Evaluation of TerraClimate gridded data in investigating the changes of reference evapotranspiration in different climates of Iran

Journal of Hydrology Regional Studies, Год журнала: 2024, Номер 52, С. 101678 - 101678

Опубликована: Янв. 28, 2024

Different climates in Iran, including the northwestern regions (cold), southern coasts (hot and humid) central dry). TerraClimate network data (5 km resolution) from 40 years (1981–2020) was used to investigate changes trend breaking point of reference crop evapotranspiration (ETo) time series for different Iran. Statistical assessment indices (RMSE, R2, BIAS) were initially employed assess accuracy with ground stations. The temporal-spatial alterations trend, ETo, its extreme values then investigated using Mann-Kendall, Sen's Slope, Pettitt, Bayesian quantile regression tests. correlation coefficient between monthly gridded ETo calculated be more than 0.95, an average value BIAS –1.1. studied had increased. increasing tendency high highest slopes cold winter (slope >70 %), hot/dry spring summer hot/humid 50 %). Additionally, findings Pettitt's test suggest that three Iran a rising break autumn (hot/dry), (hot/humid) seasons, respectively. This indicates rapid have been common 1996 2000.

Язык: Английский

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Estimation of the main air pollutants from different biomasses under combustion atmospheres by artificial neural networks

Chemosphere, Год журнала: 2024, Номер 352, С. 141484 - 141484

Опубликована: Фев. 16, 2024

Язык: Английский

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Enhancing global rainfall interception loss estimation through vegetation structure modeling

Journal of Hydrology, Год журнала: 2024, Номер 631, С. 130672 - 130672

Опубликована: Янв. 23, 2024

Accurate estimates of rainfall interception loss are crucial for modeling the water balance forested areas. However, considerable regional variability exists in process, and much uncertainty remains. This study enhances estimation at global scale by integrating remote sensing products into parameterization Gash's analytical model. We refer to this enhanced configuration as Global Interception Model (GIM). High-resolution satellite imagery was used derive vegetation indices spectral reflectance, which were then employed linear regression models estimate canopy cover fraction (c) storage capacity (Sv). Their importance ecological processes, land resource management, makes these parameters particular interest. The other two required run Gash model, namely mean evaporation rates under saturated conditions, obtained via integration MWSEP ERA5-Land meteorological products. Modeling performance evaluated using situ measurements gridded datasets. GIM exhibited a superior statistic when compared PMLv2 GLEAMv3.7a. Our results demonstrate high potential approach improving accuracy from local scales.

Язык: Английский

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Efficiency of global precipitation datasets in tropical and subtropical catchments revealed by large sampling hydrological modelling

Journal of Hydrology, Год журнала: 2024, Номер 633, С. 131016 - 131016

Опубликована: Март 5, 2024

Satellite-based and reanalysis precipitation products are widely adopted as complementary information to in situ measurements for estimating river discharge using hydrological modelling. However, there is still a notable research gap the literature associated with assessing accuracy of satellite-based or different tropical sub-tropical catchments at large-sampling modelling sensitivity analysis. We investigated precipitation, model performance parameter related seven data sets based on satellite products, i.e., CHIRPS, TRMM, GLDAS, IMERG, MERRA-2, PERSIANN-CDR, ERA5 over 714 contrasting subtropical located Brazil. used Génie Rural Journalier 4 (GR4J) simulate processes two approaches calibration: measured ground-based (approach I) each individual satellite/reanalysis II) calibrate models. The results showed that tend overestimate exception MERRA-2. CHIRPS only product produces unbiased estimates most catchments. calibration individually improved performance. MERRA-2 good terms both, estimation simulation period. In validation period, best KGE were IMERG TRMM (KGE > 0.64). errors better compensated via wet regions. varies according input, climate, catchment aridity. Overall, all exhibited their worst arid This study helps improve our understanding response regions while also providing key insights into reliability rainfall streamflow simulation. valuable hydrometeorological applications, climate change assessment, water resources disaster management, especially relatively sparse density stations.

Язык: Английский

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GRACE Downscaler: A Framework to Develop and Evaluate Downscaling Models for GRACE

Remote Sensing, Год журнала: 2023, Номер 15(9), С. 2247 - 2247

Опубликована: Апрель 24, 2023

Monitoring and managing groundwater resources is critical for sustaining livelihoods supporting various human activities, including irrigation drinking water supply. The most common method of monitoring well level measurements. These records can be difficult to collect maintain, especially in countries with limited infrastructure resources. However, long-term data collection required characterize evaluate trends. To address these challenges, we propose a framework that uses from the Gravity Recovery Climate Experiment (GRACE) mission downscaling models generate higher-resolution (1 km) predictions. designed flexible, allowing users implement any machine learning model interest. We selected four models: deep model, gradient tree boosting, multi-layer perceptron, k-nearest neighbors regressor. effectiveness framework, offer case study Sunflower County, Mississippi, using validate Overall, this paper provides valuable contribution field resource management by demonstrating remote sensing techniques improve resource, those who seek faster way begin use datasets applications.

Язык: Английский

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Semi-Arid to Arid Scenario Shift: Is the Cabrobó Desertification Nucleus Becoming Arid?

Remote Sensing, Год журнала: 2024, Номер 16(15), С. 2834 - 2834

Опубликована: Авг. 2, 2024

Monitoring areas susceptible to desertification contributes the strategic development of regions located in environments extreme hydric and social vulnerability. Therefore, objective this study is evaluate process soil degradation Desertification Nucleus Cabrobó (DNC) over past three decades using remote sensing techniques. This used primary climatic data from TerraClimate, geospatial land use cover (LULC), vegetation indices (SAVI LAI) via Google Earth Engine (GEE) Landsat 5/TM 8/OLI satellites, established aridity index (AI) 1992 2022. The results indicated 10 predominant LULC classes with native suppression, particularly agriculture urbanization. SAVI ranged −0.84 0.90, high values influenced by La Niña episodes increased rainfall; conversely, El Niño worsened rainfall regime DNC region. Based on Standardized Precipitation Index (SPI), it was possible correlate normal severe drought events years under influence phases. In summary, AI images that remained semi-arid transition an arid region a cyclical low-frequency phenomenon, occurring specific periods directly phenomena. Mann–Kendall analysis showed no increasing trend AI, Tau −0.01 p-value 0.97. During analyzed period, there increase Non-Vegetated Areas, which growing 0.42 analysis, representing exposed areas. Annual meteorological conditions within pattern region, annual averages precipitation actual evapotranspiration (ETa) close 450 mm average temperature 24 °C, showing changes only during events, did not show significant or decreasing trends analysis.

Язык: Английский

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Assessment of five global gridded precipitation estimates over a southern Mediterranean basin (Tensift, Morocco)

Geomatics Natural Hazards and Risk, Год журнала: 2025, Номер 16(1)

Опубликована: Фев. 25, 2025

Gridded Precipitation Products (GPPs) could exhibit discrepancies related to detecting precipitation amounts and patterns. This paper aims evaluate the accuracy of five GPPs currently in operational production over Tensift basin southern Mediterranean. The are reanalysis-based (ERA5, ERA5-Land, MERRA-2) multi-source data fusion (TerraClimate, MSWEPv2.8). Their annual monthly compared observations from fourteen ground gauges entire period 1980 2021 each decade this period. A set statistical metrics, such as Kling Gupta Efficiency (KGE) Root Mean Square Error (RMSE), well Bias, served carry out evaluation. Four main findings be highlighted: (i) have, general, a good correlation with gauge data; hence they used study temporal variability observed precipitation. (ii) ERA5-Land does not bring significant improvements estimates apart its finer spatial resolution. (iii) perform better plain than mountains. (iv) TerraClimate MSWEPv2.8 present consistency across decades. ERA5 TerraClimate, longest series, were visualize trends basin.

Язык: Английский

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ESTIMET: Enhanced and Spatial-Temporal Improvement of MODIS EvapoTranspiration algorithm for all sky conditions in tropical biomes

Remote Sensing of Environment, Год журнала: 2025, Номер 325, С. 114771 - 114771

Опубликована: Апрель 26, 2025

Язык: Английский

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Revealing the vegetation trend shifts related to meteorological and hydrological factors in central Asian endorheic basins

CATENA, Год журнала: 2025, Номер 256, С. 109137 - 109137

Опубликована: Май 9, 2025

Язык: Английский

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Characterization of water status and vegetation cover change in a watershed in Northeastern Brazil

Journal of South American Earth Sciences, Год журнала: 2023, Номер 130, С. 104546 - 104546

Опубликована: Авг. 25, 2023

Язык: Английский

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