In the present study, we review the methods and approaches used for uncertainty handling in hydrological forecasting of streamflow, floods, and snow. This review has six thematic sections: (1) general trends in accounting uncertainties in hydrological forecasting, (2) sources of uncertainties in hydrological forecasting, (3) methods used in the studies to address uncertainty, (4) multi-criteria approach for reducing uncertainty in hydrological forecasting and its applications (5) role of remote sensing data sources for hydrological forecasting and uncertainty handling, (6) selection of hydrological models for hydrological forecasting. Especially, a synthesis of the literature showed that approaches such as multi-data usage, multi-model development, multi-objective functions, and pre-/post-processing are widely used in recent studies to improve forecasting capabilities. This study reviews the current state-of-the-art and explores the constraints and advantages of using these approaches to reduce uncertainty. The comparative summary provided in this study offers insights into various methods of uncertainty reduction, highlighting the associated advantages and challenges for readers, scientists, hydrological modelers, and practitioners in improving the forecast task. A set of freely accessible remotely sensed data and tools useful for uncertainty handling and hydrological forecasting are reviewed and pointed out.
<p>Globally, the hydro-climatological parameters such as precipitation, temperature, and soil moisture are getting more uncertain and varying regionally as well as seasonally with the changing climate. The Nordic region and the regional agriculture are no exception to this. Recent global studies have projected the increasing trend of precipitation during winter and autumn in Northern Europe. Whereas, the declining trend during spring and summer. The studies further lead to the resulting decline in mean soil moisture that consequently will increase the potential for agricultural drought. Additionally, the summer droughts are already getting highlighted locally as the agriculture in the region experiencing substantial yield losses besides excessive rainfall as a common issue. Therefore, supplemental irrigation, and controlled drainage during water-sensitive growth stages of crops, or crop selection could be potential alternatives and need further investigation. In this study, we present an integrated irrigation and drainage approach (IIDA) based on Water Balance Simulation (WBS) to reduce the negative impact of summer droughts in Nordic agriculture. A WBS is developed in the present study for potato crop fields in Tyrn&#228;v&#228; municipal area of Finland to examine the required irrigation or drainage during the cropping season. The model considers precipitation, temperature, and soil water-holding properties as inputs to simulate daily water availability in the crop root zone and provide output as the required amount of either irrigation or drainage or a combination of both for the cropping season from 2000 to 2020. The results showed that around 20% of the mentioned period (2003, 2006, 2018, and 2019), the potato fields required supplemental irrigation between 12-120 mm during the entire season. Furthermore, except for 2009 and 2018, an annual average of 44 mm of drainage was required due to extreme rainfall events. The findings of the study will benefit to increasing the sustainability of agricultural yield in the Nordic region by reducing the negative impact of summer droughts.</p>
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