دکتر حسین ملکی نژاد

Soil moisture can be considered in the control of desertification, agricultural activities, watershed management and optimal management of water resources.   Since the country of Iran is facing many problems in these fields, the expansion of studies in the field of accurate estimation of soil moisture becomes important (Mehrabi et al., 2019). The GLDAS system may have a high error compared to the measured data in some areas. Therefore, it is necessary before the data and results of this product are used as a decision-making tool in the region.  The quality of these data should be evaluated locally using ground-measured data (Polo et al, 2016 & Sanchez-Lorenzo et al, 2013 & Zhang, 2019).In this study, Terra MODIS data was used to estimate soil moisture due to higher spatial resolution (1 km). Due to the fact that it is difficult to estimate the humidity time series in the field, and radar remote sensing methods produce humidity maps with low spatial resolution. Therefore, in this study, a new method was introduced to prepare a soil moisture map with higher spatial resolution based on NDVI and LST MODIS products.The purpose of this study is to estimate soil moisture in Jiroft city using the products of the Morris sensor and NDVI and LST indices. Considering that Jiroft plain is one of the agricultural poles of Iran. Estimating the time series of soil moisture and then providing a drought index based on soil moisture is a useful method for investigating agricultural drought in the study area.

LST and NDVI have high relative importance in arid regions (Park et al, 2016). In the study area, an algorithm based on remote sensing was used for soil moisture time series due to the lack of access to soil moisture time series. Moody's LST and NDVI products with a resolution of 1 square kilometer were used during 2007-2022. Then multiple linear regression was created using OLS method between soil moisture observations (2021 and 2022) and NDVI and LST time series data. Based on the results, both independent variables NDVI and LST were significant at the 99% level) p-value<0.01) .VIF values were less than 10. Therefore, there is no linearity between the independent variables. The standard error is small, which indicates that the estimated value is exactly the true value. The value of t statistic of two variables is higher than 2, which is considered statistically significant. In general, R2 = 0.78 and it shows the accuracy of soil moisture estimation method. R2 was obtained as 0.74 and 0.8 in the years 2021 and 2022, respectively, which indicates the accuracy of the predicted values.

Estimation of spatial and temporal changes of soil moisture is an important issue in low data areas such as Iran.  We proposed a multiple regression model based on Modis NDVI and LST to obtain surface soil moisture at a regional scale. The results showed that the multivariate linear regression method can be used to estimate soil moisture products with high resolution in areas with little data in the surface layers of the soil. Park et al. (2016) stated that LST and NDVI have high relative importance in arid regions. In the studied area, according to previous studies (Bai et al, 2020 & Wang et al, 2007), an algorithm based on remote sensing was used for soil moisture time series due to the lack of access to soil moisture time series became. Moody's LST and NDVI products with a resolution of 1 square kilometer were used during 2007-2022. Then multiple linear regression was created between soil moisture observations (2021 and 2022) and NDVI and LST time series data using OLS method.  Based on the results of simulated soil moisture changes and the OLS method in estimating soil moisture (0-30 cm), both independent variables NDVI and LST were significant at the 99% level (p-value <0.01)). VIF values are less than 10 Therefore, there is no linearity between the independent variables. The standard error is small, which indicates that the estimated value is exactly the true value. The value of t statistic of two variables is higher than 2, which is considered statistically significant. Overall, R2 was 0.7  And it showed the accuracy of the soil moisture estimation method, which is consistent with the results of (Khanmohammadi et al, 2008 & Lin et al, 2015).

Drought is one of the natural disasters that can occur in any climate. In recent decades, Iran has been continuously affected by severe and widespread droughts and has imposed harmful effects on various economic sectors, including the country's water resources. One of the needs for the growth and development of every country is water. On the other hand, due to the lack of permanent or even seasonal surface water flows in many plains of the country, one of the most important sources of water harvesting is the use of underground water reserves. Therefore, it is very important to investigate the status of these resources and determine the influencing factors on them. In this research, it has been tried to identify the areas that are exposed to severe groundwater drought and the impact of the factors affecting groundwater drought using the maximum entropy model and using MaxEnt software in the basin. The Jiroft plain watershed should be identified. To implement the maximum entropy model, 70% of the data were used for model training and 30% for model testing. The results of this study, based on the jackknife test, showed that the most important factors affecting groundwater drought are altitude, distance from the river, and soil moisture, and the model shows the most sensitivity to these parameters. gave Also, the results showed that the model has an acceptable accuracy in identifying groundwater drought, so that the accuracy of the model was estimated at 0.76.

Many factors are involved in agricultural development such as climatic conditions, soil moisture, evapotranspiration and etc. For their effectiveness, it is necessary to examine the key parameters. Timely and accurate monitoring of these committees with the help of satellite imagery is a necessity in this regard. Herat plain is one of the plains where soil salinity and lack of moisture has led to a critical situation of gardens and agricultural lands.

In this research, we have tried to study soil salinity, soil moisture and actual evapotranspiration using the MODIS sensor data for the four months of February, May, August and November 2017.

The first stage of vegetation survey shows 0.4 in May (growing season). While the maximum land surface temperature was recorded in August (54 ° C) and May (45.15 ° C). Then, in the next step, using the results of two indicators of vegetation and land surface temperature, the humidity of the area is investigated by TVDI. The humidity of the region was divided into five classes from zero to 0.5, which indicates the low soil moisture and dryness in the Herat plain. Finally, due to the dryness of the area and to verify the TVDI method, field soil samples were taken from different parts of Herat and especially its agricultural lands to estimate the soil salinity (EC, PH and soil moisture). The results showed that the soil moisture content of the samples at a depth of 5 cm above the ground varies between 0 and 0.3. Also, out of 12 soil samples, 6 samples have saline soils and one sample has saline-acid soils. Of course, it is also important to note that some of the agricultural lands whose soils are in the saline group are dry and left to their own devices.
Finally, the study of actual evapotranspiration with the SEBAL algorithm showed that in this region, despite the lack of moisture, actual evapotranspiration is very high, especially in the hot month of August.

Optimizing the use of water resources is inevitable due to water shortages in agricultural areas.  Pistachio gardening has been an attractive agricultural activity for several decades in Iran. Given the limited water resources, areas under pistachio cultivation in arid regions are not economical due to low production. There has been a continuous trend towards application of efficient irrigation systems such as pressurized subsurface drip irrigation methods, but their complexity and high initial investment, make them less suitable for small scale and scattered owners. This research describes the field performance of a very low-pressure subsurface irrigation method which has been introduced before (Dastorani et al., 2010). In this subsurface porous pipe irrigation system, water is delivered directly to the pistachio tree’s roots via perforated PVC pipes covered by plastic textile sleeves. The feasibility of this system has been demonstrated for irrigating pistachio orchards. They compared the effect of traditional (surface) irrigation and such subsurface irrigation method on crop yield and annual growth traits. Their results showed that subsurface irrigation method had relatively higher performance than the surface method. To accurately design such a system, it is necessary to assess the time variations of irrigation parameters including lateral infiltration q (leakage flow rate per unit length), local water pressure along laterals Px in terms of input water flow rate If , and pipe orifice density n, as it is the subject of this research.

Drought monitoring using appropriate drought indices is of importance in water resources management, especially in arid and semi-arid regions. Therefore, choosing the suitable drought index and calculating the desired drought index appropriately is of considerable importance in the study of drought. This study is aimed to determine the appropriate statistical distribution to calculate RDI drought index in arid and semi-arid regions of Central Iran. For this purpose, 16 synoptic stations in Central Iran were selected. To calculate RDI, precipitation and potential evapotranspiration values are required. The FAO-Penman-Monteith method was used to calculate potential evapotranspiration. To select the most appropriate statistical distribution, 17 statistical distributions were used. RDI for each synoptic station was calculated annually by fitting to each of the 17 distributions, separately. Then, based on the AIC and BIC criteria, the best statistical distribution was selected to calculate RDI for each station. While based on the literature, it is recommended to calculate RDI by fitting the data to one of the Gamma or log Normal distributions, the results showed that in most of the studied stations, the log Normal and Gamma distributions are not the most appropriate distribution. However, according to the results, Gamma distribution was one of the top 6 distributions in all the studied stations. The results also showed that the difference of RDI values ​​calculated based on different distributions in dry and wet years are relatively significant, which shows the importance of choosing the appropriate statistical distribution. The fit of the studied distributions to the precipitation data at different stations showed that the Nakagami distribution presents the best performance. In case of potential evapotranspiration, different distributions provided the best fit at different stations.

Today, due to water use and facing the world with problems such as water deficit and drought, short-term and long-term consumption management and planning is essential to achieve the goals set for water resources. The lack of data lysimeter measurements to estimate water requirements of plants is one of the biggest challenges that exist in the agricultural sector. On the other hand, using new methods to more accurately estimate the actual evapotranspiration and consequently, vegetation coefficient for different plants, especially the dominant cultivation in the plains of the country, can help better planning and management of water resources. In this study, using MODIS images and SEBAL algorithm, evapotranspiration for Marvast in Yazd province in four months (February, May, August ,November) 2017 was estimated. Maximum evapotranspiration the same time with the heating season is August and the plant occurred chlorophyll maximum amount of which is 582 mm. Then, with decreasing plant density, the evapotranspiration trend was reduced, which was the minimum evapotranspiration in February. Extraction of grapevine coefficient by FAO method showed that its amount was satisfied in May (1.23) and August (1.14). Due to the high rate of evapotranspiration and heat in these two months, the plant's need for water has been greater. Vegetation rates in the fall (November 0.25) and winter (February 29/09) were lower than during the growing season due to reduced leaf cover and reduced evaporation and transpiration. Then the values of evapotranspiration and water requirement of grapes were calculated with 5 other methods and were compared with the FAO method using statistical indicators of absolute error (MAE). The results showed that the experimental model of Hargreaves-Samani and Blaney-Criddle had a better performance in estimating the evapotranspiration of reference crop. In addition, results indicates the Hargreaves-Samani is the superior method and other methods are ranked in the next orders. Trajkovic and Bereti’s method did not show proper results, especially in the warm months.

Today, the world is facing several problems, including population growth, urbanization, food demand increasing, depletion of water resources, and environmental degradation. "Urban agriculture" as part of urban activities is an opportunity to make positive changes in the world food system and produce quality food. Urban agriculture is a new solution to deal with environmental, social, and economic problems. It is obvious that with the expansion of cities and the growth of the urban population, the demand for food will increase. Agriculture has always been the main supplier of human food and creates food security for society. In addition to its advantages and disadvantages, urban agriculture also has its challenges. Cities are the main centers for achieving the goals of sustainable development, and therefore the production of quality food in the smallest place and in the shortest time is very important. By producing food on rooftops, backyards, and suitable urban areas and by applying proper management, the food needs of citizens can be answered and the quality of the urban environment can be maintained. It also provides an opportunity for low-income citizens to achieve food security by creating jobs and reducing household food costs. The present study is based on a descriptive and review method using library studies.

The increase in greenhouse gases in recent decades and the resulting increase in temperature have upset the balance of the planet's climate system and caused widespread climate change in most parts of the world. In this study, first the SWAT model was calibrated for Jamishan watershed. The calibration and validation stages, NS and R2 coefficients were 0.6, 0.61, 0.52, and 0.54, respectively. According to the results of sensitivity analysis in the region, it was found that among the 20 parameters affecting runoff, the curve number was the most important parameter. Then, the values of temperature and precipitation for the next period based on the climate change scenario were subscaled with the outputs of the HadCM3 general atmosphere rotation model for the three scenarios A2, B1 and A1B using the LARS-WG model. Later, in order to simulate the watershed runoff, the data were introduced to the SWAT model and the results showed that the runoff in the statistical period of 2015 and 2026 increased by 6, 7 and 6% respectively compared to the observation period in each scenario A2, A1B and B1 and this shows the impact of climate change on runoff in the near future from 2016 to 2026. This study showed that changes in meteorological parameters will lead to significant changes in hydrological regime such as watershed runoff. Increasing rainfall and temperature are likely to cause floods in the region in the future.

Floods have historically been the most common, deadliest and most expensive hazards among natural hazards. The risk of flooding has increased over time, especially since countries have allowed changes in the land uses and land coves in floodplains and plains. In Iran, like the other flood-prone areas of the world, the severity of floods and the extent of their damages have increased dramatically in recent decades. Land use and vegetation play an important role in the production of runoff due to its effect on infiltration, erosion, evapotranspiration and transpiration.

Khorrambid watershed having an area of ​​88.7 km is a part of the Sivand Dam watershed. The average rainfall of this basin is 228 mm and it has a semi-arid climate in the view of Domarten. Khorrambid metropolitan basin consists of 12 smaller sub-basins in the study area with three main waterways named A, B and C that cross the city upstream of Khorrambid and pass through the city. In this study, the design, purpose, and efficiency amount of the flood and runoff output amount have been evaluated and finalized from the hydrographic network. The set of Management, Biological and Structural works carried out in the Khorrambid urban basin of the Sivand Dam Branches include: management excavation, piling, seeding, Dry working forage, Dry Stone Structures, rock and PVC mesh, rock and earth dams. Detailed studies and implementation of Khorrambid urban watershed was carried out in 1999 and the implementation of watershed management projects started in 2002 and by the end of 2010 about 33% of the projects were implemented in the study phase. At the same time, the evaluation process regarding the effect of these projects on flood and runoff control took place. This study aimed to evaluate the performance of projects (management, biological and structural) on the runoff and water resources in Khorrambid watershed in Fars province. In this study, first, the height of the dams, the length of the reservoir and the slope of the canals were measured under the basins where structural projects were carried out to determine the route of the new water movement. Then the new concentration time was calculated using the Branse-Williams method. In the next step, soil cover layer data such as the percentage of canopy cover, hydrological groups and vegetation status were obtained to determine the number of curves and maximum holding and infiltration potential in the soil. Then using SCS method and Hyfa software, modeling the flood volume and outflow runoff for sub-basin were estimated.

By analyzing the results of statistical analysis of changes it can be said that there were many changes in all land use and land cover as well as the implementation of structural and biomechanical projects in the studied area. To investigate the effect of land use and structural changes on the hydrological regime of the studied basin, SCS method was utilized. This model was formulated using GIS techniques. The results showed that due to the increase in rangeland land use (from poor to good condition) and the construction of watershed structures, flooding in the area has decreased in case there were 24-hour rainfall. This amount of runoff reduction in the basin A and C was 41% and 72%, respectively.

It is suggested that by evaluating the projects, if the performance of these projects could be evaluated in appropriate ways and from various technical and engineering aspects, the results would lead to finding the causes of the proposed operation failure and presenting appropriate solutions to address them. On the one hand, this could improve the quality of implementation of watershed management activities, on the other hand, it would increase operational efficiency, and the learnt lessons would enhance future plans. On the other hand, it is recommended that since watersheds are in fact considered as a natural-human system as well as a planning and work unit, comprehensive management of these watersheds is essential for achieving sustainable development goals. Watershed management is a complex process whose practical goals should be in line with the promotion of stakeholders` interests and stakeholders` engagement at all levels of planning and decision making. Integrated Watershed Management requires a flexible process that taking into account the challenges and constraints of the Watershed System, makes good use of its opportunities and potential conditions to ensure the social and economic well-being of its stakeholders while maintaining the security of water, food and environment in order to meet its goals of sustainable development.