Xiaoyu Song
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Xiaoyu Song has a total of 94 co-authors. Here are the top co-authors by number of shared publications:
Huaiyou Li
Xifeng Experimental Station on Soil and Water Conservation of Yellow River Conservancy Committee, Qingyang, 745000, Gansu, China
8 shared publications- Hui Liu
State Key Laboratory of Eco-hydraulics in Northwest Arid Region of China, Xi’an University of Technology, Xi’an 710048, China
6 shared publications Lanjun Li
State Key Laboratory of Eco‐hydraulics in Northwest Arid Region of China Xi'an University of Technology Xi'an China
6 shared publications- Lu Xia
Soil Health Laboratory in Shanxi Province, College of Resources and Environment, Shanxi Agricultural University, Taigu 030801, China
6 shared publications Na Fu
5 shared publications- Huai-You Li
Xifeng Experiment Station of Soil and Water Conservation, Yellow River Conservancy Committee, Qingyang 745000, China
4 shared publications
Latest Publications
- Open Access
Effects of Long-Term Vegetation Restoration on Green Water Utilization Heterogeneity in the Loess Plateau Based on Field Experiments and Modeling
Due to the differences in the green water (GW) budget patterns of different vegetation, improper vegetation restoration may not only fail to improve the ecological environment but also cause irreversible damage to ecologically vulnerable areas, especially when vegetation restoration continues to be implemented in the future, and the pressure on water scarcity increases further. However, there is a lack of standardized research on the differences in the patterns of recharge, consumption, and efficient use of GW in typical vegetation. This makes the research results vary and cannot provide direct support for water management decision-making. Therefore, in this study, 30-year-old woodlands (R. pseudoacacia and P. orientalis) and two typical grasslands (I. cylindrican and M. sativa) that are similar to each other except for species were selected in a headwater catchment in the rain-fed agricultural area. A new GW concept and assessment framework was constructed to study the GW of long-term revegetation using a combination of field experiments and model simulations during the 2019–2020 growing season. The study findings comprise the following: (1) High-efficiency green water (GWH), low-efficiency green water (GWL), ineffective green water (GWI), and available green water storage (GWA) in the four sample plots during the study period were defined, separated, and compared. (2) An analysis of GWA variations under different water scenarios. (3) The establishment of GWH and GWL thresholds. (4) Strategies to reduce GWI and optimize GW potential while maintaining soil erosion prevention measures. (5) Suggestions for vegetation restoration species based on diverse factors. This research enhances comprehension of the impact of vegetation restoration on green water dynamics in ecologically vulnerable areas such as the rain-fed agricultural zone of the Loess Plateau.
Open AccessEffects of Long-Term Vegetation Restoration on Green Water Utilization Heterogeneity in the Loess Plateau Based on Field Experiments and Modeling
Due to the differences in the green water (GW) budget patterns of different vegetation, improper vegetation restoration may not only fail to improve the ecological environment but also cause irreversible damage to ecologically vulnerable areas, especially when vegetation restoration continues to be implemented in the future, and the pressure on water scarcity increases further. However, there is a lack of standardized research on the differences in the patterns of recharge, consumption, and efficient use of GW in typical vegetation. This makes the research results vary and cannot provide direct support for water management decision-making. Therefore, in this study, 30-year-old woodlands (R. pseudoacacia and P. orientalis) and two typical grasslands (I. cylindrican and M. sativa) that are similar to each other except for species were selected in a headwater catchment in the rain-fed agricultural area. A new GW concept and assessment framework was constructed to study the GW of long-term revegetation using a combination of field experiments and model simulations during the 2019–2020 growing season. The study findings comprise the following: (1) High-efficiency green water (GWH), low-efficiency green water (GWL), ineffective green water (GWI), and available green water storage (GWA) in the four sample plots during the study period were defined, separated, and compared. (2) An analysis of GWA variations under different water scenarios. (3) The establishment of GWH and GWL thresholds. (4) Strategies to reduce GWI and optimize GW potential while maintaining soil erosion prevention measures. (5) Suggestions for vegetation restoration species based on diverse factors. This research enhances comprehension of the impact of vegetation restoration on green water dynamics in ecologically vulnerable areas such as the rain-fed agricultural zone of the Loess Plateau.
- Open Access
- 1 January 2025
- Published by International Journal of Agricultural and Biological Engineering (IJABE) in International Journal of Agricultural and Biological Engineering
- Vol. 18 (1) , 191-198
Improving the Van Bavel-Hillel model for soil evaporation in grasslands by introducing vegetation coverage resistance
Improving the Van Bavel-Hillel model for soil evaporation in grasslands by introducing vegetation coverage resistance
- 1 January 2025
- Published by International Journal of Agricultural and Biological Engineering (IJABE) in International Journal of Agricultural and Biological Engineering
- Vol. 18 (1) , 191-198
Open AccessImproving the Van Bavel-Hillel model for soil evaporation in grasslands by introducing vegetation coverage resistance
Improving the Van Bavel-Hillel model for soil evaporation in grasslands by introducing vegetation coverage resistance
- Open Access
Variation Characteristics of Actual Evapotranspiration and Uncertainty Analysis of Its Response to Local Climate Change in Arid Inland Region of China
Exploring the variation characteristics of actual evapotranspiration (ETa) and its response to climate change in the arid inland region of China is of great significance for strengthening regional water resources management and maintaining ecological environment security and stability. Taking the Dulan River Basin as the research area, based on the meteorological data from the Wulan Station and hydrological data from the Shanggaba Station from 1981 to 2020, the variation characteristics of ETa at the annual scale were analyzed. The ETa estimation model and joint distribution model of P and potential evapotranspiration (ET0) was constructed based on climate factors, and the uncertainty of ETa response to climate change was explored with the water balance method, multiple linear regression, marginal distribution function, Copula function, and Monte Carlo algorithm. The results showed that the multi-year mean value of ETa in the study area was 261.6 mm, and the interannual process showed an insignificant upward trend, and had no abrupt change during the period. There were two obvious main cycles, which were 19-year periodic changes on the 30-year time scale and 6-year periodic changes on the 9-year time scale. The ETa estimation model based on precipitation (P) and ET0 had good simulation accuracy. The optimal marginal distributions of P and ET0 were Pearson-III (P-III) distribution and Generalized Extreme Value (GEV) distribution, respectively. The Copula joint distribution probability density of P and ET0 was a symmetric saddle-shaped distribution. ETa showed an inverted ‘S’ distribution with the change in joint guarantee rate of P and ET0, ranging from 116.9 mm to 498.6 mm. ETa was an interval range under a certain joint guarantee rate. The research results can provide support for the assessment of ETa, and help to further understand the driving mechanism of climate change on ETa in the arid inland region of China.
Open AccessVariation Characteristics of Actual Evapotranspiration and Uncertainty Analysis of Its Response to Local Climate Change in Arid Inland Region of China
Exploring the variation characteristics of actual evapotranspiration (ETa) and its response to climate change in the arid inland region of China is of great significance for strengthening regional water resources management and maintaining ecological environment security and stability. Taking the Dulan River Basin as the research area, based on the meteorological data from the Wulan Station and hydrological data from the Shanggaba Station from 1981 to 2020, the variation characteristics of ETa at the annual scale were analyzed. The ETa estimation model and joint distribution model of P and potential evapotranspiration (ET0) was constructed based on climate factors, and the uncertainty of ETa response to climate change was explored with the water balance method, multiple linear regression, marginal distribution function, Copula function, and Monte Carlo algorithm. The results showed that the multi-year mean value of ETa in the study area was 261.6 mm, and the interannual process showed an insignificant upward trend, and had no abrupt change during the period. There were two obvious main cycles, which were 19-year periodic changes on the 30-year time scale and 6-year periodic changes on the 9-year time scale. The ETa estimation model based on precipitation (P) and ET0 had good simulation accuracy. The optimal marginal distributions of P and ET0 were Pearson-III (P-III) distribution and Generalized Extreme Value (GEV) distribution, respectively. The Copula joint distribution probability density of P and ET0 was a symmetric saddle-shaped distribution. ETa showed an inverted ‘S’ distribution with the change in joint guarantee rate of P and ET0, ranging from 116.9 mm to 498.6 mm. ETa was an interval range under a certain joint guarantee rate. The research results can provide support for the assessment of ETa, and help to further understand the driving mechanism of climate change on ETa in the arid inland region of China.
- Open Access
Optimizing Straw Mulching Methods to Control Soil and Water Losses on Loess Sloped Farmland
Straw mulching is a key method for controlling soil and water losses. Mulching costs may be reduced by applying it in strips rather than over entire areas. However, the effect of different straw mulching methods on the effectiveness of reducing soil erosion is unclear. In this study, the effects of straw mulching strip length (covering 1/4, 1/2, 3/4, and 4/4 of the slope length) and coverage rate (0.2, 0.5, and 0.8 kg m−2) on interception, infiltration, runoff, and soil erosion were investigated at the plot scale using rainfall simulation experiments. The further complex correlations between these variables were analyzed using structural equation modeling (SEM). Bare slopes were used as a control group. The rainfall intensity was chosen to be 60 mm h−1. The results showed that (1) the modified Merriam interception model can describe the change in interception with time under straw mulching conditions well (R2 > 0.91, NSE > 0.75). (2) A total of 35.39–78.79% of the rainwater is converted into infiltration on straw-covered slopes, while this proportion is 36.75% on bare slopes. The proportion of rainwater converted to infiltration was greatest (78.79%) when the straw covered 3/4 of the slope length at a coverage rate of 0.5 kg m−2, which was the most conducive to rainwater harvesting on the slope. (3) Straw mulching protects the topsoil from the impact of raindrops and directly affects the sediment yield (direct effect = −0.44). Straw mulching can also indirectly affect sediment yield by increasing interception, reducing runoff, and decreasing the sediment carrying capacity of runoff (indirect effect = −0.83). Compared with bare slopes, straw covering at least 1/2 of the slope length can significantly reduce runoff yield, but straw covering only 1/4 of the slope length can significantly reduce sediment yield. Moreover, once the straw mulch slope length reaches 3/4 and the coverage rate reaches 0.5 kg m−2, further increases in mulch slope length and coverage rate will not significantly reduce the runoff and sediment yields. These results assessed the effectiveness of different straw mulching methods in controlling soil and water losses on sloping farmland.
Open AccessOptimizing Straw Mulching Methods to Control Soil and Water Losses on Loess Sloped Farmland
Straw mulching is a key method for controlling soil and water losses. Mulching costs may be reduced by applying it in strips rather than over entire areas. However, the effect of different straw mulching methods on the effectiveness of reducing soil erosion is unclear. In this study, the effects of straw mulching strip length (covering 1/4, 1/2, 3/4, and 4/4 of the slope length) and coverage rate (0.2, 0.5, and 0.8 kg m−2) on interception, infiltration, runoff, and soil erosion were investigated at the plot scale using rainfall simulation experiments. The further complex correlations between these variables were analyzed using structural equation modeling (SEM). Bare slopes were used as a control group. The rainfall intensity was chosen to be 60 mm h−1. The results showed that (1) the modified Merriam interception model can describe the change in interception with time under straw mulching conditions well (R2 > 0.91, NSE > 0.75). (2) A total of 35.39–78.79% of the rainwater is converted into infiltration on straw-covered slopes, while this proportion is 36.75% on bare slopes. The proportion of rainwater converted to infiltration was greatest (78.79%) when the straw covered 3/4 of the slope length at a coverage rate of 0.5 kg m−2, which was the most conducive to rainwater harvesting on the slope. (3) Straw mulching protects the topsoil from the impact of raindrops and directly affects the sediment yield (direct effect = −0.44). Straw mulching can also indirectly affect sediment yield by increasing interception, reducing runoff, and decreasing the sediment carrying capacity of runoff (indirect effect = −0.83). Compared with bare slopes, straw covering at least 1/2 of the slope length can significantly reduce runoff yield, but straw covering only 1/4 of the slope length can significantly reduce sediment yield. Moreover, once the straw mulch slope length reaches 3/4 and the coverage rate reaches 0.5 kg m−2, further increases in mulch slope length and coverage rate will not significantly reduce the runoff and sediment yields. These results assessed the effectiveness of different straw mulching methods in controlling soil and water losses on sloping farmland.
- 24 March 2024
- Published by Wiley in Hydrological Processes
- Vol. 38 (3) , e15136
Modelling rainfall interception losses of three plantations in the Loess Plateau
The forest canopy affects the water entering the forest ecosystem by intercepting rainfall. This is especially pertinent in forests that depend on rainfall for their ecological water needs, quantifying and simulating interception losses provide critical insights into their ecological hydrological processes. In the semi‐arid areas of the Loess Plateau, afforestation has become an effective ecological restoration measure. However, the rainfall interception process of these plantations is still unclear. To quantify and model the canopy interception of these plantations, we conducted a two‐year rainfall redistribution measurement experiment in three typical plantations, including a deciduous broadleaf plantation (Robinia pseudoacacia) and two evergreen coniferous plantations (Platycladus orientalis and Pinus tabuliformis). Based on this, the revised Gash model was used to simulate their interception losses, and the model applicability across varying rainfall types was further compared and verified. The experiment clarified the rainfall redistribution in the three plantations, and the proportions of throughfall to gross rainfall in Robinia pseudoacacia, Platycladus orientalis, and Pinus tabuliformis were 84.8%, 70.4%, and 75.6%; corresponding, the stemflow proportions were 2.0%, 2.2%, and 1.8%; the interception losses were 13.2%, 27.4%, and 22.6%, respectively. The dominant rainfall pattern during the experiment was characterized by low‐amounts, moderate‐intensity, and short‐duration, during which the highest interception proportions across the three plantations were observed. We used the Penman‐Monteith equation and the regression method, respectively, to estimate the canopy average evaporation rate of the revised Gash model, finding that the latter provides a closer match to the measured cumulative interception (NSE >0.7). When simulating interception under the three rainfall patterns, the model with the regression method better simulated the cumulative interception and event‐scale interception for Platycladus orientalis and Pinus tabuliformis plantations under the dominant rainfall pattern. The results contribute valuable information to assess the impact of forest rainfall interception on regional hydrologic processes.
- 24 March 2024
- Published by Wiley in Hydrological Processes
- Vol. 38 (3) , e15136
Modelling rainfall interception losses of three plantations in the Loess Plateau
The forest canopy affects the water entering the forest ecosystem by intercepting rainfall. This is especially pertinent in forests that depend on rainfall for their ecological water needs, quantifying and simulating interception losses provide critical insights into their ecological hydrological processes. In the semi‐arid areas of the Loess Plateau, afforestation has become an effective ecological restoration measure. However, the rainfall interception process of these plantations is still unclear. To quantify and model the canopy interception of these plantations, we conducted a two‐year rainfall redistribution measurement experiment in three typical plantations, including a deciduous broadleaf plantation (Robinia pseudoacacia) and two evergreen coniferous plantations (Platycladus orientalis and Pinus tabuliformis). Based on this, the revised Gash model was used to simulate their interception losses, and the model applicability across varying rainfall types was further compared and verified. The experiment clarified the rainfall redistribution in the three plantations, and the proportions of throughfall to gross rainfall in Robinia pseudoacacia, Platycladus orientalis, and Pinus tabuliformis were 84.8%, 70.4%, and 75.6%; corresponding, the stemflow proportions were 2.0%, 2.2%, and 1.8%; the interception losses were 13.2%, 27.4%, and 22.6%, respectively. The dominant rainfall pattern during the experiment was characterized by low‐amounts, moderate‐intensity, and short‐duration, during which the highest interception proportions across the three plantations were observed. We used the Penman‐Monteith equation and the regression method, respectively, to estimate the canopy average evaporation rate of the revised Gash model, finding that the latter provides a closer match to the measured cumulative interception (NSE >0.7). When simulating interception under the three rainfall patterns, the model with the regression method better simulated the cumulative interception and event‐scale interception for Platycladus orientalis and Pinus tabuliformis plantations under the dominant rainfall pattern. The results contribute valuable information to assess the impact of forest rainfall interception on regional hydrologic processes.
- Open Access
Decoupling Vegetation Dynamics and Climate Change Impacts on Runoff and Sediment in Loess Gully Areas
While climate change and vegetation dynamics have a strong relationship, few studies have specifically measured the effects of these factors on runoff and sediment development in the gully zone of the Loess Plateau. This study investigates the monthly impacts of climatic change and vegetation dynamics on water flow and sediment movement in the gully zone of the Loess Plateau between 2000 and 2016. In this study, the standard gully watershed of the Loess Plateau is investigated using partial least squares structural equation modeling (PLS-SEM). The state of vegetation in the watershed is characterized by utilizing the vegetation index obtained using the Moderate Resolution Imaging Spectroradiometer (MODIS), along with monthly hydro-meteorological and vegetation data. The collective impacts of vegetation dynamics, climate change, and runoff contribute to 74.3% of the monthly fluctuations in sediment levels. The data indicate that 31.6% of the monthly runoff variability can be ascribed to the combined influence of climate change and vegetation dynamics. Climate change significantly influences flow and sediment via direct and indirect mechanisms, primarily by altering the growth and development of vegetation, which subsequently impacts both runoff and sediment. The impact of vegetation on sediment (−0.246) is more pronounced compared to its impact on runoff (−0.239). Furthermore, the impact of vegetation on sediment (−0.038) was significantly less significant compared to the impact on runoff (−0.208). Hence, the vegetation in the watershed primarily mitigates sediment deposition and suspended sediment transit in the water body by regulating runoff, thereby reducing the sediment load. This study examines the intricate correlation between climate change and vegetation dynamics on water flow and sediment deposition in the gully region of the Loess Plateau. It can serve as a helpful resource for managing water resources, allocating agricultural water, and planning soil conservation in the region.
Open AccessDecoupling Vegetation Dynamics and Climate Change Impacts on Runoff and Sediment in Loess Gully Areas
While climate change and vegetation dynamics have a strong relationship, few studies have specifically measured the effects of these factors on runoff and sediment development in the gully zone of the Loess Plateau. This study investigates the monthly impacts of climatic change and vegetation dynamics on water flow and sediment movement in the gully zone of the Loess Plateau between 2000 and 2016. In this study, the standard gully watershed of the Loess Plateau is investigated using partial least squares structural equation modeling (PLS-SEM). The state of vegetation in the watershed is characterized by utilizing the vegetation index obtained using the Moderate Resolution Imaging Spectroradiometer (MODIS), along with monthly hydro-meteorological and vegetation data. The collective impacts of vegetation dynamics, climate change, and runoff contribute to 74.3% of the monthly fluctuations in sediment levels. The data indicate that 31.6% of the monthly runoff variability can be ascribed to the combined influence of climate change and vegetation dynamics. Climate change significantly influences flow and sediment via direct and indirect mechanisms, primarily by altering the growth and development of vegetation, which subsequently impacts both runoff and sediment. The impact of vegetation on sediment (−0.246) is more pronounced compared to its impact on runoff (−0.239). Furthermore, the impact of vegetation on sediment (−0.038) was significantly less significant compared to the impact on runoff (−0.208). Hence, the vegetation in the watershed primarily mitigates sediment deposition and suspended sediment transit in the water body by regulating runoff, thereby reducing the sediment load. This study examines the intricate correlation between climate change and vegetation dynamics on water flow and sediment deposition in the gully region of the Loess Plateau. It can serve as a helpful resource for managing water resources, allocating agricultural water, and planning soil conservation in the region.
- Open Access
Quantitative Impacts of Climate Change and Human Activities on Grassland Productivity in Otog Banner, China from 2001 to 2020
The responses of grassland net primary productivity (NPP) to climate change (CC) and human activities (HA) have received much attention and are inconsistent on different spatial scales. The accurate and quantitative evaluation of the impacts of CC and HA on grassland NPP at a county scale is very important to reveal the external driving factors on grassland NPP and guide the protection of the grassland ecosystem in the arid sandy area of China. In this study, the improved CASA model was adopted to quantify the grassland NPP in Otog Banner, China from 2001 to 2020. The spatiotemporal dynamics of grassland NPP and the relationships between grassland NPP and climate factors in space were analyzed using the methods of simple linear regression and relative sensitivity coefficient. Furthermore, the relative contributions to grassland NPP dynamics caused by CC and HA were explored using the quantitative method based on partial derivative. The results revealed that the mean value of grassland NPP was 175.17 g C m−2 yr−1, and exhibited a significant decrease trend periodically at a rate of 2.14 g C m−2 yr−1 from 2001 to 2020. The spatial distribution of grassland NPP increased from west to east gradually and ranged in 17.48–498.09 g C m−2 yr−1. Grassland NPP exhibited significant linear patterns along the gradients of climate factors, and was the most sensitive to sunshine duration (SSD). Approximately 86.83% of the grassland showed a degradation trend and 39.71% showed a serious degradation trend. The CC contribution to grassland NPP dynamics was 0.593 g C m−2 yr−1, and precipitation was the key driving climate factor, while the contribution of HA was −2.733 g C m−2 yr−1, which was the primary factor leading to large-scale degradation of grassland in Otog banner. This study indicates that the status of the grassland ecosystem in Otog Banner is not optimistic, and measures for grassland ecosystem restoration and improvement need to be further strengthened.
Open AccessQuantitative Impacts of Climate Change and Human Activities on Grassland Productivity in Otog Banner, China from 2001 to 2020
The responses of grassland net primary productivity (NPP) to climate change (CC) and human activities (HA) have received much attention and are inconsistent on different spatial scales. The accurate and quantitative evaluation of the impacts of CC and HA on grassland NPP at a county scale is very important to reveal the external driving factors on grassland NPP and guide the protection of the grassland ecosystem in the arid sandy area of China. In this study, the improved CASA model was adopted to quantify the grassland NPP in Otog Banner, China from 2001 to 2020. The spatiotemporal dynamics of grassland NPP and the relationships between grassland NPP and climate factors in space were analyzed using the methods of simple linear regression and relative sensitivity coefficient. Furthermore, the relative contributions to grassland NPP dynamics caused by CC and HA were explored using the quantitative method based on partial derivative. The results revealed that the mean value of grassland NPP was 175.17 g C m−2 yr−1, and exhibited a significant decrease trend periodically at a rate of 2.14 g C m−2 yr−1 from 2001 to 2020. The spatial distribution of grassland NPP increased from west to east gradually and ranged in 17.48–498.09 g C m−2 yr−1. Grassland NPP exhibited significant linear patterns along the gradients of climate factors, and was the most sensitive to sunshine duration (SSD). Approximately 86.83% of the grassland showed a degradation trend and 39.71% showed a serious degradation trend. The CC contribution to grassland NPP dynamics was 0.593 g C m−2 yr−1, and precipitation was the key driving climate factor, while the contribution of HA was −2.733 g C m−2 yr−1, which was the primary factor leading to large-scale degradation of grassland in Otog banner. This study indicates that the status of the grassland ecosystem in Otog Banner is not optimistic, and measures for grassland ecosystem restoration and improvement need to be further strengthened.
- 10 November 2022
- Published by SPIE-Intl Soc Optical Eng
- Vol. 12331, 186-1117
Defect detection of solar cells based on Haar feature and kernel fuzzy c-means clustering
The detection of micro cracks on the surface of solar cells is very important to improve the durability of photovoltaic modules. In this paper, Haar feature extraction and kernel fuzzy c-means clustering algorithms are proposed to detect the defects of solar cells. Haar extended template is used to extract the edge features as training samples, combined with kernel fuzzy c-means clustering (KFCM) algorithm and improved Xie Beni index to detect the surface defects of solar cells. The recognition rate of no defects is 98%, and the recognition rate of vertical finger defects is 97%, The recognition rate of microcrack is 93%, and that of fracture is 92%.
- 10 November 2022
- Published by SPIE-Intl Soc Optical Eng
- Vol. 12331, 186-1117
Defect detection of solar cells based on Haar feature and kernel fuzzy c-means clustering
The detection of micro cracks on the surface of solar cells is very important to improve the durability of photovoltaic modules. In this paper, Haar feature extraction and kernel fuzzy c-means clustering algorithms are proposed to detect the defects of solar cells. Haar extended template is used to extract the edge features as training samples, combined with kernel fuzzy c-means clustering (KFCM) algorithm and improved Xie Beni index to detect the surface defects of solar cells. The recognition rate of no defects is 98%, and the recognition rate of vertical finger defects is 97%, The recognition rate of microcrack is 93%, and that of fracture is 92%.
- Open Access
- 15 February 2022
- Published by MDPI AG in Atmosphere
- Vol. 13 (2) , 324
Quantitative Effects of Climate Change on Vegetation Dynamics in Alpine Grassland of Qinghai-Tibet Plateau in a County
Alpine grassland in the Qinghai-Tibet Plateau is known to be sensitive to climate change. To quantify the impacts of climate change on alpine ecosystems at small scale, Wulan County in Qinghai Province was taken as the research object, and the relationships between vegetation dynamics and climate changes and the direct and indirect effects of climate factors on vegetation dynamics were analyzed using the methods of ordinary least squares, Pearson correlation analysis and path analysis, on the basis of MOD13A3 data and meteorological data from 2001 to 2020. The results showed that the Normalized Difference Vegetation Index (NDVI) in the growing season of the county and 5 vegetation types showed similar fluctuation processes and relationships with climate factors during the study period. The growing season NDVI (GSN) of shrubland and desert steppe respectively were the highest and lowest. The yearly mean values of GSN over the county ranged from 0.151 to 0.264, and increased extremely significantly with years at a rate of 0.0035 yr−1. Spatially, GSN gradually decreased from northeast to southwest, and 97.2% of the county area showed an increasing trend in GSN. With years, growing season evaporation (GSE) decreased extremely significantly at a rate of 29.6 mm yr−1, while growing season average relative humidity (GSARH) showed a significant increasing trend at a rate of 0.16% yr−1. The correlations and effects of GSE, GSARH, and growing season precipitation (GSP) on vegetation dynamics were weakened in turn. GSE was the main direct effect factor, and the latter two were the indirect effect factors through GSE. The total contribution rates of GSE, GSARH and GSP to vegetation dynamics was about 78.0%. However, growing season average temperature (GSAT) had little effect on vegetation dynamics. This study provides information for understanding the characteristics of vegetation dynamics of alpine grassland in the Qinghai-Tibet Plateau at a small scale.
- 15 February 2022
- Published by MDPI AG in Atmosphere
- Vol. 13 (2) , 324
Open AccessQuantitative Effects of Climate Change on Vegetation Dynamics in Alpine Grassland of Qinghai-Tibet Plateau in a County
Alpine grassland in the Qinghai-Tibet Plateau is known to be sensitive to climate change. To quantify the impacts of climate change on alpine ecosystems at small scale, Wulan County in Qinghai Province was taken as the research object, and the relationships between vegetation dynamics and climate changes and the direct and indirect effects of climate factors on vegetation dynamics were analyzed using the methods of ordinary least squares, Pearson correlation analysis and path analysis, on the basis of MOD13A3 data and meteorological data from 2001 to 2020. The results showed that the Normalized Difference Vegetation Index (NDVI) in the growing season of the county and 5 vegetation types showed similar fluctuation processes and relationships with climate factors during the study period. The growing season NDVI (GSN) of shrubland and desert steppe respectively were the highest and lowest. The yearly mean values of GSN over the county ranged from 0.151 to 0.264, and increased extremely significantly with years at a rate of 0.0035 yr−1. Spatially, GSN gradually decreased from northeast to southwest, and 97.2% of the county area showed an increasing trend in GSN. With years, growing season evaporation (GSE) decreased extremely significantly at a rate of 29.6 mm yr−1, while growing season average relative humidity (GSARH) showed a significant increasing trend at a rate of 0.16% yr−1. The correlations and effects of GSE, GSARH, and growing season precipitation (GSP) on vegetation dynamics were weakened in turn. GSE was the main direct effect factor, and the latter two were the indirect effect factors through GSE. The total contribution rates of GSE, GSARH and GSP to vegetation dynamics was about 78.0%. However, growing season average temperature (GSAT) had little effect on vegetation dynamics. This study provides information for understanding the characteristics of vegetation dynamics of alpine grassland in the Qinghai-Tibet Plateau at a small scale.
- 1 January 2022
- Published by ALOKI Ltd in Applied Ecology and Environmental Research
- Vol. 20 (6) , 5023-5041
THE MINIMUM ENVIRONMENTAL FLOW OF POLLUTED RIVERS IN AREAS LACKING ECOLOGICAL DATA–A CASE STUDY OF A HEAVILY POLLUTED RIVER IN THE UPPER HAI RIVER, CHINA
- 1 January 2022
- Published by ALOKI Ltd in Applied Ecology and Environmental Research
- Vol. 20 (6) , 5023-5041
THE MINIMUM ENVIRONMENTAL FLOW OF POLLUTED RIVERS IN AREAS LACKING ECOLOGICAL DATA–A CASE STUDY OF A HEAVILY POLLUTED RIVER IN THE UPPER HAI RIVER, CHINA