Mean seasonal and spatial variability in gauge‐corrected, global precipitation

Legates, David R.; Willmott, Cort J.

doi:10.1002/joc.3370100202

Cited by 1,406 publications

(872 citation statements)

References 23 publications

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“…We use this 40-year interval because it includes a high spatial coverage of rain-gauge stations 36 . We corrected for systematic rain gauge measurement error using static monthly under-catch corrections 37 provided by the Global Precipitation Climatology Center. Driving data for PET.…”

Section: Methodsmentioning

confidence: 99%

Water balance creates a threshold in soil pH at the global scale

Slessarev

Lin

Bingham

et al. 2016

Nature

437

255

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Soil pH regulates the capacity of soils to store and supply nutrients, and thus contributes substantially to controlling productivity in terrestrial ecosystems 1 . However, soil pH is not an independent regulator of soil fertility-rather, it is ultimately controlled by environmental forcing. In particular, small changes in water balance cause a steep transition from alkaline to acid soils across natural climate gradients 2,3 . Although the processes governing this threshold in soil pH are well understood, the threshold has not been quantified at the global scale, where the influence of climate may be confounded by the effects of topography and mineralogy. Here we evaluate the global relationship between water balance and soil pH by extracting a spatially random sample (n = 20,000) from an extensive compilation of 60,291 soil pH measurements. We show that there is an abrupt transition from alkaline to acid soil pH that occurs at the point where mean annual precipitation begins to exceed mean annual potential evapotranspiration. We evaluate deviations from this global pattern, showing that they may result from seasonality, climate history, erosion and mineralogy. These results demonstrate that climate creates a nonlinear pattern in soil solution chemistry at the global scale; they also reveal conditions under which soils maintain pH out of equilibrium with modern climate.Climate controls many aspects of soil chemistry, affecting soil pH (ref. 4). Alkaline soils are known to be common in arid climates, while acid soils are known to be common in humid climates 1 . Surprisingly, however, the global-scale mechanisms governing this pattern remain broadly defined, and untested by direct observation. What are the dominant chemical equilibria that constrain soil pH? What aspect of climate defines the transition between alkaline and acid soils, and is the transition linear? The answers to these questions are fundamental to understanding soil development and surface geochemistry at the global scale. Furthermore, achieving this understanding may prove essential for representing soils in models of the terrestrial biosphere, given that soil pH controls many aspects of soil fertility 5,6 . Here we illustrate that simple geochemical and hydrological concepts can be used to build a mechanistic understanding of soil pH at the global scale.Interpretations of acid-titration experiments indicate that the soil pH is typically most strongly buffered by equilibrium with two secondary minerals: calcite (CaCO 3 ), or gibbsite (Al(OH) 3 ) 7,8 Fig. 1).Local studies of climate gradients have shown that the relative importance of these two buffers is determined by leaching, which removes Ca 2+ from the soil 2,3,8,9 . In climates where evaporative demand exceeds precipitation, leaching rates are low, and dissolved Ca 2+ accumulates as CaCO 3 -buffering soil pH near 8.2 (ref. 4). Conversely, in climates where precipitation exceeds evaporative demand, water leaches through the soil, removing Ca 2+ and allowing accumulation of relatively immobile...

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Section: Methodsmentioning

confidence: 99%

Water balance creates a threshold in soil pH at the global scale

Slessarev

Lin

Bingham

et al. 2016

Nature

437

255

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“…The gauged discharge data used were collated by the Global Runoff Data Centre (GRDC) from 1348 gauging stations with tributaries larger than 2500 km 2 and with time series exceeding 12 years with < 10% missing data. The water balance model uses the data set of Legates and Willmott (1990a) for global precipitation, the formula of Hamon (1963) to calculate evapotranspiration on the basis of temperature (using the data set of Legates and Willmott, 1990b), soil type data from the FAO/UNESCO soil data bank (FAO/UNESCO, 1986), topographic data from the ETOPO5 global elevation data set (Edwards, 1989) and a contemporary land cover classification derived from the Terrestrial Ecosystem Model (Melillo et al, 1993) with Olson's land use classification (Olson, 1991).…”

Section: Hydrological Data 221 Runoff Datamentioning

confidence: 99%

Estimating surface water concentrations of “down-the-drain” chemicals in China using a global model

Whelan¹,

Hodges²,

Williams³

et al. 2012

Environmental Pollution

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Predictions of surface water exposure to "down-the-drain" chemicals are presented which employ grid-based spatially-referenced data on average monthly runoff, population density, country-specific per capita domestic water and substance use rates and sewage treatment provision. Water and chemical load are routed through the landscape using flow directions derived from digital elevation data, accounting for in-stream chemical losses using simple first order kinetics. Although the spatial and temporal resolution of the model are relatively coarse, the model still has advantages over spatially inexplicit "unit-world" approaches, which apply arbitrary dilution factors, in terms of predicting the location of exposure hotspots and the statistical distribution of concentrations. The latter can be employed in probabilistic risk assessments. Here the model was applied to predict surface water exposure to "downthe-drain" chemicals in China for different levels of sewage treatment provision.Predicted spatial patterns of concentration were consistent with observed water quality classes for China.Key Words: Global, Exposure, Chemical, Model, China Capsule AbstractA global-scale model was used to predict spatial patterns of "down-the-drain" chemical concentrations in China. Predictions were consistent with observed water quality classes, demonstrating the potential value of the model.3

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“…The Canadian Arctic archipelago and the Middle East were also excluded from the simulation because of extreme regional errors in the DTMs. The simulations used observational estimates of the modern mean annual runoff [Cogley, 1989] and precipitation [Legates and Willmott, 1990] and calculated surface water evaporation converted to the 5'x5' resolution of SWAM. Annual forcing was used because no seasonal or monthly data sets of runoff were available for all continents.…”

Section: Experimental Designmentioning

confidence: 99%

A linked global model of terrestrial hydrologic processes: Simulation of modern rivers, lakes, and wetlands

Coe¹

1998

J. Geophys. Res.

127

111

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Abstract. A terrain-based hydrologic model is developed to simulate rivers, lakes, and wetlands on the continental scale as a linked dynamical system. This surface water area model (SWAM) is an extension of earlier work and is based on a linear reservoir model. The model requires, as input, estimates of runoff, precipitation, and evaporation from either observations or climate simulations. The model develops its own river transport directions based on elevation. The river discharge is calculated at each grid cell as the accumulated flow of water across the land surface. Lake and wetland area and volume are calculated as a function of the local precipitation minus evaporation, the streamflow into and out of the grid cells, and the potential for storage of water on the surface as derived from 5'x5' resolution digital terrain models. SWAM is applied on a 5'x5' spatial resolution to simulate present-day surface waters and river transport for all continents (except Antarctica and Greenland). The model simulates the discharge of the 27 major rivers of the world in fair agreement with the observations; 12 of the rivers have simulated discharge within + 20% of the observational estimates. The discharge from rivers in arid and semi-arid climates is generally overestimated probably due to underestimated evaporation from wetlands, irrigated croplands, and reservoirs within the river basins. The modem simulated lake area (about 3% of the land area) is larger than the observed area (about 2% of the land area). Wetlands are poorly simulated by the model due to the coarse vertical and horizontal resolution of the digital terrain models. The model simulates the potential for increased surface water (up to 7.5% of the global land area) and river basin area in semi-arid and arid regions where closed basins exist in the present day climate which illustrates the utility of SWAM for climate change experiments. While higher resolution and more accurate digital terrain models are needed to improve these surface water simulations (particularly for wetlands), these preliminary results indicate that current digital terrain models are adequate for including lakes and rivers as interactive components in the surface hydrology parameterizations of climate models and for studying feedbacks between lakes and climate.

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Mean seasonal and spatial variability in gauge‐corrected, global precipitation

Cited by 1,406 publications

References 23 publications

Water balance creates a threshold in soil pH at the global scale

Water balance creates a threshold in soil pH at the global scale

Estimating surface water concentrations of “down-the-drain” chemicals in China using a global model

A linked global model of terrestrial hydrologic processes: Simulation of modern rivers, lakes, and wetlands

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