Uncertainty plays a key role in hydrological modeling and forecasting, which can have tremendous environmental, economic, and social impacts. Therefore, it is crucial to comprehend the nature of this uncertainty and identify its scope and effects in a way that enhances hydrological modeling and forecasting. During recent decades, hydrological researchers investigated several approaches for reducing inherent uncertainty considering the limitations of sensor measurement, calibration, parameter setting, model conceptualization, and validation. Nevertheless, the scope and diversity of applications and methodologies, sometimes brought from other disciplines, call for an extensive review of the state-of-the-art in this field in a way that promotes a holistic view of the proposed concepts and provides textbook-like guidelines to hydrology researchers and the community. This paper contributes to this goal where a systematic review of the last decade's research (2010 onward) is carried out. It aims to synthesize the theories and tools for uncertainty reduction in surface hydrological forecasting, providing insights into the limitations of the current state-of-the-art and laying down foundations for future research. A special focus on remote sensing and multi-criteria-based approaches has been considered. In addition, the paper reviews the current state of uncertainty ontology in hydrological studies and provides new categorizations of the reviewed techniques. Finally, a set of freely accessible remotely sensed data and tools useful for uncertainty handling and hydrological forecasting are reviewed and pointed out.

中文翻译：

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减少水文预报不确定性的方法概述：进展和挑战


不确定性在水文建模和预报中起着关键作用，这可能会对环境、经济和社会产生巨大影响。因此，理解这种不确定性的性质并以增强水文建模和预测的方式确定其范围和影响至关重要。近几十年来，考虑到传感器测量、校准、参数设置、模型概念化和验证的局限性，水文研究人员研究了几种减少固有不确定性的方法。然而，应用和方法的范围和多样性（有时来自其他学科）要求对该领域的最新技术进行广泛审查，以促进对拟议概念的整体看法，并为水文学研究人员和社区提供类似教科书的指南。本文有助于实现这一目标，对过去十年（2010 年以后）的研究进行了系统回顾。它旨在综合降低地表水文预报不确定性的理论和工具，提供对当前最新技术的局限性的见解，并为未来的研究奠定基础。已经考虑了对遥感和基于多标准的方法的特别关注。此外，本文回顾了水文研究中不确定性本体论的现状，并提供了对所审查技术的新分类。最后，回顾并指出了一组可用于不确定性处理和水文预报的免费可访问的遥感数据和工具。