نشریه پژوهش های آبخیزداری
پیاپی 141 (زمستان 1402)

The participation of villagers in watershed management activities has been paid attention to by the country's planners. Surveys have shown that the amount of people's participation was not as expected. This research is aimed at identifying the socio-economic characteristics of local communities, identifying indicators that are effective in reducing barriers and increasing public participation in the implementation of natural resources and watershed projects, understanding the expectations and needs of the local community, and finally providing scientific and technical solutions with the aim Increasing the amount of public participation was done in Asman Abad area of Cherdavel city.

In this research, the indicators influencing the non-participation of villagers in watershed management activities were determined and categorized based on four economic, social, design-executive and educational-promotional indicators and with 12 sub-indices. The necessary information in this research was collected in the form of a survey and using questionnaires, interviews and numerous meetings with community members and local experts. To determine the sample size from Cochran's correlation, SPSS software was used for data analysis and Cronbach's alpha was used to check the validity of the questionnaire.

The results obtained from this research showed that in the Asman-Abad watershed, economic, design and implementation indicators played a greater role in people's non-participation than educational-promotional and social indicators. From the perspective of experts, the sub-index of ignoring people's income as a direct economic incentive and not paying attention to non-governmental organizations were the most and least important in people's non-participation, respectively, with an average rating of 9.35 and 3.69. From the point of view of the local communities, the sub-indices of ignoring the people's income as a direct economic incentive and not trusting the results and effectiveness of the projects are the most and the least important, respectively, with an average rating of 8.16 and 5.23 in the non-participation of the people. they had. The general result of the survey of local communities indicated that the factors of implementing multi-purpose projects and considering the interests of watershed residents can be the basis for trust and attracting active participation of people in watershed management projects.

Conclusion and Suggestions:

In Asman Abad watershed, the prioritization of indicators affecting people's non-participation in watershed projects showed that economic and design-executive indicators played a greater role compared to educational-promotional and social indicators. Also, the results of the weights obtained from the Friedman test for ranking the sub-indices affecting people's non-participation showed that two sub-indices - ignoring the people's income as a direct economic incentive and not paying attention to the opinions and suggestions of the watershed residents in the different stages of needs assessment, design and the implementation of watershed projects, from the point of view of both groups, were in the first four priorities and were relatively more important in the non-participation of rural communities. Therefore, according to the findings of the research in order to create or improve people's participation in watershed management projects in the studied area, it is suggested that before the implementation of natural resources and watershed management projects, in relation to the existing problems, the conditions of the region and even the necessity of implementing the project Collect the points of view of the local community. Attracting the opinion of the residents of the watershed with the aim of cooperation in the implementation, protection, restoration and maintenance of projects, balanced and equal use of natural resources by the beneficiaries, appropriate use of the economic, social and technical abilities and capacities of the residents and the local community in creating and strengthening the participation of the local community is very effective Is.

Evapotranspiration govern the water and energy balance of the soil, primarily used in general circulation models and hydrological modeling of weather conditions. Consequently, predicting river flow, forecasting crop performance, water management systems, and the quality of rivers or lakes all depend on evapotranspiration levels. Therefore, accurate estimation of water bilan is essential. Improved and precise estimations of evapotranspiration enable effective irrigation planning and optimal water usage for other agricultural purposes. The goal of this research is to evaluate and validate the surface energy balance model, SEBS, in determining evaporation-transpiration in the Sohrin-Qareh Chiran Plain, located 30 kilometers northwest of Zanjan city.

In this study, the actual evapotranspiration were determined using the SEBS energy balance model and Landsat imagery in the Sohrin-Qareh Chiran Plain. A total of 17 Landsat-8 images, along with weather data from the Zanjan airport station, were examined. Additionally, with the help of the SEBS model, the evapotranspiration of a five-hectare wheat field was calculated and validated for the time period from September 22, 2020, to September 22, 2021. The required inputs for the SEBS model, including albedo, land surface temperature, emissivity, NDVI, vegetation cover index, leaf area index, vegetation height, and canopy density, were prepared in the ENVI software environment. The data on precipitation and water consumption volume were also determined using the soil water balance model.

The study found that the evapotranspiration estimated by the soil water balance model was 24115 m3, while the evapotranspiration estimated by the SEBS model was 28750 m3, with a 16.12% error. Additionally, the SEBS model was calibrated using four indices - R2, RMSE, MAE, and MBE - with values of 0.844, 1.06, 1.12, and 0.25, respectively. These results indicate that the SEBS algorithm is accurate enough to estimate ETa in the study area.

Conclusion and Suggestions:

Therefore, based on the results of this research, it can be said that the use of satellite images in estimating actual evapotranspiration (ET) is reliable compared to field measurement methods. Considering the limitations of traditional moisture balance methods (such as being point-specific, time-consuming, costly, requiring precise instruments, and almost impractical with the use of lysimeters) and the advantages of utilizing satellite images (covering a wide area of farms or orchards, being cost-effective and fast), acceptable results can be achieved in estimating evapotranspiration while accepting a low margin of error.

The history of flood spreading in the lands adjacent the rivers and flood irrigation reaches several thousand years. There are evidences of the use of floods to increase plant production in different parts of Iran, including the cities of Qazvin, Baluchistan, Khorasan, Fars, Isfahan and Khuzestan. Surveys conducted in 20 arid and semi-arid regions of the country indicate that in most regions, production indices and the percentage of plant canopy cover have increased significantly in the field of flood spreading compared to the control. The purpose of this research is to investigate the effect of flood spreading on rangeland vegetation dynamics and to determine the fluctuations of plant indices corresponding to climatic indices in a 6-year period.

In order to monitoring and comparison the fluctuations of vegetation indices was selected in Aquifer Management Kowsar Station, 2 networks (representative of the flood spreading area) with the names Bisheshzard 1 and Bisheshzard 4 and adjacent to them an area of ​​5 hectares outside the networks spreading as a control. The representative of the area without flood spreading). From 2016 to 2022 for 6 years, in the second half of May every year, 10 transects with a length of 150 meters and 100 plots of one square meter were established in a systematic-randomness manner in the strips of networks and the control field. The rangeland type indice species of flood spreading Gareh Bygone Plain (GBP) of Fasa shrubs are Dendrostellera lessertii (Wikstr) Van Tiegh., Heliantemum lippii (L) Pers Astragalus ssp. with understory of annual Grasses and forbs respectively. Plant indices (species name, percentage of canopy cover, number of bases per square meter, vegetative form and species biomass) and soil surface coverage (percentage of stones and pebbles, percentage of litter and percentage of bare soil) were collected every year. Using the modified six-factor method, the rangeland condition in flood distribution networks was evaluated in wet years and in dry years. For the comparison of different rangeland treatments in the survey years, flood spreading networks and strips and control area from different statistical methods (split-split plot design in time and space in the form of complete random blocks), correlation coefficients, was used step by step regression to determine the forecasting model for the production and canopy cover of rangeland plants and for average comparisons Duncan's test at the 5% level.

The results of the analysis of variance showed that the amount of plant indices evaluated between the survey years, between the networks and between the flood spreading strips had a significant difference at the level of 1% with the control. The percentage of plant canopy cover during the survey period from 8.69% in 2021 to 55.51% in 2020 and the production rate from 175.32 kg per hectare in 2021 to 813.55 kg per hectare in the year 2020 was variable. Using the adjusted 6-factor method, the rangeland condition in the networks with flood spreading in wet years was evaluated as good and in dry years as fair, while in the control area (without flood spreading) in wet years, It was assessed as poor to fair and in dry years, very poor to non-suitable for grazing. Based on the results of the correlation analysis, a positive and significant correlation was obtained between the canopy cover and plants rangeland biomass at the level of 1% (R²=0.86). The step by step regression results also showed that in the plant production prediction model, the independent variables (climate indicators) are the annual rainfall (R²=0.34) the average minimum temperature (r=0.26), the amount of rainfall in The growing season of plants (R²=0.15), the average annual temperature (R²=0.11) and their sum (R²=0.86) and in the prediction model, of plant canopy cover percentage, the independent variable of rainfall in the growing season of plants (R²=0.87) had the main and decisive contribution in estimating the value of the dependent variable.

Conclusion and Recommendations:

In general, it can be concluded that the percentage of plant canopy cover of Bishehzard network 1 in wet years (water years 2015-2016, 2016-2017, 2018-2019 and 2020-2021) compared to Bishehzard network 4 and control. It is statistically significant and in dry years (water years 2017-2018 and 2021-2022) these percentages are higher in control compared to two networks of Bishehzard 1 and 4. In general, there is a correlation between the production of plants with a canopy cover (R²=0.86), with the amount of annual rainfall (R²=0.92), with the amount of rainfall during floods (R²=0.84), with the number of floods (R²=0.96) =), with the duration of floods (R²=0.96), with the autumn and winter rainfall (R²=0.94) and with the rainfall in the plant growth Period (R²=0.93) positive and significant correlation at the level of 1% was obtained. In general, the changes in the amount of the plant canopy cover index are in harmony with the changes in the amount of annual rainfall, the number of rainy months, its distribution, and the number and volume of effective floods in the growing season of plants. Based on the statistics from 2016 to 2022, the 6-year average dry matter production in control is 252.25 and in Bishehzard 1 and 4 it is estimated to be 528.31 and 362.17 kg per hectare, respectively. The production of flood spreading networks is about 1.43 to 2 times that of control. From 2015 to 2022, there was a significant difference in plant production index fluctuations in Bishehzard 1 and 4 networks compared to the control. In general, considering that water is one of the main factors limiting the growth and development of plants in arid and semi-arid regions, the use of flood spreading as a simple, low-cost and nature-compatible method to improve quantitative growth indices rangeland plants are inevitable

Iran is located in arid and semi-arid areas of the world and the major factor in this region is water shortage. The intensive use of groundwater resources has often affected ground water levels in many parts of the world. This research was carried out with the aim of determining the appropriate management strategies for the optimal use of water resources in the Darband Samalghan watershed with the SWOT approach.

In order to carry out this research, several stages have been implemented, which include collecting information and data from the study area, as well as collecting all the strengths and weaknesses, opportunities and threats of the area, from the perspective of a group including experts and specialists in water resources to make a decision about the strategies. In the next stage, they were informed about the conditions of the region and the purpose of this study, and then scoring of internal factors (strengths and weaknesses) and external factors (opportunities and threats) was obtained. And by examining the factors with the current situation and choosing the best strategic group among SO, WO, ST and WT strategies, the SWOT matrix was formed and the most important management strategies compatible with the region were presented.

To determine the management strategies of water resources in Darband Samalghan watershed, the average of all SWOT tables was calculated. The sum of the scores obtained from the evaluation matrix of internal and external factors were 1.838 Strengths, 2.276 weaknesses, 1.908 opportunities, and 2.572 threats respectively, and as a result, the weaknesses outweigh the strengths. They prevail and also the threats are ahead compared to the opportunities. WT strategy, from the point of view of the experts present in the brainstorming session, had the most establishments among other strategies, and the strategies of this study area were close to defensive strategies. This strategy aims to minimize losses caused by threats and weaknesses.

Conclusions and suggestion:

After determining the parameters of weakness, strength, opportunity, and threat, finally the defensive strategy was determined as the best management strategy in Darband Samalghan area. According to the results obtained from this research, based on the opportunities and strengths in the region, it is possible to propose solutions that neutralize the threats and weaknesses in order to achieve the balance of the region's aquifer. If we lose time and the main factor of opportunity, the situation in the not so distant future will become much more critical than the current situation.

Urbanization has led to environmental challenges; one of these challenges is heavy metal contamination in which is a serious concern for the public health and health of watershed residents issues. One of the heavy metals that play a major role in soil pollution in urban ecosystems is Lead (Pb). Pb has been used by humans for a long time, and in recent decades, leaded gasoline is one of the main sources of this pollutant in urban watersheds. The use of digital soil mapping using the functions available in geostatistics has changed the zoning of soil pollution compared to the old methods and can lead to the optimal management of soil pollution while land use can also have a great impact on this management. The aim of this research is to determine the amount of Pb heavy metal in soil and its relationship with land use.

The study area was Shiraz urban watershed with an area of ​​41133 hectares, as a part of the Maharloo lake watershed, located in the central part of Shiraz township, Fars province in the south of Iran. Soil moisture and temperature regims of study area are xeric and thermic respectively. The studied land uses were bare lands, urban parks, gardens and mountain range lands In order to determine the physical and chemical properties of the soil, 30 soil samples were taken from the depth of 0 to 20 cm from each land use. Geographic information system (GIS) and spherical and exponential variogram geostatistical models were used to produce digital maps. Kriging method was also used to estimate the physical and chemical properties, and the amount of Pb.

Based on the results of this research, the difference in soil chemical properties such as reaction, equivalent calcium carbonate and the amount of organic matter in different uses was significant. Also, the amount of cation exchange capacity and lead pollution was significant at the level of 0.01. The results of this research showed that in urban watershed soils of Shiraz, the amount of Pb was influenced by some chemical characteristics of the soil such as organic matter and cation exchange capacity. In the studied area in different land uses, the trend of Pb contamination was as follows: mountain range lands < gardens < urban parks < bare lands.

Conclusions and suggestions:

The results of current research showed that different land uses can affect the amount of Pb. Considering the problem of soil pollution in urban watersheds and the important effect of land use on its amout, it is suggested to carry out research and urban development projects for detailed investigations of land use and its relationship with other environmental characteristics, including soil pollution. It is also suggested to carry out more local and thematic researches in urban ecosystems on the effect of various types of plant species on the amount of heavy metals in the examined soil, so that by planting that type of vegetation, soil decontamination can be helped.

Rivers serve as crucial sources of freshwater on Earth, and precise prediction of river flows plays a vital role in effective water resource management. To address this need, researchers have proposed various models. These models can be categorized into two types: (1) hydrological/hydraulic physically based models and (2) data-driven models. The cited papers provide evidence of the significance of employing data-driven models for hydrological issues, particularly in predicting river discharge.

In this study, the researchers utilized a gene expression programming model (GEP) and support vector machine (SVM) to predict the discharge of the Ferizi River. The dataset used in the study covered a period of ten years (2011-2020) and consisted of daily Ferizi river discharge readings obtained from the Moushang hydrometry station. The study area had an average altitude of 2171 meters above sea level, with a longitude range of 58° 49' 30" to 59° 4' 30" E and a latitude range of 36° 20' 1" to 36° 32' 1". For the prediction models, daily river discharge data from 1 to 5 days ahead were utilized as input variables for both the GEP and SVM models. To ensure data homogeneity and address any deficiencies, the researchers employed the run test and calculated the correlation coefficient between neighboring stations. Subsequently, the dataset was randomly divided into two groups: 80% for model training and 20% for model testing, as well as evaluating the modeling error. The performance of the models was assessed during the training and validation stages using various evaluation metrics, including root mean square error (RMSE), coefficient of correlation (R), bias, Kling Gupta (KGE), and Nash–Sutcliffe model efficiency (NSE). Additionally, in order to estimate the inflow to the Ferizi River using the SVM model, three common types of kernel functions in hydrology were examined, namely linear kernel, polynomial, and radial basis functions.

Among the different functions considered, the radial basis function was selected due to its lower error compared to other functions when applied to the variables. The best input model, Model No. 5, incorporated previous flow variables with a delay of five time steps. In the training phase, both the GEP and SVM models exhibited the highest performance in forecasting the daily flow of Moshang station. The performance of the applied models suggests that SVM (RSME = 1.15, R = 0.985, NSE = 0.85, and KGE = 0.79) demonstrates higher precision in the validation stage for river discharge prediction compared to GEP (RSME = 1.65, R = 0.964, NSE = 0.78, and KGE = 0.69).

Conclusion and Suggestions :

This study has demonstrated that the utilization of soft computing techniques, such as SVM and GEP, is a powerful tool in predicting river flow. These techniques are capable of establishing a favorable relationship between input and output parameters, enabling accurate simulation of average and maximum daily flow.

Carbon dioxide gas, produced from fossil fuels in industrial centres and near big cities, has a significant effect on climate change and global warming. Sequestration of carbon in plants and soil of protected areas, especially national natural parks, is the simplest and most economical way to reduce atmospheric carbon dioxide. The National Bamou Park, with an area of 46,913 hectares near the industrial centres of Shiraz, Zarghan, Maroodasht and Abbarik, provided a good chance for carbon sequestration. In this research economic analysis of this park's soil carbon sequestration capability in 2022 was done.

Based on vegetation cover and geomorphological conditions, 20 and 5 locations inside and outside the park were selected for sampling. Composite soil samples were taken from the 25 profiles with a depth of 30 cm length and width of 20 cm. The Wallcly-Black method was used to determine the percentage of soil organic carbon in the laboratory. The economic evaluation of the sequestered carbon was done using the damage cost avoided method at three levels: low estimate based on the values of trade in the Prototype Carbon Fund, medium estimate based on anticipated values in the future European Union carbon trading scheme and high estimate based on the damage cost assessment made by Intergovernmental Panel on Climate Change.

Based on the results, the average measures of carbon sequestered in the soil of the lands inside and outside the park were 40.05 and 21.75 tons per hectare, respectively. Based on the t-test, the average carbon sequestered inside and outside the park significantly differs at 1%. The average economic value of avoided damage related to carbon sequestration per hectare of land inside the park at low, medium and high levels are 123.12, 410.41 and 3283.26 million rials, respectively. The corresponding amounts outside the park are 66.86, 222.88 and 1783.04 million rials. The average economic value of sequestered carbon in the soil of each hectare of land inside and outside the park, based on the t-test, has a significant difference at the level of 1%.

Conclusions and Recommendations:

The suitable conditions of vegetation and soil of Bamou National Park have caused this park to have a high economic value because of the environmental services of carbon sequestration in the soil and absorption of carbon dioxide gas. Thus, it is possible the economic value of such services is considered in financial calculations, and all or part of it is allocated for the protection and expansion of these parks. An important point about the economic value of the parks and forest ecosystems services is the possibility of buying and selling carbon sequestered or carbon dioxide gas emitted into the atmosphere. For this purpose, it is suggested to pay attention to the legal frameworks and necessary infrastructures for creating an applied market of carbon sequestration and carbon dioxide emission at the national and regional levels. In addition, concerning the natural resources of Fars province and the criteria of international climate change agreements, it is possible to use foreign capital to help create and expand national parks and forest ecosystems as greenhouse gas reservoirs. Therefore, it is suggested to use these legal agreements to attract credit from international organizations.

Finding the potential of groundwater resources is one of the basic principles in water resources management. The aim of this research is to determine the potential of groundwater using support vector machine learning (SVM) models as well as metaheuristic algorithms (hybrid support vector machine model and the bee metaheuristic optimization algorithm (SVM-BA) and hybrid model of the support vector machine and particle swarm optimization algorithm (SVM-PSO).

The factors of elevation, slope, aspect, topographic humidity index, distance from stream, drainage density, distance from fault, lithology, topographic position index, land roughness index, relative slope position and flow convergence index were selected in Bojnurd region. Information on the location of 359 springs was received from the regional water company. Random division algorithm was used to divide training points (70%) and validation points (30%). Based on the removal sensitivity analysis, the importance and contribution of the input variables in determining the groundwater potential were determined. The accuracy of the models was evaluated in two stages of training and validation based on the receiver operating characteristic (ROC) curve method.

The evaluation of the accuracy of the models based on the evaluation criteria of the area under curve (AUC) showed that the prediction accuracy of the hybrid model of the support vector machine and the particle swarm optimization algorithm (SVM-PSO) is 0.945 more than other models (SVM: 0.918 and SVM-BA: 0.932). Based on the results of the superior model, the high potential class and the very high potential class accounted for 7.75% and 38.66% of the area respectively. Among the factors, relative slope position with 14.5%, distance from the fault with 13.4% and lithology with 12.3% were the most important in predicting groundwater potential.

Based on the results of this research, the support vector machine model has a high performance, and two optimization algorithms, the bee metaheuristic and particle swarm optimization algorithm, strengthen the predictive power of the model. Also machine learning models can identify the relationship between the environmental factors and the water supply of the springs and determine their role by using the available data. The relative slope position factor was identified as the most important variable and the distance from the fault factor was considered as the second most important variable in the present study. The results of the research showed that the faults in the region play an important role in aquifer recharge, storage and flow of groundwater. The lithological factor was also introduced by the model as the third important variable in identifying the state of groundwater potential. In this research, by presenting the groundwater potential map, it is possible to plan and verify land use planning for the Bojnurd watershed.