نشریه پژوهش های آبخیزداری
پیاپی 126 (بهار 1399)

The aim of this study was to model the landslide susceptibility using the Random Forest Machine learning technique and prioritization of effective factors on landslide occurrence in the watershed of the Rais-Ali Delvari Reservoir. The landslide inventory map was prepared using extensive field surveys and the Iranian Landslides Working Party Data Bank. Of the total of 279 identified landslide locations, 70% were used for the modelling processes and the remaining (30%) were applied for validation of the developed model. Different thematic layers including elevation, slope angle, plan curvature, profile curvature, topographic wetness index (TWI), distance from rivers, drainage density, distance from faults, distance from roads, lithological units, and the normalized difference vegetation index (NDVI) were selected. According to the relationship between the dependent (landslides) and the independent (effective factors) variables in the R statistical software, the random forest algorithm was run using the “Random Forest” package, and a landslide susceptibility map was prepared. Accuracy of the model was tested using the receiver operating characteristic (ROC) curve based on 30% of unused landslides in the modelling process. Accuracy results indicated that the Random Forest model with an AUC value of 0.983 had an excellent precision. Also, prioritization of the effective factors showed that the slope angle, elevation, plan curvature, distance from road, and lithological units had the highest effect on landslide occurrence. Therefore, it maybe suggested that the prepared landslide susceptibility map could be effective in decision making for land use planning, and in the managing of the Rais-Ali Delvari Reservoir Watershed.

Droughts are intrinsically regional. The critical conditions in the dry periods occur when there is a severe shortage of water resources for a long period on a wide area. Therefore, an investigation of the regional and not of a local drought offers better understanding of this phenomenon. This study aims at a regional analysis of the hydrological drought in East Azarbaijan Province for a period of 45 years (1972– 2017) using the data collected at 25 hydrometric stations with proper spatial distribution across the province. Homogeneous hydrological areas was identified based on hierarchical analysis method in the SPSS software using the following independent variables: Area, Perimeter, Length of the main basin, Main channel gradient, Drainage density, Basin shape factor, Total hydrographic network, Weighted average slope of the basin, Maximum, Minimum and Median height of the basin, and its length. Frequency analysis and probability distribution of the dependent variables (duration and intensity of hydrological drought spells) was performed on the basis of the two year return period for each hydrometric station. The factor analysis was performed using the PCA method in the SPSS software. The suitability of the data for the factor analysis was evaluated using the KMO coefficient. The value of this coefficient was estimated as 0.546, which indicates that the data were suitable for factor analysis. The result of factor analysis showed that the contribution of perimeter, height and shape of the basin were 40.13, 26.42 and 13.12% (Sum 79.68 % ) respectively in explaining the variance of the variables (i.e. the most important factors in zoning). Results of regional analysis using multivariable regression (stepwise method) indicated that perimeter, avrage height and the basin shape coefficient have a decisive role in estimating the drought severity and its duration with two-year return period in East Azarbijan. In the scarcity of hydrometric stations in most of the watersheds of the East Azarbaijan province, the regional equation presented in this study can be used to estimate hydrological drought characteristics of watersheds without observed surface runoff data.

Erosion is one of the major causes of waste of water and soil. Perhaps the main reason for failure to control erosion is the weakness of knowledge and recognition of this phenomenon. Due to the great value of soil and the subsequent problems arising from the movement of its constituents, the erosion problem must be understood and controlled. Therefore, one needs to determine the susceptibility of geologic formations to erosion, in order to determine its mitigation. This research has been carried out in order to investigate the erodibility potential of the Khanghah-Sorkh (Urmia) watershed using the BSTF rainfall simulator. The simulation was performed at two intensities of 40 and 50 mm/hr on two slopes of 0-13 and 13-25% on each geologic formation. The results showed that the highest and lowest sediments were collected from OML</sup> (the calcic-reefy of Qom) (107.4 g) and the CM Formation (tectonic mix) (4 g). Thus, the OML</sup> formation which contains marl layers, is more susceptible to erosion and produce a larger amount of sediment relative to that of the CM formation which highly resistant to erosion. Therefore, it yields a larger amount of sediment.

Drought prediction plays an important role in the planning and management of natural resources, water resources and plant water requirements. Wavelet transform is one of the new and highly effective methods for analysing signals and time series. Using the mother wavelet, the standard precipitation index (SPI) signal was analyzed and the results were considered as inputs of the artificial neural network models and the gene expression programming (GEP). Multi-layer perceptron (MLP), radial basis function (RBF), (GEP), as well as the wavelet-artificial neural networks integrated model and multi-layer perceptron (WA-MLP), radial basis function (WA- RBF) and wavelet- gene expression programming (WA- GEP) were used for drought forecasting. The rainfall data collected at the Bidestan Station for a period of 44 years were used on the Shoor Watershed in the Province of Qazvin. Moisture condition was calculated using the SPI in the short-term period of 3 months. To estimate the SPI in each period, the respective amounts were considered from the previous cycles. The results showed that among the six applied models, the WA-GEP predicted the SPI values and the short-term drought condition with a higher accuracy. The WA-GEP model proved to be the best scenario in the validation stage of R2, RMSE, MAE and NS of 0.911, 0.037, 0.022 and 0.845, respectively.

Groundwater is the most important and vital natural resource in arid and semi-arid regions. The purpose of the study is to determine the potential of groundwater in different areas of the watershed and prioritize the factors affecting it. Fourteen indices were used which affect groundwater potential namely slope, elevation, slope aspect, topographic curvature, distance from any stream, drainage density, distance from a fault, fault density, topography humidity index, lithology, land use, relative slope position, topographic position, and topographic hardness. Moreover, from the 145 springs, 30% were randomly classified as the validation data and 70% were categorized as the test data. The maximum entropy method and the MaxEnt model was used to prioritize the effective factors and zonation of groundwater potential using the ArcGIS in the Piranshahr Watershed. Further, the ROC model was used to evaluate the developed model. The results indicated that 33.6% of the watershed had groundwater potential, which is located mostly in its center. Based on the jackknife</em> chart, humidity, topography, DEM, lithology (sandstone and shale), topographic hardness, topographic position and slope were the most important factors influencing the groundwater potential. The area under the curve shows an accuracy of 93% (excellent) at the training stage and 81% (very good) at the validation stage for the determination of the watershed groundwater potential. The results of this research may be used to manage the groundwater resources of the Piranshahr Watershed, especially with regards to imminent population growth.

The Hashtgerd Plain of the Savojbolagh Watershed with an arid and semi-arid climate is one of the plains that have experienced a significant increase in groundwater exploitation in recent years. Over the past five years, the water table has dropped more than 5 meters. Therefore, the role of management factors in this plain is important. To find the effects of rainfall and climatic conditions on the groundwater level fluctuations, rainfall data from 6 rain gauge stations and 21 piezometric wells during the 1991 –2011 period were used. Meteorological and hydrological drought sequences were prepared by using the standard precipitation index (SPI) and the standard groundwater index (SWI) for six cumulative periods of these indices of 6, 9, 12, 18, 24 and 48 months. As the rainfall data series and groundwater level did not have a normal distribution, the Mann-Kendall nonparametric test was used to determine the trend of meteorological data and the water level, which showed that the slope of the groundwater level has been decreasing in all months of the period. Correlation analysis between the two indices indicates a 24-month lag between meteorological and hydrological droughts. According to the SPI6 index, the highest drought occurred during the dry season in the last quarter of of 1995 and fisrt qurter of 1996. In addition, drought zoning maps were prepared using the IDW method on a 24-months time scale, indicating severe droughts in the south of the basin. The results in some parts of the region show that there was a two-year lag between meteoroiogical and hydrological droughts. The perception of this phenomenon may help planners to manage the water resources efficiently.

Assessing the spatial distribution of recharge in karstified terrains is very important for water management and protection, but it is a complex issue due to the complexity of natural conditions and water movement in karst areas, and the application of conventional methods has not provided satisfactory results in these terrains. The KARSTLOP method is a new technique to display the spatial distribution map of recharge and arrive at the statistical mean value of the recharge in a watershed. The purpose of this study was modelling the spatial distribution of recharge using the KARSTLOP method in the Tangekhosh Watershed of Bushehr Province. The zoning map of recharge areas was prepared using the KARSTLOP method in the ArcGIS software. The results were compared with the geomorphologic map of the surface karst and the height of recharge estimated by the altitudinal isotopic gradient in order to evaluate the model's accuracy in estimating the values of recharge. Altitudinal isotopic gradient was drawn using the isotopic content of precipitation samples and the height of the sampling points during the 2016–2017 period. Digital recharge map obtained by the KARSTLOP method was shown that 45 percentage of the watershed areas had more than 60 percentage of the recharge, which corresponded to the limestone formations that contained a maximum density of the karstic landforms. The height of the recharge points of the Dovin Sarmastan, Ganavi and Tangekhosh springs was estimated at 395, 376 and 429 meters, respectively, using the altitudinal isotopic gradient method, which were placed in the altitude range of 350-550 meter and it contains the maximum recharge zone (76 to 86 percentage) of the KARSTLOP method. The comparison of the KARSTLOP recharge map with that of the recharge height of the springs using the altitudinal isotopic gradient indicated that the KARSTLOP method performed acceptably in determining the maximum recharge range and the spatial distribution of recharge in the Tangkhosh Watershed.