Dynamic Assessment of Soil Water Erosion in the Three-North Shelter Forest Region of China from 1980 to 2015

Ji, Cuicui; Li, X.; Jia, Yongxing; Wang, L.

doi:10.1134/s1064229318120050

Cited by 10 publications

(6 citation statements)

References 42 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Yulin is located in Shanxi province on the border between the loess plateau and the Inner Mongolian plateau (Figure 1). It is an ecologically fragile area in the TNSFP region with some of the worst instances of erosion in the world [14][15][16]. As a result, Yulin receives a lot of attention from the Chinese government and international societies [23].…”

Section: Study Areamentioning

confidence: 99%

“…The ecosystems within TNSFP are still fragile, and the most prominent ecological cause of the decline has been damage due to sandstorms and soil erosion. The TNSFP covers 84% of the desertified land in China and 40% of areas experiencing soil erosion [14][15][16]. The reduction of protective forests will make these problems even more serious, resulting in a sharp decrease in protection efficiency.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Estimating the Aboveground Biomass for Planted Forests Based on Stand Age and Environmental Variables

et al. 2019

View full text Add to dashboard Cite

Measuring forest aboveground biomass (AGB) at local to regional scales is critical to understanding their role in regional and global carbon cycles. The Three-North Shelterbelt Forest Program (TNSFP) is the largest ecological restoration project in the world, and has been ongoing for over 40 years. In this study, we developed models to estimate the planted forest aboveground biomass (PF_AGB) for Yulin, a typical area in the project. Surface reflectances in the study area from 1978 to 2013 were obtained from Landsat series images, and integrated forest z-scores were constructed to measure afforestation and the stand age of planted forest. Normalized difference vegetation index (NDVI) was combined with stand age to develop an initial model to estimate PF_AGB. We then developed additional models that added environment variables to our initial model, including climatic factors (average temperature, total precipitation, and total sunshine duration) and a topography factor (slope). The model which combined the total precipitation and slope greatly improved the accuracy of PF_AGB estimation compared to the initial model, indicating that the environmental variables related to water distribution indirectly affected the growth of the planted forest and the resulting AGB. Afforestation in the study area occurred mainly in the early 1980s and early 21st century, and the PF_AGB in 2003 was 2.3 times than that of 1998, since the fourth term TNSFP started in 2000. The PF_AGB in 2013 was about 3.33 times of that in 2003 because many young trees matured. The leave-one-out cross-validation (LOOCV) approach showed that our estimated PF_AGB had a significant correlation with field-measured data (correlation coefficient (r) = 0.89, p < 0.001, root mean square error (RMSE) = 6.79 t/ha). Our studies provided a method to estimate long time series PF_AGB using satellite repetitive measures, particularly for arid or semi-arid areas.

show abstract

Section: Study Areamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Estimating the Aboveground Biomass for Planted Forests Based on Stand Age and Environmental Variables

et al. 2019

View full text Add to dashboard Cite

show abstract

“…In calculating structured LAI, we multiplied the sum of LAIc and LAIg (i.e., LAIcg, s method) by the interaction weight (W i ) (Eq. (13). We tested other methods to substitute for LAIcg, including the product of LAIc and LAIg (p method), the minimum value of LAIc and LAIg (m method), and the weight re-distribution of interaction effects to LAIc and LAIg according to the corresponding weights of LAIc and LAIg (d method, i.e., W c and W g were 0.47 and 0.53 for soil conservation, respectively; 0.16 and 0.84 for water conservation, respectively, W i = 0).…”

Section: Discussionmentioning

confidence: 99%

“…Application of the weight coefficient. To test the results of the weight coefficients of forest canopy and understory grass, this study used LAI of tree canopy (LAIc) and of grass (LAIg) to calculate structured LAIs: (13) where LAIs is soil and water conservation weighted structured LAI; LAIc, LAIg, and LAIcg refer to LAI of tree canopy, grass, and their sum, respectively; W c , W g , and W i are the contribution weight coefficient of tree canopy layer, grass layer, and interaction between tree and grass layers, respectively. We then obtained the structured LAI of soil conservation (LAIs-sl) and the structured LAI of water conservation (LAIs-rd) using weight coefficients calculated by SL and RD, respectively.…”

Section: Evaluation Of Soil and Water Conservation Weightmentioning

confidence: 99%

See 1 more Smart Citation

Contribution Weight of Forest Canopy and Grass Layers to Soil and Water Conservation on Water-Eroded Areas in Southern China

2020

Eurasian Soil Sc.

View full text Add to dashboard Cite

In this study, the contribution weight of soil and water conservation effect of forest canopy layer and grass layer were calculated and analyzed using the measured data of soil loss (SL) and surface runoff depth (RD) in 12 experimental plots in Changting County, Fujian Province, China. Results indicate that the average SL and RD followed the order: pure tree > pure grass > tree-grass. Either SL or RD did not present a simple addition relationship among the three kinds of vegetated plots, especially for RD, thereby exhibiting the interaction effects between tree canopy and grass layers. The weight coefficients to soil and water conservation followed the order: grass > tree canopy > interaction between tree and grass, with 0.40, 0.35, and 0.25 for soil conservation, and 0.76, 0.14, and 0.10 for water conservation, respectively. The structured leaf area index (LAI) calculated with the weighted addition of LAIs of tree and grass correlated better with soil and water conservation effects than with overall and layered LAIs. The contribution weights in the construction of structured vegetation parameters can be applied for soil and water conservation.

show abstract

Ecology and sustainability of the Inner Mongolian Grassland: Looking back and moving forward

et al. 2020

View full text Add to dashboard Cite

Dynamic Assessment of Soil Water Erosion in the Three-North Shelter Forest Region of China from 1980 to 2015

Cited by 10 publications

References 42 publications

Estimating the Aboveground Biomass for Planted Forests Based on Stand Age and Environmental Variables

Estimating the Aboveground Biomass for Planted Forests Based on Stand Age and Environmental Variables

Contribution Weight of Forest Canopy and Grass Layers to Soil and Water Conservation on Water-Eroded Areas in Southern China

Ecology and sustainability of the Inner Mongolian Grassland: Looking back and moving forward

Contact Info

Product

Resources

About