TY - GEN
T1 - Assessing Extreme Monthly Runoff Over an Arid Basin Through Reanalysis Datasets
AU - Rau, Pedro
AU - Castillón, Fiorela
AU - Visitacion, Kimberly
AU - Yeckle, Marcela
AU - Cordova, Marco
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
PY - 2024
Y1 - 2024
N2 - Water availability in arid basins is a serious concern and its quantification remains uncertain. Climate variability as the El Niño Southern Oscillation phenomenon (ENSO) can worsen this scenario, exacerbating flooding in some regions such as the Piura basin on the northern Peruvian Pacific coast. We analyzed four geospatial runoff datasets covering a 7622 km2 basin area at ~50 km of resolution. They are two global datasets: Global Runoff (GRUN) and Linear Optimal Runoff Aggregate (LORA) based on both hydrological reanalysis; a Peruvian dataset named PISCO-Hym-GR2M based on satellite and in-situ conceptual water balance; and a semi empirical method called Rindex based only on in-situ conceptual water balance. Those monthly datasets were compared to historical observations over four selected ENSO events which accelerated and retarded the peak monthly runoff and reached up to 317 mm/month. GRUN, LORA, PISCO-Hym-GR2M and Rindex reached month predictions of 42%, 21%, 58% and 50%, respectively with an acceptable relative error below 50% during the December–May wet period. Using hydroclimatic match indices in a Taylor diagram, correlations coefficients over 0.75 were obtained for all products, the highest corresponding to the GRUN dataset. A reliable root mean square difference near 40 mm/month for GRUN and Rindex; and a reliable amplitude of the variations for PISCO-Hym-GR2M and Rindex around 80 mm/month were obtained. Most datasets underestimated runoff with shifts in peak monthly runoff timing related to spatial aggregation of input precipitation, being LORA the most accurate in matching peaks. Those products could help to study monthly runoff fluctuations, knowing their difficulty in prediction.
AB - Water availability in arid basins is a serious concern and its quantification remains uncertain. Climate variability as the El Niño Southern Oscillation phenomenon (ENSO) can worsen this scenario, exacerbating flooding in some regions such as the Piura basin on the northern Peruvian Pacific coast. We analyzed four geospatial runoff datasets covering a 7622 km2 basin area at ~50 km of resolution. They are two global datasets: Global Runoff (GRUN) and Linear Optimal Runoff Aggregate (LORA) based on both hydrological reanalysis; a Peruvian dataset named PISCO-Hym-GR2M based on satellite and in-situ conceptual water balance; and a semi empirical method called Rindex based only on in-situ conceptual water balance. Those monthly datasets were compared to historical observations over four selected ENSO events which accelerated and retarded the peak monthly runoff and reached up to 317 mm/month. GRUN, LORA, PISCO-Hym-GR2M and Rindex reached month predictions of 42%, 21%, 58% and 50%, respectively with an acceptable relative error below 50% during the December–May wet period. Using hydroclimatic match indices in a Taylor diagram, correlations coefficients over 0.75 were obtained for all products, the highest corresponding to the GRUN dataset. A reliable root mean square difference near 40 mm/month for GRUN and Rindex; and a reliable amplitude of the variations for PISCO-Hym-GR2M and Rindex around 80 mm/month were obtained. Most datasets underestimated runoff with shifts in peak monthly runoff timing related to spatial aggregation of input precipitation, being LORA the most accurate in matching peaks. Those products could help to study monthly runoff fluctuations, knowing their difficulty in prediction.
KW - Extremes
KW - GRUN
KW - LORA
KW - Peru
KW - Runoff
UR - http://www.scopus.com/inward/record.url?scp=85189508183&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-47079-0_17
DO - 10.1007/978-3-031-47079-0_17
M3 - Conference contribution
AN - SCOPUS:85189508183
SN - 9783031470783
T3 - Advances in Science, Technology and Innovation
SP - 75
EP - 77
BT - Recent Advancements from Aquifers to Skies in Hydrogeology, Geoecology, and Atmospheric Sciences - Proceedings of the 2nd MedGU, 2022 Volume 1
A2 - Chenchouni, Haroun
A2 - Zhang, Zhihua
A2 - Bisht, Deepak Singh
A2 - Gentilucci, Matteo
A2 - Chen, Mingjie
A2 - Chaminé, Helder I.
A2 - Barbieri, Maurizio
A2 - Jat, Mahesh Kumar
A2 - Rodrigo-Comino, Jesús
A2 - Panagoulia, Dionysia
A2 - Kallel, Amjad
A2 - Biswas, Arkoprovo
A2 - Turan, Veysel
A2 - Knight, Jasper
A2 - Çiner, Attila
A2 - Candeias, Carla
A2 - Ergüler, Zeynal Abiddin
PB - Springer Nature
T2 - 2nd International conference on Mediterranean Geosciences Union, MedGU 2022
Y2 - 27 November 2022 through 30 November 2022
ER -