The DOI matches its Crossref record; 48 of the 48 references it cites were found in a registry or an index.
A review of advances in flash flood forecasting
Abstract
Flash flooding is one of the most hazardous natural events, and it is frequently responsible for loss of life and severe damage to infrastructure and the environment. Research into the use of new modelling techniques and data types in flash flood forecasting has increased over the past decade, and this paper presents a review of recent advances that have emerged from this research. In particular, we focus on the use of quantitative precipitation estimates and forecasts, the use of remotely sensed data in hydrological modelling, developments in forecasting models and techniques, and uncertainty estimates. Over the past decade flash flood forecast lead‐time has expanded up to six hours due to improved rainfall forecasts. However the largest source of uncertainty of flash flood forecasts remains unknown future precipitation. An increased number of physically based hydrological models have been developed and used for flash flood forecasting and they have been found to give more plausible results when compared with the results of conceptual, statistical, and neural network models. Among the three methods for deciding flash flood occurrence discussed in this review, the rainfall comparison method (flash flood guidance) is most commonly used for flash flood forecasting as it is easily understood by the general public. Unfortunately, no existing model is capable of making reliable flash flood forecasts in urban watersheds even though the incidence of urban flash flooding is increasing due to increasing urbanisation. Copyright © 2011 John Wiley & Sons, Ltd.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Zadeh, L. A. (1965) · Information and Control · doi:10.1016/s0019-9958(65)90241-x · Cited by 67,855
Zadeh, L. A. (1996) · Cited by 46,844
Fuzzy sets as a basis for a theory of possibility
Zadeh, L. A. (1978) · Fuzzy Sets and Systems · doi:10.1016/0165-0114(78)90029-5 · Cited by 8,119
Fuzzy Logic with Engineering Applications
Ross, T. J. (2010) · Wiley eBooks · doi:10.1002/9781119994374 · Cited by 6,597
The future of distributed models: model calibration and uncertainty prediction
Beven, K., & Binley, A. (1992) · Hydrological Processes · doi:10.1002/hyp.3360060305 · Cited by 4,527
Computer Models of Watershed Hydrology
Singh, V. P. (1995) · Medical Entomology and Zoology · Cited by 3,273
Joyce, R. J., Janowiak, J. E., Arkin, P. A., & Xie, P. (2004) · Journal of Hydrometeorology · doi:10.1175/1525-7541(2004)005<0487:camtpg>2.0.co;2 · Cited by 3,208
A remote sensing surface energy balance algorithm for land (SEBAL). 1. Formulation
Bastiaanssen, W. G. M., Menenti, M., Feddes, R. A., & Holtslag, A. A. M. (1998) · Journal of Hydrology · doi:10.1016/s0022-1694(98)00253-4 · Cited by 3,118
Sensitivity Estimates for Nonlinear Mathematical Models
Sobol, I. M. (1990) · Medical Entomology and Zoology · Cited by 2,806
Henderson, F. M. (1966) · Macmillan eBooks · Cited by 2,194
Cited by
Mapping flood susceptibility in mountainous areas on a national scale in China
Zhao, G., Pang, B., Xu, Z., Yue, J., & Tu, T. (2018) · Science of The Total Environment · doi:10.1016/j.scitotenv.2017.10.037 · Cited by 389
Danumah, J. H., Odai, S. N., Saley, B. M., Szarzynski, J., Thiel, M., Kwaku, A., Kouame, F. K., & Akpa, L. Y. (2016) · Geoenvironmental Disasters · doi:10.1186/s40677-016-0044-y · Cited by 329
Perspectives for flood risk assessment and management for mega-city metro system
Lyu, H.-M., Shen, S.-L., Zhou, A., & Yang, J. (2019) · Tunnelling and Underground Space Technology · doi:10.1016/j.tust.2018.10.019 · Cited by 312
Hammami, S., Zouhri, L., Souissi, D., Souei, A., Zghibi, A., Marzougui, A., & Dlala, M. (2019) · Arabian Journal of Geosciences · doi:10.1007/s12517-019-4754-9 · Cited by 277
Dembélé, M., Hrachowitz, M., Savenije, H. H. G., Mariéthoz, G., & Schaefli, B. (2020) · Water Resources Research · doi:10.1029/2019wr026085 · Cited by 253
Metadata
- Authors
- Hapuarachchi, H. A. P., Wang, Q. J., & Pagano, T. C.
- Venue
- Hydrological Processes
- Publisher
- Wiley
- Published
- 2011-03-15
- Volume
- 25
- Issue
- 18
- Pages
- 2771-2784
- ISSN
- 0885-6087 (ISSN-L)
- 1099-1085
- OpenAlex
- W2072708097
- Cited by
- 560
- References
- 48
- FWCI
- 10.08
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: A review of advances in flash flood forecasting. https://app.cochat.ai/papers/10.1002/hyp.8040
- The paper
- Hapuarachchi, H. A. P., Wang, Q. J., & Pagano, T. C. (2011). A review of advances in flash flood forecasting. Hydrological Processes. https://doi.org/10.1002/hyp.8040
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.