scholarly journals Quantification of ecohydrological sensitivities and their influencing factors at the seasonal scale

2021 ◽  
Vol 25 (3) ◽  
pp. 1447-1466
Author(s):  
Yiping Hou ◽  
Mingfang Zhang ◽  
Xiaohua Wei ◽  
Shirong Liu ◽  
Qiang Li ◽  
...  
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Influencing Factors ◽  
Vegetation Change ◽  
Prediction Models ◽  
Edge Density ◽  
Wet Season ◽  
Slope Length ◽  
Area Index ◽  
Seasonal Scale

Abstract. Ecohydrological sensitivity, defined as the response intensity of streamflow to per unit vegetation change is an integrated indicator for assessing hydrological sensitivity to vegetation change. Understanding ecohydrological sensitivity and its influencing factors is crucial for managing water supply, reducing water-related hazards and ensuring aquatic functions by vegetation management. Yet, there is still a systematic assessment on ecohydrological sensitivity and associated driving factors especially at a seasonal scale lacking. In this study, 14 large watersheds across various environmental gradients in China were selected to quantify their ecohydrological sensitivities at a seasonal scale and to examine the role of associated influencing factors such as climate, vegetation, topography, soil and landscape. Based on the variables identified by correlation analysis and factor analysis, prediction models of seasonal ecohydrological sensitivity were constructed to test their utilities for the design of watershed management and protection strategies. Our key findings were the following: (1) ecohydrological sensitivities were more sensitive under dry conditions than wet conditions – for example, 1 % LAI (leaf area index) change, on average, induced 5.05 % and 1.96 % change in the dry and wet season streamflow, respectively; (2) seasonal ecohydrological sensitivities were highly variable across the study watersheds with different climate conditions, dominant soil types and hydrological regimes; and (3) the dry season ecohydrological sensitivity was mostly determined by topography (slope, slope length, valley depth and downslope distance gradient), soil (topsoil organic carbon and topsoil bulk density) and vegetation (LAI), while the wet season ecohydrological sensitivity was mainly controlled by soil (topsoil-available water-holding capacity), landscape (edge density) and vegetation (leaf area index). Our study provided a useful and practical framework to assess and predict ecohydrological sensitivities at the seasonal scale. The established ecohydrological sensitivity prediction models can be applied to ungauged watersheds or watersheds with limited hydrological data to help decision makers and watershed managers effectively manage hydrological impacts through vegetation restoration programs. We conclude that ecohydrological sensitivities at the seasonal scale are varied by climate, vegetation and watershed property, and their understanding can greatly support the management of hydrological risks and protection of aquatic functions.

scholarly journals Quantification of Ecohydrological Sensitivities and Their Influencing Factors at the Seasonal Scale

2020 ◽  
Author(s):  
Yiping Hou ◽  
Mingfang Zhang ◽  
Xiaohua Wei ◽  
Shirong Liu ◽  
Qiang Li ◽  
...  
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Influencing Factors ◽  
Vegetation Change ◽  
Prediction Models ◽  
Edge Density ◽  
Wet Season ◽  
Slope Length ◽  
Area Index ◽  
Seasonal Scale

Abstract. Ecohydrological sensitivity is defined as the response intensity of streamflow to per unit vegetation change. Understanding of ecohydrological sensitivity and its influencing factors is important for managing water supply, reducing water-related hazards and ensuring aquatic functions by vegetation management. However, this topic has rarely been examined. In this study, 14 large watersheds across various environmental gradients in China were selected to quantify ecohydrological sensitivities at the seasonal scale and to examine their influencing factors such as climate, vegetation, topography, soil and landscape. Based on the variables identified by correlation analysis and factor analysis, the prediction models of seasonal ecohydrological sensitivity were constructed to test their utilities for the design of watershed management and protection strategies. Our key findings were: (1) ecohydrological sensitivities were more sensitive in dry conditions than in wet conditions, for example, 1 % LAI (leaf area index) change averagely induced 5.05 % and 1.96 % change in dry and wet season streamflows, respectively; (2) seasonal ecohydrological sensitivities were highly variable across the study watersheds with different climate condition, dominant soil type and hydrological regime; and (3) the dry season ecohydrological sensitivity was mostly determined by topography (slope, slope length, valley depth, downslope distance gradient), soil (topsoil organic carbon, topsoil bulk density) and vegetation (LAI), while the wet season ecohydrological sensitivity was mainly controlled by soil (topsoil available water holding capacity), landscape (edge density) and vegetation (leaf area index). Our study provided a useful and practical framework to assess and predict ecohydrological sensitivities at the seasonal scale. We expect that ecohydrological sensitivity prediction models can be applied to ungauged watersheds or watersheds with limited hydrological data to help decision makers and watershed managers to effectively manage hydrological impacts through vegetation restoration programs. We conclude that ecohydrological sensitivities at the seasonal scale were varied by climate, vegetation and watershed property, and their understanding can greatly support management of hydrological risks and protection of aquatic functions.

scholarly journals Numerical Assessments of Leaf Area Index in Tropical Savanna Rangelands, South Africa Using Landsat 8 OLI Derived Metrics and In-Situ Measurements

2019 ◽  
Vol 11 (7) ◽  
pp. 829 ◽  
Author(s):  
Timothy Dube ◽  
Santa Pandit ◽  
Cletah Shoko ◽  
Abel Ramoelo ◽  
Dominic Mazvimavi ◽  
...  
Keyword(s):  
South Africa ◽  
Leaf Area Index ◽  
Leaf Area ◽  
National Park ◽  
Dry Season ◽  
Kruger National Park ◽  
Landsat 8 ◽  
Tropical Savanna ◽  
Wet Season ◽  
Area Index

Knowledge on rangeland condition, productivity patterns and possible thresholds of potential concern, as well as the escalation of risks in the face of climate change and variability over savanna grasslands is essential for wildlife/livestock management purposes. The estimation of leaf area index (LAI) in tropical savanna ecosystems is therefore fundamental for the proper planning and management of this natural capital. In this study, we assess the spatio-temporal seasonal LAI dynamics (dry and wet seasons) as a proxy for rangeland condition and productivity in the Kruger National Park (KNP), South Africa. The 30 m Landsat 8 Operational Land Imager (OLI) spectral bands, derived vegetation indices and a non-parametric approach (i.e., random forest, RF) were used to assess dry and wet season LAI condition and variability in the KNP. The results showed that RF optimization enhanced the model performance in estimating LAI. Moderately high accuracies were observed for the dry season (R2 of 0.63–0.72 and average RMSE of 0.60 m2/m2) and wet season (0.62–0.63 and 0.79 m2/m2). Derived thematic maps demonstrated that the park had high LAI estimates during the wet season when compared to the dry season. On average, LAI estimates ranged between 3 and 7 m2/m2 during the wet season, whereas for the dry season most parts of the park had LAI estimates ranging between 0.00 and 3.5 m2/m2. The findings indicate that Kruger National Park had high levels of productivity during the wet season monitoring period. Overall, this work shows the unique potential of Landsat 8-derived metrics in assessing LAI as a proxy for tropical savanna rangelands productivity. The result is relevant for wildlife management and habitat assessment and monitoring.

scholarly journals Long-Term Variation of Global GEOV2 and MODIS Leaf Area Index (LAI) and Their Uncertainties: An Insight into the Product Stabilities

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Hongliang Fang ◽  
Yao Wang ◽  
Yinghui Zhang ◽  
Sijia Li
Keyword(s):  
Leaf Area Index ◽  
Product Quality ◽  
Leaf Area ◽  
Vegetation Change ◽  
Temporal Variations ◽  
Area Index ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Global Vegetation

Leaf area index (LAI) is an essential climate variable that is crucial to understand the global vegetation change. Long-term satellite LAI products have been applied in many global vegetation change studies. However, these LAI products contain various uncertainties that are not been fully considered in current studies. The objective of this study is to explore the uncertainties in the global LAI products and the uncertainty variations. Two global LAI datasets—the European Geoland2 Version 2 (GEOV2) and Moderate Resolution Imaging Spectroradiometer (MODIS) (2003-2019)—were investigated. The qualitative quality flags (QQFs) and quantitative quality indicators (QQIs) embedded in the product quality layers were analyzed to identify the temporal anomalies in the quality profile. The results show that the global GEOV2 (0.042/10a) and MODIS (0.034/10a) LAI values have steadly increased from 2003 to 2019. The global LAI uncertainty (0.016/10a) and relative uncertainty (0.3%/10a) from GEOV2 have also increased gradually, especially during the growing season from April to October. The uncertainty increase is larger for woody biomes than for herbaceous types. Contrastingly, the MODIS LAI product uncertainty remained stable over the study period. The uncertainty increase indicated by GEOV2 is partly attributed to the sensor shift in the product series. Further algorithm enhancement is necessary to improve the cross-sensor performance. This study highlights the importance of studying the LAI uncertainty and the uncertainty variation. Temporal variations in the LAI products and the product quality revealed herein have significant implications on global vegetation change studies.

scholarly journals Temporal and Spatial Variations in the Leaf Area Index and Its Response to Topography in the Three-River Source Region, China from 2000 to 2017

2021 ◽  
Vol 10 (1) ◽  
pp. 33
Author(s):  
Wenqi Zhang ◽  
Huaan Jin ◽  
Huaiyong Shao ◽  
Ainong Li ◽  
Shangzhi Li ◽  
...  
Keyword(s):  
Leaf Area Index ◽  
Trend Analysis ◽  
Leaf Area ◽  
Land Surface ◽  
Vegetation Change ◽  
Source Region ◽  
Kendall Test ◽  
Hurst Index ◽  
Area Index ◽  
Topographic Factors

The Three-River Source Region (TRSR) is an important area for the ecological security of China. Vegetation growth has been affected by the climate change, topography, and human activities in this area. However, few studies have focused on analyzing time series tendencies of vegetation change in various terrain conditions. To address this issue in the TRSR, this study explored vegetation stability, tendency, and sustainability with multiple methods (e.g., coefficient of variation, Theil-Sen median trend analysis, Mann-Kendall test, and Hurst index) based on the 2000–2017 Global LAnd Surface Satellite Leaf Area Index (GLASS LAI) product. The differentiation patterns of LAI variations and multiyear mean LAI value under different topographic factors were also investigated in combination with digital elevation model (DEM). The results showed that (1) the mean LAI value in the study area increased, with a linear tendency of 0.013·10 a−1; (2) LAI values decreased from southeast to northwest in terms of spatial distribution and the CV indicated LAI variations were relatively stable; (3) the trend analysis revealed that the improved area of LAI accounted for 62.72% which was larger than the degraded area (37.28%), and hurst index revealed a weak anti-sustaining effect of the current tendencies; and (4) the increasing trend was found in multiyear mean LAI value as relief amplitude and slope increased, while LAI stability improved with increasing slope. They exhibited a clear regular pattern. Moreover, significant improvement in LAI generally occurred in low-altitude and flat areas. Finally, the overall improvement and sustainability of LAI improved when moving from sunny aspects to shady aspects, but the LAI stability decreased. Note that vegetation degradation was observed in some high slope areas and was further aggravated. This study is beneficial for revealing the spatial and temporal changes of LAI and their changing rules as a function of different topographic factors in the TRSR. Meanwhile, the results of this study provide theoretical support for sustainable development of this area.

scholarly journals Growth indices ans productivity in sugarcane

2005 ◽  
Vol 62 (1) ◽  
pp. 23-30 ◽  
Author(s):  
Maurício dos Santos Simões ◽  
Jansle Vieira Rocha ◽  
Rubens Augusto Camargo Lamparelli
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Prediction Models ◽  
Gompertz Model ◽  
Exponential Model ◽  
Index Number ◽  
Total Biomass ◽  
Biophysical Parameters ◽  
Area Index ◽  
Cane Productivity

A knowledge about the temporal development of agronomic variables in sugarcane is a very important aspect for the development of crop yield prediction models using remote sensing, and further studies are still needed. This paper describes the temporal evolution of sugarcane biophysical parameters, such as total biomass, leaf area index, number of plants per meter, and productivity. During two seasons, a commercial field in Araras/SP, planted with variety SP80-1842, on the 4th and 5th cuts, was monitored on eight different dates, and data were obtained for 2 m of sugarcane in three crop rows at 18 sampling points. Linear and multiple regression analyses were used to study growth analysis and to correlate agronomic variables (leaf area index and number of plants per meter) with biomass and productivity. Gompertz model, a sigmoidal curve, was the best adjustment curve for total biomass and yield in relation to days after cutting (r² = 0.8987 and r² = 0.9682, respectively); number of plants and leaf area index showed best fit with a cubic exponential model and a quadratic exponential model, respectively. Total biomass and cane productivity were well correlated with LAI in the first two stages of the sugarcane cycle using linear regression. At the end of the cycle, total biomass and cane productivity were more related to number of plants, and lower r² values than in other stages were obtained by the models.

Composition, leaf area index and standing biomass of eucalypt open forests near Darwin in the Northern Territory, Australia

2000 ◽  
Vol 48 (5) ◽  
pp. 629 ◽  
Author(s):  
A. P. O'Grady ◽  
X. Chen ◽  
D. Eamus ◽  
L. B. Hutley
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Carbon Balance ◽  
Stand Structure ◽  
Northern Territory ◽  
Northern Australia ◽  
Wet Season ◽  
Area Index ◽  
Standing Biomass ◽  
Open Forests

Savanna communities dominate the wet–dry tropical regions of the world and are an important community type in monsoonal northern Australia. As such they have a significant impact on the water and carbon balance of this region. Above the 1200-mm isohyet, savanna’s are dominated by Eucalyptus miniata–E. tetrodonta open forests. We have described in detail the composition and structure as well as seasonal patterns of leaf area index and above-ground biomass in the E. miniata–E. tetrodonta open forests of the Gunn Point region near Darwin in the Northern Territory of Australia. In all, 29 tree species from four phenological guilds were recorded in these forests. Stand structure suggests that the forests were still recovering from the impacts of cyclone Tracy and subsequent frequent fires. Eucalyptus miniata and E. tetrodonta were significant contributors to overstorey leaf area index and standing biomass (>70%), and both leaf area index and biomass were strongly correlated to basal area. Leaf area index was at a maximum (about 1.0) at the end of the wet season and declined over the dry season by about 30–40%. There were proportionally greater changes in the understorey reflecting the greater contribution of deciduous and semi-deciduous species in this strata. Standing biomass was about 55 t ha –1 . Detailed descriptions of leaf area index and biomass are important inputs into the development of a water and carbon balance for the savanna’s of northern Australia.

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