samin ansari; Alireza Massah Bavani; Abbas Roozbahani
Abstract
Introduction: Nowadays, the issue of climate change and its related problems are fundamental crisis in water resource management. On the other hand, considering that groundwater is the most important water resources, determination of the effects of climate change on groundwater and estimation the amount ...
Read More
Introduction: Nowadays, the issue of climate change and its related problems are fundamental crisis in water resource management. On the other hand, considering that groundwater is the most important water resources, determination of the effects of climate change on groundwater and estimation the amount of their recharge will be necessary in the future.
Materials and Methods: In this research, to analyze the effects of climate change scenarios on groundwater resources, a case study has been applied to the Sefid Dasht Plain located in Chahar Mahal and Bakhtiari Province in Iran. One of the three Atmospheric-Ocean General Circulation Models (AOGCM) which is called HadCM3, under the emission scenarios A2 and B1 is used to predict time series of climate variables of temperature and precipitation in the future. In order to downscale the data for producing the regional climate scenarios, LARS-WG model has been applied. Also, IHACRES model is calibrated and used for simulation of rainfall - runoff with monthly temperature, precipitation and runoff data. The predicted runoff and precipitation production in future have been considered as recharge parameters in the ground water model and the effects of climate change scenarios on the ground water table has been studied. To simulate the aquifer, GMS software has been used. GMS model is calibrated in both steady and unsteady state for one year available data and verification model has been performed by using the calibration parameters for four years.
Results and Discussion: Results of T- test shows that LARS-WG model was able to simulate precipitation and temperature selected station appropriately. Calibration of IHACRES model indicated the best performance with τw=6 و f=7.7 and the results shows that IHACRES model simulated minimum amount of runoff appropriately. Although it didn’t simulate the maximum amount of runoff accurately, but its performance and Nash coefficient is acceptable. Results indicate that changes of monthly precipitation in the future period are less than the base period in both scenarios A2 and B1. Precipitation increases about 26 and 33 percent under the scenario B1 and A2 respectively in the future compared to the base period. The monthly average temperature in the future compared to monthly average temperature in the base period has been increasing in both scenarios about 1 degree. Root Mean Square Error criteria for aquifer simulation was 1.6 in steady state and 1.9 in unsteady state. This result indicates that the aquifer has been accurately simulated. Assuming the same rate of pumping wells in the future period and in the base period, despite the increasing of recharge in the future period, water levels decrease notably in the central plains due to exceeding operation. At the end of the period (year 2035) the amount of cumulative groundwater recharges in the scenario A2 compared to scenario B1 increases about 10 cubic meters per second, which shows that the impacts of climate change in the A2 scenario compared to the B1 scenario is more.
Conclusion: Study the impact of climate change is important in our country because the major uses of water supply of groundwater. Enormous use of this resource has been defected aquifer problematically. So, it is necessary to survey impacts of climate change in future period on recharge and water levels aquifer by modeling and simulation. It is useful to predict the future conditions of groundwater. Although the recharge increases in future period, but with respect to high rate of groundwater use, it is impossible to achieve an equivalent level of aquifer without any planning. We need to control on pumping well and treatment of aquifer such as underground water dam, artificial recharge and etc. results of this research can be evaluated by other climatic scenarios, downscaling models and rainfall-runoff models. The results of this research, considerably helps to assess the effects of climate change scenarios on ground water resources as well as its proper planning and management.
M. E. Banihabib; K. Hasani; A. R. Massah Bavani
Abstract
Introduction: Forecasting the inflow to the reservoir is important issues due to the limited water resources and the importance of optimal utilization of reservoirs to meet the need for drinking, industry and agriculture in future time periods. In the meantime, ignoring the effects of climate change ...
Read More
Introduction: Forecasting the inflow to the reservoir is important issues due to the limited water resources and the importance of optimal utilization of reservoirs to meet the need for drinking, industry and agriculture in future time periods. In the meantime, ignoring the effects of climate change on meteorological and hydrological parameters and water resources in long-term planning of water resources cause inaccuracy. It is essential to assess the impact of climate change on reservoir operation in arid regions. In this research, climate change impact on hydrological and meteorological variables of the Shahcheragh dam basin, in Semnan Province, was studied using an integrated model of climate change assessment.
Materials and Methods: The case study area of this study was located in Damghan Township, Semnan Province, Iran. It is an arid zone. The case study area is a part of the Iran Central Desert. The basin is in 12 km north of the Damghan City and between 53° E to 54° 30’ E longitude and 36° N to 36° 30’ N latitude. The area of the basin is 1,373 km2 with average annual inflow around 17.9 MCM. Total actual evaporation and average annual rainfall are 1,986 mm and 137 mm, respectively. This case study is chosen to test proposed framework for assessment of climate change impact hydrological and meteorological variables of the basin. In the proposed model, LARS-WG and ANN sub-models (7 sub models with a combination of different inputs such as temperature, precipitation and also solar radiation) were used for downscaling daily outputs of CGCM3 model under 3 emission scenarios, A2, B1 and A1B and reservoir inflow simulation, respectively. LARS-WG was tested in 99% confidence level before using it as downscaling model and feed-forward neural network was used as raifall-runoff model. Moreover, the base period data (BPD), 1990-2008, were used for calibration. Finally, reservoir inflow was simulated for future period data (FPD) of 2015-2044 and compared to BPD. The best ANN sub-model has minimum Mean Absolute Relative Error (MARE) index (0.27 in test phases) and maximum correlation coefficient (ρ) (0.82 in test phases).
Results and Discussion: The tested climate change scenarios revealed that climate change has more impact on rainfall and temperature than solar radiation. The utmost growth of monthly rainfall occurred in May under all the three tested climate change scenarios. But, rainfall under A1B scenario had the maximum growth (52%) whereas the most decrease occurred (–21.5%) during January under the A2 climate change scenario. Rainfall dropped over the period of June to October under the three tested climate change scenarios. Furthermore, in all three scenarios, the maximum temperature increased about 2.2 to 2.6°C in May but the lowest increase of temperature occurred in January under A2 and B1 scenarios as 0.3 and 0.5°C, respectively. The maximum temperature usually increased in all months compared to the baseline period. Minimum and maximum temperatures enlarged likewise in all months, with 2.05°C in September under A2 climate change scenario. Conversely, solar radiation change was comparatively low and the most decreases occurred in February under A1B and A2 climate change scenarios as –4.2% and –4.3% , respectively, and in August under the B1 scenario as –4.2%. The greatest increase of solar radiation occurs in April, November, and March by 3.1%, 3.2%, and 4.9% for A1B, A2, and B1 scenarios, respectively. The impact of climate change on rainfall and temperature can origin changes on reservoir inflow and need new strategies to adapt reservoir operation for change inflows. Therefore, first, reservoir inflow in future period (after climate change impact) should be anticipated for the adaptation of the reservoir.
A Feed-Forward (FF) Multilayer-Perceptron (MLP) Artificial Neural Network (ANN) model was nominated for the seven tested ANN models based on minimization of error function. The selected model had 12 neurons in the hidden layer, and two delays. The comparison of forecasted flow hydrograph by selecting an ANN model and observed one proved that forecasted flow hydrograph can follow observed one closely. By comparison with the IHACRES model, this model displayed a 54% and 46% lower error functions for validation data. The selected model was used to forecast flow for the climate change scenarios of the future period.
Conclusions: The results show a reduction of monthly flow in most months and annual flow in all studied scenarios. The following main points can be concluded:
• By climate change, flow growths in dry years and it declines in wet and normal years.
• The studied climate change scenarios showed that climate change has more impact on rainfall and temperature than solar radiation.
M. Mozayyan; ali mohammad akhondali; A.R. Massah Bavani; F. Radmanesh
Abstract
Introduction: Due to the effects of climate change on water resources and hydrology, Changes in low flow as an important part of the water cycle, is of interest to researchers, water managers and users in various fields. Changes in characteristics of low flows affected by climate change may have important ...
Read More
Introduction: Due to the effects of climate change on water resources and hydrology, Changes in low flow as an important part of the water cycle, is of interest to researchers, water managers and users in various fields. Changes in characteristics of low flows affected by climate change may have important effects on various aspects of socioeconomic , environmental, water resources and governmental planning. There are several indices to assess the low flows. The used low flow indices in this research for assessing climate change impacts, is include the extracted indices from flow duration curve (Q70, Q90 and Q95), due to the importance of these indices in understanding and assessing the status of river flow in dry seasons that was investigated in Tang Panj Sezar basin in the west of Iran.
Materials and methods: In this paper, the Tang Panj Sezar basin with an area of 9410 km2 was divided into 6 smaller sub catchments and the changes of low flow indices were studied in each of the sub catchments. In order to consider the effects of climate change on low flow, scenarios of temperature and precipitation using 10 atmospheric general circulation models (to investigate the uncertainty of GCMs) for both the baseline (1971-2000) and future (2011-2040) under A2 emission scenario was prepared. These scenarios, due to large spatial scale need to downscaling. Therefore, LARS-WG stochastic weather generator model was used. In order to consider the effects of climate change on low flows in the future, a hydrologic model is required to simulate daily flow for 2011-2040. The IHACRES rainfall-runoff model was used for this purpose . After simulation of daily flow using IHACRES, with two time series of daily flow for the observation and future period in each of the sub catchment, the low flow indices were compared.
Results Discussion: According to results, across the whole year, the monthly temperature in the future period has increased while rainfall scenarios show different variations for different months, also within a month for different GCMs. Based on the results of low flow indices, in most cases, the three indices of Q70, Q90, and Q95 will show incremental changes in the future compared to the past. Also, the domain simulation by 10 GCMs for all three indices is maximum in Tang Panj Sezar and less for other sub catchments, which is related to better performance of IHACRES model in smaller sub catchments. In order to investigate the uncertainty of type changes in different indices in every sub catchment, changes in any of the indices were considered based on the median of GCMs. To achieve the correct type of changes in low flow indices, the amount of error in a simulation of the indices of IHACRES rainfall-runoff model should also be taken into consideration. Therefore, considering the error, the three indices Q70, Q90 and Q95 in all sub catchments (except for Tang Panj Sezar) will have the relative increase in the future period. The improvement of low flow state in the future period is related to the changes occurred in the state of climate scenarios. As the results indicated, most often, there is an increase in rainfall in dry seasons. Also, in different months of the wet season wet season, if the result of changes in quantity of rainfall is incremental, it can lead to an increase in river flow through groundwater recharge. On the other hand due to the limestone and karst forms in most of the basin area, water storage ability and increase the amount of river flow during low water season in this area is expected. The study on rainfall quantity in Tang Panj Sezar sub catchment also indicated that, there will be no significant increase or decrease in the quantity of rainfall in the dry season. Thus, it is expected that there will not be significant changes in low flow indices. In this sub catchment, changes in various low flow indices do not match perfectly, so more difficult to obtain reliable results. With regard to incremental changes of Q95, low flow index with less uncertainty, as well as improving indices of low flow in other sub-basins, it is possible to predict a relatively better state for low flow indices of Tang Panj Sezar in the future period.
Conclusion: Using temperature and rainfall scenarios to simulate river flow in the future, a relative increase of all three low flow indices Q70, Q90 and Q95 was predicted compared with the past period. Although all three of mentioned indices show the amount of low flow in the dry season, it is recommended that only two indices of Q90 and Q95 to assess the effects of climate change be considered. Q90 and Q95 indices are more suitable indices than Q70 for studying the effects of climate change on low flow state. These two indices indicate less quantity of flow in dry seasons; therefore, the changes of the two indices are more important in identifying the low flow state. However, there is less uncertainty in the estimation of the two Q90 and Q95 indices than Q70.
M. Delghandi; S. Broomandnasab; B. Andarzian; A.R. Massah-Bovani
Abstract
Introduction In recent years human activities induced increases in atmospheric carbon dioxide (CO2). Increases in [CO2] caused global warming and Climate change. Climate change is anticipated to cause negative and adverse impacts on agricultural systems throughout the world. Higher temperatures are expected ...
Read More
Introduction In recent years human activities induced increases in atmospheric carbon dioxide (CO2). Increases in [CO2] caused global warming and Climate change. Climate change is anticipated to cause negative and adverse impacts on agricultural systems throughout the world. Higher temperatures are expected to lead to a host of problems. On the other hand, increasing of [CO2] anticipated causing positive impacts on crop yield. Considering the socio-economic importance of agriculture for food security, it is essential to undertake assessments of how future climate change could affect crop yields, so as to provide necessary information to implement appropriate adaptation strategies. In this perspective, the aim of this study was to assess potential climate change impacts and on production for one of the most important varieties of wheat (chamran) in Khouzestan plain and provide directions for possible adaptation strategies.
Materials and Methods: For this study, The Ahvaz region located in the Khuzestan province of Iran was selected.
Ahvaz has a desert climate with long, very hot summers and mild, short winters. At first, thirteen GCM models and two greenhouse gases emission (GHG) scenarios (A2 and B1) was selected for determination of climate change scenarios. ∆P and ∆T parameters at monthly scale were calculated for each GCM model under each GHG emissions scenario by following equation:
Where ∆P, ∆T are long term (thirty years) precipitation and temperature differences between baseline and future period, respectively. average future GCM temperature (2015-2044) for each month, , average baseline period GCM temperature (1971-2000) for each month, , average future GCM precipitation for each month, , average baseline period GCM temperature (1971-2000) for each month and i is index of month. Using calculated ∆Ps for each month via AOGCM models and Beta distribution, Cumulative probability distribution function (CDF) determined for generated ∆Ps. ∆P was derived for risk level 0.10 from CDF. Using the measured precipitation for the 30 years baseline period (1971-2000) and LARS-WG model, daily precipitation time series under risk level 0.10 were generated for future periods (2015-2045 and 2070-2100). Mentioned process in above was performed for temperature. Afterwards, wheat growth was simulated during future and baseline periods using DSSAT, CERES-Wheat model. DSSAT, CERES4.5 is a model based on the crop growth module in which crop growth and development are controlled by phenological development processes. The DSSAT model contains the soil water, soil dynamic, soil temperature, soil nitrogen and carbon, individual plant growth module and crop management module (including planting, harvesting, irrigation, fertilizer and residue modules). This model is not only used to simulate the crop yield, but also to explore the effects of climate change on agricultural productivity and irrigated water. For model validation, field data from different years of observations were used in this study. Experimental data for the simulation were collected at the experimental farm of the Khuzestan Agriculture and Natural Resources Research Center (KANRC), located at Ahwaz in south western Iran.
Results and Discussion: Results showed that wheat growth season was shortened under climate change, especially during 2070-2100 periods. Daily evapotranspiration increased and cumulative evapotranspiration decreased due to increasing daily temperatures and shortening of growth season, respectively. Comparing the wheat yield under climate change with base period based on the considered risk value (0.10) showed that wheat yield in 2015-2045 and 2070-2100 was decreased about 4 and 15 percent, respectively. Four adaptation strategies were assessed (shifting in the planting date, changing the amount of nitrogenous fertilizer, irrigation regime and breeding strategies) in response to climate change. Results indicated that Nov, 21 and Dec, 11 are the best planting dates for 2015-2045 and 2070-2100, respectively. The late season varieties with heat-tolerant characteristic had higher yield in comparison with short and normal season varieties. It indicated that breeding strategy was an appropriate adaptation under climate change. It was also found that the amount of nitrogen application will be reduced by 20 percent in future periods. The increase and decease of one irrigation application (40mm) to irrigation regime of base period resulted in maximum yield for 2015-2045 and 2070-2100, respectively. But, reduction of two irrigation application (80mm) resulted in maximum water productivity (WPI).
Conclusions In the present study, four adaptation strategies of wheat (shifting in the planting date, changing the amount of nitrogenous fertilizer, irrigation regime and breeding strategies) under climate change in Ahvaz region were investigated. Result showed that Nov, 21 and Dec, 11 were the best planting dates for 2015-2045 and 2070-2100, respectively. The late season varieties with heat-tolerant characteristic had higher yield in comparison with short and normal season varieties. It indicated that breeding strategy was an appropriate adaptation strategy under climate change. It was also found that the amount of nitrogen application will be reduced by 20 percent in future periods. The increase and decease of one irrigation application (40mm) to irrigation regime of base period resulted in maximum yield for 2015-2045 and 2070-2100, respectively.
B. Mansouri; H. Ahmadzadeh; A. Massah Bavani; saeed morid; M. Delavar; S. Lotfi
Abstract
This paper evaluate impacts of climate change on temperature, rainfall and runoff in the future Using statistical model, LARS-WG, and conceptual hydrological model, SWAT. In order to the Zarrinehrud river basin, as the biggest catchment of the Lake Urmia basin was selected as a case study. At first, ...
Read More
This paper evaluate impacts of climate change on temperature, rainfall and runoff in the future Using statistical model, LARS-WG, and conceptual hydrological model, SWAT. In order to the Zarrinehrud river basin, as the biggest catchment of the Lake Urmia basin was selected as a case study. At first, for the generation of future weather data in the basin, LARS-WG model was calibrated using meteorological data and then 14 models of AOGCM were applied and results of these models were downscaled using LARS-WG model in 6 synoptic stations for period of 2015 to 2030. SWAT model was used for evaluation of climate change impacts on runoff in the basin. In order to, the model was calibrated and validated using 6 gauging stations for period of 1987-2007 and the value of R2 was between 0.49 and 0.71 for calibration and between 0.54 and 0.77 for validation. Then by introducing average of downscaled results of AOGCM models to the SWAT, runoff changes of the basin were simulated during 2015-2030. Average of results of LARS-WG model indicated that the monthly mean of minimum and maximum temperatures will increase compared to the baseline period. Also monthly average of precipitation will decrease in spring season but will increase in summer and autumn. The results showed that in addition to the amount of precipitation, its pattern will change in the future period, too. The results of runoff simulation showed that the amount of inflow to the Zarrinehrud reservoir will reduce 28.4 percent compared to the baseline period.
Mahdi Delghandi; Saeid Boroomand Nasab
Abstract
Field experiments for quantifying optimal breeding strategies are time-consuming and expensive. Crop simulation models can provide an alternative, less time-consuming and inexpensive means of determining the optimum breeding strategies. These models consider the complex interactions between weather, ...
Read More
Field experiments for quantifying optimal breeding strategies are time-consuming and expensive. Crop simulation models can provide an alternative, less time-consuming and inexpensive means of determining the optimum breeding strategies. These models consider the complex interactions between weather, soil properties and management factors. CERES-Wheat is one of best models which can simulate the growth and development of wheat. Therefore, in present paper DSSAT 4.5-CERES-Wheat was evaluated for predicting growth, phenology stages and yield of wheat (cultivar of Chamran) for Ahwaz region. For this purpose, one Experimental research was designed at the experimental farm of the Khuzestan Agriculture And Natural Resources Research Center (KANRC), located at Ahwaz in 2010-2011 growth season. Using results of this research and two another research, CERES-Wheat model was evaluated. Results of evaluation showed that most and less NRMSE were abtained for simulation of maximum Leaf Area Index (6%) and phenology stages (2%), respectively. Therefore, it can conclude that CERES-Wheat is a powerful model in order to simulation of growth, phenology stages and yield of wheat.
H. Seyyed Kaboli; A.M. AkhodAli; A.R. Masah Bavani; F. Radmanesh
Abstract
General Circulation Models (GCMs) have been identifiedas asuitable tool for studying climate change. Butthese models simulate climatic parametersinthe large-scale which has poor performance in the simulation of processes such asrain fall-run off. There fore, several of down scaling methods were developed. ...
Read More
General Circulation Models (GCMs) have been identifiedas asuitable tool for studying climate change. Butthese models simulate climatic parametersinthe large-scale which has poor performance in the simulation of processes such asrain fall-run off. There fore, several of down scaling methods were developed. This researchis presented down scaling model based onk-nearest neighbor (K-NN) non-parametric method. The modelis used to simulate daily precipitation data in Ahvaz station for the next period (2015-2044) under climate change scenarios based on out puts of three General Circulation Models, including HADCM3, NCARPC Mand CSIROMK3.5. The results indicate that them odelhasa high capacity for down scaling data. It is predicted that the frequency of storm is increased with high intensity on future period in Ahvaz station while dry spells will be prolonged.
M. Golmohammadi; A. Massah Bavani
Abstract
Abstract
This research evaluates climate change effects on drought severity in the region of Gharesou, Iran. The Standardized Precipitation Index (SPI) has been used for estimation of drought severity. A geographical information system is applied for calculating the mean areal precipitation time series ...
Read More
Abstract
This research evaluates climate change effects on drought severity in the region of Gharesou, Iran. The Standardized Precipitation Index (SPI) has been used for estimation of drought severity. A geographical information system is applied for calculating the mean areal precipitation time series from 11 meteorological stations, in and out of the area for the hydrological period Jan 1971-Dec 2000 using Inverse Distance Weighting method. This precipitation time series have been used for the estimation of Standardized Precipitation Index (SPI) for three timescales, 6, 12 and 24 months, for the region. The outputs of HadCM3-A2 were applied for the assessment of climate change impact on droughts. The HadCM3 outputs were downscaled statistically to the region of Gharesou using SDSM software to estimate precipitation time series for a future period 2040-2069. A method has been used for the estimation of annual cumulative drought severity-time scale-frequency curves. These curves integrate the drought severity and frequency for various types of drought. The SPI time series were estimated and compared with the respective time series of the historical period 1971-2000. The comparison indicated that the annual drought intensity decreases for the three examined SPI time series. Furthermore, analysis of drought period has shown that value and frequency of drought would be declined in future in the region.
Keywords: Climate Change, Drought, SPI, HadCM3, Gharesou Basin
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 ...
Read More
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
A.R. Kamal; A.R. Massah Bavani
Abstract
Abstarct
Development of greenhouse gases in future periods not only causes change in average amounts of climate variables but also makes variables of this variability affected. Then for sure concerning alternations followed with climate variables’ fluctuations and its average amounts in effecting ...
Read More
Abstarct
Development of greenhouse gases in future periods not only causes change in average amounts of climate variables but also makes variables of this variability affected. Then for sure concerning alternations followed with climate variables’ fluctuations and its average amounts in effecting on runoff would make more reliable results. In this inquiry initially fluctuations and average amounts of climate variables of Gharesuo basin were simulated by HadCM3-A2 model and Statistical Downscaling method in 2040-2069 periods. Although to mention climate fluctuation’s uncertainty in calculations, they acted to simulate 100 time series of temperature and precipitation variables for future period. Results showed that uncertainty confine of region’s climate fluctuations has increased 0.5 to 2C° in temperature and 10 to 20mm changing in precipitation in different months of year. After that and to mention Hydrology model’s uncertainty, two rainfall-runoff models of SIMHYD and IHACRES are used. These two models calibration for base period and introducing 100 time series of climate variables produced in last level into both models specified the basin runoff’s changing confine for 2040-2069 period. Results declare the coordination of two models in region’s runoff changes. As both models estimate runoff abatement for fall season and enlargement for other seasons. Finally the results of this inquiry estate the effect of hydrology model’s uncertainty and less effect of climate variability in estimating a basin’s runoff under impact of climate change.
Keywords: Climate Change, Climate Variability, Rainfall-Runoff, HadCM3