On the spatio-temporal analysis of hydrological droughts from global hydrological models

The recent concerns for world-wide extreme events related to climate change have motivated the development of large scale models that simulate the global water cycle. In this context, analysis of hydrological extremes is important and requires the adaptation of identification methods used for river basin models. This paper presents two methodologies that extend the tools to analyze spatio-temporal drought development and characteristics using large scale gridded time series of hydrometeorological data. The methodologies are classified as non-contiguous and contiguous drought area analyses (i.e. NCDA and CDA). The NCDA presents time series of percentages of areas in drought at the global scale and for pre-defined regions of known hydroclimatology. The CDA is introduced as a complementary method that generates information on the spatial coherence of drought events at the global scale. Spatial drought events are found through CDA by clustering patterns (contiguous areas). In this study the global hydrological model WaterGAP was used to illustrate the methodology development. Global gridded time series of subsurface runoff (resolution 0.5°) simulated with the WaterGAP model from land points were used. The NCDA and CDA were developed to identify drought events in runoff. The percentages of area in drought calculated with both methods show complementary information on the spatial and temporal events for the last decades of the 20th century. The NCDA provides relevant information on the average number of droughts, duration and severity (deficit volume) for pre-defined regions (globe, 2 selected hydroclimatic regions). Additionally, the CDA provides information on the number of spatially linked areas in drought, maximum spatial event and their geographic location on the globe. Some results capture the overall spatio-temporal drought extremes over the last decades of the 20th century. Events like the El Niño Southern Oscillation (ENSO) in South America and the pan-European drought in 1976 appeared clearly in both analyses. The methodologies introduced provide an important basis for the global characterization of droughts, model inter-comparison of drought identified from global hydrological models and spatial event analyse

Hydrological drought : characterisation and representation in large-scale models

De verwachting is dat door klimaatverandering de intensiteit van droogte zal toenemen in verschillende gebieden op de wereld. Uitkomsten van vijf hydrologische modellen in combinate met drie klimaatmodellen voor het A2 emissie scenario zijn gebruikt om effecten van klimaatverandering op hydrologische droogte te analyseren voor verschillende stroomgebieden. Droogtes en lage afvoeren (maandelijkse 20ste percentiel waarden, Q20) zijn geïdentificeerd uit de uitkomsten van de hydrologische modellen voor een historische periode (1971–2000) en een periode in de toekomst (2071–2100). De gesimuleerde lage afvoeren voor de historische periode zijn vergeleken met geobserveerde lage afvoeren van de verschillende stroomgebieden. De modelcombinaties (combinatie van een klimaatmodel en een hydrologisch model), die de beste resultaten gaven, zijn gebruikt voor verdere analyse. In koude klimaten werd een verschuiving in het hydrologische regime (de piek van sneeuwsmelt zal eerder optreden) waargenomen en een verhoging van de lage afvoeren tussen de historische periode en de periode in de toekomst. Voor aride klimaten gaven de modelcombinaties aan dat omstandigheden nog droger zullen worden in de toekomst. Voor vochtige klimaten werden zowel drogere als nattere situaties verwacht op basis van de modelcombinatie

A generic method for hydrological drought identification across different climate regions

The identification of hydrological drought at global scale has received considerable attention during the last decade. However, climate-induced variation in runoff across the world makes such analyses rather complicated. This especially holds for the drier regions of the world (both cold and warm), where, for a considerable period of time, zero runoff can be observed. In the current paper, we present a method that enables to identify drought at global scale across climate regimes in a consistent manner. The method combines the characteristics of the classical variable threshold level method that is best applicable in regions with non-zero runoff most of the time, and the consecutive dry days (period) method that is better suited for areas where zero runoff occurs. The newly presented method allows a drought in periods with runoff to continue in the following period without runoff. The method is demonstrated by identifying droughts from discharge observations of four rivers situated within different climate regimes, as well as from simulated runoff data at global scale obtained from an ensemble of five different land surface models. The identified drought events obtained by the new approach are compared to those resulting from application of the variable threshold level method or the consecutive dry period method separately. Results show that, in general, for drier regions, the threshold level method overestimates drought duration, because zero runoff periods are included in a drought, according to the definition used within this method. The consecutive dry period method underestimates drought occurrence, since it cannot identify droughts for periods with runoff. The developed method especially shows its relevance in transitional areas, because, in wetter regions, results are identical to the classical threshold level method. By combining both methods, the new method is able to identify single drought events that occur during positive and zero runoff periods, leading to a more realistic global drought characterization, especially within drier environments

Drought at the global scale in the 2nd part of the 20th century (1963-2001)

The large impacts of drought on society, economy and environment urge for a thorough investigation. A good knowledge of past drought events is important for both understanding of the processes causing drought, as well as to provide reliability assessments for drought projections for the future. Preferably, the investigation of historic drought events should rely on observations. Unfortunately, for a global scale these detailed observations are often not available. Therefore, the outcome of global hydrological models (GHMs) and off-line land surface models (LSMs) is used to assess droughts. In this study we have investigated to what extent simulated gridded time series from these large-scale models capture historic hydrological drought events. Results of ten different models, both GHMs and LSMs, made available by the WATCH project, were compared. All models are run on a global 0.5 degree grid for the period 1963-2000 with the same meteorological forcing data (WATCH forcing data). To identify hydrological drought events, the monthly aggregated total runoff values were used. Different methods were developed to identify spatio-temporal drought characteristics. General drought characteristics for each grid cell, as for example the average drought duration, were compared. These characteristics show that when comparing absolute values the models give substantially different results, whereas relative values lead to more or less the same drought pattern. Next to the general drought characteristics, some documented major historical drought events (one for each continent) were selected and described in more detail. For each drought event, the simulated drought clusters (spatial events) and their characteristics are given for one month during the event. It can be concluded that most major drought events are captured by all models. However, the spatial extent of the drought events differ substantially between the models. In general the models show a fast reaction to rainfall and therefore also capture drought events caused by large rainfall anomalies. More research is still needed, since here we only looked at a few selected number of documented drought events spread over the globe. To assess more in detail if these large-scale models are able to capture drought, additional quantitative analyses are needed together with a more elaborated comparison against observed drought events

Global multimodel analysis of drought in runoff for the second half of the twentieth century

During the past decades large-scale models have been developed to simulate global and continental terrestrial water cycles. It is an open question whether these models are suitable to capture hydrological drought, in terms of runoff, on global scale. A multi-model ensemble analysis was carried out to evaluate if ten of such large-scale models agree on major drought events during the second half of the 20th century. Time series of monthly precipitation, monthly total runoff from ten global hydrological models, and their ensemble median have been used to identify drought. Temporal development of area in drought for various regions across the globe was investigated. Model spread was largest in regions with low runoff and smallest in regions with high runoff. In vast regions, correlation between runoff drought derived from the models and meteorological drought was found to be low. This indicated that models add information to the signal derived from precipitation and that runoff drought cannot directly be determined from precipitation data alone in global drought analyses with a constant aggregation period. However, duration and spatial extent of major drought events differed between models. Some models showed a fast runoff response to rainfall, which led to deviations from reported drought events in slowly responding hydrological systems. By using an ensemble of models, this fast runoff response was partly overcome and delay in drought propagating from meteorological drought to drought in runoff was included. Finally, an ensemble of models also allows to consider uncertainty associated with individual model structures

Human–water interface in hydrological modelling: current status and future directions

Over recent decades, the global population has been rapidly increasing and human activities have altered terrestrial water fluxes to an unprecedented extent. The phenomenal growth of the human footprint has significantly modified hydrological processes in various ways (e.g. irrigation, artificial dams, and water diversion) and at various scales (from a watershed to the globe). During the early 1990s, awareness of the potential for increased water scarcity led to the first detailed global water resource assessments. Shortly thereafter, in order to analyse the human perturbation on terrestrial water resources, the first generation of largescale hydrological models (LHMs) was produced. However, at this early stage few models considered the interaction between terrestrial water fluxes and human activities, including water use and reservoir regulation, and even fewer models distinguished water use from surface water and groundwater resources. Since the early 2000s, a growing number of LHMs have incorporated human impacts on the hydrological cycle, yet the representation of human activities in hydrological models remains challenging. In this paper we provide a synthesis of progress in the development and application of human impact modelling in LHMs. We highlight a number of key challenges and discuss possible improvements in order to better represent the human-water interface in hydrological models

Water level data in mangrove forests and mangrove restoration sites in SE Asia

Mangrove restoration projects, aimed at restoring important values of mangrove forests after degradation, often fail because hydrological conditions are disregarded. We present a simple, but robust methodology to determine hydrological suitability for mangrove species, which can guide restoration practice. In 15 natural and 8 disturbed sites (i.e. disused shrimp ponds) in three case study regions in south-east Asia, water levels were measured and vegetation composition was determined. Using an existing hydrological classification for mangroves, sites were classified into hydrological classes, based on duration of inundation, and vegetation classes, based on occurrence of mangrove species. For the natural sites hydrological and vegetation classes were similar, showing clear distribution of mangrove species from wet to dry sites. Application of the classification to disturbed sites showed that in some locations hydrological conditions had been restored enough for mangrove vegetation to establish, in some locations hydrological conditions were suitable for various mangrove species but vegetation had not established naturally, and in some locations hydrological conditions were too wet for any mangrove species (natural or planted) to grow. We quantified the effect that removal of obstructions such as dams would have on the hydrology and found that failure of planting at one site could have been prevented. The hydrological classification needs relatively little data, i.e. water levels for a period of only one lunar tidal cycle without additional measurements, and uncertainties in the measurements and analysis are relatively small. For the study locations, the application of the hydrological classification gave important information about how to restore the hydrology to suitable conditions to improve natural regeneration or to plant mangrove species, which could not have been obtained by estimating elevation only. Based on this research a number of recommendations are given to improve the effectiveness of mangrove restoration projects

Identification of changes in hydrological drought characteristics from a multi-GCM driven ensemble constrained by observed discharge

Drought severity and related socio-economic impacts are expected to increase due to climate change. To better adapt to these impacts, more knowledge on changes in future hydrological drought characteristics (e.g. frequency, duration) is needed rather than only knowledge on changes in meteorological or soil moisture drought characteristics. In this study, effects of climate change on droughts in several river basins across the globe were investigated. Downscaled and bias-corrected data from three General Circulation Models (GCMs) for the A2 emission scenario were used as forcing for large-scale models. Results from five large-scale hydrological models (GHMs) run within the EU-WATCH project were used to identify low flows and hydrological drought characteristics in the control period (1971–2000) and the future period (2071–2100). Low flows were defined by the monthly 20th percentile from discharge (Q20). The variable threshold level method was applied to determine hydrological drought characteristics. The climatology of normalized Q20 from model results for the control period was compared with the climatology of normalized Q20 from observed discharge of the Global Runoff Data Centre. An observation-constrained selection of model combinations (GHM and GCM) was made based on this comparison. Prior to the assessment of future change, the selected model combinations were evaluated against observations in the period 2001–2010 for a number of river basins. The majority of the combinations (82%) that performed sufficiently in the control period, also performed sufficiently in the period 2001–2010. With the selected model combinations, future changes in drought for each river basin were identified. In cold climates, model combinations projected a regime shift and increase in low flows between the control period and future period. Arid climates were found to become even drier in the future by all model combinations. Agreement between the combinations on future low flows was low in humid climates. Changes in hydrological drought characteristics relative to the control period did not correspond to changes in low flows in all river basins. In most basins (around 65%), drought duration and deficit were projected to increase by the majority of the selected model combinations, while a decrease in low flows was projected in less basins (around 51%). Even if low discharge (monthly Q20) was not projected to decrease for each month, droughts became more severe, for example in some basins in cold climates. This is partly caused by the use of the threshold of the control period to determine drought events in the future, which led to unintended droughts in terms of expected impacts. It is important to consider both low discharge and hydrological drought characteristics to anticipate on changes in droughts for implementation of correct adaptation measures to safeguard future water resources