مجله تحقیقات آب و خاک ایران
سال پنجاه و چهارم شماره 5 (پیاپی 89، امرداد 1402)

In the present study, the potential map of groundwater springs was prepared using the famous and efficient Maxent model as a benchmark in Namroud catchment, Tehran province. In this study, the effect of three different scenarios on the number of presence points (100,500,800 springs), raster resolution (100,50,30) and sample size (10/90, 20/80, 30/70, 50/50) on the predicted map was evaluated. First, 18 factors affecting the emergence of springs including lithological formations, the distance from the fault, fault density, elevation classes, slope percentage, slope direction, slope length factor, curvature maps, the distance from the waterway, waterway density, the distance from the road, topographic moisture index, relative slope position, flow power index, soil texture, surface roughness index and land use cover were selected and their maps were prepared in the ArcGIS10.5 and SAGA systems. After the correlation test and classification of the effective layers, the percentage and frequency of groundwater potential in each class were obtained using the frequency ratio method, which calculates the exact weight of each class. The relative operating characteristic curve (ROC) was used to evaluate the performance of these models. The results showed that the combination of raster resolution scenarios: 30-number of points: 100-sample size: 90/20 with the highest AUC (0.953 in training phase and 0.927 in validation phase) has goodness-of-fit and prediction accuracy compared to the combinations of other scenarios. In addition, about 9.14% of the study area had high and very high potential for groundwater. Based on the combination of the best scenario, the factors of distance from the waterway, relative slope position, drainage density and topographic moisture index with values of 17.3, 14.2, 13.8 and 10.2%, respectively, are the main factors of spatial control in the study area influencing the spring occurrence.

Evaluating the monitoring network and determining the main criteria in the stations is an effective step in improving the efficiency of the monitoring and measurement network. Consecutive assessment, pathology and optimization in long-term monitoring; Leads to proper management of output data, system efficiency and reduces costs. Of course, limiting factors such as: growing needs, limited resources, the consequences of unsustainable development and occasional human interference in the water cycle, etc., cause concern in meeting the water needs of human society. In this study, the evaluation of the quality monitoring network of the country's rivers was evaluated using a multi-criteria decision-making method and by selecting four main criteria. In management and technical criteria in water monitoring stations, data quality control and assurance sub-criteria, in social criteria sub-criteria of water quality parameters, in economic criteria sub-criteria of pollution detection and in environmental criteria sub-criteria of network optimization at a specific time and place have the most weight. Also, a comparative comparison of Iran's monitoring network with the monitoring network of selected countries was performed using Spearman correlation coefficient method. The Iranian monitoring network is most consistent with the Thai monitoring network with a coefficient of 0.9. One of the most important priorities of the US Monitoring Network is to optimize monitoring at specific times and places. Japan's monitoring network focuses more on regional monitoring than grade 1 rivers.

A significant course of action to planning agricultural operations and further maintaining and developing performance on a regional scale involves the accurate and timely estimation of crop yield prior to harvesting using crop growth models. Modeling dynamic changes during crop growth can assist researchers in planning crop management strategies aimed at increasing crop yield. Such models include several parameters that can be calibrated according to the characteristics of the study area. However, insufficent information on location/spatial-wise components or the lack of  thereof in these models along with uncertainties in parameter values may lead to errors in the estimated outputs. In this light, remote sensing data assimilation can be useful for resolving such complications and evaluating the spatial variability of lands, particularly at the regional scale. Remote sensing can estimate values of input parameters for crop growth models such as Leaf Area Index (LAI), fCover, biomass, and soil characteristics. This review paper seeks to introduce and compare different methods of remote sensing data assimilation in crop growth models and examine their advantages and disadvantages. In addition, a literature review conducted in this field can guide the readers in slecting the appropriate crop growth model, relevant remote sensing data assimilation method, and pertinent state/control variables. The literature review indicates that with new sensors and methods in the estimation of remote sensing state/control variables such as LAI and the development and improvement of crop growth models, it is possible to improve the accuracy of crop yield estimation.

Irrigation performance assessments under actual operation conditions are required as a first step toward improving agricultural water management. In this study, the seasonal irrigation performance of peaches and nectarines was evaluated under actual operation conditions by monitoring 24 orchards, in Ardabil Province (Parsabad and Meshginshahr counties), Iran, during the growing season 2018-2019. The total sum of seasonal applied water and effective precipitation (I + Pe) and the fruit yield ranged from 280-1675 mm and 1.00-32.43 ton ha-1 (with a weighted average of 582 mm and 14.61 ton ha-1), respectively. The mean Relative Irrigation Supply index (RIS) for the drip irrigation method (1.25) was significantly (P < 0.05) lower than the surface irrigation method (1.66). The water productivity indicators were significantly (P < 0.05) affected by the orchardist's skill level, interplantion of trees, tree spacing, irrigation method, and disease/frost (DF) damage. Post-harvest period accounted for a mean proportion of 75, 25, and 15% of the seasonal applied water in orchards with early-season, late-season, and mixed early- and late-season cultivars, respectively. DF damage accounted for an 87 and 85% reduction in fruit yield and water productivity (WPI+Pe), respectively, compared to the orchards without severe DF damage. Under the current technological and economic constraints, most of the study orchards experienced a rational (but yet with low productivity) irrigation water management. Improving irrigation efficiency and fruit yield, controlling DF damage, and implementing regulated deficit irrigation during pre- and post-harvest stages are the most effective approaches to improve water productivity indicators in the study area.

The purpose of the research is to evaluate the global gridded products database for two variables of actual (ETa) and potential evapotranspiration (ETp) across Iran's sub-basins. For this purpose, the daily meteorological data were collected from 100 synoptic stations around the Iran during 1987-2019. The six products including TERRA, CRU, ERA5, GLEAM, GLDAS and MERRA with 0.5×0.5 spatial resolution were compared to ETa and ETp in 30 sub basins. To assess the performance of six popular ET products, across Iran's sub basins on monthly scale, the Mean Bias Error (MBE), Pearson correlation coefficient (R) and Normalized Root Mean Square Error (NRMSE), of each product were calculated at the basin scale. The results show that more accuracy of products in ETp in comparison with ETa especially in July, August and September months. The more underestimate of ETa was accrued in hyper arid sub basins (e.g. Baluchistan with MBE equal to -34 mm per month). While, the more underestimate of ETp products were achieved in humid basins e.g. Haraz sub basin with MBE= -13 mm per month. The high underestimate of ETp were calculated to GLEAM product in June, July and August with -100 mm month-1. The high correlation between ETa observed and reanalysis are belonging to TERRA and ERA5 in Winter and Spring-Summer period, respectively. Based on NRMSE, results indicated that more accuracy of ETp comparison with ETa products with 0.19 (Excellent and Good) and 0.89 (poorly weak), respectively.

The effect of obtained bagasse and filter cake from sugarcane industry with some chemical fertilizers at the same time as soil preparation and two stages of irrigation, on some characteristics of sugarcane was investigated as a factorial experiment in a randomized complete block design in 2021 in a field of 19 hectares located in Debel Khazei agro-industry company in Khuzestan province, Iran. The factors were consisted of organic amendments (no organic amendments, bagasse, filter cake, and bagasse+filter cake), urea fertilizer (with and without urea application), and triple superphosphate fertilizer (75% and 100% of the recommended amount).The factors were consisted of organic amendments (no organic amendments, 50 tons per hectare of bagasse, 50 tons per hectare of filter cake, and 50 tons per hectare of equal amounts of both bagasse and filter cake), urea fertilizer (with 150 kg per hectare and without urea application), and triple superphosphate fertilizer (75% (187.5 kg/ha) and 100% of the recommended amount (250 kg/ha).The results showed that the combined effect of organic amendment and urea fertilizer was significant on the number of buds, number of tillers, and stem weight. The maximum value of each trait was measured by the application of filter cake and urea fertilizer by 671292 buds per hectare, 757542 tillers per hectare, and 857.55 g of individual stem weight, which were 60, 78.4 and 41.35% higher than the non-application of organic amendment and urea fertilizer, respectively. The application of urea with bagasse resulted in a 7.35% increase in the number of stems compared to the control. The application of filter cake, the combination of bagasse + filter cake and bagasse with urea increased the yield by 54, 31.2 and 13.3 percent, respectively, compared to the control. The obtained yield was equal to 135.1, 120.1 and 99.4 tons per hectare, respectively. The application of filter cake with urea led to a 21.8% increase in juice percentage compared to the non-use of organic amendment and the normal level of fertilizer application (450 kg/ha during the growing season). Using 100% of the recommended dosage of phosphate fertilizer in the presence of urea increased juice percentage by 7.9% compared to the non-use of urea and the same amount of phosphate. Based on the effect of filter cake and bagasse and their application method on sugarcane's growth and yield characteristics, their use is recommended using the present research method.

An important and significant issue in applied research for the management of watersheds is to know integrated drainage sediment yield process to recognize hill slopes and fluvial system. In erosion and sediment study, investigation of form and land form evolution was the earth science study core in the long time. So determination of landform contribution in sediment and erosion yield can utilize for erosion and sediment process in watershed. In recently two decades, sediment fingerprinting method was proven as a key method for contribution of sediment proportion. The purpose of this study was to determine the geomorphic landforms in sediment yield in Chehel-Chaye catchment in Golestan province. By using Topography Position Index, four landforms including concave and convex slope, narrow valleys and slope between concave and convex slope were recognized. In eight flood events suspended sediment sampling was done in March to April 2020. By using XRF instrument, 23 geochemical traces was analysis. After bracket, kruskal-wallis and discernment function analysis, Ba، Ni،Pb، V، Mgo، Mno and Cao had the most discernment percentage in all of tracers. Based of Bayesian mixing model, in first concave slopes 60/9 and in second 28/5 percentage of sediment yield. Result of virtual sediment modeling show that root mean squared error are in 0.6 and 8/4 and mean absolute error 1/7 and 23 evaluated.

Runoff is one of the most important hydrological processes in ecosystems, which is very important in the management of water and soil resources. Although the use of soil microorganisms as soil inoculants in the bioengineering management of runoff has been confirmed, the use of soil microorganisms to control runoff in soils contaminated with petroleum has not been considered. Therefore, in order to evaluate inoculation of soil Bacteria, Cyanobacteria and fungi in reducing runoff in soil contaminated with petroleum, the present study was carried at plots of 0.5×0.5 m with slope of some 25% and level of 20000 mg kg-1 of gasoil and control contamination in three replicates. The plots will be then subjected to rainfall intensity of some 35 mm h−1 and duration of 30 min installed at the Rainfall Simulation Laboratory of Tarbiat Modares University at Faculty of Natural Resources. The results showed that the inoculation treatments, although there was no significant difference compared to the control treatment (P>0.05) except for the start of runoff (P<0.05), improved the components of runoff. The comparison of the mean of the study variables showed that the bacteria, cyanobacteria, fungi, bacteria+fungi, bacteria+cyanobacteria, cyanobacteria+fungi, and bacteria+cyanobacteria+fungi caused +47.10, -0.08, -10.72, -24.86, +14.85, +49.88 and +27.88 percent changes in runoff start time, +4.58, -54.04, +65.19, +72.20, -41.36, -84. 53 and +40.15 percent changes in runoff volume, and +4.75, +54.06 and -65.15, +72.28, -41.39 and -84.55 and +40.20 percent changes in runoff coefficient, respectively. The results of the research indicated the relative synergistic performance of the combination treatment of cyanobacteria + fungi in reducing the effect of gasoil on runoff properties. Finally, the results of the present study showed that the inoculation of native soil bacteria, cyanobacteria, and fungi can be an efficient and sustainable biological technology to improve runoff characteristics in areas contaminated with petroleum.