Scholarlink

<p>Quantifying root zone soil moisture (RZSM) is critical for assessing water availability to crops and identifying agricultural drought across Africa, with access to reliable and timely RZSM data essential for informed decision-making. While rainfall is frequently used to assess crop growing conditions, it alone may not reliably reflect crop water availability due to the impact of evapotranspiration on soil moisture and rainfall not always reflective of concurrent soil water content at rooting depth. To provide robust information on agricultural drought, this paper describes a new, operational RZSM dataset, called TAMSAT soil moisture (TAMSAT-SM), available from 1983-present at 0.25° spatial resolution. TAMSAT-SM is derived using the JULES land surface model, forced with TAMSAT rainfall estimates and other meteorological variables from the NCEP reanalysis, and tuned to SMAP satellite soil moisture observations. Comparison against other RZSM products and independent satellite-derived vegetation health data show TAMSAT-SM can reliably capture the spatial and temporal RZSM and vegetation health patterns across Africa and can be a useful tool to support existing agricultural drought monitoring efforts.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

A new, long-term root zone soil moisture dataset for operational agricultural drought monitoring over Africa

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年1月24日

查看全文
  • Ross I. Maidment,
  • Tristan Quaife,
  • Ewan Pinnington,
  • Emily Black,
  • Amsalework Ejigu,
  • Dhirendra Kumar,
  • Simon Thomas

摘要

Quantifying root zone soil moisture (RZSM) is critical for assessing water availability to crops and identifying agricultural drought across Africa, with access to reliable and timely RZSM data essential for informed decision-making. While rainfall is frequently used to assess crop growing conditions, it alone may not reliably reflect crop water availability due to the impact of evapotranspiration on soil moisture and rainfall not always reflective of concurrent soil water content at rooting depth. To provide robust information on agricultural drought, this paper describes a new, operational RZSM dataset, called TAMSAT soil moisture (TAMSAT-SM), available from 1983-present at 0.25° spatial resolution. TAMSAT-SM is derived using the JULES land surface model, forced with TAMSAT rainfall estimates and other meteorological variables from the NCEP reanalysis, and tuned to SMAP satellite soil moisture observations. Comparison against other RZSM products and independent satellite-derived vegetation health data show TAMSAT-SM can reliably capture the spatial and temporal RZSM and vegetation health patterns across Africa and can be a useful tool to support existing agricultural drought monitoring efforts.