Irrigation
M. Jamshidi Avanaki; , K. Ebrahimi; S.S. Hashemi
Abstract
IntroductionDrought, as an environmental crisis, not only impacts ecosystems but also poses risks to human activities and has significant negative effects. The occurrence of intermittent and prolonged droughts, along with significant fluctuations in climate, exacerbates water scarcity, particularly in ...
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IntroductionDrought, as an environmental crisis, not only impacts ecosystems but also poses risks to human activities and has significant negative effects. The occurrence of intermittent and prolonged droughts, along with significant fluctuations in climate, exacerbates water scarcity, particularly in surface water resources; thus, groundwater resources play a key role as a vital source for supplying water for various consumption needs.Groundwater drought is one of the serious and increasing challenges that has been acutely felt in recent years. Climate change and increasing water demand in agricultural and industrial sectors has led to increase dextraction from groundwater sources, significantly affecting many plains and groundwater resources in the country, resulting in severe depletion. This has consequently led to water crises and recurrent droughts. Therefore, understanding the relationship between drought and the status of groundwater resources is crucial. This issue not only impacts agriculture and food security but also has negative effects on public health, the economy, and the environment. For this reason, proper and sustainable management of these resources in the face of drought challenges is essential. Materials and MethodsThe examination of hydrogeological droughts and the monitoring of groundwater levels is essential for providing appropriate solutions for the protection and management of water resources.In the present study, the Groundwater Resource Index (GRI) was used to assess groundwater drought in the Qazvin Plain. Additionally, to explore the relationship between the GRI and the Standardized Precipitation Index (SPI) across different time scales, the correlation coefficient between the two indices was calculated. Subsequently, the GRI was localized within the plain by analyzing its values across various monitoring wells. Results and DiscussionThe high correlation between the GRI index and the SPI drought index over a 48-month timeframe indicated that groundwater resources in the Qazvin plain were influenced by both wet and dry weather phenomena, with a time lag of approximately three to six months before meteorological drought translated into groundwater drought. Eslamian et al. (2009) also reported a three-month time lag for the effects of drought on the groundwater resources of the Qazvin, Buin Zahra, and Hamadan plains in their research. ConclusionThe localization study of the GRI index in the Qazvin Plain region concluded that the index is highly responsive for assessing and evaluating groundwater drought. It effectively identified wet and dry years and showed a strong alignment with the behavior of the groundwater table. The analysis of drought during the years from 1996-2001 also illustrated that the impacts of drought continued into subsequent years on groundwater resources, and according to the GRI index, the decline in groundwater levels persisted in later years. This was evident even with increased precipitation in 2002 and thereafter, where we continued to witness declines and the ongoing trend of groundwater drought. AcknowledgmentsWe would like to thank the University of Tehran and the Water Resources Management Company of Iran for providing the necessary facilities to conduct this research study and prepare relevant papers.
S.M. Hosseini-Moghari; K. Ebrahimi
Abstract
Introduction: Groundwater resources are the main source of fresh water in many parts of Iran. Groundwater resources are limited in quantity and recently due to increase of withdrawal, these resources are facing great stress. Considering groundwater resources scarcity, maintaining the quality of them ...
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Introduction: Groundwater resources are the main source of fresh water in many parts of Iran. Groundwater resources are limited in quantity and recently due to increase of withdrawal, these resources are facing great stress. Considering groundwater resources scarcity, maintaining the quality of them are vital. Traditional methods to evaluate water quality insist on determining water quality parameter and comparison between them and available standards. The decisions in these methods rely on just specific parameters, in order to overcome this issue, water quality indices (WQIs) are developed. Water quality indexes include a range of water quality parameters and using mathematical operation represent an index to classify water quality. Applying the classic WQI will cause deterministic and inflexible classifications associated with uncertainties and inaccuracies in knowledge and data. To overcome this shortcoming, using the fuzzy logic in water resources problems under uncertainty is highly recommended. In this paper, two approaches are adopted to assess the water quality status of the groundwater resources of a case study. The first approach determined the classification of water samples, whilst the second one focused on uncertainty of classification analysis with the aid of fuzzy logic. In this regard, the paper emphasizes on possibility of water quality assessment by developing a fuzzy-based quality index even if required parameters are inadequate.
Materials and Methods: The case study is located in the northwest of Markazi province, Saveh Plain covers an area of 3245 km2 and lies between 34º45′-35º03′N latitude and 50º08′-50º50′E longitudes. The average height of the study area is 1108 meter above mean sea level. The average precipitation amount is 213 mm while the mean annual temperature is 18.2oC. To provide a composite influence from individual water quality parameters on total water quality, WQI is employed. In other words, WQI is a weighting average of multiple parameters. The present research used nine water quality parameters (Table 2). In this paper Fuzzy Water Quality Indices (FWQIs) have been developed, involving fuzzy inference system (FIS), based on Mamdani Implication. Firstly, five linguistic scales, namely: Excellent, Good, Poor, Very poor, and Uselessness were taken into account, and then, with respect to ‘If→then’ rules the FWQIs were developed. Later, the seven developed FIS-based indexes were compared with a deterministic water quality index. Indeed seven FWQIs based on different water quality available parameters have been developed. Then developed indices were used to evaluate the water quality of 17 wells of Saveh Plain, Iran.
Results and Discussion: The present study analysed groundwater quality status of 17 wells of Saveh Plain using FWQI and WQI. Based on the driven results from WQI and its developed fuzzy index, similar performance was observed in most of the cases. Both of them indicated that the water quality in six wells including NO.1, 2, 6, 12, 13, and 17 were suitable for drinking. Due to the fact that the values of both indexes were under 100, the mentioned wells could be considered as drinking water supplies. The indexes illustrated the very poor quality of wells NO.7, 9, 10, 11, 14, and 16. As a result, according to FWQI1 along with WQI, nearly 35% of wells have proper drinking water quality, while approximately 30% and 35% of them suffered from poor and very poor quality, respectively. The overall picture of water quality within the study area was not satisfying, hence, an accurate site selection for discovering water recourses with appropriate quality for drinking purpose must be responsible authorities’ priority. Analysis of FWQI2, FWQI3 and FWQI4 revealed that elimination of the parameters slightly changed the result of FWQI2; however, FWQI3 and FWQI4 did not vary considerably. Thus, Cl influenced the water quality slightly, but Ca and K did not affect the water quality of the plain. The results showed that inexistence of one of the mentioned parameters would not affect the computational process adversely. A glance at FWQI5, FWQI6 and FWQI7 revealed the improper performance of FWQI5 to show wells’ water quality status. Throughout the FWQI5 evaluation process, all the wells’ water quality stood in Excellent category. Due to the considerable values of TDS in the Plain, elimination of this parameter in FWQI5 caused inappropriate evaluation. Hence, whenever a case study deals with a high value of a specific quality parameter, elimination of that parameter would negatively demote validation of the analysis. Figures (3)-(6) represented the results of WQI along with seven FWQIs for 17 utilized wells’ water quality assessment in the study area during the proposed periods.
Conclusion: Throughout the present study, the capability of seven FIS-based indexing procedures in modelling the water quality analysis of 17 wells of Save Plain was discussed. The proposed FWQIs were developed on the basis of Mamdani approach by applying triangular and trapezoidal membership functions to determine the groundwater quality of the case study according to the nine parameters. The results revealed that FWQI1-4 outperformed others. On the other hand, FWQI5-7 which eliminated three out of the nine parameters, did not made a valid contribution to the computational context. This might be related to omitting the effective water quality parameters from the inputs of the model. The results also illustrated that, only six out of 17 wells of the region could be considered as suitable sources for the drinking purpose. The water quality status in five wells was not satisfying, and six wells were plagued by very poor quality of water.
F. Modaresi; Sh. Araghinejad; K. Ebrahimi; M. Kholghy
Abstract
Abstract
Climate change means a significant change in the long-term weather of a region in comparison with what has been observed during a long term period. Precipitation and minimum and maximum temperature are three variables which are affected directly by the climate change. Furthermore, the water ...
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Abstract
Climate change means a significant change in the long-term weather of a region in comparison with what has been observed during a long term period. Precipitation and minimum and maximum temperature are three variables which are affected directly by the climate change. Furthermore, the water yield of a river is one of the most important hydrological variables of a Basin which is affected by variations of the climate variables. In this research, the mentioned variables have been used to assess the climate change, and precipitation, the most important factor affecting water yield, has been used to investigate the climate change effect on the water yield of the river. A conditional probability distribution function has been used to determine the quantity of the annual water yield of a river. This approach gives a variation range demonstrating the error existing in the results. In this paper, the Gorganroud basin is selected as the case study. Precipitation and minimum and maximum temperature of the basin during the 1977-2006 have been compared with the output of scenarios of all Global Circulation models to select the most appropriate model to forecast the future climate of this basin. The obtained results show that the scenario B2 of HadCM3 model is the most appropriate scenario for this case study. If this scenario happen in the next 30 years, the quantity of water yield in Tamr station adjacent to Gorganroud river, located upstream of Boostan, Golestan and Voshmgir dams, will decrease 1.38% and 1.33% in water yield volume of return periods of 50 and 100 years, respectively. But, if the existing trend in historical data continues in the next 30 years, the quantity of water yield at this station will increase 14.94% and 14.55% in water yield volume of return periods of 50 and 100 years, respectively.
Keywords: Water yield, Climate change, Conditional probability distribution function, Gorganroud
M. Mohammadi Ghaleni; O. B ozorg Hadad; K. Ebrahimi
Abstract
Abstract
The Muskingum method is frequently used to route floods in Hydrology. However, application of the model is still difficult because of the parameter estimation’s. Recently, some of heuristic methods have been used in order to estimate the nonlinear Muskingum model. This paper presents a ...
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Abstract
The Muskingum method is frequently used to route floods in Hydrology. However, application of the model is still difficult because of the parameter estimation’s. Recently, some of heuristic methods have been used in order to estimate the nonlinear Muskingum model. This paper presents a efficient heuristic algorithm, Simulated Annealing, which has been used to estimate the three parameters nonlinear Muskingum model. The results show the high accuracy of the algorithm in estimation of the parameters, so that it is obtained terms of the sum of the square of the deviations between the observed and routed outflows (SSQ), the sum of the absolute value of the deviations between the observed and routed outflows (SAD), deviations of peak of routed and actual flows (DPO), and deviations of peak time of routed and actual outflow (DPOT), 36/78, 23/44, 0/9 and 0, respectively. As Value of the SSQ has obtained equal its value Harmony Search method that is the best answer between the heuristic Optimization Algorithms that has been used so far. Finally, the performance of the new proposed method has been compared with other methods. The results showed that the height efficiency of the algorithm in parameter optimization of the nonlinear Muskingum model. SA algorithm in the second example the Karun River flood test and the results were compared with the GA method. The results showed that SA algorithms estimate is better than the GA method. As the error sum of squares (SSQ) before 4947/06, the total absolute error (SAD) against 412/8, Dubai actual peak was 1182 cubic meters per second and peak Routing 1191 was obtained by the difference of these two (DPO) times less a percentage error and the occurrence of different steps in Dubai when the real peak and has Routing (DPOT) zero respectively. Finally, this research capability in the blank verses optimal SA algorithm making Muskingum model parameters indicated therefore, to use SA algorithm in this area is recommended.
Keywords: Flood Routing, Muskingum Model, Optimization, Simulated Annealing Algorithm
F. Modaresi; Sh. Araghinejad; K. Ebrahimi; M. Kholghy
Abstract
Abstract
Despite the significance of climate change assessment on regional planning of a basin, most of the previous researches have been focused on the point assessment of this phenomenon. This paper uses statistical tests as well as regional assessment to investigate the impact of climate change on ...
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Abstract
Despite the significance of climate change assessment on regional planning of a basin, most of the previous researches have been focused on the point assessment of this phenomenon. This paper uses statistical tests as well as regional assessment to investigate the impact of climate change on the Gorganroud-Gharehsou basin. In this regard, various tests including Man-Kendall, Cumulating Deviation, and Worsley’s Liklyhood Ratio Test have been applied to recognize the homogeneity and probable trend of seasonal and annual rainfall as well as max and min temperature data in the period of 1977 through 2006. Then, the results were generalized over the basin to result in the regions affected by the climate change impact. The results show that first: Non-homogen time series (sig.99%) have been trends (sig.95%). Second: an increasing trend in Autumn and Anuual rainfall in the north-east of the basin (sig.90%). Furthermore, the climate change is demonstrated in the basin by increasing the minimum and maximum temperature during the summer and winter seasons (sig.95%).
Keywords: Climate Change, Regional assessment, Homogeneity, Trend, Gorganroud-Gharehsou
