Upscaling plot-based measurements of RUSLE C-factor of different leaf-angled crops in semi-arid agroecosystems

Pınar M. Ö., ERPUL G.

Environmental Monitoring and Assessment, cilt.195, sa.11, 2023 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 195 Sayı: 11
  • Basım Tarihi: 2023
  • Doi Numarası: 10.1007/s10661-023-11970-8
  • Dergi Adı: Environmental Monitoring and Assessment
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, ABI/INFORM, Agricultural & Environmental Science Database, Aqualine, Aquatic Science & Fisheries Abstracts (ASFA), BIOSIS, CAB Abstracts, Compendex, EMBASE, Environment Index, Food Science & Technology Abstracts, Geobase, Greenfile, Pollution Abstracts, Public Affairs Index, Veterinary Science Database, Civil Engineering Abstracts
  • Anahtar Kelimeler: Cover-management factor (RUSLE C-factor), Leaf angle distribution (LAD), Leaf Area Index (LAI), Normalized Difference Vegetation Index (NDVI), Upscaling
  • Ankara Üniversitesi Adresli: Evet

Özet

Several models have been used to assess temporal cover change trends by using remote and proximal sensing tools. Particularly, from the point of hydrologic and erosional processes and sustainable land and soil management, it is crucial to determine and understand the variation of protective canopy cover change within a development period. Concordantly, leaf angle distribution (LAD) is a crucial parameter when using the vegetation indices (VIs) to define the radiation reflected by the canopy when estimating the cover-management factor (C-factor). This research aims to assess the C-factor of cultivated lands with sunflower and wheat that have different leaf orientations (planophile and erectophile, respectively) with the help of reduced models of NDVI and LAI for estimating crop-stage SLR values with the help of a stepwise linear regression. Those equations with R-squared values of 0.85 and 0.93 were obtained for sunflower and wheat-planted areas, respectively. The Normalized Difference Vegetation Index (NDVI), one of the two plant indices used in this study, was measured by remote and proximal sensing tools. At the same time, the Leaf Area Index (LAI) was obtained by a proximal hand-held crop sensor alone. Soil loss ratio (SLR) was upscaled for the establishment period (1P) of sunflower and the maturing period (3P) of wheat to present different growth stages simultaneously with plant-specific equations that can be easily adapted to those aforementioned crops instead of doing field measurements with conventional techniques in semi-arid cropping systems.