نشریه پژوهش های آبخیزداری
پیاپی 124 (پاییز 1398)

Groundwater vulnerability is due to the inherent vulnerability and characteristics of the occurrence of contaminating sources and human-induced pollution. Sixty four quality measuring wells, 20 observation wells and more than 28000 operating wells were sampled in order to provide vulnerability maps for 2004 and 2014. The essential factors of the inherent vulnerability included hydraulic conductivity, aquifer type, distance from the coast, and aquifer thickness. Additional factors of specific vulnerability including well density, decline of groundwater level, relative impact of seawater intrusion, condition of saltwater up-coning and hydraulic gradient were also used. The results indicated that the quality of groundwater resources had declined from 2004 to 2014 according to salinity criteria such as electrical indicated by an increase in conductivity (EC), sodium absorption ratio (SAR) and total dissolved solids (TDS). The land use factor was also used to prepare modified vulnerability maps for the year through 2004-2014. The results indicated that while the irrigated area had decreased by 8 percent during this period, the level in high-vulnerability areas had increased, which may be surmised that an increase discharge rate and double-cropping had caused degradation of the groundwater. The results showed that the mean correlation coefficient of vulnerability to salinity classes with salinity criteria such as EC, TDS and SAR had improved in 2004 from 0.65 to 0.9, and in 2014 from 0.78 to 0.87. Duo to the complexity of qualitative modeling, solute transport and groundwater salinity, the modified vulnerability maps is a good tool to predict the impending groundwater salinization.

Hydrological drought can lead to a decrease in river flow and loss of the river ecosystem quality, which limits human use of the surface water. The stream flow drought index (SDI) has been used to assess the hydrological droughts in 33 hydrometric stations of the Province of Ardabil. The SDI was calculated using the DrinC software; subsequently, characteristics of the hydrological drought were classified and analyzed. The inter-relationship of the different components of hydrological drought with those of the flow rate were also examined. Subsequently, some of the hydrological drought characteristics were interpolated to detect the spatial variations. The results indicated that all of the studied stations experienced drought events. The maximum dry-period was 62 months at the Samian Station. The results of the standard classification of the SDI in 14 stations (Aladizge, Pole-Almas, Anbaran, Baroogh, Boran, Dostbeyglu, Gilandeh, Iril, Koozetopraghi, Mashiran, Neour, Samian, Shamsabad and Sola) indicated that the number of wet-months were larger than that of the dry-months. The severest drought was observed at the Pole-Almas Station (-1.05), while the highest frequency of wet-months had been recorded at the same station. The average intensity of the highest and lowest hydrological drought events at the Pole-Almas and Anbaran Stations were -1.05 and -0.57, respectively. The spatial variations of drought occurrence showed that the stations located in the upstream areas and the Sabalan piedmonts had the lowest drought occurrence in the study area. The severe and severest drought events had been occurred in small rivers with low discharge.

Landslide is one of the most important agents of soil erosion and occurrence of natural disasters that causes annualy damage in Iran. Morphotectonic indices and landslide hazard zonation models have been increasingly used in the study of slope instability. The purpose of this study was to assess the zoning of landslide hazard at the Chergh Veis Dam Watershed of Kurdestan using the IRAT (LNRF) model and comparative comparisons of them using the cross-sectional table technique and landslide hazard zonation assessment indicators. The results of the IRAT evaluation indicate that 77.77% of the landslides are in the tectonic category; however, using the LNRF model, 64.05% occur in areas with a very high potential that is consistent with the sub-basins with the highest number and large slip density. Moreover, more than 91.64% of the total area of landslides occur in high risk areas and within less than 1000 meters of each other. An analysis of the cross-sectional tables indicate that both zoning models occur in the middle class risk assessment with an acceptable compliance, but on the high risk side duo to the faults' alignment with landslides, the IRAT model is more accurate. The total quality indicators as the LNRF model, 2.16 % indicates that the model performance is better for zoning the landslide risk in the catchment area of the Kesht-e-Wis Dam. It is suggested that any land use change and planning to exploit the landform of the dam watershed be in accordance with the land risk mapping guidelines.

A lack of sustained enthusiasm for participation in watershed management by the rural communities constitute a deterrent for rehabilitation of our drastically disturbed watersheds. Therefore, it is necessary to find the reasons if the concerned authorities to encourage them to share the burden of conservation activities on the catchments they live on, or benefit from. To this end in this research was done the priority of the factors affecting the preventing sustainable participation of rural societies in watershed management projects from experts' viewpoints in Moradabad watershed of Meymand, in southwest of Fars province. The method of preparing and completing 57 questionnaires was analyzed by T test, Analytical Hierarchy Process and Friedman nonparametric test. The results showed that from the viewpoint of experts in the Moradabad watershed of Fars province, the "economic", "educational-extension", "design-executive" and "social" indicators, respectively, have the maximum and minimum priority of non-participation sustainable rural communities are in watershed management projects. Also, the most important sub-indicators on the lack of sustainable rural societies participation in the watershed management projects in this watershed are: "low income residents of the basin", "ignoring income for the people as a direct incentive to implement plans Watershed management", "lack of training residents of the basin regarding the plans and objectives" and "low level of literacy and awareness". The range of average ratings varies from 4.85 to 8.25, so that the sub-indicator "low income residents of the watershed" with an average rating of 8.25 has the highest relative priority and "late return of watershed projects" with an average of 4.85 had the least relative priority in the lack of sustainable participation of rural societies in the watershed management plans in this watershed. This results could be used by the watershed projects planners for achieving the optimum results. It is suggested that the "activities of NGOs" and "training of exploiters", along with factors such as "implementation of multipurpose projects", taking in to account the interests of watershed dwellers in order to improve the economic conditions, to create the basis for trust and should be taken attract to active participation in the watershed management projects.

Because of incomplete model input and imperfections of the model structure there is not any single hydrological model that has the best performance in different conditions and present outputs without uncertainty. In this situation by combining individual models outputs, the strengths of each single model are used to make a new model that performs better than each single model. In this study the efficiency of nonparametric K nearest neighbor and the Fuzzy C-Means clustering based methods were compared with BGA (Bates Granger Averaging), GRA (Granger Ramanathan Averaging), AICA (Akaike Information Criterion), BICA(Bayes Information Criterion), equal weights averaging and lasso methods in averaging output of hydrological models GR5J, SimHyd , SACRAMENTO and SMAR. Firstly, using the amount of rainfall, evapotranspiration, temperature, and the daily discharge of the Kasilian Watershed in Pol Sefid city at the Bon Koh Station was simulated by each hydrological model. Then different model averaging methods were used to combine the output of each single model. Results indicated that for the calibration period, the GR5J and SACRAMENTO, and the correlation coefficient, Nash Sutcliffe efficiency and RMSE were 0.83, 0.69 and 0.24 respectively. The models SimHyd and GR5J performed better for the validation period; the correlation coefficient, Nash Sutcliffe efficiency and RMSE were 0.73, 0.27 and 0.52 respectively. The lasso and GRA model averaging had the best performance for the calibration period and for the validation data equal weights averaging and BGA had the best performance. For calibration data K nearest neighbor performed better than fuzzy K means clustering based method and the best performance for two methods was obtained at 20 neighbors and for validation data fuzzy K means clustering based method performed better and it observed model performance was improved as the number of neighbors was increased.

It is a matter of utmost importance to estimate accurately watersheds’ surface runoff in order to manage a region's water resources. Due to the inadequacy and lack of surface runoff monitoring in some watersheds, as well as high error and relatively high data demand of daily runoff estimation methods, it is necessary to rely on the monthly runoff estimation methods. Different scenarios of combining monthly surface runoff estimation methods (monthly SCS method, SCS-based runoff coefficient, integrated curve number (CN), and runoff coefficient method) with three methods of calculating monthly curve number (based on leaf area index, on retention potential, and on average CN-based reference tables) as input parameters for the surface runoff estimation methods. These estimations were applied and compared across the Araz-Kouseh Watershed in the east of the Province of Golestan. Results indicated that the monthly SCS method in combination with all methods of monthly CN has appropriately simulated the surface runoff with the Nash-Sutcliffe (NS) coefficient and bias values of higher than 0.6 and lower than 0.3, respectively. While the SCS-based runoff coefficient method performed poorly (with negative NS values and bias values above 4), particularly in combination with the average CN estimation based on reference table. The integrated method of curve number and runoff coefficient in combination with all methods of monthly CN estimation indicated relatively acceptable results (with the NS values of about 0.6) during calibration period; however, for the validation period, the results in combination with some monthly CN calculation methods was less reliable. Therefore, the monthly SCS method was selected as a suitable and robust method for the monthly surface runoff simulation of the Araz-Kouseh Watershed; thus it may be recommended for estimation of the water balance in similar watersheds in the region.

A multi-objective linear optimization model has been formulated, which is used for water and crop area allocation in two irrigation and drainage networks of Dorudzan and Karbal, including five farming regions. The developed model is based on four bankruptcy rules of proportional cutback (PC), constrained equal awards (CEL), constrained equal losses (CEL), and adjusted proportional (APR) in terms of the certainty and uncertainty in the water availability. The developed model has four objective functions to reflect the various agricultural and environmental consumptions and is solved for two dry and non-dry conditions using a fuzzy compromise approach. The outputs of the model showed that the regions with higher shares of water receives the most allocated water through the bankruptcy rules of the PC and CEL in dry and non-dry condition, respectively. On the other hand, the most allocated water for the regions with lower shares of water occurs through the bankruptcy rule of the CEA in both hydro climatic conditions. The outcome of the stability evaluation using the bankruptcy stability index (BASI) indicated that this criterion could not be used to evaluate stability under all bankruptcy situations; thus, one should take the necessary precaution for making a decision according to its output