HYDROLOGICAL MODELLING FOR THE PREVENTION AND THE MANAGEMENT OF WATER SHORTAGE IN AGRICULTURE
Tesi di Dottorato
Data di Pubblicazione:
2017
Citazione:
HYDROLOGICAL MODELLING FOR THE PREVENTION AND THE MANAGEMENT OF WATER SHORTAGE IN AGRICULTURE / A. Borghi ; tutor: A. Facchi; coodinatore: D. Bassi. DIPARTIMENTO DI SCIENZE AGRARIE E AMBIENTALI - PRODUZIONE, TERRITORIO, AGROENERGIA, 2017 Feb 24. 29. ciclo, Anno Accademico 2016. [10.13130/borghi-anna_phd2017-02-24].
Abstract:
In recent decades, frequent and severe droughts have occurred in several countries of the world under nearly all climatic regimes. Since the middle 20th century, drought areas have globally increased, and, more specifically, in southern and central Europe. Drought risk is expected to increase in the near future as a result of the climate change, leading to a decline in precipitation and an increase in air temperatures, and consequently in evapotranspiration rates in several regions, including southern Europe and the Mediterranean region.
Droughts can significantly affect the agricultural sector since they provoke losses in crop yields and livestock production, increased insect infestations, plant diseases and wind erosion. Moreover, low rainfall during the growing season may affect irrigated agriculture over subsequent years, as a result of low levels of water in reservoirs and groundwater aquifers.
In Europe, the monitoring and assessment of drought is entrusted to the European Drought Observatory (EDO), that applies a multi-indicator approach, based on earth observations (EOs) and hydrological modelling data. EDO indicators are computed considering rainfed agriculture, predominant in middle and northern Europe, and are produced on a 5 km grid. In southern Europe, however, the implementation of drought-coping measures (irrigation) can partially or completely alleviate the impacts of potentially severe droughts. Therefore, for these conditions, specific water scarcity indicators explicitly considering irrigation among the water inputs to agro-ecosystems need to be developed and adopted to inform and support stakeholders and decision makers of irrigated regions.
In this context, the main objective of the Ph.D. thesis is the presentation of the Transpirative Deficit Index (TDI), a newly developed indicator for the monitoring and the management of Water Scarcity and Drought phenomena based on the use of hydrological modelling, applied at a spatial scale of interest for end-users (250 m grid) and suited for the assessment of water scarcity and drought in Italy as well as in other southern European countries. In particular, TDI was developed as a new module integrated into the spatially distributed hydrological model IdrAgra, and in the Ph.D. research it was tested over the Irrigation District of Media Pianura Bergamasca (IDMPB), considering a simulation period of 22 years (1993-2014) and subdividing the territory by means of a grid with cells of 250 m×250 m.
As a first step in the thesis, D TDI was described as an agricultural drought index focusing on overcoming the limitation of other approaches, not taking into account with sufficient detail land cover and soil properties. The D TDI is based on the calculation of the spatially distributed actual transpiration deficit, to determine the level of drought experienced by crops within the single model cells; thus, it can provide a much more accurate measure of agricultural drought at the irrigation district scale than the one that could be achieved through meteorological drought indices such as SPI or SPEI. The auto-correlation analysis of D-TDI showed to be positive with a persistence of 30 days for the two more widespread crops in the study area, maize and permanent grass. The analysis demonstrated also that soils characterized by a high available water content can more easily compensate dry spells. Finally, a positive significant correlation between D-TDI and SPI was observed for maize, with a persistence of 40 days, while no correlation was observed for permanent grass, probably related to cutting cycles, that could mask the relation between storage capacity and short-time variability of the meteorological conditions.
Successively, a methodology to compute crop yield using mode
Tipologia IRIS:
Tesi di dottorato
Keywords:
Agricultural drought; Indicator; Hydrological model; Transpirative Deficit Index; Water scarcity; Landsat; Earth Observation
Elenco autori:
A. Borghi
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