Scholarlink

<p>This study assesses the performance of remotely sensed gridded precipitation products (GPPs) across six Nigerian eco-climatic regions to determine their suitability for ecological and hydrological applications. The three main objectives are to: (1) examine the accuracy and bias of eleven GPPs across Nigeria’s eco-climatic zones; (2) identify the top-performing products; and (3) evaluate how spatial and temporal factors influence their performance rankings. The evaluation incorporates five statistical metrics which include Pearson correlation coefficient (r), mean error (ME), root mean square error (RMSE), multiplicative bias (BIAS), and Nash–Sutcliffe Efficiency (NSE), with compromise programming (CP) used to synthesise rankings. Ground-based observations show varying degrees of positive association with remotely acquired data which connects in the range between <i>r</i> = 0.22 and <i>r</i> = 0.99 specifically in the Montane, Sudan, and Guinea Savanna regions where correlation reaches the peak values of <i>r</i> = 0.96–0.99. A statistical significance of 95% (<i>p</i> &lt; 0.05) demonstrated that the observed dependencies showed high reliability. The Tropical Wet region receives rainfall that CMORPH measures at 1.65&#xa0;mm above the estimated values as determined by Mean Bias Errors (MBE). The results indicate that CHIRPS v2.0 and GPCC v2018 provided outstanding performance across varying eco-climatic regions; however, the outcome varied according to eco-climatic setting and time framework. CHIRPS v2.0 proved most effective for annual scales in convectively dominated regions (Sudan and Sahel). Yet, GPCC v2018 proved to be the best for both monthly and seasonal changes in dry and mountainous zones (Sahel and Montane eco-regions). The research adopts an expanded approach to validation by assessing multiple time periods across distinct ecological regions, which delivers a superior method than previous studies that examined Nigeria and West Africa with limited datasets and broad national averages. The research findings present applied suggestions for selecting the most suitable rainfall data sets that support investigations together with agricultural planning and climate resilience initiatives within Nigeria.</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

Integrating Multi-Sensor Data for Ecologically Sensitive Rainfall Assessment Across Nigeria

  • 期刊论文

  • 发表日期：

    2025年11月5日

查看全文
  • Afeez Alabi Salami,
  • Muchaiteyi Togo

摘要

This study assesses the performance of remotely sensed gridded precipitation products (GPPs) across six Nigerian eco-climatic regions to determine their suitability for ecological and hydrological applications. The three main objectives are to: (1) examine the accuracy and bias of eleven GPPs across Nigeria’s eco-climatic zones; (2) identify the top-performing products; and (3) evaluate how spatial and temporal factors influence their performance rankings. The evaluation incorporates five statistical metrics which include Pearson correlation coefficient (r), mean error (ME), root mean square error (RMSE), multiplicative bias (BIAS), and Nash–Sutcliffe Efficiency (NSE), with compromise programming (CP) used to synthesise rankings. Ground-based observations show varying degrees of positive association with remotely acquired data which connects in the range between r = 0.22 and r = 0.99 specifically in the Montane, Sudan, and Guinea Savanna regions where correlation reaches the peak values of r = 0.96–0.99. A statistical significance of 95% (p < 0.05) demonstrated that the observed dependencies showed high reliability. The Tropical Wet region receives rainfall that CMORPH measures at 1.65 mm above the estimated values as determined by Mean Bias Errors (MBE). The results indicate that CHIRPS v2.0 and GPCC v2018 provided outstanding performance across varying eco-climatic regions; however, the outcome varied according to eco-climatic setting and time framework. CHIRPS v2.0 proved most effective for annual scales in convectively dominated regions (Sudan and Sahel). Yet, GPCC v2018 proved to be the best for both monthly and seasonal changes in dry and mountainous zones (Sahel and Montane eco-regions). The research adopts an expanded approach to validation by assessing multiple time periods across distinct ecological regions, which delivers a superior method than previous studies that examined Nigeria and West Africa with limited datasets and broad national averages. The research findings present applied suggestions for selecting the most suitable rainfall data sets that support investigations together with agricultural planning and climate resilience initiatives within Nigeria.