فصلنامه حفاظت منابع آب و خاک
سال دوازدهم شماره 1 (پیاپی 45، پاییز 1401)

From a hydrological point of view, measuring the flow of rivers, lakes and groundwater is a measure of drought and there is a baseline time between the lack of rainfall and the decrease of running water of inlets and lakes and groundwater. More studies have been done on meteorological droughts compared to hydrological droughts. Therefore, the purpose of this study is multivariate analysis of hydrological droughts in Lake Urmia basin using artificial data generation models and Copula functions. Therefore, using a combination of the above methods for the analysis of hydrological droughts was used as a new method for the analysis of hydrological droughts.

In this study, in order to multivariate analysis of hydrological droughts in the Urmia Lake basin, the flow data of 28 hydrometric stations in which the flow regime is real were used during a statistical period of 40 years (1978-2017). Also, Ar (1) model was used to generate artificial data and SDImod index was used for drought analysis. For this purpose, artificial data were generated in 1000 sequence. Since univariate drought analysis and analysis based on historical data can not show the horizontal of future droughts alone, so using the Ar (1) model, annual data were generated and then using the model The Valencia and Schakke generated monthly artificial data. Then drought characteristics (intensity and duration) were extracted for both historical and generation data series and common distributions in hydrology were fitted to intensity, duration and flow data. Then the transfer probability matrix and their steady state condition matrix (SSC) were also calculated. Also, multivariate analysis of hydrological droughts was performed using ten Archimedean Copula functions. The above coding was done in MATLAB software environment.

The results of this study showed that after examining the homogeneity of data and their static test, most of the data had the necessary homogeneity and the results of data homogeneity showed that the coefficient of explanation was above 0.9 and the results of static test and Their trend showed that the data were within the allowable range of 1.2 ±2.1 and ±1.96. The results of fitting the data on the common statistical distributions showed that the Log Pearson Type3 (LP3) function was known as the superior distribution functions on the flow data and the gamma and exponential distribution functions on the severity and duration of the drought, respectively. The number of drought periods based on different scales of SDImod index showed that for different periods the number of drought periods for short-term scales was more than long-term scales. Also, the average intensity and duration of drought for generated and historical data indicate an increase in the intensity of drought for generated data compared to historical data. The results of classifying drought periods for historical and generated data showed that approximately 68% of the data were in the normal range during the statistical period and 32% were other classes. The result of the Copula functions showed that the Joe Copula function in the first order and Filip Gumble and Galambos functions in the next order were known as the superior Copula functions.

Finally, the results showed that the artificial data generation models for annual and monthly data for statistical years less than 30 years maintain the statistical characteristics of mean, standard deviation, skewness and correlation between two consecutive months, while increasing The number of statistical years of model performance becomes more favorable. The cumulative probability of non-annual drought and the probability of normal and wet season in hot months of the year is higher than other months of the year. Also, with increasing periods of drought, the cumulative probability of non-drought increases, so that with increasing periods, this probability decreases and becomes almost zero. The results of the joint and conditional return periods as well as the Kendall return period showed that the probability of drought occurring in future periods is expected to be at least similar to the historical data. The results also showed that the Joe Copula function was recognized as the superior Copula function for historical and generated data. Accordingly, the theoretical Copula function is close to the 45 degree angle bisector against the experimental Copula function.

One of the new methods for controlling erosion on the outer bank of river curve is the use of plates connected to the riverbank. Coastal vanes are the environmental structures which are used to control bank erosion, divert flow from bank to river center, improve sediment transport status, develop river for sailing, restorate and develop river's aquatic habitat. Despite the many advantages of coastal vanes, there is no detailed information about erosion and sedimentation and flow patterns around them under different hydraulic and geometric conditions and fewer research have been done. In the present study, the effect of different installation scenarios of triangular permeable vanes on bed sediment longitudinal and transverse profile changes in a laboratory channel with a 180-degree bend is evaluated.

In this research, the main purpose is to investigate sedimentation and erosion patterns in the rivers’ bend using coastal triangular vanes; in this regard, the impact of distance between triangular vanes, their effective length, and Froud number on the erosion control of the outer bank of the 180 degree bend is focused. Experiments in a laboratory flume with a mild 180-degree bend with a  ratio and a rectangular cross section with a width of 0.6 meters is done. The angle of fixed triangular vanes is 60 degrees, the height of the permeable triangular vanes from the sediment surface is 10cm and the permeability of the triangular vanes is 12%. The experiments were carried out with limpid water mode. The effective lengths of the prepared vanes were 12, 15 and 20 cm with installation intervals of 60, 75 and 100 cm respectively and were run at two different inlet discharges.

Investigating the effect of the distance between permeable triangular vanes on bed topography shows that in each Froud number, with increasing the distance of vanes from each other, the maximum scour depth will be increased. The results demonstrate the use of permeable triangular vanes causes the flow deviation from the outer bank to the center and then the inner bank of the flume, which leads to control the erosion in the river outer bank. By increasing the inlet flow discharge and increasing the effective length of triangular vanes and the distance of triangular vanes from each other in a 180-degree bend, the maximum scour depth and volume are increased. The installation of triangular vanes with an effective length of  and a distance of 5L causes the flow deviation from the outer bank to the vanes cape and the middle of the flume, consequently results in a decrease in the shear stress in the middle of the flume and scour depth of the erosion channel and creates thalweg in the vanes cape.

The results illustrate that by installing the triangular vanes, the point-bars are created in the interval between them. Therefore, during the effective length of 12cm, the maximum height of the point-bar on the outer bank equals to 30 and 31% of water depth, between the 0 to 170 degrees and 68.7 to 115 degrees equal to 11 times and 3 times the distance between the vanes, for discharge values of 13.5 and 15.5 l/sec, respectively. Also, for the mentioned conditions the width of the point-bar on the outer bank reaches  85% and 75% of vanes’ effective length , respectively. Permeable triangular vanes with six pillars are recommended for meandering rivers like  Karun in 90 and 180-degree arcs. These rivers have high torsion and curvature as well as high flow depth and low flow velocity in them, which contain high suspended sediments and the slope of this type of rivers is 0.001 or less and due to the low slope, their sediment carrying potential. Sediment loads are mostly fine.

Anthropogenic water scarcity is among global concerns which threats the sustainability of the world in future. Overexploiting limited blue water resources for supplying human’s growing food demand is the main root of such a scarcity. Being still in its infancy, water footprint (WF) benchmarking is a proper method to determine the inefficient fraction of water consumption. Hence, we assessed if achieving benchmark levels can limit agricultural WF to its sustainable cap in Khuzestan province, which is the agricultural backbone of Iran.

The research consists of three stages including WF accounting, and sustainability and efficiency assessment. First, consumptive and degradative WFs were accounted for 32 in counties of Khuzestan province over the period 1986-2016. Green and blue WFs were accounted by dividing green and blue evapotranspiration by crop’s yield, respectively. The AquaCrop model was used to simulate daily evapotranspiration, and then, seasonal values were estimated by aggregating daily values. Grey WF was estimated for the applied nitrogen fertilizer in croplands. In the next stage, the sustainability status of water consumption pattern was assessed by dividing overall blue WF by blue water availability. The latter was estimated by subtracting environmental flow requirements from natural runoff. Thereafter, WF benchmarks were extracted for 10th, 25th, and 50th level of crop production, and based on which, the inefficient fractions of blue WFs were estimated for individual crops. Finally, inefficient blue WFs were compared with unsustainable ones to know if achieving benchmark levels can limit agricultural blue water consumption to its sustainable caps in the study area. A correlation assessment was also done to determine the main roots of inefficiency in Khuzestan province.

Along with a 63% increase in crop production and 53 increase in unit blue WF, the overall blue WF increased by 80% over the study period. Such an increasing pattern caused groundwater overexploitation with an annual average rate of 12 million m3 y-1. The contribution of green WF in consumptive WF decreased from 60% in 1986 to 48% in 2016. Overall grey WF, however, followed a decreasing trend, with an average annual decreasing slope of 140 m3 ha-1 y-1, which mainly occurred by a considerable reduction in cash crop’s grey WF. In 2016, a total of 0.98 billion m3 of blue water was consumed unsustainably, which was roughly 85% higher than one in 1986. The number of countries with unsustainable water consumption also increased from 2 counties in 1986, to 9 counties in 2016. Stable crops had the largest contribution in unsustainable WF. Based on the results of efficiency assessment, and considering WF benchmarks developed at 25th of crop production level, inefficient blue WF varies in the range of 0.26 to 606 million m3 y-1 in different counties in 2016. Compared with 1986, the inefficiency increased by 10-3860 m3 ha-1 in 16 counties in 2016. While achieving benchmark levels can reduce blue WF to its sustainable level at provincial scale, unsustainable blue WFs in Andimeshk and Ramshir counties are still 6.8 and 340.9 million m3 higher than the inefficient blue WFs, respectively. The correlation assessment showed that inefficiency increase along with any increase in added value by agricultural production and/or export, unit blue WF, blue water scarcity level, and access to groundwater consumption; while it decreases with any increase in the number of employees per ha, crop yield, and cash crop’s harvested area.

WF assessment showed that crop production in Khuzestan province is done at the cost of deteriorating environment, which threats the stability of agricultural system in near future. While achieving benchmark levels helps with being limited to sustainable WF caps through removing inefficient blue WF fractions, there are still the risk of unsustainability in some regions, which indicates the importance of high-resolution assessments for determining hotspots. Hence, further research is required to determine temporal hotspots as well, in order to implement a proper sustainable development plans.

At this day and age continuous flood irrigation during the crop growth period in the paddy fields of northern Iran has caused high water consumption (WC). Due to the lack of water resources in Iran, proper irrigation management is necessary to reduce WC in different rice cultivars. Therefore, the present study was conducted to investigate the effect of irrigation management on yield and yield components of four rice genotypes.

The experiment was conducted as split plot in a randomized complete block design with three iterations at the research farm of the Iranian Rice Research Institute, Mazandaran Deputy (Amol). In this experiment, rice genotypes at four levels (G1: Toloo, G2: Tarom, G3: Tisa and G4: Shiroudi) as main factor and irrigation at six levels (I1: continuous flooding (CF) from transplanting to 20 days after 50% flowering and then cutting irrigation, I2: CF from transplanting to 15 days after 50% flowering and then cutting irrigation, I3: CF from transplanting to 10 days after 50% flowering and then cutting irrigation, I4: CF from transplanting to 5 days after 50% flowering and then cutting irrigation, I5: CF from transplanting to flowering stage and then cutting irrigation and I6: Intermittent irrigation from transplanting to 10 days before harvest and then cutting irrigation) were considered as sub-factors. At physiological maturity, the yield and yield components such as plant height, panicle length, total number of tillers per hill, number of filled grains per panicle and 1000-grain weight were measured.

The results showed that the highest and lowest grain yield were 6765 and 4255 kg.ha-1 from Toloo and Tarom cultivars, respectively. Application of I1 resulted in maximum grain yield (6291.8 kg.ha-1), while with the application of I5, yield decreased by 17.4%. Application of I6 while producing optimal grain yield (5911 kg.ha-1), can have a good ability to reduce WC in paddy fields, so it was selected as the best irrigation management option in case of water shortage for irrigation.

According to the results, intermittent irrigation from transplanting to 10 days before harvest and then cutting irrigation in rice plant in the study area will have acceptable yield in water deficit conditions and to achieve maximum yield, Toloo cultivar as a suitable genotype is suggested.

Soil improvement using plant roots has been considered by many researchers in order to strengthen soil mass in terms of environmental protection and natural resources.The effect of plant root system on soil resilience is a function of the biotechnical properties of roots But due to the complex interactions between soil and plant, the impact of root reclamation on soils remains a challenge.This study investigates the effect of alfalfa root density on soil consolidation in Pazannan region in Khuzestan province

In this study, for the first time, the effect of alfalfa root system was investigated on soil resilience in greenhouse conditions. Soil samples taken from the study area after a period of 5 months under greenhouse cultivation, 3 rootless soil samples and 12 soil samples with different root densities were tested for direct cutting to measure the shear strength of soil composition and roots And the parameters of internal friction angle and adhesion of root-reinforced soil were obtained and compared with rootless soil samples.

In general, the density and number of roots has been reduced with increasing depth, and also the root density index decreases with the depth increases.Using these results and direct cutting tests   was calculated the amount of armament.The presence of roots has created a significant resistance to soil shear strength, which has been affected by increasing the amount of soil adhesion.In contrast, the internal friction angle of reinforced soil decreases with respect to the rootless soil and has the opposite behavior of the adhesion factor.And its changes are much less than the changes of the adhesion factor.Therefore, it can be known that increasing the shear strength of soil reinforced with alfalfa root is equivalent to increasing adhesion.

The results of this study show that there is a direct relationship between root density index and soil shear strength. The highest and lowest reinforcement rates for 28 and 5% density index were 87.5% and 7.5% increase in soil adhesion, respectively and there has been a maximum reduction in internal friction angle relative to rootless soil of 5.5%. This study showed that there is a decrease in the relationship between depth and root density index, depth and strength of reinforcement as biotechnological characteristics of alfalfa species.

 Wind erosion has occurred in a large part of Iran, which has caused land degradation and reduced fertility along with environmental effects. Identifying erosion-sensitive areas can help natural resource and environmental managers in soil conservation planning.

This study is a step to estimate the erodible component of soil against the wind (EF) from soil accessibility characteristics in Allahabad plain located in the east of Qazvin province. For this purpose, the soil erodibility component, which is closely related to soil erosion versus wind, using multivariate regression (MLR), artificial neural network (ANN), and artificial neural network with genetic algorithm for weight optimization (GA-ANN) were estimated using accessible characteristics. Regarding soil map, soil differences, and environmental characteristics of Allahabad plain, 103 soil samples were collected according to a stratified random pattern of 10 cm of soil surface. In soil samples, some soil properties were measured as inputs of models for estimating erodible soil components against the wind. The inputs of each model included pH, ECe, CCE, SAR, bulk density, sand particles, silt and clay, coarse soil particles with a diameter of more than 2 mm, and organic matter. Accuracy and reliability of the results of the created models were compared with each other according to the criteria of coefficient of determination, square of error, Morgan-Granger-Newbold and Akaike information criterion.

Based on data, the highest correlation between soil erodible fraction to wind erosion (EF) was observed with soil clay content (r = -0.789). Also, soil erodible components showed a correlation with other soil properties including pH, electrical conductivity, SAR, organic matter, and the should be omitted density. This correlation was significant with three properties of SAR, organic matter, and clay at a should be added 1% level. The models created by the three methods were much more capable of predicting EF in the test data series than the training series data. The results also showed that the neural network model had a should be omitted more accuracy and less estimation error compared to hybrid and regression models. The results of sensitivity analysis of the models also showed that the highest sensitivity of the model to input variables in the ANN model, related to organic matter and SAR, respectively, and in the model GA-ANN was related to soil clay content variable.

According to the results, R2 in the regression model of training data was more than 50% in estimating EF, but this value (R2 = 0.56) is not reliable. According to the test data, all three models, including regression, artificial neural network, and its combination with genetic algorithm had not been efficient enough in estimating EF, so that can be omitted the highest R2 in the neural network model in the test data (R2 = 0.43) had an accuracy of less than 50% in estimating the EF, which cannot be an appropriate accuracy in predicting EF.

The process of climate change, especially the change in temperature and precipitation, and its effect on the drought phenomenon constitute the most important topic of discussion in environmental sciences. Studying climate change and its effect on the severity and frequency of droughts in the coming decades can considerably contribute to the planning for the proper use of water resources and adapting to the destructive effects of droughts. To this end, based on the SDSM microscale method, precipitation and temperature during the 2020-2100 period were predicted in the present study using the large-scale CanESM2 model, and the effects of climate change on the meteorological drought in Ilam Province were studied using the SPI and RDI indices.

In this study, the required climatic data are obtained through one of the data reporting sites of the IPCC AR5. Twenty one CMIP5 models have been used to predict Precipitation and temperature parameters in the future. The weighting method of observational means was used to investigate the uncertainty caused by using the studied models. Then, using the SDSM model, meteorological data are generated under three scenarios: RCP 2.6, RCP4.5 and RCP8.5 of the CanESM2 model. Model historical data from 1993 to 2005 will be used to analyze the SDSM model using NCEP re-analysis data, and data from 2006 to 2100 will be used to estimate future climate change. The SPI and RDI time series were calculated in three scales of 3, 6 and 12 months for the historical and future period. The intensity, duration and frequency of the drought, according to the run theory for the spi and RDI on scale 3, 6 and 12 months.

According to the results of the uncertainty analysis, the CanESM2 model had the highest weight compared to other models for both temperature and precipitation variables. Analysis of trend in precipitation and temperature data by non - parametric mann - kendall test showed that temperature in scenario rcp8.5 has a significant positive trend ( increasing ) at 0.01 and precipitation has decreasing trend. The results of drought monitoring showed that in both SPI and RDI indices, the frequency of dry period’s decreases with increasing time scale, which is accompanied by an increase in the severity and duration of drought. The RDI index shows higher drought characteristics than SPI due to considering the average temperature in calculating dry periods. The greatest drought in the historical period according to the SPI index on a 12-month scale has an intensity of 38.22 and a duration of 26 months. RDI index on a 12-month scale has an intensity of 39.14 and a duration of 26 months.The study area will experience more severe and longer droughts in the future according to all three scenarios than in the historical period. The severity of droughts produced by RCP4.5 RCP2.6 and RCP8.5 scenarios based on 12-month SPI is 11%, 52% and 65%.

The results of the analysis with the SDSM model and the SPI and RDI drought indices indicated that in the future climatic conditions in the 2020-2100 period, an increase in temperature and a decrease in precipitation are probable. To wit, temperature rises by 3.798 C and precipitation decreases by 6.8%. The results also revealed that the study area will experience more severe and longer droughts in the future than in the historical period under all three RCP2.6, RCP4.5 and RCP8.5 scenarios. As the time scale of the drought index increases, the severity and duration of the drought increases. The RDI index has a high behavioral similarity to the SPI, but the RDI index is sensitive to environmental changes and provides better results.

One of the most important factors limiting peanut production is water stress and shortage in plant growth stages. Therefore, crop simulation models can be useful for predicting yield and assessing the effect of water stress on plant growth and development. In this study, the WOFOST model was used to simulate biomass yield, seed yield and water use productivity in peanut. As the peanut modeling research has not been well-addressed in Iran, thus, the purpose of this study is to evaluate the ability of WOFOST model to simulate the yield of two peanut cultivars under irrigation conditions at different growth stages in Astaneh Ashrafiyeh region.

This experiment was performed in the form of split plots in a randomized complete block design with three iterations. The main treatment included irrigation until the beginning of flowering time (I1), irrigation until the beginning of pod time (I2) and full irrigation (I3), and the sub-treatment included two cultivars of Jonobi peanut (C1) and Guil (C2). The WOFOST version 7.1.3 model was employed. In this model, crop growth simulation is based on carbon cycle, which models crop growth in three situations: absence of limiting factor, water limitation, and nutrient limitation.

Model evaluation showed that the root mean square between the observed and simulated values in estimating biomass yield for Jonobi and Guil cultivars in 2017 were 0.554 and 0.501%, in 2018 were 0.872 and 0.897%, and in 2019 were 0.449 and 0.466%, respectively. The root of the mean squares between the observed and simulated values in estimating seed yield for Jonobi and Guil cultivars in 2017 were 0.052 and 0.065%, in 2018 were 0.132 and 0.131%, and in 2019 were 0.101 and 0.096%, respectively. The mean values of relative error between the observed and simulated values in 2017, 2018 and 2019 for biomass yield were 10.2, 18.1, and 7.7%, and for seed yield were 4.35, 6.4 and, -4.5%, respectively; also the efficiency coefficient index ranged from 0.442 to 0.960.

Evaluation of simulated and observed values on biomass yield and seed yield demonstrate that RMSE, RMSEn and other statistical indexes were acceptable and the WOFOST model simulated two peanut cultivars accurately in different irrigation treatments.

 Aromatic geranium is an ornamental perennial plant which its essential oil is used in perfumery, cosmetics, food and pharmaceutical industries. Water scarcity is one of the most important environmental stresses limiting plants’ growth and yield, which greatly impacts the morphophysiological, biochemical and enzymatic properties of plants and limits their development and survival. Using organic osmolytes such as proline and glycine-betaine increase the capacity and speed of photosynthesis, absorb ions such as magnesium and potassium, prevent the degradation of pigment-protein compounds, maintain plant pigments, strengthen the antioxidant system, and impact in inhibiting the adverse effects of water scarcity in plants. Thus, the aim of this study is to determine the best substance and effective concentration improving the quality and aromatic geraniums flowering under water scarcity stress.

Aromatic geranium cuttings were kept in commercial greenhouses with a temperature of about 17 to 20 Cᵒ, 60 to 70% relative humidity and light intensity of about 50 to 60 µm/m2S in Karaj city. Feeding with Hoagland solution was done once a week and in order to measure the soil moisture, the potting system was used, and irrigation was carried out based on the soil weight change according to the determined field capacity (FC). Foliar spraying with proline and glycine betaine (0, 50 and, 100 mg/l) was applied for a month after two weeks of placing the cuttings in pots and  24 hours of being at different levels of low scarcity stress (25, 50, 75 and, 100% field capacity), sequently. After completing the treatments, sampling and evaluating of traits such as fresh and dry weight of shoots and roots, petals anthocyanin, total leaf chlorophyll, proline and activity of superoxide dismutase and peroxidase enzymes were performed. The experiment was performed in 2019 as a factorial experiment in a completely randomized statistical design with two factors of applying water scarcity stress and spraying with proline and glycine-betaine and their interaction. Then, data were analyzed using SPSS, the means were compared with Duncan's multiple domain and graphs were drawn in Excel.

Data means comparison showed that the highest fresh and dry weight of shoots with 67.25 and 8.53 g and the highest fresh and dry weight of roots with 15.62 and 3.45 g were observed in 100% FC (control) and the lowest shoot fresh and dry weight with 44.76 and 4.45 g and the lowest fresh and dry weight of roots with 10.57 and 1.17 g, were in 25% FC treatment (without foliar application). Also, the highest and lowest petals anthocyanin with 2.8925 and 1.5775 mg/g FW and total leaf chlorophyll with 15.3735 and 11.1632 mg/g FW were in 100% FC (control) and 25% FC treatment (without foliar application). The highest and lowest proline levels were 3.84 and 1.67 mg/g of FW in 25% FC treatment (without foliar application) and 75% FC treatment + 100 mg/l of proline. The highest activity of superoxide dismutase and peroxidase enzymes with 2.97 and 16.52 UE/g of FW in 75% FC + glycine-betaine 100 mg/l treatment and the lowest with 1.12 and 12.93 UE/g FW in 25% FC treatment (without foliar application), was obtained.

The results demonstrate that the fresh and dry weight of shoots and roots decreased with increasing water scarcity stress, which this reduction was in 25% or more of field capacity and foliar application of plants with glycine betaine and proline inhibited the negative effects of stress at a concentration of 100 mg/l, both combinations were more visible. Petal anthocyanin and total leaf chlorophyll dropped with rising water scarcity stress and, treatment of plants with glycine betaine and proline had an effective role in ameliorating plant pigments. In addition, proline levels are increased by water scarcity stress. The highest enzyme activity was in 75% FC and with increasing water scarcity stress, enzyme activity reduced. Foliar application of plants with glycine betaine and 100 mg/l proline reduced the negative effect of water stress in 50 and 75% FC compared to 25% FC. Hence, according to the research results, the use of organic osmolytes such as glycine betaine and proline can be recommended to decrease the negative effects of water scarcity stress in ornamental plants.