Showing 9 results for Scenario
A. R. Massah Bavani, S. Morid,
Volume 9, Issue 4 (1-2006)
Abstract
In this study the impact of climate change on temperature, rainfall and river flows of the Zayandeh Rud basin under two climate change scenarios for two periods (2010-2039 and 2070-2099) are investigated. For the evaluation of future climate change impact on stream flow to Chadegan reservoir, the global circulation model (GCM) outputs of the HadCM3 model (monthly temperature and precipitation) with two scenarios, A2 and B2, are obtained and downscaled to the local level for the selected time periods. The results indicate that the annual average of precipitation decreases and temperature increases for both periods that are more pronounced for the period 2079-2099. Such that 10% to 16% decrease in precipitation and 3.2 to 4.6ºC increases in temperature can be anticipated for scenarios A2 and B2, respectively. To predict future stream flow changes due to climate change, artificial neural networks (ANNs) have been applied and trained by the several input models and architectures for rainfall-runoff simulation. The results indicate that the maximum of 5.8% decrease in the annual flows. Comparison of the two scenarios indicates the more critical situation in scenario A2 for the basin.
H. Khaledian, D. Nikkami,
Volume 21, Issue 1 (6-2017)
Abstract
Appropriate utilization of agricultural land and natural resources, decreased erosion and increased production occurs in watersheds. On the other hand, land use pattern due to increasing human activities on the ground to meet different needs, is changing. Optimization of land use is one of the management methods to achieve stability and reduce soil erosion. In this study, by using linear programming (simplex) and Geographic Information System(GIS), was investigated the land use optimization in three scenario option to: current condition, management condition, and standard condition.Erosion potential by using MPSIAC Model in irrigated land 1.65, dry lands 3.31, pasture 3.64, gardens 1.49 and 3.85 tons per hectare per year was estimated for Chehel-Gazi basin. The results of the sensitivity analysis for tree scenario showed that in the event optimize land use, erosion potential in the current Condition 0.85 percent increased, But in the land management Condition 16.92 percent and in a standard Condition 32 percent decreased. The results of sensitivity analysis showed that changes in the area of pasture all three options have the greatest impact in changing erosion potential of basin.
Sh. Kouhestani, S, Eslamian, A. Besalatpour,
Volume 21, Issue 1 (6-2017)
Abstract
This study aims to investigate the changes of minimum and maximum temperature variables under the impact of climate change for time period of 2015-2100 in the Zayandeh-Rud River Basin. The outputs of 14 Global Climate Models (GCMs) under three green-house emission scenarios (RCP2.6, RCP4.5, and RCP8.5) are employed from the Fifth Assessment Report (CMIP5) of Intergovernmental Panel on Climate Change (IPCC). A novel statistical downscaling method using a Bayesian Relevance Vector Machine (RVM) is used to project the impact of climate change on the temperature variables at regional scale. The results of the weighting average of the GCMs show that the various models have different accuracy in the projecting the minimum and maximum temperatures in the study area. The results demonstrate that the MIROC5 and CCSM4 are the most reliable models in projecting the maximum and minimum temperatures, respectively. The highest increase for both maximum and minimum temperatures was obtained in winter.
On the annual basis, the maximum temperature will increase by 0.18-0.76 °C and 0.25-1.67 °C, respectively, in the near and long-term future periods under different emission scenarios. The annual minimum temperature will increase by 0.28 to 0.82 °C and 0.24-1.56 °C, respectively, in the near and long-term future periods. In a general view, changes in maximum temperature will be slightly higher than minimum temperature changes in the future.
A. H. Boali, H. Bashari, R. Jafari, M. Soleimani,
Volume 21, Issue 2 (8-2017)
Abstract
Appropriate criteria and methods are required to assess desertification potential in various ecosystems. This paper aimed to assess desertification levels in Segzi plain located in east part of Isfahan, with a focus on soil quality criteria used in MEDALUS model. Bayesian Belief Networks (BBNs) were also used to convert MEDALUS model into a predictive, cause and effects model. Soil samples were collected from 17 soil profiles in all land units and some of their characteristics such as texture, soluble sodium and chlorine, organic material, Sodium Absorption Ratio (SAR), Electrical Conductivity (EC) and CaSo4 of all soil samples were determined in soil laboratory. The effects of measured soil quality indicators on desertification intensity levels were assessed using sensitivity and scenario analysis in BBNs. Results showed that the used integrated method can appropriately accommodate uncertainty in the desertification assessments approaches created as a result of the influence of different soil characteristics on desertification. According to the results of MEDALUS model, 28.28 % and 71.72 % of the study area were classified as poor and moderate areas in terms of soil quality respectively. Sensitivity analysis by both models showed that soil organic matter, SAR and EC were identified as the most important edaphic variables responsible for desertification in the study area. Evaluating the effects of various management practices on these variables can assist managers to achieve sound management strategies for controlling desertification.
Dr. S. Akhavan, N. Delavar, Dr. A. M. Mehnatkesh,
Volume 21, Issue 2 (8-2017)
Abstract
The aim of this study was to investigate the climate change impacts on some factors affecting rainfed wheat growth such as effective rainfall, planting date and length of growing season in four stations located in Chaharmahal and Bakhtiari province. Firstly, it is necessary to predict future (2046-2065) climatic conditions. For this purpose, the output of HADCM3 general circulation model was used under three scenarios of A1B, A2 and B1. The data were downscaled by LARS-WG model. After simulating the climatic parameters in mention period, the effective rainfall during the wheat growing season was calculated by Food and Agriculture Organization method. Also, the optimum planting date was defined according to the date of the first rain (at least 10 mm in case of continuing for next days). The wheat's growth stages were determined by Growing Degree Days method. The results indicated a rise in temperature for four stations. On average, it is expected that the annual temperature increase by 1.8°C compared with the baseline period (2010-1990). Total annual precipitation in Shahrekord, Koohrang and Borujen will decrease 2.2, 7.8 and 3.6 per cent respectively. About Lordegan it will increase by 2.7 per cent. Also, the results showed that in three stations of Shahrekord, Koohrang and Borujen, the amount of effective rainfall in November will increase compared to baseline, but in Lordegan it will reduce. So, in the first three stations, in most years, planting date was obtained earlier than baseline, but in Lordegan it was later than baseline. The Length of growing season will reduce in Shahrekord, Borujen and Lordegan stations, 12 days on average and in Koohrang about 13 days.
A.r. Keshtkar, Sh. Mohammadkhan, R. Houshmandi, S. Dalfardi,
Volume 21, Issue 3 (11-2017)
Abstract
Recently, catchments were considered as planning and management units for sustainable development in many issues. Catchment sources management is considered as a new principle for development planning and management of water and soil resources emphasizing on socio-economic characteristics of the region to sustainable livelihoods and without vulnerability of plant and the residents of an area. These objectives will be achieved when the proper management of resources and the management should be applied to decrease destructive processes and strengthen the improvement processes. Aiming at biological management of watershed resources with scenario building approach, this study has assessed and prioritized biological management options in the Delichay Catchment. With a choice of four biological management activities, 16 scenarios were developed in the study area. Then, criteria weighting was carried out using analytic hierarchy process and ultimately, the best management option was chosen using TOPSIS model. The results indicated that social, ecological, economic and physical criteria were respectively prioritized from one to four and scenario number 10 was determined as the best scenario and the first priority. Also, the results showed that the multi-criteria decision making techniques included capability of expressing different aspects of the problem and are perfect tools for integrated watershed resources management.
A. Mansouri, B. Aminnejad, H. Ahmadi,
Volume 22, Issue 2 (9-2018)
Abstract
In the present paper, fluctuations of inflow into the Karun-4 Dam under different scenarios of the climate change for the future period of 2021-2050 were investigated. For this purpose, the outputs of the HadCM3 model under the scenarios of B1 (optimistic) and A2 (pessimistic) were utilized for the fourth report; additionally, the outputs of the ensemble model under RCP 2.6 (optimistic) and RCP 8.5 (pessimistic) scenarios were used for the fifth report. Moreover, in order to estimate runoff in the future period, the artificial neural network was considered as a rainfall-runoff model. The results indicated that the average annual precipitation in the five study stations under B1 and RCP 2.6 scenarios was increased by 15 and 5%, respectively, while it showed a decrease equal to 8 and 6%, respectively under the scenarios A2 and RCP 8.5. Furthermore, the average annual temperature in all scenarios showed increase, which was at least 1.06 ⁰C under the scenario B1 and 1.89 ⁰C under scenario RCP 8.5. Examining the input inflow into the Karun-4 dam showed that under both B1 and RCP 2.6 scenarios, the annual inflow will be increased by 1.8 and 1.5%, respectively; under the two scenarios A2 and RCP of 8.5, the annual inflow will be decreased to 10.4 and 9.8%, respectively.
A. Khorsand, M. Bazaneh, S. Besharat, K. Zeynalzadeh,
Volume 22, Issue 4 (3-2019)
Abstract
Subsurface drip irrigation systems, compared to other irrigation systems (basin and furrow), enhance the delivery of water and nutrients directly into the root zone. The purposes of this study were to determine wetting front advancement in a subsurface drip irrigation and to compare the results with the HYDRUS 2D model simulation. In this study, the irrigation using T-Tape was carried out on a sandy-loam soil by two emitters at different irrigation times. The Wet moisture meter device was used to determine the soil water content. Evaluation of the simulated and measured soil water content was performed by using the adjusted determination coefficient (R2), relative error (RE), and the normalized root mean square error (NRMSE). Based on the results, the NRMSE of soil water content prediction for the emitters at the depths of 20 and 40 cm was calculated to be in the range of 10 to 19 and 10 to 13 percent, respectively. Also, RE for the emitters at depths of 20 and 40 cm was in the range of -16 to -5 and 8 to 11 percent, respectively. The average R2 for the emitters at depths of 20 and 40 cm was calculated to be 0.87 and 0.98, respectively. Also, five scenarios (F1, F2, T1, T2 and S1) were evaluated to assess the amount of water stored in the soil profile and water mass balance. The results indicated that the model could be used to predict the soil water content subsurface drip irrigation.
M. Zareian,
Volume 26, Issue 2 (9-2022)
Abstract
This study was conducted to investigate the effects of climate change on temperature and precipitation changes in important synoptic weather stations in Yazd province (including Yazd, Bafgh, Marvast, and Robat-e-Poshtebadam). Accordingly, a combination of the outputs of the latest AOGCM models presented in the IPCC sixth assessment report (CMIP6) were used to increase the accuracy of temperature and precipitation forecasts. A weighting method was used based on the Kling-Gupta combined index (KGE) to combine these models. After weighting the models, the monthly temperature and precipitation changes were calculated based on SSP126, SSP245, and SSP585 emission scenarios. Then, daily temperature and precipitation time series were extracted for different weather stations using the LARS-WG downscaling model. The results showed that in all the weather stations, CanESM5 and BCC-CSM2-MR models have the best ability to simulate the temperature and precipitation of the historical period, respectively. Results also showed that in all emission scenarios, the annual temperature will increase and the annual precipitation will decrease. The annual temperature of this region will increase between 0.2 to 0.6 °C, and the annual precipitation will decrease between 2.9 and 13.7% in different weather stations. Also, the maximum temperature increase and precipitation decrease in this region, will occur in spring and autumn, respectively.
