Monitoring surface water content using visible and short-wave infrared SPOT-5 data of wheat plots in irrigated semi-arid regions

Abstract

Irrigated agriculture is an important strategic sector in arid and semi-arid regions. Given the large spatial coverage of irrigated areas, operational tools based on satellite remote sensing can contribute to their optimal management. The aim of this study was to evaluate the potential of two spectral indices, calculated from SPOT-5 highresolution visible (HRV) data, to retrieve the surface water content values (from bare soil to completely covered soil) over wheat fields and detect irrigation supplies in an irrigated area. These indices are the normalized difference water index (NDWI) and the moisture stress index (MSI), covering the main growth stages of wheat. These indices were compared to corresponding in situ measurements of soil moisture and vegetation water content in 30 wheat fields in an irrigated area of Morocco, during the 2012-2013 and 2013-2014 cropping seasons. NDWI and MSI were highly correlated with in situ measurements at both the beginning of the growing season (sowing) and at full vegetation cover (grain filling). From sowing to grain filling, the best correlation (R 2 = 0.86; p < 0.01) was found for the relationship between NDWI values and observed soil moisture values. These results were validated using a k-fold crossvalidation methodology; they indicated that NDWI can be used to estimate and map surface water content changes at the main crop growth stages (from sowing to grain filling). NDWI is an operative index for monitoring irrigation, such as detecting irrigation supplies and mitigating wheat water stress at field and regional levels in semi-arid areas.

Mapping terrestrial oil spill impact using machine learning random forest and Landsat 8 OLI imagery: a case site within the Niger Delta region of Nigeria

“…This conforms with results obtained in Kalubarme and Sharma (2015) where NDWI values were observed to be sensitive to stress conditions in wheat-cultivated farm plantations. Similarly, results obtained by Benabdelouahab et al (2015) also showed that MSI and NDWI are sensitive indicators of stress also in a wheat-cultivated farm field. However, the near-infrared and shortwave infrared bands were also observed to have the highest contribution in splitting oil contaminated and oil-free grassland landcover scheme.…”

Surface Runoff and Drought Assessment Using Global Water Resources Datasets - from Oum Er Rbia Basin to the Moroccan Country Scale

“…In Morocco, numerous studies have highlighted the potential use of remote sensing data in representing and monitoring different biophysical parameters (Ezzine et al 2015). These include traditional land cover maps and digital elevation models, as well as snow cover (Marchane et al 2015;Schulz and De Jong 2004), surface temperature (Boudhar et al 2011), near-surface soil moisture (Benabdelouahab et al 2015;Eweys et al 2017), evapotranspiration (ET) (Akdim et al 2014), precipitation (Ouatiki et al 2017), and snowmelt runoff (Boudhar et al 2009).…”

Testing Aquacrop to Simulate Durum Wheat Yield and Schedule Irrigation in a Semi-Arid Irrigated Perimeter in Morocco

“…In the study area, the soils are classified as isohumic, mainly based on French soil classification (CPCS) (Massoni et al, ; Badraoui and Stitou, ). From 30 soil samples collected from several sites providing coverage of the entire study area, soil physics properties were measured (Benabdelouahab et al, ). For three depths (0–30 cm), (30–60 cm) and (60–90 cm), permanent wilting point (PWP) and field capacity (FC) were determined using a pressure plate extractor.…”

“…Crops in semi‐arid regions, such as those in Morocco, regularly face water stress, considered the main limiting factor for crop growth. There is therefore a need to assess soil water availability in order to improve irrigation scheduling and prevent water stress adversely affecting yield (Benabdelouahab et al, ).…”