فصلنامه حفاظت منابع آب و خاک
سال یازدهم شماره 1 (پیاپی 41، پاییز 1400)

Soil improvement in loess soils, due to susceptibility to erosion, can increase strength, resistance and change or modify their mechanical properties. The purpose of this study was to investigate the changes in soil moisture curve parameters and some mechanical indices of loamy sand soils containing montmorillonite nanoclay. Thus, soil water retention was investigated by applying 1 and 5% of nanoclay and water holding capacity in soil was investigate by VanGenukhten and Brooks-Corey models. Then mechanical properties of soil was investigated by measuring Atterberg limits and how they change. Both experiments were re-evaluated over time. Nanoclay had a significant effect on water retention in various moisture suction systems and increased volumetric moisture content, especially in low suction. It also increased the fine porosity at the air entry value, indicating a decrease in the rate of water drainage from soil and increased its storage capacity in losses soil. Increasing the amount of nanoclay led to increase in Θs, but the change in Θr was not significant. As nanoclay increased, α and n parameters decreased, respectively. Predicting the parameters of the moisture curve equation using VanGenukhten model showed better results. Liquid and plasticity limits of the soil also increased. However, the increase in the amount of liquid limit was higher and the soil plasticity index increased. The increase in the surface area and the ability to maintain water by the clays and their shear strength can be due to this fact. Monitoring of atterberg and moisture curve parameters over time indicated their persistence.

In this study, the scour pattern in the vicinity of cross-vane structures with I, U and J shapes in bending channels is simulated by a new artificial intelligence method called "generalized structures group method of data handling” (GSGMDH). Initially, all the parameters affecting the scour depth in the vicinity of cross-vane structures are identified and then using these parameters, six different models are defined for each of the GMDH and GSGMDH methods. By analyzing the results yielded by the artificial intelligence models, the superior models are introduced. The GMDH and GSGMDH superior models estimate the scour values in terms of all input parameters. In addition, the accuracy of the GSGMDH models is higher than that the GMDH ones. For example, for the GMDH and GSGMDH superior models, the values of "variance accounted for" in the test mode are calculated 73.075 and 86.408, respectively. Also, the superior model forecasts the objective function values with acceptable accuracy. For example, the correlation coefficient (R), the scatter index (SI), and the Nash-Sutcliffe model efficiency coefficient (NSC) for the GSGMDH superior model in the training mode are approximated 0.913, 0.214 and 0.800, respectively. Based to the results of the sensitivity analysis, the shape factor of cross-vane structures, the ratio of the difference between the upstream and downstream flow depths to the height of the structure and the densimetric Froude number (Fd) are introduced as the most effective input parameters. An uncertainty analysis exhibits that the GSGMDH superior model has an underestimated performance.

Dracocephalum kotschyi is one of the most important medicinal plants of the family Lamiaceae which is endangered due to unfavorable environmental conditions. Therefore, in order to investigate the effect of biofertilizers at four levels (nitroxin, super nitroplus, biophosphorus and non-use of biofertilizer) on essential oil yield and nutrient uptake of D. kotschyi seedlings under drought stress at three levels (irrigation to completion 80, 60 and 40% of field capacity) a completely randomized design in 3 replication (each replication includes 25 pots containing one seedling) was performed in the greenhouse as a pot experiment containing cocopeat and perlite culture medium in a ratio of 1: 1. The highest amount of root nitrogen uptake (2.2 mg kg-1) and leaf nitrogen (57.5 mg kg-1) was observed in conventional irrigation treatment (irrigation treatment up to 80% of field capacity) and application of super nitroplus biofertilizer. The percentage of essential oil under mild stress increased by 77.53% compared to the control, while with the intensification of drought stress, the percentage of essential oil decreased by 94.49% compared to the control. The results of this study showed that the most increasing effect on essential oil percentage (1.1%) and essential oil yield (1.5 g plant-1) of D. kotschyi was related to inoculation with Super Nitroplus biofertilizer and mild drought stress, while cultivation of D. kotschyi under normal irrigation conditions and no biofertilizer resulted in the lowest production and yield of essential oil.

One of the major challenges affecting the natural ecosystems and various aspects of human life is climate change. The effects of global warming on the hydrology and water cycle in nature are very serious, and the quantitative recognition of these effects creates more readiness to deal with its consequences. In the present study, the black box model (artificial neural network) and the semi-distributed model (SWAT) were selected and examined according to error and uncertainty. This paper employed the large-scale model (CanESM2) under scenarios RCP2.6 and RCP8.5 to investigate the effect of climate change. The results of climate change in this study showed that runoff (3-59%) and temperature (1.53-6.93 °C) have an increasing trend. In particular, this increasing trend is further exhibited by extreme values and severe floods. Also, the amount of runoff will increase by 7-11% in the upcoming period. For this reason, it is necessary to pay attention in urban studies to the increase of flood occurrence in the future.

Evaporation acts as an important component and a key control factor in land hydrological processes. In the context of global warming, pan evaporation demand is expected to increase, but the decrease in measured pan evaporation has challenged the hypothesis that climate change would increase evaporation. The main purposes of this study were (1) to investigate the existence of evaporation paradox, (2) to detect the temporal trends of pan evaporation and related climatic variables on annual time scale. In this study the data of 50 synoptic weather stations in half-west and center of Iran were used. Non-parametric tests Mann-Kendall and Sen's slope estimator were used to discover trend through time series. Results showed that pan evaporation in 10% and 28% of stations had significant (p<0.05) decreasing and increasing trend, respectively. But, trend analysis of mean temperature as source of energy required for evaporation, indicated that in 94% of the stations had increasing trend. Despite the increase in temperature in the all stations, evaporation paradox has occurred in 36% of stations and only in 10% of stations evaporation paradox was significant at 5% level (p<0.05). Data analysis in stations that had evaporation paradox ( with negative pan evaporation trend) indicated that decrease in wind speed and sunshine duration and more increasing in the minimum temperature compared to the maximum temperature, were the main climatic parameters that controlling the rate of pan evaporation. Decreasing in pan evaporation in arid and semiarid areas of Iran is important in climatic studies.

In this study, the basic features of a tree vine copula such as the ability to decompose multivariate distributions into two-dimensional distributions, its flexibility in high-dimensional problems, and the use of conditional dependencies between variables have been considered. The purpose is to use C-Vine and D-Vine structures to determine the four-dimensional probabilistic distribution function of important characteristics of precipitation events of Cremona rain station located in Italy including maximum precipitation intensity total precipitation depth, wet period duration and dry period. So that, a combination of the most suitable Archimedean and elliptical copulas families was identified to fit the pair-copulas of each of the C-Vine and D-Vine structures. The optimal combined distribution functions of C-Vine and D-Vine structures were also calculated using chain density functions and compared with the four-dimensional experimental copula of important precipitation characteristics. Finally, the accuracy of C-Vine and D-Vine tree structures in determining the combined distribution functions of important precipitation characteristics was compared. The results showed that the RDLM C-Vine structure has a minimum value of evaluation criteria RMSE = 0.029 and MAE = 0.022, as well as a maximum of P-value = 0.35 and R2 = 0.998 among all C-Vine and D-Vine structures. As a result, it has the highest accuracy for frequency analyzing the of precipitation characteristics of Cremona station in Italy.

Vegetation is an important factor affecting runoff, quantity and quality of water in a watershed. This study investigates the effects of vegetation reduction in the eastern watershed of Lake Urmia on two parameters of runoff and the potential for water pollution .The WWPSS model was used to simultaneously assess the three parameters. Vegetation shows a fraction of the types of grass, tree and land without vegetation that were obtained from MODIS VCF satellite images. Runoff was calculated as accumulated water budget downstream. This model also provides an indicator to determine the potential level of water pollution. The results showed that rangeland cover decreased by an average of about 32%. Also, the average runoff production increased by 2.6, 3.16, 2.9 and 3.25 percent, respectively, in the existing conditions in 4 sub-basins of Aji Chai, Qaleh Chai, Marduq Chai and Sufi Chai compared to the situation before the reduction of vegetation coverage. According to the results, the difference in water pollution potential between the baseline and existing conditions in different parts of the watershed has fluctuated in the range between -9 to15% and an average of 0.6%. This change has increased the pollution load in some places and decreased it in others; but in general, it has led to incremental changes in water pollution potential with an average of about 2.5% in the total watershed. The method used can be used to quantify and map ecosystem water changes and its application in environmental assessment and management.

Recently, biochar has been considered as a soil conditioner. In research, the effect of the type and amount of biochar on soil properties has been emphasized. This field study was conducted to investigate the combined effect of type, amount and size of biochar particles on the total porosity (TP), penetration resistance (PR), mean weight diameter of aggregates (MWD) in a sandy loam texture. Factorial experiment was performed as a randomized complete block design with three factors of type, amount and biochar particle size in three replications. Wheat straw, vermicompost and apricot firewood biochard were added to the soil in 0.5, 1.5 and 3% and particle sizes of 0.5, 0.5-1 and 1-2 mm. All three biochar increased TP significantly and decreased PR significantly compared to control. Biochar type had the largest contribution in TP and PR changes. The highest TP was obtained in the wheat straw biochar treatment with 3% and particle size of 1-2 mm. The greatest decrease in PR was observed in wheat straw biochar with a value of 3% and a particle size of 0.5-1 mm. Interaction of type, amount and size of biochar particles had the largest contribution to MWD change. The largest MWD (1.22 mm) was observed in wheat straw biochar with biochar amount of 0.5% and particle size of 0.5 mm. The results showed that the amount and size of biochar particles had different effects on soil properties depending on the type of biochar.

In the study , irrigation efficiency and its main equation, the depth of root development has been considered as an important and indisputable factor. Therefore, determining the exact depth of root development at different stages of plant growth is importance. In this research, by digging profiles directly, the depth of wheat root changes in Hamidiyeh, Kowsar, Atabiyeh, Yasmin Ferdows, Daryoun, Weiss, Shadegan and Hindijan regions with soils with different salinities of 7.3, 23.1, 12.8, 12.7, 4.9, 24, 10.7, 14.22 dS / m respectively, were measured at a depth of 0 to 60 cm. Also, water salinity in each of the above pilots was 1.8, 1.9, 2.5, 2.2, 1.7, 2.4, 6.4 and 3.2 dS / m, respectively. The predominant soil texture of these areas is Clay Loam and Silty Clay Loam, respectively. As the results show, the texture of these pilots is heavy and the results of this research can be generalized in the same range of soil texture. In this regard, the Borg-Grimes (1986) root development depth model was evaluated based on FAO information and indigenous information obtained from the region. The results show that FAO data cause a large error of about 176% and the use of indigenous relationships in different soil salinity classes shows that using these equations with an average error of 18% can be a more appropriate estimate of Root depth various in these areas.