TY - JOUR
T1 - Catchment memory explains hydrological drought forecast performance
AU - Sutanto, S.J.
AU - van Lanen, Henny A.J.
N1 - Funding Information:
The research is supported by the ANYWHERE project (Grant Agreement No.: 700099), which is funded within the EU?s Horizon 2020 research and innovation program (www.anywhere-h2020.eu). This research is part of the Wageningen Institute for Environment and Climate Research (WIMEK-SENSE) and it supports the work of UNESCO EURO FRIEND-Water and the IAHS Panta Rhei program. We thank Edwin Sutanudjaja (Utrecht University) for providing the PCR-GLOBWB groundwater Recession Coefficient (gRC) data.
Funding Information:
The research is supported by the ANYWHERE project (Grant Agreement No.: 700099), which is funded within the EU’s Horizon 2020 research and innovation program ( www.anywhere-h2020.eu ). This research is part of the Wageningen Institute for Environment and Climate Research (WIMEK-SENSE) and it supports the work of UNESCO EURO FRIEND-Water and the IAHS Panta Rhei program. We thank Edwin Sutanudjaja (Utrecht University) for providing the PCR-GLOBWB groundwater Recession Coefficient (gRC) data.
Publisher Copyright:
© 2022, The Author(s).
PY - 2022/12
Y1 - 2022/12
N2 - Hydrological drought forecasts outperform meteorological ones, which is anticipated coming from catchment memory. Yet, the importance of catchment memory in explaining hydrological drought forecast performance has not been studied. Here, we use the Baseflow Index (BFI) and the groundwater Recession Coefficient (gRC), which through the streamflow, give information on the catchment memory. Performance of streamflow drought forecasts was evaluated using the Brier Score (BS) for rivers across Europe. We found that BS is negatively correlated with BFI, meaning that rivers with high BFI (large memory) yield better drought prediction (low BS). A significant positive correlation between gRC and BS demonstrates that catchments slowly releasing groundwater to streams (low gRC), i.e. large memory, generates higher drought forecast performance. The higher performance of hydrological drought forecasts in catchments with relatively large memory (high BFI and low gRC) implies that Drought Early Warning Systems have more potential to be implemented there and will appear to be more useful.
AB - Hydrological drought forecasts outperform meteorological ones, which is anticipated coming from catchment memory. Yet, the importance of catchment memory in explaining hydrological drought forecast performance has not been studied. Here, we use the Baseflow Index (BFI) and the groundwater Recession Coefficient (gRC), which through the streamflow, give information on the catchment memory. Performance of streamflow drought forecasts was evaluated using the Brier Score (BS) for rivers across Europe. We found that BS is negatively correlated with BFI, meaning that rivers with high BFI (large memory) yield better drought prediction (low BS). A significant positive correlation between gRC and BS demonstrates that catchments slowly releasing groundwater to streams (low gRC), i.e. large memory, generates higher drought forecast performance. The higher performance of hydrological drought forecasts in catchments with relatively large memory (high BFI and low gRC) implies that Drought Early Warning Systems have more potential to be implemented there and will appear to be more useful.
UR - http://www.scopus.com/inward/record.url?scp=85124779121&partnerID=8YFLogxK
U2 - 10.1038/s41598-022-06553-5
DO - 10.1038/s41598-022-06553-5
M3 - Article
C2 - 35177667
SN - 2045-2322
VL - 12
SP - 1
EP - 11
JO - Scientific Reports
JF - Scientific Reports
IS - 1
M1 - 2689
ER -