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Mountains play a key role in the provision of nature’s contributions to people (NCP) worldwide that support societies’ quality of life. Simultaneously, mountains are threatened by multiple drivers of change. Due to the complex interlinkages between biodiversity, quality of life and drivers of change, research on NCP in mountains requires interdisciplinary approaches. In this study, we used the conceptual framework of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) and the notion of NCP to determine to what extent previous research on ecosystem services in mountains has explored the different components of the IPBES conceptual framework. We conducted a systematic review of articles on ecosystem services in mountains published up to 2016 using the Web of Science and Scopus databases. Descriptive statistical and network analyses were conducted to explore the level of research on the components of the IPBES framework and their interactions. Our results show that research has gradually become more interdisciplinary by studying higher number of NCP, dimensions of quality of life, and indirect drivers of change. Yet, research focusing on biodiversity, regulating NCP and direct drivers has decreased over time. Furthermore, despite the fact that research on NCP in mountains becoming more policy-oriented over time, mainly in relation to payments for ecosystem services, institutional responses remained underexplored in the reviewed studies. Finally, we discuss the relevant knowledge gaps that should be addressed in future research in order to contribute to IPBES.
Ecosystem services inherently involve people, whose values help define the benefits of nature's services. It is thus important for researchers to involve stakeholders in ecosystem services research. However, a simple and practicable framework to guide such engagement, and in particular to help researchers anticipate and consider key issues and challenges, has not been well explored. Here, we use experience from the 12 case studies in the European Operational Potential of Ecosystem Research Applications (OPERAs) project to propose a stakeholder engagement framework comprising three key elements: creating space, aligning motivations, and building trust. We argue that involving stakeholders in research demands thoughtful reflection from the researchers about what kind of space they want to create, including if and how they want to bring different interests together, how much space they want to allow for critical discussion, and whether there is a role for particular stakeholders to serve as conduits between others. In addition, understanding their own motivations—including values, knowledge, goals, and desired benefits—will help researchers decide when and how to involve stakeholders, identify areas of common ground and potential disagreement, frame the project appropriately, set expectations, and ensure each party is able to see benefits of engaging with each other. Finally, building relationships with stakeholders can be difficult but considering the roles of existing relationships, time, approach, reputation, and belonging can help build mutual trust. Although the three key elements and the paths between them can play out differently depending on the particular research project, we suggest that a research design that considers how to create the space in which researchers and stakeholders will meet, align motivations between researchers and stakeholders, and build mutual trust will help foster productive researcher–stakeholder relationships.
Arctic lowlands are characterized by large numbers of small waterbodies, which are known to affect surface energy budgets and the global carbon cycle. Statistical analysis of their size distributions has been hindered by the shortage of observations at sufficiently high spatial resolutions. This situation has now changed with the high-resolution (<5 m) circum-Arctic Permafrost Region Pond and Lake (PeRL) database recently becoming available. We have used this database to make the first consistent, high-resolution estimation of Arctic waterbody size distributions, with surface areas ranging from 0.0001 km(2) (100 m(2)) to 1 km(2). We found that the size distributions varied greatly across the thirty study regions investigated and that there was no single universal size distribution function (including power-law distribution functions) appropriate across all of the study regions. We did, however, find close relationships between the statistical moments (mean, variance, and skewness) of the waterbody size distributions from different study regions. Specifically, we found that the spatial variance increased linearly with mean waterbody size (R-2 = 0.97, p < 2.2e-16) and that the skewness decreased approximately hyperbolically. We have demonstrated that these relationships (1) hold across the 30 Arctic study regions covering a variety of (bio)climatic and permafrost zones, (2) hold over time in two of these study regions for which multi-decadal satellite imagery is available, and (3) can be reproduced by simulating rising water levels in a high-resolution digital elevation model. The consistent spatial and temporal relationships between the statistical moments of the waterbody size distributions underscore the dominance of topographic controls in lowland permafrost areas. These results provide motivation for further analyses of the factors involved in waterbody development and spatial distribution and for investigations into the possibility of using statistical moments to predict future hydrologic dynamics in the Arctic.
Above and underground hydrological processes depend on soil moisture (SM) variability, driven by different environmental factors that seldom are well-monitored, leading to a misunderstanding of soil water temporal patterns. This study investigated the stability of the SM temporal dynamics to different monitoring temporal resolutions around the border between two soil types in a tropical watershed. Four locations were instrumented in a small-scale watershed (5.84 km(2)) within the tropical coast of Northeast Brazil, encompassing different soil types (Espodossolo Humiluvico or Carbic Podzol, and Argissolo Vermelho-Amarelo or Haplic Acrisol), land covers (Atlantic Forest, bush vegetation, and grassland) and topographies (flat and moderate slope). The SM was monitored at a temporal resolution of one hour along the 2013-2014 hydrological year and then resampled a resolutions of 6 h, 12 h, 1 day, 2 days, 4 days, 7 days, and 15 days. Descriptive statistics, temporal variability, time-stability ranking, and hierarchical clustering revealed uneven associations among SM time components. The results show that the time-invariant component ruled SM temporal variability over the time-varying parcel, either at high or low temporal resolutions. Time-steps longer than 2 days affected the mean statistical metrics of the SM time-variant parcel. Additionally, SM at downstream and upstream sites behaved differently, suggesting that the temporal mean was regulated by steady soil properties (slope, restrictive layer, and soil texture), whereas their temporal anomalies were driven by climate (rainfall) and hydrogeological (groundwater level) factors. Therefore, it is concluded that around the border between tropical soil types, the distinct behaviour of time-variant and time-invariant components of SM time series reflects different combinations of their soil properties.
Fine particles or sediments are one of the important variables that should be considered for the proper management of water quality and aquatic ecosystems. In the present study, the effect of catchment characteristics on the performance of an already developed model for the estimation of fine sediments dynamics between the water column and sediment bed was tested, using 13 catchments distributed worldwide. The model was calibrated to determine two optimal model parameters. The first is the filtration parameter, which represents the filtration of fine sediments through pores of the stream bed during the recession period of a flood event. The second parameter is the bed erosion parameter that represents the active layer, directly related to the re-suspension of fine sediments during a flood event. A dependency of the filtration parameter with the catchment area was observed in catchments smaller than 100 km(2), whereas no particular relationship was observed for larger catchments (>100 km(2)). In contrast, the bed erosion parameter does not show a noticeable dependency with the area or other environmental characteristics. The model estimated the mass of fine sediments released from the sediment bed to the water column during flood events in the 13 catchments within 23% bias.
Yukon’s Beaufort coast, Canada, is a highly dynamic landscape. Cultural sites, infrastructure, and travel routes used by the local population are particularly vulnerable to coastal erosion. To assess threats to these phenomena, rates of shoreline change for a 210 km length of the coast were analyzed and combined with socioeconomic and cultural information. Rates of shoreline change were derived from aerial and satellite imagery from the 1950s, 1970s, 1990s, and 2011. Using these data, conservative (S1) and dynamic (S2) shoreline projections were constructed to predict shoreline positions for the year 2100. The locations of cultural features in the archives of a Parks Canada database, the Yukon Archaeological Program, and as reported in other literature were combined with projected shoreline position changes. Between 2011 and 2100, approximately 850 ha (S1) and 2660 ha (S2) may erode, resulting in a loss of 45% (S1) to 61% (S2) of all cultural features by 2100. The last large, actively used camp area and two nearshore landing strips will likely be threatened by future coastal processes. Future coastal erosion and sedimentation processes are expected to increasingly threaten cultural sites and influence travelling and living along the Yukon coast.
Continental rift systems form by propagation of isolated rift segments that interact, and eventually evolve into continuous zones of deformation. This process impacts many aspects of rifting including rift morphology at breakup, and eventual ocean-ridge segmentation. Yet, rift segment growth and interaction remain enigmatic. Here we present geological data from the poorly documented Ririba rift (South Ethiopia) that reveals how two major sectors of the East African rift, the Kenyan and Ethiopian rifts, interact. We show that the Ririba rift formed from the southward propagation of the Ethiopian rift during the Pliocene but this propagation was short-lived and aborted close to the Pliocene-Pleistocene boundary. Seismicity data support the abandonment of laterally offset, overlapping tips of the Ethiopian and Kenyan rifts. Integration with new numerical models indicates that rift abandonment resulted from progressive focusing of the tectonic and magmatic activity into an oblique, throughgoing rift zone of near pure extension directly connecting the rift sectors.
The Postmasburg Manganese Field (PMF), Northern Cape Province, South Africa, once represented one of the largest sources of manganese ore worldwide. Two belts of manganese ore deposits have been distinguished in the PMF, namely the Western Belt of ferruginous manganese ores and the Eastern Belt of siliceous manganese ores. Prevailing models of ore formation in these two belts invoke karstification of manganese-rich dolomites and residual accumulation of manganese wad which later underwent diagenetic and low-grade metamorphic processes. For the most part, the role of hydrothermal processes and metasomatic alteration towards ore formation has not been adequately discussed. Here we report an abundance of common and some rare Al-, Na-, K- and Ba-bearing minerals, particularly aegirine, albite, microcline, banalsite, serandite-pectolite, paragonite and natrolite in Mn ores of the PMF, indicative of hydrothermal influence. Enrichments in Na, K and/or Ba in the ores are generally on a percentage level for most samples analysed through bulk-rock techniques. The presence of As-rich tokyoite also suggests the presence of As and V in the hydrothermal fluid. The fluid was likely oxidized and alkaline in nature, akin to a mature basinal brine. Various replacement textures, particularly of Na- and K- rich minerals by Ba-bearing phases, suggest sequential deposition of gangue as well as ore-minerals from the hydrothermal fluid, with Ba phases being deposited at a later stage. The stratigraphic variability of the studied ores and their deviation from the strict classification of ferruginous and siliceous ores in the literature, suggests that a re-evaluation of genetic models is warranted. New Ar-Ar ages for K-feldspars suggest a late Neoproterozoic timing for hydrothermal activity. This corroborates previous geochronological evidence for regional hydrothermal activity that affected Mn ores at the PMF but also, possibly, the high-grade Mn ores of the Kalahari Manganese Field to the north. A revised, all-encompassing model for the development of the manganese deposits of the PMF is then proposed, whereby the source of metals is attributed to underlying carbonate rocks beyond the Reivilo Formation of the Campbellrand Subgroup. The main process by which metals are primarily accumulated is attributed to karstification of the dolomitic substrate. The overlying Asbestos Hills Subgroup banded iron formation (BIF) is suggested as a potential source of alkali metals, which also provides a mechanism for leaching of these BIFs to form high-grade residual iron ore deposits.
In crop modeling and yield predictions, the heterogeneity of agricultural landscapes is usually not accounted for. This heterogeneity often arises from landscape elements like forests, hedges, or single trees and shrubs that cast shadows. Shading from forested areas or shrubs has effects on transpiration, temperature, and soil moisture, all of which affect the crop yield in the adjacent arable land. Transitional gradients of solar irradiance can be described as a function of the distance to the zero line (edge), the cardinal direction, and the height of trees. The magnitude of yield reduction in transition zones is highly influenced by solar irradiance-a factor that is not yet implemented in crop growth models on a landscape level. We present a spatially explicit model for shading caused by forested areas, in agricultural landscapes. With increasing distance to forest, solar irradiance and yield increase. Our model predicts that the shading effect from the forested areas occurs up to 15 m from the forest edge, for the simulated wheat yields, and up to 30 m, for simulated maize. Moreover, we estimated the spatial extent of transition zones, to calculate the regional yield reduction caused by shading of the forest edges, which amounted to 5% to 8% in an exemplary region.
Influence of the Main Border Faults on the 3D Hydraulic Field of the Central Upper Rhine Graben
(2019)
The Upper Rhine Graben (URG) is an active rift with a high geothermal potential. Despite being a well-studied area, the three-dimensional interaction of the main controlling factors of the thermal and hydraulic regime is still not fully understood. Therefore, we have used a data-based 3D structural model of the lithological configuration of the central URG for some conceptual numerical experiments of 3D coupled simulations of fluid and heat transport. To assess the influence of the main faults bordering the graben on the hydraulic and the deep thermal field, we carried out a sensitivity analysis on fault width and permeability. Depending on the assigned width and permeability of the main border faults, fluid velocity and temperatures are affected only in the direct proximity of the respective border faults. Hence, the hydraulic characteristics of these major faults do not significantly influence the graben-wide groundwater flow patterns. Instead, the different scenarios tested provide a consistent image of the main characteristics of fluid and heat transport as they have in common: (1) a topography-driven basin-wide fluid flow perpendicular to the rift axis from the graben shoulders to the rift center, (2) a N/NE-directed flow parallel to the rift axis in the center of the rift and, (3) a pronounced upflow of hot fluids along the rift central axis, where the streams from both sides of the rift merge. This upflow axis is predicted to occur predominantly in the center of the URG (northern and southern model area) and shifted towards the eastern boundary fault (central model area).
Study region: Tisza and Prut catchments, originating on the slopes of the Carpathian mountains. Study focus: The study reported here investigates (i) climate change impacts on flood risk in the region, and (ii) uncertainty related to hydrological modelling, downscaling techniques and climate projections. The climate projections used in the study were derived from five GCMs, downscaled either dynamically with RCMs or with the statistical downscaling model XDS. The resulting climate change scenarios were applied to drive the eco-hydrological model SWIM, which was calibrated and validated for the catchments in advance using observed climate and hydrological data. The changes in the 30-year flood hazards and 98 and 95 percentiles of discharge were evaluated for the far future period (2071-2100) in comparison with the reference period (1981-2010). New hydrological insights for the region: The majority of model outputs under RCP 4.5 show a small to strong increase of the 30-year flood level in the Tisza ranging from 4.5% to 62%, and moderate increase in the Prut ranging from 11% to 22%. The impact results under RCP 8.5 are more uncertain with changes in both directions due to high uncertainties in GCM-RCM climate projections, downscaling methods and the low density of available climate stations.
The propagation of a seismic rupture on a fault introduces spatial variations in the seismic wave field surrounding the fault. This directivity effect results in larger shaking amplitudes in the rupture propagation direction. Its seismic radiation pattern also causes amplitude variations between the strike-normal and strike-parallel components of horizontal ground motion. We investigated the landslide response to these effects during the 2016 Kumamoto earthquake (M-w 7.1) in central Kyushu (Japan). Although the distribution of some 1500 earthquake-triggered landslides as a function of rupture distance is consistent with the observed Arias intensity, the landslides were more concentrated to the northeast of the southwest-northeast striking rupture. We examined several landslide susceptibility factors: hillslope inclination, the median amplification factor (MAF) of ground shaking, lithology, land cover, and topographic wetness. None of these factors sufficiently explains the landslide distribution or orientation (aspect), although the landslide head scarps have an elevated hillslope inclination and MAF. We propose a new physics-based ground-motion model (GMM) that accounts for the seismic rupture effects, and we demonstrate that the low-frequency seismic radiation pattern is consistent with the overall landslide distribution. Its spatial pattern is influenced by the rupture directivity effect, whereas landslide aspect is influenced by amplitude variations between the fault-normal and fault-parallel motion at frequencies < 2 Hz. This azimuth dependence implies that comparable landslide concentrations can occur at different distances from the rupture. This quantitative link between the prevalent landslide aspect and the low-frequency seismic radiation pattern can improve coseismic landslide hazard assessment.
Core Ideas
3D MRI relaxation time maps reflect water mobility in root, rhizosphere, and soil.
3D NCT water content maps of the same plant complement relaxation time maps.
The relaxation time T1 decreases from soil to root, whereas water content increases.
Parameters together indicate modification of rhizosphere pore space by gel phase.
The zone of reduced T1 corresponds to the zone remaining dry after rewetting.
In situ investigations of the rhizosphere require high‐resolution imaging techniques, which allow a look into the optically opaque soil compartment. We present the novel combination of magnetic resonance imaging (MRI) and neutron computed tomography (NCT) to achieve synergistic information such as water mobility in terms of three‐dimensional (3D) relaxation time maps and total water content maps. Besides a stationary MRI scanner for relaxation time mapping, we used a transportable MRI system on site in the NCT facility to capture rhizosphere properties before desiccation and after subsequent rewetting. First, we addressed two questions using water‐filled test capillaries between 0.1 and 5 mm: which root diameters can still be detected by both methods, and to what extent are defined interfaces blurred by these imaging techniques? Going to real root system architecture, we demonstrated the sensitivity of the transportable MRI device by co‐registration with NCT and additional validation using X‐ray computed tomography. Under saturated conditions, we observed for the rhizosphere in situ a zone with shorter T1 relaxation time across a distance of about 1 mm that was not caused by reduced water content, as proven by successive NCT measurements. We conclude that the effective pore size in the pore network had changed, induced by a gel phase. After rewetting, NCT images showed a dry zone persisting while the MRI intensity inside the root increased considerably, indicating water uptake from the surrounding bulk soil through the still hydrophobic rhizosphere. Overall, combining NCT and MRI allows a more detailed analysis of the rhizosphere's functioning.
Groundwater travel time distributions (TTDs) provide a robust description of the subsurface mixing behavior and hydrological response of a subsurface system. Lagrangian particle tracking is often used to derive the groundwater TTDs. The reliability of this approach is subjected to the uncertainty of external forcings, internal hydraulic properties, and the interplay between them. Here, we evaluate the uncertainty of catchment groundwater TTDs in an agricultural catchment using a 3-D groundwater model with an overall focus on revealing the relationship between external forcing, internal hydraulic properties, and TTD predictions. Eight recharge realizations are sampled from a high-resolution dataset of land surface fluxes and states. Calibration-constrained hydraulic conductivity fields (Ks fields) are stochastically generated using the null-space Monte Carlo (NSMC) method for each recharge realization. The random walk particle tracking (RWPT) method is used to track the pathways of particles and compute travel times. Moreover, an analytical model under the random sampling (RS) assumption is fit against the numerical solutions, serving as a reference for the mixing behavior of the model domain. The StorAge Selection (SAS) function is used to interpret the results in terms of quantifying the systematic preference for discharging young/old water. The simulation results reveal the primary effect of recharge on the predicted mean travel time (MTT). The different realizations of calibration-constrained Ks fields moderately magnify or attenuate the predicted MTTs. The analytical model does not properly replicate the numerical solution, and it underestimates the mean travel time. Simulated SAS functions indicate an overall preference for young water for all realizations. The spatial pattern of recharge controls the shape and breadth of simulated TTDs and SAS functions by changing the spatial distribution of particles' pathways. In conclusion, overlooking the spatial nonuniformity and uncertainty of input (forcing) will result in biased travel time predictions. We also highlight the worth of reliable observations in reducing predictive uncertainty and the good interpretability of SAS functions in terms of understanding catchment transport processes.
Pluvial flood risk is mostly excluded in urban flood risk assessment. However, the risk of pluvial flooding is a growing challenge with a projected increase of extreme rainstorms compounding with an ongoing global urbanization. Considered as a flood type with minimal impacts when rainfall rates exceed the capacity of urban drainage systems, the aftermath of rainfall-triggered flooding during Hurricane Harvey and other events show the urgent need to assess the risk of pluvial flooding. Due to the local extent and small-scale variations, the quantification of pluvial flood risk requires risk assessments on high spatial resolutions. While flood hazard and exposure information is becoming increasingly accurate, the estimation of losses is still a poorly understood component of pluvial flood risk quantification. We use a new probabilistic multivariable modeling approach to estimate pluvial flood losses of individual buildings, explicitly accounting for the associated uncertainties. Except for the water depth as the common most important predictor, we identified the drivers for having loss or not and for the degree of loss to be different. Applying this approach to estimate and validate building structure losses during Hurricane Harvey using a property level data set, we find that the reliability and dispersion of predictive loss distributions vary widely depending on the model and aggregation level of property level loss estimates. Our results show that the use of multivariable zero-inflated beta models reduce the 90% prediction intervalsfor Hurricane Harvey building structure loss estimates on average by 78% (totalling U.S.$3.8 billion) compared to commonly used models.
Private precaution is an important component in contemporary flood risk management and climate adaptation. However, quantitative knowledge about vulnerability reduction via private precautionary measures is scarce and their effects are hardly considered in loss modeling and risk assessments. However, this is a prerequisite to enable temporally dynamic flood damage and risk modeling, and thus the evaluation of risk management and adaptation strategies. To quantify the average reduction in vulnerability of residential buildings via private precaution empirical vulnerability data (n = 948) is used. Households with and without precautionary measures undertaken before the flood event are classified into treatment and nontreatment groups and matched. Postmatching regression is used to quantify the treatment effect. Additionally, we test state-of-the-art flood loss models regarding their capability to capture this difference in vulnerability. The estimated average treatment effect of implementing private precaution is between 11 and 15 thousand EUR per household, confirming the significant effectiveness of private precautionary measures in reducing flood vulnerability. From all tested flood loss models, the expert Bayesian network-based model BN-FLEMOps and the rule-based loss model FLEMOps perform best in capturing the difference in vulnerability due to private precaution. Thus, the use of such loss models is suggested for flood risk assessments to effectively support evaluations and decision making for adaptable flood risk management.
Proxy-based reconstructions and modeling of Holocene spatiotemporal precipitation patterns for China and Mongolia have hitherto yielded contradictory results indicating that the basic mechanisms behind the East Asian Summer Monsoon and its interaction with the westerly jet stream remain poorly understood. We present quantitative reconstructions of Holocene precipitation derived from 101 fossil pollen records and analyse them with the help of a minimal empirical model. We show that the westerly jet-stream axis shifted gradually southward and became less tilted since the middle Holocene. This was tracked by the summer monsoon rain band resulting in an early-Holocene precipitation maximum over most of western China, a mid-Holocene maximum in north-central and northeastern China, and a late-Holocene maximum in southeastern China. Our results suggest that a correct simulation of the orientation and position of the westerly jet stream is crucial to the reliable prediction of precipitation patterns in China and Mongolia.
The link between streamflow extremes and climatology has been widely studied in recent decades. However, a study investigating the effect of large-scale circulation variations on the distribution of seasonal discharge extremes at the European level is missing. Here we fit a climate-informed generalized extreme value (GEV) distribution to about 600 streamflow records in Europe for each of the standard seasons, i.e., to winter, spring, summer and autumn maxima, and compare it with the classical GEV distribution with parameters invariant in time. The study adopts a Bayesian framework and covers the period 1950 to 2016. Five indices with proven influence on the European climate are examined independently as covariates, namely the North Atlantic Oscillation (NAO), the east Atlantic pattern (EA), the east Atlantic-western Russian pattern (EA/WR), the Scandinavia pattern (SCA) and the polar-Eurasian pattern (POL). It is found that for a high percentage of stations the climate-informed model is preferred to the classical model. Particularly for NAO during winter, a strong influence on streamflow extremes is detected for large parts of Europe (preferred to the classical GEV distribution for 46% of the stations). Climate-informed fits are characterized by spatial coherence and form patterns that resemble relations between the climate indices and seasonal precipitation, suggesting a prominent role of the considered circulation modes for flood generation. For certain regions, such as northwestern Scandinavia and the British Isles, yearly variations of the mean seasonal climate indices result in considerably different extreme value distributions and thus in highly different flood estimates for individual years that can also persist for longer time periods.
In precipitation nowcasting, it is common to track the motion of precipitation in a sequence of weather radar images and to extrapolate this motion into the future. The total error of such a prediction consists of an error in the predicted location of a precipitation feature and an error in the change of precipitation intensity over lead time. So far, verification measures did not allow isolating the extent of location errors, making it difficult to specifically improve nowcast models with regard to location prediction. In this paper, we introduce a framework to directly quantify the location error. To that end, we detect and track scale-invariant precipitation features (corners) in radar images. We then consider these observed tracks as the true reference in order to evaluate the performance (or, inversely, the error) of any model that aims to predict the future location of a precipitation feature. Hence, the location error of a forecast at any lead time Delta t ahead of the forecast time t corresponds to the Euclidean distance between the observed and the predicted feature locations at t + Delta t. Based on this framework, we carried out a benchmarking case study using one year worth of weather radar composites of the German Weather Service. We evaluated the performance of four extrapolation models, two of which are based on the linear extrapolation of corner motion from t - 1 to t (LK-Lin1) and t - 4 to t (LK-Lin4) and the other two are based on the Dense Inverse Search (DIS) method: motion vectors obtained from DIS are used to predict feature locations by linear (DIS-Lin1) and Semi-Lagrangian extrapolation (DIS-Rot1). Of those four models, DIS-Lin1 and LK-Lin4 turned out to be the most skillful with regard to the prediction of feature location, while we also found that the model skill dramatically depends on the sinuosity of the observed tracks. The dataset of 376,125 detected feature tracks in 2016 is openly available to foster the improvement of location prediction in extrapolation-based nowcasting models.
This study investigates possible impacts of four global warming levels (GWLs: GWL1.5, GWL2.0, GWL2.5, and GWL3.0) on drought characteristics over Niger River basin (NRB) and Volta River basin (VRB). Two drought indices-Standardized Precipitation Index (SPI) and Standardized Precipitation-Evapotranspiration Index (SPEI)-were employed in characterizing droughts in 20 multi-model simulation outputs from the Coordinated Regional Climate Downscaling Experiment (CORDEX). The performance of the simulation in reproducing basic hydro-climatological features and severe drought characteristics (i.e., magnitude and frequency) in the basins were evaluated. The projected changes in the future drought frequency were quantified and compared under the four GWLs for two climate forcing scenarios (RCP8.5 and RCP4.5). The regional climate model (RCM) ensemble gives a realistic simulation of historical hydro-climatological variables needed to calculate the drought indices. With SPEI, the simulation ensemble projects an increase in the magnitude and frequency of severe droughts over both basins (NRB and VRB) at all GWLs, but the increase, which grows with the GWLs, is higher over NRB than over VRB. More than 75% of the simulations agree on the projected increase at GWL1.5 and all simulations agree on the increase at higher GWLs. With SPI, the projected changes in severe drought is weaker and the magnitude remains the same at all GWLs, suggesting that SPI projection may underestimate impacts of the GWLs on the intensity and severity of future drought. The results of this study have application in mitigating impact of global warming on future drought risk over the regional water systems.