Scholarlink

<p>Despite the abundance of potential evapotranspiration (PET) formulas, there remains a gap in understanding their specific application in catchment modeling under changing climatic conditions or weather extremes. This study tested seven distinct PET estimation methods under different climatic conditions. The 6-year continuous data of various weather variables from 9 meteorological stations along with streamflow gauge data from a catchment outlet within a lumped hydrological model viz.., GR4J was employed. The findings revealed that almost similar runoff simulations are produced based on different PET inputs during both high and low flow events. Furthermore, when comparing individual PET series with the reference Penman–Monteith PET, the estimates exhibited substantial discrepancies, with some models yielding even an R-squared value as low as 0.38. Notably, the Priestley-Taylor formula emerged as the most adept in estimating PET under varying climatic dynamics, showcasing improved predictive capabilities, particularly during flood events. Consequently, the choice of PET model during high flow scenarios had minimal impact, whereas during low flows, certain models exhibited runoff overestimations, potentially leading to inaccuracies in water releases if not appropriately adjusted.</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

Assessing PET models for hydrological predictions-insights from climatic dynamics and extremes

  • 期刊论文

  • 发表日期：

    2025年6月2日

查看全文
  • Mehnaza Akhter,
  • Aaqib Gulzar,
  • Misbah Bashir,
  • Manzoor Ahmad Ahanger

摘要

Despite the abundance of potential evapotranspiration (PET) formulas, there remains a gap in understanding their specific application in catchment modeling under changing climatic conditions or weather extremes. This study tested seven distinct PET estimation methods under different climatic conditions. The 6-year continuous data of various weather variables from 9 meteorological stations along with streamflow gauge data from a catchment outlet within a lumped hydrological model viz.., GR4J was employed. The findings revealed that almost similar runoff simulations are produced based on different PET inputs during both high and low flow events. Furthermore, when comparing individual PET series with the reference Penman–Monteith PET, the estimates exhibited substantial discrepancies, with some models yielding even an R-squared value as low as 0.38. Notably, the Priestley-Taylor formula emerged as the most adept in estimating PET under varying climatic dynamics, showcasing improved predictive capabilities, particularly during flood events. Consequently, the choice of PET model during high flow scenarios had minimal impact, whereas during low flows, certain models exhibited runoff overestimations, potentially leading to inaccuracies in water releases if not appropriately adjusted.