نشریه پژوهش های آبخیزداری
پیاپی 132 (پاییز 1400)

Evaluating the efficiency of water resources monitoring systems and trying to improve the status of various components of these systems, such as modifying the frequency of quantitative variable sampling and relocating stations, is of particular importance. The main reason for the importance of this issue is the significant monthly cost of maintaining these systems; therefore, reducing the redundant and excess information in such systems may have a significant effect on reducing costs without decreasing the value and accuracy of the resulting information. However, if the number of stations is not optimal, the data of sensitive points may be missed. In the discrete entropy theory was used to investigate the accuracy of station information and their density in the region, and to quantitatively evaluate the network of hydrometry stations in the province of Kermanshah. Fourteen stations with a common statistical period of 30 years was evaluated. The results indicate the presence of three critical stations of Doabmarg, Shah Gozar and Hyderabad in the network, which their continued functioning need to be reconsidered. The Pol-e-Chehr, Pirsalman and Ghorbaghistan are the three most important stations in the basin that should remain active in the network, as they have the highest ranking among other stations. Doabmarg Station has the worst condition in the monitoring network and its condition needs to be carefully reviewed and revised. The indexes S (i) R (i) have almost the same values ​​in most stations; each station tries to collect information from other stations as much as it contributes data to other stations.

The aim of this study was to analyze the effectiveness of watershed management activities in a representative  sub-catchment (treated) and its comparison with a control on, and to identify the erosion sensitive areas in these sub-catchments areas of ​​58 hectares (control) and 83 hectares (treated) the using UAV photogrammetry. Based on a curve number and four other basic maps (elevation, slope, drainage direction, and accumulation density), three daily precipitation scenarios of 20, 40, and 60 mm were considered to model the LANDPLANER with two indices of Erosion Index and Topographic Threshold. The results were evaluated using the boxplot methods, foufold plot, and the area under the receiver operating characteristic curve. The Erosion index (IE) in the LANDPLANER model, considering the maximum daily precipitation of 60 mm, was 0.54821 for the control sub-catchment which was more than that of the treated one (0.15593). The modeling based on the topographic Threshold also showed that the numerical changes of the index between 0-2 in the trated sub-catchment were less than that of the control area(0-3). Therefore, it can be said that due to the appropriate protective operations that had taken place on the treated sub-catchment, this area is in a better condition than the control one, as the volume of soil erosion was less than that of the control sub-catchment. It is informative to know that all of the three precipitation scenarios predict less soil erosion in the treated sub-catchment. Therefore, simulation based on the rainfall and curve number scenarios with LANDPLANER physical model is recommended to evalute the effect of watershed management activities on the paired sub- catchments that are degraded due to soil erosion.

The materials added to the water from fish farms affect the water quality, as these are decomposed in the environment and may reduce the quality of the water so that it is not suitable for further use. Therefore, it is necessary to measure how water quality changes. The impact of the fish farms on the water in the Joobkhalleh River was investigated. Five sampling stations were selected before flowing into the farm, the outlet, and in 5, 8, and 10km after the farm, to be sampled 6 times in 2-month intervals in the spring 2015-winter 2015 period. DO (annual mean 9.0 mg/L), T (14.5˚C), pH (8.4), TDS (462mg/L), COD (8.1mg/L), [PO4]- (0.2mg/L), and [NO3] (1.3mg/L) did not show significant changes, while oxygen saturation, BOD (1.4mg/L), EC (711µS/cm), TSS (6.0mg/L), [NO2] (0.01mg/L), and [NH3] (0.13mg/L) differed significantly among the stations. Regression analysis proved a significant correlation between the increase with distance from the source for [NO2] (Pearson Correlation= 0.915), TDS (0.878), and EC (0.878). Comparison of the findings with water use criteria shows that most parameters were in the suitable range for aquaculture, except for the TDS, which was far out of the standard, and the ammonia which was slightly higher. Considering the effect of pH, these values for the annual average of ammonia and nitrite are considered toxic for fish farming. In conclusion, the annual average of ammonia and nitrite is toxic at the last point for fish farming due to the water pH; therefore, it is not appropriate to use the water for aquaculture development.

Water resources management is essential in countries, such as Iran, with arid and semi-arid climates due to global climate change and population growth. Knowledge of hydrogeological droughts and effective factors on groundwater drawdown is essential in providing management solutions for these vital resources. Therefore, the purpose of this study was to analyze the trend of groundwater variations and assessment of groundwater shortage in the Karkheh Watershed using the SPEI, SDI and GRI drought indices in an eleven -year statistical period (2006-2017). The results indicated that in most of the study areas, there was a correlation between the SPEI and SDI indices. The mean values of the GRI index in the study area of Karkheh watershed area show weak drought for the Sanghar, Nahavand, Sahneh, Hersam, Khorramabad, Tuyserkan, Asadabad, Malayer, Biston-Dinavar, Mian Rahan and Hassanabad-Qala-e-Shian areas. A more severe drought with the drought indices of -1.08, -1.13, -1.21, -1.23, -1.25, -1.31 and -1.35 was determined for Chaghloundi, Kuhdasht, Kangavar, Islamabad Gharb, Ravansar-Sanjabi, Kermanshah and Mahidasht respectively. These indicates a decrease in the water level elevation and an increase in the depth to the groundwater in these areas. The GRI drought index is more visible during the ten-year statistical period in the east, west and center of the Karkheh Catchment Area; while in the last years of this period, the central areas of the catchment had been affected by more severe droughts, which may be confirmed by the SPI zoning map. Although in most cases climatic drought, and consequently hydrological drought had caused the depletion of groundwater level in the basin, the results of comparison between the two types of drought indicated the effectiveness of other factors such as exploitation of the groundwater resources. Therefore, it is necessary to establish an integrated management for the sustainability of groundwater resources, especially in the agricultural sector, as well as reforming the management of traditional groundwater abstraction systems, before meteorological droughts and subsequent surface water shortages affect groundwater levels.

Land degradation is a multifaceted phenomenon, which is caused by various variables, including climate, land use changes and socio-human activities. In order to investigate the effects of climatic parameters on land degradation in five second degree watersheds (South Baluchistan, Bandar Abbas - Sedij, Kal - Mehran, Hillah and Mond) located in the entire Persian Gulf and Oman Sea Watershed, observational data E32 of synoptic stations were used in the mentioned catchment areas for of 31- year period (1988-2019). The IDW algorithm was used to map the climatic parameters. The results of the change detection showed that the trend of temperature class changes of 25– 27.5 follows an increasing rate of 19.03%, and the precipitation class is less than 150 mm in the region. The region is also facing an increasing trend of 17.3%. The trend of the evaporation parameter is such that the 2500-2750 and 300-3250 mm classes with the changes of -5.4, 8.3 percent, respectively, have the most decreasing and increasing effects. Moreover, the wind speed classes of less than 2 and 3-4 meters per second with changes of 5.7 and -7.5 percent show the highest increase and decrease respectively, based on the findings of the regression model, there is a significant relationship at the 0.05% level between the climatic variables (precipitation, temperature, evaporation and wind speed) on one hands and the vegetation index and salinity and the precipitation parameter on the others show the greatest effect. Considering that the four mentioned climatic variables explain 47.6% and 40.5% of the changes in the dependent variable of vegetation index and salinity, respectively, it can be concluded that part of the changes in vegetation and salinity are due to the conditions. As the climate prevails in the region, the poor vegetation and salinity were constantly fluctuating during the study period; consequently, the process of degradation followed an increasing and decreasing rate. Therefore, being aware of the effects of climatic parameters on the fluctuation of vegetation and salinity indices in a long period of 31 years, it is possible to make the necessary predictions for the optimal management of natural resources, especially during droughts. This enables the concerned authorities to control the development stages of land degradation in the coastal catchment areas of ​​the Persian Gulf and the Sea of ​​Oman.

The aim of current study was to study the trend of linear and non-linear changes in vegetation cover under the influences of climatic factors (rainfall, temperature and drought) and human activity (biological watershed management measures) using satellite images over a period of 20 years (2000-2019) on the Khor-Sefidarak Watershed, the Province of Alborz. Vegetation index (NDVI), drought index (SPI) and PolyTrend algorithm were used by extracting the monthly time series. Then, using climatic and implemented watershed management measures data for the basin, the impact of natural (temperature, precipitation and drought) and human factors on vegetation changes was assessed. The results indicated that 35% of the area had significant changes (92.6% increasing and 7.4% decreasing) in vegetation, and 65% of the area had insignificant changes during the last 20 years. The results also indicated that 87.71% of the vegetation changes in the region had experienced a linear type change and the remaining 6.62 and 5.68% haddemonstrated second and third degree nonlinear changes, respectively. Considering the effects of the two climatic variables on vegetation, precipitation did not show a significant trend over the two decades; however the temperature indicated a significant decreasing trend. Assessing the impact of drought on vegetation change, the largest decline in vegetative cover occurred in 2008, which was strongly influenced by severe climatic drought. Although the vegetation changes have not been affected by climatic factors in the long term, short-term changes in extreme events, including drought, strongly justify changes in the region's vegetation. On the other hand, the results indicated that the watershed management measures have caused changes with a linear pattern; however, the changes and expansion of the residential areas (as human factors) have caused a nonlinear pattern in vegetation. Thus the biological watershed management measures have increased and strengthened the vegetation of the region linearly; however, sudden and rapid changes in the rural areas have caused a non-linear decrease in vegetation.

An optimized land management and the planning requires updating information on the land use changes over time. The application of remote sensing capabilities and land use change modeler (LCM) may provide a suitable platform for simulating land use changes. The LCM, land use changes in the upstream area of the Siahrud River Basin were evaluated in the 1977-2015 period and simulated for 2030. The land use maps of 1977, 1988, 1998, 2009 and 2015 were prepared, using the unsupervised and supervised classification methods of the Landsat satellite images, and the LCM, for the 1977-1988, 1988-1998 and 1998-2009 periods were implemented in the form of three models. After evaluation the performance of these models, the most appropriate one was selected. Using the data for the 2009-2015 periods a prediction was made for the year 2030. The results indicate that the use of appropriate inputs for the LCM, the application of the combined methods in classification, and utilizing expert knowledge, can be effective in improving the classification results and increasing the efficiency of the LCM. (Kappa coefficient 0.82 to 0.91). Predicting land use changes in the Siahroud River Basin during the 1977 to 2030 period indicates a 67% decrease in paddy fields and 12% decrease in forest area and a 34-fold increase in the extent of the mixed agricultural and orchards, and threefold increase in the extent of the residential areas.

An increasing trend of natural resources degradation threatens human life dramatically. Desertification process is the main sign of land degradation. The principal aim of this research was an assessment of potential hazard of desertification using the MEDALUS model in the study of Golsara Torbat Heydarieh area in the province of Khorasan Razavi. The MEDALUS model was evaluated based on 5 key factors, namely: soil quality, climate quality, vegetation quality, management quality and trend of desertification (suggested factors). The quality of each factor was evaluated using the geometric mean of its indices. The desertification intensity map was prepared based on the geometric mean of all 5 key factors. In the Golsara region, 3 fragile classes (F1, F2, F3) and 1 potential class (P) and 1 non affected class (N) were evaluated. The MEDALUS model was modified by of adding a trend factor in which 3 other steps were revised. 1. After preparation the desertification intensity map based on the MEDALUS model, a new map of desertification intensity of the study area was prepared based on 4 classes of low to very severe situations showing 66% of the study area was under a moderate potential of desertification. 2. By upgrading the map of current productivity to potential productivity the current state of desertification that wasn’t considered in the MEDALUS model was run showing 60% of the study area was under a severe state of desertification. 3. Based on the map of current productivity to potential productivity, a new classification involving two main classes of potential risk and actual risk were defined for the desertification intensity map of revised the MEDALUS model. According to the final revised map of desertification in the Golsara region, 93.4% of the area was classified as the main class of actual risk and 6.6% as the main class of potential risk. These results point to the inefficiency of the current the MEDALUS model in the study area without considering the current degradation status parameter; therefore, we recommend the use of the modified model.

Desertification, a manifest sign of land degradation is mostly due to unreasonable treatment, and in many cases, over-exploitation of natural resources, mainly soil, and water. Therefore, the purpose of this study was to identify and introduce the degree of impact of human activities from the perspective of water and land management in the desertification of the Sarvestan Sub-basin. Quantitative and qualitative changes in groundwater, detection of changes in farm field expanses, and the current state of water criteria (indicators: groundwater loss, EC, irrigation systems, SAR), and agricultural criteria (indicators: yield, cultivation pattern, use of inputs and machinery) using the Iranian model, the IMDPA. The water resources of the Sarvestan Sub-basin have decreased in quality (an increase of 2700 µS/m of salinity during the preceding 21 years) and quantity (subsidence of 10 meters of water level in 25 years). The cultivated area has expanded 196% from 1993 to 2016. An application of the IMDPA model indicates that the electrical conductivity index, with a numerical value of 3.4, had the highest effect (extreme condition), and application index of agricultural inputs and machinery with a numerical value of 1.7 had the lowest effect (moderate condition) in the Sarvestan Sub-basin. The water quantity with a numerical value of 2.56 was the dominant criterion, and along with the agriculture criterion, was placed in the moderate class.

Wind erosion and dust generation is a great challenge worldwide, especially in Iran. Identification of the dust source is the first step in mitigating this occurrence. There are various approaches to detect wind erosion and dust sources including remote sensing, physical and chemical analyses, experimental models. The purpose of this study was to use the US Environmental Protection Agency (USEPA) model to identify sources of dust in the Semnan Municipality. Samples were collected randomly from 50 study points in the Municipality of Semnan (2018), and physical and chemical experiments were performed on the samples. Climate indicators, namely: rainfall, evapotranspiration and wind speed, temperature, and relative humidity for a period of 9 years were also been collected from the Meteorological Organization of Iran. The dust emission rates of Q, Q30, and Q50 were measured separately using climatic parameters and physical characteristics of the soils in different models. Geostatistic and interpolation techniques, including RBF and IDW, were also used to plot the map of climatic parameters, texture, and dust emission rates. According to the statistical tests, only the values of silt, Q30 and Q50 were normal; therefore, an interpolation of these indicators was performed using the geostatistical methods. The critical and supercritical points of sources of dust were then determined after the maps were combined. The findings indicated that the study area was super-critical in drought (19.02), rainfall (177.96 mm), and region topography (plain) indicators, and in a critical condition for soil texture with an average of more than 50 percent sand and less than 30 percent silt. The dust emission rate (Q) ranged from 9-55 kg/ha.y pointed into the warning condition for, the regional average of dusty days (2 days/y). However, the days with a wind speed of 1.98 m/s were considered as a normal condition. In a nutshell, the results indicated that the study area was not a dust source, despite the critical and supercritical conditions for some of the indicators.