scholarly journals Depth distribution of soil water sourced by plants at the global scale: A new direct inference approach

Ecohydrology ◽  
2020 ◽  
Vol 13 (2) ◽  
Author(s):  
Anam Amin ◽  
Giulia Zuecco ◽  
Josie Geris ◽  
Luitgard Schwendenmann ◽  
Jeffrey J. McDonnell ◽  
...  
Keyword(s):  
Soil Water ◽  
Depth Distribution ◽  
Global Scale ◽  
Direct Inference

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

2019 ◽  
Vol 12 (12) ◽  
pp. 5267-5289 ◽  
Author(s):  
Ganquan Mao ◽  
Junguo Liu
Keyword(s):  
Spatial Heterogeneity ◽  
Soil Water ◽  
Regional Differences ◽  
Hydrological Model ◽  
Root Zone ◽  
Water Storage ◽  
Global Scale ◽  
Distribution Model ◽  
Lumped Model ◽  
Zone Water

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.

scholarly journals A hydrological model for root zone water storage simulation on a global scale

2019 ◽  
Author(s):  
Ganquan Mao ◽  
Junguo Liu
Keyword(s):  
Soil Water ◽  
Hydrological Model ◽  
Storage Capacity ◽  
Root Zone ◽  
Water Storage ◽  
Global Scale ◽  
Distribution Model ◽  
Lumped Model ◽  
Zone Water ◽  
Strong Capacity

Abstract. The soil water stored in the root zone is a critical variable for many applications as it plays key role in several hydrological and atmospheric processes. Many studies have been done to obtain reliable soil water information in the root zone layer. However, most of them are mainly focused on the soil moisture in a certain depth rather than the water stored in the entire rooting system. In this work, a hydrological model 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 been extended now to a distribution model. To reflect the natural spatial heterogeneity of the plant rooting system across the world, a key variable that influencing the RZWS, i.e. root zone storage capacity (RZSC), is integrated into the model. The newly developed model is evaluated on runoff and RZWS simulation across ten major basins. The evaluation of runoff indicates the strong capacity of the model for monthly simulation with a good performance on time series and distribution depiction. Results also show the ability of the model for RZWS dynamics mimicing in most of the regions. This model may offer benefits for many applications due to its ability for RZWS simulation. However, attentions need to also be paid for application as the high latitude regions are not investigated by this work due to the incomplete latitudinal coverage of the RZSC. Therefore, the performance of the model in such regions are not justified.

scholarly journals Coffee and shade trees show complementary use of soil water in a traditional agroforestry ecosystem

2019 ◽  
Author(s):  
Lyssette E. Muñoz-Villers ◽  
Josie Geris ◽  
Susana Alvarado-Barrientos ◽  
Friso Holwerda ◽  
Todd E. Dawson
Keyword(s):  
Soil Water ◽  
Belowground Biomass ◽  
Root Water Uptake ◽  
Global Scale ◽  
Agroforestry Systems ◽  
Water Sources ◽  
Shade Trees ◽  
Wet Season ◽  
Trema Micrantha ◽  
Traditional Agroforestry

Abstract. On a global scale, coffee has become one of the most sensitive commercial crops that will be affected by climate change. The majority of Arabica coffee (Coffea arabica) grows in traditionally shaded agroforestry systems and accounts for ∼ 70 % of the coffee production worldwide. Nevertheless, the interaction between plant and soil water sources in these coffee plantations remains poorly understood. To investigate the functional response of dominant shade trees species and coffee (C. arabica var. typica) plants to different soil water availability conditions, we conducted a study during a normal and more pronounced dry season (2014 and 2017, respectively) and the 2017 wet season in a traditional agroecosystem in central Veracruz, Mexico. For the different periods, we specifically investigated the variations in water sources and root water uptake via MIXSIAR mixing models using δ18O and δ2H stable isotopes of rainfall, plant xylem and soil water, along with micrometeorological and soil moisture measurements. To further increase our mechanistic understanding about root activity, the distribution of belowground biomass and soil macronutrients were also examined and considered in the model. Results showed that, over the course of the two dry seasons investigated, all shade tree species (Lonchocarpus guatemalensis, Inga vera and Trema micrantha) relied on water sources from deeper soil layers (˃ 15 to 120 cm depth; 86 %), while the use of much shallower water sources (

scholarly journals DYPTOP: a cost-efficient TOPMODEL implementation to simulate sub-grid spatio-temporal dynamics of global wetlands and peatlands

2014 ◽  
Vol 7 (4) ◽  
pp. 4875-4930 ◽  
Author(s):  
B. D. Stocker ◽  
R. Spahni ◽  
F. Joos
Keyword(s):  
Water Balance ◽  
Soil Water ◽  
Temporal Dynamics ◽  
Global Scale ◽  
Future Climate Change ◽  
Computationally Efficient ◽  
Modelling Studies ◽  
Spatio Temporal ◽  
Inundation Extent ◽  
Cost Efficient

Abstract. Simulating the spatio-temporal dynamics of inundation is key to understanding the role of wetlands under past and future climate change. Earlier modelling studies have mostly relied on fixed prescribed peatland maps and inundation time series of limited temporal coverage. Here, we describe and assess the DYPTOP model that predicts the extent of inundation based on a computationally efficient TOPMODEL implementation. This approach rests on an empirical, gridcell-specific relationship between the mean soil water balance and the flooded area. DYPTOP combines the simulated inundation extent and its temporal persistency with criteria for the ecosystem water balance and the modelled peatland-specific soil carbon balance to predict the global distribution of peatlands. Here, we apply DYPTOP in combination with the LPX-Bern DGVM and benchmark the global-scale distribution, extent, and seasonality of inundation against satellite data. DYPTOP successfully predicts the spatial distribution and extent of wetlands and major boreal and tropical peatland complexes and reveals the governing limitations to peatland occurrence across the globe. Peatlands covering large boreal lowlands are reproduced only when accounting for a positive feedback induced by the enhanced mean soil water holding capacity in peatland-dominated regions. DYPTOP is designed to minimize input data requirements, optimizes computational efficiency and allows for a modular adoption in Earth system models.

scholarly journals DYPTOP: a cost-efficient TOPMODEL implementation to simulate sub-grid spatio-temporal dynamics of global wetlands and peatlands

2014 ◽  
Vol 7 (6) ◽  
pp. 3089-3110 ◽  
Author(s):  
B. D. Stocker ◽  
R. Spahni ◽  
F. Joos
Keyword(s):  
Water Balance ◽  
Soil Water ◽  
Temporal Dynamics ◽  
Grid Cell ◽  
Global Scale ◽  
Future Climate Change ◽  
Computationally Efficient ◽  
Modelling Studies ◽  
Spatio Temporal ◽  
Inundation Extent

Abstract. Simulating the spatio-temporal dynamics of inundation is key to understanding the role of wetlands under past and future climate change. Earlier modelling studies have mostly relied on fixed prescribed peatland maps and inundation time series of limited temporal coverage. Here, we describe and assess the the Dynamical Peatland Model Based on TOPMODEL (DYPTOP), which predicts the extent of inundation based on a computationally efficient TOPMODEL implementation. This approach rests on an empirical, grid-cell-specific relationship between the mean soil water balance and the flooded area. DYPTOP combines the simulated inundation extent and its temporal persistency with criteria for the ecosystem water balance and the modelled peatland-specific soil carbon balance to predict the global distribution of peatlands. We apply DYPTOP in combination with the LPX-Bern DGVM and benchmark the global-scale distribution, extent, and seasonality of inundation against satellite data. DYPTOP successfully predicts the spatial distribution and extent of wetlands and major boreal and tropical peatland complexes and reveals the governing limitations to peatland occurrence across the globe. Peatlands covering large boreal lowlands are reproduced only when accounting for a positive feedback induced by the enhanced mean soil water holding capacity in peatland-dominated regions. DYPTOP is designed to minimize input data requirements, optimizes computational efficiency and allows for a modular adoption in Earth system models.

scholarly journals Most Root-derived Carbon Inputs Do Not Contribute to the Global Bulk Soil Carbon Pool

2021 ◽  
Author(s):  
Zhongkui Luo ◽  
Guocheng Wang ◽  
Liujun Xiao ◽  
Xiali Mao ◽  
Xiaowei Guo ◽  
...  
Keyword(s):  
Depth Distribution ◽  
Soil Depth ◽  
Plant Root ◽  
Primary Source ◽  
Global Scale ◽  
Bulk Soil ◽  
Soil C ◽  
C Storage ◽  
Spatially Explicit Data ◽  
Earth System Models

Abstract Plant root-derived carbon (C) inputs (Iroot) are the primary source of C in mineral bulk soil. However, a fraction of Iroot may lose directly (Iloss, e.g., via rhizosphere microbial respiration, leaching and fauna feeding) without contributing to bulk soil C pool. This loss has never been quantified, particularly at global scale, inhibiting reliable estimation of soil C dynamics. Here we integrate three observational global datasets including radiocarbon content, allocation of photosynthetically assimilated C, and root biomass distribution in 2,034 soil profiles to quantify Iroot and its contribution to the bulk soil C pool. We show that global average Iroot in the 0-200 cm soil profile is 3.5 Mg ha-1 yr-1, ~80% of which (i.e., Iloss) is lost rather than entering bulk soil. If ignoring Iloss, bulk soil C turnover will be incorrectly estimated to be four times faster. This can explain why Earth system models (in which all Iroot enters bulk soil C pools) predict much faster soil C turnover than radiocarbon-constrained estimates. Iroot decreases exponentially with soil depth, and the top 20 cm soil contains >60% of total Iroot. Actual C input to bulk soil (i.e., Iroot – Iloss) shows a similar depth distribution to Iroot. We also map Iloss and its depth distribution across the globe. Our results demonstrate the global significance of direct C losses which limit the contribution of Iroot to bulk soil C storage; and provide spatially explicit data to facilitate reliable soil C predictions via separating direct C losses from total root-derived C inputs.

scholarly journals Weak sensitivity of the terrestrial water budget to global soil texture maps in the ORCHIDEE land surface model

2019 ◽  
Author(s):  
Salma Tafasca ◽  
Agnès Ducharne ◽  
Christian Valentin
Keyword(s):  
Soil Water ◽  
Soil Texture ◽  
Land Surface ◽  
Large Scale ◽  
Land Surface Model ◽  
Global Scale ◽  
Added Value ◽  
Surface Model ◽  
Total Runoff ◽  
The Impact

Abstract. Soil physical properties play an important role for estimating soil water and energy fluxes. Many hydrological and land surface models (LSMs) use soil texture maps to infer these properties. Here, we investigate the impact of soil texture on soil water fluxes and storage at global scale using the ORCHIDEE LSM, forced by several complex or globally-uniform soil texture maps. The model shows a realistic sensitivity of runoff processes and soil moisture to soil texture, and reveals that medium textures give the highest evapotranspiration and lowest total runoff rates. The three tested complex soil texture maps being rather similar by construction, especially when upscaled at the 0.5° resolution used here, they result in similar water budgets at all scales, compared to the uncertainties of observation-based products and meteorological forcing datasets. A useful outcome is that the choice of the input soil texture map is not crucial for large-scale modelling. The added-value of more detailed soil information (horizontal and vertical resolution, soil composition) deserves further studies.

A Global Picture of the Depth and Origin of Soil Water Uptake by Vegetation

2020 ◽  
Author(s):  
Gonzalo Miguez-Macho ◽  
Ying Fan
Keyword(s):  
Soil Water ◽  
Water Uptake ◽  
Land Surface ◽  
Global Scale ◽  
Wet Season ◽  
Deep Soil ◽  
Deep Roots ◽  
Carbon Cycles ◽  
Dry Climates ◽  
Shallow Soils

<div><span>Plants play a fundamental role in the climate system, not only as important components of the global water and carbon cycles, but because they provide a key link between water stores in the deep soil and the atmosphere. Vegetation has evolved strategies to cope with droughts, such as the existence of deep roots allowing for the shifting of water uptake to deeper layers storing past precipitation, as water from more recent precipitation on top is depleted and not replenished. Here we ask the following question: To what extent is the soil water uptake source for vegetation the recent rain reaching shallow soils, or past wet-season rain stored in deep soils, or past rain that reached the water table, which sends the water back up through capillary flux, or past rain that flowed down the topographic gradient from ridges to valleys (i.e. upland to lowland subsidy)? We address this question through (a) a synthesis of 528 observations of stable isotopes of O/H in plant xylem and source waters, compiled from the literature, and (b) a dynamic high-resolution (1km) model representing the global soil-plant-atmosphere continuum at the global scale by explicitly coupling land surface-groundwater and root uptake, driven by reanalysis atmosphere and observed leaf area. Both model and isotope methods reveal that plant use of past precipitation is globally widespread and particularly significant in semi-arid or seasonally dry climates and lowland ecosystems. Seasonal shifting to deeper uptake tapping past precipitation in dry periods is common even in wetter climates. </span>The model results allow us to further distinguish among past precipitation stored as deep soil water or from local or remote groundwater sources. Our findings shed critical lights on the depth and origin of the water supporting global photosynthesis, hence their resilience or vulnerability to seasonal-interannual droughts across the globe and vegetation response to climate change.</div>

Estimating soil moisture at various depths from near surface ESA CCI Soil Moisture

2020 ◽  
Author(s):  
Manolis G. Grillakis ◽  
Aristeidis G. Koutroulis ◽  
Christos Polykretis ◽  
Dimitrios D. Alexakis
Keyword(s):  
Soil Moisture ◽  
Soil Water ◽  
European Space Agency ◽  
Soil Layer ◽  
Global Scale ◽  
Systematic Evaluation ◽  
Multilinear Regression ◽  
Infiltration Process ◽  
Near Surface ◽  
Different Depths

<p>Soil moisture drought is a natural, reoccurring phenomenon that can affect any part of the land. It consists one of the most challenging problems for the modern agriculture as it directly affects the water, energy and food security nexus. Remote sensed soil moisture products have been proved to be valuable tools for the study of the soil moisture droughts. The European Space Agency (ESA), through the Climate Change Initiative (CCI) is currently providing nearly 4 decades of global satellite observed, fully homogenized soil moisture (SM) data for the uppermost soil layer. This data is valuable as it consists one of the most complete in time and space observed soil moisture dataset available. One of the main limitations that ESA CCI SM exhibits is the limited depth at which the soil moisture is estimated (limited to approximately 5cm of soil). In this work we use the ESA CCI SM data to estimate the Soil Water Index (SWI) at the global scale, which can serve as a soil moisture approximation for different depths. The SWI is a simple index that simulates the infiltration process. It utilizes an infiltration parameter T, which is related to the hydraulic characteristics. In this work, the T parameter is calibrated and validated at point scale based on soil moisture measurements of the International Soil Moisture Network (ISMN) and the FluxNet2015 (Tier 1) datasets. The regionalization of the T parameter at global scale is performed by linking T to physical soil descriptors using multilinear regression. Physical soil descriptors were obtained from the Soil Grids 250m dataset, i.e. bulk density, sand/silt/clay fractions, soil organic carbon and coarse fragments. The result of this operation is an SWI dataset for a series of different depths between 0 and 1m. This dataset can be used for the systematic evaluation of global hydrological models on their ability to simulate the soil water.</p>

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