Search Results (43)

This study investigates the anthropogenic transformation of small- and medium-sized river basins within the Caspian Sea catchment. The basins of seven rivers—Sunzha, Sulak, Ulluchay, Karachay, Atachay, Haraz, and Gorgan—were selected as key study areas. For both the broader Caspian region, particularly its southwestern sector, and the selected study sites, trends in land cover types were analyzed, natural resource use practices were assessed, and population density dynamics were examined. Furthermore, a range of indices were calculated to quantify the degree of anthropogenic transformation, including the coefficient of anthropogenic transformation, the land degradation index, the urbanity index, the degree of anthropogenic transformation, coefficients of absolute and relative tension of the ecological and economic balance, and the natural protection coefficient. The study was conducted using geoinformation research methods and sets of geodata databases—the global LandScan population density database, the GHS Population Grid database, the ESRI land cover type dynamics database, and OpenStreetMap (OSM) data. The analysis was performed using the geoinformation programs QGIS and ArcGIS, and a large amount of literary and statistical data was additionally analyzed. It is shown that within the studied region, there has been a decrease in the number and density of the population, as a result of which the territories of river basins are experiencing an increasing anthropogenic impact, the woody type of land cover is decreasing, and the agricultural type is increasing. The most anthropogenically transformed river basins are Karachay, Haraz, and Gorgan. Full article

Phosphorus is the primary contributor to eutrophication in water bodies, and identifying phosphorus sources in rivers is crucial for controlling phosphorus pollution and subsequent eutrophication. Although phosphate oxygen isotopes (δ¹⁸O_P) have the capacity to trace phosphorus sources and cycling in water and sediments, they have not been used in small- to medium-sized watersheds, such as the Xiaodongjiang River (XDJ), which is located in an agricultural watershed, source–complex region of southern China. This study employed phosphate oxygen isotope techniques in combination with a land-use-based mixed end-member model and the MixSIAR Bayesian mixing model to quantitatively determine potential phosphorus sources in surface water and sediments. The δ¹⁸O_P values of the surface water ranged from 5.72‰ to 15.02‰, while those of sediment ranged from 10.41‰ to 16.80‰. In the downstream section, the δ¹⁸O_P values of the surface water and sediment were similar, suggesting that phosphate in the downstream water was primarily influenced by endogenous sediment control. The results of the land-use–source mixing model and Bayesian model framework demonstrated that controlling phosphorus inputs from fertilizers is essential for reducing phosphorus emissions in the XDJ watershed. Furthermore, ongoing rural sewage treatment, manure management, and the resource utilization of aquaculture substrates contributed to reduced phosphorus pollution. This study showed that isotope techniques, combined with multi-model approaches, effectively assessed phosphorus sources in complex watersheds, offering a theoretical basis for phosphorus pollution management to prevent eutrophication. Full article

This investigation endeavors to demarcate the boundaries of small- and medium-sized river catchments within the Caspian Sea drainage basin, with a specific focus on the Northeastern Caucasus, Azerbaijan, and Iran regions. A multi-faceted approach was employed, incorporating various remote sensing methods to select key areas, including the catchments of the Sunzha, Sulak, Ulluchay, Karachay, Atachay, Haraz, and Gorgan rivers. Subsequently, geoinformation systems (GISs) and topographic maps were utilized to determine the morphometric characteristics of these catchments, accompanied by an assessment of the accuracy of remote sensing data. The aim of this study is to evaluate the accuracy and suitability of digital elevation models (DEMs) with a spatial resolution of 30 m per pixel (including ASTER DEM, ALOS DEM, NASADEM, Copernicus 30 m DEM, and SRTM 30 m DEM) and 90 m per pixel (Copernicus 90 m DEM and SRTM 90 m DEM) for delineating small- and medium-sized Caspian Sea basin river catchments. For the DEMs that successfully and accurately delineated watershed boundaries, the morphometric characteristics of the river basins were calculated. This research has yielded novel findings regarding the morphometric characteristics (area, perimeter, ruggedness of the catchment line (roundness coefficient), maximum height, minimum height, average height of the river basin, maximum slope of the surface, average slope of the surface, length of the main watercourse, basin shape parameter (catchment elongation coefficient), shape coefficient, length of the river basin, average river basin slope, and average width of the basin) of individual mountainous small- and medium-sized rivers in the Northeastern Caucasus, Azerbaijan, and Iran, with the catchments of the aforementioned rivers serving as exemplars. The practical significance of these results lies in the fact that such detailed morphometric characteristics of catchments have been obtained for the first time, and their boundaries have been clarified (burned out according to various DEMs), which can serve as a basis for decision-making processes and contribute to the development of operational environmental monitoring of the state of rivers and their catchments. Full article

Several small- and medium-sized rivers connecting to the Shichiri-Mihama coast are closed due to debris. The progression of river mouth closures increases the risk of flooding in the watershed, so countermeasures are necessary. In this study, piles were installed in a staggered pattern to prevent river mouth closures. The hydraulic model experiment was conducted to assess how countermeasure (staggered piles) installation affects topographic change under various wave conditions. The installation of the staggered piles was found to be effective in moving the location of the berm forward more than 10 cm offshore and reducing gravel accumulation by up to 57%. The effect of the staggered piles is particularly significant in wave conditions with small wave gradients. The pile row spacing should be short to maintain the complexity of the staggered arrangement. The effects of changes in the flow velocity field and differences in the bottom sediment should also be considered for practical use. Eventually, the installation of the staggered piles will be expected to prevent the long-term development of berms, thus preventing estuary closure. Full article

The crown area is a critical metric for evaluating tree growth and supporting various ecological and forestry analyses. This study compares three approaches, i.e., unsupervised clustering, region-based, and deep learning, to estimate the crown area of Pinus eldarica Medw. using UAV-acquired RGB imagery (2 cm ground sampling distance) and high-density point clouds (1.27 points/cm³). The first approach applied unsupervised clustering techniques, such as Mean-shift and K-means, to directly estimate crown areas, bypassing tree top detection. The second employed a region-based approach, using Template Matching and Local Maxima (LM) for tree top identification, followed by Marker-Controlled Watershed (MCW) and Seeded Region Growing for crown delineation. The third approach utilized a Convolutional Neural Network (CNN) that integrated Digital Surface Model layers with the Visible Atmospheric Resistance Index for enhanced segmentation. The results were compared against field measurements and manual digitization. The findings reveal that CNN and MCW with LM were the most effective, particularly for small and large trees, though performance decreased for medium-sized crowns. CNN provided the most accurate results overall, with a relative root mean square error (RRMSE) of 8.85%, a Nash–Sutcliffe Efficiency (NSE) of 0.97, and a bias score (BS) of 1.00. The CNN crown area estimates showed strong correlations (R² = 0.83, 0.62, and 0.94 for small, medium, and large trees, respectively) with manually digitized references. This study underscores the value of advanced CNN techniques for precise crown area and shape estimation, highlighting the need for future research to refine algorithms for improved handling of crown size variability. Full article

Small- and medium-sized reservoirs significantly alter natural flood processes, making it essential to understand their impact on runoff for effective water resource management. However, the lack of measured data for most small reservoirs poses challenges for accurately simulating their behavior. This study proposes a novel method that utilizes readily available satellite observation data, integrating hydraulic, hydrological, and mathematical formulas to derive outflow coefficients. Based on the Grid-XinAnJiang (GXAJ) model, the enhanced GXAJ-R model accounts for the storage and release effects of ungauged reservoirs and is applied to the Tunxi watershed. Results show that the original GXAJ model achieved a stable performance with an average NSE of 0.88 during calibration, while the NSE values of the GXAJ and GXAJ-R models during validation ranged from 0.78 to 0.97 and 0.85 to 0.99, respectively, with an average improvement of 0.03 in the GXAJ-R model. This enhanced model significantly improves peak flow simulation accuracy, reduces relative flood peak error by approximately 10%, and replicates the flood flow process with higher fidelity. Additionally, the area–volume model derived from classified small-scale data demonstrates high accuracy and reliability, with correlation coefficients above 0.8, making it applicable to other ungauged reservoirs. The OTSU-NDWI method, which improves the NDWI, effectively enhances the accuracy of water body extraction from remote sensing, achieving overall accuracy and kappa coefficient values exceeding 0.8 and 0.6, respectively. This study highlights the potential of integrating satellite data with hydrological models to enhance the understanding of reservoir behavior in data-scarce regions. It also suggests the possibility of broader applications in similarly ungauged basins, providing valuable tools for flood management and risk assessment. Full article

Rapid climate change and increasing water use have led to various problems in small- and medium-sized urban streams during dry periods, such as stream drying, water pollution, and ecological degradation, reducing their physical and ecological functions. Ensuring adequate baseflow and improving water quality during these critical periods are essential for maintaining urban stream health. While previous studies have explored the effects of Low Impact Development (LID) techniques (e.g., green roof, rainwater harvesting system, permeable pavement, infiltration trench) on infiltration and groundwater recharge, they have primarily focused on general flow regimes rather than dry and low-flow periods. This study specifically evaluates the effects of LID techniques on securing baseflow and improving water quality during dry periods, utilizing the SWAT-MODFLOW model and the Web-based Hydrograph Analysis Tool (WHAT) system. The results show that LID techniques reduce peak flow by an average of 27% and secure an additional 43% of baseflow during dry periods. Suspended solids (SS) and total phosphorus (T-P) concentrations were reduced by 15% and 41%, respectively. These findings demonstrate the effectiveness of LID techniques not only in managing stormwater runoff during flood events but also in maintaining baseflow and water quality during dry periods, thus providing valuable insights for sustainable urban watershed management. Full article

In the context of climate change, it is essential for sustainable development to assess the risks associated with climate change and human-induced vegetation degradation. The Hunshandake Sandy Land provides a variety of ecosystem services and is a substantial ecological security barrier in the Beijing–Tianjin–Hebei area of China. This study used the Normalized Difference Vegetation Index (NDVI) to analyze the spatiotemporal variation trend in vegetation in the Dabusennur Watershed using linear trend analysis and the GeoDetector model to identify the main drivers of vegetation change in the watershed. Finally, the study assessed the risk of ecological degradation in the vegetation of the watershed. The results show that the NDVI in the study area has had a fluctuating trend in the last 22 years, and the change has been small. Precipitation and groundwater depth are the key factors affecting vegetation change. The NDVI reaches its maximum value when the groundwater depth is at 2.75 m. The vegetation ecology of the basin is relatively fragile, mainly with medium risk and large risk. To cope with the ecological risk of vegetation degradation caused by climate change, appropriate water use strategies should be formulated to ensure ecological water use. The present study’s outcomes provide the basis for developing ecological engineering solutions in the arid and semi-arid parts of northern China. Full article

The results of topographic factor computations are highly sensitive to the setting of contributing area thresholds when applied to soil erosion modeling to evaluate soil erosion; however, the existing choice of contributing area thresholds is highly arbitrary. Meanwhile, due to regional-scale limitations, lower-resolution DEM data are usually used to calculate topographic factors, and with the fragmentation of land parcels in hilly areas of purple soil, lower-resolution DEM data respond to very limited topographic information. This study focuses on solving the mentioned issues by selecting the Lizixi watershed in a hilly area of purple soil as the research subject. It establishes a relationship equation between the resolution of DEM data and the optimal contributing area threshold. This is achieved by investigating the change in the contributing area threshold with the resolution of DEM data, determining the optimal contributing area threshold for different resolutions of DEM data, and establishing the relationship equation between the resolution of DEM data and the optimal contributing area threshold. Meanwhile, to solve the key problem of fragmented land parcels in the purple soil area, where the low-resolution and medium-resolution DEM data cannot accurately reflect the topographic information, combined with the principle of histogram matching, the downscaling model between the topographic factors under the low-resolution DEM data and the topographic factors under the high-resolution DEM data is established. This study confirms that the scale transformation model developed has a strong simulation effect, and the findings can offer technical assistance for the precise computation of soil erosion in small watersheds in hilly areas of purple soil. Full article

Although the theory of ecosystem services (ESs) is important for guiding land-use planning, knowledge of ESs trade-offs and supply–demand mechanisms is still lacking, and the characteristics of the correlation between the size of trade-offs and the balance between supply and demand along the precipitation gradient have not yet been clarified. In order to supplement this area of knowledge of ESs, we selected 30 small watersheds in high-, medium- and low-precipitation areas as study units. A biophysical model and socio-economic data were used to calculate supply and demand for carbon sequestration, soil conservation and water yield. Redundancy analysis and regression analysis were used to study the ESs trade-offs, the supply–demand dynamics, and the characteristics of their correlation. The results were as follows. (1) The supply and balance between supply and demand of the three ESs, the trade-off between carbon sequestration and water yield and the trade-off between soil conservation and water yield trended downwards from the high-precipitation area to the medium-precipitation area to the low-precipitation area. (2) The primary factors influencing balance between supply and demand with regard to carbon sequestration in high-, medium- and low-precipitation areas were population density and soil organic-matter content, and the size of the conditional effects were greater than 53%. The dominant factor affecting the balance between supply and demand with regard to soil conservation in the three precipitation areas was slope gradient, and the conditional effect was greater than 40%. The most significant determinants of balance between supply and demand with regard to water yield in the three precipitation areas were grassland area, forest area and precipitation, and the conditional effects were greater than 22%. (3) The most significant determinants of the trade-off between carbon sequestration and water yield in high-, medium- and low-precipitation areas were forest, soil organic-matter content and population density, and the conditional effects were all greater than 45%; the primary factors affecting the trade-off between soil conservation and water yield in high-, medium- and low-precipitation areas were grassland and slope gradient, and the conditional effects were all greater than 24%. (4) The relationship between the balance between supply and demand and trade-off size often followed a quadratic function; the next-most-common relationship was a monotonous nonlinear response, and a linear response relationship was relatively rare. This study revealed the factors influencing balance between supply and demand and trade-offs with regard to ESs and the characteristics of their correlations in areas with different degrees of precipitation, which provided a new idea for the synchronous regulation of ESs in the context of conflicts and supply–demand imbalance. Full article

The viewpoint and reaction of a country towards climate change are shaped by its political, cultural, and scientific backgrounds, in addition to the distinct characteristics of its evolving climate and the anticipated and actual consequences of the phenomenon in the times ahead. A region’s climate has a significant impact on how water is managed and used, mostly in the primary sector, and both the distribution of ecosystem types and the amount and spreading of species on Earth. As a result, the environment and agricultural practices are affected by climate, so evaluating both distribution and evolution is extremely pertinent. Towards this aim, the climate distribution and evolution in the São Francisco River basin (SFRB) is assessed in three periods (1970–2000, 1981–2022) in the past and 2041–2060 in the future from an ensemble of GCMs under two SSPs (Shared Socioeconomic Pathways), SSP2-4.5 and SSP5-8.5. The Köppen-Geiger (KG) climate classification system is analyzed, and climate change impacts are inferred for this watershed located in central-eastern Brazil, covering an area equivalent to 8% of the country. Results predict the disappearance of the hot summer (Csa) and warm summer (Csb) Mediterranean climates, and a reduction/increase in the tropical savanna with dry winter (Aw)/dry summer (As). A striking increase in the semi-arid hot (BSh-steppe) climate is predicted with a higher percentage (10%) under SSP5-8.5. The source and the mouth of SFRB are projected to endure the major impacts of climate change that are followed by a predicted increase/decrease in temperature/precipitation. Future freshwater resource availability and quality for human use will all be impacted. Consequences on ecosystems, agricultural, and socioeconomic sectors within the SFRB might deepen the current contrasts between regions, urban and rural areas, and even between population groups, thus translating, to a greater extent, the inequality that still characterizes Brazilian society. Maps depicting land use and cover changes in SFRB from 1985 to 2022 highlight tendencies such as urbanization, agricultural expansion, deforestation, and changes in shrubland and water bodies. Urban areas fluctuated slightly, while cropland significantly increased from 33.57% to 45.45% and forest areas decreased from 3.88% to 3.50%. Socioeconomic data reveals disparities among municipalities: 74.46% with medium Human Development Index (HDI), 0.59% with very high HDI, and 9.11% with low HDI. Most municipalities have a Gross Domestic Product (GDP) per capita below US$6000. Population distribution maps show a predominance of small to medium-sized urban and rural communities, reflecting the basin’s dispersed demographic and economic profile. To achieve sustainable adaptation and mitigation of climate change impacts in SFRB, it is imperative that integrated measures be conducted with the cooperation of stakeholders, the local population, and decision-makers. Full article

Geological hazards in Xinxian County, Xinyang City, Henan Province, are characterized by their small scale, wide distribution, and significant influence from regional tectonics. This study focuses on collapses and landslide hazards within the area, selecting twelve evaluation factors: aspect, slope shape, normalized difference vegetation index (NDVI), topographic relief, distance from geological structure, slope, distance from roads, land use cover type, area of land change (2012–2022), average annual rainfall (2012–2022), and river network density. Utilizing data from historical disaster sites across the region, the information quantity method and hierarchical analysis method are employed to ascertain the information quantity and weight of each factor. Subsequently, a random forest model is applied to perform susceptibility zoning of geological hazards in Xinxian County and to examine the characteristics of these geological disasters. The results show that in the study area, the primary factors influencing the development of geohazards are the distance from roads, rock groups, and distance from geological structure areas. A comparison of the susceptibility results obtained through two methods, the analytic hierarchy process information quantity method and the random forests model, reveals that the former exhibits a higher accuracy. This model categorizes the geohazard susceptibility in the study area into four levels: low, medium, high, and very high. Notably, the areas of very high and high susceptibility together cover 559.17 km², constituting 35.99% of the study area’s total area, and encompass 57 disaster sites, which represent 72.15% of all disaster sites. Geological hazards in Xinxian County frequently manifest on steep canyon inclines, along the curved and concave banks of mountain rivers, within watershed regions, on gully inclines, atop steep cliffs, and on artificially created slopes, among other sites. Areas with very high and high vulnerability to these hazards are mainly concentrated near the county’s geological formations. The gneiss formations are widely exposed in Xinxian County, and the gneisses’ strength is significantly changed under weathering, which makes the properties of the different degrees of weathering of the rock and soil bodies play a decisive role in the stability of the slopes. This paper provides a basis for evaluating and preventing geologic hazards in the Dabie mountainous area of the South Henan Province, and the spatial planning of the national territory. Full article

Assessing the impact of varied rainfall patterns on soil and water loss within a hilly watershed over an extended temporal scope holds paramount importance in comprehending regional runoff and sediment traits. This study utilized continuous rainfall and sediment data spanning from 2013 to 2021, and the K-means clustering method was employed to analyze rainfall types. Subsequently, the rain-type characteristics underwent further analysis through LSD, and a multiple linear regression equation was formulated. The result showed that: within the Qiaotou small basin, rainfall, maximum rainfall intensity within 30 min (I₃₀), and rainfall erosivity exhibited notable effects on sediment yield and loss. The water-sediment attributes of 305 rainfall events were characterized by rainfall below 100 mm, I₃₀ of less than 35 mm/h, a runoff coefficient below 0.5, and sediment content under 0.6 g/L. According to the characteristics of different rainfall types and the degree of influence on water and sediment in small watersheds, 305 rainfall events in the basin were divided into three types by the K-means clustering analysis method: A (heavy rainfall, moderate rain), B (small rainfall, light rain), and C (medium rainfall, heavy rain). The most frequent rain type observed was B, followed by C, while A had the lowest frequency. Despite the lower intensity of B-type rainfall, it holds significant regional importance. Conversely, C-type rainfall, although intense and short, serves as the primary source of sediment production. The multiple regression equation effectively models both sediment yield modulus and flood peak discharge, exhibiting an R² coefficient exceeding 0.80, signifying significance. This equation enables the quantitative calculation of pertinent indicators. Sediment yield modulus primarily relies on sediment concentration, runoff depth, and rainfall, while peak discharge is significantly influenced by runoff depth, sediment concentration, and I₃₀. Furthermore, the efficacy of various soil and water conservation measures for flow and sediment reduction correlates with I₃₀. Overall, the impact of different measures on reducing flow and sediment increases with a higher I₃₀, accompanied by a reduced fluctuation range. Full article

The background values of pollutants are becoming increasingly prominent in evaluating water quality and management, and their load and output characteristics are of great significance to the study of changes in the background values. Thus, this paper studies the estimation method for background pollutant fluxes into a river in a forested river source in northeastern China with deficient data or without data. Based on the results of a soak experiment and leaching experiment, as well as natural rainfall runoff experiments, the conversion relationship of the pollutant concentration in the medium was established, the transformation relationship of the pollutant concentration in the medium was established, its load into the river in a small watershed was estimated, and the estimation method was verified according to the measurements (average relative error: 20.5%). Then, the background pollutant loading into the river was calculated on a large scale by improving the pollutant output coefficient model and the universal soil loss equation (average relative error: 18.7%, 24.7%). The results show that the method mentioned above can better reflect the background pollutant loading into the river. This study provides an effective strategy to estimate the background pollutant loading into rivers in areas without data or with missing data, and also provides a theoretical basis for the study of zoning and the formulation of a water environment evaluation system based on background values. Full article

The uneven distribution of meteorological stations in small and medium-sized watersheds in China and the lack of measured hydrological data have led to difficulty in flood simulation and low accuracy in flood forecasting. Traditional hydrological models no longer achieve the forecasting accuracy needed for flood prevention. To improve the simulation accuracy of floods and maximize the use of hydrological information from small and medium-sized watersheds, high-precision hydrological models are needed as a support mechanism. This paper explores the applicability of the Liuxihe model for flood simulation in the Caojiang river basin and we compare flood simulation results of the Liuxihe model with a traditional hydrological model (Xinanjiang model). The results show that the Liuxihe model provides excellent simulation of field floods in Caojiang river basin. The average Nash–Sutcliffe coefficient is 0.73, the average correlation coefficient is 0.9, the average flood peak present error is 0.33, and the average peak simulation accuracy is 93.9%. Compared with the traditional flood hydrological model, the Liuxihe model simulates floods better with less measured hydrological information. In addition, we found that the particle swarm optimization (PSO) algorithm can improve the simulation of the model, and its practical application only needs one representative flood for parameter optimization, which is suitable for areas with little hydrological information. The study can support flood forecasting in the Caojiang river basin and provide a reference for the preparation of flood forecasting schemes in other small and medium-sized watersheds. Full article