{"title":"Evaluation of Baseflow Modeling with BlueM.Sim for Long-Term Hydrological Studies in the German Low Mountain Range of Hesse, Germany","authors":"M. Kissel, Michael Bach, B. Schmalz","doi":"10.3390/hydrology10120222","DOIUrl":null,"url":null,"abstract":"So far, research with the hydrological model BlueM.Sim has been focused on reservoir management and integrated river basin modeling. BlueM.Sim is part of the official toolset for estimating immissions into rivers in Hesse (Germany) via long-term continuous modeling. Dynamic runoff modeling from rural catchments is permitted within the Hessian guidelines, but in practice, a constant flow or low flow is used. However, due to increasing water stress in the region caused by climate change, the dynamic modeling of runoff from rural catchments will become necessary. Therefore, dynamic baseflow modeling with BlueM.Sim is of the greatest importance. This study evaluated baseflow modeling with BlueM.Sim in a representative hard-rock aquifer in the German Low Mountain range. Two model setups (Factor Approach (FA): CN method + monthly baseflow; Soil Moisture Approach (SMA): physical soil moisture simulation) were calibrated (validated) for a 9-year (5-year) period. The FA achieved an NSE of 0.62 (0.44) and an LnNSE of 0.64 (0.60) for the calibration and validation periods. The selection of a solution for the successful validation of the FA was challenging and required a selection that overestimated baseflow in the calibration period. This is due to the major disadvantage of the FA, namely, that baseflow can only vary according to an estimated yearly pattern of monthly baseflow factors. However, the data requirements are low, and the estimation of monthly baseflow factors is simple and could potentially be regionalized for Hesse, leading to a better representation of baseflow than in current practice. The SMA achieved better results with an NSE of 0.78 (0.75) and an LnNSE of 0.72 (0.78). The data requirements and model setup are extensive and require the estimation of many parameters, which are limitations to its application in practice. Furthermore, a literature review has shown that a single linear reservoir, as in BlueM.Sim, is not optimal for modeling baseflow in hard-rock aquifers. However, for detailed climate change impact studies in the region with BlueM.Sim, the SMA should be preferred over the FA. It is expected that BlueM.Sim would benefit from implementing a more suitable model structure for baseflow in hard-rock aquifers, resulting in improved water balance and water quality outcomes.","PeriodicalId":37372,"journal":{"name":"Hydrology","volume":"90 11","pages":""},"PeriodicalIF":3.1000,"publicationDate":"2023-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Hydrology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/hydrology10120222","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"WATER RESOURCES","Score":null,"Total":0}
引用次数: 0
Abstract
So far, research with the hydrological model BlueM.Sim has been focused on reservoir management and integrated river basin modeling. BlueM.Sim is part of the official toolset for estimating immissions into rivers in Hesse (Germany) via long-term continuous modeling. Dynamic runoff modeling from rural catchments is permitted within the Hessian guidelines, but in practice, a constant flow or low flow is used. However, due to increasing water stress in the region caused by climate change, the dynamic modeling of runoff from rural catchments will become necessary. Therefore, dynamic baseflow modeling with BlueM.Sim is of the greatest importance. This study evaluated baseflow modeling with BlueM.Sim in a representative hard-rock aquifer in the German Low Mountain range. Two model setups (Factor Approach (FA): CN method + monthly baseflow; Soil Moisture Approach (SMA): physical soil moisture simulation) were calibrated (validated) for a 9-year (5-year) period. The FA achieved an NSE of 0.62 (0.44) and an LnNSE of 0.64 (0.60) for the calibration and validation periods. The selection of a solution for the successful validation of the FA was challenging and required a selection that overestimated baseflow in the calibration period. This is due to the major disadvantage of the FA, namely, that baseflow can only vary according to an estimated yearly pattern of monthly baseflow factors. However, the data requirements are low, and the estimation of monthly baseflow factors is simple and could potentially be regionalized for Hesse, leading to a better representation of baseflow than in current practice. The SMA achieved better results with an NSE of 0.78 (0.75) and an LnNSE of 0.72 (0.78). The data requirements and model setup are extensive and require the estimation of many parameters, which are limitations to its application in practice. Furthermore, a literature review has shown that a single linear reservoir, as in BlueM.Sim, is not optimal for modeling baseflow in hard-rock aquifers. However, for detailed climate change impact studies in the region with BlueM.Sim, the SMA should be preferred over the FA. It is expected that BlueM.Sim would benefit from implementing a more suitable model structure for baseflow in hard-rock aquifers, resulting in improved water balance and water quality outcomes.
HydrologyEarth and Planetary Sciences-Earth-Surface Processes
CiteScore
4.90
自引率
21.90%
发文量
192
审稿时长
6 weeks
期刊介绍:
Journal of Hydrology publishes original research papers and comprehensive reviews in all the subfields of the hydrological sciences, including water based management and policy issues that impact on economics and society. These comprise, but are not limited to the physical, chemical, biogeochemical, stochastic and systems aspects of surface and groundwater hydrology, hydrometeorology, hydrogeology and hydrogeophysics. Relevant topics incorporating the insights and methodologies of disciplines such as climatology, water resource systems, ecohydrology, geomorphology, soil science, instrumentation and remote sensing, data and information sciences, civil and environmental engineering are within scope. Social science perspectives on hydrological problems such as resource and ecological economics, sociology, psychology and behavioural science, management and policy analysis are also invited. Multi-and interdisciplinary analyses of hydrological problems are within scope. The science published in the Journal of Hydrology is relevant to catchment scales rather than exclusively to a local scale or site. Studies focused on urban hydrological issues are included.