فصلنامه حفاظت منابع آب و خاک
سال دهم شماره 1 (پیاپی 37، پاییز 1399)

Accurate estimation of evapotranspiration is one of the most important issues in water balance calculation at the catchment and field scale. The lack of meteorological observations for using empirical methods and the high costs of measuring evapotranspiration using lysimeter restricts the usability of these methods in most cases. To tackle these problems, this research addressed the performance of reanalysis models including W3RA, HBV-SIMREG, PCR-GLOBW, WATER-GAP, and Ensemble for estimation of evapotranspiration at different climate regions of Iran. Besides, the reference evapotranspiration for assessment of the above models obtained using lysimeter measurements. Findings showed that in most cases studies the Ensemble model’s performance with the RMSE value ranges from 3.42 to 7.57 mm/day is the weakest one, while the results of HBV-SIMREG and W3RA show the best agreements with lysimeter dataset. Analyzing the outputs based on mean bias error (MBE) depicted that the estimated evapotranspiration based on W3RA and Ensemble have the minimum and maximum bias, respectively. As an overall conclusion, although results indicate that PCR-GLOBW has the maximum correlation coefficient (CC) with the reference datasets, HBV-SIMREG is the best and reliable model for estimation of evapotranspiration in most climate regions of Iran and can be considered as an alternative dataset, especially in data-limited areas.

The frequency and intensity of extreme rainfalls will increase over many areas of the globe due to climate change. So, it is required to revise result of such studies based on the climate change scenarios. One of the most effective tools in such studies is Weather Generators, including LARS-WG. While GCMs predict future changes in the various characteristics of precipitation, usually in downscaling using LARS-WG, just changes of monthly averages are considered. In this paper, the future climate change impact on extreme precipitation in Gorgan and Khoramabad stations are assessed; while, the results of two methods of applying just change in averages (simple method) or applying changes in various characteristics of precipitation (complete method) in downscaling are compared. For future, CanESM2 outputs under RCP2.6, RCP4.5, and RCP8.5 scenarios for 2036-2065 period were used. The results showed that for climate change impact assessment on extreme rainfalls, additional to change in averages, change in other precipitation characteristics should be considered. Because the results of the two methods are different. In Gorgan, for example, the annual maximum daily rainfall with a return period of 15 years in the future will increase by 16 to 21 percent according to the more complete method, but between 37 and 49 percent according to the simpler method. Based on the complete, Intensity of the extreme rainfalls at both stations will increase in the future. This increase will be between 23% and 30% for the 2-year return period and between 25% and 29% for the 30-year return period.

Permeable vanes are structures that move the erosion of the outer bank of the river by diverting the erosive flow from the outer arch of the river to its center. In this study, the pattern of erosion and sedimentation around the hydraulic structure in the installation conditions of different distances from each other has been studied. Six-pillar concrete elements are materials that form a permeable structure overlapping and are applicable without drying the riverbed. These blocks need to be examined for how the structure works. With this concept, in the present study, the performance of this structures were performed in a laboratory channel with a width of 60 cm and a 180 degree flume under different hydraulic conditions (Fr = 0.227, 0.244, 0.261, 0.278). The required data were measured at different distances (5L, 6L, 7L, 8L) with an effective length equal to 20% of the width of the flume (L=12cm). Control experiment was performed in similar conditions to other scenarios without groins construction. Comparison of the results of the control and main experiments showed that the construction of permeable rectangular groin with a distance of 5L had the best efficiency in reducing the maximum depth of scour at the outer bank compared to the control experiments equal to 70.1% and 57.9% in Froud numbers of 0.227 and 0.261, respectively.

Developing a precise and rapid method for assessing the impact of farming operations on soil quality is important for sustainable resource management and monitoring management approaches in agricultural ecosystems. The objective of this study was to evaluate the efficiency of spectroscopy as a rapid and quantitative approach for monitoring physical and biological soil quality under agricultural management in Zanjan province. 77 soil samples were collected from the depth of 0-20 cm under irrigated and rain-fed agriculture. Important physical and biological properties, affecting soil quality in this province, were measured using standard methods. Then, soil spectral data were determined in VIS-NIR region and spectral models were calculated using partial least square regression. The average reflectance of soil spectra from 450 to 2450 nm, were significantly different (p < 0.05) between rain-fed and irrigated land uses. Moreover, land use type had a significant impact on most physical and biological properties, measured in this study. Spectral models with excellent accuracy(RPD>2.5 and R2>0.8) were noted for soil microbial respiration, clay content and soil organic content. The models with good accuracy (2<RPD0.76) for microbial carbon biomass, aggregate stability, sand content and with moderate accuracy (1.5<RPD0.65) for bulk density, hydraulic conductivity and silt content were obtained. However, sorptivity was not estimated with appropriate accuracy using spectral models. The effect of management operations under irrigated and rain-fed land use was detectable using soil reflectance spectral signature, and spectral data showed an overall good ability for evaluating physical and biological indicators of soil quality.

Determining the optimal number of required wells and pumping flow and selecting the place of drilling wells to meet the water needs of different uses is one of the important issues of water resources management in arid and semi-arid regions.The results showed that changing the coordinates of wells due to the variable thickness of the aquifer and also different water quality in different areas, will affect the cost of extraction and water treatment, respectively, and on the other hand, the distance from the place of consumption will increase the cost of transmission Changing the pumping flow of wells will also affect the energy consumption of the pump in the process of water extraction and transfer. Based on the results, the cost of the optimal design has been reduced by about 10% compared to the existing design. The results showed that water level drop and groundwater quality had the highest weight coefficient.Also, the areas that had the most drop, the best water quality, the shortest distance and the lowest height to the place of consumption, had the highest weight coefficient and the areas that had the lowest drop, The average annual drop in water level in this area varies from 1.13 to 0.3 meters. There are 422 deep wells in this area, about 60 of which have a discharge of more than 20 liters per second and are a good option for replacing the city's drinking water supply wells.

Little is known about the long term effects of nanoparticles on soil properties. Therefore, the objective of this study was to investigate the three years effects of nanoparticles on aggregate stability and some of the soil chemical properties. Different amounts (1, 3 and 5 percentage by weight) of two types of nanoparticle of metal oxides, MgO and Fe3O4 were mixed with a loamy soil in three replications and their possible effects on different properties of the soil after three years were investigated. The results showed that application of nanoparticles, increased the pH of the soil from 7.7 in the control to 8.1- 9.3 and the electrical conductivity from 0.31 in the control to 0.34 -0.56 dSm-1, due to the increase in the alkali cations. The percentage of calcium carbonate increased from 19.75% in the control to 20.5-22.7% due to the accumulation of nanoparticles in the soil, with the highest increase in three variables with 5% magnesium nano oxide. 3% nano iron oxide significantly increased the cation exchange capacity from 23.50 in the control to 24.28 cmolc/kgsoil. Also the nanoparticles increased the mean weight diameter, due to their high specific surface area, with the greater effect of magnesium nano oxide (increased from 33 to 1242 percentage compared to the control) than iron nano oxide (increased from 97 to 173 percentage compared to the control). In general, the results of this study showed that, nanoparticles with specific physico-chemical properties can affect some properties of soil.

Drought is a natural disaster and inevitable phenomenon, which should be considered preventable, but can be managed and organized. The main purpose of this study is to show how copula functions are used in the four-variable analysis of drought in the west of Iran. For this purpose, the drought characteristics, including severity, duration, inter arrival time and peak were extracted using modified Standardized Precipitation Index (SPImod). Then the frequency distributions were fitted to the mentioned drought characteristics and the best fitted marginal distribution were specified for every drought characteristics. The results showed that the gamma and exponential distributions had the best fitness on the drought severity and duration, respectively. Also, for drought peak and inter arrival time variables, the GEV function was known as the best fitted marginal distribution. In order to four variate analysis of drought characteristics, these variables were paired two by two using nested copula method. For this purpose, the fitness of nine copula functions, including Clayton, Ali-Mikhail- Haq, Farlie- Gamble- Morgenstern, Frank, Gamble, Gamble- Hougaard, Plackett, Philip Gamble and Joe were examined using Akaike Information Criterion (AIC), Maximum Likelihood (ML), and Nash-Sutcliffe Efficiency (NSE) criteria. The results showed that Joe copula is the best function for constructing the multivariate distribution in the study area. Also, this study showed that a four-variate analysis of drought provide useful information for planners and managers for drought prediction and planning to cope with drought consequences.

Temperature is a key factor in yield, crop water requirement, and then virtual water of various agricultural products. Therefore, it is necessary to investigate the effect of latitude as one of the most effective factors on the variation of virtual water of agricultural products. In this research, the virtual water content of nine major plants including wheat, barley, alfalfa, sugar beet, corn, watermelon, tomato, onion and potato in four eastern provinces (including 56 cities) of Iran was calculated based on 20-year statistical data. Then, the average virtual water of each plant was calculated in different latitudes from 〖25〗^° to 〖38〗^°N at 1^° intervals using ArcGIS software. The regression between the average virtual water with crop water requirement and yield of the products revealed a positive correlation between virtual water and crop water requirement (r=0.65) and a negative correlation between virtual water and yield (r= 0.74). The average virtual water from the lowest to the highest was 0.19, 0.38, 0.45, 0.46, 0.53, 0.57, 1.59, 1.69, and 1.80 thousand cubic meters per ton for corn, sugar beet, onion, watermelon, tomato, potato, alfalfa, barley, and wheat, respectively. The results showed that the variation pattern of virtual water of the studied products across different latitude was Gaussian. Despite the different maximum values of virtual water, they occurred in the latitude range of 〖30〗^° to 〖33〗^° N and by moving away from the mentioned range to higher or lower latitude, the virtual water content of all products decreases.

Heavy metals enter from human being activities into soil and food cycle and can lead to poisoning. In this research, the influence of adding poplar wood biochar, mixture biochar and zeolite on the decrease of Pb, Ni and Cd adsorption by potato was investigated. To produce biochar, a lab scale gasification reactor (850°C) was used. A random trial including 3 repetitions was conducted in a greenhouse located in Basminj, Tabriz. Additives percentages were 2, 3 and 5 wt%. The amount of Ni, Pb and Cd traits were significant at 1% probability level. The highest and lowest Pb adsorption were belonged to treatment with no additives (6.89 mg per g) and poplar biochar factor (3.85 mg per g). Compared to mixture biochar (3.31 mg per g) and zeolite (4.5 mg per g), poplar wood biochar factor (2.75 mg per g) had the lowest Ni adsorption. The second (3%) and third (5%) levels treatments of poplar biochar (2.8 and 2.05 mg per g) accompanied with the third level (5%) mixture biochar factor (2.93 mg per g) had the lowest Ni and the treatment with no additives (6.75 mg per g) had the maximum Ni. The highest Cd amount was belonged to the treatment with no additives (1.96 mg per g). Furthermore, poplar biochar factor (1.18 mg per g) included the lowest Cd amount compared to the mixture biochar (1.58 mg per g) and zeolite (1.52 mg per g). Considering all, the poplar wood biochar showed the highest decline of metal adsorption.