Browsing by Author "Semenov, Mikhail M."

Now showing 1 - 1 of 1
  • Thumbnail Image
    ItemOpen Access
    Assessing future drought risks and wheat yield losses in England
    (Elsevier, 2020-11-24) Clarke, D.; Hess, Tim M.; Haro Monteagudo, David; Semenov, Mikhail M.; Knox, Jerry W.
    Droughts pose a major risk to agricultural production. By comparing the outputs from an ecophysiological crop model (Sirius) with four drought severity indicators (DSI), a comparative assessment of the impacts of drought risk on wheat yield losses has been evaluated under current (baseline) and two future climate scenarios. The rationale was to better understand the relative merits and limitations of each approach from the perspective of quantifying agricultural drought impacts on crop productivity. Modelled yield losses were regressed against the highest correlated variant for each DSI. A cumulative distribution function of yield loss for each scenario (baseline, near and far future) was calculated as a function of the best fitting DSI (SPEI-5July) and with the equivalent outputs from the Sirius model. Comparative analysis between the two approaches highlighted large differences in estimated yield loss attributed to drought, both in terms of magnitude and direction of change, for both the baseline and future scenario. For the baseline, the average year differences were large (0.25 t ha−1 and 1.4 t ha−1 for the DSI and Sirius approaches, respectively). However, for the dry year, baseline differences were substantial (0.7 t ha−1 and 2.7 t ha−1). For the DSI approach, future yield losses increased up to 1.25 t ha−1 and 2.8 t ha−1 (for average and dry years, respectively). In contrast, the Sirius modelling showed a reduction in future average yield loss, down from a baseline 1.4 t ha−1 to 1.0 t ha−1, and a marginal reduction for a future dry year from a baseline of 2.7 t ha−1 down to 2.6 t ha−1. The comparison highlighted the risks in adopting a DSI response function approach, particularly for estimating future drought related yield losses, where changing crop calendars and the impacts of CO2 fertilisation on yield are not incorporated. The challenge lies in integrating knowledge from DSIs to understand the onset, extent and severity of an agricultural drought with ecophysiological crop modelling to understand the yield responses and water use relations with respect to changing soil moisture conditions.