Loughborough University
Leicestershire, UK
LE11 3TU
+44 (0)1509 263171
Loughborough University

Loughborough University Research Publications


Publications for Louise Slater

From (year): To (year):

Download all publications as Word document


Journal Articles

Khouakhi, A, Villarini, G, Zhang, W, Slater, LJ (Accepted for publication) Seasonal predictability of high sea level frequency using ENSO patterns along the U.S. West Coast, Advances in Water Resources, 131, ISSN: 0309-1708. DOI: 10.1016/j.advwatres.2019.07.007.

Slater, LJ, Thirel, G, Harrigan, S, Delaigue, O, Hurley, A, Khouakhi, A, Prosdocimi, I, Vitolo, C, Smith, K (2019) Using R in hydrology: A review of recent developments and future directions, Hydrology and Earth System Sciences, 23(7), pp.2939-2963, ISSN: 1027-5606. DOI: 10.5194/hess-23-2939-2019.

Slater, LJ, Thirel, G, Harrigan, S, Delaigue, O, Hurley, A, Khouakhi, A, Prodoscimi, I, Vitolo, C, Smith, K (2019) Using R in hydrology: a review of recent developments and future directions, Hydrology and Earth System Sciences Discussions, pp.1-33, DOI: 10.5194/hess-2019-50.

Slater, L and Villarini, G (2018) Enhancing the predictability of seasonal streamflow with a statistical-dynamical approach, Geophysical Research Letters, 45(13), pp.6504-6513, ISSN: 0094-8276. DOI: 10.1029/2018GL077945.

Villarini, G and Slater, LJ (2018) Examination of changes in annual maximum gauge height in the continental United States using quantile regression, Journal of Hydrologic Engineering, 23(3), ISSN: 1084-0699. DOI: 10.1061/(ASCE)HE.1943-5584.0001620..

Lutz, SR, Popp, A, Van Emmerik, T, Gleeson, T, Kalaugher, L, Mobius, K, Mudde, T, Walton, B, Hut, R, Savenije, H, Slater, L, Solcerova, A, Stoof, C, Zink, M (2018) HESS Opinions: Science in today's media landscape – challenges and lessons from hydrologists and journalists, Hydrology and Earth System Sciences, ISSN: 1027-5606. DOI: 10.5194/hess-2018-13.

Slater, L and Wilby, R (2017) Measuring the changing pulse of rivers, Science, 357(6351), pp.552-552, ISSN: 0036-8075. DOI: 10.1126/science.aao2441.

Slater, LJ, Villarini, G, Bradley, AA, Vecchi, GA (2017) A dynamical statistical framework for seasonal streamflow forecasting in an agricultural watershed, Climate Dynamics, ISSN: 0930-7575. DOI: 10.1007/s00382-017-3794-7.

Clubb, FJ, Mudd, SM, Milodowski, DT, Valters, DA, Slater, LJ, Hurst, MD, Limaye, AB (2017) Geomorphometric delineation of floodplains and terraces from objectively defined topographic thresholds, Earth Surface Dynamics, 5(3), pp.369-385, DOI: 10.5194/esurf-5-369-2017.

Wilby, R, Clifford, N, De Luca, P, Harrigan, S, Hillier, J, Hodgkins, R, Johnson, MF, Matthews, TKR, Murphy, C, Noone, S, Parry, S, Prudhomme, C, Rice, S, Slater, L, Smith, K, Wood, P (2017) The “dirty dozen” of freshwater science: Detecting then reconciling hydrological data biases and errors, Wiley Interdisciplinary Reviews (WIREs) Water, ISSN: 2049-1948. DOI: 10.1002/wat2.1209.

Slater, L and Villarini, G (2017) On the impact of gaps on trend detection in extreme streamflow time series, International Journal of Climatology, ISSN: 1097-0088. DOI: 10.1002/joc.4954.

Slater, L, Villarini, G, Bradley, A (2017) Weighting of NMME temperature and precipitation forecasts across Europe, Journal of Hydrology, ISSN: 0022-1694. DOI: 10.1016/j.jhydrol.2017.07.029.

Zhang, W, Villarini, G, Slater, L, Vecchi, GA, Bradley, A (2017) Improved ENSO forecasting using Bayesian updating and the North American Multi Model Ensemble (NMME), Journal of Climate, ISSN: 1520-0442. DOI: 10.1175/JCLI-D-17-0073.1.

Slater, L and Villarini, G (2017) Evaluating the drivers of seasonal streamflow in the U.S. Midwest, Water, ISSN: 2073-4441. DOI: 10.3390/w9090695.

Slater, LJ and Villarini, G (2016) Recent trends in U.S. flood risk, Geophysical Research Letters, 43(24), pp.12,428-12,436, ISSN: 0094-8276. DOI: 10.1002/2016GL071199.

Slater, LJ, Villarini, G, Bradley, AA (2016) Evaluation of the skill of North-American Multi-Model Ensemble (NMME) Global Climate Models in predicting average and extreme precipitation and temperature over the continental USA, Climate Dynamics, ISSN: 0930-7575. DOI: 10.1007/s00382-016-3286-1.

Slater, L (2016) To what extent have changes in channel capacity contributed to flood hazard trends in England and Wales?, Earth Surface Processes and Landforms, 41(8), pp.1115-1128, ISSN: 0197-9337. DOI: 10.1002/esp.3927.

Slater, L, Singer, MB, Kirchner, JW (2015) Hydrologic versus geomorphic drivers of trends in flood hazard, Geophysical Research Letters, 42(2), pp.370-376, ISSN: 0094-8276. DOI: 10.1002/2014GL062482.

Slater, L (2015) Changing channels, Planet Earth, (Autumn), pp.22-23, ISSN: 1479-2605.

Clubb, FJ, Mudd, SM, Milodowski, DT, Hurst, MD, Slater, L (2014) Objective extraction of channel heads from high-resolution topographic data, Water Resources Research, 50(5), pp.4283-4304, ISSN: 0043-1397. DOI: 10.1002/2013WR015167.

Slater, L and Singer, MB (2013) Imprint of climate and climate change in alluvial riverbeds: Continental United States, 1950-2011, Geology, 41(5), pp.595-598, ISSN: 0091-7613. DOI: 10.1130/G34070.1.

Piegay, H, Alber, A, Slater, L, Bourdin, L (2009) Census and typology of braided rivers in the French Alps, Aquatic Sciences, 71(3), pp.371-388, ISSN: 1015-1621. DOI: 10.1007/s00027-009-9220-4.



Chapters

Villarini, G and Slater, L (2017) Climatology of flooding in the United States. In Oxford Research Encyclopedia of Natural Hazard Science, © Oxford University Press (OUP). DOI: 10.1093/acrefore/9780199389407.013.123.



Other

Clubb, FJ, Mudd, SM, Milodowski, DT, Valters, DA, Slater, LJ, Hurst, MD, Limaye, AB (2017) Geomorphometric delineation of floodplains and terraces from objectively defined topographic thresholds, Abstract. Floodplain and terrace features can provide information about current and past fluvial processes, including channel response to varying discharge and sediment flux; sediment storage; and the climatic or tectonic history of a catchment. Previous methods of identifying floodplain and terraces from digital elevation models (DEMs) tend to be semi-automated, requiring the input of independent datasets or manual editing by the user. In this study we present a new, fully automated method of identifying floodplain and terrace features based on two thresholds: local gradient, and elevation compared to the nearest channel. These thresholds are calculated statistically from the DEM using quantile-quantile plots and do not need to be set manually for each landscape in question. We test our method against field-mapped floodplain initiation points, published flood hazard maps, and digitised terrace surfaces from seven field sites from the US and one field site from the UK. For each site, we use high-resolution DEMs derived from light detection and ranging (LiDAR) where available, as well as coarser resolution national datasets to test the sensitivity of our method to grid resolution. We find that our method is successful in extracting floodplain and terrace features compared to the field-mapped data from the range of landscapes and grid resolutions tested. The method is most accurate in areas where there is a contrast in slope and elevation between the feature of interest and the surrounding landscape, such as confined valley settings. Our method provides a new tool for rapidly and objectively identifying floodplain and terrace features on a landscape scale, with applications including flood risk mapping, reconstruction of landscape evolution, and quantification of sediment storage routing. . DOI: 10.5194/esurf-2017-21.



Getting in touch

Research Office
Loughborough University
Loughborough
Leicestershire
LE11 3TU
researchpolicy@lboro.ac.uk
+44 (0)1509 222453