Uncertainty assessment of GlobalSoilMap soil available water capacity products: A French case study

Dobarco, Mercedes Ŕomàn; Bourennane, Hocine; Arrouays, Dominique; Saby, Nicolas; Isabelle, Cousin; Martín, Manuel

doi:10.1016/j.geoderma.2019.02.036

Cited by 53 publications

(18 citation statements)

References 72 publications

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“…The partial results presented in Section 4.2 can then be compared to those of previous studies in similar conditions. The performances delivered for particle size fractions were slightly worse than those provided recently by Román Dobarco et al [36] for all of France (R 2 = 0.27, 0.43, and 0.46 for clay, silt, and sand content, respectively) with, however, the same hierarchy between sand, silt, and clay mapping performances. Vaysse and Lagacherie [11] obtained in the same study area better mapping performances for particle size fractions (between 0.19 and 0.36) but the same poor performances for thickness and coarse fragment, however, with another validation technique (independent validation test instead of cross validation).…”

Section: Sawc Mapping Trajectories Performance Comparisonscontrasting

confidence: 73%

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What is the Best Inference Trajectory for Mapping Soil Functions: An Example of Mapping Soil Available Water Capacity over Languedoc Roussillon (France)

Styc

Lagacherie

2019

Soil Systems

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Extending digital soil mapping to the mapping of soil functions that can support end-user decisions comes to coupling a digital soil mapping procedure and a soil function assessment method. This can be done following various possible inference trajectories following the order with which “combining primary soil properties”, “aggregating soil layers across depths” and “mapping” are executed to provide the targeted output. Eighteen inference trajectories, designed for computing soil available water capacity maps in the Languedoc–Roussillon region (France), were compared with regard to their mapping performances. The best performance (SSMSE = 0.42) was obtained by a trajectory that, before mapping, combined the three first GlobalSoilMap soil layers and computed the available water capacity of each layer. The worst (SSMSE = 0.07) was observed when all the soil layers and soil properties were combined prior to mapping. We explain the observed differences between trajectories by examining the differences in mapping errors and in error propagation between the compared trajectories, which involve both the correlations between the soil properties and between their mapping errors. This paves the way to spatial soil inference systems that could perform an ex ante selection of the best possible inference trajectory for mapping a soil function.

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Section: Sawc Mapping Trajectories Performance Comparisonscontrasting

confidence: 73%

“…However, this evaluation remains incomplete since we did not take into account the error of the PTFs coefficient applied. However, Román Dobarco [36] found that PTF error played a minor role in SAWC mapping error.…”

Section: Level Of Performance In Predicting Sawcmentioning

confidence: 97%

What is the Best Inference Trajectory for Mapping Soil Functions: An Example of Mapping Soil Available Water Capacity over Languedoc Roussillon (France)

Styc

Lagacherie

2019

Soil Systems

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“…AWC depends to a large extent on the bulk density and the silt content. Hence, PTFs that do not include BD typically result in lower AWC values in soils with lower bulk densities, such as those found in the upper soil horizons of forest soils in a study by [56,57]. They also identified the BD and soil texture as major factors explaining spatial variance in AWC for a study area in China.…”

Section: Discussionmentioning

confidence: 95%

A Comparative Investigation of Various Pedotransfer Functions and Their Impact on Hydrological Simulations

Mohajerani

Teschemacher

Casper

2021

Water

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Soil hydraulic properties, which are basically saturated and unsaturated hydraulic conductivity and water retention characteristics, remarkably control the main hydrological processes in catchments. Thus, adequate parameterization of soils is one of the most important tasks in physically based catchment modeling. To estimate these properties, the choice of the PTFs in a hydrological model is often made without taking the runoff characteristics of the catchment into consideration. Therefore, this study introduces a methodology to analyze the sensitivity of a catchment water balance model to the choice of the PTF. To do so, we define 11 scenarios including different combinations of PTFs to estimate the van Genuchten parameters and saturated hydraulic conductivity. We use a calibrated/validated hydrological model (WaSiM-ETH) as a baseline scenario. By altering the underlying PTFs, the effects on the hydraulic properties are quantified. Moreover, we analyze the resulting changes in the spatial/temporal variation of the total runoff and in particular, the runoff components at the catchment outlet. Results reveal that the water distribution in the hydrologic system varies considerably amongst different PTFs, and the water balance components are highly sensitive to the spatial structure of soil hydraulic properties. It is recommended that models be tested by careful consideration of PTFs and orienting the soil parameterization more towards representing a plausible hydrological behavior rather than focusing on matching the calibration data.

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“…The propagation of the uncertainty attached to these input variables and parameters was based on an analytical formulation of

C_{bal}

and

C_{sat}

, taking advantage, among others, of the simplicity of the RothC model and the availability of explicit solutions of Equation (1) (see Supporting Information S3). We applied a first‐order Taylor analysis to calculate the variance of intermediate functions of

C_{bal}

and

C_{sat}

, an approach which was previously applied in soil sciences (Heuvelink et al, 1989; Román Dobarco et al, 2019). Using the Taylor analysis enables one to approximate the variance of any continuously differentiable function of a set of variables or parameters.…”

Section: Methodsmentioning

confidence: 99%

Feasibility of the 4 per 1000 aspirational target for soil carbon: A case study for France

Martín

Dimassi

Dobarco

et al. 2021

Global Change Biology

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Increasing soil organic carbon (SOC) stocks is a promising way to mitigate the increase in atmospheric CO2 concentration. Based on a simple ratio between CO2 anthropogenic emissions and SOC stocks worldwide, it has been suggested that a 0.4% (4 per 1000) yearly increase in SOC stocks could compensate for current anthropogenic CO2 emissions. Here, we used a reverse RothC modelling approach to estimate the amount of C inputs to soils required to sustain current SOC stocks and to increase them by 4‰ per year over a period of 30 years. We assessed the feasibility of this aspirational target first by comparing the required C input with net primary productivity (NPP) flowing to the soil, and second by considering the SOC saturation concept. Calculations were performed for mainland France, at a 1 km grid cell resolution. Results showed that a 30%–40% increase in C inputs to soil would be needed to obtain a 4‰ increase per year over a 30‐year period. 88.4% of cropland areas were considered unsaturated in terms of mineral‐associated SOC, but characterized by a below target C balance, that is, less NPP available than required to reach the 4‰ aspirational target. Conversely, 90.4% of unimproved grasslands were characterized by an above target C balance, that is, enough NPP to reach the 4‰ objective, but 59.1% were also saturated. The situation of improved grasslands and forests was more evenly distributed among the four categories (saturated vs. unsaturated and above vs below target C balance). Future data from soil monitoring networks should enable to validate these results. Overall, our results suggest that, for mainland France, priorities should be (1) to increase NPP returns in cropland soils that are unsaturated and have a below target carbon balance and (2) to preserve SOC stocks in other land uses.

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Uncertainty assessment of GlobalSoilMap soil available water capacity products: A French case study

Cited by 53 publications

References 72 publications

What is the Best Inference Trajectory for Mapping Soil Functions: An Example of Mapping Soil Available Water Capacity over Languedoc Roussillon (France)

What is the Best Inference Trajectory for Mapping Soil Functions: An Example of Mapping Soil Available Water Capacity over Languedoc Roussillon (France)

A Comparative Investigation of Various Pedotransfer Functions and Their Impact on Hydrological Simulations

Feasibility of the 4 per 1000 aspirational target for soil carbon: A case study for France

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