Climate change impact assessment on hydrology of Karkheh Basin, Iran (original) (raw)
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Hydrologic responses of climate change on the Karkheh River Basin
2009
Future of the Karkheh River Basin and its people’s livelihoods clearly depends on natural resources like water, soil, vegetation and livestock. As water is the most limiting natural resource in this basin, any increase in water productivity will almost certainly benefit rural livelihoods. To ensure the sustainability of the improvements in water productivity, assessment of the possible impacts of climate change on hydrology and water resources in the basin is necessary. In this study the potential impacts of climate change on hydrology in the Karkheh River Basin were assessed using a macroscale hydrology model driven by ١٢st century simulations of temperature and precipitation downscaled from runs of CGCM١ model with two emissions scenarios (A١ and B١) for ٣ periods: (١٢٢٢- ١٢٣٢), (١٢٠٢-١٢٠٢), (١٢٠٢-١٢٢٢). At first, the monthly precipitation and temperature output of each GCM was bias-corrected and statistically downscaled to a ٢/١° grid using a statistical technique and SDSM model. Then, we forced a hydrologic model using the downscaled data to generate streamflow at strategic points. The hydrologic model used in this study was the variable infiltration capacity (VIC) model. The model was run on a daily time step for a ٢/١-degree resolution over the Karkheh River Basin. The downscaled data from each of ١ projected climates were used to force the land surface hydrology model to simulate hydrologic responses in the Karkheh River Basin, which produced projected streamflow at inflow points to major reservoirs major reservoirs. As the results of this study, by ١٢٠٢-١٢٢٢ the median warming relative to ٢٢٠٢- ٢٢٢٢ is ٢.٣°C and ٢.٢°C under B١ and A١ emissions scenarios, respectively. For the same periods, the model has projected median precipitation decreases of ٠% (B١) and increases of ٢٢% (A١). Median changes by ١٢٠٢-١٢٢٢ in reservoir inflow are ٢١% (B١) and ٢٠% (A١), with largest flow reductions during the rising limb of the seasonal hydrograph, from April through September.
Journal of Water and Climate Change, 2017
In this paper, two approaches to assess the impacts of climate change on streamflows have been used. In the first approach (direct), a statistical downscaling technique was utilized to predict future streamflows based on large-scale data of general circulation models (GCMs). In the second approach (indirect), GCM outputs were downscaled to produce local climate conditions which were then used as inputs to a hydrological simulation model. In this article, some data-mining methods such as model-tree, multivariate adaptive regression splines and group method of data handling were utilized for direct downscaling of streamflows. Projections of HadCM3 model for A2 and B2 SRES scenarios were also used to simulate future climate conditions. These evaluations were done over three subbasins of Karkheh River basin in southwest Iran. To achieve a comprehensive assessment, a global uncertainty assessment method was used to evaluate the results of the models. The results indicated that despite simplifications included in the direct downscaling, this approach is accurate enough to be used for assessing climate change impacts on streamflows without computational efforts of hydrological modeling. Furthermore, comparing future climate projections, the uncertainty associated with elimination of hydrological modeling is estimated to be high.
Impacts of climate change could have far-reaching and unpredictable consequences on water resources in many watersheds. In the past decade, many researchers have focused on assessing the impacts of climate change on the hydrologic cycle processes. In this study, impacts of the climate change on the Rainfall-Runoff Process (RRP) in Pishin Basin in Sistan-Baluchestan Province in southeast of Iran is investigated. AFFDEF which is a distributed rainfall-runoff model has been calibrated using Genetic Algorithm (GA) and tested using daily records of Pishin reservoir inflows and rain gauges in the basin. The calibrated model has been then utilized to simulate RRP under assessed conditions of climate change till the year 2050 using A2 and A1B scenarios from the SRES family of scenarios generated by the Intergovernmental Panel on Climate Change (IPCC). The results have shown that the calibrated model has been able to properly regenerate reservoir inflows and can be utilized as a useful tool for runoff prediction under different climate change scenarios.
Assessment of climate change impact on surface water: a case study—Karoun River Basin, Iran
Arabian Journal of Geosciences, 2022
Over the last few decades, the climate change has been increased due to the increased industrial activities, greenhouse gas emissions, and CO 2 level. This change has affected the water resource management so that the amount of water entered from upstream of watersheds has been transformed every year, and the water resource management has become difficult for the surface runoff, entered water, flood and drought. The problem becomes more serious when the study area (Kan watershed) is located upstream of such urban watershed as Tehran, where the climate change studies on the water resources are very important. In this study, using the Statistical downscaling model (SDSM), the data of CanESM2 Canadian general circulation model (GCM) was downscaled under the Representative Concentration Pathway (RCP) 2.6, RCP4.5, and RCP8.5. In order to study the climate change, the artificial neural network (ANN) and IHACRES models were used over the period of 2010-2040. The study results showed that the temperature is increased in the upcoming period of 2006-2100 (0.8-5.6 C �), and the highest temperature changes are related to winter and summer. The precipitation in the upcoming period shows an increasing trend on the annual average, but, in general, it can be said that the 4-55% precipitation shows an increasing trend. The runoff in the upcoming period of 2010-2040 under RCP2.6, RCP4.5 and RCP8.5 is À 4, 26 and À 2 percent in the ANN model and 26, 28 and 33 percent in the IHACRES model, respectively.
Climate Change Impacts on Hydrological and Meteorological Variables in the Karkheh River Basin
2009
Understanding and projecting the impacts of climate change on water resources and hydrology will help decision-makers with making reliable judgements, which take into account a sustainable future for water demand and supply. Since water is the most limited natural resource in the Karkheh River Basin, any change in the basin's water resources will almost certainly affect rural livelihoods. To ensure the sustainability of improvements in water productivity, an assessment of the possible impacts of climate change on hydrology and water resources in the basin is necessary. First, daily temperature and precipitation from a Global Climate Model using two emissions scenarios (A2 and B2) for three periods () of the 21st century were used to assess the range of potential climate changes on the basin. Raw GCM-data were bias-corrected and statistically downscaled to a 1/2° grid using a Statistical Downscaling Model (SDSM) coupled to an empirically developed linear regression technique, in order to make 1/2° grid-based data. Then, the Variable Infiltration Capacity hydrologic model (VIC) was applied using the downscaled data to generate streamflows, focusing on inflow at the inlet of the Karkheh reservoir. The results were used to compare with another study in the basin. According to the results, the basin will experience a warmer climate than it used to experience during the last 40 years. By 2070-2099 the mean warming relative to 1961-2000 will be 1.3°C and 1.9°C under B2 and A2 scenarios, respectively. For the first half of the century, the model projected mean annual precipitation increases by 7% (B2) and 11% (A2) in rainy seasons relative to historical amount (~4 mm/day). But for the last of this century, the model projected the mean annual precipitation changes +0.5 to +1 mm/day in the east and -0.5 to +0.5 mm/day in the west of the basin. Although the average annual precipitation will not considerably change by the end of the century, relative to historical data changes in timing and form are expected in the basin. Due to these impacts, mean changes by 2070-2099 in Karkheh reservoir inflow will be about +15% (B2) and +21% (A2) for rainy seasons and the Karkheh streamflow will decrease during April and May as a result of earlier snow-melt.
Assessment of climate change impacts in a semi-arid watershed in Iran using regional climate models
Journal of Water and Climate Change, 2014
This paper aims to summarize in detail the results of the climate models under various scenarios by temporal and spatial analysis in the semi-arid Karkheh Basin (KB) in Iran, which is likely to experience water shortages. The PRECIS and REMO models, under A2, B2 and A1B scenarios, have been chosen as regional climate models (RCMs). These regional climate models indicate an overall warming in future in KB under various scenarios. The increase in temperature in the dry months (June, July and August) is greater than the increase in the wet months (January, February, March and April). In order to perform climate change impact assessment on water resources, the Arc-SWAT 9.3 model was used in the study area. SWAT (Soil and Water Assessment Tool) model results have been obtained using present and future climate data. There is an overall reduction in the water yield (WYLD) over the whole of the KB. The deficit of WYLD is considerable over the months of April to September throughout KB due to the increase in average temperature and decrease in precipitation under various emission scenarios. Statistical properties in box-and-whisker plots have been used to gain further understanding relevant to uncertainty analysis in climate change impacts. Evaluation of uncertainty has shown the highest uncertain condition under B2.
Sustainability
Rivers are the main source of fresh water in mountainous and downstream areas. It is crucial to investigate the possible threats of climate change and understand their impact on river watersheds. In this research, climate change’s impact on the mountainous watershed of the Jajrood River, upstream of Latyan Dam in Iran, was assessed by using a multivariate recursive quantile-matching nesting bias correction (MRQNBC) and the soil and water assessment tool (SWAT). Also, this study considered ten global circulation models (GCMs) from the coupled model intercomparison project phase VI (CMIP6). With a higher correlation coefficient, the MIROC6 model was selected among other models. For the future period of 2031–2060, the large-scale outputs of the MIROC6 model, corresponding to the observational data were extracted under four common socioeconomic path scenarios (SSPs 1–2.6, 2–4.5, 3–7.0, 5–8.5). The bias was corrected and downscaled by the MRQNBC method. The downscale outputs were given t...
2021
Drought appears as an environmentally integral part of climate change. This study was conducted to investigate the impact of climate change on climate variables, meteorological drought and pattern recognition for severe weather conditions in the Karkheh River Basin in the near future (2043-2071) and the distant future (2072-2100). The outputs of GFDL-ESM2, HadGEM2-ES, IPSL-CM5A-LR, MIROC and NoerESM1-M models were downscaled under the RCP 2.6 and RCP8.5 scenarios using the Climate Change Toolkit (CCT) at 17 meteorological stations. Then the SPEI index was calculated for the base and future periods and compared with each other. The results showed that the basin annual precipitation will likely increase in both future periods, especially in the near future. The annual maximum and minimum temperatures may also increase especially in the distant future. The rise in the maximum temperature will be possibly greater than the minimum temperature. Seasonal changes in maximum and minimum temp...
Water Supply, 2020
Climate change is one of the leading factors that directly affect hydrological processes in large basins. This study assesses the impacts of climate change on streamflow, sediment and crop yield, actual evapotranspiration (AET), and water budget. In addition, the effects of land use and land cover (LULC) alteration with climate change on streamflow and sediment yield have been evaluated in the Dez river basin in the southwest of Iran. Five General Circulation Models (GCMs) based on two scenarios, Representative Concentration Pathway (RCP) 4.5 and RCP 8.5 for the near period (2021–2040) are considered. Hydrological simulation is performed using the Soil and Water assessment tool (SWAT) with good performance in the calibration (1990 to 2010) and validation (2010 to 2017) periods. The precipitation and temperature projected show a major upward trend related to the base period. The results showed that climate change increases the runoff and sediments. In addition, results projected that...
Earth Science Informatics, 2021
This study sets out to simulate various hydrological responses to climate change. The semi-distributed hydrologic model of the Soil and Water Assessment Tool, SWAT, was used to simulate different parts of the hydrological cycles. The comprehensive assessment of the effect of climate change on runoff, crop yield, and water balance in Siminehroud and Zarrinehroud watersheds is the novelty of this research. The simulation period was from 1988 to 2014. The runoff model was calibrated using the plant parameters, and the initial crop yield was used to calibrate the model. During the calibration and validation periods, the statistical measures, namely NS and R 2 , were obtained as 0.69 and 0.82, respectively. Using the multisite statistical downscaling of the LARS-WG climate model, we introduced the future climatic conditions as inputs to the model based on two optimistic (RCP2.6) and pessimistic (RCP8.5) scenarios. The most significant changes in the runoff in the upcoming period, was in June, reduced by 4.2 m 3 s −1 , and in May, increased by 4.8 m 3 s −1 in the optimistic scenario. In the RCP8.5 pessimistic scenario, the most significant runoff change was observed in June and October. The results indicated that these changes would lead to a decrease in the main crops across the region.