Comparative evaluation of the dynamics of terrestrial water storage and drought incidences using multiple data sources: Tana sub-basin, Ethiopia

Journal of Water and Climate Change, Год журнала: 2024, Номер 15(3), С. 1102 - 1119

Опубликована: Фев. 9, 2024

Abstract Evaluating water storage changes and addressing drought challenges in areas like the Tana sub-basin Ethiopia is difficult due to limited data availability. The aim of this study was evaluate dynamics terrestrial anomaly incidences by employing multiple source. Gravity Recovery Climate Experiment (GRACE) Global Land Data Assimilation System (GLDAS) datasets were used assess long-term using weighted deficit index (WWSDI). WWSDI identify periods, which ranged from severe extreme drought. Despite overall increase average annual total (TWSA) 0.43 cm/year a net gain 50.68 cm equivalent height 2003 2022, there instances deficits, particularly 2005, 2006, 2009, during historical periods. TWSA exhibited strong correlation with Lake precipitation anomalies after adjusting lag times. displayed high WSDI but weak SPI SPEI. Therefore, utilization GRACE GLDAS promising for evaluating monitoring data-deficient regions Ethiopia.

Язык: Английский

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Estimation of Groundwater Storage Change and Groundwater Recharge Using GRACE data in Jedeb Watershed Under the Application of Google Earth Engine

Air Soil and Water Research, Год журнала: 2024, Номер 17

Опубликована: Янв. 1, 2024

Over exploitation of Ground Water (GW) has resulted in lowering water table the Jedeb watershed. In this study, storage changes with GRACE satellite data and total annual precipitation CHIRPS Google Earth Engine system were investigated for watershed during 2003–2017. The groundwater recharge is estimated from a time series using fluctuation method. According to results obtained on fluctuations between 2003 2017, it was found that biggest increase levels (15 cm) occurred 2008, 2013, 2015, decrease (12.5 2012. net rate varied 18 25 cm/year 14-year period, average 21 cm/year. This study indicates GRACE-based estimation skilled enough provide monthly updates trend resource managers policymakers

Язык: Английский

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Remote Sensing Estimation of Shallow and Deep Aquifer Response to Precipitation‐Based Recharge Through Downscaling

Water Resources Research, Год журнала: 2024, Номер 60(12)

Опубликована: Дек. 1, 2024

Abstract The Gnangara groundwater system is a highly productive water resource in southwestern Australia. However, it considered one of the most vulnerable systems to climate change, due consistent declines precipitation and recharge, regional models project further into future. This study introduces new framework underpinned by machine learning techniques provide reliable estimates precipitation‐based recharge over whole Perth Basin (including system). By combining baseflow, evaporation, extraction, was estimated (testing site) (calibration using downscaled Groundwater Storage Anomalies (GWSA) from Gravity Recovery Climate Experiment (GRACE) mission. random forest regression (RFR) model used downscale spatial resolution GRACE 0.05° (approx. 5 km), providing estimable signals relatively small calibration site (∼2,200 km 2 ) order discern any meaningful original resolution. Our reveals that can be for accurately. growing impacts which has led sporadic patterns Western Australia, limit efficiency satellite remote sensing methods estimating especially deep complex aquifers.

Язык: Английский

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Downscaling inversion of GRACE-derived groundwater storage changes based on ensemble learning

International Journal of Digital Earth, Год журнала: 2023, Номер 16(1), С. 2998 - 3022

Опубликована: Авг. 10, 2023

Gravity Recovery and Climate Experiment (GRACE) satellite data monitors changes in terrestrial water storage, including groundwater, at a regional scale. However, the coarse spatial resolution limits its applicability to small watershed areas. This study introduces novel ensemble learning-based model using meteorological topographical enhance resolution. The effectiveness was evaluated groundwater-level observation from Henan rainstorm-affected area July 2021. factors influencing Groundwater Storage Anomalies (GWSA) were explored Permutation Importance (PI) other methods. results demonstrate that feature engineering Blender learning improve downscaling accuracy; Root Mean Square Error (RMSE) can be reduced by up 18.95%. Furthermore, decreased RMSE 3.58%, achieving an R-Square (R2) value of 0.7924. Restricting inversion June–August greatly enhanced accuracy, as evidenced holdout dataset test with R2 0.8247. overall GWSA variation January August exhibited 'slow rise, slow fall, sharp rise.' Additionally, heavy rain exhibits lag effect on groundwater supply. Meteorological drive fluctuations values distribution. Human activities also have significant impact.

Язык: Английский

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Spatio-temporal distribution of groundwater recharge under climate change in the Namngum++ river basin in lower Mekong region

Groundwater for Sustainable Development, Год журнала: 2024, Номер 25, С. 101171 - 101171

Опубликована: Апрель 3, 2024

Язык: Английский

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