Estimation of reference evapotranspiration (ETo) is a key element in water resources management and crop water requirement which, in turn, affects irrigation scheduling. ETo is subject to the influence of various climatic parameters including minimum temperature (Tmin), maximum temperature (Tmax), relative humidity (RH), windspeed (WS), and sunshine hours (SH). Usually, the influence of the climatic parameters and a dominating climatic factor influencing ETo is estimated on yearly basis. However, in diverse climatic regions, ETo varies with the varying climate. Therefore, this study aims to estimate the spatiotemporal variation in the influence of the climatic parameters on ETo in Punjab, Pakistan, for the period 1950–2021, specifically focusing on decennial, annual, and monthly patterns. The study area was divided into five agroclimatic zones. The Penman–Monteith model was used to estimate ETo. The influence was assessed using geographic weighted regression (GWR) and multiscale geographic weighted regression (MGWR) as the primary methods. As per results from MGWR, ETo in Punjab was highly influenced by the Tmin, Tmax, and WS. Additionally, annual ETo exhibited a higher value in southern Punjab in comparison to northern Punjab, with a range of 2975 mm/year in the cotton–wheat zone to 1596 mm/year in the rain-fed zone. Over the course of the past seventy years, Punjab experienced an average increasing slope of 5.18 mm/year in ETo. Tmin was the highest monthly dominant factor throughout the year, whereas WS and SH were recorded to be the dominant factor in the winters, specifically. All in all, accurate estimation of ETo, which serves as an essential component for crop water requirement, could potentially help improve the irrigation scheduling of crops in the agroclimatic zones.
|Number of pages||19|
|Early online date||12 Jul 2023|
|Publication status||Published - 12 Jul 2023|
Bibliographical noteCopyright © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
- reference evapotranspiration
- geographic weighted regression
- multiscale geographic weighted regression