This thesis examines how information can benefit drought management decisions at the basin scale. Three perspectives are tested. The question is first approached from a data-centric perspective, assessing the usefulness of remotely sensed datasets to detect early stages of drought and determining how much time can be gained to inform operational land and water management practices. A user-centric approach is then followed, identifying through semi-structured interviews the information use and needs voiced by farmers and reservoir operators to support water allocation decisions during droughts, and quantifying the value of (new) information to support these decisions through modelling. Lastly, the user-centric and data-centric perspectives are combined to assess the usefulness of seasonal forecasts of water availability to support water allocation decisions in irrigated agriculture through a risk-based approach and the factors that have an impact on that usefulness.

The assessment from the user-centric perspective provided essential knowledge on the decisions, the courses of action available to decision makers, and the conditions that determine the selection of one of the available courses of action at each decision point. This knowledge is necessary to assess whether the information can change the decision outcome, which is a prerequisite for its usefulness. The user perspective also helped confirm there is a perceived need for additional information among the decision makers interviewed. The assessment from the data-centric perspective showed the ability of the selected datasets to provide key information required by the decision makers in a timely manner, while the combined perspective allowed to demonstrate the capacity of information available from seasonal forecasts to actually impact the outcome of the decision. These three perspectives show that there are multiple factors that need to be considered when assessing the usefulness of information. Notably, these are (i) the ability of information to provide either the observations or predictions that are needed by the decision maker at the time when they are needed, and (ii) the capacity of the decision maker to change the course of action as a result of the available information. The results show that both of these factors depend on the options available to the decision maker. These may differ for different individuals, depending also on the level of risk aversion decision makers have as well as their technical capacities, and the context of the decision. Changes in the market value of goods, or weather variability, may also impact the usefulness of information for the decisions analysed in this research.

Bringing these perspectives and their respective methods together contributes to fill the gap between technical and human-centred approaches to assess the usefulness of information for drought management decisions.

Seasonal forecasts of water availability have clear potential benefit for decisions in irrigated agriculture. This potential depends in part on how accurate the information provided is. The actual benefit, however, depends on how the information is used in the decisions, by whom, and the outcome of those decisions. In this paper we assess how useful seasonal forecasts are in supporting drought management decisions by farmers at the irrigation district level. We model the decisions irrigated farmers make on what and when to plant in the Ebro basin (Spain), and the interconnected decisions reservoir operators make on whether to apply curtailments to the water allocated to farmers. The modelled farmers are supplied from a reservoir with capacity for a single irrigation season and therefore their decisions are conditioned by the expected water availability through to the end of the season. Different farmer behaviours are considered as a function of their risk averseness and their technical capacity. The value of seasonal streamflow forecasts to inform these decisions is compared against that of current practice using extrapolated historical records, as well as against a reference forecast based on climatology. Results show that seasonal forecasts of water availability have skill, albeit limited. How salient information is to the decisions that farmers make, however, differs for each type of farmer as they take key decisions at different points in the season. As a consequence, seasonal forecast information is found to not serve the various farmer types considered equally. Our results illustrate how assessing the usefulness of information to servicing a decision can be approached from a combined technical and user-centric perspective.

The implementation of drought management plans contributes to reduce the wide range of adverse impacts caused by water shortage. A crucial element of the development of drought management plans is the selection of appropriate indicators and their associated thresholds to detect drought events and monitor their evolution. Drought indicators should be able to detect emerging drought processes that will lead to impacts with sufficient anticipation to allow measures to be undertaken effectively. However, in the selection of appropriate drought indicators the connection to the final impacts is often disregarded. This paper explores the utility of remotely sensed data sets to detect early stages of drought at the river basin scale, and how much time can be gained to inform operational land and water management practices. Six different remote sensing data sets with different spectral origin and measurement frequency are considered, complemented by a group of classical in situ hydrologic indicators. Their predictive power to detect past drought events is tested in the Ebro basin. Qualitative (binary information based on media records) and quantitative (crop yields) data of drought events and impacts spanning a period of 12 years are used as a benchmark in the analysis. Results show that early signs of drought impacts can be detected up to some 6 months before impacts are reported in newspapers, with the best correlation-anticipation relationships for the Standard Precipitation Index (SPI), the Normalized Difference Vegetation Index (NDVI) and Evapotranspiration (ET). Soil Moisture (SM) and Land Surface Temperature (LST) offer also good anticipation, but with weaker correlations, while Gross Primary Production (GPP) presents moderate positive correlations only for some of the rainfed areas. Although classical hydrological information from water levels and water flows provided better anticipation than remote sensing indicators in most of the areas, correlations were found to be weaker. The indicators show a consistent behaviour with respect to the different levels of crop yield in rainfed areas among the analysed years, with SPI, NDVI and ET providing again the stronger correlations. Overall, the results confirm remote sensing products’ ability to anticipate reported drought impacts and therefore appear as a useful source of information to support drought management decisions.