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Journal ArticleDOI

WAYS v1: a hydrological model for root zone water storage simulation on a global scale

17 Dec 2019-Geoscientific Model Development (Copernicus GmbH)-Vol. 12, Iss: 12, pp 5267-5289
TL;DR: In this article, a hydrological model named the Water And ecosYstem Simulator (WAYS) is developed to simulate the root zone water storage (RZWS) on a global scale.
Abstract: . The soil water stored in the root zone is a critical variable for many applications, as it plays a key role in several hydrological and atmospheric processes. Many studies have been conducted to obtain reliable information on soil water in the root zone layer. However, most of them are mainly focused on the soil moisture within a certain depth rather than the water stored in the entire rooting system. In this work, a hydrological model named the Water And ecosYstem Simulator (WAYS) is developed to simulate the root zone water storage (RZWS) on a global scale. The model is based on a well-validated lumped model and has now been extended to a distribution model. To reflect the natural spatial heterogeneity of the plant rooting system across the world, a key variable that influences RZWS, i.e., root zone storage capacity (RZSC), is integrated into the model. The newly developed model is first evaluated based on runoff and RZWS simulations across 10 major basins. The results show the ability of the model to mimic RZWS dynamics in most of the regions through comparison with proxy data, the normalized difference infrared index (NDII). The model is further evaluated against station observations, including flux tower and gauge data. Despite regional differences, generally good performance is found for both the evaporation and discharge simulations. Compared to existing hydrological models, WAYS's ability to resolve the field-scale spatial heterogeneity of RZSC and simulate RZWS may offer benefits for many applications, e.g., agriculture and land–vegetation–climate interaction investigations. However, the results from this study suggest an additional evaluation of RZWS is required for the regions where the NDII might not be the correct proxy.

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Citations
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01 Dec 2004
TL;DR: In this paper, the authors search the literature for a common set of variables that might be combined into an index to quantify the greenness of vegetation throughout the year, such as daylength (photoperiod), evaporative demand (vapor pressure deficit), and suboptimal (minimum) temperatures.
Abstract: The phenological state of vegetation significantly affects exchanges of heat, mass, and momentum between the Earth's surface and the atmosphere. Although current patterns can be estimated from satellites, we lack the ability to predict future trends in response to climate change. We searched the literature for a common set of variables that might be combined into an index to quantify the greenness of vegetation throughout the year. We selected as variables: daylength (photoperiod), evaporative demand (vapor pressure deficit), and suboptimal (minimum) temperatures. For each variable we set threshold limits, within which the relative phenological performance of the vegetation was assumed to vary from inactive (0) to unconstrained (1). A combined Growing Season Index (GSI) was derived as the product of the three indices. Ten-day mean GSI values for nine widely dispersed ecosystems showed good agreement (r>0.8) with the satellite-derived Normalized Difference Vegetation Index (NDVI). We also tested the model at a temperate deciduous forest by comparing model estimates with average field observations of leaf flush and leaf coloration. The mean absolute error of predictions at this site was 3 days for average leaf flush dates and 2 days for leaf coloration dates. Finally, we used this model to produce a global map that distinguishes major differences in regional phenological controls. The model appears sufficiently robust to reconstruct historical variation as well as to forecast future phenological responses to changing climatic conditions.

366 citations

01 Apr 2015
TL;DR: The SWBM dataset as discussed by the authors is derived with a simple water balance model (SWBM) forced with precipitation, temperature and net radiation, and extends over the period 1984-2013 with a daily time step and 0.5° × 0. 5° resolution.
Abstract: Land surface hydrology can play a crucial role during extreme events such as droughts, floods and even heat waves. We introduce in this study a new hydrological dataset for Europe that consists of soil moisture, runoff and evapotranspiration (ET). It is derived with a simple water balance model (SWBM) forced with precipitation, temperature and net radiation. The SWBM dataset extends over the period 1984–2013 with a daily time step and 0.5° × 0.5° resolution. We employ a novel calibration approach, in which we consider 300 random parameter sets chosen from an observation-based range. Using several independent validation datasets representing soil moisture (or terrestrial water content), ET and streamflow, we identify the best performing parameter set and hence the new dataset. To illustrate its usefulness, the SWBM dataset is compared against several state-of-the-art datasets (ERA-Interim/Land, MERRA-Land, GLDAS-2-Noah, simulations of the Community Land Model Version 4), using all validation datasets as reference. For soil moisture dynamics it outperforms the benchmarks. Therefore the SWBM soil moisture dataset constitutes a reasonable alternative to sparse measurements, little validated model results, or proxy data such as precipitation indices. Also in terms of runoff the SWBM dataset performs well, whereas the evaluation of the SWBM ET dataset is overall satisfactory, but the dynamics are less well captured for this variable. This highlights the limitations of the dataset, as it is based on a simple model that uses uniform parameter values. Hence some processes impacting ET dynamics may not be captured, and quality issues may occur in regions with complex terrain. Even though the SWBM is well calibrated, it cannot replace more sophisticated models; but as their calibration is a complex task the present dataset may serve as a benchmark in future. In addition we investigate the sources of skill of the SWBM dataset and find that the parameter set has a similar impact on the simple model results as the choice of the forcing dataset. The newly derived SWBM dataset is of relevance for a range of applications given the deficit of available land datasets. It is available for download on www.iac.ethz.ch/url/SWBM-Dataset.

31 citations

Journal ArticleDOI
01 Mar 2020
TL;DR: In this paper, the authors evaluated the environmental sustainability of blue, green and grey WF for China's 31 mainland provinces in 2002, 2007 and 2012, and identified the unsustainable hotspots.
Abstract: Water footprint (WF) measures human appropriation of water resources for consumptive use of surface and ground water (blue WF) and soil water (green WF) and for assimilating polluted water (grey WF). Questions have been often asked about the exact meaning behind the numbers from WF accounting. However, to date environmental sustainability of WF has never been assessed at the sub-national level over time. This study evaluated the environmental sustainability of blue, green and grey WF for China's 31 mainland provinces in 2002, 2007 and 2012, and identified the unsustainable hotspots. Overall, the total WF increased by 30% between 2002 and 2012. The growth can be attributed to the increase of grey WF because the green and blue WF showed only a slight rise. Among all provinces investigated in 2012, eleven showed unsustainable blue WF (sustainability index SI

31 citations

Journal ArticleDOI
TL;DR: In this paper, the authors proposed a "nexus" approach that integrates a water supply constrained multi-regional input-output (mixed MRIO) model, scenario analysis, and multi-criteria decision analysis (MCDA) to quantify the trade-offs and synergies at the sectoral level for the capital region of China, i.e. the Beijing-Tianjin-Hebei urban agglomeration.

28 citations

01 Apr 2015
TL;DR: The ERA-Interim/Land dataset as mentioned in this paper provides a global integrated and coherent estimate of soil moisture and snow water equivalent, which can also be used for the initialization of numerical weather prediction and climate models.
Abstract: ERA-Interim/Land is a global land surface reanalysis data set covering the period 1979–2010. It describes the evolution of soil moisture, soil temperature and snowpack. ERA-Interim/Land is the result of a single 32-year simulation with the latest ECMWF (European Centre for Medium-Range Weather Forecasts) land surface model driven by meteorological forcing from the ERA-Interim atmospheric reanalysis and precipitation adjustments based on monthly GPCP v2.1 (Global Precipitation Climatology Project). The horizontal resolution is about 80 km and the time frequency is 3-hourly. ERA-Interim/Land includes a number of parameterization improvements in the land surface scheme with respect to the original ERA-Interim data set, which makes it more suitable for climate studies involving land water resources. The quality of ERA-Interim/Land is assessed by comparing with ground-based and remote sensing observations. In particular, estimates of soil moisture, snow depth, surface albedo, turbulent latent and sensible fluxes, and river discharges are verified against a large number of site measurements. ERA-Interim/Land provides a global integrated and coherent estimate of soil moisture and snow water equivalent, which can also be used for the initialization of numerical weather prediction and climate models.

25 citations

References
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Book
01 Jan 1998
TL;DR: In this paper, an updated procedure for calculating reference and crop evapotranspiration from meteorological data and crop coefficients is presented, based on the FAO Penman-Monteith method.
Abstract: (First edition: 1998, this reprint: 2004). This publication presents an updated procedure for calculating reference and crop evapotranspiration from meteorological data and crop coefficients. The procedure, first presented in FAO Irrigation and Drainage Paper No. 24, Crop water requirements, in 1977, allows estimation of the amount of water used by a crop, taking into account the effect of the climate and the crop characteristics. The publication incorporates advances in research and more accurate procedures for determining crop water use as recommended by a panel of high-level experts organised by FAO in May 1990. The first part of the guidelines includes procedures for determining reference crop evapotranspiration according to the FAO Penman-Monteith method. These are followed by updated procedures for estimating the evapotranspiration of different crops for different growth stages and ecological conditions.

21,958 citations

Journal ArticleDOI
TL;DR: In this paper, an updated gridded climate dataset (referred to as CRU TS3.10) from monthly observations at meteorological stations across the world's land areas is presented.
Abstract: This paper describes the construction of an updated gridded climate dataset (referred to as CRU TS3.10) from monthly observations at meteorological stations across the world's land areas. Station anomalies (from 1961 to 1990 means) were interpolated into 0.5° latitude/longitude grid cells covering the global land surface (excluding Antarctica), and combined with an existing climatology to obtain absolute monthly values. The dataset includes six mostly independent climate variables (mean temperature, diurnal temperature range, precipitation, wet-day frequency, vapour pressure and cloud cover). Maximum and minimum temperatures have been arithmetically derived from these. Secondary variables (frost day frequency and potential evapotranspiration) have been estimated from the six primary variables using well-known formulae. Time series for hemispheric averages and 20 large sub-continental scale regions were calculated (for mean, maximum and minimum temperature and precipitation totals) and compared to a number of similar gridded products. The new dataset compares very favourably, with the major deviations mostly in regions and/or time periods with sparser observational data. CRU TS3.10 includes diagnostics associated with each interpolated value that indicates the number of stations used in the interpolation, allowing determination of the reliability of values in an objective way. This gridded product will be publicly available, including the input station series (http://www.cru.uea.ac.uk/ and http://badc.nerc.ac.uk/data/cru/). © 2013 Royal Meteorological Society

5,552 citations

Journal ArticleDOI
TL;DR: In this paper, a generalization of the single soil layer variable infiltration capacity (VIC) land surface hydrological model previously implemented in the Geophysical Fluid Dynamics Laboratory (GFDL) general circulation model (GCM) is described.
Abstract: A generalization of the single soil layer variable infiltration capacity (VIC) land surface hydrological model previously implemented in the Geophysical Fluid Dynamics Laboratory (GFDL) general circulation model (GCM) is described. The new model is comprised of a two-layer characterization of the soil column, and uses an aerodynamic representation of the latent and sensible heat fluxes at the land surface. The infiltration algorithm for the upper layer is essentially the same as for the single layer VIC model, while the lower layer drainage formulation is of the form previously implemented in the Max-Planck-Institut GCM. The model partitions the area of interest (e.g., grid cell) into multiple land surface cover types; for each land cover type the fraction of roots in the upper and lower zone is specified. Evapotranspiration consists of three components: canopy evaporation, evaporation from bare soils, and transpiration, which is represented using a canopy and architectural resistance formulation. Once the latent heat flux has been computed, the surface energy balance is iterated to solve for the land surface temperature at each time step. The model was tested using long-term hydrologic and climatological data for Kings Creek, Kansas to estimate and validate the hydrological parameters, and surface flux data from three First International Satellite Land Surface Climatology Project Field Experiment (FIFE) intensive field campaigns in the summer-fall of 1987 to validate the surface energy fluxes.

3,297 citations

Journal ArticleDOI
TL;DR: The Twentieth Century Reanalysis (20CR) dataset as discussed by the authors provides the first estimates of global tropospheric variability, and of the dataset's time-varying quality, from 1871 to the present at 6-hourly temporal and 2° spatial resolutions.
Abstract: The Twentieth Century Reanalysis (20CR) project is an international effort to produce a comprehensive global atmospheric circulation dataset spanning the twentieth century, assimilating only surface pressure reports and using observed monthly sea-surface temperature and sea-ice distributions as boundary conditions. It is chiefly motivated by a need to provide an observational dataset with quantified uncertainties for validations of climate model simulations of the twentieth century on all time-scales, with emphasis on the statistics of daily weather. It uses an Ensemble Kalman Filter data assimilation method with background ‘first guess’ fields supplied by an ensemble of forecasts from a global numerical weather prediction model. This directly yields a global analysis every 6 hours as the most likely state of the atmosphere, and also an uncertainty estimate of that analysis. The 20CR dataset provides the first estimates of global tropospheric variability, and of the dataset's time-varying quality, from 1871 to the present at 6-hourly temporal and 2° spatial resolutions. Intercomparisons with independent radiosonde data indicate that the reanalyses are generally of high quality. The quality in the extratropical Northern Hemisphere throughout the century is similar to that of current three-day operational NWP forecasts. Intercomparisons over the second half-century of these surface-based reanalyses with other reanalyses that also make use of upper-air and satellite data are equally encouraging. It is anticipated that the 20CR dataset will be a valuable resource to the climate research community for both model validations and diagnostic studies. Some surprising results are already evident. For instance, the long-term trends of indices representing the North Atlantic Oscillation, the tropical Pacific Walker Circulation, and the Pacific–North American pattern are weak or non-existent over the full period of record. The long-term trends of zonally averaged precipitation minus evaporation also differ in character from those in climate model simulations of the twentieth century. Copyright © 2011 Royal Meteorological Society and Crown Copyright.

3,043 citations

Journal ArticleDOI
TL;DR: The datasets and algorithms used to create the Collection 5 MODIS Global Land Cover Type product, which is substantially changed relative to Collection 4, are described, with a four-fold increase in spatial resolution and changes in the input data and classification algorithm.

2,713 citations