16 citations as recorded by crossref.

1. Developing stage-specific drought vulnerability curves for maize: The case study of the Po River basin B. Monteleone et al. 10.1016/j.agwat.2022.107713
2. Assessing the impact of sowing dates and ENSO in a drought index-based insurance for soybean D. Perondi et al. 10.1016/j.crm.2023.100544
3. Sustainable Geoinformatic Approaches to Insurance for Small-Scale Farmers in Colombia A. Abd Rabuh et al. 10.3390/su16125104
4. Assessment of climate impact on grape productivity: A new application for bioclimatic indices in Italy L. Massano et al. 10.1016/j.scitotenv.2023.167134
5. Evaluating Sustainability Improvement of Pressure Regime in Water Distribution Systems Due to Network Partitioning I. Borzì 10.3390/w14111787
6. Estimations of Crop Losses Due to Flood Using Multiple Sources of Information and Models: The Case Study of the Panaro River B. Monteleone et al. 10.3390/w15111980
7. Data-driven approaches to built environment flood resilience: A scientometric and critical review P. Rathnasiri et al. 10.1016/j.aei.2023.102085
8. Modelling the response of wheat yield to stage-specific water stress in the Po Plain B. Monteleone et al. 10.1016/j.agwat.2023.108444
9. Navigating Flood Resilience: Challenges, Solutions, and Lessons Learnt from the Dominican Republic H. Reynoso Vanderhorst et al. 10.3390/w16030382
10. Big data, risk classification, and privacy in insurance markets M. Eling et al. 10.1057/s10713-024-00098-5
11. Sustainability risk in insurance companies: A machine learning analysis F. Oquendo‐Torres & M. Segovia‐Vargas 10.1111/1758-5899.13440
12. The Role of Data-Driven Methodologies in Weather Index Insurance L. Hernández-Rojas et al. 10.3390/app13084785
13. Evolution of research on climate risk insurance: A bibliometric analysis from 1975 to 2022 Y. Lin et al. 10.1016/j.accre.2023.08.003
14. Index-based insurance to mitigate current and future extreme events financial losses for water utilities G. Gesualdo et al. 10.1016/j.ijdrr.2023.104218
15. Comparison of deep learning models for milk production forecasting at national scale L. Cesarini et al. 10.1016/j.compag.2024.108933
16. Where and how machine learning plays a role in climate finance research A. Alonso-Robisco et al. 10.1080/20430795.2024.2370325