Testing climate resilience of irrigated agriculture with an online drought risk management tool

19:00 Tuesday 28 May

PO178

PS16

 

Lamprini Papadimitriou (United Kingdom) 1; Ian Holman (United Kingdom) 1; Jerry Knox (United Kingdom) 1; Mick Redman (United Kingdom) 1; David Haro (Spain) 2

1 - Cranfield Water Science Institute; 2 - Estación Experimental de Aula Dei - Centro Superior de Investigaciones Científicas (EEAD - CSIC)

Introduction

Irrigated agriculture is a sector of key importance for food security and economic development, currently experiencing multiple stressors due to rising water demands, competition between sectors for the availability of resources, climate related uncertainties, and droughts. The UK relies on supplementary irrigation to ensure the quality and quantity of many of its high-value fruit and vegetables. An extra stressor for these farms are possible regulatory changes to farmers’ water abstraction licenses.

D-Risk (www.d-risk.eu) is a freely available web-tool, developed by Cranfield University in collaboration with agricultural stakeholders, to help irrigated farming businesses understand and manage their current and future drought and abstraction risks.

Objectives

To explore how the management of current drought risk by irrigated businesses using D-Risk provides resilience to future climate change.

Methods

D-Risk is forced by an ensemble of 100 gridded series of 30-year simulated ‘current’ weather covering the UK from the Weather@Home 2 (w@h2) regional climate model to account for the natural climate variability. 100 time series of future weather for the Near Future (2020-2049) and Far Future (2070-2099) under RCP 8.5 are also used as forcing. Other data needed are information on a farm’s cropping and irrigation patterns, local soil data and abstraction licenses. The tool then calculates the probability distribution function of annual irrigation deficit and license headroom.

Results

Farmers are reluctant to consider adaptation to climate change but are comfortable with adapting to natural climate variability. For two case studies of farms of different cropping and irrigation patterns, the risk profiles produced by ‘current’ and ‘future’ climate data are used to assess the impacts of climate change on annual irrigation deficit, to examine the extent to which adapting to the natural variability of historical climate provides resilience to future climatic trends.

Conclusions

This work is significant to clarify whether the risk reduction adaptation measures for irrigated agriculture, based on current climate variability, are resilient to operate under climate change. This outcome will then be used in D-Risk to support the design of climate resilient reservoirs to reduce water related risks at the farm level. Another important outcome of this work is that due to the user engagement with the tool, D-Risk acts as a science translation tool to familiarize farmers with the notions of climate change impacts and uncertainties relating to drought risk, helping to bridge the gap between short and long-term planning and possibly foster participatory approaches in water management.