Irrigation
M. Mohammadi Ghaleni; H. Kardan Moghaddam
Abstract
IntroductionThe water quantity and quality has always been one of the main challenges in the issue of allocating water resources for different uses. Water quality management requires the collection and analysis of large amounts of water quality parameters that will be evaluated and concluded. Many tools ...
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IntroductionThe water quantity and quality has always been one of the main challenges in the issue of allocating water resources for different uses. Water quality management requires the collection and analysis of large amounts of water quality parameters that will be evaluated and concluded. Many tools have been found to simplify the evaluation of water quality data, and the water quality index (WQI) is one of these widely used tools. In summary, the WQI can be defined as a number obtained from the combination of several quality parameters based on standards for its extraction. The aim of this study was to develop and introduce the new Surface water Drinking Water Quality Index (SDWQI) adopt the water quality parameters measured on hydrometric stations of Iran. In developing this index, criteria such as the availability of required parameters in most rivers and simple and accurate methods have been considered. Also, the ability to calculate with the minimum general parameters of water quality, simple calculations and in terms of the international standard WHO for drinking is one of the advantages of the introduced index.Materials and MethodsFor this purpose, 12 water quality parameters including Total Dissolved Solids (TDS), Electrical Conductivity (EC), Total Hardness (TH), pH, Chloride (Cl-), Sulfate (SO42-), Carbonate (CO32-), Bicarbonate (HCO3-), Magnesium (Mg2+), Sodium (Na+), Calcium (Ca2+) and Potassium (K+) have been used from Rudbar and Astaneh hydrometric stations located on Sefidroud river. Then initial preprocessing on data e.g. correlation analysis, and multivariate statistical methods including cluster analysis (CA) and principal components analysis (PCA) are used to selecting and weighting of water quality parameters using the “clustering” and “factoextra” packages in R 4.1.1. In order to develop the SDWQI were performed four steps including, parameter selection, sub-indexing, weighting and aggregation of the index. Also, in order to evaluate the index of the present research, the results of the SDWQI have been compared with the WHO drinking water quality index and Schoeller drinking water quality classification.Results and DiscussionCorrelation analysis between water quality parameters shows a significant correlation between TDS, EC and TH parameters and also with Cl-, Ca2+ and Mg2+ parameters at the level of 1% in both Astaneh and Rudbar stations. On the other hand, the lowest values of Pearson correlation coefficient are related to pH and CO32- parameters with other quality parameters. The results of CA indicate that most of the water quality parameters are located in separate clusters. So only the parameters TDS, EC, Cl- and Na+ in both Rudbar and Astaneh stations are in the same cluster. The weights of the parameters showed that TDS and K+ are assigned with the highest and lowest weights equal to 0.163 and 0.031 based on PCA method. Also, PCA results show that first and second principal components covered 59.3% and 67.6% of the total variance of measured water quality parameters in Rudbar and Astaneh stations, respectively. Water quality classification results indicate that (40.5%, 16.4% and 23.7%) and (90.1%, 73.1% and 57.3%) of data in Rudbar and Astaneh stations, respectively, fell into the excellent and good categories for drinking purposes based on Schoeller classification, WHOWQI and SDWQI.ConclusionGenerally, the comparison of the SDWQI with the WHO index and the Schoeller classification shows the rigidity of the new index in the classification of water quality for drinking purposes. Each water quality index developed in order to evaluate the uncertainty of results, should be tested for data with different characteristics in terms of the range of variation with different limit values (minimum and maximum). The index developed in the present study is no exception to this rule and in order to better evaluate the results, it is suggested that to be evaluated and analyzed with data from other hydrometric stations. Another important points that should be considered in using any water quality index, including the present research index, is to examine the allowable limits of water quality parameters that are not considered in these indicators. The results of the study indicated that, two most important steps in the development of a quality index that have a great impact on its results are sub-indexing and weighting of parameters. According to the results, two ideas recommended for future research. One, choosing an appropriate method such as non-deterministic (fuzzy) and intelligent (machine learning) methods to sub-index the parameters and two, to weigh the parameters more effectively, multivariate statistical methods such as clustering, factor analysis and principal component analysis should be used.
M. Nasiri; M. Hamidi; H. Kardan Moghaddam
Abstract
Introduction: The issue of seawater intrusion has become an environmental problem considering the increasing trend in groundwater extraction from coastal aquifers. Increased groundwater exploitation and lack of coastal aquifers management have caused seawater intrusion into coastal aquifer. The intrusion ...
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Introduction: The issue of seawater intrusion has become an environmental problem considering the increasing trend in groundwater extraction from coastal aquifers. Increased groundwater exploitation and lack of coastal aquifers management have caused seawater intrusion into coastal aquifer. The intrusion has led to the salinization of aquifers, causing many problems in the exploitation of water resources. This pumping has continually increased the risk of seawater intrusion and deterioration of freshwater quality in the sari-Neka aquifer. Seawater intrusion limits the usage of groundwater for agriculture, industry, and public water supply.
Materials and Methods: For the present study, Sari-Neka aquifer was selected. The study area is located in the southern shores of the Caspian Sea, in the northern part of Iran. The MODFLOW version 2000 is used to simulate a steady-state and transient groundwater flow system in Sari-Neka aquifer. To simulate solute transport, MT3DMS and SEAWAT are used. In MT3DMS, advection package, dispersion, and source/sink mixing packages are used. The numerical code MT3DMS does not consider the effect the density. Thus, SEAWAT-Variable Density Flow package was initialized. The necessary data for modeling of groundwater flow can be categorized into water resources data, meteorological data, hydrodynamic characterization, topography map, and geological information. To build the flow model, flow type (steady-state and transient state), initial conditions (groundwater level in September 2010 for the steady-state) and type of boundary conditions (general head boundary), flow package (LPF package), temporal discretization (48 monthly stress periods from September 2010 to August 2014 in transient condition) and monthly time steps were assigned to the model. To prepare the flow and transport model grid, the study area was discredited horizontally into 3694 active square cells (500×500 m). The MT3DMS model was used to simulate the qualitative changes on the aquifer surface and the SEAWAT model to simulate the depth of the aquifer. Therefore, the conceptual model of solute transport was prepared by making the necessary changes in the conceptual flow model. September 2010 groundwater level data and TDS and Cl data are taken as the initial conditions in the flow and transport model, respectively. The Caspian Sea bordering the study area in the north is represented by a constant TDS concentration of 35000 mg/l and constant CL282.2 meq/l. In this model, we entered the water heads of the observation wells, hydraulic conductivity, storage coefficient, effective porosity, aquifer discharge, and aquifer recharge, porosity, Coefficient of molecular water diffusion, Longitudinal dispersivity, Horizontal transverse dispersivity, vertical transverse dispersivity.
Results and Discussion: The calibration of the flow model was carried out for both steady and transient conditions using the trial and error approach. Monthly groundwater levels of data from 14 observation wells were used for calibration purposes. Steady-state calibration for the flow model was performed by comparing the observed groundwater levels and calculated values of groundwater levels in September 2010. During calibration, hydraulic conductivity values were adjusted, until groundwater level values calculated by MODFLOW were matched the observed values within an acceptable level of accuracy (±1m). After steady-state calibration, the transient model was simulated for the four year period between September 2010 and August 2014 that was divided into 48 stress periods with monthly time steps. At the end of flow model calibration, the resulting hydraulic conductivity ranged from 5.3 to 21. 6 m/day, while the resulting specific yield values were from %3.4 to % 5.9. The validation flow model was simulated for the period between September 2010 and August 2014 (12 stress periods). The values of the correlation coefficient in the steady-state model, transient model and validation model in the flow model were obtained 0.99, 0.98, and 0.97, respectively. The results illustrate a good agreement between the observed and calculated groundwater levels. The transport model was calibrated using TDS and CL concentration data from September 2010 to August 2014 (8 stress periods) by adjusting parameters affecting the dispersion process. To confirm the accuracy of the model, TDS and CL concentration data from August 2014 to September 2015 were used for validation purposes. By considering the TDS and Cl concentration in September 2010 as the initial condition, the transient model was run. Transport model calibration was achieved through a trial-and-error. The values of the correlation coefficient in the transport model for TDS are obtained 0.83 and 0.87 in the transient model and validation model, respectively. The values of the correlation coefficient in the transport model for CL were obtained 0.82 and 0.86 in the transient model and validation model, respectively.
Conclusion: After the validation of transport model and assuming all the hydrogeologic conditions remain, a predictive 6-year simulation run using SEAWAT model indicates that further seawater intrusion into the coastal aquifers can occur in the study area.
Hamid Kardan Moghaddam; Mohammad Ebrahim Banihabib
Abstract
Introduction: Due to the increase in water consumption resulting from climate change and rapid population growth, overexploitation of groundwater resources take place particularly in arid regions. This increased consumption and reduced groundwater quality is a major problem especially in arid areas of ...
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Introduction: Due to the increase in water consumption resulting from climate change and rapid population growth, overexploitation of groundwater resources take place particularly in arid regions. This increased consumption and reduced groundwater quality is a major problem especially in arid areas of concern among water resources managers and planners. The use of modern simulation tools to evaluate the performance of an aquifer could help the managers and planners to decide. In this research, finite difference method was used to simulate the behavior of the quality and quantity of groundwater.
Materials and Methods: Increasing the concentration of salts in the groundwater aquifers intensifies with severe water withdrawing and causes the uplift of salt water in aquifers. This is much more severe in adjacent aquifers of saline aquifers in deserts and coastal areas. Front influx of saltwater into freshwater aquifers causes interference and disturbance in water quality and complex hydro-chemical reactions occurs in the joint border area including the process of cation, groundwater flow, the reduction of sulfate, the reaction of Carbonatic and changes in the dolomitic calcite. Sarayan Aquifer has a negative balance and the annual groundwater table drawdown of 62 cm.
In this study, Total Dissolved Solids (TDS) as a groundwater quality factor was simulated to investigate the effect of the overexploitation on the saline interface of desert aquifer using MT3D module of GMS model for a period of 5 years with time steps of 6 months. One of the most important steps of the simulation of groundwater quality is to use qualitative model to predict the groundwater level which in this study were performed by quantitative models in two steady and unsteady flow states with time steps of 6 months The four basic steps of a proper modeling of the groundwater quality are sensitivity analysis of the input parameters, calibration of the sensitive parameters of the model, validation of the time step and groundwater quality forecast for the future periods. These modeling steps were carried out for steady and unsteady states by GMS software.
Aquifer hydraulic conductivity and the specific yield of aquifers were selected as two critical parameters of quantitative model in steady and unsteady states. The model was calibrated based on these two parameters and then using pest method, the value of these parameters was finalized. In order to evaluate the response of the aquifer to different periods of droughts, the verification of the model was conducted during the ten periods. The results show that observed water level has suitable correlation with simulated water level. In the same period, the simulation of water quality for TDS parameter carried out using the results of the quantitative model. After identification of sensitive parameters in the model, calibration of the model was carried out taking into account the factor of 0.5 for the ratio of horizontal to vertical distribution, vertical diffusion length of 0.2, 1 meter for effective molecular diffusion coefficient, and 20 for longitudinal diffusion.
Results and Discussion: In the total area of the aquifer, the water demand of all sectors are supplied using groundwater resources. This water withdrawal trend exacerbated the decline in groundwater levels and reduced water quality. Also in the southern strip of the aquifer, there is a desert saline groundwater aquifer, which causes the intrusion of salt water to the aquifer and negative effects on its quality. The factors influencing the salinity of groundwater in the Sarayan Aquifer are geological formations, supplying the aquifer from salty formations in the region, evaporation from the shallow part of the aquifer especially in the southern strip that leaves salt and reducing the volume of water, existence of fine soil in the media of groundwater flow. Front influx is from saltwater desert aquifer to the Sarayan Aquifer. Due to the osmotic pressure of the soil layers in the aquifer, the pollutants transferred from the higher concentration to lower concentration and an influx of salt water into the aquifer will occur from outside of the aquifer. Since the direction of groundwater flow is from the north to the south of the aquifer and salt water intrusion is from the south to the north, the velocity of saltwater intrusion dropped so quickly water. However, overexploitation of groundwater and negative aquifer balance caused uplift of the salt water in aquifer.
Conclusion: Review of the result of forecasted TDS concentration in Sarayan Aquifer, shows an increase in TDS concentration. This increase indicates that there is no potential for more water withdrawing in the southern parts of the aquifer by urban and agricultureal sectors. The variaty of TDS changes between 712 mg/lit in the northern strip of the aquifer to 8500 mg/lit in the southern strip shows that due to the increased concentration of TDS, the border area of water users will be changed. The forecasting of the future status of aquifer water quality showed that continuing withdrawing of water intensifies salt water interference from the desert and concentration of TDS will increase during the next 5 years. To manage aquifer quality and quantity, three scenarios of water withdraw reduction were used. The results are shown restoration of the aquifer quality and quantity using these scenarios.
Therefore the result of this research shows that the management of groundwater is necessary to improve the quality of desert aquifers and prevent salt water interference from desert considering recent droughts.
Parisa Noorbeh; Abbas Roozbahani; Hamid Kardan Moghaddam
Abstract
Introduction: During the last decades, runoff decreasing is observed in our country as many dam reservoirs face water supply crisis even in normal periods. This decreasing trend is mainly due to the uncontrolled withdrawals, lack of supply and demand management as well as droughts. Using different flow ...
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Introduction: During the last decades, runoff decreasing is observed in our country as many dam reservoirs face water supply crisis even in normal periods. This decreasing trend is mainly due to the uncontrolled withdrawals, lack of supply and demand management as well as droughts. Using different flow prediction methods for surface water resources state analysis is important in water resources planning aspects. These methods can provide the possibility of planning for proper operation by using different factors to meet the needs of the region. Due to the stochastic nature of the hydrological processes, various models are used for prediction. Among these models, Bayesian Networks (BNs) probabilistic model has been considered by many researchers in recent years and it has shown the efficiency on these issues. Due to the growth of demand in different sectors and crises caused by drought of the water supply system that has put the basin under water stress, the water shortage has appeared in different sectors. Regarding to the strategic situation of Zayandeh Rood Dam in providing water resources for tap water, industry, agriculture and environmental water rights in Gavkhooni basin, this research presents the development of a model for prediction of Zayandeh Rood Dam annual inflow and hydrological wet and dry periods. Since the uncertainty of the predictions increase when the prediction horizon increases, this factor is the most important challenge of long-term prediction. Using Bayesian Network with reducing this uncertainty, provides the possibility of planning for water resources management, especially for optimal water allocation.
Materials and Methods: In this study for prediction of zayandeh Rood dam inflow five scenarios were defined by applying Bayesian Network Probabilistic approach. According to this, prediction of numerical annual dam inflow (scenario1), annual wet and dry hydrological periods (scenario 2, 3, 4) and range of annual inflow (scenario 5) were performed. For this purpose rainfall, runoff, snow, and discharge of transferred water to the basin from the first and the second tunnel of koohrang and Cheshmeh Langan tunnel were considered as predictor variables and the amount of Zayandeh Rood Dam inflow was selected as predictant for modeling and different conditions of input variable’s learning have been analyzed considering different patterns. Calibration and validation of the model have been done based on observed annual inflow data and the relevant predictors in scenario 1, by using SDI Hydrological drought index and long-term average of inflow to classify the runoff and clustering the other parameters in scenario 2, 3 and 4 and with classification of annual inflow data and other parameters by using clustering in scenario 5. To achieve this target, K-means method has been used for clustering and Davies-Bouldin and Silhouette Width has been used to determine optimal number of clusters.
Results and Discussion: The results of Bayesian Network modeling showed that the scenario 1 has a good potential to predict the dam inflow so that the best pattern of this scenario (considering discharge of first tunnel of Koohrang and Cheshmeh Langan tunnel, Zayandeh Rood natural inflow and rainfall with two years lag time as predictor variables), has had a correlation coefficient of 0.78 between observed and predicted dam inflow and relative error of 0.21 which shows an acceptable accuracy in prediction. Among scenarios 2, 3 and 4 for prediction of wet and dry hydrological periods, scenario 2 in which classification of runoff has been based on the long-term average, in the best pattern (with dam inflow with one-year lag predictor), is able to be predicted up to 75% accuracy. The analysis of the results showed that the scenario 5 is not very accurate in prediction of dam inflow’s range.
Conclusions: The results showed that the Bayesian Network model has a good efficiency to predict annual dam inflow numerically as well as hydrological dry and wet periods. Obtained results from prediction of hydrological dry and wet periods will be effective in better planning of water resources in order to considering possible ways of drought effect reduction. The overall results provide the possibility of water resources planning for the water authorities of this region. Systematic planning leads to optimal use of water and soil resources and helps considerably to analyze and modify the policy or rule curve of this dam for allocating water to downstream especially for agriculture and environment and industry sectors.
Hamid Kardan Moghaddam; Mohammad ebrahim banihabib; Saman Javadi
Abstract
Introduction: Groundwater is predominantly a renewable resource, and when managed properly can ensure a long-term water supply for increasing water demand and for climate change impacted region. Surface water renews as part of the hydrologic cycle in an average time period ranging from approximately ...
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Introduction: Groundwater is predominantly a renewable resource, and when managed properly can ensure a long-term water supply for increasing water demand and for climate change impacted region. Surface water renews as part of the hydrologic cycle in an average time period ranging from approximately 16 days (rivers) to 17 years (lakes and reservoirs); however, the average renewal time for groundwater is approximately 1400 years for aquifers to millions years for some deep fossil groundwater. Groundwater depletion, which is the reduction in the volume of groundwater storage, can lead to land subsidence, negative impacts on water supply, reduction in surface water flow and spring discharges, and loss of wetlands. Water balancing strategy has been considered as one of the most effective options to mitigate the groundwater depletion, and thus the balancing scenarios are applied as main approach to manage ground water sustainably. The purpose of the water balancing strategy in aquifers management is that groundwater level to be returned to the primary water level and to compensate the water resources shortage of aquifers’ storage.
Materials and Methods:
1. Case study: Birjand aquifer with an area of 1100 square kilometers is situated in eastern part of Iran. The location of the aquifer is between 59o 45 and 58o 43 east longitude, and 33o 08 and 32o 34 north latitude.
2. Modeling: Laplace Equation is the basic equation for groundwater flow study in steady or unsteady states. In simulation by using numerical models, the boundary of the model, recharge and discharge resources, evaporation and recharge zones are important elements. After finding the key components of the conceptual model, the MODFLOW software was applied for simulation of groundwater. MODFLOW, which is a computer code that solves the groundwater flow equation and uses finite-difference method, is provided by the U.S. Geological Survey.
3. Sustainability Analysis: In order to achieve the objective of this study, water balancing scenarios should be evaluated for sustainability of the groundwater system using appropriate indices. Here, three indicators of reliability, vulnerability and desirability are proposed and were employed to assess the stability of groundwater system in different balancing scenarios in lumped and distributed forms. The aquifer sustainability index is expressed in Equation 4. In this equation, three indicators of aquifer reliability (Equation 1), aquifer vulnerability (Equation 2) and Desirability (Equation 3) have been used to assess the stability of groundwater system. The aquifer reliability index means in what extent the withdrawal scenario has been able to return the aquifer to its original state using the Equation 1 as follows:
(1)
In which the number of periods where the groundwater level is above the desired level (equilibrium balance) and the total number of time steps in simulation. The vulnerability index indicates the amount of shortage in the groundwater storage and expresses the severity of the system failures using the Equation 2 as follows:
(2)
In this equation, the desired groundwater level at time step t, the groundwater level simulated in t time period for each scenario, the groundwater level without scenarios and n the number of periods where the groundwater level is lower than the desired level. The index of the likelihood of returning the system to a favorable state is presented as an indicator of the desirability of the system using the Equation 3 as follows:.
(3)
In this equation, indicates the f ground water level after the depletion, is the desired level of groundwater and is the groundwater level (without the scenario). After estimating three indicators of reliability, vulnerability and desirability, the sustainability index for each scenario can be appraised using Equation 4.
(4)
In this equation, groundwater sustainability index, reliability index, desirability index and vulnerability index.
Results and Discussion: In this study, six water balancing strategies were employed to reduce 1, 1.5, 2, 2.5, 3 and 3.5 percent water withdrawing for agricultural water use. Results of the simulation of different water balancing strategies demonstrated that with reducing in water use, the stability index has been improved significantly. The improvement changes from 32% increase in the index for 1% water withdrawing reduction scenario to 88% increase in the index for the 3.5% water withdrawing reduction scenario. Moreover, the reviewing of the stability indices of the system in various scenarios reveals that a 2.5% reduction in water use will assistance the aquifer status achieve to a stable state.
Conclusion: In order to manage groundwater withdrawal, it is easier to assess the impact of the water balancing scenarios using the groundwater sustainability index. The review of sustainability indices in the studied aquifer shows that by reducing 1% of the water harvest, 32% of the system's stability increases, and if water harvest reduction reaches 3.5%, the index increases 88%. Considering the distributed potential and possibility of the investigation of different scenarios by proposed indices in this study, they can be applied to assess and manage other similar aquifers.
