S.M. Hosseini-Moghari; Sh. Araghinejad
Abstract
Introduction: Due to economic, social, and environmental perplexities associated with drought, it is considered as one of the most complex natural hazards. To investigate the beginning along with analyzing the direct impacts of drought; the significance of drought monitoring must be highlighted. Regarding ...
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Introduction: Due to economic, social, and environmental perplexities associated with drought, it is considered as one of the most complex natural hazards. To investigate the beginning along with analyzing the direct impacts of drought; the significance of drought monitoring must be highlighted. Regarding drought management and its consequences alleviation, drought forecasting must be taken into account (11). The current research employed multi-layer perceptron (MLP), adaptive neuro-fuzzy inference system (ANFIS), radial basis function (RBF) and general regression neural network (GRNN). It is interesting to note that, there has not been any record of applying GRNN in drought forecasting.
Materials and Methods: Throughout this paper, Standard Precipitation Index (SPI) was the basis of drought forecasting. To do so, the precipitation data of Gonbad Kavous station during the period of 1972-73 to 2006-07 were used. To provide short-term, mid-term, and long-term drought analysis; SPI for 1, 3, 6, 9, 12, and 24 months was evaluated. SPI evaluation benefited from four statistical distributions, namely, Gamma, Normal, Log-normal, and Weibull along with Kolmogrov-Smirnov (K-S) test. Later, to compare the capabilities of four utilized neural networks for drought forecasting; MLP, ANFIS, RBF, and GRNN were applied. MLP as a multi-layer network, which has a sigmoid activation function in hidden layer plus linear function in output layer, can be considered as a powerful regressive tool. ANFIS besides adaptive neuro networks, employed fuzzy logic. RBF, the foundation of radial basis networks, is a three-layer network with Gaussian function in its hidden layer, and a linear function in the output layer. GRNN is another type of RBF which is used for radial basis regressive problems. The performance criteria of the research were as follows: Correlation (R2), Root Mean Square Error (RMSE), Mean Absolute Error (MAE).
Results Discussion: According to statistical distribution analysis, the optimal precipitation distribution in many cases was not Gamma distribution. The various time-scales of SPI revealed that, at least in 50% of the events, Gamma was not the selected distribution. Throughout the drought forecasting on the basis of SPI time-series with four aforementioned networks, 80% of the data was allocated to the training process whilst the rest of them considered for the test process. The proper parameters of the networks were chosen via trial and error. Moreover, Cross-validation was used to overcome the over-estimation. The results revealed that the long-term SPIs outdid the others. Performance of the networks promoted with increases in time scales of SPI. In other words, the performance criteria improved proportional to the increases in the time-scales. Based on the Table 3, the least and best performance were contributed to SPI1 and SPI24, respectively. In this regard, R2 of MLP for observed and estimated values of SPI vitiated from 0.009 to 0.949. Similar to MLP, correlation of ANFIS, RBF, and GRNN increased from 0.021 to 0.925, 0.263 to 0.953, and 0.210 to 0.955. Comparison of observed and estimated mean values via Z test indicated that null hypothesis of equal mean observed and estimated values was only rejected for SPI1 with α=0.01. Hence, except SPI1 forecasting, the all other scenarios have remained the mean of observed time series which highlighted the robustness of artificial intelligence in drought forecasting.
Conclusion: The main objective of the ongoing research was monitoring and forecasting of drought based upon various time scales of SPI. In doing so, the precipitation data of Gonbad Kavous station during the period of 1972-73 to 2006-07 were used. Based on K-S test, the best statistical distribution test for different time scales of SPI evaluation was chosen, and then, the SPI was calculated based on the most fitted distribution. After generating the time-series, MLP, ANFIS, RBF, and GRNN were applied for drought forecasting. According to the findings, the lowest performance of forecasting belonged to SPI1 where its RBF’s best performance for R2, RMSE, and MAE were 0.263, 0.806, and 0.989. Furthermore, increases in SPI time-scale promoted the performance of networks. Thus, the worst and best performance belonged to SPI1 and SPI24, respectively. Among the utilized models, ANFIS stood superior to the others, and GRNN followed up after it.
Parvaneh KazemiMeresht; Shahab Araghinejad
Abstract
Introduction: In spite of improving the water productivity due to development in water infrastructure systems, population increasing causing the water withdrawal is triple in the last fifty years. In this situation competition on water consumption especially in the agricultural sector which is the biggest ...
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Introduction: In spite of improving the water productivity due to development in water infrastructure systems, population increasing causing the water withdrawal is triple in the last fifty years. In this situation competition on water consumption especially in the agricultural sector which is the biggest consumer in the world and also in Iran is a severe problem. Water allocation has been assessed widely in the recent past. Additionally, several studies have explored methods to incorporate conflict resolution methods in water allocation. In a general classification, there are two types of methods. One is the method based on game theory, graph theory and general models based oncooperative game into a category that has the ability to consider the stakeholder preferences and assess the several scenarios under specified policy. Although this type of methods iseligible to cooperate the stakeholder in modeling but due to their weakness on considering the information on details and their limitations in adoption with changes caused from uncertainty, they are not popular in practical cases. Another type of conflict resolution method which is eligible to considering more detailed information of systems has the optimization approach basically, has the most interests between researchers. There is namely the Nash bargaining solution, the Kalai-Smorodinesky solution, the Equal loss solution and the area monotonic solution. There are several studies which areapplied these methods to investigate about groundwater (5, 6 and10). There are a few applications of water resource allocation models which is incorporated with conflict resolution methods in Transboundary Rivers nowadays and restricted to game theory related methods (1 and 2). The aim of this study is the assessment of the application of conflict resolution methods such as symmetric and non symmetric Nash solution, non symmetricKalai-Smorodinesky, non symmetric equal loss solution and finally the area monotonic solution in water allocation between beneficiary's provinces in Atrak basin. The performances of these methods are compared with each other and also with the common water allocation model.
Materials and Methods: In the last decades, Atrak river basin located at the eastern north of Iran, shared between three provinces; Razavi Khorasan, northern Khorasan and Golestan, has a tense conflict between upstream and downstream beneficiaries. It is predictable that this conflict will be more tense in the near future due to development of upstream and increasing the water withdrawal. Because of the venial role of the Razavi Khorasan province in the Atrak basin, this province is considered as a coalition with northern Khorasan. Related data for 41 years time series and other information were gathered. Due to Hydrology studies, wet and dry periods in the two regions have not differences. As a fact that the main problem of water allocation belongs to the agricultural sector and it is the biggest consumer in the region, supply of the municipal, industrial and environmental requirement is assumed.To begin, a linear programming model is developed to optimize the agricultural water resource allocation using the LINGO® which is a comprehensive tool designed to make building and solving Linear, Nonlinear (convex &nonconvex/Global), Quadratic, Quadratically Constrained, Second Order Cone, Stochastic, and Integer optimization models faster, easier and more efficient. In the second place, conflict resolution methods such as symmetric Nash, non symmetric Nash, Kalai-Smorodinsky, equal loss, uniform area solutions are applied as an object function of water allocation models one by one. In all of these methods the stakeholder preferences should be defined with their weights in the object function. Moreover, the mentioned models are assessed with performance criteria such as reliability in time and in volume and also the resiliency.
Results and Discussion: Comparison of the results of 4 water allocation models using conflict resolution methods besides the common water allocation model using LP is shown in the figure 3 which shows the differences between models in mean of Agricultural water deficit in both provinces separately.
Figure 3- Mean of long term of agricultural deficit in different models
As mentioned before water allocation models are evaluated with performance criteria and the result is revealed in the table3.
Table 3- Comparison of conflict resolution models using the performance criteria
Reliability in time
(%) Reliability in volume
(%) Resiliency
(%)
Golestan Khorasan Total Golestan Khorasan Total Golestan Khorasan Total
LP 100 20 26 100 31 55 100 18 23
Nash 41 34 36 57 54 55 38 33 42
Kalai 32 37 29 50 54 53 25 38 31
Loss 12 39 34 41 57 52 11 40 37
Area 59 12 8 64 17 34 41 14 9
It is clear that models which have the Nash, Kalai-Smorodinesky, Equal Loss, Area Monotonic solution as the object function produce an equitable allocation between two stakeholders in comparing with the LP.
Conclusion: Without better management in agricultural water in the future which is treated by increasing population and changing the climate, growing conflicts between stakeholders are expected. In this study application of conflict resolution methods in water allocation models in Atrak basin is considered. Comparison of models in terms of their performance to allocate water equitably between two beneficiary provinces is appraised. Results revealed that the conflict resolution methods have the same action in water allocation in general though; the Nash has desirable results than others. All the conflict resolution models have the better performance in general in comparison with the common water allocation model using the linear programming. To conclude, the dependencies of results to provinces weights are appraised. Application of conflict resolution methods are proposed instead of common water allocation models without stakeholder's preference consideration due to water allocation between several stakeholders equitably.
L. Parviz; M. Kholghy; P. Irannejad; Sh. Araghinejad; Kh. Valizadeh
Abstract
Abstract
Land surface hydrological models has importance in the determination of soil moisture and temperature, the rate of evapotranspiration, stream flow by emphasis on the land surface physical and dynamic process descriptions. In this research, VIC land surface hydrological model has been used for ...
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Abstract
Land surface hydrological models has importance in the determination of soil moisture and temperature, the rate of evapotranspiration, stream flow by emphasis on the land surface physical and dynamic process descriptions. In this research, VIC land surface hydrological model has been used for the land surface temperature and stream flow determination. The VIC runoff simulation in each cell is based on both the infiltration excess and saturation runoff. Also for within-grid and between-grids routing, VIC model was coupled to the routing model. For running VIC model, Sefidroad River basin based on DEM of basin was divided in to 18 cells with 57 km resolution. The comparison of observed and simulated stream flow in the outlet of basin hydrometery station, indicated that Nash coefficient increased by using the inverse distance method that is corrected to the height for using interpolation of meteorological variables in each cell. The land surface temperature estimation in the energy mode of VIC model has accurate results than the water mode. The VIC model in the runoff simulation is more sensitive to the infiltration shape parameter. The infiltration shape parameter is effective in the surface and subsurface runoff simulation but the high influence of this parameter is related to the surface runoff. Ws and Ds play an important role in the subsurface runoff simulation. Comparison between observed and simulated stream flow using calibrated parameters in some of hydrometery stations indicated the ability of model in stream flow simulation.
Keywords: Land surface hydrological model, VIC model, Sefidroad River basin, Infiltration shape parameter
M. Soleymani Nanadegan; M. Parsinejad; Sh. Araghinejad; A. Massah Bavani
Abstract
Abstract
In this study, impact of climate change on net irrigation requirement (In) and yield of wheat using CGCM3 climate projection model, one of the AOGCM models, in Behshahr area is evaluated. changes in temperature and precipitation were simulated run under the IPCC scenario A2 for 2011-2040, 2041-2070 ...
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Abstract
In this study, impact of climate change on net irrigation requirement (In) and yield of wheat using CGCM3 climate projection model, one of the AOGCM models, in Behshahr area is evaluated. changes in temperature and precipitation were simulated run under the IPCC scenario A2 for 2011-2040, 2041-2070 and 2071-2100 periods. This work was done by using statistical and proportional downscaling techniques. For In estimating, Potential evapotranspiration (ETo) and effective rainfall (Pe) were calculated using Hargreaves – Samani equation and USDA method, respectively. Impact of water deficit on crop yield was estimated using the linear crop-water production function developed by FAO. Results showed that Net irrigation requirement (In) will increase when sowing date is moved toward winter season which would be of further limitations under climate change conditions. For the specific proposed sowing dates, the relative crop yield reduction (YD) was not significantly changed in the future compared to base period. If the sowing date is moved forward to winter season, YD will increase due to a higher evapotraspiration and lower available effective rainfall.
Keywords: Climate change, Net irrigation requirement, Wheat yield, General Circulation Model, CGCM3
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
V. R. Verdinejad; T. Sohrabi; N. Heydari; Sh. Araghinejad; M. Feizi
Abstract
Abstract
In this study, seven main field crops of the Rudasht and Abshar Irrigation Networks of Esfahan (with 54,000 ha designed command area) such as Wheat, Barley, Onion, Sunflower, Fodder Mays and Sugar beet were selected and SWAP model was calibrated by inverse modeling base on field experiments ...
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Abstract
In this study, seven main field crops of the Rudasht and Abshar Irrigation Networks of Esfahan (with 54,000 ha designed command area) such as Wheat, Barley, Onion, Sunflower, Fodder Mays and Sugar beet were selected and SWAP model was calibrated by inverse modeling base on field experiments results in order to determine crop water salinity production functions. Field experiments were conducted with effect of saline water with different irrigation managements on crop yield at Research Station of Drainage and Soil Reclamation of Rudasht during 1996 to 1998 and 2005 to 2007. In terms of insufficient field treatments and in order to fit proper crop yield production function, SWAP calibrated model was run for different quantity and quality levels of irrigation water. Quadratic form of crop yield production function was calculated for 6 salinity levels of irrigation water include 1, 2, 4, 6, 8 and 10 dS/m and each crop. Optimal irrigation depth in different condition include scarcity of water quantity, land quantity and water quantity and quality was calculated base on crop yield production function, cost production function and marketable price of each crop based on 2008 with respect to maximize net benefit. Results of analysis showed that in scarcity of water quantity for 10000 m3 available water, maximum net benefit gain onion cultivation with 52.6×106 Rials beside with 1.16 ha of area cultivation. In land scarcity condition for specified available water, maximum net benefit gain onion cultivation, too. In scarcity of water quantity and quality condition, with increasing salinity of irrigation water, for 10000 m3 available water salinity level of irrigation water equal 2 dS/m, maximum net benefit gain onion cultivation with 35.11×106 Rials beside with 1.44 ha of area cultivation, too. In salinity level equal 6 dS/m, maximum net benefit gain wheat cultivation with 18.37×106 Rials and next maximum net benefit barely cultivation with 13.9×106 Rials. Yield of Onion and Fodder Maize decreased severely so that for higher than salinity level of irrigation water equal 6 dS/m, net benefit was negative. In salinity level equal 10 dS/m, maximum net benefit gain barely and next sugar beet cultivation.
Keywords: Salinity, SWAP model, Maximum net benefit, Optimal irrigation depth, zayanderud river basin
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
