|Twenty-three unsolved problems in hydrology (UPH)–a community perspective|
G Blöschl, MFP Bierkens, A Chambel, C Cudennec, G Destouni, A Fiori, ...
Hydrological sciences journal 64 (10), 1141-1158, 2019
|Satellite-derived Digital Elevation Model (DEM) selection, preparation and correction for hydrodynamic modelling in large, low-gradient and data-sparse catchments|
AA Jarihani, JN Callow, TR McVicar, TG Van Niel, JR Larsen
Journal of Hydrology 524, 489-506, 2015
|Blending Landsat and MODIS data to generate multispectral indices: A comparison of “Index-then-Blend” and “Blend-then-Index” approaches|
AA Jarihani, TR McVicar, TG Van Niel, IV Emelyanova, JN Callow, ...
Remote Sensing 6 (10), 9213-9238, 2014
|Evaluation of multiple satellite altimetry data for studying inland water bodies and river floods|
AA Jarihani, JN Callow, K Johansen, B Gouweleeuw
Journal of Hydrology 505, 78-90, 2013
|Assessment of UAV and ground-based structure from motion with multi-view stereo photogrammetry in a gullied savanna catchment|
J Koci, B Jarihani, JX Leon, RC Sidle, SN Wilkinson, R Bartley
ISPRS International Journal of Geo-Information 6 (11), 328, 2017
|Hydrogeomorphic processes and scaling issues in the continuum from soil pedons to catchments|
RC Sidle, T Gomi, JCL Usuga, B Jarihani
Earth-Science Reviews 175, 75-96, 2017
|Landslide detection using multi-scale image segmentation and different machine learning models in the higher himalayas|
S Tavakkoli Piralilou, H Shahabi, B Jarihani, O Ghorbanzadeh, ...
Remote Sensing 11 (21), 2575, 2019
|Where does all the water go? Partitioning water transmission losses in a data-sparse, multi-channel and low-gradient dryland river system using modelling and remote sensing|
AA Jarihani, JR Larsen, JN Callow, TR McVicar, K Johansen
Journal of Hydrology 529, 1511-1529, 2015
|When is migration a maladaptive response to climate change?|
J Chris, C Stacy, C Chanthan, J Ben
Regional Environment Change, 1-12, 2018
|A semi-automated object-based gully networks detection using different machine learning models: A case study of Bowen catchment, Queensland, Australia|
H Shahabi, B Jarihani, S Tavakkoli Piralilou, D Chittleborough, M Avand, ...
Sensors 19 (22), 4893, 2019
|Rainfall-runoff modelling using hydrological connectivity index and artificial neural network approach|
H Asadi, K Shahedi, B Jarihani, RC Sidle
Water 11 (2), 212, 2019
|Characterisation of hydrological response to rainfall at multi spatio-temporal scales in savannas of semi-arid Australia|
B Jarihani, RC Sidle, R Bartley, CH Roth, SN Wilkinson
Water 9 (7), 540, 2017
|Linking hydrological connectivity to gully erosion in savanna rangelands tributary to the Great Barrier Reef using structure‐from‐motion photogrammetry|
J Koci, RC Sidle, B Jarihani, MJ Cashman
Land Degradation & Development 31 (1), 20-36, 2020
|Effect of reduced grazing pressure on sediment and nutrient yields in savanna rangeland streams draining to the Great Barrier Reef|
J Koci, RC Sidle, AE Kinsey-Henderson, R Bartley, SN Wilkinson, ...
Journal of Hydrology 582, 124520, 2020
|Hydrogeomorphic processes affecting dryland gully erosion: Implications for modelling|
RC Sidle, B Jarihani, SLI Kaka, J Koci, A Al-Shaibani
Progress in Physical Geography: Earth and Environment 43 (1), 46-64, 2019
|Quantifying the effectiveness of gully remediation on off-site water quality: preliminary results from demonstration sites in the Burdekin catchment|
R Bartley, A Hawdon, A Henderson, S Wilkinson, N Goodwin, B Abbott, ...
NESP Project 2 (4), 2017
|Monitoring of vegetation condition using the NDVI/ENSO anomalies in Central Asia and their relationships with ONI (very strong) phases|
D Aralova, K Toderich, B Jarihani, D Gafurov, L Gismatulina
Earth Resources and Environmental Remote Sensing/GIS Applications VII 10005 …, 2016
|Development of alternative SWAT-based models for simulating water budget components and streamflow for a karstic-influenced watershed|
MR Eini, S Javadi, M Delavar, PW Gassman, B Jarihani
Catena 195, 104801, 2020
|Measuring, modelling and managing gully erosion at large scales: A state of the art|
M Vanmaercke, P Panagos, T Vanwalleghem, A Hayas, S Foerster, ...
Earth-Science Reviews, 103637, 2021
|Gully erosion susceptibility mapping (GESM) using machine learning methods optimized by the multi‑collinearity analysis and K-fold cross-validation|
O Ghorbanzadeh, H Shahabi, F Mirchooli, K Valizadeh Kamran, S Lim, ...
Geomatics, Natural Hazards and Risk 11 (1), 1653-1678, 2020