Preface: Water and Food Security
H.
Mianabadi
author
text
article
2016
per
Iran-Water Resources Research
Iranian Water Resources Association
1735-2347
11
v.
3
no.
2016
0
1
https://www.iwrr.ir/article_15235_2bbd67c45d5b5a7f1fe3fe5845dae089.pdf
Developing an Operational Water Resources Decision Support System for Zarrineh- Rood Basin with Emphasis on Supply Urmia Lake Water Requirement and Optimal Water Allocation in Agricultural Sector
A.
Abbasi
MSc Graduate in Water Resources Management, Tarbiat Modares University, Tehran, Iran
author
M.
Delavar
Assist-Professor of Tarbiat Modares University, Department of Water Resources Management,Tehran, Iran
author
S.
Morid
Professor of Tarbiat Modares University , Department of Water Resources Management, Tehran, Iran.
author
text
article
2016
per
Zarrineh-Rood is one of the most important rivers of Urmia lake basin. Since, agricultural sector plays a key role in this region, and also in recent year the water resources in this basin is faced with a lot of pressure that lead to many environmental problems in urmia lake. so the evaluation of efficient water allocation to the agricultural crops, especially in drought conditions may have a noticeable impact on the water productivity on the basin. In the current study, attempt to determine the best solution for water and land allocation by developing an operational decision support system using prediction of flow during the next year by support vector machine(SVM) and also an agricultural water allocation model that is based on the old and new FAO crop response to water equations. The results show that each of these methods proposes a different composition of optimal allocation and Cultivated area. Also the FAO-2009 method in comparison to FAO-1979, has led to a higher income and productivity at all levels of drought conditions. In addition, SVM prediction results show an over-90% correlation for flow prediction in both supply all of the Urmia lake water requirement and reduction of lake water allocation based on drought condition. So and holistic model with linking prediction model and water allocation model is so suitable for water resources planning and also for applying management scenario in deferent future conditions. This package can be used as an decision support system for basin water resources management.
Iran-Water Resources Research
Iranian Water Resources Association
1735-2347
11
v.
3
no.
2016
1
16
https://www.iwrr.ir/article_13982_79fb23d1acd9b247b8f440ad8e5ae169.pdf
A Simulation-Optimization Approach for Reducing Seepage Rate in Water Conveyance Canals
M.
Mohammad Rezapour Tabari
Assistant Prof., Department of Engineering, Shahrekord University, Shahrekord
author
M.
Mazak Mari
M.Sc. Student in Civil Engineering - Hydraulic Structures, Shahrkord University, Shahrekord, Iran
author
text
article
2016
per
The optimal design of water conveyance canal sections is one of the guidelines in management of water resources. Design of canal section with minimum loss of water is to consider minimizing seepage and evaporation under uniform flow condition. So far, the optimal design of canal sections was based on inaccurate estimates of seepage rate which needs to be revised. In this study, the seepage from a canal in miscellenouse conditions was modeled using SEEP/W software. The accurate soft model between input and output data was then extracted. Comparing the extracted soft model with other empirical equation, indicate the high accuracy of the selected soft model. This model were then used in optimization process with the aim of minimizing the canal water loss. The results are presented in terms of dimensionless graphs which made a simple design of canal dimensions possible. Comparing the results with other similar studies indicated the significant changes in optimal canal dimension.
Iran-Water Resources Research
Iranian Water Resources Association
1735-2347
11
v.
3
no.
2016
17
30
https://www.iwrr.ir/article_13985_770c85f978ca9fa699bb198acebef99f.pdf
Using Unsupervised Estimator Technique to Predict Reference Crop Evapotranspiration
F.
Farsadnia
Ph.D. Student in irrigation and drainage, Department of Water EngineeringCollege of Agriculture, Ferdowsi University of Mashhad, Mashhad, Iran.
author
S.
Zahmati
M.Sc. Student, Department of Water Engineering, College of Agriculture
author
B.
Ghahreman
Professor, Department of Water Engineering, College of Agriculture, Ferdowsi University of Mashhad, Mashhad, Iran
author
A.R.
Moghaddam Nia
Associate Professor of Hydrology, Faculty of Natural Resources, University of Tehran, Karaj, Iran.
author
text
article
2016
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Evapotranspiration is the main component of hydrologic cycle and has an important role in crop water requirement estimations, water balances studies, and water resource management. There are a lot of direct and indirect methods to estimate reference crop evapotranspiration, but each has some limitations. For example, limitations that can be mentioned for direct measuring are the insufficient precision in measuring devices and the scale problems. An indirect method like Penman-Monteith on the other hand needs a lot of daily climatic parameters. This research tried to use self-organizing maps as an unsupervised artificial neural network method to predict evapotranspiration by minimum meteorological data input. Based on fuzzy clustering indices, evapotranspiration values in the study area, Mashhad plain, are divided into two clusters with low and high ETo coincided with the climate of the area. Also, in order to validate the model, statistical indices containing root mean square error, determination coefficient, and Nash–Sutcliffe model efficiency coefficient are used and the results are compared with the experimental models output. The results showed that even the simplest SOM model which employs mean temperature and maximum sunshine duration as input have less errors compared to the experimental equations.
Iran-Water Resources Research
Iranian Water Resources Association
1735-2347
11
v.
3
no.
2016
31
42
https://www.iwrr.ir/article_13988_ffa21f03094a4c7a5d926271e5c9ce3f.pdf
Developing an Optimal Groundwater Allocation Model Considering Stakeholder Interactions; Application of Fallback Bargaining Models
M.R.
Alizadeh
M.Sc. Student, Department of Engineering, Civil and Environmental Engineering Division, Shiraz University,شیراز, Iran.
author
M.R.
Nikoo
Assistant Professor, Department of Engineering, Civil and Environmental Engineering Division, Shiraz University, شیراز, Iran
author
Gh.R.
Rakhshandehrou
Professor, Department of Engineering, Civil and Environmental Engineering Division, Shiraz University, Shiraz, Iran
author
text
article
2016
per
In last few decades conflict-resolution models are being increasingly used in water resource management for cases such as the groundwater problems as an appropriate approach to consider the oppositions and trade-offs between the stakeholders involved in the conflict and to reach to an applicable optimal resolution. In this paper, by integrating simulation-optimization models of groundwater exploitation and bargaining methods, the optimal allocation scenarios are derived taking into account the preferences of the stakeholders and social criteria such as justice. Trade-off Pareto front between the rival objectives was computed through linking the NSGA-II multi-objective optimization model and M5P meta model which was trained and validated based on MODFLOW simulation results. Monte-Carlo method was used to develop a database for training and validating meta models for different allocation scenarios. Considering multi-objective nature of the problem, the best solutions on Pareto fronts were selected using fallback bargaining models. The effectiveness of the proposed methodology was verified in a case study performed on Daryan aquifer, Fars province, Iran. Results indicated that the total groundwater withdrawal after applying the optimal scenarios of allocation was reduced approximately 56% which resulted in the mean water level uplift of 4.2 meters in the aquifer
Iran-Water Resources Research
Iranian Water Resources Association
1735-2347
11
v.
3
no.
2016
43
56
https://www.iwrr.ir/article_14006_2eb17f51366f0d5bef2382815c8611ac.pdf
Economic Assessment of Change in Cropping Pattern in Siminehrud Sub-basin to Improve Agricultural Water Management: An Effort to Restore Urmia Lake Using PES Scheme
A.
Daneshi
MSc. Graduate in Watershed Management Engineering, Faculty of Natural Resources, Tarbiat Modares University, Nour, Iran
author
M.
Vafakhah
Associate Professor, Watershed Management Engineering Group, Faculty of Natural Resources, Tarbiat Modarres University, Nour, Iran
author
M.
Panahi
Associate Professor, Science and Research Branch, Islamic Azad University, Tehran, Iran
author
text
article
2016
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Due to the drying up issue of Urmia Lake, currently several options are under review. Decreasing water demand in agricultural sector through programs like “change in cropping patterns” may undoubtedly be considered as a notable option which requires an economic assessment of further implications of it. In the present research, based on Payment for Ecosystem Services (PES) policy tool, we attempted to analyze the results of a technical and economic assessment of likely changes in cropping pattern in a sub-basin of Urmia Lake. For this purpose, first a GIS based land use map was prepared and the suitable areas was identified. Then all information required for assessing the PES scheme were collected according to an Interview-Questionnaire mixed technique. During the field survey phase, 398 questionnaires were completed by farmers in Siminehrud sub-basin. Among various options of PES, payment to farmers to encourage them to change the cropping pattern using three oily plant species (soya, canola and safflower) has been proposed. Then the results have been analyzed in terms of economic impacts. The findings of this study showed that only changing the crop pattern to consider safflower is economically feasible and also technically efficient.
Iran-Water Resources Research
Iranian Water Resources Association
1735-2347
11
v.
3
no.
2016
57
68
https://www.iwrr.ir/article_14007_94d18051585a1fccb106f129af0c560a.pdf
A Comparison among the Performance of the Stochastic Models in Generating the Monthly Streamflow and Rainfall Data
M.
Montaseri
Associate Professor, Department of Water Engineering, Urmia University, Urmia, Iran,
author
J.
Heydari
Department of Water Engineering, Urmia University, Urmia, Iran
author
text
article
2016
per
Synthetic data generation models have been recognized as useful tools to predict and generate alternative time series or long-term series throughout the studies conducted in the domain of water resources management. Accordingly, these models have widely been used by different researchers across the world. In the recent decades, these models have been developed to generate annual, monthly, and daily rainfall or river flow data. Among the synthetic data generated, monthly data are of great importance since they are used in the critical and important studies in the field of water resource systems, such as storage tanks and drought monitoring. Accordingly, the utilization of the monthly synthetic data models leads to more detailed analyses about the real performance of such systems. On the other hand, the theoretical basis of different stochastic models is the generation of diverse monthly data and the performance of these models can remarkably be affected by this fact. Therefore, one can argue that selecting an appropriate model is one of the major concerns of water resources experts. As such, this study made use of the Monte Carlo simulation method to compare and assess the performance of four types of non-parametric Bootstrap models as well as parametric models of Valencia-Schaake, Thomas-Fiering, and Fragment in monthly synthetic data generation. To do this, the monthly flow data of Nazluchay, Shaharchay, and Barandozchay rivers, located at the Western Azerbaijan province in the North West of Iran, were analyzed over a 47-year period. Then, 1000 synthetic time series of monthly flows for these rivers were generated and used for each of the desired seven models over a 47-year period thereof. The results indicated that, compared to other models, the Valencia-Schaake distribution model had a very high performance in terms of all well-known assessment statistical indicators.
Iran-Water Resources Research
Iranian Water Resources Association
1735-2347
11
v.
3
no.
2016
69
84
https://www.iwrr.ir/article_14008_962114e602ad4d40bc699bae7fc92bca.pdf
Spatio-temporal Groundwater Level Prediction Using Hybrid Genetic-Kriging Model
(Case Study: Hadishahr Plain)
M.H.
Habibi
MSc. Student of Hydrogeology, Department of Earth Science, University of Tabriz, Tabriz, Iran.
author
A.A.
Nadiri
Assistant Professor, Department of Earth Science, Faculty of the Natural Resources, University of Tabriz, Tabriz, Iran
author
A.
Asghari Moghaddam
Professor, Department of Earth Science, Faculty of the Natural Resources, University of Tabriz, Tabriz, Iran
author
text
article
2016
per
In recent decades, the application of intelligent evolutionary methods and hybrid models for forecasting groundwater spatiotemporal fluctuations were more focused by researchers. Genetic algorithm and Neuro-Fuzzy are new methods which are applicable in single and hybrid forms for forecasting in complex and nonlinear problems. In this research, aforementioned methods were applied to study the Hadishahr plain aquifer. The Hadishahr plain is located in the north of East Azerbaijan province and it is a part of Julfa–Duzal study area. This aquifer suffers from groundwater level declination due to groundwater withdrawal increase. To achieve practical ways for spatio-temporal groundwater level forecasting, the artificial intelligence methods such as neuro–fuzzy (NF), genetic programming (GP) and combination their best model with geostatistical methods were used. Precipitation and evaporation in t0 time step and groundwater table in t0-1 time step were the inputs to the Neuro-Fuzzy and Genetic Programming. The results showed that the average RMSE of selective piezometers for genetic programming and neuro-fuzzy were 19 and 23 centimeter in the test step, respectively. Then, genetic programming was used to present a hybrid model in combination with the geostatistical model (kriging). Finally, the hybrid model “genetic - kriging” were applied to predict the spatiotemporal prediction of the groundwater level. The simulated results were extended to the whole plain and the area with no groundwater level monitoring network.
Iran-Water Resources Research
Iranian Water Resources Association
1735-2347
11
v.
3
no.
2016
85
99
https://www.iwrr.ir/article_14009_1eaba82f2055b7ee746423ed1be21e3c.pdf
Hazard Management of Inundation and Pollutants in Urban Floods Using Optimal Conventional and Novel Strategies
M.
Karami
MSc graduate, Department of Civil and Environmental Engineering, Amirkabir University of Technology, Iran
author
A.
Ardeshir
Associate Professor, Department of Civil and Environmental Engineering, Amirkabir University of Technology, Iran.
author
K.
Behzadian
Assistant Professor, Environmental Research Center, Amirkabir University of Technology, Iran.
author
text
article
2016
per
Urbanisation by decreasing in pervious areas would result in increase in the risk of flood inundation and cause more discharge of pollutants into receiving water bodies. This paper presents the management of urban flood hazard in terms of inundation and pollutants discharge into receiving water bodies using a combination of the conventional and novel techniques. Conventional techniques include increasing the dimension of conduits as well as decreasing their roughness. Novel techniques on the other hand include bio-retention systems, pervious pavements, infiltration trenches, and detention ponds in urban drainage networks. In this study the multi-objective optimization model is developed using multi-objective genetic algorithm coupled with a simulation model of urban drainage system using SWMM software. The objectives are to minimize the economic cost, the inundation flood hazard, and the expected pollution reaching the receiving waters. Pollution control consider pollutants of TSS, TN, and TP. The suggested methodology was applied to a case study for the urban drainage system of Golestan city in Tehran Province. Results indicated that applying the optimal methods can considerably decrease the expected flood and pollutants. Results of Pareto front showed that indirect relation exists between the solutions of optimal control of expected inundation and the optimal control of expected pollutants in receiving water bodies.
Iran-Water Resources Research
Iranian Water Resources Association
1735-2347
11
v.
3
no.
2016
100
112
https://www.iwrr.ir/article_14012_dc92efb565f7ffd17c64a7e61f12a3f6.pdf
Comparison and Evaluation of Different Sources of Uncertainty in the Study of Climate Change Impact on Runoff in Semi-arid Basins
(Case study: Azam Harat River Basin)
M.
Yaghobi
M.Sc. Graduate, Department of Water Science and Engineering, College of Abouraihan, University of Tehran, Pakdasht, Iran.
author
A.
Massah Bavani
Assistant Professor, Department of Water Science and Engineering, College of Abouraihan, University of Tehran, Pakdasht, Iran
author
text
article
2016
per
Present study assess the impact of climate change on the AZAM-HARAT River basin runoff in the 2015-2030 period considering the sources of uncertainty in adjustment of model parameters for two rainfall-runoff models of IHACRES and HEC-HMS, as well as A1B, A2 and B1 greenhouse gasses emission scenarios of AOGCM models, and LARS-WG and SDSM downscaling models. First in calibration and verification of rainfall-runoff models, sensitivity analysis of the model parameters was done. Then the climatic variables of 15 AOGCM models and climatic scenario were downscaled using LARS-WG model and these data were introduced to each of the hydrological models to determine the runoff variation ranges. Results showed that the temperature in the future period will increase about 1.5 ̊C and also the amount and distribution of the rainfall will vary greatly. These variations in rainfall will result in changes in the runoff. The results showed that the uncertainty related to hydrological models in some months is higher than AOGCM models and greenhouse gases emission scenarios which is due to the critical parameters in the structure of the hydrological models. To assess downscaling uncertainty, data of HadCM3-A2 model were downscaled using LARS-WG and SDSM models. The results showed that the uncertainty of hydrological models is much greater than that in the downscaling methods. It is also shown that the uncertainties in the AOGCM models are larger than greenhouse gases emissions scenarios.
Iran-Water Resources Research
Iranian Water Resources Association
1735-2347
11
v.
3
no.
2016
113
130
https://www.iwrr.ir/article_14014_8df306ec9c5e23cebf38ec9b03930f7b.pdf
Estimation of Daily Reference Evapotranspiration with Limited Meteorological Data in Selected Iran’s Semi-Arid Climates
B.
Bakhtiari
Assistant Prof, Department of Water Engineering, College of Agriculture, Shahid Bahonar University of Kerman, Kerman, Iran.
author
A.
Mohebbi Dehaghani
M.Sc. graduate in Water Resources Engineering, Department of Water Engineering, College of Agriculture, Shahid Bahonar University of Kerman, Kerman, Iran
author
K.
Qaderi
Assistant Professor, Department of Water Engineering, College of Agriculture, Shahid Bahonar University of Kerman, Kerman, Iran
author
text
article
2016
per
Accurate estimation of evapotranspiration has a great influence on water resources management and planning, especially in arid and semi-arid areas. Different methods have been presented by researchers for evapotranspiration estimation. These include a variety of empirical equations and data-driven methods. In this study to estimate the daily reference evapotranspiration at eight semi-arid climates in Iran, three methods based on the adaptive network-based fuzzy inference system (ANFIS), support vector machines (SVM), and model tree (M5) as well as five empirical equation were used. Meteorological data including maximum and minimum temperatures, relative humidity, wind speed, and the sunshine hours were used. Eleven different combinations of these variables have been used as input variables in data-driven methods for evapotranspiration modeling for the period of 1980 to 2009. Eighty percent of the data were used for the training and twenty percent were used to test the models. The results were compared with those of the standard Penman-Monteith FAO-56 equation. Performance of the methods was evaluated using statistical indices of mean square of error (RMSE), coefficient of determination (R2), and index of agreement (d). Support vector machines and adaptive networks based on fuzzy inference system methods presented best performance with RMSE between 0.24~1.55 (mm.day-1) in nine combination of meteorological variables. RMSE of empirical equations varied between 0.71~5.96 (mm day-1). Blaney-Criddle and McGunness-Bordne equation presented the highest accuracy in most stations. M5 model has a lower performance compared to ANFIS and SVM methods in the studied climates.
Iran-Water Resources Research
Iranian Water Resources Association
1735-2347
11
v.
3
no.
2016
131
144
https://www.iwrr.ir/article_14017_83512b9cd3a578620067742ba2af01c0.pdf
Assessment of Climate Change Impacts on Aquatic Habitat Suitability in Kordan River
Case Study: Oxynemacheilus bergianus
R.
Morid
M.Sc. student, Land Use Assessment and Planning Group, Energy and Environment Faculty, Islamic Azad University Science and Research Branch, Iran
author
S.
Igderi
Associated Professor, Aquaculture Group, Faculty of Natural Resources, University of Tehran, Iran
author
M.
Delavar
Assistant Professor, Water Resources Department, Faculty of Agriculture, Tarbiat Modares University, Tehran, Iran
author
text
article
2016
per
Climate change has significant impacts on living organisms and the environment. Therefore, it is important to predict and assess its impacts in order to reduce vulnerability and also to confront to climate change. Water resources will be the first resources to be affected by climate change and the rivers are considered as vital ecosystems in this situation. So assessing the impacts of the climate change on animal and plant species status in the rivers can provide a projection of the ecosystem. This study attempted to evaluate the effect of climate change on one of the southern Alborz water systems, Kordan River, and to estimate the changes in the aquatic Habitat Suitability Index (HIS) along a two-kilometer reach of the river. In this regard the future climate change in the region was first projected using HadCM3 general circulation model in three 30-year periods of 2011-2040, 2041-2070, and 2071-2099 considering A2 and B1 scenarios. Also the SWAT model was used to simulate effects of climate change on the river flow and the water temperature. Results showed that the changes in temperature and precipitation would have a decreasing effect on the river flow and the water temperature during the future periods; the average flow would decrease from 3.3 cms in the base period to 2.66 and 2.8 cms in A2 and B1 scenarios, respectively. Also it is indicated that the climate change has a significant impact on habitat suitability index for Oxynemacheilus bergianus. Assessing the rational distribution curve would also declare a 20 to 25 decrease in the HSI equaling 0.4 to 0.6 in the period of 2071 to 2099.
Iran-Water Resources Research
Iranian Water Resources Association
1735-2347
11
v.
3
no.
2016
145
158
https://www.iwrr.ir/article_14018_3b1e2decb9b6067d8771e39bc6eb8c1f.pdf
Survey of Spatiotemporal Impact of Land Use on Water Quality in Chaghakhor Wetland Using IRWQI Index and Statistical Methods
J.
Samadi
Engineering Graduate of Fisheries Department, Faculty of Natural Resources,
Isfahan University of Technology & Member of Young Researchers and Elite Club of Islamic Azad University, Naragh Branch, Iran.
author
text
article
2016
per
Purpose of this study is to use the physicochemical parameters (DO, pH, NO3-, PO4-3, TDS, and TSI) and water quality index of IRWQI to assess the pollution and spatiotemporal impact of land use on water quality in Chaghakhor wetland in Chaharmahal-o-Bakhtiari province, Iran. Twelve stations were selected for the sampling and measurement based on a systematic non-random method. At first, index model of IRWQI was prepared in GIS environment based on average of surface and depth of qualitative parameters by interpolation functions. Results demonstrated that IRWQI index with the Pearson correlation coefficient of 0.78 and the parameters of PO4-3, NO3- and TDS with the partial correlation coefficients of -0.82, -0.64, and 0.62, respectively were caused by the sewage pollution of farmlands and residential area in the south and the west half of the wetland. Also using the GIS based spatiotemporal impacts of the land use using statistical methods showed that the highest impact on the water quality of Coghakhor Wetland is created in spring and early autumn with correlation coefficients of 0.70 and 0.59. The lowest impact is reached in the summer with correlation coefficient of less than 0.1. Maximum trophic state and the worst quality status is resulted for the surface water temperature of 10.5 to 13.5 °C and in the first half of autumn and spring. The status was shown as moderate to fairly good with values of 50 to 61 for this condition which is due to the increased agricultural activities, floods, and seasonal rainfalls. The best quality is reported for water surface temperatures of either more than 19.5 °C or less than 6 °C in the summer and the first half of winter. The Status for this condition was 70 to 82 which is due to the decreased agricultural activities, floods, and the drainage resulted from the seasonal rainfalls.
Iran-Water Resources Research
Iranian Water Resources Association
1735-2347
11
v.
3
no.
2016
159
171
https://www.iwrr.ir/article_14019_4245aa9ad99c0c6ac944c5f29b3699d6.pdf
Prediction of Avulsion Phenomenon on Alluvial Fans Using FLO-2D Hydraulic Model
Z.
Mollaei
- M.Sc. graduate, Drainage and Irrigation Engineering, Ferdowsi University of Mashhad, Mashhad, Iran
author
H.
Madani
M.Sc. graduate, Water Resources Management, Ferdowsi University of Mashhad, Mashhad, Iran
author
A.R.
Farid Hosseini
Assistant Professor, Department of Water Engineering, Ferdowsi University of Mashhad, Mashhad, Iran
author
K.
Davary
Associated Professor, Department of Water Engineering, Ferdowsi University of Mashhad, Mashhad, Iran
author
text
article
2016
per
The risk of flood incorporated with the potential of channel shift across the width of alluvial fans may cause substantial damages. This shift is called avulsion. The earlier methods of determining avulsion on alluvial fans (such as FAN mathematical model) were received negative criticism and did not give accurate results. Given that flow on alluvial fans is two-dimensional, FLO-2D model was used in this research to identify the areas with avulsion potential. The avulsion phenomenon was studied on two alluvial fans in Iran; one in the North-east (Ferizi) and one in the south-east (Sarbaz). Using this model, flow was simulated based on 100 and 500-year discharges. Then areas with avulsion potential were identified by plotting the results of the model on the recent aerial photographs of the alluvial fans. Results showed that massive evulsions had happened in the areas with no expectation of such phenomenon. Thus, using this method can help to identify areas with avulsion risk and reduce the potential damages caused by it.
Iran-Water Resources Research
Iranian Water Resources Association
1735-2347
11
v.
3
no.
2016
172
181
https://www.iwrr.ir/article_14020_e182d8f318552bb26b0d2a38199be366.pdf
Evaluation of Cokriging and Neurofuzzy Model Performance in Estimating the Nitrate Concentration in Karaj Aquifer
E.
Poor Farah Abadi
MSC graduate in Water Resources Engineering, Agriculture and Natural Resources Campus, University of Tehran, Karaj, Iran
author
M.
Kholghi
Associate Professor, Department of Irrigation and Reclamation Engineering, Agriculture and Natural Resources Campus, University of Tehran, Karaj
author
text
article
2016
per
Recently, new techniques based on geostatistical methods have been used to estimate groundwater nitrate concentrations in unmeasured areas as well as to determine new sampling locations. In this study the Cokriging and Anfis models have been developed in interpolation step for nitrate parameter spatiovariation in Karaj aquifer. Nitrate concentrations have been estimated annually using samples derived from 179 drinking water wells. For this purpose, values of nitrate concentration in 1384 (2005) have been considered as the initial values. Nitrate concentration in 1379 to 1383 (200-2004) have been applied as the covariate for cokriging model and as the input parameters for neuro fuzzy model. The comparison between cokriging and Anfis results showed that in five neuro fuzzy models, the error function are less than the cokrihging model, especially for the data of 2004.
Iran-Water Resources Research
Iranian Water Resources Association
1735-2347
11
v.
3
no.
2016
182
186
https://www.iwrr.ir/article_14021_61c5ec28ea0d1fe36c19fc9d22d88e34.pdf