Rainfall–runoff modelling and water balance analysis for Al-Hindiyah barrage, Iraq using remote sensing and GIS

Khan

Muhammad

et al. 2022

Land

Accurate estimation of evapotranspiration (ET) is vital for water resource development, planning and management, particularly in the present global warming context. A large number of empirical ET models have been developed for estimating ET. The main limitations of this method are that it requires several meteorological variables and an extensive data span to comprehend the ET pattern accurately, which is not available in most developing countries. The efficiency of 30 empirical ET models has been evaluated in this study to rank them for Pakistan to facilitate the selection of suitable models according to data availability. Princeton Global Meteorological Forcing daily climate data with a 0.25° × 0.25° resolution for 1948–2016 were utilized. The ET estimated using Penman–Monteith (PM) was considered as the reference. Multi-criteria group decision making (MCGDM) was used to rank the models for Pakistan. The results showed the temperature-based Hamon as the best model for most of Pakistan, followed by Hargreaves–Samani and Penman models. Hamon also showed the best performance in terms of different statistical metrics used in the study with a mean bias (PBias) of −50.2%, mean error (ME) of −1.62 mm and correlation coefficient (R2) of 0.65. Ivan showed the best performance among the humidity-based models, Irmak-RS and Ritch among the radiation-based models and Penman among the mass transfer-based models. Northern Pakistan was the most heterogeneous region in the relative performance of different ET models.

Section: Introductionmentioning

confidence: 99%

Ranking of Empirical Evapotranspiration Models in Different Climate Zones of Pakistan

Khan

Muhammad

et al. 2022

Land

“…Suliman et al [21] evaluated the skill of remote sensing rainfall products to characterize droughts in Iraq and showed higher performance of PERSIANN data to study droughts in the country. Jaber et al [59] also showed the efficacy of remote sensing precipitation in rainfall-runoff modelling in Iraq. Studies in the nearby region also showed the applicability of satellite rainfall in hydrological applications in Jordan [60], Iran [61], Saudi Arabia [62,63], and Turkey [64].…”

Section: Discussionmentioning

confidence: 98%

Utilizing Satellite Data to Establish Rainfall Intensity-Duration-Frequency Curves for Major Cities in Iraq

Zeri

Wang

et al. 2023

Water

This study generates intensity-duration-frequency curves for three important cities in Iraq using Global Precipitation Measurement Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (IMERG), Global Satellite Mapping of Precipitation near real-time (GSMaP NRT), and gauge corrected (GSMaP GC) satellite precipitation datasets. Many probability distribution functions were used to fit the maximum yearly rainfall data. The Sherman equation was used to create intensity-duration-frequency (IDF) curves for rainfall intensities with 2-, 5-, 10-, 25-, 50-, and 100-year return periods, with the estimated coefficients of the best-fit distribution serving as the fitting parameters. The discrepancy between the IDF curves produced from the satellites and the observed data was used to bias correct the satellite IDF curves. The Generalized Extreme Value Distribution model best describes the hourly rainfall distribution of satellite data. GSMaP GC was the best option for creating IDF curves with higher correlations with observed data at Baghdad, Basra, and Mosul. The study indicates the necessity of gauge correction of satellite rainfall data to reduce under- and over-estimating observed rainfall. GSMaP GC can reasonably estimate rainfall in a predominantly arid climate region like Iraq. The generated IDF curves may be an important step toward achieving sustainable urban stormwater management in the country.

“…Evapotranspiration (ET) plays a vital role in hydrological processes and water resources management, including irrigation scheduling (Shahid 2011), vapour ux modelling (Fisher et al 2009), surface water runoff modelling (Wigmosta et al 1994), water balance estimation (Jaber et al 2016), groundwater recharge estimate (Salem et al 2017;Salehie et al 2022c), reservoir management (Ismail et al 2017), water stress assessment (Mohsenipour et al 2018) and climate change impact assessment (Shiru et al 2018; Salehie et al 2022a, b). ET is responsible for nearly two-thirds of water losses from the earth's surface.…”

Section: Introductionmentioning

confidence: 99%

Ranking of Empirical Evapotranspiration Models in Different Climate Zones of Pakistan

Khan

Shahid

et al. 2022

Preprint

Accurate estimation of evapotranspiration (ET) is vital for water resources development, planning and management, particularly in the present global warming context. A large number of empirical ET models have been developed for estimating ET. The main limitations of this method are that it requires several meteorological variables and an extensive data span to comprehend the ET pattern accurately, which is not available in most developing countries. The efficiency of 30 empirical ET models has been evaluated in this study to rank them for Pakistan to facilitate the selection of suitable models according to the availability of data. Princeton Global Meteorological Forcing daily climate data with a 0.25°×0.25° resolution for 1948–2016 was utilized. The ET estimated using Penman-Monteith (PM) was considered as the reference. Multi-criteria group decision-making (MCGDM) was used for the ranking of the models for Pakistan. The results showed the temperature-based Hamon as the best model for most Pakistan, followed by Hargreaves-Samani and Penman models. Hamon also showed the best performance in terms of different statistical metrics used in the study with a mean bias (PBias) of -50.2%, mean error (ME) of -1.62 mm and correlation coefficient (R2) of 0.65. Ivan showed the best performance among the humidity-based models, Irmak-RS and Ritch among the radiation-based models and Penman among the mass transfer-based models. Northern Pakistan was the most heterogeneous region in the relative performance of different ET models.