Land use/land cover change effect on soil erosion and sediment delivery in the Winike watershed, Omo Gibe Basin, Ethiopia

Assessing climate and land use impacts on surface water yield using remote sensing and machine learning

Climate and land use changes are critical factors affecting watershed water yields, with significant implications for water resources at both local and regional levels. This study examined the combined effects of temporal and spatial climate variability and land use/land cover (LULC) changes on surface water yield and availability in the Gilgel Gibe watershed, Ethiopia, from 1993 to 2023. Utilizing the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) hydrological models, machine learning, and remote sensing techniques, this study assessed variations in water resources and their impacts on basin water yield. This study utilized Landsat (30 m), MODIS (500 m-1 km), and 4 km resolution climate datasets from the United States Geological Survey (USGS) and NASA POWER for large-scale climate and land-use analyses from 1993 to 2023. An ensemble of machine learning models, including Random Forest (RF), Support Vector Machine (SVM), and XGBoost (XGB), were used to evaluate the effects of climate variability and land use on annual water yield. The study revealed significant land cover changes over a 30-year period. Shrubland decreased from 1,108.37 km2 (21.54%) in 1993 to 295.22 km2 (5.74%) in 2023. Grasslands and wetlands also showed declining trends. In contrast, water bodies increased from 12.51 km2 (0.24%) to 41.57 km2 (0.81%), primarily due to the construction of the Gilgel Gibe hydroelectric dam, and forested areas slightly decreased from 626.73 km2 (12.18%) to 534.18 km2 (10.38%). The surface runoff decreased to 15.78% in 2021 and 15.28% in 2022, whereas the water yield dropped from 1.22% in 1993 to 0.83% by 2023. This study also showed a reduction in lateral flow and higher evapotranspiration levels in 2000 and 2017. The decrease in runoff can be attributed to the loss of wetlands and grasslands, reduced precipitation, and regulatory effects of hydropower operations. In contrast, elevated evapotranspiration levels were primarily attributed to temperature extremes, vegetation stress, and potential increases in irrigation practices. These findings underscore the importance of climatic elements in regulating river discharge and the necessity for smart land use planning to prevent negative environmental consequences on water resources.

Unveiling spatiotemporal patterns and key drivers of soil conservation from a "historical-future-intervention" perspective: A case study of the Danjiangkou Reservoir Area, China

The soil conservation of ecosystems in water source areas is crucial for ensuring water quality and supply. It is primarily shaped by natural factors like rainfall intensity, soil characteristics, and topography, alongside the impact of human activities. As the starting point and core water source area of the South-to-North Water Diversion Middle Route Project, the Danjiangkou Reservoir has experienced increasing risks of soil erosion under the combined effects of extreme climate events and land cover changes. Effectively assessing these changes and formulating policies to address future challenges is of great significance for the stable operation of the reservoir and the long-term, sustainable transfer of clean water. This study incorporates human intervention factors to generate three future development scenarios for the DRA, including protection priority, natural development, and economic priority, corresponding to SSP1-2.6, SSP2-4.5, and SSP5-8.5 stem from the future climate, social, and economic scenarios (CMIP6-SSP-RCP), respectively. Additionally, we uses land use/land cover (LULC) data from 2000 to 2020 as historical input and applies the LULC simulation model model (PLUS) to predict land use types for the 2025-2035 period under the current land use continuation scenario, and employ the InVEST model to quantify SC (soil conservation) services for both the 2000-2020 period and the different future scenarios (2025-2035). The findings indicate that the land use structure in the reservoir area has undergone changes over the past two decades, with a reduction in forest and grassland, leading to a gradual weakening of soil conservation capacity. Among the future scenarios, the protection-priority scenario, which involves human intervention, offers the highest soil conservation. LULC is identified as a major variable influencing these changes. The findings offer scientific evidence and support for future land use and soil conservation management in the DRA.

Dynamic response of vegetation, land surface temperature and carbon storage to changes in land use and land cover in Mysuru City, Karnataka, India

Land use and land cover (LULC) changes are associated with notable environmental concerns, such as alterations in land surface temperature, loss of vegetation and the impact on carbon sequestration, especially within urban settings. Urban planners worldwide are investigating these impacts. A study utilizing remote sensing and geographic information system techniques examined changes in land surface temperature (LST), normalized difference vegetation index (NDVI) and carbon sequestration in Mysuru City from 1992 to 2022. The results showed a 2.39% decrease in vegetation cover and a substantial 36.97% increase in urban areas, leading to elevated LST by an average of 4 °C. Carbon storage has significantly declined to 25 Mg ha-1 in 2022 from 56 Mg ha-1 in 1992. The spatial extent of zero-level carbon storage has steadily diminished over the years. The analysis indicates a negative relationship between LST and carbon storage, with a weak correlation explained by a coefficient of determination (R2) value of 0.063 in 1992 and 0.024 in 2022. Conversely, a positive relationship exists between the NDVI and carbon storage, suggesting that effective strategies such as afforestation, reforestation and urban greening practices can enhance carbon sequestration capacity and mitigate climate change impacts in rapidly growing cities. The results of this study offer valuable insights for city planners and policymakers, aiding in the identification of areas experiencing increased LST and diminishing natural landscapes. Furthermore, the study can serve as a foundation for identifying urban hotspots, cold spots and areas conducive to urban thermal comfort. The results of this study can be enhanced by using a higher spatial resolution satellite dataset, thus providing a prospect for future research.

Integration of remote sensing and machine learning algorithm for agricultural drought early warning over Genale Dawa river basin, Ethiopia

Drought remains a menace in the Horn of Africa; as a result, the Ethiopia's Genale Dawa River Basin is one of the most vulnerable to agricultural drought. Hence, this study integrates remote sensing and machine learning algorithm for early warning identification through assessment and prediction of index-based agricultural drought over the basin. To track the severity of the drought in the basin from 2003 to 2023, a range of high-resolution satellite imagery output indexes were used, including the Vegetation Condition Index (VCI), Thermal Condition Index (TCI), and Vegetation Health Index (VHI). Additionally, the Artificial Neural Network machine learning technique was used to predict agricultural drought VHI for the period of 2028 and 2033. Results depict that during the 2023 period, 25% of severe drought and 18% of extreme drought countered at the lower part of the basin at Dolo ado and Chereti regions. A high TCI value was found that around 23.24% under extreme drought and low precipitation countered in areas of Moyale, Dolo ado, Dolobay, Afder, and Bure lower than 3.57 mm per month. Similarly, increment of severe drought from 24.26% to 24.58% and 16.53% to 16.58% of extreme drought value of VHI might be experienced during the 2028 and 2033 period respectively in the area of Mada Wolabu, Dolo ado, Dodola, Gore, Gidir, and Rayitu. The findings of this study are significantly essential for the institutes located particularly in the basin as they will allow them to adapt drought-coping mechanisms and decision-making easily.

Utilizing InVEST ecosystem services model combined with deep learning and fallback bargaining for effective sediment retention in Northern Iran

This study aimed to integrate game theory and deep learning algorithms with the InVEST Ecosystem Services Model (IESM) for Sediment Retention (SR) modeling in the Kasilian watershed, Iran. The Kasilian watershed is characterized by multiple sub-watersheds, which vary in their environmental conditions and SR potential, with a total of 19 sub-watersheds. The research was carried out in four phases: mapping SR using the IESM, implementing the Fallback bargaining algorithm based on game theory, applying deep learning algorithms (CNN, LSTM, RNN), and performing statistical analysis for optimal model selection. Based on the results, the analysis of geo-environmental criteria indicated that sub-watersheds with poor conditions regarding rain erosivity, soil erodibility, LS, elevation, and land use faced greater challenges in SR. Utilizing the Fallback bargaining algorithm for sub-watershed prioritization revealed that sub-watershed 5 emerged as having the highest SR potential due to high rain erosivity and a significant LS factor. Spatial SR mapping via game theory algorithm demonstrated that northern sub-watersheds in the Kasilian watershed had greater SR potential. Deep learning algorithms were also utilized for SR distribution modeling, where the RNN model was deemed optimal, yielding error statistics of MAE: 0.05, MSE: 0.04, R2: 0.79, RMSE: 0.20, and AUC: 0.97. The SR distribution patterns demonstrated that RNN and LSTM algorithms exhibited similar classification outcomes, differing from those of the CNN algorithm. The prioritization of sub-watersheds using various approaches revealed that the Fallback bargaining algorithm showed a 47% similarity with the InVEST model results. In contrast, deep learning models such as CNN, LSTM, and ARANN exhibited 84%, 79%, and 79% similarity, respectively. These findings supported SR zonation maps, reinforcing that deep learning models outperformed the game theory algorithm. The Alpha Diversity Indices (ADI) confirmed that the outputs from the LSTM and RNN models showed identical changes across all indices. Minimal variations in the other approaches suggested that all five methods yielded similar results based on diversity indices (including Taxa, Dominance, Simpson, and Equitability), indicating no significant differences among them when compared to the InVEST model in sediment modeling.

Evolution and driving mechanism of multiple ecosystem services in resource-based region of Northern China

Understanding the spatiotemporal characteristics and comprehensive service capabilities of various ecosystem services is crucial for maintaining regional ecosystem security, and clarifying the driving mechanisms of ecosystem services plays a guarantee for achieving regional sustainable development. Based on the ecological issues of Shanxi Province (SXP) in China, an assessment system covering eight targeted ecosystem services were constructed to quantitatively analyze the spatio-temporal patterns and contribution rates of driving factors. The water conservation, sand fixation, environment purification and habitat quality in the Loess Hills of western SXP have improved, with significant increase in hotspots. The comprehensive service capacity of ecosystem services in the Fenwei Basin (central SXP) has deteriorated, and the coldspots have expanded. The water conservation, carbon storage, habitat quality and recreation culture in the Yanshan-Taihang Mountains (eastern SXP) were enhanced, while product supply, carbon storage and environment purification were deteriorated. Land use is the dominant influencing factor on product supply. Water and soil conservation, sand fixation, and environment purification are dominated by climate factors. Carbon storage, habitat quality and recreation culture are influenced by underlying surface conditions. The current study provided a research paradigm, which will help the government with appropriate management policies to ensure the effectiveness of ecological protection and restoration, and offers insights for facilitating ecological sustainability and economic transformation in resource-based regions worldwide.

How does cultivated land fragmentation affect soil erosion: Evidence from the Yangtze River Basin in China

Reducing soil erosion (SE) is crucial for achieving harmony between human society and the ecological environment. The cultivated land fragmentation (CLF), directly or indirectly, alters soil structure, diminishes its water-holding capacity, and escalates the risk of SE. Scientific assessment of the effect of CLF on SE can provide new insights into controlling of SE across watersheds in China. However, few studies have quantified the effect of CLF on SE. Therefore, we utilized land use change data in the Yangtze River basin from 2000 to 2020, measuring the levels of CLF and SE using Fragstats and InVEST models. The bivariate spatial autocorrelation model was employed to reveal the spatial relationship between CLF and SE. Additionally, we constructed a spatial Durbin model and introduced the geographically and temporally weighted regression model to analyze the role of CLF on SE. The south bank of the upper and middle reaches of the Yangtze River basin exhibited high CLF and SE. The bivariate spatial autocorrelation results showed a significant positive spatial correlation between CLF and SE. The spatial Durbin model results showed that CLF had a spatial spillover effect and time lag on SE, and the effect of CLF on SE had an inverted "N" curve. The study also confirmed that last SE and neighboring SE areas influenced local SE. Currently, CLF had a negative effect on SE in the Sichuan Basin, Yunnan-Guizhou Plateau, and the middle and lower Yangtze River Plain, and positively in Qinghai, Hunan, and Jiangxi provinces. These findings suggest that the government should enhance cross-regional and cross-sectoral cooperation and monitoring of cultivated land changes to prevent and control SE effectively.

Identifying priority areas for conservation: using ecosystem services hotspot mapping for land-use/land-cover planning in central of Iran

The modeling and mapping of hotspots and coldspots ecosystem services (ESs) is an essential factor in the decision-making process for ESs conservation. Moreover, spatial prioritization is a serious stage in conservation planning. In the present research, based on the InVEST software, Getis-Ord statistics (Gi*), and a set of GIS methods, we quantified and mapped the variation and overlapping among three ESs (carbon storage, soil retention, and habitat quality). Furthermore, an approach was proffered for detecting priority areas to protect multiple ecosystem services. Hotspots recognized via the Gi* statistics technique contain a higher capacity for supplying ESs than other areas. This means that protecting these areas with a bigger number of overlapped hotspots can provide more services. Results indicated that population growth accompanied by the increase in construction sites and low-yield agricultural lands in the Zayanderood dam watershed basin has resulted in ES losses. This situation is represented by increasing soil erosion, reduced carbon storage, reduced biodiversity, and fragmented habitat distribution due to land-use change. The statistically significant carbon storage, soil retention, and habitat quality hotspots with above 95% confidence level account for 21.5%, 39.3%, and 16.9% of the study area, respectively. Therefore, a clear framework was presented in this study for setting ES-based conservation priority. Decision makers and land-use planners can also combine this technique into their framework to identify and conserve ES hotspots to support their targeted ecosystem policies.

Predicting reservoir sedimentation using multilayer perceptron - Artificial neural network model with measured and forecasted hydrometeorological data in Gibe-III reservoir, Omo-Gibe River basin, Ethiopia

The estimation and prediction of the amount of sediment accumulated in reservoirs are imperative for sustainable reservoir sedimentation planning and management and to minimize reservoir storage capacity loss. The main objective of this study was to estimate and predict reservoir sedimentation using multilayer perceptron-artificial neural network (MLP-ANN) and random forest regressor (RFR) models in the Gibe-III reservoir, Omo-Gibe River basin. The hydrological and meteorological parameters considered for the estimation and prediction of reservoir sedimentation include annual rainfall, annual water inflow, minimum reservoir level, and reservoir storage capacity. The MLP-ANN and RFR models were employed to estimate and predict the amount of sediment accumulated in the Gibe-III reservoir using time series data from 2014 to 2022. ANN-architecture N4-100-100-1 with a coefficient of determination (R2) of 0.97 for the (80, 20) train-test approach was chosen because it showed better performance both in training and testing (validation) the model. The MLP-ANN and RFR models' performance evaluation was conducted using MAE, MSE, RMSE, and R2. The models' evaluation result revealed that the MLP-ANN model outperformed the RFR model. Regarding the train data simulation of MLP-ANN and RFR shown R2 (0.99) and RMSE (0.77); and R2 (0.97) and RMSE (1.80), respectively. On the other hand, the test data simulation of MLP-ANN and RFR demonstrated R2 (0.98) and RMSE (1.32); and R2 (0.96) and RMSE (2.64), respectively. The MLP-ANN model simulation output indicates that the amount of sediment accumulation in the Gibe-III reservoir will increase in the future, reaching 110 MT in 2030-2031, 130 MT in 2050-2051, and above 137 MTin 2071-2072.

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.

Mapping land-use and land-cover changes through the integration of satellite and airborne remote sensing data

An integrated, remotely sensed approach to assess land-use and land-cover change (LULCC) dynamics plays an important role in environmental monitoring, management, and policy development. In this study, we utilized the advantage of land-cover seasonality, canopy height, and spectral characteristics to develop a phenology-based classification model (PCM) for mapping the annual LULCC in our study areas. Monthly analysis of normalized difference vegetation index (NDVI) and near-infrared (NIR) values derived from SPOT images enabled the detection of temporal characteristics of each land type, serving as crucial indices for land type classification. The integration of normalized difference built-up index (NDBI) derived from Landsat images and airborne LiDAR canopy height into the PCM resulted in an overall performance of 0.85, slightly surpassing that of random forest analysis or principal component analysis. The development of PCM can reduce the time and effort required for manual classification and capture annual LULCC changes among five major land types: forests, built-up land, inland water, agriculture land, and grassland/shrubs. The gross change LULCC analysis for the Taoyuan Tableland demonstrated fluctuations in land types over the study period (2013 to 2022). A negative correlation (r =  - 0.79) in area changes between grassland/shrubs and agricultural land and a positive correlation (r = 0.47) between irrigation ponds and agricultural land were found. Event-based LULCC analysis for Taipei City demonstrated a balance between urbanization and urban greening, with the number of urbanization events becoming comparable to urban greening events when the spatial extent of LULCC events exceeds 1000 m2. Besides, small-scale urban greening events are frequently discovered and distributed throughout the metropolitan area of Taipei City, emphasizing the localized nature of urban greening events.

Indexing and segment-level mapping of soil quality in a spatially complex watershed in northern Iran

Soil quality (SQ) modeling and mapping is a leading research field aiming to provide reproducible and cost-effective yet accurate SQ predictions at the landscape level. This endeavor was conducted in a complex watershed in northern Iran. We classified the region into spectrally and topographically homogenous land units (average area of 48 ± 23 ha) using object-based segmentation analysis. Following the physicochemical analysis of soil samples from 98 stations, the Nemoro soil quality index (SQIn) was produced using the minimum dataset procedure and a non-linear sigmoid scoring function. SQIn values averaged 0.21 ± 0.06 and differed statistically between major land uses. To predict and map SQIn for each land unit, the best-performing regression model (F(3, 84) = 45.57, p = 0.00, R2 = 0.62) was built based on the positive contribution of the mean Landsat 8-OLI band 5, and negative influence of land surface temperature retrieved from Landsat 8-OLI band 10 and surface slope (t-test p-values < 0.01). Results showed that dense-canopy woodlands located in low-slope land units exhibit higher SQIn while regions characterized by either low-vegetation or steep-sloped land units had SQ deficits. This study provides insights into SQ prediction and mapping across spatially complex large-scale landscapes.

Evaluating the impact of land use and land cover changes on sediment yield dynamics in the upper Awash basin, Ethiopia the case of Koka reservoir

Land Use and Land Cover changes (LULC) are the driving forces to change the hydrological response of the watershed. In this study, the Quantum Geography Information System Interference Soil and Water Assessment Tool Plus (QSWAT-PLUS) model was applied to evaluate the effects of LULC on sediment load at the Upper Awash River Basin (UARB) which are causing sedimentation problems in Koka reservoir. The LULC data for 2005, 2010, and 2015 were obtained from historical satellite images using Earth Resources Observation and Science (ERDAS) 2014. The classification of LULC changes showed that the agricultural practice, and the settlement land both increased by 6.7 % and 6.3 %, respectively. In contrast, the forest area, woodland, shrubland, and water bodies decreased by 5.47 %,0.93 %,0.96 %, and 1.34 % from 2000 to 2015 respectively. The model evaluation results were satisfactory for the three LULC scenarios. The average annual surface runoff volume for the 2005 LULC data was 182.2 mm, which increased to 193.29 mm in 2010 and 205.3 mm in 2015. Similarly, the average annual sediment yield that would enter to the Koka reservoir under the 2005, 2010, and 2015 LULC scenarios were 26.03 t/ha/yr, 26.34 t/ha/yr, and 28.33 t/ha/yr respectively. In general, streamflow, surface runoff, and sediment output increased by 4.55 %, 12.68 %, and 8.84 %, respectively due to the rapid change of LULC from 2000 to 2015. Temporarily, the sediment load at the upstream side of the Koka Dam watershed was 60.8 % during the wet season. The southwest direction of the watershed was identified as the primary erosion-prone area. Based on the simulation results, the filter strip, contour, and terraces reduced the watershed sediment yield by up to 60 %, 65 %, and 80 %, respectively. Therefore, the selected best management practices are highly effective in reducing silt along the entire upstream side of the Koka Dam watershed.

The spatio-temporal dynamics of suspended sediment sources based on a novel indexing approach combining Bayesian geochemical fingerprinting with physically-based modelling

Applications of sediment source fingerprinting continue to increase globally as the need for information to support improved management of the sediment problem persists. In our novel research, a Bayesian fingerprinting approach using MixSIAR was used with geochemical signatures, both without and with informative priors based on particle size and slope. The source estimates were compared with a newly proposed Source Sensitivity Index (SSI) and outputs from the INVEST-SDR model. MixSIAR results with informative priors indicated that agricultural and barren lands are the principal sediment sources (contributing ∼5-85% and ∼5-80% respectively during two sampling periods i.e. 2018-2019 and 2021-2022) with forests being less important. The SSI spatial maps (using % clay and slope as informative priors) showed >78% agreement with the spatial map derived using the INVEST-SDR model in terms of sub-catchment prioritization for spatial sediment source contributions. This study demonstrates the benefits of combining geochemical sediment source fingerprinting with SSI indices in larger catchments where the spatial prioritization of soil and water conservation is both challenging but warranted.

Evaluation of best management practices to reduce sediment yield in the upper Gilo watershed, Baro akobo basin, Ethiopia using SWAT

The increasing sediment yield in the watershed is caused by natural and human activities, which significantly shifts the hydro-meteorological in the watershed. The Modified Universal Soil Loss Equation (MUSLE) equation in the Soil and Water Assessment Tool (SWAT) was used to estimate sediment yields for each hydrological response unit (HRU) based on peak runoff, daily runoff volume, area of hydrological response unit, and other estimated and default hydrological model parameters. The amount of sediment yield from each HRU is then summed to give the total soil erosion for the watershed.The spatio-temporal variations of sediment yield in the Upper Gilo watershed was simulated to identify the hotspot area and select the effective management practices (BMPs) for reducing significant problems. Model calibration and validation were carried out using sediment yield data from 1990 to 2004 and 2005 to 2014. The results indicated that the watershed total sediment yield is 1021.8 tonnes/yr. Furthermore, 17 sub-basins (37.8% of total watershed area) are severely threatened by high soil erosion. According to the simulation results, the filter strips, terraces, and contours reduced the watershed sediment yield by up to 53.2%, 45.4%, and 48%. Overall, the selected BMPs are highly effective in reducing sediment yield in watershed-prone areas.

Assessment of soil erosion hazard and its relation to land use land cover changes: Case study from alage watershed, central Rift Valley of Ethiopia

Soil erosion by water and wind is among the most crucial land degradation processes in Ethiopia. This is also the case for Alage watershed located in the cental Rift Valley system. This study aimed at assessment of soil erosion hazard and its relation to land use land cover change in the watershed during the period from 1984 to 2016 for a better land management. The study is based on application of Remote Sensing (RS) and Geographical Information System (GIS) to extract inputs factor values for the Revised Universal Soil Loss Equation (RUSLE). Time-series satellite imageries of Landsat TM 1984, ETM+ 2000 and OLI 2016 were used for land use land cover change detection and determination of cover management (C) factor of the RUSLE. Biophysical data such as rainfall, soil properties, land management practices including soil and water conservation measures within the watershed were collected using field survey and secondary data sources. Slope steepness and slope length factors were derived using Digital Elevaition Model (DEM). Long-term average annual soil loss rates were estimated by the RUSLE integrated with GIS for 1984, 2000 and 2016. Using satellite imageries, the land use land cover and changes within the watershed during the three periods were obtained through a supervised classification with maximum likelihood algorithim. The results of land use land cover change indicated that the proportion of rain-fed cropland, bare land and built up areas increased by 17.4%, 5.9% and 2.9% respectively over the three study period. In contrast the proportion of bush/shrub land, irrigated cropland, grass land, forested areas and waterbodies decresaed by 15.5%, 4.7%, 3.4%, 2.3% and 0.3% respectively during the same period. Estimated average annual soil loss rates showed an increasing trend from 24.3 ton ha-1 yr-1 in 1984 to 38 ton ha-1 yr-1 in 2016. Increasing trends of average annual soil loss rate is attributed to increased proportion of cropland, bare land and built up areas during those periods leading to decreased protective vegetation cover. Hotspot areas within the watershed require implementation of land management practices to prevent further degradation and expansion of gullies. This study is relevant to demonstrate environmental implication of land use land cover change for future land management practices and land use policy in the Rift Valley of central Ethiopia.

Assessment of Multiple Ecosystem Services and Ecological Security Pattern in Shanxi Province, China

The ecological security pattern construction could effectively regulate ecological processes and ensure ecological functions, then rationally allocate natural resources and green infrastructure, and, finally, realize ecological security. In view of serious soil erosion, accelerated land desertification, soil pollution and habitat degradation in Shanxi Province, the spatial distribution of six key ecosystem services, including water conservation (WC), soil conservation (SC), sand fixation (SF), carbon storage (CS), net primary productivity (NPP) and habitat quality (HQ), was analyzed by using multiple models. The comprehensive ability of multiple ecosystem services in different regions was quantified by calculating multiple ecosystem services landscape index (MESLI). Combined with ecosystem services hotspots, the ecological security pattern of Shanxi Province was constructed by using the minimum cumulative resistance model. The results showed that the spatial differences in ecosystem services in Shanxi Province were obvious, which was low in the seven major basins and Fen River valley, and high in the mountains (especially Taihang and Lvliang Mountains) for WC, SC, CS, NPP and HQ, while high SF was only distributed in the northern Shanxi. The MESLI showed that the ability to provide multiple ecosystem services simultaneously was low in Shanxi Province, with the medium and low grade MESLI regions accounting for 58.61%, and only 18.07% for the high grade MESLI regions. The important protected areas and ecological sources of the ecological security pattern were concentrated in the Lvliang and Taihang Mountains, which were consistent with the key areas of ecosystem services. The ecological corridors illustrated network distribution with ecological sources as the center, the low-, medium- and high-level buffers accounted for 26.34%, 17.03% and 16.35%, respectively. The results will provide important implications for economic transformation, high-quality development and ecological sustainable development in resource-based regions worldwide.

Spatiotemporal Variation of Soil Erosion Characteristics in the Qinghai Lake Basin Based on the InVEST Model

The present study aims to quantitatively assess soil erosion intensity (SEI) and amounts in the Qinghai Lake Basin (QLB) over the 1990-2020 period using the Integrated Valuation Ecosystem Services and Tradeoffs (InVEST) model based on multi-source data. In addition, the changing trends and driving factors of soil erosion (SE) in the study area were systematically analyzed. The result showed: (1) An increasing-decreasing trend in the total soil erosion amount (SEA) in the QLB over the 1990-2020 period, with an average SEI of 579.52 t/km². In addition, very low and low erosion classes covered 94.49% of the total surface area, while areas with high SEI were mainly distributed in alpine areas with low vegetation coverage (VC). (2) The highest average SEI was observed in bare land, while grassland and unused land were the main land use (LU) types where SE mainly occurred, with the ratio of the two being 95.78%. (3) The average value of SEI was positively correlated with altitude values below 4800 m. In addition, areas with altitude ranges of 4000-4400 m, 3600-4000 m, and 4400-4800 m were the main areas where SE occurred, with an average total soil erosion ratio (SER) value of 88.73%. (4) The average SEI was directly proportional to the slope degrees. SE occurred mainly in the areas with slope degree ranges of 15-25°, 25-35°, 8-15°, and >35°, accounting for 93.16% of the average total SER value. (5) The q value of the two-factor interaction was greater than that of the single-factor interaction. In addition, the areas with a high SE risk were mainly those with 1220-2510 m rainfall, <0.104 VC, the land use/land cover (LULC) type bare land, the altitude range 4400-4800 m, and a slope of >35°. The interaction between rainfall, VC, LULC, elevation, and slope had a significant impact on the spatial distribution of SEI.

Quantitative assessment of sediment delivery and retention in four watersheds in the Godavari River Basin, India, using InVEST model - an aquatic ecosystem services perspective

Sediment export and retention are important ecosystem processes in any landscape causing soil erosion and sediment loading in waterways consequently affecting the health of aquatic habitats downstream. The present study quantifies sediment export and retention in four watersheds, viz., Hivra, Satrapur, Konta, and Jagdalpur in the Godavari River Basin, India, using Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) ecosystem service modelling tool. The  results revealed that the sediment export yields ranged from 0.75 (Hivra) to 2.77 t/ha/year (Jagdalpur). The mean deviation between modelled values and observed sediment export yield was - 11.11%, which indicated good prediction by the model. The sediment retention ranged from 16.04 (Hivra) to 101.52 t/ha/year (Konta). Most sediment export and retention occurred on cropland or shrubland land use land cover types in all four watersheds. For decision making on soil conservation, soil loss tolerance limits have been established for these watersheds. For aquatic habitats, sediment concentration is considered more important than the total annual sediment export, since water turbidity is an important determinant of water quality, and the aquatic lives therein. Therefore, the temporal distribution of rainfall and corresponding sediment export becomes important, since these two factors determine the sediment concentration as well as turbidity in the waterbody. In current study, "Precipitation Concentration Index adjusted Sediment Export Yield Index" was developed to account for the effects of the temporal rainfall distribution and its impact on sediment export. The index for four watersheds was quantified (Hivra > Satrapur > Konta > Jagdalpur), which is concordant to the turbidity values reported by respective gauge stations. Thus, the proposed index can efficiently capture the impact of temporal rainfall distribution on sediment export, and consequently its effect on water turbidity. The study revealed the potential of InVEST model to quantify the sediment export and retention in the watersheds studied. Together with the proposed index, it would help the policy makers in making informed decisions for planning conservation strategies for aquatic biodiversity.

Spatiotemporal dynamics of soil loss and sediment export in Upper Bilate River Catchment (UBRC), Central Rift Valley of Ethiopia

Soil loss is one of the major challenges for agricultural production in the Ethiopian highlands. The rate and distribution of soil loss (SL) and sediment export (SE) are essential to map degradation “hotspot” areas for prioritizing soil and water conservation measures. The objective of this study was to estimate the dynamics of SL and SE in the Upper Bilate River Catchment of Central Ethiopia. The Sediment Delivery Ratio (SDR) module of the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model was used to estimate and map SL and SE. The primary input data were rainfall, soil data, land use, and other biophysical parameters of the study area. The model output confirmed that the average total soil loss of the catchment was 36.8 million ton/yr. It is modeled that soil loss doubles within 30 years. The average annual sediment export was about 3.62 ton/ha/yr. The mean annual soil loss of the study area was 23 ton/ha/yr, which exceeded the soil loss tolerance (SLT), estimated to range between (2–18 ton/ha/yr) in Ethiopia. Based on the soil erosion risk level, about 22% of the catchment area was classified as severely degraded, while 62 % was moderately degraded. Severe soil erosion prevails in the sub-watershed (SW)-5, SW-4, and SW-13. Therefore, these sub-watersheds need priority conservation action to restore the ecosystem processes of the study area.

Anthropogenic Land Use and Land Cover Change as Potential Drivers of Sediment Sources in the Upper Crocodile River, North West Province, South Africa

In this study, we investigated the accelerating pace of anthropogenic land use and land cover change (LULCC) disturbance, which has generated enormous impacts on the Crocodile River. Spot images from 1996, 2009 and 2022 were used to generate the land use maps and quantify the changes. A supervised classification with the maximum likelihood classifier was used to classify the images. Sediment sources were classified into two sources, revealed by erosional characteristics in the catchment. A gamma spectrometry detector, high-purity germanium (HPGe) "Well" detector by Canberra and inductively coupled plasma mass spectrometry (ICP-MS) were used for the analysis of the samples. The results revealed that from 1996-2022, built-up areas, bare land and water bodies increased by 3.48%, 2.47% and 1.90%, respectively. All the LULCC classes increased annually from 1996-2022, except for grassland, which shrunk. The results of the radionuclides analysis showed that ²¹⁰Pb_ex was found to be a more effective tracer than ¹³⁷Cs. The mass balance model revealed that subsurface sources contributed 60%, while surface sources contributed 40%, of the sediment load in the river. This research provides valuable information necessary for integrated catchment management policies for future LULCC and soil erosion to be adopted.

Impact of Accessibility to Cities at Multiple Administrative Levels on Soil Conservation: A Case Study of Hunan Province

The development of traffic infrastructure involves massive land use changes along the transportation routes and stimulates urban sprawl at transfer nodes, leading to a degradation in ecosystem services, including soil conservation. For developing countries, especially for China, it is very important to differentiate the influences between different standards of traffic infrastructure associated with the different administrative levels of the regions where they are constructed on soil conservation. In this study, we attempt to analyze the differences in the influence of accessibility at different levels on soil conservation, for the case study area in Hunan province in China. The results indicate that: (1) traffic conditions in Hunan province have witnessed continuous improvement, and the time taken to access mega-cities, prefecture-level cities, and county-level cities from various regions has been significantly reduced. (2) The total annual soil conservation in Hunan province is maintained at approximately 2.93 × 109 t. However, the spatial heterogeneity shows severe degradation in regions with lower accessibility, and weak enhancement in regions with higher accessibility. (3) A negative spatial autocorrelationship exists between accessibility and soil conservation at all levels, with the increase of administrative rank of the destination making it more obvious and intense, along with an increased tendency for the spatial distribution to concentrate. (4) Building more railways and highways from prefecture-level cities with LH clusters nearby as transfer nodes, instead of the construction of national roads and provincial roads that diverge from these railways and highways, will help limit the massive expansion of construction land and soil erosion within prefecture-level cities, rather than spreading to towns of LH clusters. This research provides an important scientific basis for future regional planning and traffic infrastructure construction, and also a reference for traffic infrastructure development in other geographically similar regions on a synchronous development stage in the world.

Identify the Impacts of the Grand Ethiopian Renaissance Dam on Watershed Sediment and Water Yields Dynamics

The construction of large-scale water reservoir facilities in transboundary river basins always arouses intense concern and controversy. The Grand Ethiopian Renaissance Dam (GERD) under construction in Ethiopia is perceived to affect water security in Egypt and Sudan. Therefore, this study investigated the water and sediment balance of the Blue Nile River (BNR) basin and identified the spatio-temporal variation in sediment and water yields along with the construction of GERD using Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) sediment and water yield models. The BNR basin experienced increasing water and sediment yields between 1992 and 2020 and has shown a growth trend since 2020. The lion’s share of water and sediment yields come from upstream of the GERD. Taken together, these results imply that the construction of the GERD will serve as a water storage and silt trap for Sudan and Egypt.

Distribution of ecological restoration projects associated with land use and land cover change in China and their ecological impacts

China is prone to broad land degradation and thus has been implementing ecological restoration projects (ERPs) since the reform and opening up. The extent of ERPs, as well as the varied planting efforts including tree gain projects (TGPs), grass gain projects (GGPs), and shrub gain projects (SGPs), have remained largely unknown. In addition, the mixed success of ERPs on preventing soil erosion and improving biodiversity is not well known. Based on a land use and land cover (LULC) product and a trajectory-based change detection approach, we successfully generated the first national map of ERPs associated with land use and land cover change (LUCC) and its three associated subcategories. Then, we applied the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model to evaluate the dynamics of sediment retention and habitat quality. In addition, we explored the heterogeneous patterns for the ecological impacts of ERPs. Our results suggested that during the past 40 years, a total ERP area of 9.54 × 10⁶ hm² was observed nationwide, mainly in the northwestern provinces of China. Of the three ERP subcategories, TGPs accounted for the largest area (48.55%), followed by GGPs (47.50%) and SGPs (3.96%). The national average sediment retention experienced a significant increase, whereas the national average habitat quality experienced a significant decline. ERP-driven increases in habitat quality were offset partly by the LUCCs induced by economic development policies in some regions, especially in northeast China. The simultaneous effect of construction land expansion and ERP implementation on sediment retention made the synchronization between ERP implementation and sediment retention improvement insignificant. We also suggested the optimal direction for ERP implementation.

Integrating ecosystem services and landscape connectivity to construct and optimize ecological security patterns: a case study in the central urban area Chongqing municipality, China

Rapid urbanization is often accompanied by the irrational utilization of natural resources and environmental degradation. Ecological security pattern (ESP) is an effective way for rational allocation of resources, which is conducive to achieving sustainable development. Taking the central urban area Chongqing municipality as the study area, ecological sources were identified by integrating ecosystem services and landscape connectivity. Combining natural and anthropogenic factors, a resistance surface was constructed and modified, and four ecological function zones were determined. Ecological corridors were extracted and prioritized by Linkage Mapper and the gravity model, and ecological nodes were also obtained. A network connectivity assessment was performed to compare the connectivity of ESPs before and after optimization. The results showed that ESPs included 2453.72 km² of ecological sources, 189 ecological corridors, 69 ecological nodes and 4 ecological function zones. The ecological sources primarily consisted of forestland, cultivated land and water bodies in Jinyun, Zhongliang, Tongluo, Mingyue and other mountainous areas, with the maximum distribution index value at the tenth level of the terrain niche index gradient. The Yangtze River and Jialing River were also the most important ecological sources. Ecological corridors were mainly dominated by forestland and cultivated land. Ecological nodes were concentrated in Yubei, Banan and Jiulongpo districts. The optimized ESPs had higher network connectivity and closure, with a more uniform distribution of ecological corridors, and included 2461.95 km² of ecological sources, 218 ecological corridors and 72 ecological nodes. Finally, recommendations for sustainable development were proposed. This study provides a theoretical reference for decision-making related to ecological protection and urban planning.

Study on the Water Quality Characteristics of the Baoan Lake Basin in China under Different Land Use and Landscape Pattern Distributions

Land use and landscape pattern highly affect water quality. Their relationship can assist in land-use management and improve land-use efficiency. In this study, a water quality survey of rivers and lakes was performed in 2020 to analyze the effects of land use and the landscape pattern on the water quality of the rivers and lakes in the Baoan Lake basin and is expected to provide a reference for land use planning. The results demonstrated that the effects of land use on water quality were generally higher during the dry season than during the wet season; however, the opposite was demonstrated for the landscape pattern index. Cropland and urban land were closely correlated with deteriorating water quality, with contributions to total nitrogen, total phosphorous, and ammonia nitrogen in the basin. The impact of the landscape pattern of the basin on water quality was controlled by the original land-use type. In addition, the landscape configuration formed different land-use types to produce different effects on water quality. The basin scale better explained the changes in water quality, especially for construction land, followed by the 250 m and 500 m scales in the buffer zone.

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

In recent years, the Cerrado biome in Brazil (Brazilian savannah) has faced severe environmental problems due to abrupt changes in land use/cover (LUC), causing increased soil loss, sediment yield and water turbidity. Thus, this study aimed to evaluate the impacts of soil loss and sediment delivery ratio (SDR) over the last 30 years to simulate future scenarios of soil losses from 2050 to 2100 and to investigate an episode of sediment delivery that occurred in the Rio da Prata Basin (RPB) in 2018. In this study, the following were used: an estimation of soil losses for 1986, 1999, 2007 and 2016 using the Revised Universal Soil Loss Equation (RUSLE), an estimation of SDR, sediment export and sediment deposition using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model, an association of RUSLE factor C to LUC data for 2050 and 2100 based on the CA-Markov hybrid model, and an estimation of future soil erosion scenarios for 2050 and 2100. The results show that over the last 30 years (1986-2016), there has been a reduction in the areas of highly intense and severe degrees. Future soil erosion scenarios (2050-2100) showed a 13.84% increase in areas of soil loss >10 Mg ha^-1 year^-1. The results highlighted the importance of assessing the impacts of LUC changes on soil erosion and the export of sediments to agricultural watersheds in the RPB, one of the best ecotourism destinations in Brazil. In addition, the increase in soil loss in the region intensified sediment yield events and increased water turbidity. Furthermore, riparian vegetation, although preserved, was not able to protect the watercourse, showing that it is essential to adopt the best management practices in the agricultural production areas of the basin, especially where ramps are extensive or the slope is greater than 2%, to reduce the runoff velocity and control the movement of sediments on the surface towards the drainage canals. The results of this study are useful for drawing up a soil and water conservation plan for the sustainable production of agriculture and maintenance of ecosystem services in the region.

The effect of different land use planning scenarios on the amount of total soil losses in the Mikail Stream Micro-Basin

Erosion is seen as a major productivity problem in the world. Unplanned agricultural practices caused by human activities initiate the soil erosion process. Especially in sloping areas, agricultural activities without soil conservation measures accelerate this process. This study prepared land use planning (LUP) scenarios to reduce soil losses in the Mikail Stream Micro-Basin, which has an erosion problem and a rough topography. ILSEN land evaluation method, which is formed by interpreting FAO land evaluation principles according to Turkish conditions, was used in the creation of the scenarios. Soil conservation (terracing and contour agriculture) land-use types (LUT) that can help in erosion reduction were included in the ILSEN method and 8 different LUP scenarios were created. Soil protected (terracing and contour farming) LUTs that can help reduce erosion were included in the ILSEN method and 8 different LAP scenarios were created. The RUSLE Method integrated with the Geographic Information System (GIS) was used to calculate the estimated amount of soil loss caused by the scenarios created. For land evaluation and erosion studies, serial-based soil map of the area and Google Earth images were used. Scenario 7 created has reduced soil loss by 79% compared to the present land use (Scenario 8) of the basin. While the soil loss caused by the present land-use of the basin was 335.95 tons ha^-1 year^-1 on average, the amount of soil loss caused by the 7th scenario was calculated as 69.05 tons ha^-1 year^-1 on average. The results showed that the ILSEN land evaluation method can be a model to be used in the creation of erosion-reducing LUP scenarios in areas with erosion problems.

Assessment of soil erosion extent using RUSLE model integrated with GIS and RS: the case of Megech-Dirma watershed, Northwest Ethiopia

Soil erosion valuation at a spatial scale is crucial for assessing natural resource quality in a farming country like Ethiopia. The study's goal was to determine the rate of soil erosion in the Megech-Dirma catchment in Northwest Ethiopia using the Revised Universal Soil Loss Equation model aggregation with Geographic Information System and Remote Sensing. Sediment yield and transport were also estimated using sediment delivery ratio. Revised Universal Soil Loss Equation model data inputs included precipitation data for the R value, soil data for the K value, land cover data from satellite images for the C and P value, and topographical data from a Digital Elevation Model for the LS component. It was completed using the ArcGIS 10.4 software. The mean annual soil loss is 110.60 t ha^-1 yr^-1. Each year, a total of 8499.74 t ha^-1 yr^-1 of soil eroded and on average resulting in 1605.30 t/km²/yr, sediment material has been transported to the stream channels and deposited with a sediment delivery ratio of 1.87. The strength of soil erosion in the area is divided into six categories. The erosion rate classes were 46.38 percent (0-12 t ha^-1 yr^-1) low, 13.63 percent (12-20 ha^-1 yr^-1) moderate, 9.22 percent (20-35 ha^-1 yr^-1) high, 12.30 percent (35-50 ha^-1 yr^-1) very high, 7.20 percent (50 up to 100 ha^-1 yr^-1) severe, and 11.27 percent (>100 ha^-1 yr^-1) very severe erosion. According to erosion severity, 46.38 percent of the watershed is at risk of low erosion, while 11.27 percent is at risk of extremely severe erosion. The north and northeastern sections of the watershed have a moderate to extremely severe erosion risk due to steep slopes, high rainfall, and weak conservation measures. The severely eroded parts of the plateau and steep portions are proposed to be covered by plantation, stone bund, and check dam constructions.

Spatio-temporal Differentiation of Coupling Coordination between Ecological Footprint and Ecosystem Service Functions in the Aksu Region, Xinjiang, China

The ecological footprint and ecosystem service functions in the northwest arid region of China have their unique characteristics and are limited by natural resources. The coordination level between the pressure of human activities on the ecosystem and the ecosystem service capacity can be objectively reflected on by exploring the coupling coordination relationship between these two aspects. This work used the ecological footprint and Integrated Valuation of Ecosystem Services and Trade-offs models to quantitatively analyze the spatial and temporal variations of the ecological footprint and ecosystem service functions in the Aksu region in Xinjiang. A coupling coordination degree model and spatial autocorrelation analysis were used to assess the coupling coordination level and spatial agglomeration characteristics of the regional ecological footprint and ecosystem service functions. The results showed that the ecological footprint of the Aksu region has been high in the northeast and low in the southwest, with noticeable spatial heterogeneity, from 2005 to 2018. Carbon (66.17%) and cropland (26.64%) are the main contributing factors to the regional ecological footprint. The biocapacity is dominated by cropland, built-up land, and forest land. The ecological footprint and biocapacity showed an increasing trend, ranging from an ecological surplus to an ecological deficit, with a continued ecological deficit. The level of ecosystem service functions in the Aksu region was low, with significant spatial variability. The high values were concentrated in the northern part of the region and the Tarim and Hotan River Basins. The coupling coordination level of the ecological footprint and ecosystem service functions in the Aksu area was high in the north and low in the south. The aforementioned coupling coordination level was dominated by the spatial pattern of the ecosystem service functions and had noticeable spatial agglomeration characteristics. The coupling coordination degree of the ecological footprint and water supply function showed an upward trend. By contrast, the coupling coordination degree of the ecological footprint with soil conservation and biodiversity maintenance functions showed a downward trend.

Expressing carbon storage in economic terms: The case of the upper Omo Gibe Basin in Ethiopia

Terrestrial carbon storage is important for planning decisions regarding climate change. Therefore, modelling the spatial distribution of carbon storage and valuation can help restore the sustainability of the ecosystems. This study aimed at showing the spatial and temporal variations in carbon storage and valuation in the upper Omo Gibe Basin. Land use/cover and carbon pool data based on field data collection and laboratory analyses supported by GIS and remote sensing were used. The Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) software was used for modelling carbon storage. The Global voluntary carbon market price and Tropical Economics of Ecosystems and Biodiversity (TEEB) data were used for describing carbon storage in economic terms. ANOVA was carried out to detect significant differences in carbon stock correlation with parameters. The results show that the annual carbon stock declined by 0.37 t/ha and the carbon market declined from USD 25.04 billion in 1988 to USD 24.01 billion in 2018. The highest loss of carbon storage and valuation was found in forest land followed by grazing land. Moreover, carbon stock was positively correlated with NDVI and habitat quality (p < 0.05). Slopes did not affect carbon stock (p > 0.05). This study helps promote and enhance carbon trading.

Exploring the Effects of Land Use Changes on the Landscape Pattern and Soil Erosion of Western Hubei Province from 2000 to 2020

Accelerated land use and land cover changes affect regional landscape patterns and change the ecological environment, including soil conservation capabilities. This is not conducive to the sustainable development of human society. In this research, we explored the land use change pattern and landscape change pattern in western Hubei from 2000 to 2020. Using the Chinese soil loss equation and stepwise regression, we measure how landscape patterns affect soil erosion under land use and cover changes in western Hubei Province. The results show that average soil erosion in the mountainous areas of western Hubei tended to increase from 2000 to 2010 and decrease from 2010 to 2020; soil erosion was higher in the western than in the eastern part of the study area. The land in areas with high-intensity and low-intensity soil erosion was mainly waterfront/grassland and cropland/forestland, respectively, and the area of moderate to severe soil erosion was greatest when the slope was 10–20°. When the slope exceeded 20°, the soil erosion area of each grade tended to decrease; thus, 20° is the critical slope for soil erosion in the study area. The landscape pattern in mountainous areas changed dramatically from 2000 to 2020. At the landscape level, landscape fragmentation increased and connectivity decreased, but the area of landscape diversity was stable. Soil erosion in western Hubei was positively correlated with the contiguity index, aggregation index and largest patch index but negatively correlated with the Shannon evenness index. The higher the landscape fragmentation and the greater the accumulation of single land-use types, the more severe the soil erosion is, while the higher the landscape connectivity and the richer the landscape diversity, the less severe the soil erosion is. The results can inform regional landscape management and soil conservation research.

Spatial-Temporal Responses of Ecosystem Services to Land Use Transformation Driven by Rapid Urbanization: A Case Study of Hubei Province, China

Exploring the changes of ecosystem services value caused by land use transformation driven by urbanization is crucial for ensuring the safety of the regional ecological environment and for enhancing the value of ecosystem services. Based on the land use remote sensing data during the rapid urbanization development period of Hubei Province from 1995 to 2015, this study analyzed the characteristics of land use/land cover change and land use transformation. The spatial-temporal response characteristics and evolution of ecosystem services value (ESV) to land use transformation driven by urbanization were measured by equivalent factor method, spatial autocorrelation analysis, hot spot analysis and gravity model. We found that: (1) Driven by urbanization, the most significant feature of land use transformation in Hubei Province was the expansion of the built-up land and the significant reduction of cropland and forest, among which 90% of the new built-up land was converted from cropland and forest. (2) This land use transformation became the main source of ESV losses. Especially, the sharp increase of the built-up land from 2010 to 2015, occupying cropland and forest, resulted in ESV losses of nearly USD 320 million. The service capacity of climate regulation, soil conservation, gas regulation and food production undertaken by cropland and forest decreased. (3) The ecosystem services value in the study area showed spatial distribution characteristics of high in the west and low in the middle and east regions. The center of gravity of ESV shifted from northwest to southeast. Due to the sharp increase of the built-up land from 2010 to 2015, the center of gravity shift rebounded. This study can help policymakers better understand the trade-offs between land use transformation and ecosystem services driven by urbanization.

Suitable Land-Use and Land-Cover Allocation Scenarios to Minimize Sediment and Nutrient Loads into Kwan Phayao, Upper Ing Watershed, Thailand

Human activity and land-use changes have affected the water quality of Kwan Phayao, Upper Ing watershed, due to the associated high sediment load and eutrophication. This study aims to identify suitable LULC allocation scenarios for minimizing sediment and nutrient export into the lake. For this purpose, the LULC status and change were first assessed, based on classified LULC data in 2009 and 2019 from Landsat images, using the SVM algorithm. Later, the land requirements of three scenarios between 2020 and 2029 were estimated, based on their characteristics, and applied to predict LULC change using the CLUE-S model. Then, actual LULC data in 2019 and predicted LULC data under three scenarios between 2020 and 2029 were used to estimate sediment and nutrient export using the SDR and NDR models. Finally, the ecosystem service change index identified a suitable LULC allocation for minimizing sediment or/and nutrient export. According to the results, LULC status and change indicated perennial trees and orchards, para rubber, and rangeland increased, while forest land and paddy fields decreased. The land requirements of the three scenarios provided reasonable results, as expected, particularly Scenario II, which adopts linear programming to calculate the land requirements for maximizing ecosystem service values. For sediment and nutrient export estimation under the predicted LULC for the three scenarios, Scenario II led to the lowest yield of sediment and nutrient exports, and provided the lowest average ESCI value among the three scenarios. Thus, the LULC allocation under Scenario II was chosen as suitable for minimizing sediment or/and nutrient export into Kwan Phayao. These results can serve as crucial information to minimize sediment and nutrient loads for land-use planners, land managers, and decision makers.

Allometric equations for selected Acacia species (Vachellia and Senegalia genera) of Ethiopia

BACKGROUND

Allometric equations are used to estimate biomass and carbon stock of forests. In Ethiopia, despite the presence of large floral diversity, only a few site-specific allometric equations have been developed so far. This study was conducted in the Omo-Gibe woodland of south-western Ethiopia to develop an allometric equation to estimate the Above-ground Biomass (AGB) of the four Acacia species (Senegalia polyacantha, Vachellia seyal, Vachellia etbaica and Vachellia tortilis). Fifty-four (54) Acacia trees were sampled and measured within 35 temporarily established square plots. In each plot, dendrometric variables were measured to derive the models based on combinations of Diameter at Breast Height (DBH), height, and wood density as predictor variables. Model performance was evaluated using goodness-of-fit statistics. The biomass was compared using four allometric biomass models that have been widely used in the tropics.

RESULTS

The model containing DBH alone was more accurate to estimate AGB compared to the use of multiple predictor variables. This study, therefore, substantiated the importance of site-specific allometric equations in estimating the AGB of Acacia woodlands. This is because a site-specific allometric equation recognizes the environmental factors, vegetation types and management practices.

CONCLUSIONS

The results of this study contribute to a better understanding of allometric equations and an accurate estimate of AGB of Acacia woodlands in Ethiopia and similar ecosystems elsewhere.

Impact of landscape pattern changes on hydrological ecosystem services in the Beressa watershed of the Blue Nile Basin in Ethiopia

Landscape pattern changes are mostly due to human activities, and such changes often affect ecosystem functions and services. This study was conducted to evaluate the response of hydrological ecosystem services (HESs) to structural landscape changes. Spatiotemporal changes in two specific HES indicators, water yield (WY) and sediment export (SE), were quantified by analyzing historic (1972-2017) and projected land use/land cover changes (2017-2047). The Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) Model was used for this purpose. Results indicated that WY and SE changed significantly (p ˂ 0.01) during the study period. The total WY and SE increased by 30.29% and 98.69%, respectively, between 1972 and 2017. Analysis of the projections for the next three decades (2017-2047) suggested an increase in WY and SE by 4.8% and 93.11%, respectively. Furthermore, results revealed that WY and SE are strongly influenced by landscape composition, and metrics such as percentage of landscape (PLAND), mean patch size (MPS), and large patch index (LPI) of farmland and plantations were found to be key factors affecting HESs degradation in the Beressa watershed. PLAND (VIP = 1.34; w = 0.55; and VIP = 1.32; w = 0.56) and MPS (VIP = 1.32; w = 0.50 and VIP = 1.31; w = 0.56)) of farmland cover contributed most to the changes in WY and SE, respectively. Similarly, PLAND (VIP = 1.33; w = 0.54 and VIP = 1.28; w = 0.52), LPI (VIP = 1.27; w = 0.52 and VIP = 1.30; w = 0.54) and MPS (VIP = 1.29; w = 0.52) of plantation cover also contributed more to the change in WY and SE. Besides that, of anthropogenic factors, compositions of natural vegetation and grassland cover were found to heavily influence HESs in the watershed studied. The findings of the study suggest that soil and water conservation interventions are vital to minimize and control water-related problems and enhance ESs.

Detecting the Complex Relationships and Driving Mechanisms of Key Ecosystem Services in the Central Urban Area Chongqing Municipality, China

Ecosystem services (ESs) are highly vulnerable to human activities. Understanding the relationships among multiple ESs and driving mechanisms are crucial for multi-objective management in complex social-ecological systems. The goals of this study are to quantitatively evaluate and identify ESs hotspots, explore the relationships among ESs and elucidate the driving mechanisms. Taking central urban area Chongqing municipality as the study area, biodiversity (BI), carbon fixation (CF), soil conservation (SC) and water conservation (WC) were evaluated based on the InVEST model and ESs hotspots were identified. The complex interactions among multiple ESs were determined by utilizing multiple methods: spearman correlation analysis, bivariate local spatial autocorrelation and K-means clustering. The linear or nonlinear relationships between ESs and drivers were discussed by generalized additive models (GAMs). The results showed that during 2000–2018, except for CF that exhibited no obvious change, all other ESs showed a decrease tendency. High ESs were clustered in mountains, while ESs in urban areas were lowest. At administrative districts scale, ESs were relatively higher in Beibei, Banan and Yubei, and drastically decreased in Jiangbei. Multiple ES hotspots demonstrated clear spatial heterogeneity, which were mainly composed of forestland and distributed in mountainous areas with high altitude and steep slope. The relationships between ES pairs were synergistic at the entire scale. However, at grid scale, the synergies were mainly concentrated in the high-high and low-low clusters, i.e., mountainous areas and urban central areas. Five ESs bundles presented the interactions among multiple ESs, which showed well correspondence with social-ecological conditions. GAMs indicated that forestland and grassland had positive impact on BI and CF. Additionally, SC was mainly determined by geomorphological factors, while WC were mainly influenced by precipitation. Furthermore, policy factors were confirmed to have a certain positive effect on ESs. This study provides credible references for ecosystem management and urban planning.

Spatial Variation and Terrain Gradient Effect of Ecosystem Services in Heihe River Basin over the Past 20 Years

With the advent of large-scale development, extreme imbalance in the ecology of the Heihe River Basin (HRB) has caused a series of ecological problems. In order to explore the spatiotemporal variation of ecosystem services (ESs) and to assess the characteristics of ESs under the terrain gradient effect (TGE), the three key ESs were quantified based on the InVEST model using five series of land-use data obtained from remote sensing images from 2000 to 2020 in this study. The terrain index was used to analyze the influence of terrain on ESs. The results show that most of the ESs were in high numbers in the south and low numbers in the north, as well as high numbers in the middle and upper reaches and low numbers at downstream locations. It was found that high-quality habitats degrade to general-quality habitats, and poor-quality habitats evolve into general-quality habitats. It was also found that the water production volume continues to decline and soil conservation becomes relatively stable with little change. This study illustrates different ESs showing obvious TGE with changes in elevation and slope. These results indicate that the effect of land-use change is remarkable and TGE is highly important to ESs in inland watersheds. This research study can provide a scientific basis for the optimization of regional ecosystem patterns. The results are of great significance in terms of rational planning land use, constructing ecological civilizations, and maintaining the physical conditions of land cover at inland river basins.

Assessment of Soft Computing Techniques for the Prediction of Suspended Sediment Loads in Rivers

A key goal of sediment management is the quantification of suspended sediment load (SSL) in rivers. This research focused on a comparison of different means of suspended sediment estimation in rivers. This includes sediment rating curves (SRC) and soft computing techniques, i.e., local linear regression (LLR), artificial neural networks (ANN) and the wavelet-cum-ANN (WANN) method. Then, different techniques were applied to predict daily SSL at the Pirna and Magdeburg Stations of the Elbe River in Germany. By comparing the results of all the best models, it can be concluded that the soft computing techniques (LLR, ANN and WANN) better predicted the SSL than the SRC method. This is due to the fact that the former employed non-linear techniques for the data series reconstruction. The WANN models were the overall best performer. The WANN models in the testing phase showed a mean R2 of 0.92 and a PBIAS of −0.59%. Additionally, they were able to capture the suspended sediment peaks with greater accuracy. They were more successful as they captured the dynamic features of the non-linear and time-variant suspended sediment load, while other methods used simple raw data. Thus, WANN models could be an efficient technique to simulate the SSL time series because they extract key features embedded in the SSL signal.

The Spatiotemporal Dynamics of Land Use Land Cover Change, and Its Impact on Soil Erosion in Tagaw Watershed, Blue Nile Basin, Ethiopia

The Blue Nile basin is one of the hot-spots of soil erosion areas in Ethiopia. However, the impact of land use changes on soil erosion is poorly understood in the Tagaw watershed. Hence, the objective of the study is to assess the impact of land use changes on soil erosion in Tagaw watershed over the last 31 years. Rainfall, soil, satellite images and topographic data are acquired from field survey and secondary sources. A Revised Universal Soil Loss Equation (RUSLE) model is used to estimate soil erosion. The mean annual and total potential soil losses of the watershed are 19.3, 22.9, 26 and 0.06-503.56, 0.11-516.67, and 0.00-543.5 tons ha-1 yr-1 for 1995, 2006 and 2016 respectively. The highest soil loss is found for bare land. The RUSLE model further showed that the highest soil erosion occurred in 2016 whereas the lowest soil erosion occurred in 1995.

Spatial Differentiation and Driving Factor Analysis of Urban Construction Land Change in County-Level City of Guangxi, China

The change of urban construction land is most obvious and intuitive in the change of global land use in the new era. The supply and allocation of construction land is an important policy tool for the government to carry out macro-control and spatial governance, which has received widespread attention from political circles, academia, and the public. An empirical study on the change of construction land and its driving factors in 70 county-level cities in Guangxi, China based on the GeoDetector method reveals the driving mechanism of the construction land change in county-level cities and provides more detailed information and a more accurate basis for county-level city policy makers and decision makers. The study shows a significant heterogeneity in the action intensity and interaction between construction land change and its driving factors in county-level cities, where population and GDP size, transportation, and industrial structure are determining factors. Besides, the factors of fiscal revenue, social consumption, utility investment, and real economy have a very weak action force individually, but they can achieve significant synergistic enhancement effects when coupled with other factors. In the end, urban construction land change at different scales and their driving mechanisms are somewhat different, and it is recommended to design differentiated and precise construction land control and spatial governance policies according to local conditions.

Quantitative Analysis of Factors Influencing Spatial Distribution of Soil Erosion Based on Geo-Detector Model under Diverse Geomorphological Types

The Loess Plateau of China suffers from severe erosion, which results in a great variety of economic and ecological problems. For scientific control of soil erosion, the key questions urgently to be addressed in this paper are: (1) Which are the driving factors under diverse geomorphological types? (2) Do these driving factors operate independently or by interacting? (3) Which zones under diverse geomorphological types suffer from severe erosion and need more attention? In this paper, the RUSLE model was applied here to demonstrate the spatio-temporal variations in soil erosion from 2010 to 2017 in Yan’an City, and the Geo-detector model proved to be a useful tool to solve the questions mentioned above. The results showed that the average erosion modulus in Yan’an City decreased by 1927.36 t/km2·a from 2010 to 2017. The intensity of soil erosion in the northern Baota District, central Ganquan County, Luochuan County, Ansai County, and Zhidan County decreased to varying degrees. The effect size of driving factors affecting soil erosion varied significantly in diverse geomorphological types. The effect size of interaction between land-use types and vegetation coverage, land-use types and slope, slope and precipitation was higher than that of a single factor. High-risk zones with severe erosion were closer to cultivated land and forest land with steep slopes (>25°) in the mid-elevation hills of Yan’an City. Additionally, based on the specificity of the study area, the Geo-detector model performed better in a relatively flat region, and factors with macroscopic spatial distributions weaken its explanatory power on soil erosion on a regional scale. Based on data selection, data of different accuracy sparked the issue of “data coupling”, which led to the enormous deviation of model results in mid-elevation plains. Results from our analysis provide insights for a more ecologically sound development of Yan’an City and provide references for the scientific use of the Geo-detector model.

Modelling Sediment Retention Services and Soil Erosion Changes in Portugal: A Spatio-Temporal Approach

Soils provide important regulating ecosystem services and have crucial implications for human well-being and environmental conservation. However, soil degradation and particularly soil erosion jeopardize the maintenance and existence of these services. This study explores the spatio–temporal relationships of soil erosion to understand the distribution patterns of sediment retention services in mainland Portugal. Based on Corine Land Cover maps from 1990 to 2018, the InVEST Sediment Delivery Ratio (SDR) model was used to evaluate the influence of sediment dynamics for soil and water conservation. Spatial differences in the sediment retention levels were observed within the NUTS III boundaries, showing which areas are more vulnerable to soil erosion processes. Results indicated that the Region of Leiria, Douro and the coastal regions have decreased importantly in sediment retention capacity over the years. However, in most of the territory (77.52%), changes in sediment retention were little or were not important (i.e., less than 5%). The statistical validation of the model proved the consistency of the results, demonstrating that the InVEST SDR model is an appropriate tool for estimating soil loss potential by water at regional/national levels, although having its limitations. These findings can be relevant to support strategies for more efficient land-use planning regarding soil erosion mitigation practices and to stimulate further investigation at a national level on this important ecosystem service.

Responses of Runoff and Soil Loss to Rainfall Regimes and Soil Conservation Measures on Cultivated Slopes in a Hilly Region of Northern China

Cultivated land plays an important role in water and soil loss in earthy/rocky mountainous regions in northern China, however, its response to soil conservation measures and rainfall characteristics are still not fully understood. In the present study, 85 erosive rainfall events in 2011–2019 were grouped into three types, and the responses of runoff and soil loss to soil conservation measures and rainfall regimes on five cultivated plots with different slopes in the upstream catchment of the Miyun Reservoir were evaluated. Results found that mean event runoff depths and soil loss rates on the five plots ranged from 0.03 mm to 7.05 mm and from 0.37 t km⁻² to 300.51 t km⁻² respectively, depending on rainfall regimes, soil conservation measures, and slope gradients. The high frequency (i.e., 72.94%) rainfall regime A with a short rainfall duration (RD), low rainfall amount (P), and high mean rainfall intensity (I_m) yielded a lower runoff depth and higher soil loss rate. Rainfall regime B with a longer RD, and a higher P and I_m, however, produced higher a runoff depth and lower soil loss rate. Terraced plots had the highest runoff and soil loss reduction efficiencies of over 96.03%. Contour tillage had comparable sediment reduction efficiency to that of the terraced plots on gentle slopes (gradient less than 11.0%), while its runoff reduction efficiency was less than 13.11%. This study implies that in the Miyun Reservoir catchment and similar regions in the world, contour tillage should be promoted on gentle slopes, and the construction of terraced plots should be given ample consideration as they could greatly reduce water quantity and cause water shortages in downstream catchments.

Water Erosion Risk Assessment in the Kenya Great Rift Valley Region

The Kenya Great Rift Valley (KGRV) region unique landscape comprises of mountainous terrain, large valley-floor lakes, and agricultural lands bordered by extensive Arid and Semi-Arid Lands (ASALs). The East Africa (EA) region has received high amounts of rainfall in the recent past as evidenced by the rising lake levels in the GRV lakes. In Kenya, few studies have quantified soil loss at national scales and erosion rates information on these GRV lakes’ regional basins within the ASALs is lacking. This study used the Revised Universal Soil Loss Equation (RUSLE) model to estimate soil erosion rates between 1990 and 2015 in the Great Rift Valley region of Kenya which is approximately 84.5% ASAL. The mean erosion rates for both periods was estimated to be tolerable (6.26 t ha−1 yr−1 and 7.14 t ha−1 yr−1 in 1990 and 2015 respectively) resulting in total soil loss of 116 Mt yr−1 and 132 Mt yr−1 in 1990 and 2015 respectively. Approximately 83% and 81% of the erosive lands in KGRV fell under the low risk category (<10 t ha−1 yr−1) in 1990 and 2015 respectively while about 10% were classified under the top three conservation priority levels in 2015. Lake Nakuru basin had the highest erosion rate net change (4.19 t ha−1 yr−1) among the GRV lake basins with Lake Bogoria-Baringo recording annual soil loss rates >10 t ha−1 yr−1 in both years. The mountainous central parts of the KGRV with Andosol/Nitisols soils and high rainfall experienced a large change of land uses to croplands thus had highest soil loss net change (4.34 t ha−1 yr−1). In both years, forests recorded the lowest annual soil loss rates (<3.0 t ha−1 yr−1) while most of the ASAL districts presented erosion rates (<8 t ha−1 yr−1). Only 34% of all the protected areas were found to have erosion rates <10 t ha−1 yr−1 highlighting the need for effective anti-erosive measures.

The Impact of Land Use Change on Water-Related Ecosystem Services in the Bashang Area of Hebei Province, China

Land use change is an important scientific issue recognized for its potential to alter ecosystem services (ESs), especially water-related ecosystem services (WRESs). Using the integrated valuation of ecosystem services and trade-offs (InVEST) model, this study quantified and mapped spatiotemporal variations in land use and corresponding WRESs in the Bashang area of Hebei Province, China (BAHP) to investigate how land use change impacted WRESs by means of scenario analysis, especially, in which a new evaluation indicator, average ecology effect (AEE) was proposed and well applied. The results indicated that woodland expansion (+602.61 km2) and grassland shrinkage (−500.57 km2) dominated the land use change in the BAHP in 2000–2018, which altered local WRESs, including the moderate declines in water purification and water yield, as well as a significant enhancement in soil conservation. In scenario analysis, compared to baseline levels, riparian woodland buffer and planting trees scenarios slightly decreased water yield but strengthened water purification and soil conservation; reclaiming wasteland and integrated development scenarios significantly enhanced soil conservation but lowered water yield and water purification; fertilizer reduction scenario effectively mitigated water deterioration. According to AEE, the riparian woodland buffer (RWB) scenario performed greater than the planting trees (PT) scenario on variations of WRESs per unit area, which differed completely from the results based on total variations. Overall, a multiple-scale indicator for a comprehensive evaluation of ESs should receive more attention.