Cover Image

Dataset and Model Code for SWAT+ and Machine Learning Assessment of Satellite Precipitation in Data-Scarce Regions

Fuente: Zenodo

Saved in:

Bibliographic Details
Main Author:	Almeida, Manuel
Format:	Recurso digital
Published:	Zenodo 2025
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Hydrological Modelling Using Gridded and Ground‐Based Precipitation Datasets in Data‐Scarce Mountainous Regions
by: Rajesh Khatakho, et al.
Published: (2024)

An Algorithm for Learning Smaller Representations of Models With Scarce Data
by: de Wynter, Adrian
Published: (2020)

Learning Shortest Paths When Data is Scarce
by: Matsypura, Dmytro, et al.
Published: (2026)

Data-driven Precipitation Nowcasting Using Satellite Imagery
by: Park, Young-Jae, et al.
Published: (2024)

Scarce Resource Allocations That Rely On Machine Learning Should Be Randomized
by: Jain, Shomik, et al.
Published: (2024)

SWAT_Files
by: Srinivas
Published: (2024)

Evaluation of Machine Learning Models to Improve Daily Precipitation Estimations From Orbital Remote Sensing and Reanalysis Data
by: Emerson da Silva Freitas, et al.
Published: (2025)

Rainy: Unlocking Satellite Calibration for Deep Learning in Precipitation
by: Yu, Zhenyu, et al.
Published: (2025)

Benchmarking Quantum Surrogate Models on Scarce and Noisy Data
by: Stein, Jonas, et al.
Published: (2023)

Monthly actual evapotranspiration satellite data with SWAT and SWAT-CUP format
by: Abbaspour, Karim, et al.
Published: (2019)

DYffCast: Regional Precipitation Nowcasting Using IMERG Satellite Data. A case study over South America
by: Seal, Daniel, et al.
Published: (2024)

Chunked Data Shapley: A Scalable Dataset Quality Assessment for Machine Learning
by: Loizou, Andreas, et al.
Published: (2025)

Language Models can Exploit Cross-Task In-context Learning for Data-Scarce Novel Tasks
by: Chatterjee, Anwoy, et al.
Published: (2024)

When Data Is Scarce: Scaling Sparse Language Models with Repeated Training
by: Wu, Boqian, et al.
Published: (2026)

Neural Stochastic Processes for Satellite Precipitation Refinement
by: Nagashima, Shunya, et al.
Published: (2026)

Geostatistical Interpolation Approach for Improving Flood Simulation Within a Data‐Scarce Region in the Tibetan Plateau
by: Kanon Guédet Guédé, et al.
Published: (2024)

Hydrological Modelling of Flow and Nitrate Load Using SWAT+
by: Mahesh R. Tapas, et al.
Published: (2025)

Analysis of Local Hydro‐meteorological Drought Characteristics Using Regional IMDAA Reanalysis and SWAT
by: Ankita Manekar, et al.
Published: (2026)

Leveraging Natural Language Processing and Machine Learning for Evidence-Based Food Security Policy Decision-Making in Data-Scarce Making
by: Singh, Karan Kumar, et al.
Published: (2026)

A Transfer Framework for Enhancing Temporal Graph Learning in Data-Scarce Settings
by: Agarwal, Sidharth, et al.
Published: (2025)

Improving Open-world Continual Learning under the Constraints of Scarce Labeled Data
by: Li, Yujie, et al.
Published: (2025)

Cross-Learning from Scarce Data via Multi-Task Constrained Optimization
by: Agorio, Leopoldo, et al.
Published: (2025)

Topological Inductive Bias fosters Multiple Instance Learning in Data-Scarce Scenarios
by: Kazeminia, Salome, et al.
Published: (2023)

Evaluation of the Performance of Climate Forecast System Reanalysis Precipitation Data for Modeling Hydrology and Phosphorus Flux Using the SWAT Model in a Mediterranean Watershed in Algeria (North Africa): A Case Study of the Tafna River
by: Samia Bouzid, et al.
Published: (2026)

Deriving Canada-wide soils dataset for use in Soil and Water Assessment Tool (SWAT)
by: Cordeiro, Marcos R C, et al.
Published: (2017)

Scarce Data, Noisy Inferences, and Overfitting: The Hidden Flaws in Ecological Dynamics Modelling
by: Castro, Mario, et al.
Published: (2025)

A Framework for the Bayesian Calibration of Complex and Data-Scarce Models in Applied Sciences
by: Schenk, Christina, et al.
Published: (2026)

Evaluating the Role of Training Data Origin for Country-Scale Cropland Mapping in Data-Scarce Regions: A Case Study of Nigeria
by: Gajardo, Joaquin, et al.
Published: (2023)

GPROF-IR: An Improved Single-Channel Infrared Precipitation Retrieval for Merged Satellite Precipitation Products
by: Pfreundschuh, Simon, et al.
Published: (2026)

Exploring Pathological Speech Quality Assessment with ASR-Powered Wav2Vec2 in Data-Scarce Context
by: Nguyen, Tuan, et al.
Published: (2024)

CRU and GCM data for SWAT model
by: Abbaspour, Karim, et al.
Published: (2019)

Transferring Self‐Supervised Pretrained Models for SHM Data Anomaly Detection With Scarce Labeled Data
by: Mingyuan Zhou, et al.
Published: (2025)

Multi-View Subgraph Neural Networks: Self-Supervised Learning with Scarce Labeled Data
by: Wang, Zhenzhong, et al.
Published: (2024)

Self-Supervised Federated Learning under Data Heterogeneity for Label-Scarce Diatom Classification
by: Tan, Mingkun, et al.
Published: (2026)

Improvement of Soil Water Assessment Tool (SWAT) wetland module for modelling of ephemeral pond hydrology
by: Mohammad Bizhanimanzar, et al.
Published: (2024)

Use of Machine Learning Techniques for Monthly Precipitation and Air Temperature Forecasting in Different Climate Regions Across Brazil
by: Cleverson Henrique de Freitas, et al.
Published: (2025)

Selection of CMIP6 Models for Regional Precipitation Projection and Climate Change Assessment in the Jhelum and Chenab River Basins
by: Jamal, Saad Ahmed, et al.
Published: (2026)

Performance Assessment of Multiple Satellite Rainfall Products in the Levant Region
by: Fakhry Jayousi, et al.
Published: (2025)

The Impact of an XAI-Augmented Approach on Binary Classification with Scarce Data
by: Wen, Ximing, et al.
Published: (2024)

MAGPI: Multifidelity-Augmented Gaussian Process Inputs for Surrogate Modeling from Scarce Data
by: Rex, Atticus, et al.
Published: (2026)