Understanding Spatio-Temporal Hydrological Dynamics Using SWAT: A Case Study in the Pativilca Basin DOI Creative Commons

Yenica Pachac-Huerta,

Waldo Lavado‐Casimiro, Melania Zapana

et al.

Hydrology, Journal Year: 2024, Volume and Issue: 11(10), P. 165 - 165

Published: Oct. 4, 2024

This study investigates the hydrological dynamics of Pativilca Basin in Southern Hemisphere using SWAT (Soil and Water Assessment Tool) model. Seventy-seven watersheds across a mountainous region were analyzed elevation data, land cover, soil type, gridded meteorological products (RAIN4PE PISCO) for simulations. Watershed delineation, aided by Digital Elevation Model, enabled identification critical drainage points definition Hydrological Response Units (HRUs). The model calibration validation, performed SWAT-CUP with SUFI-2 algorithm, achieved Nash–Sutcliffe Efficiency (NSE) values 0.69 0.72, respectively. Cluster analysis categorized into six distinct groups unique climatic characteristics. results showed significant spatial variability precipitation temperature, pronounced seasonality influencing daily flow patterns. higher-altitude exhibited greater water storage more effective aquifer recharge, whereas lower-altitude watersheds, despite receiving less precipitation, displayed higher flows due to runoff from upstream areas. These findings emphasize importance incorporating resource planning regions demonstrate model’s effectiveness predicting responses Basin, laying groundwork future research mountain hydrology.

Language: Английский

Climate change impacts on flood dynamics and seasonal flow variability in central Nepal: the Kaligandaki River Basin case DOI
Koshish Raj Maharjan, Utsav Bhattarai, Pawan Kumar Bhattarai

et al.

Theoretical and Applied Climatology, Journal Year: 2025, Volume and Issue: 156(3)

Published: Feb. 11, 2025

Language: Английский

Citations

0
Assessing monthly rainfall and runoff trends for sustainable water resource management in lower Shoalhaven river DOI Creative Commons
Rong Ji, Shu‐Qing Yang, Muttucumaru Sivakumar

et al.

Discover Water, Journal Year: 2025, Volume and Issue: 5(1)

Published: March 3, 2025

Language: Английский

Citations

0
Sensitivity Analysis of Soil Hydraulic Parameters for Improved Flow Predictions in an Atlantic Forest Watershed Using the MOHID-Land Platform DOI Creative Commons
Dhiego da Silva Sales, Jader Lugon, David de Andrade Costa

et al.

Eng—Advances in Engineering, Journal Year: 2025, Volume and Issue: 6(4), P. 65 - 65

Published: March 27, 2025

Soil controls water distribution, which is crucial for accurate hydrological modeling. MOHID-Land a physically based, spatially distributed model that uses van Genuchten–Mualem (VGM) functions to calculate content in porous media. The hydraulic soil parameters of VGM are dependent on type and typically estimated from experimental data; however, they often obtained using pedotransfer functions, carry significant uncertainty. As result, calibration frequently required account both the natural spatial variability uncertainties estimation. This study focuses representative Atlantic Forest watershed. It assesses sensitivity channel flow mathematical approach based residuals derivative, aimed at enhancing efficiency MOHID-Land. model’s performance significantly improved following calibration, considering only five parameters. NSE 0.16 base simulation 0.53 after calibration. A analysis indicated curve adjustment parameter (n) as most sensitive parameter, followed by saturated (θs) 10% variation. Additionally, combined change θs, n, residual (θr), (α), conductivity (Ksat) values improves performance, reducing peaks increasing baseflow.

Language: Английский

Citations

0
Enhancing River Flow Predictions in Mohid-Land Through Integration of Gridded Soil Data and Hydraulic Parameters Using the Mohid Soil Tool DOI
Dhiego da Silva Sales, David de Andrade Costa, Jader Lugon

et al.

Published: Jan. 1, 2025

Language: Английский

Citations

0
Quantile Analysis of Economic Growth, Foreign Direct Investment, and Renewable Energy on CO2 Emissions in Brazil: Insights for Sustainable Development DOI Creative Commons

Fatema Fauze Moh Ben Abd Alah,

Opeoluwa Seun Ojekemi

Energies, Journal Year: 2025, Volume and Issue: 18(9), P. 2256 - 2256

Published: April 29, 2025

Brazil, as an emerging and newly industrialized nation, presents a complex dynamic between economic advancement environmental sustainability. This study investigates the influence of coal consumption (COAL), gross domestic product (GDP), renewable energy (REN), foreign direct investment (FDI) on CO2 emissions in Brazil using quarterly data from 1990Q1 to 2020Q4. Employing Quantile-on-Quantile Kernel-Based Regularized Least Squares (QQKRLS) method Granger Causality (QQGC) test, we uncover significant nonlinear distributional heterogeneities these relationships. Results show that COAL, GDP, FDI consistently exert positive impact across most quantiles, whereas REN significantly reduces emissions, particularly at upper emission quantiles. analysis confirms all four variables are predictors emissions. The contributes methodologically by applying QQKRLS QQGC reveal nuanced interactions distribution—an over traditional linear approaches. Empirically, it provides Brazil-specific evidence dual role growth both driving offering potential for sustainable transition. Based findings, recommend policies prioritize sector-specific screening promote green technologies, accelerate infrastructure, impose adaptive carbon pricing mechanisms reflect heterogeneous These insights support Brazil’s climate targets guide balanced path toward inclusive development.

Language: Английский

Citations

0
Assessing the sensitivity of physiographical parameters in modeling hydrological ecosystem services that support food security: The case of Vietnamese Mekong Delta DOI Creative Commons
Sreejita Banerjee, Ho Huu Loc, Indrajit Pal

et al.

Modeling Earth Systems and Environment, Journal Year: 2025, Volume and Issue: 11(4)

Published: May 2, 2025

Language: Английский

Citations

0
Developing an ensemble machine learning framework for enhanced climate projections using CMIP6 data in the Middle East DOI Creative Commons
Younes Khosravi, Taha B. M. J. Ouarda, Saeid Homayouni

et al.

npj Climate and Atmospheric Science, Journal Year: 2025, Volume and Issue: 8(1)

Published: May 8, 2025

Language: Английский

Citations

0
Water quality estimates using machine learning techniques in an experimental watershed DOI Creative Commons
David de Andrade Costa, Yared Bayissa, Kargean Vianna Barbosa

et al.

Journal of Hydroinformatics, Journal Year: 2024, Volume and Issue: 26(11), P. 2798 - 2814

Published: Nov. 1, 2024

ABSTRACT This study aims to identify the best machine learning (ML) approach predict concentrations of biochemical oxygen demand (BOD), nitrate, and phosphate. Four ML techniques including Decision tree, Random Forest, Gradient Boosting XGBoost were compared estimate water quality parameters based on biophysical (i.e., population, basin area, river slope, level, stream flow), physicochemical properties conductivity, turbidity, pH, temperature, dissolved oxygen) input parameters. The innovation lies in combination on-the-spot variables with additional characteristics watershed. model performances evaluated using coefficient determination (R2), Nash-Sutcliffe efficiency (NSE), Root Mean Squared Error (RMSE) Kling-Gupta Efficiency (KGE) coefficient. robust five-fold cross-validation, along hyperparameter tuning, achieved R2 values 0.71, 0.66, 0.69 for phosphate, BOD; NSE 0.67, 0.65, 0.62, KGE 0.64, 0.75, 0.60, respectively. yielded good results, showcasing superior performance when considering all analysis performed, but his was closely match by other algorithms. overall modeling design approach, which includes careful consideration data preprocessing, dataset splitting, statistical evaluation metrics, feature analysis, curve are just as important algorithm selection.

Language: Английский

Citations

3
Evaluating the potential of Nature-based solutions to mitigate land use and climate change impacts on the hydrology of the Gefersa and Legedadi watersheds in Ethiopia DOI Creative Commons
Yared Bayissa, Raghavan Srinivasan, Johannes Hunink

et al.

Journal of Hydrology Regional Studies, Journal Year: 2024, Volume and Issue: 57, P. 102130 - 102130

Published: Dec. 12, 2024

Language: Английский

Citations

2
The water cycle of small catchments impacted with tailings mudflows: A study in the Ferro-Carvão watershed after the breakup of B1 dam in Brumadinho DOI Creative Commons
Polyana Pereira, Luís Filipe Sanches Fernandes, Renato Farias do Valle

et al.

The Science of The Total Environment, Journal Year: 2024, Volume and Issue: 949, P. 174971 - 174971

Published: July 26, 2024

The B1 tailings dam of Córrego do Feijão iron-ore mine owned by Vale, S.A. company collapsed in 25 January 2019 releasing to the Ferro-Carvão stream watershed (32.6 km2) as much 11.7 Mm3 waste. A major share (8.9 Mm3) has been deposited along channel and margins forming a 2.7 km2 patch. main purpose this study was question whether deposit impacted local water cycle how. Using Soil Water Assessment Tool (SWAT) hydrologic model, balance components 36 response units (HRU) were calculated for pre- (S1) post- (S2) rupture scenarios represented appropriate soil, land use cover. results revealed an increase evapotranspiration from S1 S2, related sudden removal vegetation valley replacement with blanket mud, which raised exposure Earth's surface sunlight hence soil evaporation. For 11 HRU (10.3 located around deposit, decrease lateral flow observed, accompanied percolation slight groundwater flow. In case, changes observed between S2 reflected barrier effect imposed flows tailings, shifted towards vertical direction (percolation). Thus, followed easier route until reaching shallow aquifer being converted into As per modelling outcomes, impacts are relevant because they affected 1/3 watershed, claim complete tailings.

Language: Английский

Citations

0