GRACE Satellites Enable Long-Lead Forecasts of Mountain Contributions to Streamflow in the Low-Flow Season

Terrestrial water storage (TWS) in high mountain areas contributes large runoff volumes to nearby lowlands during the low-flow season when streamflow is critical to downstream water supplies. The potential for TWS from GRACE (Gravity Recovery and Climate Experiment) satellites to provide long-lead streamflow forecasting in adjacent lowlands during the low-flow season was assessed using the upper Yellow River as a case study. Two linear models were trained for forecasting monthly streamflow with and without TWS anomaly (TWSA) from 2002 to 2016. Results show that the model based on streamflow and TWSA is superior to the model based on streamflow alone at up to a five-month lead-time. The inclusion of TWSA reduced errors in streamflow forecasts by 25% to 50%, with 3–5-month lead-times, which represents the role of terrestrial hydrologic memory in streamflow changes during the low-flow season. This study underscores the high potential of streamflow forecasting using GRACE data with long lead-times that should improve water management in mountainous water towers and downstream areas.

[1]  Q. Shao,et al.  Assessment of the impact of climate change on flow regime at multiple temporal scales and potential ecological implications in an alpine river , 2018, Stochastic Environmental Research and Risk Assessment.

[2]  Brian F. Thomas,et al.  River basin flood potential inferred using GRACE gravity observations at several months lead time , 2014 .

[3]  Dennis P. Lettenmaier,et al.  Skill in streamflow forecasts derived from large-scale estimates of soil moisture and snow , 2010 .

[4]  Minjiao Lu,et al.  Variability of soil moisture memory for wet and dry basins , 2015 .

[5]  J. Famiglietti,et al.  GRACE satellite observations reveal the severity of recent water over-consumption in the United States , 2017, Scientific Reports.

[6]  Lei Wang,et al.  Streamflow change on the Qinghai-Tibet Plateau and its impacts , 2019, Chinese Science Bulletin.

[7]  Chao Gao,et al.  Total Basin Discharge From GRACE and Water Balance Method for the Yarlung Tsangpo River Basin, Southwestern China , 2019, Journal of Geophysical Research: Atmospheres.

[8]  S. Kanae,et al.  Hydrological Cycles Change in the Yellow River Basin during the Last Half of the Twentieth Century , 2008 .

[9]  D. Myronidis,et al.  Changes in climatic patterns and tourism and their concomitant effect on drinking water transfers into the region of South Aegean, Greece , 2021, Stochastic Environmental Research and Risk Assessment.

[10]  Hahn Chul Jung,et al.  Satellite Gravimetry Improves Seasonal Streamflow Forecast Initialization in Africa , 2020, Water Resources Research.

[11]  F. Landerer,et al.  Emerging trends in global freshwater availability , 2018, Nature.

[12]  Q. Tang,et al.  Water scarcity under various socio-economic pathways and its potential effects on food production in the Yellow River basin , 2016 .

[13]  J. Zeng,et al.  Evaluation of remotely sensed and reanalysis soil moisture products over the Tibetan Plateau using in-situ observations , 2015 .

[14]  V. Singh,et al.  Evaluation of ecological instream flow considering hydrological alterations in the Yellow River basin, China , 2018 .

[15]  M. Watkins,et al.  Improved methods for observing Earth's time variable mass distribution with GRACE using spherical cap mascons , 2015 .

[16]  H. Apel,et al.  Forecast of seasonal water availability in Central Asia with near-real time GRACE water storage anomalies , 2019, Environmental Research Communications.

[17]  Y. Wada,et al.  Groundwater depletion causing reduction of baseflow triggering Ganges river summer drying , 2018, Scientific Reports.

[18]  Srinivas Bettadpur,et al.  High‐resolution CSR GRACE RL05 mascons , 2016 .

[19]  Long-Range River Discharge Forecasting Using the Gravity Recovery and Climate Experiment , 2014, Journal of Water Resources Planning and Management.

[20]  Qiuhong Tang,et al.  Soil Moisture Drought Monitoring and Forecasting Using Satellite and Climate Model Data over Southwestern China , 2017 .

[21]  M. Watkins,et al.  Quantifying and reducing leakage errors in the JPL RL05M GRACE mascon solution , 2016 .

[22]  Andrea Castelletti,et al.  Value of long‐term streamflow forecasts to reservoir operations for water supply in snow‐dominated river catchments , 2016 .

[23]  Tao Yang,et al.  Impacts of climate change on flow regime and sequential threats to riverine ecosystem in the source region of the Yellow River , 2018, Environmental Earth Sciences.

[24]  Ben Livneh,et al.  How can we better understand low river flows as climate changes , 2015 .

[25]  S. Seneviratne,et al.  Observed changes in dry-season water availability attributed to human-induced climate change , 2020, Nature Geoscience.

[26]  Dennis P. Lettenmaier,et al.  Seasonal hydrologic prediction in the United States: understanding the role of initial hydrologic conditions and seasonal climate forecast skill , 2011 .

[27]  Using GRACE in a streamflow recession to determine drainable water storage in the Mississippi River basin , 2019, Hydrology and Earth System Sciences.

[28]  T. Bolch,et al.  Importance and vulnerability of the world’s water towers , 2019, Nature.

[29]  S. Seneviratne,et al.  Inferring Soil Moisture Memory from Streamflow Observations Using a Simple Water Balance Model , 2013 .

[30]  Hong Yang,et al.  Multimodel assessments of human and climate impacts on mean annual streamflow in China , 2019, Hydrology and Earth System Sciences.

[31]  J. Dozier,et al.  Inroads of remote sensing into hydrologic science during the WRR era , 2015 .

[32]  Q. Tang Global change hydrology: Terrestrial water cycle and global change , 2019, Science China Earth Sciences.

[33]  Randal D. Koster,et al.  Soil Moisture Memory in Climate Models , 2001 .

[34]  L. Qi,et al.  Soil Moisture Memory and Its Effect on the Surface Water and Heat Fluxes on Seasonal and Interannual Time Scales , 2019, Journal of Geophysical Research: Atmospheres.

[35]  Frank Flechtner,et al.  Contributions of GRACE to understanding climate change , 2019, Nature Climate Change.

[36]  Q. Tang,et al.  The influence of groundwater representation on hydrological simulation and its assessment using satellite‐based water storage variation , 2019, Hydrological Processes.

[37]  M. Watkins,et al.  GRACE Measurements of Mass Variability in the Earth System , 2004, Science.

[38]  S. Shukla,et al.  On the sources of global land surface hydrologic predictability , 2013 .

[39]  J. Reager,et al.  Using GRACE in a streamflow recession to determine drainable water storage in the Mississippi River basin , 2019, Hydrology and Earth System Sciences.

[40]  Dennis P. Lettenmaier,et al.  Soil Moisture, Snow, and Seasonal Streamflow Forecasts in the United States , 2012 .

[41]  Q. Tang,et al.  Anthropogenic impacts on mass change in North China , 2013 .