Articles | Volume 22, issue 6
https://doi.org/10.5194/hess-22-3533-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/hess-22-3533-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
29 Jun 2018
Research article |
| 29 Jun 2018
| 29 Jun 2018
Seasonal streamflow forecasting in the upper Indus Basin of Pakistan: an assessment of methods
Stephen P. Charles
CORRESPONDING AUTHOR
CSIRO Land and Water, Floreat, 6014, Australia
Quan J. Wang
The University of Melbourne, Parkville, 3010, Australia
Mobin-ud-Din Ahmad
CSIRO Land and Water, Canberra, 2601, Australia
Danial Hashmi
Water and Power Development Authority, Lahore, Pakistan
Andrew Schepen
CSIRO Land and Water, Dutton Park, 4102, Australia
Geoff Podger
CSIRO Land and Water, Canberra, 2601, Australia
David E. Robertson
CSIRO Land and Water, Clayton, 3168, Australia
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Cited
19 citations as recorded by crossref.
- Synoptic–Dynamic Patterns Affecting Iran’s Autumn Precipitation during ENSO Phase Transitions F. Bahrami et al. 10.3390/cli9070106
- Hydrologic interpretation of machine learning models for 10-daily streamflow simulation in climate sensitive upper Indus catchments H. Mushtaq et al. 10.1007/s00704-024-04932-8
- Streamflow Variations in Monthly, Seasonal, Annual and Extreme Values Using Mann-Kendall, Spearmen’s Rho and Innovative Trend Analysis M. Ashraf et al. 10.1007/s11269-020-02723-0
- Development of a national 7-day ensemble streamflow forecasting service for Australia H. Hapuarachchi et al. 10.5194/hess-26-4801-2022
- Co-designing Indus Water-Energy-Land Futures Y. Wada et al. 10.1016/j.oneear.2019.10.006
- Effects of riparian buffer and stream channel widths on ecological indicators in the upper and lower Indus River basins in Pakistan A. Hira et al. 10.3389/fenvs.2023.1113482
- Socio-hydrological assessment of water security in canal irrigation systems: A conjoint quantitative analysis of equity and reliability A. Siddiqi et al. 10.1016/j.wasec.2018.11.001
- An improved long short-term memory network for streamflow forecasting in the upper Yangtze River S. Zhu et al. 10.1007/s00477-020-01766-4
- Flood Risk Assessment Based on Hydrodynamic Model—A Case of the China–Pakistan Economic Corridor X. Sun et al. 10.3390/w15244295
- A blueprint for coupling a hydrological model with fine- and coarse-scale atmospheric regional climate change models for probabilistic streamflow projections C. Rajulapati et al. 10.1016/j.jhydrol.2024.132080
- Impacts of Stressors on Riparian Health Indicators in the Upper and Lower Indus River Basins in Pakistan A. Hira et al. 10.3390/ijerph192013239
- A new approach of coupled long-range forecasts for streamflow and groundwater level D. Robertson et al. 10.1016/j.jhydrol.2024.130837
- A Medium and Long-Term Runoff Forecast Method Based on Massive Meteorological Data and Machine Learning Algorithms Y. Li et al. 10.3390/w13091308
- Investigating the effects of local weather, streamflow lag, and global climate information on 1-month-ahead streamflow forecasting by using XGBoost and SHAP: two case studies involving the contiguous USA J. Liu et al. 10.1007/s11600-022-00928-y
- Improving medium-range streamflow forecasts over South Korea with a dual-encoder transformer model D. Lee & K. Ahn 10.1016/j.jenvman.2024.122114
- Hydropower and seasonal pumped hydropower storage in the Indus basin:pros and cons J. Hunt et al. 10.1016/j.est.2021.102916
- Hydrological peaks evaluation at Chitral and Tarbela stations, Pakistan, using combined Bayesian regularized neural network and signal difference average based variational mode decomposition method: A case study M. Khan & S. Hassan 10.2166/ws.2021.347
- Predictive performance of ensemble hydroclimatic forecasts: Verification metrics, diagnostic plots and forecast attributes Z. Huang & T. Zhao 10.1002/wat2.1580
- Ecological-economic assessment of forest land degradation neutrality in the Indus River Basin of Pakistan M. Arif et al. 10.1007/s10668-024-05116-0
19 citations as recorded by crossref.
- Synoptic–Dynamic Patterns Affecting Iran’s Autumn Precipitation during ENSO Phase Transitions F. Bahrami et al. 10.3390/cli9070106
- Hydrologic interpretation of machine learning models for 10-daily streamflow simulation in climate sensitive upper Indus catchments H. Mushtaq et al. 10.1007/s00704-024-04932-8
- Streamflow Variations in Monthly, Seasonal, Annual and Extreme Values Using Mann-Kendall, Spearmen’s Rho and Innovative Trend Analysis M. Ashraf et al. 10.1007/s11269-020-02723-0
- Development of a national 7-day ensemble streamflow forecasting service for Australia H. Hapuarachchi et al. 10.5194/hess-26-4801-2022
- Co-designing Indus Water-Energy-Land Futures Y. Wada et al. 10.1016/j.oneear.2019.10.006
- Effects of riparian buffer and stream channel widths on ecological indicators in the upper and lower Indus River basins in Pakistan A. Hira et al. 10.3389/fenvs.2023.1113482
- Socio-hydrological assessment of water security in canal irrigation systems: A conjoint quantitative analysis of equity and reliability A. Siddiqi et al. 10.1016/j.wasec.2018.11.001
- An improved long short-term memory network for streamflow forecasting in the upper Yangtze River S. Zhu et al. 10.1007/s00477-020-01766-4
- Flood Risk Assessment Based on Hydrodynamic Model—A Case of the China–Pakistan Economic Corridor X. Sun et al. 10.3390/w15244295
- A blueprint for coupling a hydrological model with fine- and coarse-scale atmospheric regional climate change models for probabilistic streamflow projections C. Rajulapati et al. 10.1016/j.jhydrol.2024.132080
- Impacts of Stressors on Riparian Health Indicators in the Upper and Lower Indus River Basins in Pakistan A. Hira et al. 10.3390/ijerph192013239
- A new approach of coupled long-range forecasts for streamflow and groundwater level D. Robertson et al. 10.1016/j.jhydrol.2024.130837
- A Medium and Long-Term Runoff Forecast Method Based on Massive Meteorological Data and Machine Learning Algorithms Y. Li et al. 10.3390/w13091308
- Investigating the effects of local weather, streamflow lag, and global climate information on 1-month-ahead streamflow forecasting by using XGBoost and SHAP: two case studies involving the contiguous USA J. Liu et al. 10.1007/s11600-022-00928-y
- Improving medium-range streamflow forecasts over South Korea with a dual-encoder transformer model D. Lee & K. Ahn 10.1016/j.jenvman.2024.122114
- Hydropower and seasonal pumped hydropower storage in the Indus basin:pros and cons J. Hunt et al. 10.1016/j.est.2021.102916
- Hydrological peaks evaluation at Chitral and Tarbela stations, Pakistan, using combined Bayesian regularized neural network and signal difference average based variational mode decomposition method: A case study M. Khan & S. Hassan 10.2166/ws.2021.347
- Predictive performance of ensemble hydroclimatic forecasts: Verification metrics, diagnostic plots and forecast attributes Z. Huang & T. Zhao 10.1002/wat2.1580
- Ecological-economic assessment of forest land degradation neutrality in the Indus River Basin of Pakistan M. Arif et al. 10.1007/s10668-024-05116-0
Discussed (final revised paper)
Latest update: 14 Dec 2024
Short summary
Predictions of irrigation-season water availability are important for water-limited Pakistan. We assess a Bayesian joint probability approach, using flow and climate indices as predictors, to produce streamflow forecasts for inflow to Pakistan's two largest dams. The approach produces skilful and reliable forecasts. As it is simple and quick to apply, it can be used to provide probabilistic seasonal streamflow forecasts that can inform Pakistan's water management.
Predictions of irrigation-season water availability are important for water-limited Pakistan. We...
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