In this study, the effectiveness of a bivariate analysis of agricultural drought characteristics for irrigation planning was evaluated. The case study was conducted in locations in central Italy and was based on olive crops which are widely grown in that area under rainfed or deficit irrigation regimes. For each locality, the available time series of daily precipitation and maximum and minimum temperatures were used to simulate the daily soil water dynamics (SWt) for olive crops. The simulation was performed assuming 10 irrigation strategies, different for both the volume and date of the interventions. By applying the Theory of Runs to SWt, with a threshold corresponding to the readily available water, the agricultural drought events in the time series were identified and characterised by their duration D (days) and severity S (i.e. the cumulative evapotranspiration deficit in mm) for each locality and strategy. A 2-parameter Gamma distribution was fitted to both D and S, whilst their dependence structure was modelled by a Gumbel copula. The evaluation of the best irrigation strategy in each locality was obtained by comparing the contour lines of the pairs (d,s) having a 10-year return period for the condition D ≥ d AND S ≥ s. Results showed a great influence of both climate and irrigation strategy on the joint distribution of D and S. Some strategies, despite a very similar behaviour in the severity, differed a lot in terms of the associated values of duration, thus denoting different dynamics of water stress (more or less intense). Among the single-irrigation strategies, the optimal one was usually represented by an application at the end of June. Among the double-irrigation strategies, the optimal one involved two interventions, one at the end of June and one at the end of July. These results were also discussed taking into account the corresponding probability of consecutive severe drought events.

Bivariate analysis of drought duration and severity for irrigation planning

Vergni L.
;
Todisco F.;Mannocchi F.
2020

Abstract

In this study, the effectiveness of a bivariate analysis of agricultural drought characteristics for irrigation planning was evaluated. The case study was conducted in locations in central Italy and was based on olive crops which are widely grown in that area under rainfed or deficit irrigation regimes. For each locality, the available time series of daily precipitation and maximum and minimum temperatures were used to simulate the daily soil water dynamics (SWt) for olive crops. The simulation was performed assuming 10 irrigation strategies, different for both the volume and date of the interventions. By applying the Theory of Runs to SWt, with a threshold corresponding to the readily available water, the agricultural drought events in the time series were identified and characterised by their duration D (days) and severity S (i.e. the cumulative evapotranspiration deficit in mm) for each locality and strategy. A 2-parameter Gamma distribution was fitted to both D and S, whilst their dependence structure was modelled by a Gumbel copula. The evaluation of the best irrigation strategy in each locality was obtained by comparing the contour lines of the pairs (d,s) having a 10-year return period for the condition D ≥ d AND S ≥ s. Results showed a great influence of both climate and irrigation strategy on the joint distribution of D and S. Some strategies, despite a very similar behaviour in the severity, differed a lot in terms of the associated values of duration, thus denoting different dynamics of water stress (more or less intense). Among the single-irrigation strategies, the optimal one was usually represented by an application at the end of June. Among the double-irrigation strategies, the optimal one involved two interventions, one at the end of June and one at the end of July. These results were also discussed taking into account the corresponding probability of consecutive severe drought events.
2020
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11391/1464829
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 12
  • ???jsp.display-item.citation.isi??? 10
social impact