Detection of Long-Term Vegetation Degradation in Baluchistan in Southwest Asia Using Ndvi Products of the Modis Sensor of Terra Satellite

Mahmoudi, Peyman; Shirazi, Safdar Ali; Jahanshahi, Seyed Mahdi Amir; Firoozi, Fatemeh; Mazhar, Nausheen

doi:10.30638/eemj.2021.029

Cited by 2 publications

(4 citation statements)

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“…Central India is among the areas where cropland has increased or intensified the most since the 1950s [43]. Moreover, the prevailing decrease in bare areas over most parts of South Asia does not coincide with the increase in land degradation experienced in the past century [29]. The largest decreases in primary and secondary vegetation were exhibited by G (−7.45%) and MIROC (−9.86%) models, and the peaks of cropland increase were simu by CESM2 (+8.16%) and MPI (+7.67%).…”

Section: Lulcc and The Differences Among Models In South Asiamentioning

confidence: 99%

Section: Lulcc and The Differences Among Models In South Asiamentioning

confidence: 99%

“…Even so, wet agreement over a particularly dry area of Pakistan (Figure 9), around the Baluchistan region, seemed rather unlikely for two reasons. First, the Normalized Difference Vegetation Index (NDVI) trends in southwest Asia, according to [29], had somewhat decreased in the recent past due to long-term vegetation degradation, especially in croplands and shrublands. Second, the wet bias caused by, among other reasons, the high sensitivity to convection processes, reduced the reliability of the results in an otherwise dry area by either suggesting ambiguous effects or amplified ones.…”

Section: Pr Changesmentioning

confidence: 99%

“…All these changes have been associated with the decline of forest cover and other naturally vegetated landscapes, especially during the last few decades [23][24][25][26][27][28]. Vegetation degradation from crop plantations or shrubland was also observed with an increasing area of barren land [29]. Despite an overall decrease in natural vegetated and forested landscapes, there were many areas in Nepal, Bhutan, or Sikkim experiencing an increase in forest cover due to reforestation programs, effective forest conservation policies, and enforcement of community forestry and sustainable agroforestry systems [30][31][32].…”

Section: Introductionmentioning

confidence: 99%

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Biogeophysical Effects of Land-Use and Land-Cover Changes in South Asia: An Analysis of CMIP6 Models

Santos

Schickhoff

Hasson

et al. 2023

Land

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The identification of the biogeophysical effects due to land-use, land-cover, and land- management changes (LULCC) is yet to be clearly understood. A range of factors, such as the inclusion of an interactive ocean model component, representation of land management, transient LULCC, and accountability for atmospheric feedback, potentially shifts how models may detect the impacts of the land surface on the climate system. Previous studies on the biogeophysical effects of LULCC in South Asia have either neglected one of those factors or are single model results. Therefore, we analyzed the outputs from 11 models, participants of the Coupled Model Intercomparison Project in its Sixth Phase (CMIP6), which derived from experiments with and without LULCC and compared the two simulations with respect to changes in near-surface temperature and total precipitation means. The CMIP6 simulations, to a certain extent, accounted for the elements previously overlooked. We examined the grid cells that robustly indicated a climatic impact from LULCC. Additionally, we investigated the atmospheric feedback and the dominant fluxes with their associated land surface variables involved in the changes in temperature and precipitation. Our results indicated that the biogeophysical effects from LULCC favored surface net cooling and surface net drying over the robust areas at all seasons. The surface net cooling was strongly influenced by the decrease in available energy and the increase in latent heat and total evapotranspiration. Surface net drying was highly promoted by local hydrological processes, especially in areas outside the monsoon core. The study also revealed that non-local sources might influence precipitation in some parts of South Asia, although this was inconclusive. Our research presented similar results to previous studies but with different magnitudes, which highlighted the added value of CMIP6-GCMs simulations but also their pitfalls.

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Section: Lulcc and The Differences Among Models In South Asiamentioning

confidence: 99%

Section: Lulcc and The Differences Among Models In South Asiamentioning

confidence: 99%

Section: Pr Changesmentioning

confidence: 99%