Pub Date : 2024-05-07DOI: 10.5194/hess-28-2023-2024
Yu Zhu, Shiyin Liu, Ben W. Brock, Lide Tian, Ying Yi, Fuming Xie, D. Shangguan, Yiyuan Shen
Abstract. The influence of supraglacial debris cover on glacier mass balance in the Karakoram is noteworthy. However, understanding of how debris cover affects the seasonal and long-term variations in glacier mass balance through alterations in the glacier's energy budget is incomplete. The present study coupled an energy–mass balance model with heat conduction within debris layers on debris-covered Batura Glacier in Hunza Valley to demonstrate the influence of debris cover on glacial surface energy and mass exchanges during 2000–2020. The mass balance of Batura Glacier is estimated to be -0.262±0.561 m w.e. yr−1, with debris cover accounting for a 45 % reduction in the negative mass balance. Due to the presence of debris cover, a significant portion of incoming energy is utilized for heating debris, leading to a large energy emission to the atmosphere via thermal radiation and turbulent sensible heat. This, in turn, reduces the melt latent heat energy at the glacier surface. We found that the mass balance exhibits a pronounced arch-shaped structure along the elevation gradient, which is associated with the distribution of debris thickness and the increasing impact of debris cover on the energy budget with decreasing elevation. Through a comprehensive analysis of the energy transfer within each debris layer, we have demonstrated that the primary impact of debris cover lies in its ability to modify the energy flux reaching the surface of the glacier. Thicker debris cover results in a smaller temperature gradient within debris layers, consequently reducing energy reaching the debris–ice interface. Over the past 2 decades, Batura Glacier has exhibited a trend towards less negative mass balance, likely linked to a decrease in air temperature and reduced ablation in areas with thin or sparse debris cover.
摘要上冰川碎屑覆盖对喀喇昆仑山冰川质量平衡的影响值得关注。然而，人们对碎屑覆盖如何通过改变冰川的能量预算来影响冰川质量平衡的季节性和长期性变化的了解还不全面。本研究将能量-质量平衡模型与洪扎谷地被碎屑覆盖的巴图拉冰川碎屑层内的热传导相结合，展示了 2000-2020 年期间碎屑覆盖对冰川表面能量和质量交换的影响。巴图拉冰川的质量平衡估计为-0.262±0.561 m w.e. yr-1，碎屑覆盖使负质量平衡减少了 45%。由于碎屑覆盖的存在，很大一部分进入的能量被用于加热碎屑，导致大量能量通过热辐射和湍流显热排放到大气中。这反过来又减少了冰川表面的融化潜热能。我们发现，质量平衡沿海拔梯度呈现出明显的拱形结构，这与碎屑厚度分布以及碎屑覆盖对能量预算的影响随海拔降低而增大有关。通过对每个碎屑层内的能量传递进行综合分析，我们证明碎屑覆盖的主要影响在于其改变到达冰川表面的能量通量的能力。较厚的碎屑覆盖层会导致碎屑层内的温度梯度变小，从而减少到达碎屑-冰界面的能量。在过去的二十年里，巴图拉冰川呈现出负质量平衡减少的趋势，这可能与气温下降以及碎屑覆盖较薄或稀疏地区的消融减少有关。
{"title":"Debris cover effects on energy and mass balance of Batura Glacier in the Karakoram over the past 20 years","authors":"Yu Zhu, Shiyin Liu, Ben W. Brock, Lide Tian, Ying Yi, Fuming Xie, D. Shangguan, Yiyuan Shen","doi":"10.5194/hess-28-2023-2024","DOIUrl":"https://doi.org/10.5194/hess-28-2023-2024","url":null,"abstract":"Abstract. The influence of supraglacial debris cover on glacier mass balance in the Karakoram is noteworthy. However, understanding of how debris cover affects the seasonal and long-term variations in glacier mass balance through alterations in the glacier's energy budget is incomplete. The present study coupled an energy–mass balance model with heat conduction within debris layers on debris-covered Batura Glacier in Hunza Valley to demonstrate the influence of debris cover on glacial surface energy and mass exchanges during 2000–2020. The mass balance of Batura Glacier is estimated to be -0.262±0.561 m w.e. yr−1, with debris cover accounting for a 45 % reduction in the negative mass balance. Due to the presence of debris cover, a significant portion of incoming energy is utilized for heating debris, leading to a large energy emission to the atmosphere via thermal radiation and turbulent sensible heat. This, in turn, reduces the melt latent heat energy at the glacier surface. We found that the mass balance exhibits a pronounced arch-shaped structure along the elevation gradient, which is associated with the distribution of debris thickness and the increasing impact of debris cover on the energy budget with decreasing elevation. Through a comprehensive analysis of the energy transfer within each debris layer, we have demonstrated that the primary impact of debris cover lies in its ability to modify the energy flux reaching the surface of the glacier. Thicker debris cover results in a smaller temperature gradient within debris layers, consequently reducing energy reaching the debris–ice interface. Over the past 2 decades, Batura Glacier has exhibited a trend towards less negative mass balance, likely linked to a decrease in air temperature and reduced ablation in areas with thin or sparse debris cover.\u0000","PeriodicalId":507846,"journal":{"name":"Hydrology and Earth System Sciences","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141004562","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-07DOI: 10.5194/hess-28-1981-2024
David A. Jimenez, Andrea Menapace, A. Zanfei, Eber José de Andrade Pinto, Bruno Brentan
Abstract. General circulation models generate climate simulations on grids with resolutions ranging from 50 to 600 km. The resulting coarse spatial resolution of the model outcomes requires post-processing routines to ensure reliable climate information for practical studies, prompting the widespread application of downscaling techniques. However, assessing the effectiveness of multiple downscaling techniques is essential, as their accuracy varies depending on the objectives of the analysis and the characteristics of the case study. In this context, this study aims to evaluate the performance of downscaling the daily precipitation series in the Metropolitan Region of Belo Horizonte (MRBH), Brazil, with the final scope of performing frequency analyses and estimating total precipitation and the number of rainy days per hydrological year at both annual and multiannual levels. To develop this study, 78 climate model simulations with a horizontal resolution of 100 km, which participated in the SSP1-2.6 and/or SSP5-8.5 scenarios of CMIP6, are employed. The results highlight that adjusting the simulations from the general circulation models by the delta method, quantile mapping and regression trees produces accurate results for estimating the total precipitation and number of rainy days. Finally, it is noted that employing downscaled precipitation series through quantile mapping and regression trees also yields promising results in terms of the frequency analyses.
{"title":"Assessing downscaling techniques for frequency analysis, total precipitation and rainy day estimation in CMIP6 simulations over hydrological years","authors":"David A. Jimenez, Andrea Menapace, A. Zanfei, Eber José de Andrade Pinto, Bruno Brentan","doi":"10.5194/hess-28-1981-2024","DOIUrl":"https://doi.org/10.5194/hess-28-1981-2024","url":null,"abstract":"Abstract. General circulation models generate climate simulations on grids with resolutions ranging from 50 to 600 km. The resulting coarse spatial resolution of the model outcomes requires post-processing routines to ensure reliable climate information for practical studies, prompting the widespread application of downscaling techniques. However, assessing the effectiveness of multiple downscaling techniques is essential, as their accuracy varies depending on the objectives of the analysis and the characteristics of the case study. In this context, this study aims to evaluate the performance of downscaling the daily precipitation series in the Metropolitan Region of Belo Horizonte (MRBH), Brazil, with the final scope of performing frequency analyses and estimating total precipitation and the number of rainy days per hydrological year at both annual and multiannual levels. To develop this study, 78 climate model simulations with a horizontal resolution of 100 km, which participated in the SSP1-2.6 and/or SSP5-8.5 scenarios of CMIP6, are employed. The results highlight that adjusting the simulations from the general circulation models by the delta method, quantile mapping and regression trees produces accurate results for estimating the total precipitation and number of rainy days. Finally, it is noted that employing downscaled precipitation series through quantile mapping and regression trees also yields promising results in terms of the frequency analyses.\u0000","PeriodicalId":507846,"journal":{"name":"Hydrology and Earth System Sciences","volume":"9 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141004427","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-07DOI: 10.5194/hess-28-1999-2024
Yanchen Zheng, G. Coxon, Ross Woods, Daniel Power, M. Rico‐Ramirez, David McJannet, R. Rosolem, Jianzhu Li, Ping Feng
Abstract. Reanalysis soil moisture products are valuable for diverse applications, but their quality assessment is limited due to scale discrepancies when compared to traditional in situ point-scale measurements. The emergence of cosmic ray neutron sensors (CRNSs) with field-scale soil moisture estimates (∼ 250 m radius, up to 0.7 m deep) is more suitable for the product evaluation owing to their larger footprint. In this study, we perform a comprehensive evaluation of eight widely used reanalysis soil moisture products (ERA5-Land, CFSv2, MERRA2, JRA55, GLDAS-Noah, CRA40, GLEAM and SMAP L4 datasets) against 135 CRNS sites from the COSMOS-UK, COSMOS-Europe, COSMOS USA and CosmOz Australia networks. We evaluate the products using six metrics capturing different aspects of soil moisture dynamics. Results show that all reanalysis products generally exhibit good temporal correlation with the measurements, with the median temporal correlation coefficient (R) values spanning 0.69 to 0.79, though large deviations are found at sites with seasonally varying vegetation cover. Poor performance is observed across products for soil moisture anomalies time series, with R values varying from 0.46 to 0.66. The performance of reanalysis products differs greatly across regions, climate, land covers and topographic conditions. In general, all products tend to overestimate data in arid climates and underestimate data in humid regions as well as grassland. Most reanalysis products perform poorly in steep terrain. Relatively low temporal correlation and high bias are detected in some sites from the west of the UK, which might be associated with relatively low bulk density and high soil organic carbon. Overall, ERA5-Land, CRA40, CFSv2, SMAP L4 and GLEAM exhibit superior performance compared to MERRA2, GLDAS-Noah and JRA55. We recommend that ERA5-Land and CFSv2 could be used in humid climates, whereas SMAP L4 and CRA40 perform better in arid regions. SMAP L4 has good performance for cropland, while GLEAM is more effective in shrubland regions. Our findings also provide insights into directions for improvement of soil moisture products for product developers.
{"title":"Evaluation of reanalysis soil moisture products using cosmic ray neutron sensor observations across the globe","authors":"Yanchen Zheng, G. Coxon, Ross Woods, Daniel Power, M. Rico‐Ramirez, David McJannet, R. Rosolem, Jianzhu Li, Ping Feng","doi":"10.5194/hess-28-1999-2024","DOIUrl":"https://doi.org/10.5194/hess-28-1999-2024","url":null,"abstract":"Abstract. Reanalysis soil moisture products are valuable for diverse applications, but their quality assessment is limited due to scale discrepancies when compared to traditional in situ point-scale measurements. The emergence of cosmic ray neutron sensors (CRNSs) with field-scale soil moisture estimates (∼ 250 m radius, up to 0.7 m deep) is more suitable for the product evaluation owing to their larger footprint. In this study, we perform a comprehensive evaluation of eight widely used reanalysis soil moisture products (ERA5-Land, CFSv2, MERRA2, JRA55, GLDAS-Noah, CRA40, GLEAM and SMAP L4 datasets) against 135 CRNS sites from the COSMOS-UK, COSMOS-Europe, COSMOS USA and CosmOz Australia networks. We evaluate the products using six metrics capturing different aspects of soil moisture dynamics. Results show that all reanalysis products generally exhibit good temporal correlation with the measurements, with the median temporal correlation coefficient (R) values spanning 0.69 to 0.79, though large deviations are found at sites with seasonally varying vegetation cover. Poor performance is observed across products for soil moisture anomalies time series, with R values varying from 0.46 to 0.66. The performance of reanalysis products differs greatly across regions, climate, land covers and topographic conditions. In general, all products tend to overestimate data in arid climates and underestimate data in humid regions as well as grassland. Most reanalysis products perform poorly in steep terrain. Relatively low temporal correlation and high bias are detected in some sites from the west of the UK, which might be associated with relatively low bulk density and high soil organic carbon. Overall, ERA5-Land, CRA40, CFSv2, SMAP L4 and GLEAM exhibit superior performance compared to MERRA2, GLDAS-Noah and JRA55. We recommend that ERA5-Land and CFSv2 could be used in humid climates, whereas SMAP L4 and CRA40 perform better in arid regions. SMAP L4 has good performance for cropland, while GLEAM is more effective in shrubland regions. Our findings also provide insights into directions for improvement of soil moisture products for product developers.\u0000","PeriodicalId":507846,"journal":{"name":"Hydrology and Earth System Sciences","volume":"61 S2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141002915","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-06DOI: 10.5194/hess-28-1935-2024
Mugni Hadi Hariadi, G. van der Schrier, G. Steeneveld, Samuel J. Sutanto, E. Sutanudjaja, D. Ratri, A. Sopaheluwakan, A. Klein Tank
Abstract. This article provides high-resolution information on the projected changes in annual extreme rainfall and high- and low-streamflow events over Southeast Asia under extreme climate change. The analysis was performed using the bias-corrected result of the High-Resolution Model Intercomparison Project (HighResMIP) multi-model experiment for the period 1971–2050. Eleven rainfall indices were calculated, along with streamflow simulation using the PCR-GLOBWB hydrological model. The historical period 1981–2010 and the near-future period 2021–2050 were considered for this analysis. Results indicate that, over former mainland Southeast Asia, Myanmar will face more challenges in the near future. The east coast of Myanmar will experience more extreme high-rainfall conditions, while northern Myanmar will have longer dry spells. Over the Indonesian maritime continent, Sumatra and Java will suffer from an increase in dry-spell length of up to 40 %, while the increase in extreme high rainfall will occur over Borneo and mountainous areas in Papua. Based on the streamflow analysis, the impact of climate change is more prominent in a low-flow event than in a high-flow event. The majority of rivers in the central Mekong catchment, Sumatra, Peninsular Malaysia, Borneo, and Java will experience more extreme low-flow events. More extreme dry conditions in the near future are also seen from the increasing probability of future low-flow occurrences, which reaches 101 % and 90 %, on average, over Sumatra and Java, respectively. In addition, based on our results over Java and Sumatra, we found that the changes in extreme high- and low-streamflow events are more pronounced in rivers with steep hydrographs (rivers where flash floods are easily triggered), while rivers with flat hydrographs have a higher risk in terms of the probability of low-flow change.
{"title":"A high-resolution perspective of extreme rainfall and river flow under extreme climate change in Southeast Asia","authors":"Mugni Hadi Hariadi, G. van der Schrier, G. Steeneveld, Samuel J. Sutanto, E. Sutanudjaja, D. Ratri, A. Sopaheluwakan, A. Klein Tank","doi":"10.5194/hess-28-1935-2024","DOIUrl":"https://doi.org/10.5194/hess-28-1935-2024","url":null,"abstract":"Abstract. This article provides high-resolution information on the projected changes in annual extreme rainfall and high- and low-streamflow events over Southeast Asia under extreme climate change. The analysis was performed using the bias-corrected result of the High-Resolution Model Intercomparison Project (HighResMIP) multi-model experiment for the period 1971–2050. Eleven rainfall indices were calculated, along with streamflow simulation using the PCR-GLOBWB hydrological model. The historical period 1981–2010 and the near-future period 2021–2050 were considered for this analysis. Results indicate that, over former mainland Southeast Asia, Myanmar will face more challenges in the near future. The east coast of Myanmar will experience more extreme high-rainfall conditions, while northern Myanmar will have longer dry spells. Over the Indonesian maritime continent, Sumatra and Java will suffer from an increase in dry-spell length of up to 40 %, while the increase in extreme high rainfall will occur over Borneo and mountainous areas in Papua. Based on the streamflow analysis, the impact of climate change is more prominent in a low-flow event than in a high-flow event. The majority of rivers in the central Mekong catchment, Sumatra, Peninsular Malaysia, Borneo, and Java will experience more extreme low-flow events. More extreme dry conditions in the near future are also seen from the increasing probability of future low-flow occurrences, which reaches 101 % and 90 %, on average, over Sumatra and Java, respectively. In addition, based on our results over Java and Sumatra, we found that the changes in extreme high- and low-streamflow events are more pronounced in rivers with steep hydrographs (rivers where flash floods are easily triggered), while rivers with flat hydrographs have a higher risk in terms of the probability of low-flow change.\u0000","PeriodicalId":507846,"journal":{"name":"Hydrology and Earth System Sciences","volume":"361 21","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141006225","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-06DOI: 10.5194/hess-28-1957-2024
A. Herr, L. Merrin, P. Mitchell, A. O'Grady, Kate L. Holland, Richard Mount, D. Post, C. Pavey, A. Sparrow
Abstract. Describing and classifying a landscape for environmental impact and risk assessment purposes is a non-trivial challenge because this requires region-specific landscape classifications that cater for region-specific impacts. Assessing impacts on ecosystems from the extraction of water resources across large regions requires a causal link between landscape features and their water requirements. We present the rationale and implementation of an ecohydrological classification for regions where coal mine and coal seam gas developments may impact on water. Our classification provides the essential framework for modelling the potential impact of hydrological changes from future coal resource developments at the landscape level. We develop an attribute-based system that provides representations of the ecohydrological entities and their connection to landscape features and make use of existing broad-level classification schemes into an attribute-based system. We incorporate a rule set with prioritisation, which underpins risk modelling and makes the scheme resource efficient, where spatial landscape or ecosystem classification schemes, developed for other purposes, already exist. A consistent rule set and conceptualised landscape processes and functions allow for the combination of diverse data with existing classification schemes. This makes the classification transparent, repeatable and adjustable, should new data become available. We apply the approach in three geographically different regions, with widely disparate information sources, for the classification, and provide a detailed example of its application. We propose that it is widely applicable around the world for linking ecohydrology to environmental impacts.
{"title":"A generalised ecohydrological landscape classification for assessing ecosystem risk in Australia due to an altering water regime","authors":"A. Herr, L. Merrin, P. Mitchell, A. O'Grady, Kate L. Holland, Richard Mount, D. Post, C. Pavey, A. Sparrow","doi":"10.5194/hess-28-1957-2024","DOIUrl":"https://doi.org/10.5194/hess-28-1957-2024","url":null,"abstract":"Abstract. Describing and classifying a landscape for environmental impact and risk assessment purposes is a non-trivial challenge because this requires region-specific landscape classifications that cater for region-specific impacts. Assessing impacts on ecosystems from the extraction of water resources across large regions requires a causal link between landscape features and their water requirements. We present the rationale and implementation of an ecohydrological classification for regions where coal mine and coal seam gas developments may impact on water. Our classification provides the essential framework for modelling the potential impact of hydrological changes from future coal resource developments at the landscape level. We develop an attribute-based system that provides representations of the ecohydrological entities and their connection to landscape features and make use of existing broad-level classification schemes into an attribute-based system. We incorporate a rule set with prioritisation, which underpins risk modelling and makes the scheme resource efficient, where spatial landscape or ecosystem classification schemes, developed for other purposes, already exist. A consistent rule set and conceptualised landscape processes and functions allow for the combination of diverse data with existing classification schemes. This makes the classification transparent, repeatable and adjustable, should new data become available. We apply the approach in three geographically different regions, with widely disparate information sources, for the classification, and provide a detailed example of its application. We propose that it is widely applicable around the world for linking ecohydrology to environmental impacts.\u0000","PeriodicalId":507846,"journal":{"name":"Hydrology and Earth System Sciences","volume":"3 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141009543","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-22DOI: 10.5194/hess-28-1287-2024
F. Aristizabal, T. Chegini, Gregory Petrochenkov, F. Salas, J. Judge
Abstract. Given the availability of high-quality and high-spatial-resolution digital elevation maps (DEMs) from the United States Geological Survey's 3D Elevation Program (3DEP), derived mostly from light detection and ranging (lidar) sensors, we examined the effects of these DEMs at various spatial resolutions on the quality of flood inundation map (FIM) extents derived from a terrain index known as Height Above Nearest Drainage (HAND). We found that using these DEMs improved the quality of resulting FIM extents at around 80 % of the catchments analyzed when compared to using DEMs from the National Hydrography Dataset Plus High Resolution (NHDPlusHR) program. Additionally, we varied the spatial resolution of the 3DEP DEMs at 3, 5, 10, 15, and 20 m (meters), and the results showed no significant overall effect on FIM extent quality across resolutions. However, further analysis at coarser resolutions of 60 and 90 m revealed a significant degradation in FIM skill, highlighting the limitations of using extremely coarse-resolution DEMs. Our experiments demonstrated a significant burden in terms of the computational time required to produce HAND and related data at finer resolutions. We fit a multiple linear regression model to help explain catchment-scale variations in the four metrics employed and found that the lack of reservoir flooding or inundation upstream of river retention systems was a significant factor in our analysis. For validation, we used Interagency Flood Risk Management (InFRM) Base Level Engineering (BLE)-produced FIM extents and streamflows at the 100- and 500-year event magnitudes in a sub-region in eastern Texas.
摘要鉴于美国地质调查局的三维高程计划（3DEP）提供了高质量、高空间分辨率的数字高程图（DEM），这些高程图主要由光探测和测距（lidar）传感器绘制，我们研究了这些不同空间分辨率的 DEM 对根据地形指数（即最近排水沟以上高度（HAND））绘制的洪水淹没图（FIM）范围质量的影响。我们发现，与使用国家水文数据集加高分辨率（NHDPlusHR）程序中的 DEM 相比，使用这些 DEM 提高了约 80% 的受分析流域的洪水淹没图范围质量。此外，我们还改变了 3DEP DEM 的空间分辨率（3、5、10、15 和 20 米），结果表明，不同分辨率对 FIM 范围质量的总体影响不大。然而，对 60 米和 90 米更高分辨率的进一步分析表明，FIM 技能明显下降，这突出表明了使用极高分辨率 DEM 的局限性。我们的实验表明，在更精细的分辨率下生成 HAND 和相关数据需要大量的计算时间。我们拟合了一个多线性回归模型，以帮助解释所采用的四项指标在流域尺度上的变化，并发现在我们的分析中，河流滞留系统上游缺乏水库洪水或淹没是一个重要因素。为了进行验证，我们使用了机构间洪水风险管理 (InFRM) 基础工程 (BLE) 制作的 FIM 范围以及德克萨斯州东部一个次区域的 100 年一遇和 500 年一遇的河水流量。
{"title":"Effects of high-quality elevation data and explanatory variables on the accuracy of flood inundation mapping via Height Above Nearest Drainage","authors":"F. Aristizabal, T. Chegini, Gregory Petrochenkov, F. Salas, J. Judge","doi":"10.5194/hess-28-1287-2024","DOIUrl":"https://doi.org/10.5194/hess-28-1287-2024","url":null,"abstract":"Abstract. Given the availability of high-quality and high-spatial-resolution digital elevation maps (DEMs) from the United States Geological Survey's 3D Elevation Program (3DEP), derived mostly from light detection and ranging (lidar) sensors, we examined the effects of these DEMs at various spatial resolutions on the quality of flood inundation map (FIM) extents derived from a terrain index known as Height Above Nearest Drainage (HAND). We found that using these DEMs improved the quality of resulting FIM extents at around 80 % of the catchments analyzed when compared to using DEMs from the National Hydrography Dataset Plus High Resolution (NHDPlusHR) program. Additionally, we varied the spatial resolution of the 3DEP DEMs at 3, 5, 10, 15, and 20 m (meters), and the results showed no significant overall effect on FIM extent quality across resolutions. However, further analysis at coarser resolutions of 60 and 90 m revealed a significant degradation in FIM skill, highlighting the limitations of using extremely coarse-resolution DEMs. Our experiments demonstrated a significant burden in terms of the computational time required to produce HAND and related data at finer resolutions. We fit a multiple linear regression model to help explain catchment-scale variations in the four metrics employed and found that the lack of reservoir flooding or inundation upstream of river retention systems was a significant factor in our analysis. For validation, we used Interagency Flood Risk Management (InFRM) Base Level Engineering (BLE)-produced FIM extents and streamflows at the 100- and 500-year event magnitudes in a sub-region in eastern Texas.\u0000","PeriodicalId":507846,"journal":{"name":"Hydrology and Earth System Sciences","volume":" 33","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140213327","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-15DOI: 10.5194/hess-28-1251-2024
C. Wasko, Seth Westra, R. Nathan, A. Pepler, T. Raupach, Andrew Dowdy, F. Johnson, Michelle Ho, Kathy McInnes, Doerte Jakob, Jason P. Evans, G. Villarini, Hayley J. Fowler
Abstract. In response to flood risk, design flood estimation is a cornerstone of planning, infrastructure design, setting of insurance premiums, and emergency response planning. Under stationary assumptions, flood guidance and the methods used in design flood estimation are firmly established in practice and mature in their theoretical foundations, but under climate change, guidance is still in its infancy. Human-caused climate change is influencing factors that contribute to flood risk such as rainfall extremes and soil moisture, and there is a need for updated flood guidance. However, a barrier to updating flood guidance is the translation of the science into practical application. For example, most science pertaining to historical changes to flood risk focuses on examining trends in annual maximum flood events or the application of non-stationary flood frequency analysis. Although this science is valuable, in practice, design flood estimation focuses on exceedance probabilities much rarer than annual maximum events, such as the 1 % annual exceedance probability event or even rarer, using rainfall-based procedures, at locations where there are few to no observations of streamflow. Here, we perform a systematic review to summarize the state-of-the-art understanding of the impact of climate change on design flood estimation in the Australian context, while also drawing on international literature. In addition, a meta-analysis, whereby results from multiple studies are combined, is conducted for extreme rainfall to provide quantitative estimates of possible future changes. This information is described in the context of contemporary design flood estimation practice to facilitate the inclusion of climate science into design flood estimation practice.
{"title":"A systematic review of climate change science relevant to Australian design flood estimation","authors":"C. Wasko, Seth Westra, R. Nathan, A. Pepler, T. Raupach, Andrew Dowdy, F. Johnson, Michelle Ho, Kathy McInnes, Doerte Jakob, Jason P. Evans, G. Villarini, Hayley J. Fowler","doi":"10.5194/hess-28-1251-2024","DOIUrl":"https://doi.org/10.5194/hess-28-1251-2024","url":null,"abstract":"Abstract. In response to flood risk, design flood estimation is a cornerstone of planning, infrastructure design, setting of insurance premiums, and emergency response planning. Under stationary assumptions, flood guidance and the methods used in design flood estimation are firmly established in practice and mature in their theoretical foundations, but under climate change, guidance is still in its infancy. Human-caused climate change is influencing factors that contribute to flood risk such as rainfall extremes and soil moisture, and there is a need for updated flood guidance. However, a barrier to updating flood guidance is the translation of the science into practical application. For example, most science pertaining to historical changes to flood risk focuses on examining trends in annual maximum flood events or the application of non-stationary flood frequency analysis. Although this science is valuable, in practice, design flood estimation focuses on exceedance probabilities much rarer than annual maximum events, such as the 1 % annual exceedance probability event or even rarer, using rainfall-based procedures, at locations where there are few to no observations of streamflow. Here, we perform a systematic review to summarize the state-of-the-art understanding of the impact of climate change on design flood estimation in the Australian context, while also drawing on international literature. In addition, a meta-analysis, whereby results from multiple studies are combined, is conducted for extreme rainfall to provide quantitative estimates of possible future changes. This information is described in the context of contemporary design flood estimation practice to facilitate the inclusion of climate science into design flood estimation practice.\u0000","PeriodicalId":507846,"journal":{"name":"Hydrology and Earth System Sciences","volume":"7 19","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140239375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-14DOI: 10.5194/hess-28-1215-2024
Annika Nolte, E. Haaf, B. Heudorfer, Steffen Bender, Jens Hartmann
Abstract. Groundwater level (GWL) dynamics result from a complex interplay between groundwater systems and the Earth system. This study aims to identify common hydrogeological patterns and to gain a deeper understanding of the underlying similarities and their link to physiographic, climatic, and anthropogenic controls of groundwater in coastal regions. The most striking aspects of GWL dynamics and their controls were identified through a combination of statistical metrics, calculated from about 8000 groundwater hydrographs, pattern recognition using clustering algorithms, classification using random forest, and SHapley Additive exPlanations (SHAPs). Hydrogeological similarity was defined by four clusters representing distinct patterns of GWL dynamics. These clusters can be observed globally across different continents and climate zones but simultaneously vary regionally and locally, suggesting a complicated interplay of controlling factors. The main controls differentiating GWL dynamics were identified, but we also provide evidence for the currently limited ability to explain GWL dynamics on large spatial scales, which we attribute mainly to uncertainties in the explanatory data. Finally, this study provides guidance for systematic and holistic groundwater monitoring and modeling and motivates a consideration of the different aspects of GWL dynamics, for example, when predicting climate-induced GWL changes, and the use of explainable machine learning techniques to deal with GWL complexity – especially when information on potential controls is limited or needs to be verified.
{"title":"Disentangling coastal groundwater level dynamics in a global dataset","authors":"Annika Nolte, E. Haaf, B. Heudorfer, Steffen Bender, Jens Hartmann","doi":"10.5194/hess-28-1215-2024","DOIUrl":"https://doi.org/10.5194/hess-28-1215-2024","url":null,"abstract":"Abstract. Groundwater level (GWL) dynamics result from a complex interplay between groundwater systems and the Earth system. This study aims to identify common hydrogeological patterns and to gain a deeper understanding of the underlying similarities and their link to physiographic, climatic, and anthropogenic controls of groundwater in coastal regions. The most striking aspects of GWL dynamics and their controls were identified through a combination of statistical metrics, calculated from about 8000 groundwater hydrographs, pattern recognition using clustering algorithms, classification using random forest, and SHapley Additive exPlanations (SHAPs). Hydrogeological similarity was defined by four clusters representing distinct patterns of GWL dynamics. These clusters can be observed globally across different continents and climate zones but simultaneously vary regionally and locally, suggesting a complicated interplay of controlling factors. The main controls differentiating GWL dynamics were identified, but we also provide evidence for the currently limited ability to explain GWL dynamics on large spatial scales, which we attribute mainly to uncertainties in the explanatory data. Finally, this study provides guidance for systematic and holistic groundwater monitoring and modeling and motivates a consideration of the different aspects of GWL dynamics, for example, when predicting climate-induced GWL changes, and the use of explainable machine learning techniques to deal with GWL complexity – especially when information on potential controls is limited or needs to be verified.\u0000","PeriodicalId":507846,"journal":{"name":"Hydrology and Earth System Sciences","volume":"14 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140243826","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-13DOI: 10.5194/hess-28-1191-2024
Stephanie R. Clark, J. Lerat, J. Perraud, Peter Fitch
Abstract. A deep learning model designed for time series predictions, the long short-term memory (LSTM) architecture, is regularly producing reliable results in local and regional rainfall–runoff applications around the world. Recent large-sample hydrology studies in North America and Europe have shown the LSTM model to successfully match conceptual model performance at a daily time step over hundreds of catchments. Here we investigate how these models perform in producing monthly runoff predictions in the relatively dry and variable conditions of the Australian continent. The monthly time step matches historic data availability and is also important for future water resources planning; however, it provides significantly smaller training datasets than daily time series. In this study, a continental-scale comparison of monthly deep learning (LSTM) predictions to conceptual rainfall–runoff (WAPABA model) predictions is performed on almost 500 catchments across Australia with performance results aggregated over a variety of catchment sizes, flow conditions, and hydrological record lengths. The study period covers a wet phase followed by a prolonged drought, introducing challenges for making predictions outside of known conditions – challenges that will intensify as climate change progresses. The results show that LSTM models matched or exceeded WAPABA prediction performance for more than two-thirds of the study catchments, the largest performance gains of LSTM versus WAPABA occurred in large catchments, the LSTMs struggled less to generalise than the WAPABA models (e.g. making predictions under new conditions), and catchments with few training observations due to the monthly time step did not demonstrate a clear benefit with either WAPABA or LSTM.
{"title":"Deep learning for monthly rainfall–runoff modelling: a large-sample comparison with conceptual models across Australia","authors":"Stephanie R. Clark, J. Lerat, J. Perraud, Peter Fitch","doi":"10.5194/hess-28-1191-2024","DOIUrl":"https://doi.org/10.5194/hess-28-1191-2024","url":null,"abstract":"Abstract. A deep learning model designed for time series predictions, the long short-term memory (LSTM) architecture, is regularly producing reliable results in local and regional rainfall–runoff applications around the world. Recent large-sample hydrology studies in North America and Europe have shown the LSTM model to successfully match conceptual model performance at a daily time step over hundreds of catchments. Here we investigate how these models perform in producing monthly runoff predictions in the relatively dry and variable conditions of the Australian continent. The monthly time step matches historic data availability and is also important for future water resources planning; however, it provides significantly smaller training datasets than daily time series. In this study, a continental-scale comparison of monthly deep learning (LSTM) predictions to conceptual rainfall–runoff (WAPABA model) predictions is performed on almost 500 catchments across Australia with performance results aggregated over a variety of catchment sizes, flow conditions, and hydrological record lengths. The study period covers a wet phase followed by a prolonged drought, introducing challenges for making predictions outside of known conditions – challenges that will intensify as climate change progresses. The results show that LSTM models matched or exceeded WAPABA prediction performance for more than two-thirds of the study catchments, the largest performance gains of LSTM versus WAPABA occurred in large catchments, the LSTMs struggled less to generalise than the WAPABA models (e.g. making predictions under new conditions), and catchments with few training observations due to the monthly time step did not demonstrate a clear benefit with either WAPABA or LSTM.\u0000","PeriodicalId":507846,"journal":{"name":"Hydrology and Earth System Sciences","volume":"2005 21","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140246455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-07DOI: 10.5194/hess-28-1173-2024
Ariel Henrique do Prado, D. Mair, Philippos Garefalakis, Chantal Schmidt, Alexander C. Whittaker, S. Castelltort, F. Schlunegger
Abstract. The construction of check dams is a common practice around the world where the aim is to reduce the damage by flooding events through mountain streams. However, quantifying the effectiveness of such engineering structures has remained very challenging and requires well-selected case studies, since the outcome of such an evaluation depends on site-specific geometric, geologic and climatic conditions. Conventionally, the check dams' effectiveness has been estimated using information about how the bedload sediment flux in the stream changes after the check dams are constructed. A permanent lowering of the bedload flux not only points to a success in reducing the probability of sediment transport occurrence but also implies that the sediment input through the system is likely to decrease. Here, we applied a method for data acquisition and two different equations (Meyer-Peter–Müller and Recking approach) to estimate and compare the sediment transport in a mountain stream in Switzerland under engineered and non-engineered conditions. Whereas the first equation is derived from a classical approach that is based on flume experiment data with a slope of less than 0.02 m m−1, the second equation (Recking) has been derived based on a bedload field dataset comprising active mountain streams under steeper conditions. We selected the Guerbe (Gürbe) River situated in the Swiss Alps as a case study, which has been engineered since the end of the 19th century. This has resulted in more than 110 check dams along a ca. 5 km reach where sediment has continuously been supplied from adjacent hillslopes, primarily by landsliding. We measured the riverbed grain size, topographic gradients and river widths within selected segments along this reach. Additionally, a gauging station downstream of the reach engineered with check dams yielded information to calibrate the hydroclimatic situation for the study reach, thus offering ideal conditions for our catchment-scale experiment. Using the acquired data and the dataset about historical runoff covering the time interval between 2009 and 2021 and considering the current engineered conditions, we estimated a mean annual volume of transported bedload which ranges from 900 to 6000 m3 yr−1. We then envisaged possible channel geometries before the check dams were constructed. We inferred (1) higher energy gradients which we averaged over the length of several check dams and which we considered a proxy for the steeper river slope under natural conditions; (2) channel widths that are smaller than those measured today, thereby anticipating that the channel was more confined in the past; and (3) larger grain size percentiles, which we consider to be similar to the values measured from preserved landslides in the region. Using such potential non-engineered scenarios as constraints, the two equations both point towards a larger sediment flux compared to the engineered state, although the results of these equations differed sign
{"title":"Check dam impact on sediment loads: example of the Guerbe River in the Swiss Alps – a catchment scale experiment","authors":"Ariel Henrique do Prado, D. Mair, Philippos Garefalakis, Chantal Schmidt, Alexander C. Whittaker, S. Castelltort, F. Schlunegger","doi":"10.5194/hess-28-1173-2024","DOIUrl":"https://doi.org/10.5194/hess-28-1173-2024","url":null,"abstract":"Abstract. The construction of check dams is a common practice around the world where the aim is to reduce the damage by flooding events through mountain streams. However, quantifying the effectiveness of such engineering structures has remained very challenging and requires well-selected case studies, since the outcome of such an evaluation depends on site-specific geometric, geologic and climatic conditions. Conventionally, the check dams' effectiveness has been estimated using information about how the bedload sediment flux in the stream changes after the check dams are constructed. A permanent lowering of the bedload flux not only points to a success in reducing the probability of sediment transport occurrence but also implies that the sediment input through the system is likely to decrease. Here, we applied a method for data acquisition and two different equations (Meyer-Peter–Müller and Recking approach) to estimate and compare the sediment transport in a mountain stream in Switzerland under engineered and non-engineered conditions. Whereas the first equation is derived from a classical approach that is based on flume experiment data with a slope of less than 0.02 m m−1, the second equation (Recking) has been derived based on a bedload field dataset comprising active mountain streams under steeper conditions. We selected the Guerbe (Gürbe) River situated in the Swiss Alps as a case study, which has been engineered since the end of the 19th century. This has resulted in more than 110 check dams along a ca. 5 km reach where sediment has continuously been supplied from adjacent hillslopes, primarily by landsliding. We measured the riverbed grain size, topographic gradients and river widths within selected segments along this reach. Additionally, a gauging station downstream of the reach engineered with check dams yielded information to calibrate the hydroclimatic situation for the study reach, thus offering ideal conditions for our catchment-scale experiment. Using the acquired data and the dataset about historical runoff covering the time interval between 2009 and 2021 and considering the current engineered conditions, we estimated a mean annual volume of transported bedload which ranges from 900 to 6000 m3 yr−1. We then envisaged possible channel geometries before the check dams were constructed. We inferred (1) higher energy gradients which we averaged over the length of several check dams and which we considered a proxy for the steeper river slope under natural conditions; (2) channel widths that are smaller than those measured today, thereby anticipating that the channel was more confined in the past; and (3) larger grain size percentiles, which we consider to be similar to the values measured from preserved landslides in the region. Using such potential non-engineered scenarios as constraints, the two equations both point towards a larger sediment flux compared to the engineered state, although the results of these equations differed sign","PeriodicalId":507846,"journal":{"name":"Hydrology and Earth System Sciences","volume":"34 127","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140260166","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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