Scholarlink

<p>Drought is one of the most commonly damaging climate-related environmental hazards in the world. Traditionally, it is defined as the deviation of cumulative rainfall from long term normal condition, which results soil moisture stress, disturbance of ecosystem, crop failure and extensive socioeconomic losses. For a long periods drought assessment has depended on only precipitation based indices. However, under the recent climate change, these approaches are inadequate. Currently, rising temperatures intensify atmospheric evaporative demand, modify precipitation patterns, and results in drought becoming more severe. This pattern has intensifies the hydrological deficits, alter land surface phenology, and affects the livelihoods of the community due to following crop failure and water resource scarcity. The impacts of drought are more severe in developing countries where their livelihoods are highly depending on rain fed agriculture and climate sensitive water resources. Thus, this paper reviews the conceptual foundation of drought and examines the recent emerging technologies for drought risk assessment and modeling. The paper synthesizes, recent advancement of remote sensing technology that provides continuous, and multi-temporal observation of the Earth’s surface and the atmosphere to drought risk assessment and modeling. Furthermore, it indicates the role GeoAI in capturing nonlinear interactions among different variables in drought assessment and modeling. Thus, based on the review of literature, GeoAI frameworks play a significant role in drought modeling by integrating multisource data with advanced computational models. The review highlights the emergence of Big Earth Data, cloud computing platforms, Internet of Things (IoT) based smart sensors and multisource data fusion for real time drought monitoring and multiscale drought forecasting. Generally, the findings of this literature review indicate that, there is a paradigm shift in drought modeling towards integrative modeling frameworks. Hence, emerging technologies enhance drought modeling as well as support proactive decision making in climate mitigation and adaptation.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Emerging technologies to multiscale drought risk assesment and modeling in the era of Big Earth Data and GeoAI

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年6月20日

查看全文
  • Ayalneh Yedem Fentie,
  • Daniel Ayalew Mengistu

摘要

Drought is one of the most commonly damaging climate-related environmental hazards in the world. Traditionally, it is defined as the deviation of cumulative rainfall from long term normal condition, which results soil moisture stress, disturbance of ecosystem, crop failure and extensive socioeconomic losses. For a long periods drought assessment has depended on only precipitation based indices. However, under the recent climate change, these approaches are inadequate. Currently, rising temperatures intensify atmospheric evaporative demand, modify precipitation patterns, and results in drought becoming more severe. This pattern has intensifies the hydrological deficits, alter land surface phenology, and affects the livelihoods of the community due to following crop failure and water resource scarcity. The impacts of drought are more severe in developing countries where their livelihoods are highly depending on rain fed agriculture and climate sensitive water resources. Thus, this paper reviews the conceptual foundation of drought and examines the recent emerging technologies for drought risk assessment and modeling. The paper synthesizes, recent advancement of remote sensing technology that provides continuous, and multi-temporal observation of the Earth’s surface and the atmosphere to drought risk assessment and modeling. Furthermore, it indicates the role GeoAI in capturing nonlinear interactions among different variables in drought assessment and modeling. Thus, based on the review of literature, GeoAI frameworks play a significant role in drought modeling by integrating multisource data with advanced computational models. The review highlights the emergence of Big Earth Data, cloud computing platforms, Internet of Things (IoT) based smart sensors and multisource data fusion for real time drought monitoring and multiscale drought forecasting. Generally, the findings of this literature review indicate that, there is a paradigm shift in drought modeling towards integrative modeling frameworks. Hence, emerging technologies enhance drought modeling as well as support proactive decision making in climate mitigation and adaptation.