SOIL AND WATER CONSERVATION ENGINEERING, 3007
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Date
2019-10
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
JAU, JUNAGADH
Abstract
Water is one of the most vital natural resources for life on the Earth. Water must
be considered as a finite resource that has limits and boundaries to its availability and
suitability for use. Irrigation is the largest user of freshwater. The efficient irrigation
water management requires monitoring of soil moisture and estimation of irrigation
water requirement. The measurement of soil moisture for large area with the remote
sensing provide various advantages. Remote sensing systems, provide a repetitive and
consistent view of the earth that is invaluable to monitoring the earth system and the
effect of human activities on the earth.
The remote sensing based bio-physical variable maps were used to estimate the
soil moisture in Uben river catchment and command area of Gujarat state, India. Multi
date satellite images of Landsat-8 for Rabi season, year 2018-19 were used in the
ArcGIS 10.3 software to derive remote sensing based bio-physical variable maps like
Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index
(SAVI), Enhanced Vegetation Index (EVI), Land Surface Temperature (LST). Other
soil moisture indices like Normalized Difference Water Index (NDWI), Land Surface
Water Index (LSWI), Moisture Stress Index (MSI), Vegetation Condition Index (VCI),
Temperature Condition Index (TCI), Soil Moisture Index (SMI), Temperature
Vegetation Dryness Index (TVDI), Moisture Index (MI), Normalized Vegetation
Supply Water Index (NVSWI) were used to estimate the soil moisture content. The
remote sensing based soil moisture and land surface temperature (LST) was validated
with ground measurement. The relationship between vegetation indices and soil
moisture indices, LST and soil moisture indices, LST and vegetation indices, In-situ
soil moisture and LST, In-situ soil moisture and vegetation indices and In-situ soil
moisture and soil moisture indices were also developed. The irrigation water
requirement was calculated based on soil moisture at the time of satellite overpass.
The average Normalized Difference Vegetation Index (NDVI) values ranged
from -0.132 to 0.368 for wheat crop and 0.092 to 0.294 for coriander crop. The average
NDVI value for wheat and coriander crop was increased from Initial stage to Mid-crop
growth stage and then decreased during End season stage. The cotton crop shows higher
NDVI value in December i.e. 0.204 then decreased due to harvesting of cotton. The
average NDVI values in waste land was less as compared to agricultural land with crop and forest area due to no vegetation and exposed soil. The remote sensing based average
value of LST was observed lower during December i.e. 23.33℃ and higher during
March i.e. 38.69℃. The LST value was lower in agricultural land with crop in
comparison to waste land. The remote sensing based soil moisture indices showed
higher soil moisture in area near the river, canal command and Girnar forest. The
maximum area under less soil moisture was observed in March.
The strongest relationship of vegetation indices was observed with Normalized
Difference Water Index (NDWI) or Land Surface Water Index (LSWI) as compare to
other soil moisture indices with average coefficient of determination (R2
) of 0.950. It
was also found that strongest relationship of LST was observed with TCI and TVDI as
compare to other soil moisture indices (R2=0.824 for cotton crop). In-situ soil moisture
with NDWI or LSWI give higher R2
i.e. 0.650 as compared to other soil moisture
indices. The maximum irrigation water requirement for wheat crop as per the time of
satellite overpasses during Rabi 2018-19 was 47.84 mm for sandy loam type soil and
72.02 mm for clay loam soil based on remote sensing study.