Improving the Representation of Long‐Term Storage Variations With Conceptual Hydrological Models in Data‐Scarce Regions. Issue 4 (7th April 2021)

• Record Type: Journal Article
• Authors: Hulsman, Petra; Hrachowitz, Markus; Savenije, Hubert H. G.
• Is Part Of: Water resources research. Volume 57:Issue 4(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-04-07
• Subjects: GRACE -- hydrology -- Luangwa Basin -- modeling -- poorly gauged -- semi‐arid; Hydrology -- Periodicals; 333.91
• DOI: 10.1029/2020WR028837
• Languages: English
• ISSNs: 0043-1397

Abstract

Abstract: In the Luangwa basin in Zambia, long‐term total water storage variations were observed with Gravity Recovery and Climate Experiment, but not reproduced by a standard conceptual hydrological model that encapsulates our current understanding of the dominant regional hydrological processes. The objective of this study was to identify potential processes underlying these low‐frequency variations through combined data analysis and model hypothesis testing. First, we analyzed the effect of data uncertainty by contrasting observed storage variations with multi‐annual estimates of precipitation and evaporation from multiple data sources. Second, we analyzed four different combinations of model forcing and evaluated their skill to reproduce the observed long‐term storage variations. Third, we formulated alternative model hypotheses for groundwater export to potentially explain low‐frequency storage variations. Overall, the results suggest that the initial model's inability to reproduce the observed low‐frequency storage variations was partly due to the forcing data used and partly due to the missing representation of regional groundwater export. More specifically, the choice of data source affected the model's ability to reproduce annual maximum storage fluctuations, whereas the annual minima improved by adapting the model structure to allow for groundwater export from a deeper groundwater layer. This suggests that, in contrast to previous research, conceptual models can reproduce long‐term storage fluctuations if a suitable model structure is used. Overall, the results highlight the value of alternative data sources and iterative testing of model structural hypotheses to improve runoff predictions in a poorly gauged basin leading to enhanced understanding of its hydrological processes. Plain Language Summary: According to satellite observations, the total amount of water stored on and below the land surface varied over the years in the Zambian Luangwa river basin. However, this variation was not well reproduced by existing rainfall‐runoff models, resulting in inaccurate predictions of runoff and water availability. The goal of this study was to identify processes causing long‐term fluctuations in the total water storage by using alternative data sources and by adjusting the model structure. First, we analyzed whether similar long‐term fluctuations existed in the climate using different satellite products. Second, we tested whether these fluctuations could be better represented using different data sources. Third, we tested whether they could be caused by inter‐basin groundwater flow. We indeed showed that long‐term storage fluctuations were better represented by alternative data sources and by incorporating groundwater loss from the basin, leading to more reliable runoff predictions in the poorly gauged Luangwa basin. Key Points: Observed long‐term total water storage changes are not reproduced by a standard hydrological model in the Luangwa Basin Fluctuations in the annual maxima were improved by using alternative forcing data in the hydrological model Fluctuations in the annual minima were improved by introducing groundwater export from a deep groundwater layer