find new water resources, effective use of available water is the best choice to tackle water deficit which in turn, requires accurate estimation of evapotranspiration or water needs of plants. Crop evapotranspiration is usually calculated using the two-step FAO method. In this method, first the reference crop evapotranspiration (ET0), representing effect of weather on crop evapotranspiration is estimated by models using weather variables and then, multiplied by crop coefficient (Kc) which reflects crop characteristics on evapotranspiration. A review on the research conducted around the world revealed that each model may have different accuracies and performances at different watersheds or locations. Subsequently, using these models without testing their accuracy and relevance at each watershed may increase error in estimating (ET0) and hence crop water requirements which may complicate any planning for the watershed in the future. Therefore, this research was conducted to evaluate the accuracy and performance of the FAO proposed models at Haji Abad watershed of Hormozgan Province.

In this research which was conducted in Haji Abad watershed of Hormozgan for four years, reference crop(grass) evapotranspiration was measured weekly using a drainable lysimeter. In the first year, a large square drainable lysimeter (3 m wide ×3 m long × 1.9 m tall) was installed in the center of a 2-ha agricultural field which was representative of the watershed. In the next third years, grass (Cynodon dactylon L.) was grown inside the lysimeter and in the 900 m2 surrounding field. At full cover and when grass height reached 8 cm, evapotranspiration from grass inside the lysimeter was measured weekly by the water balance method. Reference crop evapotranspiration was also estimated using the FAO models: Adjusted penman and Blaney- Criddle, Radiation, Evaporation pan and Penman-Monteith. The estimated (ET0) values from the FAO models were compared with the data measured from lysimeter using linear regression, root mean square error and error percentage in estimating seasonal (ET0) and subsequently, the most appropriate models were recommended for the watershed.

Seasonal grass evapotranspiration measured from the lysimeter was 2729.8 mm and estimated by Adjusted penman and Blaney- Criddle, Penman-Monteith, Radiation and Evaporation pan 3405, 2695.2, 2868, 2789.2 and 2054.6 mm, respectively. The FAO adjusted Penman, Penman-Monteith and Radiation models overestimated ETo by as much as 24.7, 5.1 and 2.2% respectively, whereas, the FAO evaporation pan and Blaney- Criddle underestimated it by as much as 24.7 and 1.3%, respectively. Comparing weekly (ET0) data showed that adjusted penman model overestimated (ET0) but the FAO evaporation pan model underestimated it for most of the periods. FAO radiation model had tendency to overestimate at ETo<7 mmday-1 (normally in Fall and Winter) but underestimate at (ET0)>10 mmday-1 (normally in Summer).

Conclusion and Suggestions :

According to the results, the FAO Blaney-Criddle and Penman-Monteith models had respectively higher accordance and homogeneity with the real data measured from lysimeter and can predict (ET0) with higher accuracy than the other tested models. Therefore, these models are recommended, respectively as the most appropriate models to estimate (ET0) in Haji Abad Watershed and the areas having the same climate. Furthermore, the FAO Blaney-Criddle model needs fewer weather parameters and hence, may be used in the areas with limited climatic data.