Abstract. Real-time operational flood forecasting most often concentrates on issuing streamflow predictions at specific points along the rivers of a watershed. However, we are now witnessing an increasing number of studies aimed at also including flood mapping as part of the forecasting system. While this additional new information (flood extent, depth, velocity, etc.) can potentially be useful for decision-makers, it could also be overwhelming. This is especially true for probabilistic and ensemble forecasting systems. While ensemble streamflow forecasts for a given point in space can be visualized relatively easily, the visualization and communication of probabilistic forecasts for water depth and extent pose additional challenges. Confusion typically arises from too much information, counterintuitive interpretation, or simply too much complexity in the representation of the forecast. The communication and visualization of probabilistic streamflow forecasts has been studied in the past, but this is not the case for the probabilistic flood forecast map, which is still an emerging product. In this paper, we synthesize the results of a large-scale survey (28 government representatives, 52 municipalities, 9 organizations, and 38 citizens and farmers, for a total of 140 people) regarding the users' preferences in terms of visualizing probabilistic flood forecasts over an entire river reach. The survey was performed through interviews, during which the interviewees were asked about their needs in terms of hydrological forecasting. We also presented the interviewees with four prototypes representing alternative visualizations of the same probabilistic forecast in order to understand their preferences in terms of colour maps, wording, and the representation of uncertainty. Our results highlight several issues related to the understanding of probabilities in the specific context of visualizing forecasted flood maps. We propose several suggestions for visualizing probabilistic flood maps and also describe potential adaptations for different categories of end users. This study is the first to investigate the visualization of probabilistic flood maps, which are gaining popularity. Given that the interview questions were not tied to a specific geographical location, our findings are applicable outside of the study area and, therefore, to other operational centres interested in providing probabilistic flood forecast maps to decision-making organizations and citizens.
{"title":"Uncertainty in three dimensions: the challenges of communicating probabilistic flood forecast maps","authors":"Valérie Jean, Marie-Amélie Boucher, Anissa Frini, Dominic Roussel","doi":"10.5194/hess-27-3351-2023","DOIUrl":"https://doi.org/10.5194/hess-27-3351-2023","url":null,"abstract":"Abstract. Real-time operational flood forecasting most often concentrates on issuing streamflow predictions at specific points along the rivers of a watershed. However, we are now witnessing an increasing number of studies aimed at also including flood mapping as part of the forecasting system. While this additional new information (flood extent, depth, velocity, etc.) can potentially be useful for decision-makers, it could also be overwhelming. This is especially true for probabilistic and ensemble forecasting systems. While ensemble streamflow forecasts for a given point in space can be visualized relatively easily, the visualization and communication of probabilistic forecasts for water depth and extent pose additional challenges. Confusion typically arises from too much information, counterintuitive interpretation, or simply too much complexity in the representation of the forecast. The communication and visualization of probabilistic streamflow forecasts has been studied in the past, but this is not the case for the probabilistic flood forecast map, which is still an emerging product. In this paper, we synthesize the results of a large-scale survey (28 government representatives, 52 municipalities, 9 organizations, and 38 citizens and farmers, for a total of 140 people) regarding the users' preferences in terms of visualizing probabilistic flood forecasts over an entire river reach. The survey was performed through interviews, during which the interviewees were asked about their needs in terms of hydrological forecasting. We also presented the interviewees with four prototypes representing alternative visualizations of the same probabilistic forecast in order to understand their preferences in terms of colour maps, wording, and the representation of uncertainty. Our results highlight several issues related to the understanding of probabilities in the specific context of visualizing forecasted flood maps. We propose several suggestions for visualizing probabilistic flood maps and also describe potential adaptations for different categories of end users. This study is the first to investigate the visualization of probabilistic flood maps, which are gaining popularity. Given that the interview questions were not tied to a specific geographical location, our findings are applicable outside of the study area and, therefore, to other operational centres interested in providing probabilistic flood forecast maps to decision-making organizations and citizens.","PeriodicalId":13143,"journal":{"name":"Hydrology and Earth System Sciences","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136152981","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-20DOI: 10.5194/hess-27-3329-2023
Francesco Fatone, Bartosz Szeląg, Przemysław Kowal, Arthur McGarity, Adam Kiczko, Grzegorz Wałek, Ewa Wojciechowska, Michał Stachura, Nicolas Caradot
Abstract. An innovative tool for modeling the specific flood volume was presented that can be applied to assess the need for stormwater network modernization as well as for advanced flood risk assessment. Field measurements for a catchment area in Kielce, Poland, were used to apply the model and demonstrate its usefulness. This model extends the capability of recently developed statistical and machine learning hydrodynamic models developed from multiple runs of the US Environmental Protection Agency (EPA) Storm Water Management Model (SWMM). The extensions enable the inclusion of (1) the characteristics of the catchment and its stormwater network, calibrated model parameters expressing catchment retention, and the capacity of the sewer system; (2) extended sensitivity analysis; and (3) risk analysis. Sensitivity coefficients of calibrated model parameters include correction coefficients for percentage area, flow path, depth of storage, and impervious area; Manning roughness coefficients for impervious areas; and Manning roughness coefficients for sewer channels. Sensitivity coefficients were determined with respect to rainfall intensity and characteristics of the catchment and stormwater network. Extended sensitivity analysis enabled an evaluation of the variability in the specific flood volume and sensitivity coefficients within a catchment, in order to identify the most vulnerable areas threatened by flooding. Thus, the model can be used to identify areas particularly susceptible to stormwater network failure and the sections of the network where corrective action should be taken to reduce the probability of system failure. The simulator developed to determine the specific flood volume represents an alternative approach to the SWMM that, unlike current approaches, can be calibrated with limited topological data availability; therefore, the aforementioned simulator incurs a lower cost due to the lower number and lower specificity of data required.
{"title":"An advanced tool integrating failure and sensitivity analysis into novel modeling of the stormwater flood volume","authors":"Francesco Fatone, Bartosz Szeląg, Przemysław Kowal, Arthur McGarity, Adam Kiczko, Grzegorz Wałek, Ewa Wojciechowska, Michał Stachura, Nicolas Caradot","doi":"10.5194/hess-27-3329-2023","DOIUrl":"https://doi.org/10.5194/hess-27-3329-2023","url":null,"abstract":"Abstract. An innovative tool for modeling the specific flood volume was presented that can be applied to assess the need for stormwater network modernization as well as for advanced flood risk assessment. Field measurements for a catchment area in Kielce, Poland, were used to apply the model and demonstrate its usefulness. This model extends the capability of recently developed statistical and machine learning hydrodynamic models developed from multiple runs of the US Environmental Protection Agency (EPA) Storm Water Management Model (SWMM). The extensions enable the inclusion of (1) the characteristics of the catchment and its stormwater network, calibrated model parameters expressing catchment retention, and the capacity of the sewer system; (2) extended sensitivity analysis; and (3) risk analysis. Sensitivity coefficients of calibrated model parameters include correction coefficients for percentage area, flow path, depth of storage, and impervious area; Manning roughness coefficients for impervious areas; and Manning roughness coefficients for sewer channels. Sensitivity coefficients were determined with respect to rainfall intensity and characteristics of the catchment and stormwater network. Extended sensitivity analysis enabled an evaluation of the variability in the specific flood volume and sensitivity coefficients within a catchment, in order to identify the most vulnerable areas threatened by flooding. Thus, the model can be used to identify areas particularly susceptible to stormwater network failure and the sections of the network where corrective action should be taken to reduce the probability of system failure. The simulator developed to determine the specific flood volume represents an alternative approach to the SWMM that, unlike current approaches, can be calibrated with limited topological data availability; therefore, the aforementioned simulator incurs a lower cost due to the lower number and lower specificity of data required.","PeriodicalId":13143,"journal":{"name":"Hydrology and Earth System Sciences","volume":"181 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136314021","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-14DOI: 10.5194/hess-27-3293-2023
Olivier Delaigue, Pierre Brigode, Guillaume Thirel, Laurent Coron
Abstract. Hydrological modeling is at the core of most studies related to water, especially for anticipating disasters, managing water resources, and planning adaptation strategies. Consequently, teaching hydrological modeling is an important, but difficult, matter. Teaching hydrological modeling requires appropriate software and teaching material (exercises, projects); however, although many hydrological modeling tools exist today, only a few are adapted to teaching purposes. In this article, we present the airGRteaching package, which is an open-source R package. The hydrological models that can be used in airGRteaching are the GR rainfall-runoff models, i.e., lumped processed-based models, allowing streamflows to be simulated, including the GR4J model. In this package, thanks to a graphical user interface and a limited number of functions, numerous hydrological modeling exercises representing a wide range of hydrological applications are proposed. To ease its use by students and teachers, the package contains several vignettes describing complete projects that can be proposed to investigate various topics such as streamflow reconstruction, hydrological forecasting, and assessment of climate change impact.
{"title":"airGRteaching: an open-source tool for teaching hydrological modeling with R","authors":"Olivier Delaigue, Pierre Brigode, Guillaume Thirel, Laurent Coron","doi":"10.5194/hess-27-3293-2023","DOIUrl":"https://doi.org/10.5194/hess-27-3293-2023","url":null,"abstract":"Abstract. Hydrological modeling is at the core of most studies related to water, especially for anticipating disasters, managing water resources, and planning adaptation strategies. Consequently, teaching hydrological modeling is an important, but difficult, matter. Teaching hydrological modeling requires appropriate software and teaching material (exercises, projects); however, although many hydrological modeling tools exist today, only a few are adapted to teaching purposes. In this article, we present the airGRteaching package, which is an open-source R package. The hydrological models that can be used in airGRteaching are the GR rainfall-runoff models, i.e., lumped processed-based models, allowing streamflows to be simulated, including the GR4J model. In this package, thanks to a graphical user interface and a limited number of functions, numerous hydrological modeling exercises representing a wide range of hydrological applications are proposed. To ease its use by students and teachers, the package contains several vignettes describing complete projects that can be proposed to investigate various topics such as streamflow reconstruction, hydrological forecasting, and assessment of climate change impact.","PeriodicalId":13143,"journal":{"name":"Hydrology and Earth System Sciences","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135552729","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-11DOI: 10.5194/hess-27-3265-2023
Tobias Schnepper, Jannis Groh, Horst H. Gerke, Barbara Reichert, Thomas Pütz
Abstract. Accurate precipitation data are essential for assessing the water balance of ecosystems. Methods for point precipitation determination are influenced by wind, precipitation type and intensity and/or technical issues. High-precision weighable lysimeters provide precipitation measurements at ground level that are less affected by wind disturbances and are assumed to be relatively close to actual precipitation. The problem in previous studies was that the biases in precipitation data introduced by different precipitation measurement methods were not comprehensively compared with and quantified on the basis of those obtained by lysimeters in different regions in Germany. The aim was to quantify measurement errors in standard precipitation gauges as compared to the lysimeter reference and to analyze the effect of precipitation correction algorithms on the gauge data quality. Both correction methods rely on empirical constants to account for known external influences on the measurements, following a generic and a site-specific approach. Reference precipitation data were obtained from high-precision weighable lysimeters of the TERrestrial ENvironmental Observatories (TERENO)-SOILCan lysimeter network. Gauge types included tipping bucket gauges (TBs), weighable gauges (WGs), acoustic sensors (ASs) and optical laser disdrometers (LDs). From 2015-2018, data were collected at three locations in Germany, and 1 h aggregated values for precipitation above a threshold of 0.1 mm h−1 were compared. The results show that all investigated measurement methods underestimated the precipitation amounts relative to the lysimeter references for long-term precipitation totals with catch ratios (CRs) of between 33 %–92 %. Data from ASs had overall biases of −0.25 to −0.07 mm h−1, while data from WGs and LDs showed the lowest measurement bias (−0.14 to −0.06 mm h−1 and −0.01 to −0.02 mm h−1). Two TBs showed systematic deviations with biases of −0.69 to −0.61 mm h−1, while other TBs were in the previously reported range with biases of −0.2 mm h−1. The site-specific and generic correction schemes reduced the hourly measurement bias by 0.13 and 0.08 mm h−1 for the TBs and by 0.09 and 0.07 mm h−1 for the WGs and increased long-term CRs by 14 % and 9 % and by 10 % and 11 %, respectively. It could be shown that the lysimeter reference operated with minor uncertainties in long-term measurements under different site and weather conditions. The results indicate that considerable precipitation measurement errors can occur even at well-maintained and professionally operated stations equipped with standard precipitation gauges. This generally leads to an underestimation of the actual precipitation amounts. The results suggest that the application of relatively simple correction schemes, manual or automated data quality checks, instrument calibrations, and/or an adequate choice of observation period can help improve the data quality of gauge-based measurements for water balanc
摘要准确的降水数据是评价生态系统水分平衡的基础。确定点降水的方法受风、降水类型和强度和/或技术问题的影响。高精度可称重的降水计提供地面降水测量，受风干扰的影响较小，并且假定相对接近实际降水。以往研究存在的问题是，不同降水测量方法引入的降水数据偏差没有在德国不同地区溶渗仪获得的降水数据的基础上进行全面的比较和量化。目的是量化标准降水计与参考渗湿计的测量误差，并分析降水校正算法对测量数据质量的影响。这两种校正方法都依赖于经验常数来解释已知的外部对测量的影响，遵循通用和特定地点的方法。参考降水数据由TERENO -SOILCan网络的高精度可称重渗湿仪获得。量具类型包括翻斗量具(TBs)、可称重量具(WGs)、声学传感器(ASs)和光学激光测差仪(ld)。2015-2018年，在德国的三个地点收集了数据，并比较了超过0.1 mm h−1阈值的1 h累积值。结果表明，所有研究的测量方法相对于长期降水总量的蒸渗计参考资料都低估了降水量，其捕获比在33% ~ 92%之间。来自as的数据总体偏差为- 0.25至- 0.07 mm h - 1，而来自WGs和ld的数据显示最小的测量偏差(- 0.14至- 0.06 mm h - 1和- 0.01至- 0.02 mm h - 1)。两个TBs显示出系统偏差，偏差为−0.69至−0.61 mm h−1，而其他TBs在先前报道的范围内，偏差为−0.2 mm h−1。位点特异性和一般校正方案分别使TBs的每小时测量偏差降低了0.13和0.08 mm h - 1, WGs的每小时测量偏差降低了0.09和0.07 mm h - 1，长期cr分别提高了14%和9%，10%和11%。可以看出，在不同地点和天气条件下的长期测量中，渗湿计基准的不确定度较小。结果表明，即使在配备标准降水计的维护良好和专业操作的台站，也会出现相当大的降水测量误差。这通常会导致对实际降水量的低估。结果表明，采用相对简单的校正方案、手动或自动数据质量检查、仪器校准和/或适当选择观测周期，有助于提高基于量具的水平衡计算、生态系统建模、水资源管理、农业灌溉需求评估或基于雷达的降水分析的数据质量。
{"title":"Evaluation of precipitation measurement methods using data from a precision lysimeter network","authors":"Tobias Schnepper, Jannis Groh, Horst H. Gerke, Barbara Reichert, Thomas Pütz","doi":"10.5194/hess-27-3265-2023","DOIUrl":"https://doi.org/10.5194/hess-27-3265-2023","url":null,"abstract":"Abstract. Accurate precipitation data are essential for assessing the water balance of ecosystems. Methods for point precipitation determination are influenced by wind, precipitation type and intensity and/or technical issues. High-precision weighable lysimeters provide precipitation measurements at ground level that are less affected by wind disturbances and are assumed to be relatively close to actual precipitation. The problem in previous studies was that the biases in precipitation data introduced by different precipitation measurement methods were not comprehensively compared with and quantified on the basis of those obtained by lysimeters in different regions in Germany. The aim was to quantify measurement errors in standard precipitation gauges as compared to the lysimeter reference and to analyze the effect of precipitation correction algorithms on the gauge data quality. Both correction methods rely on empirical constants to account for known external influences on the measurements, following a generic and a site-specific approach. Reference precipitation data were obtained from high-precision weighable lysimeters of the TERrestrial ENvironmental Observatories (TERENO)-SOILCan lysimeter network. Gauge types included tipping bucket gauges (TBs), weighable gauges (WGs), acoustic sensors (ASs) and optical laser disdrometers (LDs). From 2015-2018, data were collected at three locations in Germany, and 1 h aggregated values for precipitation above a threshold of 0.1 mm h−1 were compared. The results show that all investigated measurement methods underestimated the precipitation amounts relative to the lysimeter references for long-term precipitation totals with catch ratios (CRs) of between 33 %–92 %. Data from ASs had overall biases of −0.25 to −0.07 mm h−1, while data from WGs and LDs showed the lowest measurement bias (−0.14 to −0.06 mm h−1 and −0.01 to −0.02 mm h−1). Two TBs showed systematic deviations with biases of −0.69 to −0.61 mm h−1, while other TBs were in the previously reported range with biases of −0.2 mm h−1. The site-specific and generic correction schemes reduced the hourly measurement bias by 0.13 and 0.08 mm h−1 for the TBs and by 0.09 and 0.07 mm h−1 for the WGs and increased long-term CRs by 14 % and 9 % and by 10 % and 11 %, respectively. It could be shown that the lysimeter reference operated with minor uncertainties in long-term measurements under different site and weather conditions. The results indicate that considerable precipitation measurement errors can occur even at well-maintained and professionally operated stations equipped with standard precipitation gauges. This generally leads to an underestimation of the actual precipitation amounts. The results suggest that the application of relatively simple correction schemes, manual or automated data quality checks, instrument calibrations, and/or an adequate choice of observation period can help improve the data quality of gauge-based measurements for water balanc","PeriodicalId":13143,"journal":{"name":"Hydrology and Earth System Sciences","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135980712","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-08DOI: 10.5194/hess-27-3241-2023
Samah Larabi, Juliane Mai, Markus Schnorbus, B. Tolson, F. Zwiers
Abstract. Land surface models have many parameters that have a spatially variable impact on model outputs. In applying these models, sensitivity analysis (SA) is sometimes performed as an initial step to select calibration parameters. As these models are applied to large domains, performing sensitivity analysis across the domain is computationally prohibitive. Here, using a Variable Infiltration Capacity model (VIC) deployment to a large domain as an example, we show that watershed classification based on climatic attributes and vegetation land cover helps to identify the spatial pattern of parameter sensitivity within the domain at a reduced cost. We evaluate the sensitivity of 44 VIC model parameters with regard to streamflow, evapotranspiration and snow water equivalent over 25 basins with a median size of 5078 km2. Basins are clustered based on their climatic and land cover attributes. Performance in transferring parameter sensitivity between basins of the same cluster is evaluated by the F1 score. Results show that two donor basins per cluster are sufficient to correctly identify sensitive parameters in a target basin, with F1 scores ranging between 0.66 (evapotranspiration) and 1 (snow water equivalent). While climatic attributes are sufficient to identify sensitive parameters for streamflow and evapotranspiration, including the vegetation class significantly improves skill in identifying sensitive parameters for the snow water equivalent. This work reveals that there is opportunity to leverage climate and land cover attributes to greatly increase the efficiency of parameter sensitivity analysis and facilitate more rapid deployment of land surface models over large spatial domains.
{"title":"Towards reducing the high cost of parameter sensitivity analysis in hydrologic modeling: a regional parameter sensitivity analysis approach","authors":"Samah Larabi, Juliane Mai, Markus Schnorbus, B. Tolson, F. Zwiers","doi":"10.5194/hess-27-3241-2023","DOIUrl":"https://doi.org/10.5194/hess-27-3241-2023","url":null,"abstract":"Abstract. Land surface models have many parameters that have a spatially variable impact on model outputs. In applying these models, sensitivity analysis (SA) is sometimes performed as an initial step to select calibration parameters. As these models are applied to large domains, performing sensitivity analysis across the domain is computationally prohibitive. Here, using a Variable Infiltration Capacity model (VIC) deployment to a large domain as an example, we show that watershed classification based on climatic attributes and vegetation land cover helps to identify the spatial pattern of parameter sensitivity within the domain at a reduced cost. We evaluate the sensitivity of 44 VIC model parameters with regard to streamflow, evapotranspiration and snow water equivalent over 25 basins with a median size of 5078 km2. Basins are clustered based on their climatic and land cover attributes. Performance in transferring parameter sensitivity between basins of the same cluster is evaluated by the F1 score. Results show that two donor basins per cluster are sufficient to correctly identify sensitive parameters in a target basin, with F1 scores ranging between 0.66 (evapotranspiration) and 1 (snow water equivalent). While climatic attributes are sufficient to identify sensitive parameters for streamflow and evapotranspiration, including the vegetation class significantly improves skill in identifying sensitive parameters for the snow water equivalent. This work reveals that there is opportunity to leverage climate and land cover attributes to greatly increase the efficiency of parameter sensitivity analysis and facilitate more rapid deployment of land surface models over large spatial domains.\u0000","PeriodicalId":13143,"journal":{"name":"Hydrology and Earth System Sciences","volume":" ","pages":""},"PeriodicalIF":6.3,"publicationDate":"2023-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45216015","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-08DOI: 10.5194/hess-27-3221-2023
Ronan Abhervé, C. Roques, Alexandre Gauvain, L. Longuevergne, Stéphane Louaisil, Luc Aquilina, J. de Dreuzy
Abstract. The assessment of effective hydraulic properties at the catchment scale, i.e., hydraulic conductivity (K) and transmissivity (T), is particularly challenging due to the sparse availability of hydrological monitoring systems through stream gauges and boreholes. To overcome this challenge, we propose a calibration methodology which only considers information from a digital elevation model (DEM) and the spatial distribution of the stream network. The methodology is built on the assumption that the groundwater system is the main driver controlling the stream density and extension, where the perennial stream network reflects the intersection of the groundwater table with the topography. Indeed, the groundwater seepage at the surface is primarily controlled by the topography, the aquifer thickness and the dimensionless parameter K/R, where R is the average recharge rate. Here, we use a process-based and parsimonious 3D groundwater flow model to calibrate K/R by minimizing the relative distances between the observed and the simulated stream network generated from groundwater seepage zones. By deploying the methodology in 24 selected headwater catchments located in northwestern France, we demonstrate that the method successfully predicts the stream network extent for 80 % of the cases. Results show a high sensitivity of K/R to the extension of the low-order streams and limited impacts of the DEM resolution as long the DEM remains consistent with the stream network observations. By assuming an average recharge rate, we found that effective K values vary between 1.0×10-5 and 1.1×10-4 m s−1, in agreement with local estimates derived from hydraulic tests and independent calibrated groundwater model. With the emergence of global remote-sensing databases compiling information on high-resolution DEM and stream networks, this approach provides new opportunities to assess hydraulic properties of unconfined aquifers in ungauged basins.
摘要在集水区尺度上的有效水力特性评估，即由于通过流计和钻孔的水文监测系统的稀疏可用性，因此，水力电导率(K)和透射率(T)的研究尤其具有挑战性。为了克服这一挑战，我们提出了一种仅考虑数字高程模型(DEM)和河流网络空间分布信息的校准方法。该方法是建立在地下水系统是控制河流密度和延伸的主要驱动力的假设之上的，其中常年河流网络反映了地下水位与地形的交集。实际上，地表地下水渗流主要受地形、含水层厚度和无量纲参数K/R控制，其中R为平均流量。在这里，我们使用一个基于过程的简化的三维地下水流动模型，通过最小化由地下水渗流区产生的观测和模拟流网络之间的相对距离来校准K/R。通过在法国西北部的24个选定的水源集水区部署该方法，我们证明该方法成功地预测了80%的河流网络范围。结果表明，只要DEM与河流网络观测值保持一致，K/R对低阶河流的扩展具有很高的敏感性，并且DEM分辨率的影响有限。通过假设平均充电率，我们发现有效K值在1.0×10-5和1.1×10-4 m s−1之间变化，与水力试验和独立校准的地下水模型得出的当地估计值一致。随着汇编高分辨率DEM和流网络信息的全球遥感数据库的出现，这种方法为评估未测量盆地的非承压含水层的水力特性提供了新的机会。
{"title":"Calibration of groundwater seepage against the spatial distribution of the stream network to assess catchment-scale hydraulic properties","authors":"Ronan Abhervé, C. Roques, Alexandre Gauvain, L. Longuevergne, Stéphane Louaisil, Luc Aquilina, J. de Dreuzy","doi":"10.5194/hess-27-3221-2023","DOIUrl":"https://doi.org/10.5194/hess-27-3221-2023","url":null,"abstract":"Abstract. The assessment of effective hydraulic properties at the catchment scale,\u0000i.e., hydraulic conductivity (K) and transmissivity (T), is particularly\u0000challenging due to the sparse availability of hydrological monitoring\u0000systems through stream gauges and boreholes. To overcome this challenge, we\u0000propose a calibration methodology which only considers information from a digital elevation model (DEM) and the spatial distribution of the stream\u0000network. The methodology is built on the assumption that the groundwater\u0000system is the main driver controlling the stream density and extension,\u0000where the perennial stream network reflects the intersection of the\u0000groundwater table with the topography. Indeed, the groundwater seepage at\u0000the surface is primarily controlled by the topography, the aquifer\u0000thickness and the dimensionless parameter K/R, where R is the average\u0000recharge rate. Here, we use a process-based and parsimonious 3D groundwater\u0000flow model to calibrate K/R by minimizing the relative distances between\u0000the observed and the simulated stream network generated from groundwater\u0000seepage zones. By deploying the methodology in 24 selected headwater\u0000catchments located in northwestern France, we demonstrate that the method\u0000successfully predicts the stream network extent for 80 % of the cases.\u0000Results show a high sensitivity of K/R to the extension of the low-order\u0000streams and limited impacts of the DEM resolution as long the DEM remains\u0000consistent with the stream network observations. By assuming an average\u0000recharge rate, we found that effective K values vary between 1.0×10-5 and 1.1×10-4 m s−1, in agreement with local estimates derived from hydraulic tests and independent calibrated groundwater model. With the emergence of global remote-sensing databases compiling information on high-resolution DEM and stream networks, this approach provides new opportunities to assess hydraulic properties of unconfined aquifers in ungauged basins.\u0000","PeriodicalId":13143,"journal":{"name":"Hydrology and Earth System Sciences","volume":" ","pages":""},"PeriodicalIF":6.3,"publicationDate":"2023-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44526870","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-08DOI: 10.5194/hess-27-3205-2023
R. Crago, Joszef Szilagyi, R. Qualls
Abstract. This study compares four different hypotheses regarding the nature of the Priestley–Taylor parameter α. They are as follows: α is a universal constant. The Bowen ratio (H/LE, where H is the sensible heat flux, and LE is the latent heat flux) for equilibrium (i.e., saturated air column near the surface) evaporation is a constant times the Bowen ratio at minimal advection (Andreas et al., 2013). Minimal advection over a wet surface corresponds to a particular relative humidity value. α is a constant fraction of the difference from the minimum value of 1 to the maximum value of α proposed by Priestley and Taylor (1972). Formulas for α are developed for the last three hypotheses. Weather, radiation, and surface energy flux data from 171 FLUXNET eddy covariance stations were used. The condition LEref/LEp> 0.90 was taken as the criterion for nearly saturated conditions (where LEref is the reference, and LEp is the apparent potential evaporation rate from the equation by Penman, 1948). Daily and monthly average data from the sites were obtained. All formulations for α include one model parameter which is optimized such that the root mean square error of the target variable was minimized. For each model, separate optimizations were done for predictions of the target variables α, wet-surface evaporation (α multiplied by equilibrium evaporation rate) and actual evaporation (the latter using a highly successful version of the complementary relationship of evaporation). Overall, the second and fourth hypotheses received the best support from the data.
摘要本研究比较了关于Priestley-Taylor参数α性质的四种不同假设。它们是:α是一个普遍常数。平衡(即近地表饱和气柱)蒸发的波文比(H/LE，其中H为感热通量，LE为潜热通量)是最小平流时波文比的常数倍(Andreas et al.， 2013)。湿面上的最小平流对应于一个特定的相对湿度值。α是由Priestley和Taylor(1972)提出的从1的最小值到最大值的差的常数分数。为后三个假设推导出了α的公式。使用了来自171个FLUXNET涡动相关变差的天气、辐射和地表能量通量数据。采用leef /LEp> 0.90作为近饱和条件的判据(leef为参考，LEp为Penman, 1948公式中的表观潜在蒸发速率)。从这些地点获得每日和每月的平均数据。α的所有公式都包含一个模型参数，该参数经过优化，使目标变量的均方根误差最小。对于每个模型，分别对目标变量α、湿面蒸发(α乘以平衡蒸发率)和实际蒸发(后者使用了一个非常成功的蒸发互补关系版本)的预测进行了优化。总体而言，第二和第四种假设得到了数据的最佳支持。
{"title":"What is the Priestley–Taylor wet-surface evaporation parameter? Testing four hypotheses","authors":"R. Crago, Joszef Szilagyi, R. Qualls","doi":"10.5194/hess-27-3205-2023","DOIUrl":"https://doi.org/10.5194/hess-27-3205-2023","url":null,"abstract":"Abstract. This study compares four different hypotheses regarding the nature\u0000of the Priestley–Taylor parameter α. They are as follows:\u0000 α is a universal constant. The Bowen ratio (H/LE, where H is the sensible heat flux, and LE is\u0000the latent heat flux) for equilibrium (i.e., saturated air column near the\u0000surface) evaporation is a constant times the Bowen ratio at minimal\u0000advection (Andreas et al., 2013). Minimal advection over a wet surface corresponds to a particular relative humidity value. α is a constant fraction of the difference from the minimum value of 1 to the maximum value of α proposed by Priestley and Taylor (1972).\u0000Formulas for α are developed for the last three hypotheses. Weather,\u0000radiation, and surface energy flux data from 171 FLUXNET eddy covariance\u0000stations were used. The condition LEref/LEp> 0.90 was\u0000taken as the criterion for nearly saturated conditions (where LEref is\u0000the reference, and LEp is the apparent potential evaporation rate from the equation by Penman, 1948). Daily and monthly average data from the sites were\u0000obtained. All formulations for α include one model parameter which\u0000is optimized such that the root mean square error of the target variable was\u0000minimized. For each model, separate optimizations were done for predictions\u0000of the target variables α, wet-surface evaporation (α\u0000multiplied by equilibrium evaporation rate) and actual evaporation (the\u0000latter using a highly successful version of the complementary relationship\u0000of evaporation). Overall, the second and fourth hypotheses received the best\u0000support from the data.\u0000","PeriodicalId":13143,"journal":{"name":"Hydrology and Earth System Sciences","volume":" ","pages":""},"PeriodicalIF":6.3,"publicationDate":"2023-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42082224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-06DOI: 10.5194/hess-27-3169-2023
M. Journée, E. Goudenhoofdt, S. Vannitsem, L. Delobbe
Abstract. The exceptional flood of July 2021 in central Europe impacted Belgium severely. As rainfall was the triggering factor of this event, this study aims to characterize rainfall amounts in Belgium from 13 to 16 July 2021 based on two types of observational data. First, observations recorded by high-quality rain gauges operated by weather and hydrological services in Belgium have been compiled and quality checked. Second, a radar-based rainfall product has been improved to provide a reliable estimation of quantitative precipitation at high spatial and temporal resolutions over Belgium. Several analyses of these data are performed here to describe the spatial and temporal distribution of rainfall during the event. These analyses indicate that the rainfall accumulations during the event reached unprecedented levels over large areas. Accumulations over durations from 1 to 3 d significantly exceeded the 200-year return level in several places, with up to 90 % of exceedance over the 200-year return level for 2 and 3 d values locally in the Vesdre Basin. Such a record-breaking event needs to be documented as much as possible, and available observational data must be shared with the scientific community for further studies in hydrology, in urban planning and, more generally, in all multi-disciplinary studies aiming to identify and understand factors leading to such disaster. The corresponding rainfall data are therefore provided freely in a supplement (Journée et al., 2023; Goudenhoofdt et al., 2023).
摘要2021年7月发生在中欧的特大洪水对比利时造成了严重影响。由于降雨是该事件的触发因素，本研究旨在基于两种类型的观测数据，表征2021年7月13日至16日比利时的降雨量。首先，对比利时气象和水文部门使用的高质量雨量计记录的观测结果进行了汇编和质量检查。其次，改进了基于雷达的降雨产品，以提供比利时高时空分辨率定量降水的可靠估计。这里对这些数据进行了一些分析，以描述事件期间降雨的时空分布。这些分析表明，该事件期间的降雨量在大片地区达到了前所未有的水平。在一些地方，1 ~ 3 d的累积量显著超过200年的年回报水平，Vesdre盆地局部地区2和3 d的累积量超过200年的年回报水平的比例高达90%。这样一个破纪录的事件需要尽可能多地记录下来，而且现有的观测数据必须与科学界共享，以便进一步研究水文学、城市规划，更广泛地说，用于旨在确定和了解导致这种灾难的因素的所有多学科研究。因此，相应的降雨数据在补编中免费提供(journae et al.， 2023;Goudenhoofdt et al.， 2023)。
{"title":"Quantitative rainfall analysis of the 2021 mid-July flood event in Belgium","authors":"M. Journée, E. Goudenhoofdt, S. Vannitsem, L. Delobbe","doi":"10.5194/hess-27-3169-2023","DOIUrl":"https://doi.org/10.5194/hess-27-3169-2023","url":null,"abstract":"Abstract. The exceptional flood of July 2021 in central Europe impacted Belgium severely. As rainfall was the triggering factor of this event, this study aims to characterize rainfall amounts in Belgium from 13 to 16 July 2021 based on two types of observational data. First, observations recorded by high-quality rain gauges operated by weather and hydrological services in Belgium have been compiled and quality checked. Second, a radar-based rainfall product has been improved to provide a reliable estimation of quantitative precipitation at high spatial and temporal resolutions over Belgium. Several analyses of these data are performed here to describe the spatial and temporal distribution of rainfall during the event. These analyses indicate that the rainfall accumulations during the event reached unprecedented levels over large areas. Accumulations over durations from 1 to 3 d significantly exceeded the 200-year return level in several places, with up to 90 % of exceedance over the 200-year return level for 2 and 3 d values locally in the Vesdre Basin. Such a record-breaking event needs to be documented as much as possible, and available observational data must be shared with the scientific community for further studies in hydrology, in urban planning and, more generally, in all multi-disciplinary studies aiming to identify and understand factors leading to such disaster. The corresponding rainfall data are therefore provided freely in a supplement (Journée et al., 2023; Goudenhoofdt et al., 2023).\u0000","PeriodicalId":13143,"journal":{"name":"Hydrology and Earth System Sciences","volume":" ","pages":""},"PeriodicalIF":6.3,"publicationDate":"2023-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46758681","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-06DOI: 10.5194/hess-27-3191-2023
A. Foucher, S. Morera, Michael Sanchez, J. Orrillo, O. Evrard
Abstract. Although extreme El Niño events (EENEs) have always impacted hydrological anomalies and sediment transport in South America, their intensification by global warming and their association with changes in human activities and land cover after humid periods may lead to the acceleration of sediment transfers in river systems and dam reservoirs. This situation may threaten soil and water resources in arid and semiarid regions highly dependent on water originating from large dams. In this study, we investigated the sediment sequence accumulated in the Poechos Reservoir (northern Peru) and provided a retrospective reconstruction of the interactions of El Niño–Southern Oscillation (ENSO), agricultural practices and vegetation cover changes with sediment dynamics (1978–2019). To this end, a sediment core was dated and characterized by physical and chemical analyses (e.g., scanner tomography, X-ray fluorescence, particle size analysis) to estimate the evolution of sedimentation rates and changes in sediment sources during the last 5 decades. Sediment tracing results indicated the occurrence of changes in sediment sources associated with positive and negative phases of the Eastern Pacific index with a greater contribution of the lowland dry-forest area in comparison to that of the Andean area to sediment during the El Niño events (mean contribution of 76 %; up to 90 % during the coastal El Niño events (CENEs) of 2016–2017). This source contribution was mostly controlled by the stationary rainfall occurring during the EENEs in the lowland dry-forest area characterized by a low vegetation cover. Overall, after an extreme phase of ENSO, like after the EENE 1982–1983, the normal discharges and persistent sediment supplies from the middle- and upper-catchment parts led to river aggradation and the storage of substantial amounts of sediment in alluvial plains. In the absence of a significant EENE between 1983 and 1997, the large volume of sediment stored in the alluvial plains was exported by the EENE 1997–1998 resulting in an increase in sedimentation rate of 140 % after 1997 with a significant aggradation of the deltaic zone of the reservoir. In addition to the impact of extreme climate events on sediment dynamics, the development of agriculture along the riverine system after an extreme phase of ENSO increased the availability of sediments in the main channel of the rivers, easily transported by the next EENE. This study suggests that intensification of human activities associated with a higher frequency of extreme rainfall events amplified the quantity of sediment transported by the river system, which will significantly decrease the lifespan of the reservoir, which is essential to meeting the freshwater demands of the farmers and the populations living in this arid and semiarid region.
{"title":"El Niño–Southern Oscillation (ENSO)-driven hypersedimentation in the Poechos Reservoir, northern Peru","authors":"A. Foucher, S. Morera, Michael Sanchez, J. Orrillo, O. Evrard","doi":"10.5194/hess-27-3191-2023","DOIUrl":"https://doi.org/10.5194/hess-27-3191-2023","url":null,"abstract":"Abstract. Although extreme El Niño events (EENEs) have always impacted\u0000hydrological anomalies and sediment transport in South America, their\u0000intensification by global warming and their association with changes in\u0000human activities and land cover after humid periods may lead to the\u0000acceleration of sediment transfers in river systems and dam reservoirs. This\u0000situation may threaten soil and water resources in arid and semiarid regions\u0000highly dependent on water originating from large dams. In this study, we\u0000investigated the sediment sequence accumulated in the Poechos Reservoir\u0000(northern Peru) and provided a retrospective reconstruction of the\u0000interactions of El Niño–Southern Oscillation (ENSO), agricultural\u0000practices and vegetation cover changes with sediment dynamics (1978–2019). To\u0000this end, a sediment core was dated and characterized by physical and\u0000chemical analyses (e.g., scanner tomography, X-ray fluorescence, particle\u0000size analysis) to estimate the evolution of sedimentation rates and\u0000changes in sediment sources during the last 5 decades. Sediment tracing results indicated the occurrence of changes in sediment\u0000sources associated with positive and negative phases of the Eastern Pacific\u0000index with a greater contribution of the lowland dry-forest area in\u0000comparison to that of the Andean area to sediment during the El Niño\u0000events (mean contribution of 76 %; up to 90 % during the coastal El\u0000Niño events (CENEs) of 2016–2017). This source contribution was mostly\u0000controlled by the stationary rainfall occurring during the EENEs in the lowland dry-forest area characterized by a low vegetation cover. Overall, after an extreme phase of ENSO, like after the\u0000EENE 1982–1983, the normal discharges and persistent sediment supplies from\u0000the middle- and upper-catchment parts led to river aggradation and the\u0000storage of substantial amounts of sediment in alluvial plains. In the\u0000absence of a significant EENE between 1983 and 1997, the large volume of\u0000sediment stored in the alluvial plains was exported by the EENE 1997–1998\u0000resulting in an increase in sedimentation rate of 140 % after 1997 with\u0000a significant aggradation of the deltaic zone of the reservoir. In addition\u0000to the impact of extreme climate events on sediment dynamics, the\u0000development of agriculture along the riverine system after an extreme phase\u0000of ENSO increased the availability of sediments in the main channel of the\u0000rivers, easily transported by the next EENE. This study suggests that\u0000intensification of human activities associated with a higher frequency of\u0000extreme rainfall events amplified the quantity of sediment transported by\u0000the river system, which will significantly decrease the lifespan of the\u0000reservoir, which is essential to meeting the freshwater demands of the farmers and the\u0000populations living in this arid and semiarid region.\u0000","PeriodicalId":13143,"journal":{"name":"Hydrology and Earth System Sciences","volume":" ","pages":""},"PeriodicalIF":6.3,"publicationDate":"2023-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43248203","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-29DOI: 10.5194/hess-27-3143-2023
Theresa Boas, H. Bogena, D. Ryu, H. Vereecken, A. Western, H. Hendricks Franssen
Abstract. Long-range weather forecasts provide predictions of atmospheric, ocean and land surface conditions that can potentially be used in land surface and hydrological models to predict the water and energy status of the land surface or in crop growth models to predict yield for water resources or agricultural planning. However, the coarse spatial and temporal resolutions of available forecast products have hindered their widespread use in such modelling applications, which usually require high-resolution input data. In this study, we applied sub-seasonal (up to 4 months) and seasonal (7 months) weather forecasts from the latest European Centre for Medium-Range Weather Forecasts (ECMWF) seasonal forecasting system (SEAS5) in a land surface modelling approach using the Community Land Model version 5.0 (CLM5). Simulations were conducted for 2017–2020 forced with sub-seasonal and seasonal weather forecasts over two different domains with contrasting climate and cropping conditions: the German state of North Rhine-Westphalia (DE-NRW) and the Australian state of Victoria (AUS-VIC). We found that, after pre-processing of the forecast products (i.e. temporal downscaling of precipitation and incoming short-wave radiation), the simulations forced with seasonal and sub-seasonal forecasts were able to provide a model output that was very close to the reference simulation results forced by reanalysis data (the mean annual crop yield showed maximum differences of 0.28 and 0.36 t ha−1 for AUS-VIC and DE-NRW respectively). Differences between seasonal and sub-seasonal experiments were insignificant. The forecast experiments were able to satisfactorily capture recorded inter-annual variations of crop yield. In addition, they also reproduced the generally higher inter-annual differences in crop yield across the AUS-VIC domain (approximately 50 % inter-annual differences in recorded yields and up to 17 % inter-annual differences in simulated yields) compared to the DE-NRW domain (approximately 15 % inter-annual differences in recorded yields and up to 5 % in simulated yields). The high- and low-yield seasons (2020 and 2018) among the 4 simulated years were clearly reproduced in the forecast simulation results. Furthermore, sub-seasonal and seasonal simulations reflected the early harvest in the drought year of 2018 in the DE-NRW domain. However, simulated inter-annual yield variability was lower in all simulations compared to the official statistics. While general soil moisture trends, such as the European drought in 2018, were captured by the seasonal experiments, we found systematic overestimations and underestimations in both the forecast and reference simulations compared to the Soil Moisture Active Passive Level-3 soil moisture product (SMAP L3) and the Soil Moisture Climate Change Initiative Combined dataset from the European Space Agency (ESA CCI). These observed biases of soil moisture and the low inter-annual differences in simulated crop yield indicat
{"title":"Seasonal soil moisture and crop yield prediction with fifth-generation seasonal forecasting system (SEAS5) long-range meteorological forecasts in a land surface modelling approach","authors":"Theresa Boas, H. Bogena, D. Ryu, H. Vereecken, A. Western, H. Hendricks Franssen","doi":"10.5194/hess-27-3143-2023","DOIUrl":"https://doi.org/10.5194/hess-27-3143-2023","url":null,"abstract":"Abstract. Long-range weather forecasts provide predictions of atmospheric, ocean and land surface conditions that can potentially be used in land surface and hydrological models to predict the water and energy status of the land surface or in crop growth models to predict yield for water resources or agricultural planning. However, the coarse spatial and temporal resolutions of available forecast products have hindered their widespread use in such modelling applications, which usually require high-resolution input data. In this study, we applied sub-seasonal (up to 4 months) and seasonal (7 months) weather forecasts from the latest European Centre for Medium-Range Weather Forecasts (ECMWF) seasonal forecasting system (SEAS5) in a land surface modelling approach using the Community Land Model version 5.0 (CLM5). Simulations were conducted for 2017–2020 forced with sub-seasonal and seasonal weather forecasts over two different domains with contrasting climate and cropping conditions: the German state of North Rhine-Westphalia (DE-NRW) and the Australian state of Victoria (AUS-VIC). We found that, after pre-processing of the forecast products (i.e. temporal downscaling of precipitation and incoming short-wave radiation), the simulations forced with seasonal and sub-seasonal forecasts were able to provide a model output that was very close to the reference simulation results forced by reanalysis data (the mean annual crop yield showed maximum differences of 0.28 and 0.36 t ha−1 for AUS-VIC and DE-NRW respectively). Differences between seasonal and sub-seasonal experiments were insignificant. The forecast experiments were able to satisfactorily capture recorded inter-annual variations of crop yield. In addition, they also reproduced the generally higher inter-annual differences in crop yield across the AUS-VIC domain (approximately 50 % inter-annual differences in recorded yields and up to 17 % inter-annual differences in simulated yields) compared to the DE-NRW domain (approximately 15 % inter-annual differences in recorded yields and up to 5 % in simulated yields). The\u0000high- and low-yield seasons (2020 and 2018) among the 4 simulated years\u0000were clearly reproduced in the forecast simulation results. Furthermore,\u0000sub-seasonal and seasonal simulations reflected the early harvest in the\u0000drought year of 2018 in the DE-NRW domain. However, simulated inter-annual yield variability was lower in all simulations compared to the\u0000official statistics. While general soil moisture trends, such as the\u0000European drought in 2018, were captured by the seasonal experiments, we\u0000found systematic overestimations and underestimations in both the forecast and reference simulations compared to the Soil Moisture Active Passive Level-3 soil moisture product (SMAP L3) and the Soil Moisture Climate Change Initiative Combined dataset from the European Space Agency (ESA CCI). These observed biases of soil moisture and the low inter-annual differences in simulated crop yield indicat","PeriodicalId":13143,"journal":{"name":"Hydrology and Earth System Sciences","volume":" ","pages":""},"PeriodicalIF":6.3,"publicationDate":"2023-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47769390","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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