Multi-source global wetland maps combining surface water imagery and groundwater constraints

Abstract

Many maps of open water and wetlands have been developed based on three main methods: (i) compiling national/regional wetland surveys; (ii) identifying inundated areas via satellite imagery; and (iii) delineating wetlands as shallow water table areas based on groundwater modelling. However, the resulting global wetland extents vary from 3% to 10 21% of the land surface area because of inconsistencies in wetland definitions and limitations in observation or modelling systems. To reconcile these differences, we propose composite wetland (CW) maps, combining two classes of wetlands: (1) regularly flooded wetlands (RFW) obtained by overlapping selected open-water and inundation datasets; and (2) groundwaterdriven wetlands (GDW) derived from groundwater modelling (either direct or simplified using several variants of the topographic index). Wetlands are statically defined as areas with persistent near-saturated soil surfaces because of regular 15 flooding or shallow groundwater. Seven CW maps were generated at the 15 arc-sec resolution (ca 500 m at the Equator) using geographic information system (GIS) tools and by combining one RFW and different GDW maps. To validate this approach, these CW maps were compared with existing wetland datasets at the global and regional scales. The spatial patterns were decently captured, but the wetland extents were difficult to assess against the dispersion of the validation datasets. Compared with the only regional dataset encompassing both GDWs and RFWs, over France, the CW maps performed well and better 20 than all other considered global wetland datasets. Two CW maps, showing the best overall match with the available evaluation datasets, were eventually selected. These maps provided global wetland extents of 27.5 and 29 million km², i.e., 21.1% and 21.6% of global land area, which are among the highest values in the literature and in line with recent estimates also recognizing the contribution of GDWs. This wetland class covers 15% of the global land area compared with 9.7% for RFW (with an overlap of ca. 3.4%), including wetlands under canopy/cloud cover, leading to high wetland densities in the tropics and small 25 scattered wetlands that cover less than 5% of land but are highly important for hydrological and ecological functioning in temperate to arid areas. By distinguishing the RFWs and GDWs based globally on uniform principles, the proposed dataset might be useful for large-scale land surface modelling (hydrological, ecological and biogeochemical modelling) and environmental planning. The dataset consisting of the two selected CW maps and the contributing GDW and RFW maps is available from PANGAEA at https://doi.pangaea.de/10.1594/PANGAEA.892657 30 Earth Syst. Sci. Data Discuss., https://doi.

Influence of Hillslope Flow on Hydroclimatic Evolution Under Climate Change

“…The above changes in the regional hydrology are consistent with the results obtained by Tootchi (2019) based on offline simulations in the Seine River basin (Northern France, temperate humid climate). This author also illustrates the sensitivity of the hillslope parametrization to soil depth and the exchange factor E F (Equation 1), and to the extent of the lowland fraction: when the latter increases from 5% to 75% in the Seine River basin, annual mean SM and ET increase by 21% and 6%, respectively, while annual mean R decrease by 24%.…”

“…The water table is practically defined as the top of the uppermost saturated soil layer when starting from the impermeable soil bottom. If the whole soil column becomes saturated, the excess water will add to surface runoff and flow into the river (Tootchi, 2019). The soil depth is kept at 2 m in the lowland fraction, and it is discretized into 22 layers (with increasing height from 1 mm in the top layer to 12.5 mm in the eighth layer and all layers below) to accurately simulate the water table depth and the overlying soil moisture gradients and resulting water fluxes according to the Richards equation (Campoy et al., 2013).…”

“…Baseflow Q base (mm/s) to the streams comes from the lowland fraction. Following Darcy's law, it originates from the saturated layers below the water table, and is given by a solution of the long‐term linearized Boussinesq equation at the catchment scale (Brutsaert, 2005; Tootchi, 2019) in equivalent water depth: $$${Q}_{\mathit{base}}=\sum\limits _{i=wtl}^{22}{q}_{i}={E}_{F}\ast \frac{{\pi }^{2}}{4}\ast \frac{{\Delta}h}{B}\ast \frac{1}{B}\ast \sum\limits _{i=wtl}^{22}{\Delta}{z}_{i}\ast {K}_{i}$$$ where E F [–] is the exchange factor multiplied by $$\frac{{\pi }^{2}}{4}$$, which accounts for variations of hydraulic conductivity along horizontal direction, anisotropy and riverbed clogging, based on water table shape (Brutsaert, 2005). The term $$\frac{{\Delta}h}{B}$$ corresponds to the mean gradient along hillslopes in the lowland fraction.…”

Supplementary material to "Modelling northern peatlands area and carbon dynamics since the Holocene with the ORCHIDEE-PEAT land surface model (SVN r5488)"

“…As demonstrated by Stocker et al (2014), the choice of m and determines the parameter set ( , , , ). In contrast to their study, in which m and were considered as tunable but globally uniform parameters, we tested different combinations of m (m= (5,6,7,8,9,10,11,12,13,14,15)) and ( = (4,5,6,7,8,9,10,11,12)) at each grid cell and select the combination that matches with the CW-WTD wetlands map (Tootchi et al, 2018).…”