Multi‐month time‐lag effects of regional vegetation responses to precipitation in arid and semi‐arid grassland: A case study of Hulunbuir, Inner Mongolia

Wu, Taosuo; Bai, Hongmei; Feng, Feng; Lin, Qian

doi:10.1111/nrm.12342

Cited by 4 publications

(3 citation statements)

References 18 publications

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“…According to the results, NDVI shows a good interrelation with water area with one time step lag (Figure 7). This result is consistent with the research from [70,71]. Therefore, the relationship between NDVI and the water area of the wetland during the growth season is calculated from the following equation: The effect of wetland water on wetland vegetation is clear in satellite images in dry and wet conditions.…”

Section: Water Area and Ndvi Interrelationsupporting

confidence: 88%

A Simulation Optimization Approach for Wetland Conservation and Management in an Agricultural Basin

Hatamkhani,

Moridi

2023

Sustainability

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Decreasing water quantity and growth in water demand have increased the competition between satisfying societal water needs and protecting ecosystem requirements. Wetlands are some of the most productive ecosystems on Earth. They provide various services to people’s livelihoods, in addition to being suitable habitats for many plant and wildlife species. However, wetlands are under threat of loss and degradation due to anthropogenic activities, particularly the diversion of water for irrigation. The flow regime is usually considered the most crucial ecological factor and a key component of wetland management. So, determining the allocation of environmental requirements is a main factor for managing, restoring, and protecting wetlands, and it is crucial to reach a compromise for optimal water allocation between different sectors. For this purpose, in this research, a new approach is developed to achieve the optimal environmental flow of the wetland in an agricultural-dominated basin using a combination of remote sensing and the simulation optimization method. Waterbirds and vegetation are used as bioindicators of wetland ecosystems. First, using remote sensing data and analyses, we obtained the interrelation between the wetland water regime, vegetation, and waterbird characteristics using different time series of Landsat spectral indices. Then, by employing the long-term simulation optimization (WEAP-MOPSO) model, the optimal e-flow of the wetland is evaluated in such a way that the suitable ecological condition of the wetland is achieved and the wetland is able to provide its functions and services.

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Section: Water Area and Ndvi Interrelationsupporting

confidence: 88%

A Simulation Optimization Approach for Wetland Conservation and Management in an Agricultural Basin

Hatamkhani,

Moridi

2023

Sustainability

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“…The most notable difference between the images occurs in the rivers where water is lying in the second image causing the pixels to become whiter. Normally, vegetation growth in arid and semi-arid environments tends to occur 1-2 months after rainfall [37,38]. As the temporal baseline between images is 12 days, the difference in vegetation cover should be relatively small.…”

Section: Resultsmentioning

confidence: 99%

Mapping Erosion Hotspots: Coherent Change Detection in the Quilpie Region, Queensland, Australia

Cook,

Agha Karimi,

Grinham

et al. 2024

Remote Sensing

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Erosion is a powerful force that has moulded the Earth ever since water has been present on its rocky surface. In its seemingly harmless pursuit, erosion threatens ecosystems, reduces agricultural production, and impacts water quality. When trying to investigate erosion, there is no easy way to identify hotspots, only leaving the possibility of predicting where erosion should be occurring. This study aimed to develop a method to identify erosion using Synthetic Aperture Radar (SAR) images in a process called Coherent Change Detection (CCD). In doing so, it was found that CCD can be used to identify erosion due to rain events; however, false positives were also found due to soil moisture changes. This study used a new method for removing soil moisture effects that utilised the drying out of the soil to map where changes had occurred. This helped limit false positives, but more work is required to ensure soil moisture does not interfere with the results. Field data comprising aerial imagery and soil sampling were collected to improve the SAR processing as well as validate the results. The results of this study indicate the feasibility of developing an erosion analysis system capable of providing near real-time data specifically for arid regions.

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“…At the individual plant scale, an accumulation of rainfall and temperature is required to initiate the plant life cycle (i.e., seed germination, seedling growth, flowering). At the ecosystem scale, biogeochemical cycles that provide soil nutrients for plant uptake and growth also require cumulative temporal effects [ 58 , 59 , 60 ].…”

Section: Discussionmentioning

confidence: 99%

Considering Climatic Factors, Time Lag, and Cumulative Effects of Climate Change and Human Activities on Vegetation NDVI in Yinshanbeilu, China

Wang,

Liu,

2023

Plants

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Climate and human activities are the basic driving forces that control and influence the spatial distribution and change of vegetation. Using trend analysis, the Hurst index, correlation analysis, the Moran index, path analysis, residual analysis, and other methods, the effects of human activities and climate factors on vegetation change were analyzed. The results show that: (1) The research area’s normalized difference vegetation index (NDVI) exhibited a substantial upward trend from 2001 to 2020, increasing at a rate of 0.003/a, and the vegetation cover was generally healthy. The generally constant NDVI region made up 78.45% of the entire area, and the grassland, cultivated land, and forest land showed the most visible NDVI aggregation features. (2) The Vegetation is mainly promoted by water and heat, particularly precipitation, have a major impact on plants, with the direct influence of precipitation on vegetation growth being much greater than the indirect effect through the temperature. (3) The trend of NDVI residuals showed obvious spatial variability, presenting a distribution characteristic of high in the south and low in the north. The results of this study can provide a basis for the scientific layout of ecological protection and restoration projects in the Yinshanbeilu area.

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Multi‐month time‐lag effects of regional vegetation responses to precipitation in arid and semi‐arid grassland: A case study of Hulunbuir, Inner Mongolia

Cited by 4 publications

References 18 publications

A Simulation Optimization Approach for Wetland Conservation and Management in an Agricultural Basin

A Simulation Optimization Approach for Wetland Conservation and Management in an Agricultural Basin

Mapping Erosion Hotspots: Coherent Change Detection in the Quilpie Region, Queensland, Australia

Considering Climatic Factors, Time Lag, and Cumulative Effects of Climate Change and Human Activities on Vegetation NDVI in Yinshanbeilu, China

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