The Impact of Climate Change on Climate Variables and Meteorological Drought Using the climate change Toolkit (CCT) in the Karkheh River Basin, Iran

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 temperatures and precipitation indicate that the greatest increase in temperature and decrease in precipitation may occur in summer. Hence meteorological drought was also found to increase in the distant future. The application of the CCT model in the region showed that at least once a wet period similar to the flood conditions of 2019 will be observed for the near future. There will also be at least one similar drought in 2014 for the distant future in the region. However, in previous climate studies, future events have not been calculated based on identifying the pattern of those events in the past.

Regional Frequency Analysis of Drought Severity and Duration in Karkheh River Basin - Iran Using Univariate L-Moments Method

Drought is one of the natural disasters that causes a great damage to the human life and natural ecosystems. The main differences are in the gradual effect of drought over a relatively long period; impossibility of accurately determining time of the beginning and end of drought; and geographical extent of the associated effects. On the other hand, lack of a universally accepted definition of drought has added to the complexity of this phenomenon. In the last decade, due to increasing frequency of drought in Iran and reduction of water resources, its consequences have become apparent and have caused problems for planners and managers. Therefore, in this study, to investigate severity and duration of meteorological, hydrological and agricultural drought in Karkheh River basin, regional frequency analysis of standardized precipitation index ( SPI ), standardized evapotranspiration index ( SEI ), standardized runoff index ( SRI ) and standardized soil moisture index ( SSI ) was performed using L-moments. Then, using Hosking and Wallis heterogeneity test, basin was divided into four homogeneous areas. After that, based on the Z statistic of goodness-of-fit test for each distribution, the best regional distribution function for each homogeneous region was selected. The results showed that hydrological drought occurs with a very short time delay in Karkheh River Basin after the meteorological drought and two indicators show meteorological and hydrological drought conditions well. Agricultural drought occurs after meteorological and hydrological drought, respectively, and its severity and duration are less than the other indicators. Meteorological, hydrological and agricultural droughts do not occur at the same time in all of the years and in general, the SPI drought Index shows the most severe droughts compared with the other three indices.

Bias correction capabilities of quantile mapping methods for rainfall and temperature variables

This study aims to conduct a thorough investigation to compare the abilities of QM techniques as a bias correction method for the raw outputs from GCM/RCM combinations. The Karkheh River basin in Iran was selected as a case study, due to its diverse topographic features, to test the performances of the bias correction methods under different conditions. The outputs of two GCM/RCM combinations (ICHEC and NOAA-ESM) were acquired from the CORDEX dataset for this study. The results indicated that the performances of the QMs varied, depending on the transformation functions, parameter sets, and topographic conditions. In some cases, the QMs' adjustments even made the GCM/RCM combinations' raw outputs worse. The result of this study suggested that apart from DIST, PTF:scale, and SSPLIN, the rest of the considered QM methods can provide relatively improved results for both rainfall and temperature variables. It should be noted that, according to the results obtained from the diverse topographic conditions of the sub-basins, the empirical quantiles (QUANT) and robust empirical quantiles (RQUANT) methods proved to be excellent options to correct the bias of rainfall data, while all bias correction methods, with the notable exceptions of performed PTF:scale and SSPLIN, performed relatively well for the temperature variable.

Assessment of streamflow decrease due to climate vs. human influence in a semiarid area

This paper uses the Budyko method to investigate mean annual streamflow changes, due to climate variation and human influence, in the important Karkheh River Basin in western Iran. To validate the results, hydrological modelling (HBV model) and Landsat 5 Thematic Mapper (TM) images were used for the study period between 1980 and 2012. The recently developed DBEST (Detecting Breakpoints and Estimating Segments in Trend) method identified an abrupt negative change in the streamflow trend in 1994–5. The results show that the observed streamflow decrease in the Karkheh River is associated with both climate variation and human influence. The combination of increased irrigated area (from 9 to 19 % of the total basin area), reduction of forests (from 11 to 3 %), and decreasing annual precipitation has significantly reduced streamflow in the basin. Moreover, the results show that the streamflow reduction in the Karkheh Basin is more sensitive to the change in precipitation than temperature.