Global groundwater droughts are more severe than they appear in hydrological models:an investigation through a Bayesian merging of GRACE and GRACE-FO data with a water balance model

Realistic representation of hydrological drought events is increasingly important in world facing decreased freshwater availability. Index-based drought monitoring systems are often adopted to represent the evolution and distribution of hydrological droughts, which mainly rely on hydrological model simulations to compute these indices. Recent studies, however, indicate that model derived water storage estimates might have difficulties in adequately representing reality. Here, a novel Markov Chain Monte Carlo - Data Assimilation (MCMC-DA) approach is implemented to merge global Terrestrial Water Storage (TWS) changes from the Gravity Recovery And Climate Experiment (GRACE) and its Follow On mission (GRACE-FO) with the water storage estimations derived from the W3RA water balance model. The modified MCMC-DA derived summation of deep-rooted soil and groundwater storage estimates is then used to compute standardized groundwater drought indices globally to show the impact of GRACE/GRACE-FO DA on a global index-based hydrological drought monitoring system. Our numerical assessment covers the period of 2003–2021, and shows that integrating GRACE/GRACE-FO data modifies the seasonality and inter-annual trends of water storage estimations. Considerable increases in the length and severity of extreme droughts are found in basins that exhibited multi-year water storage fluctuations and those affected by climate teleconnections

Drought in the Anthropocene

Drought management is inefficient because feedbacks between drought and people are not fully understood. In this human-influenced era, we need to rethink the concept of drought to include the human role in mitigating and enhancing drought

Drought in a human-modified world: reframing drought definitions, understanding, and analysis approaches

In the current human-modified world, or Anthropocene, the state of water stores and fluxes has become dependent on human as well as natural processes. Water deficits (or droughts) are the result of a complex interaction between meteorological anomalies, land surface processes, and human inflows, outflows, and storage changes. Our current inability to adequately analyse and manage drought in many places points to gaps in our understanding and to inadequate data and tools. The Anthropocene requires a new framework for drought definitions and research. Drought definitions need to be revisited to explicitly include human processes driving and modifying soil moisture drought and hydrological drought development. We give recommendations for robust drought definitions to clarify timescales of drought and prevent confusion with related terms such as water scarcity and overexploitation. Additionally, our understanding and analysis of drought need to move from single driver to multiple drivers and from uni-directional to multi-directional. We identify research gaps and propose analysis approaches on (1) drivers, (2) modifiers, (3) impacts, (4) feedbacks, and (5) changing the baseline of drought in the Anthropocene. The most pressing research questions are related to the attribution of drought to its causes, to linking drought impacts to drought characteristics, and to societal adaptation and responses to drought. Example questions include: (i) What are the dominant drivers of drought in different parts of the world? (ii) How do human modifications of drought enhance or alleviate drought severity? (iii) How do impacts of drought depend on the physical characteristics of drought vs. the vulnerability of people or the environment? (iv) To what extent are physical and human drought processes coupled, and can feedback loops be identified and altered to lessen or mitigate drought? (v) How should we adapt our drought analysis to accommodate changes in the normal situation (i.e. what are considered normal or reference conditions) over time? Answering these questions requires exploration of qualitative and quantitative data as well as mixed modelling approaches. The challenges related to drought research and management in the Anthropocene are not unique to drought, but do require urgent attention. We give recommendations drawn from the fields of flood research, ecology, water management, and water resources studies. The framework presented here provides a holistic view on drought in the Anthropocene, which will help improve management strategies for mitigating the severity and reducing the impacts of droughts in future

Water resources, climate change and energy

The objective of this chapter is to summarise our understanding of the physical interactions between water resources, energy use, and climate change and mitigation. The distribution and pressures on our water resources will be reviewed, as well as our current understanding of observed and projected changes due to climate change. By addressing a set of relevant questions, the aim is to provide a framework within which we can interpret which interactions are likely and which less likely; which are desirable and which not desirable. The questions addressed include the following: What are the characteristics, drivers and challenges of water resource management? Why do water resource management challenges vary between countries? Are concepts like green and blue water, embedded water, peak water and integrated water resources management useful in managing the relationship between water, climate and energy? What are the observed and projected impacts of climate change on water resources? Why does it seem that climate change makes water management harder everywhere? Does it matter whether climate change is man-made? How do melting ice caps and glaciers affect water resources? What is the relationship between drought and water resources? How do climate change, floods and water resources interact? Will climate change affect water use? What are the potential impacts of water management on climate and energy security? What adaptation measures are considered in water management? What is their influence on energy security and climate mitigation measures? For example, can changes in water management change climate? What do water management changes mean for energy use? How can climate mitigation and energy security measures impact on water security? Can switching between energy sources affect water security? What impact do the by-products of energy generation have on climate and the water cycle? What is the impact of climate mitigation measures such as landscape carbon storage

Planted forests and water

This chapter provides an overview of the effects of planted forests on water resources. Planted forests include both intensively managed forest plantations and more extensively managed planted forests (sensu FAO, 2004) that have been established for wood production, water and soil protection, landscape restoration, biodiversity conservation or other purposes. In most cases, the general impacts on water resources of different types of planted forests will be similar, with differences resulting from tree species selection or management activities

Global Maps of Streamflow Characteristics Based on Observations from Several Thousand Catchments

Streamflow (Q) estimation in ungauged catchments is one of the greatest challenges facing hydrologists. We used observed Q from approximately 7500 small catchments (<10,000 km2) around the globe to train neural network ensembles to estimate Q characteristics from climate and physiographic characteristics of the catchments. In total 17 Q characteristics were selected, including mean annual Q, baseflow index, and a number of flow percentiles. Training coefficients of determination for the estimation of the Q characteristics ranged from 0.56 for the baseflow recession constant to 0.93 for the Q timing. Overall, climate indices dominated among the predictors. Predictors related to soils and geology were the least important, perhaps due to data quality. The trained neural network ensembles were subsequently applied spatially over the entire ice-free land surface including ungauged regions, resulting in global maps of the Q characteristics (0.125° resolution). These maps possess several unique features: 1) they represent purely observation-driven estimates; 2) are based on an unprecedentedly large set of catchments; and 3) have associated uncertainty estimates. The maps can be used for various hydrological applications, including the diagnosis of macro-scale hydrological models. To demonstrate this, the produced maps were compared to equivalent maps derived from the simulated daily Q of five macro-scale hydrological models, highlighting various opportunities for improvement in model Q behavior. The produced dataset is available via http://water.jrc.ec.europa.eu.JRC.H.1-Water Resource

Global satellite-based river gauging and the influence of river morphology on its application

In the face of a sparse global river gauging station network in decline, new approaches are needed to reconstruct and monitor river discharge from satellite observations. Where in-situ river discharge measurements are not available, it may be possible to use discharge estimates from a hydrological model, provided the model simulations are of sufficient quality, to construct satellite-based discharge gauging. We tested this approach by developing model- and gauge-based satellite gauging reaches (SGRs) using 0.05° MODIS optical remote sensing at ~10,000 gauged and ~370,000 ungauged river reaches globally. Model-based SGRs are aimed to infer temporal flow patterns and reflect unusually high or low river discharge behavior (i.e. flood or drought conditions), if not necessarily absolute discharge volumes. The model-based SGRs achieved a discharge prediction skill that was often similar to gauge-based SGRs, and sometimes better than the model itself. Our results showed promising opportunities to develop model-based SGRs in sparsely gauged basins in South America, Africa, and Asia. We selected river reaches, with mean widths ranging from 67 to 3105 m, representing both poor and successful SGRs in different environments for case studies to analyze conditions for successful SGR development. River size and morphology were the main factors determining the performance of SGRs. Wide channels with strong temporal variations, broad floodplains and multiple braided or anastomosing channels provided the best conditions for SGRs. The probability of constructing a successful SGR could be predicted from high-resolution inundation summary data available globally, and can thus be predicted anywhere. Ongoing increases in the spatial and temporal resolution of remote sensing will further increase the number of river reaches for which satellite-based discharge gauging will become possible

Merging Landsat and airborne LiDAR observations for continuous monitoring of floodplain water extent, depth and volume

The Darling River system in Australia is under pressure from water extraction and climate change. Management interventions such as environmental flow releases require understanding of water storage dynamics and the connectivity of floodplains and wetlands. Such knowledge can be gleaned from the long observational record of the Landsat series of satellite sensors and high (<5 m) resolution digital elevation models derived from airborne light detection and ranging (LiDAR). Here, for the first time, we develop and demonstrate an approach to reconstruct 16-day floodplain water dynamics, including extent, depth, and volume for a long Landsat time series (1987 to present). Time series mapping of surface water extent at 5-m resolution was achieved by topographic downscaling of Landsat-derived surface water data. We propose a simple and effective algorithm to restore missing data in the images caused by, e.g., cloud and shadows, swath edges and the Landsat 7 Scan Line Corrector (SLC) failure, thereby increasing the number of useable images five-fold. The 5-m surface water extent maps clearly delineate the narrow river channel and the boundary of floodplain wetlands. They can capture the development, peak and retreat of flood events. By combining Landsat and airborne LiDAR observations, we produced time series of surface water depth mapping at 5-m resolution, accounting for the degree of hydraulic surface water connectivity. Based on these maps, we derived 16-day floodplain volume dynamics for 1987 to present. The correlation coefficient between upstream river flow records and floodplain volume time series was 0.88, indicating that the estimates were robust. The algorithms developed can be used for ongoing very high-resolution mapping to assist in managing human water use and environmental health in the Murray-Darling Basin

Global vegetation gross primary production estimation using satellite-derived light-use efficiency and canopy conductance

Climate and physiological controls of vegetation gross primary production (GPP) vary in space and time. In many ecosystems, GPP is primary limited by absorbed photosynthetically-active radiation; in others by canopy conductance. These controls further vary in importance over daily to seasonal time scales. We propose a simple but effective conceptual model that estimates GPP as the lesser of a conductance-limited (Fc) and radiation-limited (Fr) assimilation rate. Fc is estimated from canopy conductance while Fr is estimated using a light use efficiency model. Both can be related to vegetation properties observed by optical remote sensing. The model has only two fitting parameters: maximum light use efficiency, and the minimum achieved ratio of internal to external CO2 concentration. The two parameters were estimated using data from 16 eddy covariance flux towers for six major biomes including both energy- and water-limited ecosystems. Evaluation of model estimates with flux tower-derived GPP compared favourably to that of more complex models, for fluxes averaged; per day (r2=0.72, root mean square error, RMSE=2.48μmolCm2s-1, relative percentage error, RPE=-11%), over 8-day periods (r2=0.78 RMSE=2.09μmolCm2s-1,RPE=-10%), over months (r2=0.79, RMSE=1.93μmolCm2s-1, RPE=-9%) and over years (r2=0.54, RMSE=1.62μmolCm2s-1, RPE=-9%). Using the model we estimated global GPP of 107PgCy-1 for 2000-2011. This value is within the range reported by other GPP models and the spatial and inter-annual patterns compared favourably. The main advantages of the proposed model are its simplicity, avoiding the use of uncertain biome- or land-cover class mapping, and inclusion of explicit coupling between GPP and plant transpiration