Multilevel Drought Hazard Assessment under Climate Change Scenarios in Semi-Arid Regions—A Case Study of the Karkheh River Basin in Iran

Abstract

Studies using Drought Hazard Indices (DHIs) have been performed at various scales, but few studies associated DHIs of different drought types with climate change scenarios. To highlight the regional differences in droughts at meteorological, hydrological, and agricultural levels, we utilized historic and future DHIs derived from the Standardized Precipitation Index (SPI), Standardized Runoff Index (SRI), and Standardized Soil Water Index (SSWI), respectively. To calculate SPI, SRI, and SSWI, we used a calibrated Soil and Water Assessment Tool (SWAT) for the Karkheh River Basin (KRB) in Iran. Five bias-corrected Global Circulation Models (GCMs) under two Intergovernmental Panel on Climate Change (IPCC) scenarios projected future climate. For each drought type, we aggregated drought severity and occurrence probability rate of each index into a unique DHI. Five historic droughts were identified with different characteristics in each type. Future projections indicated a higher probability of severe and extreme drought intensities for all three types. The duration and frequency of droughts were predicted to decrease in precipitation-based SPI. However, due to the impact of rising temperature, the duration and frequency of SRI and SSWI were predicted to intensify. The DHI maps of KRB illustrated the highest agricultural drought exposures. Our analyses provide a comprehensive way to monitor multilevel droughts complementing the existing approaches.

Assessing the Uncertainty of Multiple Input Datasets in the Prediction of Water Resource Components

“…As shown, more than 50% of the observed discharges are within the 95PPU bands depicted with green shades in all configurations, except C3L1 and C3L2, where significant overestimations can be noticed, especially after 2000. A significant decrease is recorded in the observed values in the region at the end of the period due to severe droughts occurring after 2000 [44]. This can also be noticed in the temporal variation of rainfall for these datasets ( Figure S2).…”

A Guideline for Successful Calibration and Uncertainty Analysis for Soil and Water Assessment: A Review of Papers from the 2016 International SWAT Conference

“…In this special issue, Kamali et al [8] address the issue of the existence of many datasets and their effects on the assessment of water resources. They combined 4 different climate data with 2 different land-use maps to build 8 different models that they calibrated and validated.…”

“…11-Kamali et al [8] studied the impact of different databases on the water-resources estimates and concluded that while different databases may produce similar calibration results, the calibrated parameters are significantly different for different databases. They highlighted that "As the use of any one database among several produces questionable outputs, it is prudent for modelers to pay more attention to the selection of input data".…”

Impact of climate change on meteorological, hydrological and agricultural droughts in the Lower Mekong River Basin: a case study of the Srepok Basin, Vietnam

“…Moreover, von Gunten et al () used drought indices and the HydroGeoSphere hydrological model to project hydrological impacts of droughts in the context of climate change in the Lerma catchment (Spain) and indicated an increase in drought severity in the future. In another study, Kamali et al () assessed meteorological, agricultural and hydrological droughts in the Karkheh River Basin (Iran) using three drought indices and Soil and Water Assessment Tool (SWAT) and found that the frequency of extreme droughts is predicted to increase in the future. In those studies, a common implemented approach is using a hydrological model with two input data sets; one is historical hydro‐meteorological data from observations, and another is projected data through outputs of the general circulation models (GCMs) and the hydrological model.…”

“…The three drought indices have been widely used to evaluate the agricultural and hydro‐meteorological droughts (e.g. Leng et al , ; Kamali et al , ). Regarding the hydrological modelling, the SWAT model has been popularly used as a modelling tool to study on climate change impact on hydrology at a catchment scale.…”