Land use without adequate soil erosion control measures is continuously increasing the risk of soil erosion by water mainly in developing tropical countries. These countries are prone to environmental disturbance due to high population growth and high rainfall intensity. The aim of this study is to assess the state of soil erosion by water in Uganda at national and district levels, for various land cover and land use (LCLU) types, in protected areas as well to predict the impact of support practices on soil loss reduction. Predictions obtained using the Revised Universal Soil Loss Equation (RUSLE) model indicated that the mean rate of soil loss risk in Uganda’s erosion‐prone lands was 3.2 t∙ha−1∙y−1, resulting in a total annual soil loss of about 62 million tons in 2014. About 39% of the country’s erosion‐prone lands were comprised of unsustainable mean soil loss rates >1 t∙ha−1∙y−1. Out of 112 districts in Uganda, 66 districts were found to have unsustainable estimated soil loss rates >1 t∙ha−1∙y−1. Six districts in Uganda were found to have mean annual soil loss rates of >10 t∙ha−1∙y−1: Bududa (46.3 t∙ha−1∙y−1), Kasese (37.5 t∙ha−1∙y−1), Bundibugyo (28.9 t∙ha−1∙y−1), Bulambuli (20.9 t∙ha−1∙y−1), Sironko (14.6 t∙ha−1∙y−1) and Kotido (12.5 t∙ha−1∙y−1). Among the LCLU types, the highest soil loss rates of 11 t∙ha−1∙y−1 and 10.6 t∙ha−1∙y−1 were found in moderate natural forest and dense natural forest, respectively, mainly due to their locations in highland areas characterized by steep slopes ranging between 16% to 21% and their high rainfall intensity, ranging from 1255 mm∙y−1 to 1292 mm∙y−1. Only five protected areas in Uganda were found to have high mean estimated mean soil loss rates >10 t∙ha−1∙y−1: Rwenzori Mountains (142.94 t∙ha−1∙y−1), Mount Elgon (33.81 t∙ha−1∙y−1), Bokora corridor (12.13 t∙ha−1∙y−1), Matheniko (10.39 t∙ha−1∙y−1), and Nangolibwel (10.33 t∙ha−1∙y−1). To manage soil erosion in Uganda’s protected areas, there is an urgent need to control wildfires and human‐induced disturbances such as timber harvesting and soil compaction from domestic animals. Our study analysis revealed that well‐established terraces and strip‐cropping could significantly reduce soil loss rates in Uganda’s croplands by 80% (from 1.5 t∙ha−1∙y−1 to 0.3 t∙ha−1∙y−1) and by 47% (from 1.5 t∙ha−1∙y−1 to 0.8 t∙ha−1∙y−1), respectively, well below the sustainable soil erosion tolerance rate (1 t∙ha−1∙y−1) for land and water conservation.

Deforestation and natural grassland conversion to agricultural land use constitute a major threat to soil and water conservation. This study aimed at assessing the status of land cover and land use (LCLU) in the Lake Kivu basin, and its related impacts in terms of soil erosion by water using the Universal Soil Erosion Equation (USLE) model. The results indicated that the Lake Kivu basin is exposed to soil erosion risk with a mean annual rate of 30 t·ha⁻¹, and only 33% of the total non-water area is associated with a tolerable soil loss (≤10 t·ha⁻¹·year⁻¹). Due to both natural factors (abundant tropical precipitation and steep slopes) and anthropogenic activities without prior appropriate conservation practices, all land-use types—namely settlement, cropland, forestland, and grassland—are exposed to a severe mean erosion rate of 41 t·ha⁻¹·year⁻¹, 31 t·ha⁻¹·year⁻¹, 28 t·ha⁻¹·year⁻¹, and 20 t·ha⁻¹·year⁻¹, respectively. The cropland that occupied 74% of the non-water area in 2015 was the major contributor (75%) to the total annual soil loss in the Lake Kivu basin. This study showed that conservation practices in the cropland cells would result in a mean erosion rate of 7 t·ha⁻¹·year⁻¹, 18 t·ha⁻¹·year⁻¹, and 35 t·ha⁻¹·year⁻¹ for terracing, strip-cropping, and contouring, respectively. The adoption of terracing would be the best conservation practice, among others, that could reduce soil erosion in cropland areas up to about 23%. The erosion risk minimization in forests and grasslands implies an increase in overstorey canopy and understorey vegetation, and control of human activities such as fires, mining, soil compaction from domestic animals grazing, and so on. Soil erosion control in settled areas suggests, among other things, the revegetation of construction sites, establishment of outlet channels, rainfall water harvesting systems, and pervious paving block with grass.

With high resolution and wide coverage, satellite precipitation products like Global Precipitation Measurement (GPM) could support hydrological/ecological research in the Tianshan Mountains, where the spatial heterogeneity of precipitation is high, but where rain gauges are sparse and unevenly distributed. Based on observations from 46 stations from 2014–2015, we evaluated the accuracies of three satellite precipitation products: GPM, Tropical Rainfall Measurement Mission (TRMM) 3B42, and the Climate Prediction Center morphing technique (CMORPH), in the Tianshan Mountains. The satellite estimates significantly correlated with the observations. They showed a northwest–southeast precipitation gradient that reflected the effects of large-scale circulations and a characteristic seasonal precipitation gradient that matched the observed regional precipitation pattern. With the highest correlation (R = 0.51), the lowest error (RMSE = 0.85 mm/day), and the smallest bias (1.27%), GPM outperformed TRMM and CMORPH in estimating daily precipitation. It performed the best at both regional and sub-regional scales and in low and mid-elevations. GPM had relatively balanced performances across all seasons, while CMORPH had significant biases in summer (46.43%) and winter (−22.93%), and TRMM performed extremely poorly in spring (R = 0.31; RMSE = 1.15 mm/day; bias = −20.29%). GPM also performed the best in detecting precipitation events, especially light and moderate precipitation, possibly due to the newly added Ka-band and high-frequency microwave channels. It successfully detected 62.09% of the precipitation events that exceeded 0.5 mm/day. However, its ability to estimate severe rainfall has not been improved as expected. Like other satellite products, GPM had the highest RMSE and bias in summer, suggesting limitations in its way of representing small-scale precipitation systems and isolated deep convection. It also underestimated the precipitation in high-elevation regions by 16%, suggesting the difficulties of capturing the orographic enhancement of rainfall associated with cap clouds and feeder–seeder cloud interactions over ridges. These findings suggest that GPM may outperform its predecessors in the mid-/high-latitude dryland, but not the tropical mountainous areas. With the advantage of high resolution and improved accuracy, the GPM creates new opportunities for understanding the precipitation pattern across the complex terrains of the Tianshan Mountains, and it could improve hydrological/ecological research in the area.

Stormwater runoff poses serious environmental problems and public health issues in Rwanda, a tropical country that is increasingly suffering from severe floods, landslides, soil erosion and water pollution. Using the WetSpa Extension model, this study assessed the changes in rainfall runoff depth in Rwanda from 1990 to 2016 in response to precipitation and land use changes. Our results show that Rwanda has experienced a significant conversion of natural forest and grassland to cropland and built-up areas. During the period 1990–2016, 7090.02 km² (64.5%) and 1715.26 km² (32.1%) of forest and grassland covers were lost, respectively, while the cropland and built-up areas increased by 135.3% (8503.75 km²) and 304.3% (355.02 km²), respectively. According to our estimates, the land use change effect resulted in a national mean runoff depth increase of 2.33 mm/year (0.38%). Although precipitation change affected the inter-annual fluctuation of runoff, the long-term trend of runoff was dominated by land use change. The top five districts that experienced the annual runoff depth increase (all >3.8 mm/year) are Rubavu, Nyabihu, Ngororero, Gakenke, and Musanze. Their annual runoff depths increased at a rate of >3.8 mm/year during the past 27 years, due to severe deforestation (ranging from 62% to 85%) and cropland expansion (ranging from 123% to 293%). These areas require high priority in runoff control using terracing in croplands and rainwater harvesting systems such as dam/reservoirs, percolation tanks, storage tanks, etc. The wet season runoff was three times higher than the dry season runoff in Rwanda; appropriate rainwater management and reservation could provide valuable irrigation water for the dry season or drought years (late rainfall onsets or early rainfall cessations). It was estimated that a reservation of 30.5% (3.99 km³) of the runoff in the wet season could meet the cropland irrigation water gap during the dry season in 2016.

Deserts are one of the ecosystems most sensitive to global climate change. However, there are few studies examining how changing abiotic and biotic factors under climate change will affect plant species diversity in the temperate deserts of Asia. This study aimed to: (i) characterize species distributions and diversity patterns in an Asian temperate desert; and (ii) to quantify the effects of spatial and environment variables on plant species diversity. We surveyed 61 sites to examine the relationship between plant species diversity and several spatial/environmental variables in the Gurbantunggut Desert. Spatial and environmental variables were used to predict plant species diversity in separate multiple regression and ordination models. Variation in species responses to spatial and environmental conditions was partitioned by combining these variables in a redundancy analysis (RDA) and by creating multivariate regression trees (MRT). We found 92 plant species across the 61 sites. Elevation and geographic location were the dominant environmental factors underlying variation in site species richness. A RDA indicated that 93% of the variance in the species–environment relationships was explained by altitude, latitude, longitude, precipitation and slope position. Precipitation and topographic heterogeneity, through their effects on water availability, were more important than soil chemistry in determining the distribution of species. MRT analyses categorized communities into four groups based on latitude, soil pH and elevation, explaining 42.3% of the standardized species variance. Soil pH strongly influenced community composition within homogeneous geographic areas. Our findings suggest that precipitation and topographic heterogeneity, rather than edaphic heterogeneity, are more closely correlated to the number of species and their distributions in the temperate desert.