Analyzing climate change and its effects on drought and water scarcity (case study: Ardabil, Northwestern Province of Iran, Iran)

This study analyses the impact of climate change on the inflows, sediment loads, and nutrient inputs to the Sabalan dam reservoir, a warm monomictic lake located northwest of Iran. For this purpose, the Soil and Water Assessment Tool (SWAT) was calibrated (2005–2018) and validated (2001–2004). Future climate-based data under the AR5 emission scenarios were obtained from the HadGEM2–ES general circulation model and then downscaled using the LARSWG 6.0. The tuned SWAT model was used to investigate the climate change impact on the hydrological processes and pollution loads to the Sabalan dam reservoir. Our findings based on the Nash–Sutcliffe efficiency coefficient and the coefficient of determination indicated an acceptable performance of the SWAT model in the simulation of inflows, sediment loads, and nutrient inputs to the reservoir. Inflow and sediment load to the reservoir will increase during the period of 2030–2070 compared to the base period (1998–2018). The annual total nitrogen (phosphorus) load to the reservoir will increase by 8.5% (9.4%), 7.3% (8.2%), and 5% (3.4%) under the emission scenarios of RCP2.6, RCP4.5, and RCP8.5, respectively. An increase in sediment loads and nutrient inputs to the Sabalan dam reservoir will significantly exacerbate the reservoir eutrophic condition, leading to water quality deterioration with acute consequences for the positive functions of the dam.

Section: Projected Precipitation and Air Temperature In The Study Regionsupporting

confidence: 91%

Climate Change Impact on Inflow and Nutrient Loads to a Warm Monomictic Lake

Parmas,

Noori,

Hosseini

et al. 2023

“…Droughts carry profound implications across various sectors within Iranian cities [66]. The strain on water resources affects not only the daily lives of residents but also the economic vitality of these metropolises.…”

Section: Discussionmentioning

confidence: 99%

A CMIP6 Multi-Model Analysis of the Impact of Climate Change on Severe Meteorological Droughts through Multiple Drought Indices—Case Study of Iran’s Metropolises

Afsari,

Nazari-Sharabian,

Hosseini

et al. 2024

This study extensively explores the impact of climate change on meteorological droughts within metropolises in Iran. Focused on Tehran, Mashhad, Isfahan, Karaj, Shiraz, and Tabriz, this research employed CMIP6 climate models under varying climate change scenarios (SSPs) to forecast severe meteorological droughts spanning the period from 2025 to 2100. The investigation utilized a diverse set of drought indices (SPI, DI, PN, CZI, MCZI, RAI, and ZSI) to assess the drought severity in each city. This study is crucial as it addresses the pressing concerns of rapidly decreasing water levels in Iran’s dams, serious declines in underground aquifers, and the compounding issues of land subsidence and soil erosion due to excessive groundwater withdrawal in the face of severe droughts. This study culminated in the generation of box plots and heatmaps based on the results. These visual representations elucidated the distribution of the drought values under different indices and scenarios and provided a depiction of the probability of severe drought occurrences until the end of the century for each city. The resulting findings serve as invaluable tools, furnishing policymakers with informed insights to proactively manage and fortify metropolitan resilience against the evolving challenges posed by a changing climate.

“…Additionally, the temperature is growing more rapidly. The researchers assessed the feasibility of drought prediction in Erazcose using the SPI approach and discovered that yearly drought is forecast using spring rainfall with a correlation coefficient of 0.89 and a square root of a projected error of 5.7 • [67]. The researchers conducted an assessment of the hydrological and hydrological drought conditions in the south-eastern part of Lake Urmia.…”

Section: Case Study Iranmentioning

confidence: 99%

Scientometric Analysis-Based Review for Drought Modelling, Indices, Types, and Forecasting Especially in Asia

Kong

et al. 2021

An extended drought period with low precipitation can result in low water availability and issues for humans, animals, and plants. Drought forecasting is critical for water resource development and management as it helps to reduce negative consequences. In this study, scientometric analysis and manual comprehensive analysis on drought modelling and forecasting are used. A scientometric analysis is used to determine the current research trend using bibliometric data and to identify relevant publication field sources with the most publications, the most frequently used keywords, the most cited articles and authors, and the countries that have made the greatest contributions to the field of water resources. This paper also tries to provide an overview of water issues, such as drought classification, drought indices, historical droughts, and their impact on Asian countries such as China, Pakistan, India, and Iran. There have been many models established for this purpose and choosing the appropriate model for study is a long procedure for researchers. An appropriate, comprehensive, pedagogical study of model ideas and historical implementations would benefit researchers by helping them to avoid overlooking viable model options, thus reducing their time spent on the topic. As a result, the goal of this paper is to review drought-forecasting approaches and recommend the best models for the Asian region. The models are divided into four categories based on their mechanisms: Regression analysis, stochastic modelling, machine learning, and dynamic modelling. The basic concepts of each approach in terms of the model’s historical use, benefits, and limitations are explained. Finally, prospects for future drought research in Asia are discussed as well as potential modelling techniques.