IRANIAN JOURNAL OF WATERSHED MANAGEMENT SCIENCE AND ENGINEERING
Year:2016 | Volume:9 | Issue:31|Papers Count:11

Undoubtedly, wise management of land and water resources is necessary for sustainable land And it is now because of the lack of proper management of land and water resources, and competing demands on their use, population growth and climate change will cause The problems associated with land use changes and water resources in the past decade to become the greatest human challenges In the study area change and unsustainable land shortage in the last decade was And the threat of ecological and hydrological effects caused by the addition of the micro-and macro-scale, sustainable living in the study area has also been challenged.This study presents a model to determine land use and land ownership maps to separate the villages.So using TM images to map land was in 2012.The image preprocessing steps were performed and the image data points were taken from various parts of the GPS and 1: 25000 topographic maps And the method of maximum likelihood classification was attempted. And using water resources data relating to 1391, the primary and supplementary field studies and other information on land ownership maps to separate each village.. The results show that except plain Farsan, Shalamzar and other wheat plains of the province are faced with negative balance Plains Groundwater equilibration and for Kord, BorougenSfyddsht, child care, and Khanmirza Flared be 13, 30, 66, 32, 48 and 12% respectively, reduced water uptake. In the plains Farsan, Shalamzar and wheat results show that we can harvest 30 percent respectively 45.38 and watering the plains, was increased The results can be accurate to the land, especially land and water resources planning based on demographic and economic characteristics of each country shall be used.

In the study ofclimate changes, Prediction of the futureclimatic parametersis performedbygeneral circulationmodels (GCMs) andemissions scenarios ofgreenhouse gases.However, Global Circulation Models have very course spatial resolutions.For this reason, downscaling methods are needed to bridge the gap between the large scale climate scenarios and the fine scale where local stations exist. Downscaling methods are divided into two categories: 1) statistical models and 2) Dynamic models. Among these methods, statistical methods are much more popular which is due to low expenses and less time consuming procedures. Lars-WG and SDSM models are among the most concise methods of statistical tools for downscaling. Herein this research these two models were used in simulating precipitation and temperature changes in Urmia lake basin located in the north west of Iran. Four synoptic stations includingSaqez, Tabriz Khoy and Urmia were considered. These four stations had a good and long data especially in base period (1961-1990). In order to assess the models, MSE, RMSE & MAE indexes along with regression and bias were used. Results show that both models were good in simulating temperature but SDSM was better in simulating precipitation according to statistical performance measures and has less uncertainty. But it has more complex and time consuming procedures. While Lars-WG is simpler and faster comparing with SDSM. In general, none of the models has absolute superior in simulating climatic parameters and both can be used in climate change predictions.

In order to investigate Mahvalat plain aquifer in Khorasan Razavi, quantitative changes (with completion of questionnaire and periodic data of groundwater level) and qualitative changes (with sampling and chemical analysis) of groundwater resources has been carried out. The analysis of periodic data of groundwater level in a 14-year period (1994-1995 to 2007-2008), showed that the Average drop of groundwater level has been annually 1.35 m. The data analysis of questionnaires showed that the total annual depletion by wells and Qanats is 254 MCM, the annual recharge of basin is 157 MCM and the annual reservoir deficit is 97 MCM. Chemical analysis of 48 water samples from wells and 3 water samples from Qanats showed that the water quality has reduced from the northeastern plain to margins. In terms of classifying the quality of groundwater for agricultural purposes by Wilcox, 5.88% of samples in Class C3-S1, 19.61% of samples in Class C3-S2, 9.80% of samples in class C4-S2, 23.53% of samples in class C4-S3 and 41.18% of samples were placed in class C4-S4. According to this method, 74.51 percent of groundwater samples are not suitable for agriculture.

Artificial recharge projectshas significant role to play as a scientific and practical approachin order to optimize use of water resources, especially aquifers. Artificial recharge projects in Sefeiddasht- Fradnbeh plain was implemented for food security, in agricultural development and sustainable natural resources and optimal utilization of available resources and their potentials. In this project, surface runoff, water from a few springs and subterranean streams which enter into Borougen’s river and then join in the Karun River were considered. The water enters into the pools of artificial recharge project with structures such as diversion dams, conveyance channels and the inverted siphon crossing road and then water was infiltrated into aquifer. The current research project was implemented in order to evaluate yield and affected quantity in project related to stored water in aquifer. The results show that runoff input to the project was 6.1, 5.3 and 7.3 million cubic meters per year during 2003 to 2006 years, respectively and they affected Sefieddasht plain and part of Faradonbehplain. In order to investigate the effects of artificial recharge on water table and fluctuations in the volume of water stored in aquifer and groundwater resources management, Modflow model was used. For evaluating the performance and behaviour of the aquifer, six scenarioswere used.Scenario no.1: With normal time condition for implementation in the short term, medium term and long term 2, 15 and 30 years, respectively, Scenarios No.2 and 3: In these scenarios average annual rainfall are assumed to reduce by 20 and 40 percent, Scenarios No.4 and 5: In these scenarios, average annual precipitationare enhanced by 20 and 40 percent over entire area, and scenario no.6: the scenario includes reduction in rainfall by 20 percent, reduction in canal seepage by 50 percent with increase in agricultural area by 20 percent, increase in domestic water demand by 10 percent. The results show that inscenario no.1, for artificial recharge project area, the simulated results for 15 and 30 years of groundwater table fluctuation rises by 19.4 m and 23.9 m after 15 and 30 years of operation in the aquifer.In scenarios no.2 and 3, the avarage groundwater table has gone down by almost 0.9 and 1.45 m as comapred to normal scenario or business as usual approach. In scenarios no.4 and 5, the rises in water table were 1.45 and 2.69 meters, but in scenario no.6, groundwater table was reduced 3.45 meters in the whole area.

Increasing populationin one side and water demands in other sides, the importance of groundwater resources as one of the most important fresh water resources, be more and more apparent. In this study, stream density, distance from drainage, slope, elevation, thickness of the aquifer, water table, rainfall, topography wetness index and the rate of permeability criteria were used to identify areas with potential of groundwater in Varamin plain. The Map of these criteria prepared and weighted using Analytical Hierarchy Process method, and with determination of the effective rate for each class and using fuzzy logic, prediction map of groundwater potential with two methods of AHP and fuzzy AHP were preparedandaccuracy of the method was evaluatedusingwells with highdis charge. The results showed that, due to hydro-geologicalcomplexity of the area, accuracy of fuzzy AHP and AHP was respectively 61 and 54 percent. Also, the areas with high potential were located in the northern half of the plainswhichcovered with coarse sedimentduring the Quaternary. The results showed that application of fuzzy AHP method, besid essaving time and money, had a good abilitytopredict the groundwater potential.

Assessing effects of land use spatial pattern on hydrologic characteristics and variation of flow hydrograph can provide new information leading more effective decision-making and integrated watershed management. However, less attention has been relatively paid to this subject. The emphasis of this research is to quantify the contribution and effects of different land use types and spatial pattern on flood hydrographs in Galaz Watershed (103 km2 area), located in West-Azarbaijan Province, Iran. In the present study, the Clark's Time-Area model has been employed for simulation of hydrograph. The Time Area Histogram (TAH) of the study watershed has been derived based on a spatially distributed travel time approach, and the flow hydrograph was simulated in incorporating with the different land use types and design rainfall.The hydrograph has been routed to the watershed outlet. Then, the distribution of flow hydrograph and the peak discharge were analyzed considering different land uses between isochrones. According to the results, the effect of land use types and patterns led to variations of time area histograms and the obtained hydrograph. Based on the results, the higher peak discharge were determined for rangeland, agriculture and forest land use types, respectively. The generated runoff volume of the rangeland, agriculture, and forest land use types were 84, 12, and 4%, respectively. The implemented method can be used to simulate the effects of land use changes in storm basis to study the temporal flow variations and also to quantify the components of flow hydrograph.

Soil erosion hazard in catchments are the major problems that can affect ecological balance of such areas.This study aimed to determine the optimal use of land to reduce erosion and increase the resident's income of Qushchi watershed in West Azerbaijan province. Income and expenses for the current land uses were calculated with field studies. Damages resulting from the soil erosion were estimated by soil depth equal to the specified land uses. For three different options including the current status of land uses without and with land management, and the standard status of land uses, multi-objective linear programming model was established by LINGO software. Then, the optimization problem of the land use was solved by simplex method. Finally, the best option of land use was determined by comparing erosion rate and its cost in each scenario. Then, the circumstances and the recommended conditions were compared. The results indicated that the current surface area of current land uses is not suitable to reduce erosion and increase income of residents and should change in the optimum conditions. At the optimum level, horticulture area of 408 to 507 (ha), irrigated land area of 169 to 136 (ha) and Dry farming of 636 to 570 (ha) should change while conversion of rangeland area not indispensable. In addition, the results showed that in case of the optimization of land use only, soil erosion and the profitability of the whole area will 0.75 percent decrease and 3.68 percent increase, respectively. In case of land management practices, 42.27 percent will decrease and 21.39 percent increase and with the standard conditions 60.95 percent will decrease and 24.20 percent increase. The results of the sensitivity analysis showed that the change in the horticulture and range land have the greatest impact on increasing profitability and reducing soil erosion of Qushchi watershed.

Nowadays, groundwater quality change and salinization of water resources is a major hazard to developing of agriculture, particularly in dry lands. In this study, the application of Fuzzy Set theory to evaluate quality of groundwater was studied. In recent years, fuzzy-logic-based methods have adjusted to spot uncertainty in environmental problems. In this study, the 49 groundwater samples of Sarab plain in 2014 that analyzed in Hydrogeology laboratory of Tabriz University was used. Values of irrigation indices including the Sodium Absorption Ratio, Permeability Index, the Kelley Ratio, Magnesium Adsorption Ratio, Residual Sodium Bicarbonate, Dissolved Sodium Percentage and Electrical Conductivity as an indicator of total dissolved solids in water are used in this research. Based onFuzzy Water Quality Model, the groundwater quality is classified in three categories; desirable, acceptable and unacceptable. Results showed 41 Samples come in desirable category with certainty level of 65 to 83 percent and 26 samples classified in the acceptable category whose certainty level ranged from 37 to 65.4 percent and the remaining three samples were in rejected category with the maximum certainty level of 23.4 percent.

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 sediment rating curve (SRC), it was tried to use daily suspended data from Ghazaghly station of Gorganroud River, as an average monthly values in Minitab 16 software and finally suspended sediment was predicted for 111 months. In the next step, different combinations of all types of SRC and bias correction factors were used in Excel software to evaluate ability of SRC in suspended sediment estimation. Based on the results of this study, monthly SRC without bias correction factor was the most appropriate SRC models. To compare efficiency of different models in estimating suspended sediment, Root Mean Square Errors (RMSE) and Normalized Mean Square Errors (NMSE) were used. Time series model performance measured by RMSE and NMSE was about 71.34 and 2.48, respectively compared to SRC model with RMSE 220.75 and NMSE 28.62.Results showed a good ability of time series models in estimating average monthly suspended sediment.

Accurate estimation of the re-aerationrate coefficient is very important for the purposes of dissolved oxygen and self-purification modeling in rivers. The main target of this paper is to evaluate 29 commonly used re-aerationrate coefficient prediction equations, in Sefidroud River, North of Iran, as a case study. In this paper, the river’s dissolved oxygen has been modeled involving Streeter- Phelps method. Then the predicted re-aerationrate coefficient results have been compared with four series of collected and measured data of the river. The studied reach of the river has a length of 110km, including 12 water quality sampling stations along that and it is extended from downstream of Sefidroud Dam to the south coast of Caspian Sea.According to the results, among all equations Parkhurst-Pomeroy equation has shown the most accurate prediction of the re-aerationrate coefficient values, with the statistical parameters of Standard Error (SE), Mean Multiplicative Error (MME), Sum of Square of Residuals (SSR) equal to 0.51, 1.05 and 2.35, respectively. Moreover, results indicate that the river has a high Biochemical Oxygen Demand (BOD) and also, a low Self-Purification capacity, during September, which is simultaneous with the seepage of nonpoint drained agricultural pollutions.

The aim of this research is the rainfall prediction of Khorasan Razavi province using artificial neural network. At the first step, the time series of average regional rainfall using Kriging method in the desired time period was calculated. In the next step, time series of climatic predictors including Sea Level Pressure (SLP), Sea Surface Temperature (SST), Sea Surface Pressure gradient (SLP), the difference between sea surface temperature and 1000 hpa level, Sea Surface Temperature gradient (SST), Air Temperature At 700 hpa, thickness between 500 and 1000 hpa level, Relative Humidity at 300 hpa, outgoing long wave radiation, Precipitable water, meridional wind and zonal wind in the different time steps were obtained. The relation between average regional rainfall and climatic predictors using Pearson’s correlation coefficient were calculated. After identifying of the appropriate predictors, artificial neural network model was calibrated from 1970 to 1997. Finally, model was tested in the period between 1998-2007. The model that used in this research has an input layer, one hidden Layer and an output layer. Results reveal those artificial neural networks are promising and efficient. Root mean square error for this model was obtained 6.9 millimeters.