فصلنامه علوم و مهندسی آبیاری
سال چهل و هفتم شماره 1 (بهار 1403)

Agricultural water management studies require accurate information on actual evapotranspiration. This information must have sufficient spatial detail to allow analysis on the farm or basin level (Sanchez et al., 2008). The methods used to estimate evapotranspiration are grouped into two main groups, which include direct methods and indirect or computational methods (Alizade and Kamali, 2007). Basics of the indirect methods are based on the relationship between meteorological parameters, which impedes the use of these data with a lack or impairment. On the other hand, this information is a point specific to meteorological stations, and their regional estimates are another problem of uncertainty of their own. To this end, the use of remote sensing technology can be a suitable approach to address these constraints. Real evapotranspiration can be estimated by satellite imagery that has short and long wavelengths and is estimated using surface energy equations (Chihda et al., 2010). Examples of such algorithms include SEBAL (Bastiaanssen et al., 1998 Bastiaanssen, 2000;), METRIC (Allen et al., 2007), SEBS (Su, 2002). Among the above mentioned algorithms, energy billing algorithms have been used (Bagheriharooni et al., 2013; Teixeira et al., 2009). Among the factors of superiority of the SEBAL algorithm, in comparison with other remote sensing algorithms, is a satellite imagery analysis algorithm based on physical principles and uses satellite simulation and requires minimum meteorological information from ground measurements or air models (Bastiaanssen et al., 2002).

Rivers are known as the main sources of surface water in the world, which experience seasonal fluctuations in water level. These resources have severe damage to human societies and nature in flood conditions and have irreparable consequences in the drought seasons. Optimal utilization of these resources with maintaining the environmental conditions of the waterway and minimizing flood damage is considered one of the river engineering goals. Since the conventional methods of river management are imposed serious environmental threats on waterways and wetlands, consideration to these water resources requires attention to issues related to plant ecosystems, solving challenges of coastal bed erosion and predict the condition and management of the river in the future (Callow, 2012; Dawson and Haslam, 1983; Fan et al., 2013; Rose et al., 2010; Rowinski et al., 2018). One of the strategies that cause loss of flow energy in the river improves the hydrological system and river ecosystem is the presence of vegetation in the river banks and floodplains. Native vegetation in floodplains and coastal forests plays an important role in conserving waterway ecosystems, flood management, coastal protection in urban lands and agriculture adjacent to the river (Fathi-Moghadam, 1996). Vegetation will also control the width of the river and increase the stability of the shores by absorbing and settling suspended sediments in river banks. The plant species along rivers and waterways are composed of various vegetative components, mainly affected by the environmental conditions of their habitat, including the distance from the waterway bed, hydrological characteristics of the river, climatic and soil conditions. Obviously, the effect of each plant species in the ecosystem cycle varies and for each section of the river, a specific combination of plants will create optimal conditions.

Many theories are found for subsurface drainage system design (Kumar et al., 2013). These were formulated by some of the soil characteristics that are important in designing and operating drainage systems. Most of these formulas have simplified and just involved flow parameters or assumed soil media as a maximum of two layers. In paddy fields, used equations for water table depth prediction have no accordance with field condition. Due to specific flow situations in these fields, much difference was observed in results (Darzi-Naftchali et al., 2013). The differences were because of special layered soil in paddy fields and soil hydraulic characteristics, hardpan layer existence formed in long cultivation and tillage, its effect on flow, and of course, lack of a suitable formula for these fields. So, designing rules for subsurface drainage in paddy fields needs investigation and implementation of new relations to predict the flow pattern suitably. Determination of design criteria and suitable formulas needed to predict flow network around drain tubes. Jafari-Talukolaee et al. (2017) reported in predicting water table profile between bilevel subsurface drainage in paddy fields due to the existence of resistance in vertical flow direction based on soil layers, and field results have no suitable agreement with analytical solution. Darzi-Naftchali et al. (2013), analyzing the effect of subsurface drainage systems on water balance and water table in paddy fields for a successive rice and canola cultivation season, obtained that shallow drainage systems were more influenced than deep drainage systems in water table control. The flow pattern of water towards the drain tube and the components of the flow network are the basis of the drainage system design. By determining the flow path towards the drains and the water table profile variation, the distance and depth of the drains in paddy fields can be determined with greater accuracy.

The use of practical methods for increasing water conveyance efficiency and optimal use of limited water resources is vital, especially in the world's arid regions, where water scarcity is always a concern. In that respect, efforts to reduce the cost of irrigation canals while maintaining the characteristics, technical standards, prevent damage to the structure, prevent leakage and loss of water at different stages of water transfer and distribution are of great interest to researchers (Abbasi, 2011). One of the solutions is to use pozzolanic materials, which replace a part of cement as cheap materials and thus reduce the finished price of cement. Changes in concrete fluidity and plastic behavior and hydration of cement are the most important physical changes that a pozzolan creates in concrete. Moreover, it can improve the strength and permeability of hardened concrete, resistance to thermal cracks, sulfates, and expansion (Luhar et al., 2019). Regarding using pozzolans to strengthen concrete, one of the most widely used plants in this field is bamboo. Bamboo is a plant that grows in tropical, subtropical and even temperate regions and any favourable regions in terms of ecological factors. On average, 20 million tons of this plant are produced annually in Asian and Latin American countries, which indicates its availability (Frías et al., 2012). Based on observations, Bamboo fibers increase the water absorption ratio (Xie et al., 2015). Furthermore, with the increase in the percentage of bamboo fiber, porosity is also growing (Da Costa Correia et al., 2014). However, Xie et al. (2015) stated that more than 25 to 35% of fiber use reduces stiffness (Xie et al., 2015). Taking these features into consideration, this study aimed to evaluate improvements in compressive strength, tensile strength, durability and elasticity of concrete with bamboo pozzolans.

Remote sensing is a fast and cost-effective solution in preparing and presenting this data to climate models due to the difficulty of preparing snow meteorological data in the field. The presence of clouds is one of the problems of satellite images that cause temporal-spatial fragmentation of snow data and increase its resolution efficiency. This study aims to provide a suitable framework for removing the effect of clouds on satellite images and generating the satellite snow metering data without disturbing cloud effects. For this purpose, first, daily MOD10A1 images of the MODIS sensor products were refined (temporally and spatially) using local snow depth data, average temperature, and daily rainfall of the Lake Urmia catchment and western part of the Caspian Sea basin. A multivariate linear regression model application showed that the normalized snow differential index (NDSI) values correlate with existing snow metering station data (r= 0.85 and RMSE= 0.047). Accordingly, the cloud-covered areas in the MODIS images were replaced with the values obtained from the model. Then, new NDSI values were calculated using geostatistical methods and the location of each pixel's location. By examining the relationship between the NDSI and the cumulative snowfall from January to March 2016, it was found that replacing the primary satellite images with corrected images can increase the R2 from 0.63 to 0.81. Therefore the proposed methodology could improve the accuracy of satellite snow metering.

Drought is one of the most destructive phenomena in the world, especially in Iran. The timely prediction of drought and its severity can make it easier to take the necessary measures to combat this phenomenon. Different methods have been proposed to predict droughts; however, what matters is which method can make the predictions more accurate. Many researchers have compared the CANFIS model with other models such as neural networks and linear regression Malik and Kumar (2020b); Malik et al(2020a); Malik et al (2019), but it has not been tested against the M5 tree model. In this study, CANFIS, M5, MLPNN and MLR models have been used to predict drought in Kermanshah synoptic station, to enhance the accuracy of drought prediction by using a variety of modeling methods in addition to the influential variables of the SPI index.

Scour around the bridge piers is a kind of erosion that occurs due to complex vortex flows and finally creates a hole around the bridge piers (Yang et al., 2019). The maximum scour depth, which called Equilibrium scour depth, can take a very long time to reach. Although many researches have been carried out to determine the equilibrium scour time, there is still no suitable criteria for determining the equilibrium scour time for the complex piers which consist of the pile group, pile cap and piers. In the present study, considering the importance of this fact that the local scour process is dependent on time, the effect of the complex pier geometrical parameters on the equilibrium scour time around the complex pier is investigated. In addition, a regression equation for the estimation of equilibrium scour time was presented which has suitable performance to estimate desired output in the range of the experimental data of the present study.

Turbidity currents, or dense flows, occurs when a fluid moves within another fluid with different densities, also Turbidity Current occurs when a fluid with a higher or lower density than the ambient fluid enters a fluid with a different density. The main cause of this phenomenon is the effect of the difference in density on gravitational acceleration; hence, Turbidity Currents are also referred to as gravitational flows (Graf & Altinakar, 2003). Karamichemeh (2014) investigated the effect of slope and concentration on turbulent flows in the submerged region along a straight path. To achieve this, they conducted 60 experiments with four discharge rates ranging from 5.0 to 2.0 liters per second, four concentrations with volumetric mass of 1013, 1009, 1006, and 1016 kilograms per cubic meter, and three slopes of 8, 12, and 16 percent. The results of this study showed that with an increase in the Richardson number (inverse of the square root of the densimetric Froude number), the intensity of mixing decreases. Additionally, the intensity of mixing in the submerged region is greater compared to the intensity of mixing in the body region. Given the limited studies on the movement of Turbidity currents in curved paths, the aim of this research is to investigate the effect of bends on the Water Entrainment in the plunging region.