Gonzalo Miguez-Macho

Global Patterns of Groundwater Table Depth

Water Flowing Underground In addition to serving as an out-of-sight, yet much-needed water source, groundwater influences ecosystems on land—especially when the groundwater depth is shallow. Fan et al. (p. 940) used government archives and published studies to construct a global map of groundwater depth based on over 1,000,000 direct well measurements. A groundwater model was then used to construct a continuous global map of groundwater depth. The findings reveal the global influence of sea level and climate on groundwater depths across several regions and ecosystems. Up to 32% of the global land area contains ecosystems that are influenced by shallow groundwater. Shallow groundwater affects terrestrial ecosystems by sustaining river base-flow and root-zone soil water in the absence of rain, but little is known about the global patterns of water table depth and where it provides vital support for land ecosystems. We present global observations of water table depth compiled from government archives and literature, and fill in data gaps and infer patterns and processes using a groundwater model forced by modern climate, terrain, and sea level. Patterns in water table depth explain patterns in wetlands at the global scale and vegetation gradients at regional and local scales. Overall, shallow groundwater influences 22 to 32% of global land area, including ~15% as groundwater-fed surface water features and 7 to 17% with the water table or its capillary fringe within plant rooting depths.

Regional Climate Simulations over North America: Interaction of Local Processes with Improved Large-Scale Flow

Abstract The reasons for biases in regional climate simulations were investigated in an attempt to discern whether they arise from deficiencies in the model parameterizations or are due to dynamical problems. Using the Regional Atmospheric Modeling System (RAMS) forced by the National Centers for Environmental Prediction–National Center for Atmospheric Research reanalysis, the detailed climate over North America at 50-km resolution for June 2000 was simulated. First, the RAMS equations were modified to make them applicable to a large region, and its turbulence parameterization was corrected. The initial simulations showed large biases in the location of precipitation patterns and surface air temperatures. By implementing higher-resolution soil data, soil moisture and soil temperature initialization, and corrections to the Kain–Fritch convective scheme, the temperature biases and precipitation amount errors could be removed, but the precipitation location errors remained. The precipitation location biases ...

Hydrologic regulation of plant rooting depth

Significance Knowledge of plant rooting depth is critical to understanding plant-mediated global change. Earth system models are highly sensitive to this particular parameter with large consequences for modeled plant productivity, water–energy–carbon exchange between the land and the atmosphere, and silicate weathering regulating multimillion-year-timescale carbon cycle. However, we know little about how deep roots go and why. Accidental discoveries of >70-m-deep roots in wells and >20-m-deep roots in caves offer glimpses of the enormous plasticity of root response to its environment, but the drivers and the global significance of such deep roots are not clear. Through observations and modeling, we demonstrate that soil hydrology is a globally prevalent force driving landscape to global patterns of plant rooting depth. Plant rooting depth affects ecosystem resilience to environmental stress such as drought. Deep roots connect deep soil/groundwater to the atmosphere, thus influencing the hydrologic cycle and climate. Deep roots enhance bedrock weathering, thus regulating the long-term carbon cycle. However, we know little about how deep roots go and why. Here, we present a global synthesis of 2,200 root observations of >1,000 species along biotic (life form, genus) and abiotic (precipitation, soil, drainage) gradients. Results reveal strong sensitivities of rooting depth to local soil water profiles determined by precipitation infiltration depth from the top (reflecting climate and soil), and groundwater table depth from below (reflecting topography-driven land drainage). In well-drained uplands, rooting depth follows infiltration depth; in waterlogged lowlands, roots stay shallow, avoiding oxygen stress below the water table; in between, high productivity and drought can send roots many meters down to the groundwater capillary fringe. This framework explains the contrasting rooting depths observed under the same climate for the same species but at distinct topographic positions. We assess the global significance of these hydrologic mechanisms by estimating root water-uptake depths using an inverse model, based on observed productivity and atmosphere, at 30″ (∼1-km) global grids to capture the topography critical to soil hydrology. The resulting patterns of plant rooting depth bear a strong topographic and hydrologic signature at landscape to global scales. They underscore a fundamental plant–water feedback pathway that may be critical to understanding plant-mediated global change.

Simulated Water Table and Soil Moisture Climatology Over North America

We demonstrate the link between two terrestrial water reservoirs: the root-zone soil moisture and the groundwater, and contribute our simulated climatologic water table depth and soil moisture fields over North America to the community. Because soil moisture strongly influences land-atmosphere fluxes, its link to the groundwater may affect the spatiotemporal variability of these fluxes. Here we simulate the climatologic water table depth at 30-arc-s resolution as constrained by U.S. Geological Survey site observations. Then, we use this water table climatology as the lower boundary for the soil, and variable infiltration capacity (VIC)-simulated land surface flux climatology as the upper boundary, to calculate the soil moisture climatology (SMC) at 14 depths (down to 4 m). Comparisons with VIC, the North America Regional Reanalysis (NARR), and observations suggest the following: first, SMC is wetter than VIC, despite their having identical land surface flux; second, while climate is the dominant signature...

Modeling seasonal snowpack evolution in the complex terrain and forested Colorado Headwaters region: A model intercomparison study

Correctly modeling snow is critical for climate models and for hydrologic applications. Snowpack simulated by six land surface models (LSM: Noah, Variable Infiltration Capacity, snow-atmosphere-soil transfer, Land Ecosystem-Atmosphere Feedback, Noah with Multiparameterization, and Community Land Model) were evaluated against 1 year snow water equivalent (SWE) data at 112 Snow Telemetry (SNOTEL) sites in the Colorado River Headwaters region and 4 year flux tower data at two AmeriFlux sites. All models captured the main characteristics of the seasonal SWE evolution fairly well at 112 SNOTEL sites. No single model performed the best to capture the combined features of the peak SWE, the timing of peak SWE, and the length of snow season. Evaluating only simulated SWE is deceiving and does not reveal critical deficiencies in models, because the models could produce similar SWE for starkly different reasons. Sensitivity experiments revealed that the models responded differently to variations of forest coverage. The treatment of snow albedo and its cascading effects on surface energy deficit, surface temperature, stability correction, and turbulent fluxes was a major intermodel discrepancy. Six LSMs substantially overestimated (underestimated) radiative flux (heat flux), a crucial deficiency in representing winter land-atmosphere feedback in coupled weather and climate models. Results showed significant intermodel differences in snowmelt efficiency and sublimation efficiency, and models with high rate of snow accumulation and melt were able to reproduce the observed seasonal evolution of SWE. This study highlights that the parameterization of cascading effects of snow albedo and below-canopy turbulence and radiation transfer is critical not only for SWE simulation but also for correctly capturing the winter land-atmosphere interactions.

Sensitivity of model-simulated summertime precipitation over the Mississippi River Basin to the spatial distribution of initial soil moisture

[1] Using a numerical model, the Regional Atmospheric Modeling System (RAMS), we simulate July precipitation over parts of the Mississippi River Basin and surroundings for each of three years, 1995–1997, with six different initial soil moisture patterns: three (control, dry, and wet) with a realistic (observationally based) spatial distribution, and three (control, dry, and wet) with a horizontally homogeneous distribution. Our goal is to determine the impact on future simulated precipitation of changing the initial soil moisture spatial distribution. The spatially homogeneous initial soil moisture pattern represents, in effect, a ‘‘wet west/dry east’’ anomaly imposed on the realistic soil moisture pattern (that reflects the west-to-east climatological gradient). The impact of this anomaly, i.e., increasing soil moisture in the western half and decreasing it in the eastern half of the simulation domain, is most pronounced for the dry experiments and weakens nonlinearly with increasing domain-average initial soil moisture. In the dry regime, the impact is to enhance the total monthly precipitation in both the west and east. We examine the various terms in the atmospheric moisture budget to interpret these results. The changes in precipitation in the runs with a homogeneous compared to realistic initial soil moisture spatial pattern are consistent with enhanced evaporation in the western half of the model domain accompanied by enhanced west-to-east horizontal moisture transport that helps restore the initially depleted soil moisture in the east. In this manner, the zonal moisture flux acts toward re-establishing the initial climatological soil moisture pattern of the region, thus acting as a negative feedback mechanism. In addition, the soil moisture anomaly generally produces diminished meridional moisture transport into the simulation domain from the south through a decrease in the low-level meridional wind speed. This decrease in meridional flux acts in the same direction as the zonal flux change in the west, and in the opposite direction to the zonal flux change in the east. Since this change is most pronounced in the west, it therefore also contributes to the overall negative feedback of the atmospheric dynamics on the initial soil moisture. The persistence timescale of the impact of this particular soil moisture anomaly pattern on precipitation is on the order of 3 months in the dry regime. Sensitivity of the results to a change in convection scheme is also explored. INDEX TERMS: 1854 Hydrology: Precipitation (3354); 1866 Hydrology: Soil moisture; 3322 Meteorology and Atmospheric Dynamics: Land/atmosphere interactions; 3354 Meteorology and Atmospheric Dynamics: Precipitation (1854); KEYWORDS: land/atmosphere, precipitation, soil moisture

Moisture recycling in the Iberian Peninsula from a regional climate simulation: Spatiotemporal analysis and impact on the precipitation regime

The contribution of the evapotranspiration from a certain region to the precipitation over the same area is referred to as water recycling. In this paper, we explore the spatiotemporal links between the recycling mechanism and the Iberian rainfall regime. We use a 9 km resolution Weather Research and Forecasting simulation of 18 years (1990–2007) to compute local and regional recycling ratios over Iberia, at the monthly scale, through both an analytical and a numerical recycling model. In contrast to coastal areas, the interior of Iberia experiences a relative maximum of precipitation in spring, suggesting a prominent role of land-atmosphere interactions on the inland precipitation regime during this period of the year. Local recycling ratios are the highest in spring and early summer, coinciding with those areas where this spring peak of rainfall represents the absolute maximum in the annual cycle. This confirms that recycling processes are crucial to explain the Iberian spring precipitation, particularly over the eastern and northeastern sectors. Average monthly recycling values range from 0.04 in December to 0.14 in June according to the numerical model and from 0.03 in December to 0.07 in May according to the analytical procedure. Our analysis shows that the highest values of recycling are limited by the coexistence of two necessary mechanisms: (1) the availability of sufficient soil moisture and (2) the occurrence of appropriate synoptic configurations favoring the development of convective regimes. The analyzed surplus of rainfall in spring has a critical impact on agriculture over large semiarid regions of the interior of Iberia.

Seasonal variations in North Atlantic atmospheric river activity and associations with anomalous precipitation over the Iberian Atlantic Margin

This work was funded by the Ministerio Espanol de Economia y Competitividad (CGL2013-45932-R) and the European Commission FP7 project EartH2Observe. S.B. would additionally like to thank the CSIC JAE-PREDOC programme for financial support.

Potential hydrologic changes in the Amazon by the end of the 21st century and the groundwater buffer

This study contributes to the discussions on the future of the Amazon rainforest under a projected warmer-drier climate from the perspectives of land hydrology. Using IPCC HadGEM2-ES simulations of the present and future Amazon climate to drive a land hydrology model that accounts for groundwater constraint on land drainage, we assess potential hydrologic changes in soil water, evapotranspiration (ET), water table depth, and river discharge, assuming unchanged vegetation. We ask: how will ET regimes shift at the end of the 21st century, and will the groundwater help buffer the anticipated water stress in some places-times? We conducted four 10 yr model simulations, at the end of 20th and 21st century, with and without the groundwater. Our model results suggest that, first, over the western and central Amazon, ET will increase due to increased potential evapotranspiration (PET) with warmer temperatures, despite a decrease in soil water; that is, ET will remain PET or atmospheric demand-limited. Second, in the eastern Amazon dry season, ET will decrease in response to decreasing soil water, despite increasing PET demand; that is, ET in these regions-seasons will remain or become more soil water or supply-limited. Third, the area of water-limited regions will likely expand in the eastern Amazonia, with the dry season, as indicated by soil water store, even drier and longer. Fourth, river discharge will be significantly reduced over the entire Amazon but particularly so in the southeastern Amazon. By contrasting model results with and without the groundwater, we found that the slow soil drainage constrained by shallow groundwater can buffer soil water stress, particularly in southeastern Amazon dry season. Our model suggests that, if groundwater buffering effect is accounted for, the future Amazon water stress may be less than that projected by most climate models.

Sensitivity of a Global Forecast Model to Initializations with Reanalysis Datasets

A global research model is initialized with reanalysis datasets obtained from NCEP and ECMWF. The globally averaged accuracy of the resulting 120-h predictions varies little between the different initializations, but a perceptible difference arises in the mid- to high latitudes of the Southern Hemisphere, where ECMWF initialized forecasts have somewhat greater skill. Most of this benefit is explained by differences of the longer-wave components (wavenumbers 0‐15) of the initial data. This motivates further diagnoses of globally computed sensitivity measures to initial data changes. Approximately 67% of the 120-h forecast difference produced by changing initial data from ECMWF to NCEP reanalyses is due to initial changes only in wavenumbers 0‐15, and more than 85% of this difference is produced by initial changes in wavenumbers 0‐20. The result implies downscale uncertainty growth and contradicts several recent predictability investigations based upon singular vector analyses, which emphasize upscale uncertainty growth. The results do not imply that singular vector analyses are in error. They only suggest that large-scale errors of the initial state may play a more prominent role than suggested in some singular vector analyses. Downscale uncertainty evolution may be due to greater analysis uncertainty at large spatial scales than considered in prior recent studies emphasizing upscale predictability loss.