Search

Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) data were analyzed to study the vegetation dynamics over different meteorological subdivisions in India for the period 2000–2016. Soil moisture (SM), rainfall (RF), and land use land cover (LULC) data were analyzed to identify the climatic and anthropogenic drivers that cause vegetation changes at the subdivision scale. Principal component analysis and MK (Mann-Kendall) test showed significant greening trend over semi-arid regions of Northwest India (NWI) and South India (SI) while slight browning trend seen over some of the subdivisions in Indo-Gangetic (IG) plains and Western Ghats (WG). It is found that the NDVI has superior correlation with soil moisture compared with rainfall and the croplands (CL) found to have significant increasing trend over the NWI and SI. Increasing trend in soil moisture over the NWI and SI may have contributed to increase in CL area and the greening trend. Over IG plains, the NDVI showed moderate correlation with SM and RF, and the greening trend (browning trend) in some regions can be attributed to increase in natural vegetation mosaic (decrease of CL). The NDVI has shown browning trend over the core monsoon regions of Madhya Pradesh (an increase of barren lands over west MP and decrease of CL over east MP) and Western Ghats (significant decrease of CL over Konkan and Goa). This study revealed that the soil moisture and LULC changes are the major driving factors for the vegetation changes over majority of the subdivisions in India. [ABSTRACT FROM AUTHOR]

The objective of this study is to apply and test a simple parametric water balance model for prediction of soil moisture regime in the presence of vegetation. The intention was to evaluate the differences in model parameterization and performance when applied to small watersheds under three different types of land covers ( Acacia, degraded forest and natural forest). The watersheds selected for this purpose are located in the sub-humid climate within the Western Ghats, Karnataka, India. Model calibration and validation were performed using a dataset comprising depth-averaged soil moisture content measurements made at weekly time steps from October 2004 to December 2008. In addition to this, a sensitivity analysis was carried out with respect to the water-holding capacity of the soils with the aim of explaining the suitability and adaptation of exotic vegetation types under the prevailing climatic conditions. Results indicated reasonably good performance of the model in simulating the pattern and magnitude of weekly average soil moisture content in 150 cm deep soil layer under all three land covers. This study demonstrates that a simple, robust and parametrically parsimonious model is capable of simulating the temporal dynamics of soil moisture content under distinctly different land covers. Also, results of sensitivity analysis revealed that exotic plant species such as Acacia have adapted themselves effectively to the local climate. [ABSTRACT FROM AUTHOR]