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Human interventions influence drought propagation and low flow in a number of ways. Abstraction decreases low flow and makes hydrological drought events more severe; water transfers do the opposite. Reservoirs change water availability in time, and, dependent on the reservoir management, low flow can be increased and hydrological drought shifted in time. Land surface changes affect evapotranspiration, infiltration and surface runoff processes, influencing the timing and severity of hydrological drought. Qualitative methods (e.g., interviews, surveys) and socio-hydrological models can give valuable insights into the complexity of human-water interactions. Socio-hydrological models can also be used to explore feedbacks of water management scenarios. To quantify of the effect of natural and human drivers several approaches using observations, modelling or a combination of both can be used. Here, we demonstrate the use of these approaches to selected case studies around the world and show that the human influence on low flow and hydrological drought can be both aggravating and alleviating.

The chapter describes two categories of process-based models, namely, hydrological and socio-hydrological models. It starts with an explanation of the modelling chain from climate drivers via process-based models to identification of hydrological and socio-hydrological drought characteristics. Then, the first category of process-based models is introduced, that is, hydrological models, which are divided in three types: spatially lumped, semi-distributed and spatially distributed models. Spatially distributed models are further subdivided based on whether they simulate lateral groundwater flow (GWfl) or not (nGWfl). An example model of each of these three types, including an application is given, that is, HBV (spatially lumped, semi-distributed), PCR-GLOBWB (spatially distributed model, nGWfl) and SIMGRO (spatially distributed model, GWfl). The second category of process-based models, that is, the socio-hydrological models, is also divided into three types: coupled-component, system-dynamics and agent-based models. The chapter addresses calibration and validation of process-based models and concludes with some guidance on how to select an adequate model, considering also the associated uncertainty.

Hydrological data are the foundation of hydrological research, as well as effective water management. Hydrological data are therefore of pivotal importance to any drought or low flow study. While there have been significant advances in hydrological data acquisition, analysis and dissemination in recent decades, it is still crucially important to ensure data are of suitable quality to support analysis and decision-making. In this chapter, key concepts in hydrological data are first reviewed, and then main types of hydrological data (river flow and groundwater level) are explored, giving due attention to how they are derived, including challenges and limitations. Key supporting datasets are also considered, such as hydrometeorological datasets (e.g., precipitation, evaporation, soil moisture) and spatial datasets available at different scales (local, regional and global) that provide important context for hydrological observations. Example datasets containing flow data are provided that cover different scales (international, regional and local). Local datasets also include groundwater and meteorological data.

This paper presents a simple water budget model that can be used to quantify present and to predict future groundwater depletion rates in areas where there is a lack of the comprehensive long-term data needed to develop sophisticated numerical groundwater models. This study applied the water budget model in Wadi Zabid, Yemen, a region where groundwater withdrawals have far exceeded replenishment rates for 50 years, resulting in falling groundwater levels. The findings indicate that the present groundwater use in the wadi is unsustainable, mainly due to the expansion of agricultural lands. The current average groundwater depletion rate was calculated as − 0.93 m/yr, which is in line with the observed average of − 1.11 m/yr (1972–2016). Scenario analysis shows that reducing the groundwater depletion rate by two-thirds of the current rate (from 0.93 to 0.32 m/yr) would require a one-third reduction in agricultural lands (from 435 to 305 km2) in the study region, combined with a one-third increase in surface water inflow from upstream (from 132 to 172 mm/yr, also necessitating a reduction of agriculture in the upstream region). Economic incentives to support alternative livelihoods with lower water requirements, alongside utilization of non-conventional water sources (e.g., exploring the feasibility of seawater desalination) could reduce groundwater depletion. The simple water budget approach proved to be a useful means for this type of analysis in data-scarce regions.

Chapter 1 introduces the reader to the drought hazard and to the scope of the book. How to define drought and the need to distinguish between different types of drought are discussed, underlining the wide range - and often devastating - impacts that drought may cause. An overview of key characteristics of hydrological drought, including low flow and drought deficit characteristics, such as drought duration, is presented and their dependency on the type of hydrological regime highlighted. Drought is considered a natural phenomenon; however, the influence of human interventions and climate change cannot be disregarded. A warming climate has led to a higher awareness of the drought hazard, increased focus on drought research and the need for improved water management and drought preparedness. With this background, a brief history of the advance of drought research and management in Europe over the last decades is provided with reference to major international studies and initiatives. The chapter closes with an overview of the structure of the textbook, including a brief summary of each chapter.

Human activities both aggravate and alleviate streamflow drought. Here we show that aggravation is dominant in contrasting cases around the world analysed with a consistent methodology. Our 28 cases included different combinations of human-water interactions. We found that water abstraction aggravated all drought characteristics, with increases of 20%-305% in total time in drought found across the case studies, and increases in total deficit of up to almost 3000%. Water transfers reduced drought time and deficit by up to 97%. In cases with both abstraction and water transfers into the catchment or augmenting streamflow from groundwater, the water inputs could not compensate for the aggravation of droughts due to abstraction and only shift the effects in space or time. Reservoir releases for downstream water use alleviated droughts in the dry season, but also led to deficits in the wet season by changing flow seasonality. This led to minor changes in average drought duration (-26 to +38%) and moderate changes in average drought deficit (-86 to +369%). Land use showed a smaller impact on streamflow drought, also with both increases and decreases observed (-48 to +98%). Sewage return flows and pipe leakage possibly counteracted the effects of increased imperviousness in urban areas; however, untangling the effects of land use change on streamflow drought is challenging. This synthesis of diverse global cases highlights the complexity of the human influence on streamflow drought and the added value of empirical comparative studies. Results indicate both intended and unintended consequences of water management and infrastructure on downstream society and ecosystems.

Hydrological drought forecasts outperform meteorological ones, which is anticipated coming from catchment memory. Yet, the importance of catchment memory in explaining hydrological drought forecast performance has not been studied. Here, we use the Baseflow Index (BFI) and the groundwater Recession Coefficient (gRC), which through the streamflow, give information on the catchment memory. Performance of streamflow drought forecasts was evaluated using the Brier Score (BS) for rivers across Europe. We found that BS is negatively correlated with BFI, meaning that rivers with high BFI (large memory) yield better drought prediction (low BS). A significant positive correlation between gRC and BS demonstrates that catchments slowly releasing groundwater to streams (low gRC), i.e. large memory, generates higher drought forecast performance. The higher performance of hydrological drought forecasts in catchments with relatively large memory (high BFI and low gRC) implies that Drought Early Warning Systems have more potential to be implemented there and will appear to be more useful.

Streamflow drought forecasting is a key element of contemporary drought early warning systems (DEWS). The term streamflow drought forecasting (not streamflow forecasting), however, has created confusion within the scientific hydrometeorological community as well as in operational weather and water management services. Streamflow drought forecasting requires an additional step, which is the application of a drought identification method to the forecasted streamflow time series. The way streamflow drought is identified is the main reason for this misperception. The purpose of this study, therefore, is to provide a comprehensive overview of the differences between different drought identification approaches to identify droughts in European rivers, including an analysis of both historical drought and implications for forecasting. Streamflow data were obtained from the LISFLOOD hydrological model forced with gridded meteorological observations (known as LISFLOOD-Simulation Forced with Observed, SFO). The same model fed with seasonal meteorological forecasts of the European Centre for Medium-Range Weather Forecasts system 5 (ECMWF SEAS 5) was used to obtain the forecasted streamflow. Streamflow droughts were analyzed using the daily and monthly variable threshold methods (VTD and VTM, respectively), the daily and monthly fixed threshold methods (FTD and FTM, respectively), and the Standardized Streamflow Index (SSI). Our results clearly show that streamflow droughts derived from different approaches deviate from each other in their characteristics, which also vary in different climate regions across Europe. The daily threshold methods (FTD and VTD) identify 25ĝ%-50ĝ% more drought events than the monthly threshold methods (FTM and VTM), and accordingly the average drought duration is longer for the monthly than for the daily threshold methods. The FTD and FTM, in general, identify drought occurrences earlier in the year than the VTD and VTM. In addition, the droughts obtai

Drought is a complex natural phenomenon. The description of the way in which drought changes (moves) in space may help to acquire knowledge on its drivers and processes to improve its monitoring and prediction. This research presents the application of an approach to characterise the dynamics of drought. Tracks, severity, duration, as well as localisation (onset and end position), and rotation of droughts were calculated. Results of calculated droughts were compared with documented information. Data from the Standardized Precipitation Evaporation Index (SPEI) Global Drought Monitor was used to identify droughts in India as an example for the period 1901–2013. Results show regions where droughts with considerable coverage tend to occur. Paths, i.e. consecutive spatial tracks, of six of the most severe reported droughts were analysed. In all of them, areas overlap considerably over time, which suggest that drought remains in the same region for a period of time. Results of this research are being used to build a model to predict the spatial drought tracks, incl. India (https://www.researchgate.net/project/STAND-Spatio-Temporal-ANalysis-of-Drought)., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Water Resources