The added value of robustness analysis for drought risk management

Drought risk refers to the expected value of yield loss. The risk reduction achieved by implementing an alternative strategy could be compared with the investment costs of the proposed strategy. This is the basis of risk-based decision making.

A risk analysis typically combines probabilities and consequences. Drought risk can be quantified based on the results with the RAM model, since each set of 1000 model runs

(either current or future climate) represents the probability distribution of the precipitation deficit. The expected value of the simulated yield deficits can thus be considered the risk (in % per year) for current and future climate conditions. Gouda inlet closure could also be taken into account by assigning a probability of occurrence to both the open and closed situation. The yield losses could also be expressed into monetary values, allowing quantification of monetary drought risk. All proposed measures will reduce the drought risk to some extent.

In the robustness analysis, we have separated the source of a drought, precipitation deficit/water supply deficit, from the consequences of a drought, crop yield loss. In a traditional risk analysis, different measures (reducing demand/increasing supply) will reduce the risk to some extent. The robustness criteria additionally show which aspect of the risk curve is affected by the measure. For example, increasing the storage capacity and increasing the contingency supply may have a comparable effect on the balance between demand and supply, but they score differently on the robustness criteria. We suggested that the storage capacity will increase the resistance threshold, but other aspects of robustness (manageability and Gouda inlet insensitivity) may not be affected, which means that high yield deficits under rare drought conditions are still possible. From a robustness perspective, the contingency supply option may therefore be more desirable. The robustness analysis thus provides additional insight that can be used in a drought risk decision making context.

6.5 Conclusion

This paper explored how system robustness analysis can be operationalized in the context of drought risk management, by proposing and quantifying system robustness criteria for an agricultural polder area in the Netherlands. To this end, we defined water shortage as a situation in which actual evaporation is smaller than the potential evaporation needed for crop growth. Water shortage is caused by a combination of precipitation deficit and water supply shortage, the latter caused by closure of the Gouda inlet. As a measure of drought impact we chose the relative crop yield deficit. We analysed how sensitive the yield deficit is for a change in precipitation deficit as

well as for a change in water supply, and we analysed how this robustness is affected by drought reduction measures.

The robustness was quantified by drawing a relationship between precipitation deficit and yield deficit, for two situations: a closed Gouda inlet and an open Gouda inlet throughout the season. This relationship was then used to quantify the four robustness criteria: resistance threshold, proportionality, manageability, and Gouda inlet insensitivity. Proportionality could not discriminate between the alternative configurations. Therefore, it seems not a relevant criterion in a drought context. The following system characteristics explained the high robustness scores of the studied drought risk system:

 A storage capacity of at least 160 mm

 Limited drought sensitivity of crops

 High diversity of crop types within the area in combination with a variation of drought sensitivity in time

 Small area with access to external water supply (sprinkler installations)

Furthermore, we showed that drought timing has a larger effect on the yield deficit than Gouda inlet closure. This can however change when more areas are irrigated. Installing sprinkler installations (as in extending the irrigated area) reduces the yield deficit for many conditions, but it also increases the water demand thereby increasing the dependence on water supply from Gouda. Because the Gouda inlet is not available under some conditions, a high dependence is not desirable. This can only be (partly) counteracted by also increasing the contingency supply capacity. When this capacity is not large enough, yield deficits can still occur under some conditions. The yield deficits under these conditions could be further decreased if the supply water would be prioritized for the high-value crops. Although this was not simulated in the case study, we expect that increasing the storage capacity will increase the resistance threshold, and reducing the crop sensitivity will enhance the manageability.

Robustness analysis provides insight into the conditions under which drought impacts can be expected. The use of a Rapid Assessment Model allowed simulating a large

number of time series of precipitation and evapotranspiration, which implicitly represented a large range of drought conditions.

The robustness analysis allowed comparing alternative strategies under a range of drought conditions and helps explaining the effectiveness of these strategies. We showed that a robustness analysis provides insight into which system characteristics are responsible for ‘no response’ under frequent drought conditions (resistance threshold) and ‘limited response’ under rare drought conditions (manageability). Although the case study results are specific for the Netherlands situation, we believe that the conceptual framework for system robustness analysis could be valuable for other drought risk systems as well. We therefore conclude that robustness analysis has added value for drought risk management under climate change.

Acknowledgements

The authors would like to thank Jules Beersma and Alexander Bakker (KNMI) for providing the climate data, and Marjolijn Haasnoot (Deltares and Technical University Delft) for providing the Rapid Assessment Model. This paper was funded by the Netherlands Knowledge for Climate programme.

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Discussion, conclusions and

recommendations