Sustainable land management (SLM) is widely recognized as the key to reducing rates of land degradation, and preventing desertification. Many efforts have been made worldwide by various stakeholders to adopt and/or develop various SLM practices. Nevertheless, a comprehensive review on the spatial distribution, prospects, and challenges of SLM practices and research is lacking. To address this gap, we gathered information from a global SLM database provided by the World Overview of Conservation Approaches and Technologies (WOCAT) and two bibliographic databases of academic research. Over 1900 SLM practices and 1181 academic research papers from 129 and 90 countries were compiled and analyzed. Relatively better SLM dissemination was observed in dry subhumid countries and countries with medium scores on the Human Development Index (HDI), whereas dissemination and research were both lower in humid countries with low HDI values. Cropland was the main land use type targeted in both dissemination and research; degradation caused by water erosion and mitigation aimed at water erosion were also the main focus areas. Other dominant land use types (e.g., grazing) and SLM purposes (e.g., economic benefits) have received relatively less research attention compared to their dissemination. Overall, over 75 % of the 60 countries experiencing high soil erosion rates (>10 t ha^-1 yr^-1) also have low HDI scores, as well as poor SLM dissemination and research implying the limited evidence-based SLM dissemination in these countries. The limitation of research evidence can be addressed in the short term through integrating existing scientific research and SLM databases by adopting the proposed Research Evidence for SLM framework. There is, however, a great need for additional detailed studies of country-specific SLM challenges and prospects to create appropriate evidence-based SLM dissemination strategies to achieve multiple SLM benefits.

Gully erosion is one of the most extreme land degradation processes that exhibit spatial and temporal variation depending on topography, soil, climate, and land use and management characteristics. This study investigated the impact of changes in rainfall, land use/land cover (LULC), and land use management (LUM) practices on gully erosion in two midland watersheds (treated Kecha and untreated Laguna) in the Upper Blue Nile basin of Ethiopia by using the LANDPLANER model in combination with intensive field measurements and remote sensing products. We simulated gully erosion under past (in 2005), present (in 2021), and three potential future curve number conditions, each time under four rainfall scenarios (10, 30, 60, and 100 mm) using the dynamic erosion index (e), static topographic (esp), and erosion channel (esp_channel) thresholds. Density plot analyses showed that gullies frequently occur in low-lying gentle slope areas with relatively higher curve number values. The best predictions of gullies identified through true positive rates (TPR) and true negative rates (TNR) were achieved considering the static esp_channel > 1 for Kecha (TPR = 0.667 and TNR = 0.544) and the dynamic e > 0.1 for 60 mm of rainfall in Laguna (TPR = 0.769 and TNR = 0.516). Despite the 10 mm rainfall having negligible erosion-triggering potential in both watersheds, the 60 and 100 mm rainfall scenarios were 4–5 and 10–17 times, respectively, higher than the 30 mm rainfall scenario. While the LULC change in the untreated Laguna watershed increased the impact of rainfall on gully initiation by only 0–2% between 2005 and 2021, the combination of LULC and LUM significantly reduced the impact of rainfall in the treated Kecha watershed by 64–79%. Similarly, the gully initiation area in Kecha was reduced by 28% (from 33% in 2005 to 5% in 2021) due to changes in LULC and LUM practices, whereas Laguna showed little increment by only 1% (from 42% in 2005 to 43% in 2021) due to LULC change. In addition, the future predicted alternative land use planning options showed that gully initiation areas in Laguna could be reduced by 1% with only LULC conversion; 39% when only LUM practices were implemented; and 37% when both were combined. These results indicate that LUM practices outweigh the impact of LULC on gully erosion in the studied paired watersheds. Overall, LANDPLANER successfully simulated the spatio-temporal variation of gully erosion with scenario-based analyses and hence can be used to predict gullies in the study area and other data-scarce regions with similar agro-ecological settings.

This study evaluated the accuracy of two new generation satellite rainfall estimates (SREs): Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) and Integrated Multi-satellite Retrieval for GPM (IMERG) over Bolivia’s complex terrain. These SREs were compared against rainfall data from rain gauge measurements on a point-to-pixel basis for the period 2002–2020. The evaluation was performed across three regions with distinct topographical settings: Altiplano (Highland), Valles (Midland), and Llanos (Lowland). IMERG exhibited better accuracy in rainfall detection than CHIRPS, with the highest rainfall detection skills observed in the Highland region. However, IMERG’s higher rainfall detection skill was countered by its higher false alarm ratio. CHIRPS provided a more accurate estimation of rainfall amounts across the three regions, exhibiting low random errors and relative biases below 10%. IMERG tended to overestimate rainfall amounts, with marked overestimation by up to 75% in the Highland region. Bias decomposition revealed that IMERG’s high false rainfall bias contributed to its marked overestimation of rainfall. We showcase the utility of long-term CHIRPS data to investigate spatio-temporal rainfall patterns and meteorological drought occurrence in Bolivia. The findings of this study offer valuable insights for choosing appropriate SREs for informed decision-making, particularly in regions of complex topography lacking reliable gauge data.