Assessment of current and future land use/cover changes in soil erosion in the Rio da Prata basin (Brazil)

Towards a more comprehensive scenario analysis: Response of soil erosion to future land use and climate change in the Central Yunnan Urban Agglomeration, China

Rapid urbanization and climate change exacerbate soil erosion globally, threatening ecosystem services and sustainable development. However, current predictive studies on future soil erosion often lack comprehensive consideration of the interactions between land use and climate change. This study proposed a comprehensive scenario analysis framework that integrated four Shared Socioeconomic Pathways (SSPs) from CMIP6 with four bespoke land-use scenarios (Inertial Development (IDS), Urban Development Priority (UDPS), Ecological Protection Priority (EPPS), and Farmland Protection Priority (FPPS)) to create 16 future scenarios, allowing for a more nuanced understanding of potential soil erosion trajectories. The results indicated that (1) compared to the baseline period (2000-2020), future soil erosion in the Central Yunnan Urban Agglomeration (CYUA) would improve, albeit with significant differences among the scenarios. The most notable improvement was under EPPS + SSP1-2.6 scenario (ScC1). (2) The lower Jinsha, upper Nanpan, and Red river basins were high-risk areas for soil erosion in the CYUA, each dominated by different factors, necessitating differentiated soil erosion control measures. (3) Land-use and climate change jointly influenced the direction of erosion development, with the lightest erosion occurring under the EPPS and heaviest erosion occurring under the FPPS. The largest decrease in erosion occurs under SSP1-2.6, whereas the smallest decrease occurs under SSP5-8.5. (4) Climate change had a more significant impact on soil erosion than land-use change, with the reduction rates of the soil erosion modulus and area between different climate change scenarios relative to the past 20 years being 9% and 3.77%, respectively, approximately eight and four times the magnitude of change under different land-use scenarios. This study recommends reducing carbon emissions, enhancing vegetation cover, and controlling slope land development to effectively mitigate the soil erosion risk in CYUA and promote regional sustainable development. The proposed comprehensive scenario analysis method provides new insights into future global small-scale regional predictions.

Dynamics of Land use and Land cover in the Belitung Island, Indonesia

Belitung Island, situated in the Southeast Asian tin belt, experiences substantial transformations in land use and land cover (LULC) driven by mining activities, impacting both local economic growth and the ecosystem. This study aims to elucidate the dynamic LULC changes on Belitung Island and evaluate deforestation trends. LULC data spanning from 1990 to 2020 were acquired from The Indonesian Ministry of Environment and Forestry (KLHK), employing supervised classification of satellite imageries. The dataset demonstrated an overall accuracy ranging from 0.79 to 0.92 and was reclassified into six types based on the Intergovernmental Panel on Climate Change or IPCC's classes, encompassing forest, cropland, grassland, other land, settlements, and wetlands. Our research unveiled a notable reduction of over 25 % in forest cover within the past 30 years. Notably, 2020 exhibited instances of reforestation, which subsequently transformed into cropland (0.57 %), grassland (0.32 %), and other lands (0.39 %). Belitung Island grapples with challenges related to sustainable development, environmental conservation, and food security. Forest Landscape Restoration (FLR) emerges as a potential strategy to address some of the socioeconomic and ecological issues.

CA-Markov prediction modeling for the assessment of land use/land cover change in two sub-basins of the Tocantins-Araguaia River Basin

Due to the anthropogenic pressures of expansion areas for livestock and agricultural production in the Brazilian Cerrado, it is of paramount importance to understand the dynamics of land use/land cover (LULC) changes in this region. Thus, we investigated LULC changes in two sub-basins of the Tocantins-Araguaia River basin from 1997 to 2015 and consequently projected future changes for the timespan between 2030 and 2050. The Formoso sub-basin experienced significant expansion of agricultural and pasture areas, whereas the Sono sub-basin limited farmland expansion (more stable native vegetation) due to substantial protected areas, trends that were also observed for future projections (2030 and 2050). Pastureland in the Formoso sub-basin increased by 5.8%, while the Sono sub-basin saw significant gains in cultivated land, according to change detection analyses during the 1997-2015 period. High stability probabilities of no change (> 70%) for grassland areas in the Sono River sub-basin and pasturelands in the Formoso River sub-basin were computed. The CA-Markov model demonstrated a high consistency level with actual LULC classes for both sub-basins, as indicated by an overall Kappa coefficient above 0.8. Future projections for 2030 and 2050 show a substantial expansion of agriculture and pasture in both sub-basins, driven by specific factors such as soil organic carbon stocks, distance from rural settlements, and proximity to rivers. Short- and mid-term simulations indicate substantial expansion of agriculture and pasture in both basins, with potential adverse impacts on water erosion. Consequently, developing policies for soil management and sustainable land use planning is essential for agroecosystem sustainability, promoting a balanced approach to economic development while addressing climate change and anthropogenic challenges.

Multi-datasets to monitor and assess meteorological and hydrological droughts in a typical basin of the Brazilian semiarid region

This study analyzed the meteorological and hydrological droughts in a typical basin of the Brazilian semiarid region from 1994 to 2016. In recent decades, this region has faced prolonged and severe droughts, leading to marked reductions in agricultural productivity and significant challenges to food security and water availability. The datasets employed included a digital elevation model, land use and cover data, soil characteristics, climatic data (temperature, wind speed, solar radiation, humidity, and precipitation), runoff data, images from the MODIS/TERRA and AQUA sensors (MOD09A1 and MODY09A1 products), and soil water content. A variety of methods and products were used to study these droughts: the meteorological drought was analyzed using the Standardized Precipitation Index (SPI) derived from observed precipitation data, while the hydrological drought was assessed using the Standardized Soil Index (SSI), the Nonparametric Multivariate Standardized Drought Index (NMSDI), and the Parametric Multivariate Standardized Drought Index (PMSDI). These indices were determined using water balance components, including streamflow and soil water content, from the Soil Water Assessment Tool (SWAT) model, and evapotranspiration data from the Surface Energy Balance Algorithm for Land (SEBAL). The findings indicate that the methodology effectively identified variations in water dynamics and drought periods in a headwater basin within Brazil's semiarid region, suggesting potential applicability in other semiarid areas. This study provides essential insights for water resource management and resilience building in the face of adverse climatic events, offering a valuable guide for decision-making processes.

Assessment of the impact of conservation measures by modeling soil loss in Minas Gerais, Brazil

Gullies are significant contributors to soil degradation in several regions of Brazil, including Minas Gerais, where erosion processes have caused soil loss. The characterization of erosion processes is crucial for the application of measures for recovering degraded areas and reducing erosion impacts. This study models soil loss with the use of InVEST software and assesses the impact of three different scenarios, namely (1) implementation of soil conservation practices and replacement of pasture areas for temporary agriculture, (2) reforestation of pasture areas, and (3) preservation of ciliary forests. Soil loss, sediment exportation, retention, and deposition for the present scenario (2019), as well as the three aforementioned hypothetical scenarios, were estimated. In the present scenario, the estimated mean annual soil loss was 2.75 t/ha year, with 1,449.54 t/year sediment exportation, 9,042.13 t/year retention, and 1,449.54 t/year deposition. The model predicted scenario 1 would result in 2.23 t/ha year mean annual soil loss, 1,300.59 t/year sediment exportation, 9,191.08 t/year retention, and 11,755.76 t/year deposition. Scenario 2 showed 1.92 t/ha year mean annual soil loss, 1,046.69 t/year sediment exportation, 9,444.98 t/year retention, and 10,229.77 t/year deposition, whereas the results for scenario 3 were 2.36 t/ha year, 616.65 t/year, 9,862.06 t/year, and 13,206.47 t/year, respectively. Reforestation and preservation of ciliary forests, along with soil conservation practices, were effective measures for reducing soil loss. Such findings are valuable for the management of areas degraded by erosion processes.

Spatiotemporal foresting of soil erosion for SSP-RCP scenarios considering local vegetation restoration project: A case study in the three gorges reservoir (TGR) area, China

Soil erosion is a common form of land degradation. The Coupled Model Intercomparison Project Phase 6 (CMIP6) provides a scenario framework for global socio-economic development and climate change by combining Shared Socioeconomic Pathways (SSP) and Representative Concentration Pathways (RCP). The soil erosion estimation under global climate change and land-use change scenarios provided by CMIP6 is valuable for representing future changes and hotspots. This study estimated the future changes in soil erosion in the Three Gorges Reservoir (TGR) area, China, which has suffered severe soil loss over an extended period, and vegetation restoration projects have been conducted since 1999. The scenarios provided by SSP1-2.6, SSP2-4.5, and SSP5-8.5 were coupled with the scenarios of regional vegetation restoration projects to reflect future land use changes (LUC) and climate change. The results showed that future soil erosion from 2020 to 2100 in the TGR area will experience a non-significant decreasing trend (with trend slopes of -0.013, -0.020, and-0.006 in SSP1-2.6, SSP2-4.5, and SSP5-8.5, respectively, with p > 0.05). However, with the R factors calculated by different methods, this decreasing trend becomes either insignificant or a significant increasing trend. SSP1-2.6 will experience the lowest soil erosion in 2100 owing to the large amount of forest increase in this scenario. Furthermore, as estimates, the grain-for-green policy (GGP) will reduce 89353.47, 92737.73 and 42916.52 ton soil erosion per year in SSP1-2.6, SSP2-4.5 and SSP3-8.5 by 2100, respectively. In the future, the GGP will become increasingly important for controlling soil loss in the TGR area owing to the increasing precipitation in all scenarios, which increases the risk of soil loss.

A cloud-integrated GIS for forest cover loss and land use change monitoring using statistical methods and geospatial technology over northern Algeria

Over the last two decades, forest cover has experienced significant impacts from fires and deforestation worldwide due to direct human activities and climate change. This paper assesses trends in forest cover loss and land use and land cover changes in northern Algeria between 2000 and 2020 using datasets extracted from Google Earth Engine (GEE), such as the Hanssen Global Forest Change and MODIS Land Cover Type products (MCD12Q1). Classification was performed using the pixel-based supervised machine-learning algorithm called Random Forest (RF). Trends were analyzed using methods such as Mann-Kendall and Sen. The study area comprises 17 basins with high rainfall variability. The results indicated that the forest area decreased by 64.96%, from 3718 to 1266 km², during the 2000-2020 period, while the barren area increased by 40%, from 134,777 to 188,748 km². The findings revealed that the Constantinois-Seybousse-Mellegue hydrographic basin was the most affected by deforestation and cover loss, exceeding 50% (with an area of 1018 km²), while the Seybouse River basin experienced the highest percentage of cover loss at 40%. Nonparametric tests showed that seven river basins (41%) had significantly increasing trends of forest cover loss. According to the obtained results, the forest loss situation in Algeria, especially in the northeastern part, is very alarming and requires an exceptional and urgent plan to protect forests and the ecological system against wildfires and climate change. The study provides a diagnosis that should encourage better protection and management of forest cover in Algeria.

Deforestation and fires in the Brazilian Amazon from 2001 to 2020: Impacts on rainfall variability and land surface temperature

Deforestation and fires in the Amazon are serious problems affecting climate, and land use and land cover (LULC) changes. In recent decades, the Amazon biome area has suffered constant fires and deforestation, causing severe environmental problems that considerably impact the land surface temperature (LST) and hydrological cycle. The Amazon biome lost a large forest area during this period. Thus, this study aims to analyze the deforestation and burned areas in the Amazon from 2001 to 2020, considering their impacts on rainfall variability and LST. This study used methods and procedures based on Google Earth Engine for analysis: (a) LULC evolution mapping, (b) vegetation cover change analysis using vegetation indices, (c) mapping of fires, (d) rainfall and LST analyses, and (e) analysis of climate influence and land cover on hydrological processes using the geographically weighted regression method. The results showed significant LULC changes and the main locations where fires occurred from 2001 to 2020. The years 2007 and 2010 had the most significant areas of fires in the Brazilian Amazon (233,401 km² and 247,562 km², respectively). The Pará and Mato Grosso states had the region's largest deforested areas (172,314 km² and 144,128 km², respectively). Deforestation accumulated in the 2016-2020 period is the greatest in the period analyzed (254,465 km²), 92% higher than in the 2005-2010 period and 82% higher than in the 2001-2005 period. The study also showed that deforested areas have been increasing in recent decades, and the precipitation decreased, while an increase is observed in the LST. It was also concluded that indigenous protection areas have suffered from anthropic actions.

Soil Erosion Characteristics and Scenario Analysis in the Yellow River Basin Based on PLUS and RUSLE Models

Soil erosion is an important global environmental issue that severely affects regional ecological environment and socio-economic development. The Yellow River (YR) is China's second largest river and the fifth largest one worldwide. Its watershed is key to China's economic growth and environmental security. In this study, six impact factors, including rainfall erosivity (R), soil erosivity (K), slope length (L), slope steepness (S), cover management (C), and protective measures (P), were used. Based on the revised universal soil loss equation (RUSLE) model, and combined with a geographic information system (GIS), the temporal and spatial distribution of soil erosion (SE) in the YR from 2000 to 2020 was estimated. The patch-generating land use simulation (PLUS) model was used to simulate the land-use and land-cover change (LUCC) under two scenarios (natural development and ecological protection) in 2040; the RUSLE factor P was found to be associated with LUCC in 2040, and soil erosion in the Yellow River Basin (YRB) in 2040 under the two scenarios were predicted and evaluated. This method has great advantages in land-use simulation, but soil erosion is greatly affected by rainfall and slope, and it only focuses on the link between land-usage alteration and SE. Therefore, this method has certain limitations in assessing soil erosion by simulating and predicting land-use change. We found that there is generally slight soil erosivity in the YRB, with the most serious soil erosion occurring in 2000. Areas with serious SE are predominantly situated in the upper reaches (URs), followed by the middle reaches (MRs), and soil erosion is less severe in the lower reaches. Soil erosion in the YRB decreased 11.92% from 2000 to 2020; thus, soil erosion has gradually reduced in this area over time. Based on the GIS statistics, land-use change strongly influences SE, while an increase in woodland area has an important positive effect in reducing soil erosion. By predicting land-use changes in 2040, compared to the natural development scenario, woodland and grassland under the ecological protection scenario can be increased by 1978 km2 and 2407 km2, respectively. Soil erosion can be decreased by 6.24%, indicating the implementation of woodland and grassland protection will help reduce soil erosion. Policies such as forest protection and grassland restoration should be further developed and implemented on the MRs and URs of the YR. Our research results possess important trend-setting significance for soil erosion control protocols and ecological environmental protection in other large river basins worldwide.

Spatial-Temporal Variations and Trade-Offs of Ecosystem Services in Anhui Province, China

Research on the spatiotemporal evolution and trade-offs of ecosystem services (ESs) is important for optimizing the ecological security barrier system and promoting coordinated socio-economic development. Natural factors, e.g., climate change, and human factors, e.g., unreasonable land use, have impacted and damaged ecosystem structure and function, leading to challenges with ES trade-offs and the spatial identification of priority protected areas. Here, the spatiotemporal evolution characteristics of five ESs (water yield, nitrogen export, soil retention, carbon storage, and habitat quality) in Anhui Province, China, from 2000-2020 were analyzed based on the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model. The trade-offs and spatial patterns among different ESs were explored using Pearson correlation and hotspot analyses; the dynamics of natural growth, cultivated land protection, and ecological protection scenarios for ESs in 2030 were simulated and analyzed by coupling InVEST with the patch-generating land use simulation (PLUS) model. The results reveal the following. (1) From 2000-2020, increases in water yield and soil retention occurred, with concurrent declines in the other services; the total nitrogen high-value area was mainly concentrated in the plain, with the other services' high-value areas mainly concentrated in the Dabieshan and Southern Anhui Mountains, with each ES showing similar spatial distributions across years. (2) The ESs were mainly synergistic, with trade-offs mainly between nitrogen export and other services. (3) Hotspot overlap between water yield and the other ESs was relatively low; no more than 6.53% of ecosystems per unit area provided five ESs simultaneously. (4) Other than water yield, the ecological protection scenario was more conducive to improving ecosystem functions. This study's results indicate inadequate synergy among ESs in Anhui Province; competition among land types must be further balanced in the future. This study provides a basic reference for implementing ecological projects and constructing ecological security patterns.

Ecological risk of imidacloprid on the Brazilian non-target freshwater organisms Chironomus sancticaroli and Poecilia reticulata

Imidacloprid (IMI) is a neonicotinoid insecticide widely used in agriculture worldwide. This pesticide has been found in freshwater ecosystems, including Brazilian freshwaters. For this reason, studies are being conducted to detect the presence of IMI in freshwater and understand its effects on the aquatic biota. In the present study, the acute toxic effect of the imidacloprid commercial formulation (ICF) Galeão^® on the Brazilian non-target aquatic organisms Chironomus sancticaroli and Poecilia reticulata was evaluated. Enzymatic activities (glutathione S-transferase (GST), catalase (CAT), and ascorbate peroxidase (APX)) were also determined. Moreover, we considered 11 studies that detected IMI concentrations up to 3.65 µg.L^-1 in 28 different Brazilian freshwaters to evaluate the acute ecological risk of IMI in these environments. From the ecotoxicological assays, we determined the LC₅₀ values for C. sancticaroli (LC_50-48 h 1.52 µg.L^-1) and P. reticulata (LC_50-96 h 122.65 mg.L^-1). The high sensitivity of C. sancticaroli demonstrates that this species could be used as a bioindicator in studies investigating the contamination of freshwater by IMI. Enzymatic activity changes were observed in both organisms and offered sublethal responses to the effects of the pollution by IMI on aquatic biota. Our results suggest that the presence of IMI in Brazilian aquatic ecosystems can represent a potential ecological risk for the aquatic insect populations and, consequently, cause an imbalance in these ecosystems. The present study provides relevant and comparable toxicity information that may be useful to develop public policies to protect the Brazilian aquatic ecosystem from IMI contamination.

Investigating Relationships between Runoff–Erosion Processes and Land Use and Land Cover Using Remote Sensing Multiple Gridded Datasets

Climate variability, land use and land cover changes (LULCC) have a considerable impact on runoff–erosion processes. This study analyzed the relationships between climate variability and spatiotemporal LULCC on runoff–erosion processes in different scenarios of land use and land cover (LULC) for the Almas River basin, located in the Cerrado biome in Brazil. Landsat images from 1991, 2006, and 2017 were used to analyze changes and the LULC scenarios. Two simulations based on the Soil and Water Assessment Tool (SWAT) were compared: (1) default application using the standard model database (SWATd), and (2) application using remote sensing multiple gridded datasets (albedo and leaf area index) downloaded using the Google Earth Engine (SWATrs). In addition, the SWAT model was applied to analyze the impacts of streamflow and erosion in two hypothetical scenarios of LULC. The first scenario was the optimistic scenario (OS), which represents the sustainable use and preservation of natural vegetation, emphasizing the recovery of permanent preservation areas close to watercourses, hilltops, and mountains, based on the Brazilian forest code. The second scenario was the pessimistic scenario (PS), which presents increased deforestation and expansion of farming activities. The results of the LULC changes show that between 1991 and 2017, the area occupied by agriculture and livestock increased by 75.38%. These results confirmed an increase in the sugarcane plantation and the number of cattle in the basin. The SWAT results showed that the difference between the simulated streamflow for the PS was 26.42%, compared with the OS. The sediment yield average estimation in the PS was 0.035 ton/ha/year, whereas in the OS, it was 0.025 ton/ha/year (i.e., a decrease of 21.88%). The results demonstrated that the basin has a greater predisposition for increased streamflow and sediment yield due to the LULC changes. In addition, measures to contain the increase in agriculture should be analyzed by regional managers to reduce soil erosion in this biome.