A reexamination of the dry gets drier and wet gets wetter paradigm over global land: insight from terrestrial water storage changes

The “dry gets drier and wet gets wetter” (DDWW) paradigm has been widely used to summarize the expected trends of the global hydrologic cycle under climate change. However, the paradigm is challenged over land due to different measures and datasets, and is still unexplored from the perspective of terrestrial water storage anomaly (TWSA). Considering the essential role of TWSA in wetting and drying of the land surface, here we built upon a large ensemble of TWSA datasets including satellite-based products, global hydrological models, land surface models, and global climate models to evaluate the DDWW hypothesis during the historical (1985–2014) and future (2071–2100) periods under various scenarios. We find that 27.1 % of global land confirms the DDWW paradigm, while 22.4 % of the area shows the opposite pattern during the historical period. In the future, the DDWW paradigm is still challenged with the percentage supporting the pattern lower than 20 %, and both the DDWW-validated and DDWW-opposed proportion increase along with the intensification of emission scenarios. Our findings will provide insights and implications for global wetting and drying trends from the perspective of TWSA under climate change.

Regional Sampling of Forest Canopy Covers Using UAV Visible Stereoscopic Imagery for Assessment of Satellite-Based Products in Northeast China

Canopy cover is an important parameter affecting forest succession, carbon fluxes, and wildlife habitats. Several global maps with different spatial resolutions have been produced based on satellite images, but facing the deficiency of reliable references for accuracy assessments. The rapid development of unmanned aerial vehicle (UAV) equipped with consumer-grade camera enables the acquisition of high-resolution images at low cost, which provides the research community a promising tool to collect reference data. However, it is still a challenge to distinguish tree crowns and understory green vegetation based on the UAV-based true color images (RGB) due to the limited spectral information. In addition, the canopy height model (CHM) derived from photogrammetric point clouds has also been used to identify tree crowns but limited by the unavailability of understory terrain elevations. This study proposed a simple method to distinguish tree crowns and understories based on UAV visible images, which was referred to as BAMOS for convenience. The central idea of the BAMOS was the synergy of spectral information from digital orthophoto map (DOM) and structural information from digital surface model (DSM). Samples of canopy covers were produced by applying the BAMOS method on the UAV images collected at 77 sites with a size of about 1.0 km2 across Daxing’anling forested area in northeast of China. Results showed that canopy cover extracted by the BAMOS method was highly correlated to visually interpreted ones with correlation coefficient (r) of 0.96 and root mean square error (RMSE) of 5.7%. Then, the UAV-based canopy covers served as references for assessment of satellite-based maps, including MOD44B Version 6 Vegetation Continuous Fields (MODIS VCF), maps developed by the Global Land Cover Facility (GLCF) and by the Global Land Analysis and Discovery laboratory (GLAD). Results showed that both GLAD and GLCF canopy covers could capture the dominant spatial patterns, but GLAD canopy cover tended to miss scattered trees in highly heterogeneous areas, and GLCF failed to capture non-tree areas. Most important of all, obvious underestimations with RMSE about 20% were easily observed in all satellite-based maps, although the temporal inconsistency with references might have some contributions.

Central Asia performance review in land governance indices and assessment frameworks

Academic scholarship captures different land governance dimensions while focusing mainly on agrarian, legal, and economic aspects. However, little to no attention is paid to land governance consideration through public policy lenses. In particular, this holds for Central Asian (CA) countries where there is a noticeable lack of academic works on land governance effectiveness and anti-corruption strategies in the land sector. This review paper analyzes the question of how Central Asian countries are presented in land governance indices and assessment frameworks such as the World Bank’s Land Governance Assessment Framework (LGAF), Global Property Rights Index (Prindex), Global Land Governance Index (LANDex), and The Open Data Barometer. The paper uses the integrative review of academic works and the author’s empirical data on Central Asian performance in land governance indices and assessment programs. The findings revealed that while the Prindex results for the region are promising, the underperformance and lack of active engagement of Central Asian countries in the Open Data Barometer, LANDex, and LGAF are still visible. This fact could be explained by various reasons, including the lack of institutional and legal capacities in CA countries and the limitation in methodology and data collection techniques observed in present land indices. Considering that the subject is understudied, it is anticipated that this review paper will give both scholars and practitioners from the region and abroad the impetus to improve Central Asian performance in global land governance indices and assessment programs.

Global land use extent and dispersion within natural land cover using Landsat data

The conversion of natural land cover into human-dominated land use systems has significant impacts on the environment. Global mapping and monitoring of human-dominated land use extent via satellites provides an empirical basis for assessing land use pressures. Here, we present a novel 2019 global land cover, land use, and ecozone map derived from Landsat satellite imagery and topographical data using derived image feature spaces and algorithms suited per theme. From the map, we estimate the spatial extent and dispersion of land use disaggregated by climate domain and ecozone, where dispersion is the mean distance of land use to all land within a subregion. We find that percent of area under land use and distance to land use follow a power law that depicts an increasingly random spatial distribution of land use as it extends across lands of comparable development potential. For highly developed climate/ecozones, such as temperate and sub-tropical terra firma vegetation on low slopes, area under land use is contiguous and remnant natural land cover have low areal extent and high fragmentation. The tropics generally have the greatest potential for land use expansion, particularly in South America. An exception is Asian humid tropical terra firma vegetated lowland, which has land use intensities comparable to that of temperate breadbaskets such as the United States’ corn belt. Wetland extent is inversely proportional to land use extent within climate domains, indicating historical wetland loss for temperate, sub-tropical, and dry tropical biomes. Results highlight the need for planning efforts to preserve natural systems and associated ecosystem services. The demonstrated methods will be implemented operationally in quantifying global land change, enabling a monitoring framework for systematic assessments of the appropriation and restoration of natural land cover.

A harmonized global land evaporation dataset from model-based products covering 1980–2017

Land evaporation (ET) plays a crucial role in the hydrological and energy cycle. However, the widely used model-based products, even though helpful, are still subject to great uncertainties due to imperfect model parameterizations and forcing data. The lack of available observed data has further complicated estimation. Hence, there is an urgency to define the global proxy land ET with lower uncertainties for climate-induced hydrology and energy change. This study has combined three existing model-based products – the fifth-generation ECMWF reanalysis (ERA5), Global Land Data Assimilation System Version 2 (GLDAS2), and the second Modern-Era Retrospective analysis for Research and Applications (MERRA-2) – to obtain a single framework of a long-term (1980–2017) daily ET product at a spatial resolution of 0.25∘. Here, we use the reliability ensemble averaging (REA) method, which minimizes errors using reference data, to combine the three products over regions with high consistencies between the products using the coefficient of variation (CV). The Global Land Evaporation Amsterdam Model Version 3.2a (GLEAM3.2a) and flux tower observation data were selected as the data for reference and evaluation, respectively. The results showed that the merged product performed well over a range of vegetation cover scenarios. The merged product also captured the trend of land evaporation over different areas well, showing the significant decreasing trend in the Amazon Plain in South America and Congo Basin in central Africa and the increasing trend in the east of North America, west of Europe, south of Asia and north of Oceania. In addition to demonstrating a good performance, the REA method also successfully converged the models based on the reliability of the inputs. The resulting REA data can be accessed at https://doi.org/10.5281/zenodo.4595941 (Lu et al., 2021).

Análisis de la precipitación y la evaporación en el Orinoco colombiano según los modelos climáticos regionales del experimento CORDEX-CORE

Con el fin de representar la precipitación y evaporación total mensual en una cuenca hidrográfica del Orinoco colombiano, este trabajo evaluó la capacidad de los modelos climáticos regionales incluidos en el Experimento regional coordinado de reducción de escala (CORDEX-CORE). Para ello, complementariamente, se incluyeron datos de precipitación y evaporación total de fuentes como Climate Hazards Center InfraRed Precipitation with Station data (CHIRPS), el reanálisis atmosférico (ERA5), Global Precipitation Climatology Center (GPCC) y Global Land Evaporation Amsterdam Model (GLEAM). Las comparaciones entre los ensambles de los modelos y las observaciones se hicieron utilizando métodos gráficos y métodos cuantitativos, entre ellos: diagramas de cajas, porcentajes de sesgo, eficiencia de Nash-Sutcliffe, entre otros. Los resultados evidencian que los valores promedio de precipitación están adecuadamente representados, en términos de su temporalidad y magnitud, por el ensamble del modelo RegCM, mientras que los valores promedio de evaporación total están mejor representados por el ensamble del modelo REMO en términos de la temporalidad, más no en su magnitud. Por otra parte, las estimaciones de caudal de largo plazo evidencian que los valores de evaporación total proporcionados por los modelos permiten una adecuada estimación del caudal promedio de largo plazo, pero no la adecuada estimación del ciclo anual de caudales. Este trabajo es pionero en la evaluación de los datos de precipitación y evaporación total mensual suministrados por CORDEX-CORE en el Orinoco colombiano, sienta precedentes para la incorporación de datos de modelos regionales para fines hidrológicos en zonas poco instrumentadas del país, y es el primer paso hacia la evaluación de escenarios regionalizados de cambio climático.