Floodplains representation in Land Surface Model : toward higher resolution

<p>Floodplains are flat regions close to rivers which are temporarily or permanently flooded. When they are next to large streamflow, their flooding is mainly related to the river overflow and, thus, to the precipitation occurring in the upstream regions. Large floodplains are important for the regional water cycle, the hydrological resources, the ecological services they provide and, when they are located in tropical regions, for their interaction with the atmosphere. Large tropical floodplains exist in the Amazon, the Mississippi, the Congo, the Paraguay and the Nile basins. </p><p>On the one hand, floodplains are regions with scarce ground observations which lead to difficulties to assess the accuracy of the satellite products that limits their calibration. One the other hand, the dynamic of the floodplains is usually not integrated in Land Surface Models and even less in Earth System Models although they may be important for land-atmosphere interactions. There is a need to develop numerical schemes in order to be able to represent the impact of the floodplains on the water cycle. These schemes will also allow us to better understand the hydrological dynamics in these regions. </p><p>The Land Surface component of the IPSL Earth System Model, ORCHIDEE (CMIP6 version) includes a river routing scheme with a floodplains scheme at a resolution of 0.5°. This scheme allows the water from the precipitation over the upstream region to flood and evaporate over the floodplains. Recent developments in ORCHIDEE driven by the need for a higher resolution routing scheme, based on sub-grid hydrological units, allowed us to implement a floodplain scheme which improves the representation of the overbank flow and the spatial distribution of ponded water with respect to the CMIP6 version of ORCHIDEE. </p><p>This study focuses on the Pantanal region which is the world’s largest tropical floodplains and is located in the La Plata Basin, in the Upper Paraguay River (South America). ORCHIDEE’s sensitivity to the activation of floodplain schemes has been assessed through simulations performed at various resolutions. These simulations have shown the importance of representing floodplains to simulate the water cycle in the area. Combining these simulations and observations, we estimated the evapotranspiration loss by models when the floodplains scheme is deactivated to 90 mm/year over the Pantanal. The higher resolution scheme shows realistic simulations of the river discharge over the floodplains and is expected to improve the spatial distribution of the flooded area and, thus, the representation of evapotranspiration.</p>

Determinants of tree cover in tropical floodplains

Tree cover differentiates forests from savannas and grasslands. In tropical floodplains, factors differentiating these systems are poorly known, even though floodplains cover 10% of the tropical landmass. Seasonal inundation potentially presents trees with both challenges (soil anoxia) and benefits (moisture and nutrient deposition), the relative importance of which may depend on ecological context, e.g. if floods alleviate water stress more in more arid ecosystems. Here, we use remotely sensed data across 13 large tropical and sub-tropical floodplain ecosystems on five continents to show that climatic water balance (i.e. precipitation—potential evapotranspiration) strongly increases floodplain tree cover in interaction with flooding, fire and topography. As predicted, flooding increases tree cover in more arid floodplains, but decreases tree cover in climatically wetter ones. As in uplands, frequent fire reduced tree cover, particularly in wet regions, but—in contrast with uplands—lower elevation and sandier soils decreased tree cover. Our results suggest that predicting the impacts of changing climate, land use and hydrology on floodplain ecosystems depends on considering climate-disturbance interactions. While outright wetland conversion proceeds globally, additional anthropogenic activities, including alteration of fire frequencies and dam construction, will also shift floodplain tree cover, especially in wet climates.

Methane emissions from floodplains in the Amazon Basin: challenges in developing a process-based model for global applications

Tropical wetlands are estimated to represent about 50% of the natural wetland methane (CH4) emissions and explain a large fraction of the observed CH4 variability on timescales ranging from glacial–interglacial cycles to the currently observed year-to-year variability. Despite their importance, however, tropical wetlands are poorly represented in global models aiming to predict global CH4 emissions. This publication documents a first step in the development of a process-based model of CH4 emissions from tropical floodplains for global applications. For this purpose, the LPX-Bern Dynamic Global Vegetation Model (LPX hereafter) was slightly modified to represent floodplain hydrology, vegetation and associated CH4 emissions. The extent of tropical floodplains was prescribed using output from the spatially explicit hydrology model PCR-GLOBWB. We introduced new plant functional types (PFTs) that explicitly represent floodplain vegetation. The PFT parameterizations were evaluated against available remote-sensing data sets (GLC2000 land cover and MODIS Net Primary Productivity). Simulated CH4 flux densities were evaluated against field observations and regional flux inventories. Simulated CH4 emissions at Amazon Basin scale were compared to model simulations performed in the WETCHIMP intercomparison project. We found that LPX reproduces the average magnitude of observed net CH4 flux densities for the Amazon Basin. However, the model does not reproduce the variability between sites or between years within a site. Unfortunately, site information is too limited to attest or disprove some model features. At the Amazon Basin scale, our results underline the large uncertainty in the magnitude of wetland CH4 emissions. Sensitivity analyses gave insights into the main drivers of floodplain CH4 emission and their associated uncertainties. In particular, uncertainties in floodplain extent (i.e., difference between GLC2000 and PCR-GLOBWB output) modulate the simulated emissions by a factor of about 2. Our best estimates, using PCR-GLOBWB in combination with GLC2000, lead to simulated Amazon-integrated emissions of 44.4 ± 4.8 Tg yr−1. Additionally, the LPX emissions are highly sensitive to vegetation distribution. Two simulations with the same mean PFT cover, but different spatial distributions of grasslands within the basin, modulated emissions by about 20%. Correcting the LPX-simulated NPP using MODIS reduces the Amazon emissions by 11.3%. Finally, due to an intrinsic limitation of LPX to account for seasonality in floodplain extent, the model failed to reproduce the full dynamics in CH4 emissions but we proposed solutions to this issue. The interannual variability (IAV) of the emissions increases by 90% if the IAV in floodplain extent is accounted for, but still remains lower than in most of the WETCHIMP models. While our model includes more mechanisms specific to tropical floodplains, we were unable to reduce the uncertainty in the magnitude of wetland CH4 emissions of the Amazon Basin. Our results helped identify and prioritize directions towards more accurate estimates of tropical CH4 emissions, and they stress the need for more research to constrain floodplain CH4 emissions and their temporal variability, even before including other fundamental mechanisms such as floating macrophytes or lateral water fluxes.

Methane emissions from floodplains in the Amazon Basin: towards a process-based model for global applications

Tropical wetlands are estimated to represent about 50% of the natural wetland emissions and explain a large fraction of the observed CH4 variability on time scales ranging from glacial-interglacial cycles to the currently observed year-to-year variability. Despite their importance, however, tropical wetlands are poorly represented in global models aiming to predict global CH4 emissions. This study documents the first regional-scale, process-based model of CH4 emissions from tropical floodplains. The LPX-Bern Dynamic Global Vegetation Model (LPX hereafter) was modified to represent floodplain hydrology, vegetation and associated CH4 emissions. The extent of tropical floodplains was prescribed using output from the spatially-explicit hydrology model PCR-GLOBWB. We introduced new Plant Functional Types (PFTs) that explicitly represent floodplain vegetation. The PFT parameterizations were evaluated against available remote sensing datasets (GLC2000 land cover and MODIS Net Primary Productivity). Simulated CH4 flux densities were evaluated against field observations and regional flux inventories. Simulated CH4 emissions at Amazon Basin scale were compared to model simulations performed in the WETCHIMP intercomparison project. We found that LPX simulated CH4 flux densities are in reasonable agreement with observations at the field scale but with a~tendency to overestimate the flux observed at specific sites. In addition, the model did not reproduce between-site variations or between-year variations within a site. Unfortunately, site informations are too limited to attest or disprove some model features. At the Amazon Basin scale, our results underline the large uncertainty in the magnitude of wetland CH4 emissions. In particular, uncertainties in floodplain extent (i.e., difference between GLC2000 and PCR-GLOBWB output) modulate the simulated emissions by a factor of about 2. Our best estimates, using PCR-GLOBWB in combination with GLC2000, lead to simulated Amazon-integrated emissions of 44.4 ± 4.8 Tg yr−1. Additionally, the LPX emissions are highly sensitive to vegetation distribution. Two simulations with the same mean PFT cover, but different spatial distributions of grasslands within the basin modulated emissions by about 20%. Correcting the LPX simulated NPP using MODIS reduces the Amazon emissions by 11.3%. Finally, due to an intrinsic limitation of LPX to account for seasonality in floodplain extent, the model failed to reproduce the seasonality in CH4 emissions. The Inter Annual Variability (IAV) of the emissions increases by 90% if the IAV in floodplain extent is account for, but still remains lower than in most of WETCHIMP models. While our model includes more mechanisms specific to tropical floodplains, we were unable to reduce the uncertainty in the magnitude of wetland CH4 emissions of the Amazon Basin. Our results stress the need for more research to constrain floodplain CH4 emissions and their temporal variability.