مجله مهندسی و مدیریت آبخیز
سال یازدهم شماره 4 (زمستان 1398)

In arid areas, water resources management and utilization is of great importance in minimizing the damage caused by water shortages in these areas while maximizing water resources efficiency. The present research aims to assess water resources management in Sistan with an approach to cope with dust storms and desertification phenomena using lexicographic goal programming method. Lexicographic goal programming is one of the most important multi-objective optimization problem solving methods. GAMS programming was considered to design research model. The results showed that according to the experts, in order to coping with dusts phenomenon, followed by meeting domestic demands in Sistan, water transfer priorities are related to critical control point of Hamoon Wetland and plantation areas in wind sedimentation. For this, once research model was run and under optimal water resources management, in addition to meeting all domestic consumption demands, the amount of water transmitted to Hamoon Lake to supply its minimum water requirement was 61.4 million cubic meters. Hence, the water needed for the stabilization of the critical control point of Hamoon Wetland was fully supplied. In addition, under optimal management conditions, water transportation to plantation farms of northern Mohammad Shahkarm and Jazinak cities was increased by 13.22 and 7.76 million cubic meters, respectively, i.e. up to twice a current value. As a result, all of water demands in these sectors have been met completely. According to the results, under optimal water management conditions in addition to meeting basic needs, water transferring to critical control point of fine grain sediment origins to stabilize them.

In this research, LAPSUS model is introduced as a suitable model to surface runoff rutting by Multiple Flow Direction (MFD) algorithms. Flow distribution algorithms grouped into two main types including Single Flow Direction (SFD) and MFD algorithms. LAPSUS model is a landscape evolution and a multi-module dynamic landscape evolution model. Studied processes included overland erosion, land sliding, tillage erosion and tectonics. Input data in LAPSUS model was DEM, rainfall, runoff coefficient and convergence factor. This model has written in C++. This model has been used for runoff rutting in Kakhk watershed of Gonabad, Iran, for the first time. For this purpose, surface runoff resulted from 34 rainfall events was simulated for multiple flow direction analysis between 2008 and 2018. Results showed that LAPSUS model can simulate total volumes of events with a high accuracy by MFD with the amount of nRMSE of 3.9 percent.

Growth of population and changes due to earth heating, have differently affected the environment. These changes have challenged the water resources exploitation process both qualitatively and quantitatively. Reduced fresh groundwater level and higher level of seawater in coastal aquifers have resulted in reduced water exploitation in these zones. This study simulated the aquifer quality due to seawater intrusion using a numerical model in GMS v.10. The quality of the aquifer was analyzed and predicted using two qualitative models of SEAWAT and MT3D. The 10-years prediction model has shown a direct relationship between increased Total Dissolved Solids (TDS) concentration and reduced water table. The horizontal to vertical diffusion ratio of 0.5 and vertical to horizontal diffusion ratio of 0.2 were obtained following the calibration of molecular diffusion coefficient. Analysis of qualitative results indicated the increased TDS concentration at the northwest of the aquifer which is probably due to seawater intrusion toward the coast. Results of simulation using qualitative model indicated the seawater intrusion from two dimensions of groundwater level and depth. Further, the density difference between seawater and fresh groundwater resources has resulted in seawater intrusion performance curve. The position of seawater intrusion toward the coast indicated increased concentration of more than 2000 mgL-1 during the prediction period. Three methods of reduced groundwater harvesting, increased aquifer feeding plans and construction of ground dams were examined and analyzed in this study in order to decide about the factors influencing the increase or decrease of seawater intrusion into the coast. Findings of the analysis indicated the highest effect of reduced groundwater harvesting in limiting the seawater intrusion compared to the two other methods.

The hydrological regime of a river is the main influencing factor on the dynamics of river ecosystem and damming operations have a significant impact on river flow discharge. Therefore, the main objective of this research was to investigate the combined effects of  changing climate variables and the Yamchi Dam construction on the discharge flow of the Balkhlu-Chai River in Ardebil using IHA Software 7.1 during the pre and after dam construction period (1973-2003) and (2004-2014). Toward this, the trend in the amounts of precipitation, temperature and evapotranspiration variables were evaluated using MAKESENS software. Then, the changes to 33 hydrological parameters and Range of Variability Approach (RVA) were firstly estimated. Subsequently, changes in the parameters of the flow rate in the periods before and after dam construction were investigated in the magnitude, duration, timing, frequency and rate of change categories. According to the results of trend analysis the precipitation had a significant decreasing trend, while, the temperature has been increased during the available time period. Based on the results, about 92% of the minimum flow discharge was attributed to that after the dam construction, while 25% of the maximum discharge belongs to this period, which indicates a decrease in the magnitude of discharge flow due to the dam construction and decreasing trend of rainfall. Also, the number of high flow pulses during the period of before dam construction was 38% higher than the period of after dam construction, while the number of low pulses in the period after dam construction was reduced by 60.7% compared to the period pre-dam construction. The value of Rise Rate index in the after-dam construction period is 0.11, but in the period before the dam construction is 0.3, which indicates a notable decrease in the mentioned indicator. Generally, based on the Magnitude group parameters, it can be concluded that the average amount of river flow during the period after the construction of the dam decreased by 52% compared with the period before the dam construction which lead to considerable environmental issue regarding the river ecosystem and flow condition. It should be noted that the variation in the hydrologic indicators is mainly influenced by the dam construction and also the change of climate variables has also been influential in this regard, and the separation of affecting factors need to be considered in further studies.

Variations in the type of storms, distribution of rainfall over the basin and other influencing factors such as soil texture, land use types and slope classes leads to significant differences in the spatial distribution of water components. In this study, using the monthly scale data, including rainfall, groundwater depth, temperature, evaporation and wind speed, WetSpass-M model was used to analyze the spatial distribution of water components at the basin of interest in the south-east of the Karun Basin. The modeled results were calibrated to simulate the monthly streamflow. Considering the fact that the Vanak Basin is a mountainous area, the snow cover maps were introduced to the model in order to include melting process. Evaluation of the model's performance using the Nash-Sutcliff coefficient of 0.61 and 0.54 during the calibration and validation period, respectively showed that this objective function was acceptable. This means the model has produced acceptable outputs. After this step, the spatial distribution of runoff and groundwater recharge in relation to various land use and slope classes were studied. Analysis of the monthly spatial distribution of runoff and groundwater recharge maps showed that due to change in slope and land classes, the runoff coefficient has a significant impact on both groundwater recharge and runoff. In such a way that the forest areas and mild slopes have generated an average 138 mm annual runoff and 596 mm annual recharge accordingly, it means a lower runoff coefficient and higher recharge values. The highest montly recharge value was in February (82 mm in thin forests with the slops of less than 10˚). This may be used to provide a better understanding of the factors affecting the distribution of water balance components or help in the maintenance, management and planning of surface water and groundwater resources.

Watershed collaborative governance is a holistic approach for attracting individual and communal involvement of active institutions and stakeholders of a specific arena, in line with ultimate objectives of both the institution and user and constant improvement at all dimensions. Present study was carried out in Sarayan district of South Khorasan Province within Se Ghale Watershed and analyzed the effectiveness of holistic projects through quantifying measures taken for establishing collaborative governance of watershed. Analysis based on the results of holistic projects reveals new horizons for future projects in other watershed areas. Macro-level indicators of stakeholders’ network were measured through social network analysis method before and after implementation of a collaborative project in South Khorasan Province. A positive trend was found out following project implementation. Macro-level indicators including the level of density (54.1 prior project implementation and 74.2 post project implementation), reciprocity (48.8 before and 67.32 after project implementation), centralization of out-group and in-group ties, average geodesic distance (1.37 pre-project and 1.25 post-project implementation) reinforce cross-sectoral links and pave the way for less centralized decision-making. This is a proof in favor of applying network analysis and cross-sectoral approach in operationalizing policies of sustainable natural resources management. What’s more, this new approach will be rather useful for administrators and planners and it will reinforce organizational cohesion of policy-making network.

Weirs are one of the common structures for discharge and flow measurement. Therefore, these types of hydraulic structures depending on the purpose of usage, have different shapes. Weirs have been widely used for the purpose of flow measurement and flow control in open channels. Generally they are used as normal weirs. For the purpose of flow diversion, they can also be used as side weirs or skew weirs. Various weirs of modified plan form have been suggested in the past to enhance their discharging capacity with minimum head over the weirs and to restrict the afflux. The aim of this study is to apply different methods to investigate the discharging capacity of a sharp-crested curved plan-form weirs under free flow conditions using original experimental dataset through the Artificial Neural Networks (ANNs) and Genetic Expression Programming (GEP) techniques. Subsequently, for training and testing of the proposed equation, experimental data of Kumar et al. have been used. A preliminary investigation on various GEP operators is also carried out for selecting the proper operators. The obtained results indicate that applied machine learning techniques have reliable performance in predicting discharging capacity of a sharp-crested curved plan-form weirs. Comparison of results obtained from this equation with the experimental data reveals high accuracy of the new equation of genetic programming and result of the ANNs. Determination coefficient of the proposed equation for discharge coefficient have been calculated as 0.956 and 0.924 for the model with best functions (F2 and F4), also this parameter calculated for ANNs as 0.962 for testing phase.

One of the most important last century challenges in the world was drought and monitoring and assessing drought severity and duration to combat and mitigate its impacts is very necessary. In recent decades, with developing of remote sensing issues, satellite-based estimating drought with high spatial resolution and different time steps were widely used. Hence, the aim of this study was focused on the analyzing drought and error distribution of TRMM satellite data-based estimation with ground data over the period 1998 to 2014. In this regard, in order to assess the accuracy of meteorological drought index based on the TRMM satellite data, 41 synoptic stations were used in Iran. In this study, error assessment criteria were included NSE, RMSE, ME, Bias and correlation coefficient and also the IDW interpolation method in ArcGIS 10.3 was used for spatial analysis. Results of drought index showed that in terms of severity, Kerman, Bushehr, Kashmar, Ghazvin, Bojnurd, Kashan stations have suffered from at least one extreme status for 1998 to 2014 and in terms of frequency, the most frequent drought was in Karaj station. Results of spatial analysis of error criteria  showed that the drought index estimated of TRMM satellite had the lower error in northeast of Iran (around Mashhad and Kashmar stations) and southwest of Iran (around Shahrkord, Esfahan, Yasouj, and Shiraz stations) while the most error was in central region of Iran (around Biarjomand, Tabass stations), respectively. In most areas of the country, drought index estimated by TRMM data had acceptable agreement with ground stations data. Calibrating the TRMM data with ground stations can be used for drought monitoring in areas without stations for networks 0.25*0.25 latitude and longitude degrees.

The precipitation is important factor among climatic factors and factors that affect on hydrology and water balance of a watershed and prediction of its behavior is very important for ecosystem management and water resources. In this study, long-term precipitation threshold trend was assessed using Non-parametric statistical approaches (Spearman Rho, Kendall's Tau, Mann-Kendall and Sen's slope Estimator) and Homogeneity tests (Von Neumann, Buishand, Standard normal homogeneity and Pettitt) at eight synoptic stations during 1984 to 2013 in north-west Iran. According to the results of non-parametric and homogeneity tests, all precipitation thresholds had decreasing trend at 0.01 significant level and showed sudden descending changes at 0.05 significant level in Maragheh station. Mann-Kendall, Spearman and Kendall's Tau tests together provided similar results in all series that were different by Sen method results in some thresholds. These means that all precipitation thresholds have trend by 26% of non-parametric tests, in order to determine change point of precipitation thresholds. Buishand, Standard normal homogeneity and Pettitt tests provided similar results that were different with Von Neumann results in all thresholds. In this research, 25.92 percent of precipitation threshold was heterogeneous in the study area by studying these sudden changes. It was found that natural and unnatural factors including meteorological droughts or human factors have caused sudden changes in precipitation threshold.

It is very important to be aware of the quantitative and qualitative characteristics of land changes in environmental planning, land management and sustainable development. At present, the use of vegetation map is one of the important pillars in generating information for macro and micro planning. In this study, temporal and spatial variations of vegetation were used in Fars Province. The data from Landsat satellite were calculated from OLI and ETM sensors during a thirty years period (1986-2016) and the NDVI index was measured. Quantitative changes of vegetation were also classified. The index is classified into three classes, including rich, poor and vegetation-free. The temperature changes of the ground level in the study period were also calculated using MODIS images. Results showed quantitative and qualitative changes of vegetation over 30 years for the studied area, so that the vegetation-free areas increased by 107. 49 ha and the areas with poor vegetation decreased by 366.56 ha and the rich vegetation cover has dropped by 455.55 ha. The largest reduction in the area was made on lands with rich vegetation. The MODIS images revealed that surface temperature has increased in the province. The temperature variation is more than 3 degrees (from -2.8 to 0.96° C) and it was observed that the highest temperature reduction was in the eastern and heading to the province. Finally, in order to investigate the relationship between vegetation and LST, the annual isobars were plotted along with the difference in NDVI in the studied period. The results showed that in most areas the vegetation cover was denser with lower temperatures.

Having predicted river flow, we can predict and control natural disasters such as flood and drought in addition to managing utilization of water resources. New models in this domain can help correct management and planning. In this study, three models are evaluated: Gene Expression Planning (GEP), Bayesian Network (BN), and Support Vector Machine (SVM). The data used for this research is precipitation data and daily flow of Gamasiab River in Nahavand during 10 years period (1381-1391). Results indicated that the relative superiority of the gene expression planning model to other models and better performance of SVM model in comparison with BN in daily river flow modeling. In addition, implementing gene expression planning model was faster than other models and could provide results in a short time. The SVM model is also more fitted to estimate the final minimum values. Finally, GEP model with coefficient of determination of 0.9230 and root mean square of 0.5867 in the training phase and coefficient of determination of 0.9025 and root mean square of 0.4936 in the test phase was selected as the superior model.

Landscape is one of the main factors influencing hydrological processes of the watershed. Changes in structure and spatial pattern of land use play important role in surface runoff and sediment yield. Determining the relationship between landscape patterns and hydrological processes can be used as an indicator of watershed soil erosion and sediment yield. Therefore, due to the problems in field measurement of sediment yield, its estimation using landscape properties and land use pattern is an appropriate alternative for current estimation methods. The purpose of this research is to determine the relationship between watershed sediment yield and landscape metrics in the selected sub-watersheds of Golestan Province. To this end, suspended sediment concentration data for all hydrometric stations of the studied province were obtained from the relevant resources and appropriate sub-watersheds were selected. Then, using the land use map of Golestan Province, 15 landscape metrics related to sediment yield were determined for different land uses by Fragstats 4.2 software. In order to determine the relationship between watershed sediment yield and landscape metrics, a partial least squares regression was used which combines the methods of principal component analysis and multiple linear regression. The relative importance of landscape metrics was determined through examining the values of Variable Importance for the Projection (VIP) and Regression Coefficients (RCs). The results of this study indicated that the watershed sediment yield is densely associated with land use patterns. The main indices in reducing sediment yield were the Largest Patch Index (LPI), the average of the nearest neighbor distance (ENN-MN) and the average of perimeter-area ratio (PARA –MN) with values of VIPs of 1.296, 1.184 and 1.747,  and regression coefficients of -0.014, -0.039, and -0.002, respectively. The main indices in incrising sediment yield were Landscape Shape Index (LSI) and mean patch size (AREA-MN) with regression coefficients of 0.020 and 0.017, respectively. The landscape characteristics in watersheds could account for as much as 71% of the variation in sediment yield of watershed. The results of study showed that the landscape characteristics can be used for watershed sediment yield modeling.

Todays, satellite precipitation data with high spatial and temporal resolution is an appropriate alternative source for conducting various studies of meteorology and hydrology in areas with inappropriate distribution of stations. These data are very important for a country like Iran which is always faced with problems of water shortage and precipitation. Therefore, the main purpose of this study is to evaluate the accuracy of GPM and TRMM daily precipitation against the recorded daily precipitation data of selected stations in Iran. Statistical methods were used to achieve this purpose. The data used include daily precipitation data from meteorological stations and daily rainfall from latest GPM and TRMM products in the period 2015-2000 in Iran. Statistical analysis showed that the daily precipitation values of these sensors are not accurate in Iran, and the estimated precipitation error is significant for most stations. Comparison of rainfall estimates from TRMM and GPM showed that although there is a great similarity between the estimates of precipitation values of GPM and TRMM, however, GPM data are more accurate than TRMM data in Iran. In terms of location, the best accuracy of the GPM and TRMM databases were observed in west of Iran, especially along the Zagros mountains, and like many other databases, the lowest accuracy was observed in coastal areas, especially along the Caspian Sea. Comparison of total annual precipitation of the stations and the remote sensing databases showed that not only there is a difference between the estimates of precipitation, there is also a spatial difference between high and low precipitation cores.

Availability and supplying adequate water is a fundamental prerequisite for socio-economic development of human societies. The purpose of this study was to evaluate the sustainability of surface water resources. The following criterion including resources (availability, variability), access (access to health), usage (domestic water use, agricultural water consumption), environment (baseflow, natural vegetation, environmental flow) and socio-economic capacities (literacy rates, the economically active population, employment in non-agricultural sector) were used to assess effective components on surface water sustainability in 21 sub-watersheds of Ardabil Province. The values of different criteria were standardized based on maximum method according to their numerical interval. The comparison of different water related components was provided using multi-dimensional spider-plots in the study area. The lowest and highest values of resource criteria (water per capita and rainfall coefficient of variations) were obtained in Shamsabad (16) and Hir (93) watersheds, respectively. The Nir, Pol-Almas, and Doostbeiglou watersheds having 60, 58, and 54 scores were identified as good condition, considering environment criteria and the other watersheds are critical. The capacity index had the highest and lowest values in Pol-Almas and Polsoltan watershed, respectively. Considering the access criteria, Shamsabad and Ahmad-Kandi watersheds had the highest and lowest scores, respectively. The mean standardized values of resource, usage, access, capacity and environment were 50, 60, 42, 38 and 25, respectively. In conclusion, the results showed that the access and resource criteria had the highest variations, and the environmental criteria were defined as undesirable conditions over the study area. It should be noted that the Central and Eastern parts of the study area had the same condition ​​in terms of their criteria scores.

Suspended Load Concentration (SLC) estimation is one of the most important environmental and engineering issues in the coastal zone. The SLC distribution pattern near the coast can be determined by in situ measurement and combination with remote sensing products according to the topography and the types of dominant currents in the study area. The research objective was to identify the spatial and temporal variations of the surface SLC in the Hendijan Delta (Northern Persian Gulf) using remote sensing technique. The water samples were taken from more than 60 stations during the passage of the Landsat 8/OLI satellite over the study area on Feb. 20, 2016 and Feb. 6, 2017. The range of SLC variations was obtained between (0-740)  mgl-1. Atmospheric correction was applied using SWIR algorithm on Landsat 8/OLI images to estimate the net water reflectance. There is a high correlation between  provided from satellite data and the measured SLC. The empirical algorithm got an exponential form with the combination of the bands 4 and 5 performed using statistical tests. For developing this algorithm more than 50 types of equations were assessed. The proposed algorithm determines the SLC from the Landsat 8/OLI images with Pearson’s 0.93, root mean square error 28.12 mgl-1 and relative root mean square error 34.24%. The algorithm was applied to timescale of satellite images, and the spatial distribution of suspended sediment concentration has been mapped over the Hendijan Delta. According to this results, the rate of decline in SLC from near the coast to the distance of 5 km of the Hendijan Delta was estimated about 2800 to 20 mgl-1 on Feb 20, 2016 and 800 mgl-1 on Feb 6, 2017. Landsat images can be used effectively to retrieved SLC in the Hendijan River Delta.

Gully erosion is one of the most important advanced (accelerated) forms of water erosion; so, identification and consideration of effective factors and its zoning is one of the important tools for controlling this phenomenon. The main purpose of the present study is spatial modeling and assessment of gully erosion using a probabilistic Weights-of-evidence (WofE) model and its different scenarios for selecting the location of gullies identified in Maharloo Watershed, Fars Province. For this aim, first, using extensive field observations, points of headcut, end, and also the boundary of the gullies (gully polygons) were identified and the gully inventory map for the study area was prepared. Then, thematic layers such as percent slope, slope aspect, plan curvature, elevation, Topographic Wetness Index, average annual precipitation, NDVI, land use, lithological units, distance from river, distance from road, drainage density, and some soil characteristics (percent silt, percent clay, EC and pH) were identified as effective factors on gully occurrence and their maps were prepared and classified in GIS environment. In the next step, using WofE algorithm, the relationship between effective factors and three different scenarios according to gully locations (head, end and gully polygons) were determined and the weight of each factor's classes was calculated. Ultimately, gully erosion zonation maps were prepared in the ArcGIS software environment. Evaluation of three gully erosion zoning maps using the ROC curve and 30% of unused gullies in the modeling process indicated that the accuracy of the models prepared based on three scenarios are 0.847, 0.861 and 0.792, respectively. Also, results of layer weighting using WofE model indicated that rainfall increasing, high drainage density, high silt percentage, low altitudes, southern directions, low distances from roads and river, Asmari, Aghajari, Razak, Gachsaran, Mishan and Sachun geological formations, as well as bare lands, have played an effective role in the occurrence of gully erosion in the study area. In order to control and prevent this kind of erosion in the Maharlo Watershed, the protective measures and watershed management were performed in the early stages.

Knowledge about soil texture is very important in agricultural studies due to its direct impact on other soil properties. However, determining the soil texture in vast areas requires a lot of time and money. For this reason, researchers are looking for ways to determine this important feature of the soil on a large scale. One of these methods is the use of surface soil spectrometry. In this method, the choice of calibration method significantly affects the accuracy of measuring the characteristics of the surface. In this study, the performance of two regression techniques, namely, partial least-squares regression (PLSR), principal component regression (PCR) were compared to identify the best method to assess sand, silt and clay. For this purpose, 50 soil samples from Tehran province were collected and used as a data set for Calibration and Validation. Soil samples with different moisture levels (oven dry, 5, 10, 15 and 20 w/w) were scanned using a FieldSpec Pro Spectroradiometer with a measurement range of 350–2500 nm. The spectra were subjected to three pre-processed techniques, e.g., Savitzky–Golay (SG) smoothing, first derivative with SG smoothing (FD-SG), Normalization with SG smoothing (Normal-SG). The R2 results from cross-validation indicated that the PLSR model had a better performance than PCR. Normal + SG pre-processing method for clay loam texture and SG method for sandy clay loam texture showed better estimation of measured properties. The amount of R2 for clay was 0.74, 0.81, 0.97 and 0.87, respectively, in moisture content of oven dry, 5, 15 and 20% in   clay loam texture And 0.95 and 0.61 at oven dry and 5% levels in sandy clay loam. Silt was better predicted by R2 0.67 in moisture content of 5% in clay loam texture and R2 0.97 in moisture content of 20% at sandy clay loam texture. Sand was also predicted (R2= 0.86 and 0.72) in moisture content of 5 and 10% in clay loam texture.

In any water resource management plan, there is a pivotal need to undertake the future conditions to allocate the water resources to different sectors (e.g. drinking-water supply, agriculture sector, etc.) more efficiently. Meanwhile, it is important to forecast water resources inflow for future months. To this aim, it is of prime interest to adopt models that are capable of coping with data scarcity problem and able to forecast the stream flow with the least possible error. The current study was aimed at forecasting the monthly inflow of the Boustan Dam by employing three models namely: time series method, Artificial Neural Network (ANN), Support Vector Machine (SVM), and their ensembles. The hydrometric data was obtained from the Tamar Station. Afterward, the models were compared by using several evaluation criteria. According to the Akaike and Schwarz criteria, the ARIMA (2, 0, 0) (1, 0, 1) was found to be the best time series model with a parsimonious behavior. Moreover, the ANN model with two and four input neurons and the SVM model with three input neurons were the best performing models compared to their other counterparts with different input numbers. Considering the evaluation criteria altogether, the time series method was the best performing model with the RMSE, AARE, MBE, and CE values of 0.88, 4.71, -0.024, and 0.36, respectively. Therefore, the time series method was introduced as the premier model for monthly inflow forecasting in the studied stations.

In this study, long-term memory and dynamic behavior of daily flow time-series of Khorramabad River, which its basin is mountainous and has urban land use, is investigated by Hurst exponent. The Hurst exponent of runoff signal of Khorramabad River during 1991-2014 period was obtained as 0.8. This value shows long-term memory and nonlinear, dynamic signal of this river’s runoff. By applying neural network and wavelet transforms, the rainfall-runoff time-series of this river was simulated. In this respect, by taking the time-series of rainfall and rainfall-runoff as input to the artificial neural network and wavelet-neural network hybrid, four models including: 1) rainfall, neural network, 2) rainfall-runoff, neural network, 3) rainfall, wavelet-neural network and 4) rainfall-runoff, wavelet-neural network were developed. In the hybrid models of wavelet-neural network, time-series of rainfall and runoff were decomposed to high-frequency and low-frequency sub-signals. Results of evaluating the accuracy and efficiency of the four models showed that the wavelet–neural network model correctly simulated the runoff behavior with the best efficiency at 99% confidence level. Comparison of the results of wavelet–neural network model to the neural network model, using Morgan-Granger-Newbold, showed significant superiority of the first model. Also, results of evaluating signal error of the four implemented models, using two tests of Von-Neumann and Buishand test, showed that there is a significant substitution point in the signal error of the neural network model and signal of rainfall-runoff model. Therefore, existence of very different monthly and periodical fluctuations in 1991-1998 and 1999-2014 in the behavior of rainfall-runoff leads to reduction of efficiency and precision coefficient of neural network model. While, in the hybrid model of wavelet-neural network, allocation of relative weight to each sub-signal, has effectively reduced the short-term, average and long-term fluctuations in modeling error.

Determining the precise location of sub-watersheds in flood production is very important. In some cases, it is time consuming and costly to do this by conducting field studies and mapping topographic maps. Today, the new and growing technology of LIDAR active sensor data is used to collect data from the ground surface, which operate based on measuring the distance of the laser. In this research, Gorgan Shast-Kalateh forest basin was selected due to various data. In order to prepare sub-watersheds and their characteristics, it is necessary to have a digital elevation model. In the above model, LIDAR and radar data and other sensors were used with spatial resolutions of 1, 12.5 and 30 m, respectively to control the ground data. The streams were extracted using the appropriate model in each method and all types of watershed characteristics were obtained through Arc-Hydro and IDRISI software. The distance index of each  stream from others and ground reality were investigated. Comparison of analyses was done in SPSS software. The sig-value for comparing altitudes along the streams for LIDAR with a pairwise t test was 0.13, which shows no significant difference. Comparison of the streams of different digital models between the land 12.5th m and 30th m and LIDAR, the sig-value of 0.002 in Wilcoxon test, shows significant difference. Also, based on the overall conclusion, it was observed that there is a significant difference at 95% probability level, between the methods used. Eventually, LIDAR data had the highest accuracy with ground reality.

This study was conducted to evaluate the capability of the DHSVM model to simulate hydrological processes in a mountainous watershed with a minimum agricultural land use. The required climatic parameters were set for the daily time step. The inverse distance method was used to interpolate the climatic variables from the stations to the network cells. Time inputs to the model were prepared for the years 2008 to 2013. The land cover map was prepared using the supervised classification method of Landsat TM data. The stream network map was generated using the DEM map in ArcGIS software. The soil texture map was prepared using field sampling and in the laboratory. Primary tests to the determine sensitivity of input parameters showed that this model is sensitive to lateral hydraulic conductivity, exponential coefficient of hydraulic conductivity, porosity, field capacity, and minimum stomatal resistance. In this study, except for the lateral hydraulic conductivity and exponential decrease coefficient, all other parameters (soil and vegetation) were determined based on previous studies and field measurements in a similar way for both categories of data.  The time series of the data were divided into three, warm- up or preparation periods (2008-2009), calibration (2009-2011) and validation (2011-2013). The model was calibrated using stream flow data from 2008 to 2010. Different efficiency criteria were calculated between simulated and observed flows. NSE value for calibrating was 0.59 and for validation was 0.606. In general, the results of this model implementation in the studied basin with the quality and quantity of input data to the model are satisfactory.

The erosion rate ranking of geological formations can be a useful way for identifying and prioritizing the watershed sub-basins and it is important in view of decision making and management of the watersheds. Therefore, the present research was conducted with the aim of prioritizing the implementation of soil conservation operations in the Hablehrood sub-basins in northern Garmsar based on the degree of sensitivity of rock units to erosion. The method is based on the expert opinions and rainfall simulator experiment and comparison of the obtained results with erosion and sediment estimations of empirical models such as PSIAC, EPM and SWAT. Results showed that erosion rate ranking of the sub-basins based on the results of rainfall simulator conformed to the output of the three mentioned models in 12 sub-basins of 21 sub-basins and in other six sub-basins with two models, and in the remaining three sub-basins, it only conformed to one model output. Rainfall simulation results showed the highest correlation with the PSIAC model with a specific sediment yield of 9.2 t km-2 and based on the results of the observation data of the Bonkouh sediment-debit station, a special sediment of 8.02 t km-2 without considering the bedload, it became clear that the PSIAC model provided the most reliable estimate of sediment yield. Thus, matching the results of rainfall simulator in the erosion rate ranking of sub-basins with the PSIAC model shows that the rainfall simulator study on lithology units quite reliable with a 90% confidence level for erosion ranking classification of sub-basins and it can be used in similar basins.

Bedload movement plays an essential role in the process of bedload transport and morphological characteristics of rivers. Slope, flow rate and particle size are important parameters in the amount of bedload transport in the erodible beds. Many studies have been investigated the effects of these parameters on the non-erodible beds. In this research, performing a laboratory model in the erodible substrates, the effects of slope, flow rates, particle size and suspended particle concentration on the amount of bedload transport was investigated. The experiments were carried out in the discharge rate of 0.90 to 4.75 ls-1 with the concentrations of the suspended particles 0, 10gl-1 and the slopes of 2, 3 and 5 percent, on the uniform non cohesive particles with the grain diameter of 1.7 and 3.29 mm. The Froude numbers of these currents were obtained in the range of 0.93 to 1.51 and the non-dimensional bed load discharge was calculated in the range of 0.004-0.131. In the experimental results, the variation of the bedload transport capacity in relation to the discharge was shown in the different slopes and grain sizes. Furthermore, increasing the concentration of suspended particles to 10 gl-1, did not has a significant effect on the bed transport capacity. Applying dimensional analysis, the effective parameters on the non-dimensional bed load discharge (ϕ)were investigated. Moreover, to determine ϕ relation to the shear stress (ϴ), particle size (D*) and slope (S). In the scope of the experiment, an experimental relationship was proposed. Results indicated that for determining the non-dimensional bedload discharge in the steep slopes of erodible beds, considering the slope and dimensionless particle diameters as independent parameters had a better result than shear stress correction. Sensitivity analysis of effective parameters on the experimental relationship showed that the slope parameter had the most effect on the experimental relationship.

Monitoring the area and their marginal land uses changes in lakes are one of the strategies to achieve proper management of lakes and wetlands. In the present study to monitor Maharlu Lake area and its marginal land uses changes in Fars Province, the Landsat images of 1987, 2001 and 2013 were selected in wet and dry periods (March and September). By applying geometric and atmospheric corrections, the maximum probability algorithm was used for providing land use map. The Kappa coefficients for the September of 1987, 2001 and 2013 were 0.85, 0.88 and 0.89, and for April of 1987 and 2013 were 0.86 and 0.88, respectively. After providing land use map and validation, the method of comparing satellite images was used to monitor the changes. The changes were monitored by comparing Landsat images after classification. Results showed that the Maharlu Lake area has decreased by 82% in September 2013 compared to 1987. This reduction was 20% in March, 2013 compared to 1979. By reducing the water level of lake in September, bare soil and saline lands were increased by 39 and 37.5%, respectively. Agricultural and range lands have been decreased by 28 and 3.5% from 1987 to 2013, respectively. In general, the area under cultivation around the Maharlu Lake and the water level has been decreased significantly due to the lack of significant changes in rainfall during the long-term period and significant increase in evapotranspiration of Maharlu area during the last three decades. Due to recent droughts, bare soils and saline lands have been increased during this period. This has different consequences which require the proper management and planning of lakes and wetlands, especially during the drought periods.

In the present study, the effect of climate change on the flow of the Hablehroud River was assessed, using the HadCM3 general circulation model, the LRAS-WG downscaling model, and the SWAT hydrologic model. First, using the LARS-WG model, the output of HadCM3 model in the period of 2011-2040 was downscaled and the necessary data for the SWAT model were obtained. The downscaling results showed that there is no meaningful difference between the future precipitation and the precipitation observed in the base period of 1995-2010. It was also observed that in the A2, B1, and A1B emission scenarios, the mean of minimum temperature will increase by 0.59, 0.47, and 0.43 0C, respectively, and the mean of maximum temperature will increase by 0.51, 0.39, and 0.35 0C. In the next stage, the SWAT model was calibrated and validated using the monthly flow data recorded at Bonkouh gaging station located at the outlet of the basin. The values of the coefficient of determination and Nash-Sutcliffe in validation phase were 0.8 and 0.72, respectively. Introducing the downscaled rainfall and temperature data to the SWAT model, the variation of the basin outflow was simulated in the period of 2011-2040. Results showed that in the three scenarios under study, the annual flow will increase 10.66, 17.72, and 17.52% in comparison to the base period.