JOURNAL OF WATERSHED MANAGEMENT RESEARCH
Year:2016 | Volume:6 | Issue:12|Papers Count:21

This study evaluates the performance of the linear first-order Volterra model for simulating nonlinear rainfall-runoff process. For this end, fifteen storm events over the Navrood River basin were collected. 70% and 30% of the events were used to calibrate and test the suitability of the model. Finally, the performance of the model was compared with the artificial neural networks (multilayer perceptron (MLP)) using five performance criteria namely; coefficient of efficiency, root mean square error, error of total volume, relative error of peak discharge and error of time for peak to arrive. Results indicated that the intelligent MLP models outperformed the Volterra model. The linear Volterra model was not more effective in simulating the rainfall-runoff process. It needs to be extended to higher orders and also the number of the parameters should be reduced.

Recent studies show that cluster analysis methods are one of the most useful techniques of regionalization of watersheds for regional flood frequency analysis. In this study combination of Ward and K-means clustering algorithms is used for regionalization of gauging stations in Sefidrood and Aras watersheds in order to use advantages and decrease influences of disadvantages of two main categories of cluster analysis methods. Also effects of selection and usage of some geographical, physiographic and meteorological attributes and their combinations on homogeneity of regions formed by cluster analysis is studied. Assessment of homogeneity of final regions and performance of regional flood frequency analysis using L-moments show that combination of longitude, latitude and drainage area as attributes used for regionalization of Sefidrood and Aras watersheds may be the best option to form maximum number of homogeneous regions. Furthermore, Wakeby distribution may be used as regional distribution for heterogeneous regions.

The appropriate use of a conceptual rainfall-runoff model depends on how well its parameters are calibrated. Generally, rainfall-runoff models deal with numerous parameters that cannot be measured directly and should be estimated through optimization tools. The purpose of the optimization approach is to finalize the best set of parameters associated with a given calibration data set that optimize the evaluation criteria. In this paper, a continuous genetic algorithm calibration method has been used to estimate the NASH conceptual model parameters (n, k).The efficiency of the method was evaluated using the estimated parameters to simulate different rainfall - runoff events that happened in the Kasilian watershed in Mazandaran province during previous years. The calibration and validation results have shown that the suitability and efficiency of this model for auto calibrating of Nash conceptual rainfall-runoff model is more accurate and favorable.

Modeling of hydrological processes provides appropriate information for watershed management through a deep and comprehensive insight on watershed systems. In this research a daily basis distributed water balance model for the Chehelchay watershed in the Golestan province in north east of Iran has been developed using the PCRaster GIS and dynamic modelling language. Various components of the watershed water balance including precipitation, snowmelt, evapotranspiration, soil moisture, surface runoff, interflow and baseflow have been simulated. Total discharge has been obtained by aggregating surface runoff, interflow and baseflow. Calibration of the developed model has been carried out by observed daily discharge during 2007-2008. For validation, the observed data of 2004-2006 period has been used. The Nash-Satcliffe efficiency criterion has been used to evaluate the model results. The results indicated that the value of the Nash-Satcliffe coefficient was 0.7 and 0.5 for the calibration and validation period, respectively. Since a Nash-satcliffe value for both the calibration and validation period is greater than 0.36, it can be concluded that the developed model has a relatively good capability to simulate the Chehelchay watershed discharge. Given that the results are suitable, different components of the water balance of the Chehelchai watershed have been calculated. The model results showed that the runoff coefficient of the watershed is 19.1 percent which is similar to its observed counterpart of 22 percent. The results of the developed model were also compared with the results of WetSpa model in this watershed.

Flood is one of the natural disaster phenomena and flood prediction is very important. The rainfall-runoff process and flood are physical phenomena that these analyses are difficult due to the influence of various parameters. There are different methods and models for these phenomena analysis. This study is carried out for rainfall-runoff process simulation using artificial neural network (ANN) involving snow water equivalent (SWE) in Latyan watershed located in Tehran province. For this reason, 92 images of MODIS were obtained during three years from 2003-2004 to 2006-2007 from the NASA site. Snow cover areas (SCAs) were extracted from each images and SWE were computed during these years. The rainfall, temperature and stream flow were available during these years. Multilayer perception networks with back propagation algorithm were used for finding the structure of the networks. Results showed that ANN with 4-10-1 structure, 4 neurons in input layer, 10 neurons in middle layer and 1 neuron in output layer, with performance coefficient of 0.85, determination coefficient of 0.68 and root mean squared error of 0.04 as the best structure had good precision in runoff estimation and SWE was caused to increase the accuracy of the model.

In order to assessment and prediction of hydrological processes with inherent complexity, processes changes effects on the nonlinear behavior of watershed system in the past and future and specification of water and soil conservation operation, using indirectly methods such as simulation of watershed processes therewith directly methods is necessary. The objective of this research is evaluation of runoff generation in space and time using distributed hydrological WetSpa model in Taleghan watershed of the Sefidrood basin. Thus flow hydrographs and peak discharges in any space of the stream network were predicted also spatially distribution of hydrological processes such as runoff was simulated using incorporating of both daily meteorological data in an 11 year period and three base maps information. Simulated results reveal that there is good agreement between observations and simulations. The Nash- Sutcliffe criteria, 83.3% and accuracy of the simulation show the high performance of the model in this watershed. Regarding to the outputs and spatially distributed hydrological factors in daily time step the model is capable to analyze topography, soil type, and land use effects on the hydrological behavior of the watershed.

Surface water that is the result of rainfall-runoff responses in a basin is a potential water source that if it is managed properly, can be useful to demand secure. Rain Water Harvestings an suitable option for monopoly and store runoff for future use, especially during the period that has restricted access to water. In this study has determined susceptible places for Rain Water Harvesting using AHP method in Birjand plain at southern Khorasan Province. For research using opinions of various experts, effective criteria's in rain water harvesting process are determined and are pair wise compared together then paired comparison matrix of criteria was established and weight of each of them was estimated. After determining the weights, spatial layers of criteria combined together and was created the final layer of rain water harvesting prone areas. the results showed that with placing Talent plain in four-class weak, moderate, good and very good respectively, 0.82, 46.1, 50.4 and 2.66 percent of the total basin is allocated to the classes listed and generally from west to East of plain, is added on its ability to rain water harvesting.

The purpose of this study is to produce a groundwater spring potential map based on statistical and probability logistic regression method. The spatial locations of the springs in mountainous Miradeh watershed, Kurdistan province, with 381 Km2 were determined. Based on field and local study and Water Resources Management Company, spatial location of 904 springs in the study area were registered and 304 springs selected randomly as test data set and the remaining 600 spring were used for training the network. Forward stepwise LR was used to analyze the data and to find the most influential factors on spring occurrence that are statistically significant. The accuracy of model evaluates and verified using statistics such as: -2LL, Cox, Snell and Nagelkerke R2. The accuracy of each model to predict was evaluated using calculating the area under the ROC curve values. ArcGIS was used to apply the proposed method and calculate statistical and Probability of spring occurrence potential. This can help planners and engineers in groundwater development plans and land-use planning.

This study investigated motivation factors affecting on farmer’s participation in terrace cropping operations in agricultural land in Chehel-Chai watershed in Golestan province. Research method was descriptive and the statistical population of the study consisted 75 farmers participated in terrace cropping operations in agricultural land in Chehel-Chai watershed in Golestan province. Using systematic random sampling, 62 of them were chosen. Information was gathered through a questionnaire and its face validity was confirmed by experts of soil conservation and agricultural extension. The reliability analysis was conducted with completing 30 questionnaires outside the geographic research region and Cronbach's alpha coefficient was 0.81. Data were analyzed using SPSSwin16 software. The results showed most important motivators for farmer’s participation in terrace cropping operations in agricultural land were cooperate with other farmers implementer operations, encourage other farmers and perform the operations by neighbors adjacent farm. Also the results showed a greater impact of individual social motivators for farmer’s participation in implementation of terrace cropping operations in farms. This study has proposed attention to interpersonal relationship between farmers and offering technical advice by visiting experts to farms and communication resources especially radio and television in order to continue participating farmers in implementation of terrace cropping operations.

Today, as the focus of watershed planning and management for sustainable development in many of the issues. Ecological watersheds can be evaluated and ranked them according to various ecological criteria for the watershed, one of the important steps in the planning and management of watersheds. Since the cost of watershed management projects and heavy construction project budget is limited, it is necessary that measures should be based on priorities in the watershed. A multi-criteria decision making technique in this approach is suitable for solving such problems. The use of these techniques with respect to various criteria decision making, it is the best option or options to select from available options and decisions to be implemented. In this study, TOPSIS method as the most popular methods of multi-criteria decision making has been used in watershed Zydasht Taleghan. Ten indicators of soil conservation, erosion and sedimentation, species, age class, species composition, poisonous plants, forage production, grazing capacity, quantity of water, evaporation and transpiration were measured and used TOPSIS method the criteria for prioritizing actions Watershed. The TOPSIS method and the ten indices were considered and used as technique for Order- Preference in terms of similarity to ideal solution, D1, Dint1, Dint2, and D2 sub-basins in Zydasht of Taleghan were prioritized for the watershed planning, respectively.

Due to severe fluctuations in rainfall in different regions of Iran, droughts are amongst natural disasters which occurs in negative fluctuations, when rainfall is lower than long term average and forcing adverse effects on agriculture and economy. Meteorological drought is one of the droughts that occurs in the earliest stages of drought phenomenon. In this study, using standardized precipitation index (SPI) the status of meteorological drought is reviewed and linear moment method is used to analysis regional frequency. For regional analysis, with linear moment method, a computer program, developed by Hosking, is used. After surviving distorted criterion and homogenous degree criterion, it became clear that one of the stations of Karun basin 1, has distorted criterion. Also, the results of goodness-of-fit criteria showed that the pearson distribution type III, can be fitted regionally for whole region. So this distribution will be used to analysis drought indexes in this area.

In recent years due to increase of drought frequency, lakes water levels, in arid and semiarid regions of the Iran, have dropped significantly. Therefore, in addition to ecosystem degradations, drought challenges socio-economic sectors as well. The purpose of this study was to evaluate the water level fluctuations of Parishan Lake during the wet and dry periods, and the impact of drought indices on lake water balance. By help of the SPI, CZI, MCZI and ZSI drought indices, the impact of drought on the lake water level fluctuations were investigated using meteorological data of 5 stations close to the lake. Three time scales of 3, 12 and 48 months were used for this purpose. There were significant relationships (P£0.05) between the lake water level fluctuations and drought indices of SPI, CZI, MCZI and ZSI for all evaluated stations. Long-term time scale SPI and ZSI indices had better relationship (r=0.6) with lake water level fluctuations compared to other indices. With removal of phase lag between drought and water level fluctuations, regression relations for 4 drought indices of short- term time scales were improved. Findings of this research indicated that drought was the more effective and important factor on decline of the lake water level during the 2000 decade.

Droughts event can be effect on available groundwater and water resources in the many components that it cause deficit. This purpose, for the deal with droughts hazard for make decisions it is necessary to monitoring and assessing droughts feature in point of view concluding; severity, geographic extending. In this study the hydrological droughts analyzed based on the clustering, surface water index and moving average methods in the 6 selected hydrometric stations in Ilam province over the 1982-2011. The results of the SDI showed that only occurred the moderate and slightly droughts states for the 3 and 6 reference periods. In the 9 and 12 reference periods, additionally we observed the severity droughts states in the three past decade. All of the stations experienced one wet year severity droughts in over the 1991 to 1996 period in the three past three decade. In contrast, all of the stations had been in the hydrological droughts event in over the 1996 to 2006. Hydrometric stations classified in three clusters based on surface water drought statuses. The results of clustering showed that Ivan, Holeylan and Tangsazin stations labeled in cluster 1 and Nazarabad station in cluser 2 and finally the Sarjooi and Dartoot stations classified in cluster 3. Ultimately, The Mann-Kendall and Linear Regression were applied to explore the relationship between hydrological droughts and river flow trends. The results of the trends test showed that all of the stations had decreasing trends.

Multi-site modeling of rainfall is one of the most important issues in environmental sciences especially in watershed management. For this purpose, different statistical models have been developed which involve spatial approaches in simulation and modeling of daily rainfall values. The hidden Markov is one of the multi-site daily rainfall models which in addition to simulation of daily rainfall values, explores the spatial and temporal pattern of rainfall events. In this study, the winter (January to April) rainfall pattern of 130 rain gauges have been modeled using hidden Markov approach during a 21 years period (1990-2010). The aim of this study was finding temporal and spatial distribution of weather patterns and stochastic simulation of occurrence and amount of rainfall, simultaneously. To achieve this goal, different hidden Markov algorithms including, Viterbi decoding algorithm, Expectation-Maximization (EM) algorithm and a stochastic simulation approach with the probability transformation were applied. It is expected that extracted patterns, using hidden Markov model, are consistent with synoptic patterns and accordingly eight different weather pattern as the definite set of possible cases were recognized. The most frequent rainfall pattern extracted from hidden Markov model was the dry pattern (stable condition) in which the rainfall occurrence probability is low in most of the stations. This pattern has the maximum initial probability of 0.429 and maximum Markov transfer probability of 0.637 Besides, multi-site simulation of winter rainfall keeping the basic statistic of mean, standard deviation of total seasonal rainfall and percentile values in each station and also spatial correlation of occurrence or nonoccurrence of rainfall produced reasonable result. In general this approach can be recommended for regional studies.

Drought is a phenomenon that threating water quality in addition to its shortage. In this paper we investigate the effect of drought on surface water quality of Kashkan watershed. For this purpose, during the collection of meteorological data and water quality data during 20 years (1987 to 2009) from Meteorology and Water Resources offices of Lorestan province, initially duration and severity of meteorological and hydrological droughts were determined by SPI, RDI and SDI Indices. Later in periods that intensity and duration of drought were more than other period, percent changes of water quality to the long-term average was calculated then agricultural and drinking water quality analysis in the form of two charts Schuler and Wilcox was performed. Also, the linear trend of data was investigated for highlighting the effect of drought on water quality changes. Results indicate that drought has significant changes in parameters of surface water resources especially EC, TDS, NA, CL and SO24.Also the results showed that water quality in terms of Schuler & Wilcox graphs has changed in effect of drought. The quality of Afarineh and Chan Anjir rivers drinking water has changed from ok classes to acceptable grade and for agricultural purposes has changed from C2S1 grade to C3S1 grade. Finally, the overall analysis of linier trend graphs shows that the increasing trend of drought has a negative impact on surface waters quality of Kashkan watershed.

Watershed erosion and sediment load of rivers are serious water resources management challenges, which have negative consequences on the operation of water installations and dams. This study has done with the aim of investigating the relationship between hydro geomorphologic characteristics and calculation the amount of especial deposition around watersheds, because of depending on the volume of runoff and soil erosion rates or sediment discharge with hydrogeomorphologic characteristics in the watershed. In order to achieving to the object of research and investigating the role of percent of vegetation cover density, slope rates and soil permeability in fancies formation, Zonouz Chai catchment, one of sub-basins of Zilber Chai watershed, which has a higher number of drainage density than other sub-basins was selected and the weights of all effective factors were calculated according to the analytic hierarchy method (AHP). Afterwards, based on the multiple regression model using stepwise method the correlation coefficients (R2) were determined at 95% confidence level and amount of runoff volume was calculated in Zonouz Chai and Zilber Chai based on SCS method. Finally, correlation coefficients of watershed characteristics were estimated and were replaced as exponential coefficients for discharge-sediment equation, which was suggested. Then especial deposition rates were calculated in Zonouz Chai and Zilber Chai respectively, 163 and 672 (ton/km2/y). Comparison of computational results with observational rates, based on 35 statistic data years, was found, in the two watersheds has acceptable accuracy at 85% and 91%, respectively.

Soil erosion leads to washing topsoil, organic matter and soil fertility will decrease eventually. In order to combat erosion and loss of soil, conservation and watershed sediment generation in the NIR region, based on the WSM modeling was performed to estimate the severity of soil deposits. The model with six factors was scored for each work unit. Usually suitable model for certain areas that used them in different situations, needs to model coefficients be calibrated in the study area. For calibration, were measured the amount of precipitation from the model (estimated) and the simulated rain (objective) per work units in this watershed. The results were showed that in some work units the amount of estimated is more than 10 times versus the amount of real data (model with overestimating). The coefficients correction was done by optimizing in the Solver, with convergence (10-4), mutation and forward derivative (0.075) technology, with default values. With using the correction coefficients in the model and establishing a revised model, estimated sediment was closer to the objective values and were increased the correlation between estimate and the observed. Thus the modified model for areas with similar soil and climatic conditions in Yazd province, which has been used with caution. It is suggested to improve the coefficients, with the modified model results in a basin with actual values, to evaluate more confidently be used as local models.

Water and soil are the most important natural resources of each country and are the foundation of human life. Soil erosion and sediment production causes reduced fertility of arable land and therefore are threatening human life; On the other hand, increasing sedimentation amount in watersheds has an important role in reducing useful life of dams and dewatering reducing capacity of them. Thus the study of soil erosion and the estimation of the output sediment watershed are necessary. Researches carrying out the quantitative assessment of sediment production using the different models are one of solutions that through which one can partly control and minimize the amount of this phenomenon. The aim of this research is to evaluate efficiency of the WEPP model in estimation the output sediment Sulachai watershed. The method in WEPP model this is that, to the beginning the file related to each of the model parameters such as climate, soil, topography, management and drainage is created and entered on the software GeoWEPP and finally sediment load is calculated. WEPP model has required performance in sediment estimation for the three-scale slope, catchment area and flow-direction. Estimated sediment by each of the above three scales, is 0.213, 0.178 and 0.785 respectively, and for observed sediment is about 0.241 ton/hectares/year. The results of the comparison of WEPP model with the observed sediment indicated that from among the scales available in the WEPP model, slope and catchment area scales were closer to the amount of sediment observed and have offered more acceptable results than the flow-direction scale.

Rock falls are natural process of activities geomorphic on steep slopes in mountainous terrains. At this research, rock fall susceptibility mapping was generated by logistic regression (LR), frequency ratio (FR) and analytical hierarchy process (AHP) at a long 11 km of the Salavat Abad road in the eastern of Sanandaj, Kurdistan, Iran. Dependent variables is occurrence and nonoccurrence of rock falls and independent variables are including; slope degree, slope aspect, slope curvature, elevation of sea, lithology, distance from road, distance from fault, land use. The maps which were generated with the methods, compared and verified with rock-falls situation using the success rate curve (SRC). Results showed that the logistic regression, analytical hierarchy process and frequency ratio methods had an accuracy of 85.09, 83.2 and 76.76 percent of the area under the curve (AUC), respectively. Therefore, logistic regression is more proper than the other methods for determining regions prone to the rock fall in the case study.

Identification of factors affecting on existing of landslide as well as its zonation in the given watershed is one of the basic tools for landslide control and selection of approach and effective solution as well. In this study landslide hazard mapping provided using previous landslide distribution and multivariate regression model in GIS environment in Aghmashhad. With reviewing previous resources and studying of Aghmashahd watershed, the eight factors of altitude, slope, aspect, geology, soil, land use, distance from river and distance from road were selected. With a field observation of the whole watershed, the local information and GPS were listed and landslide preparation map was prepared with stepwise multivariate regression in the statistical software SPSS. The distance from the river factor was selected as major factor affecting the landslide. The benefit of this model is to assess the expansive areas in short time. Research result showed that there is a significant correlation at the 0.01 level (P<0.01) between potential hazard values, classes and current land slide area.

Accurate estimation of suspended sediment in rivers is very important from different aspects including agriculture, soil conservation, shipping, dam construction and aquatic research. There are different methods for suspended sediment estimation. In the present study to evaluate the ability of time-series models including Markov and ARIMA in predicting suspended sediment and to compare their results to Artificial Neural Networks it was tried to use daily suspended data from Ghazaghly station of Gorganroud River, as average monthly values in Minitab 16 software and Neurosolutions 5, and finally suspended sediment was predicted for 111 months. Calculation of the error measurement indices including RMSE and NMSE based on the results of this study showed a good ability of Artificial Neural Network models in estimating average monthly suspended sediment. On the other hand between time series models, Markov model has better ability in estimating monthly suspended sediment in comparison to the ARIMA model.