Drought and surface water ponding (DSP) are one of the major natural hazards affecting crop production, especially in low-land irrigated areas. This work focus on an irrigated area in north-eastern Italy, a territory of about 400k ha, part of the central Veneto, where water demands is met through a mechanical and well-regulated widespread distribution of water resources. For this complex landscape, reliance on weather data alone is not sufficient to monitor areas of DSP, particularly when these data can be i) untimely, sparse, and incomplete, and ii) water inflows are mechanically controlled, with varying flow exchanges, not necessarily reflecting climatic fluctuations. Augmenting climatic data with satellite images to identify the location and severity of DSP phenomena, therefore, is a must for complete, up-to-date, and comprehensive coverage of current crop conditions. The objective of this research is to apply and standardize open source data to augment DSPmonitoring techniques. The study was conducted with 5 years (2015-2021) of Sentinel2-10m satellite images. Z-scores of the NDVI distribution are used to estimate the probability of occurrence of the present vegetation condition at a given location relative to the possible range of vegetative vigor, historically. This information is coupled with soil data, topographic information, and accurate information on the system water fluxes, to identify and target locations more susceptible to DSP. Findings indicate that the framework, along with other monitoring tools, is useful for assessing the extent and severity of DSP at a spatial resolution of 10m. The framework is capable of providing a near-real-time indicator of vegetation conditions within irrigated regions, and, more specifically, areas of varying water management conditions.

Drought and surface water ponding monitoring in irrigated landscapes

Zaccone, Claudio;
2022

Abstract

Drought and surface water ponding (DSP) are one of the major natural hazards affecting crop production, especially in low-land irrigated areas. This work focus on an irrigated area in north-eastern Italy, a territory of about 400k ha, part of the central Veneto, where water demands is met through a mechanical and well-regulated widespread distribution of water resources. For this complex landscape, reliance on weather data alone is not sufficient to monitor areas of DSP, particularly when these data can be i) untimely, sparse, and incomplete, and ii) water inflows are mechanically controlled, with varying flow exchanges, not necessarily reflecting climatic fluctuations. Augmenting climatic data with satellite images to identify the location and severity of DSP phenomena, therefore, is a must for complete, up-to-date, and comprehensive coverage of current crop conditions. The objective of this research is to apply and standardize open source data to augment DSPmonitoring techniques. The study was conducted with 5 years (2015-2021) of Sentinel2-10m satellite images. Z-scores of the NDVI distribution are used to estimate the probability of occurrence of the present vegetation condition at a given location relative to the possible range of vegetative vigor, historically. This information is coupled with soil data, topographic information, and accurate information on the system water fluxes, to identify and target locations more susceptible to DSP. Findings indicate that the framework, along with other monitoring tools, is useful for assessing the extent and severity of DSP at a spatial resolution of 10m. The framework is capable of providing a near-real-time indicator of vegetation conditions within irrigated regions, and, more specifically, areas of varying water management conditions.
Drought, surface water, monitoring, irrigated landscapes
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11562/1066443
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