Pub Date : 2024-01-05DOI: 10.5194/hess-28-103-2024
C. Cammalleri, C. De Michele, A. Toreti
Abstract. The joint probability of precipitation and soil moisture is here investigated over Europe with the goal to extrapolate meaningful insights into the potential joint use of these variables for the detection of agricultural droughts within a multivariate probabilistic modeling framework. The use of copulas is explored, being the framework often used in hydrological studies for the analysis of bivariate distributions. The analysis is performed for the period 1996–2020 on the empirical frequencies derived from ERA5 precipitation and LISFLOOD soil moisture datasets, both available as part of the Copernicus European Drought Observatory. The results show an overall good correlation between the two standardized series (Kendall's τ= 0.42±0.1) but also clear spatial patterns in the tail dependence derived with both non-parametric and parametric approaches. About half of the domain shows symmetric tail dependence, well reproduced by the Student's t copula, whereas the rest of the domain is almost equally split between low- and high-tail dependences (both modeled with the Gumbel family of copulas). These spatial patterns are reasonably reproduced by a random forest classifier, suggesting that this outcome is not driven by chance. This study stresses how a joint use of standardized precipitation and soil moisture for agriculture drought characterization may be beneficial in areas with strong low-tail dependence and how this behavior should be carefully considered in multivariate drought studies.
{"title":"Exploring the joint probability of precipitation and soil moisture over Europe using copulas","authors":"C. Cammalleri, C. De Michele, A. Toreti","doi":"10.5194/hess-28-103-2024","DOIUrl":"https://doi.org/10.5194/hess-28-103-2024","url":null,"abstract":"Abstract. The joint probability of precipitation and soil moisture is here investigated over Europe with the goal to extrapolate meaningful insights into the potential joint use of these variables for the detection of agricultural droughts within a multivariate probabilistic modeling framework. The use of copulas is explored, being the framework often used in hydrological studies for the analysis of bivariate distributions. The analysis is performed for the period 1996–2020 on the empirical frequencies derived from ERA5 precipitation and LISFLOOD soil moisture datasets, both available as part of the Copernicus European Drought Observatory. The results show an overall good correlation between the two standardized series (Kendall's τ= 0.42±0.1) but also clear spatial patterns in the tail dependence derived with both non-parametric and parametric approaches. About half of the domain shows symmetric tail dependence, well reproduced by the Student's t copula, whereas the rest of the domain is almost equally split between low- and high-tail dependences (both modeled with the Gumbel family of copulas). These spatial patterns are reasonably reproduced by a random forest classifier, suggesting that this outcome is not driven by chance. This study stresses how a joint use of standardized precipitation and soil moisture for agriculture drought characterization may be beneficial in areas with strong low-tail dependence and how this behavior should be carefully considered in multivariate drought studies.\u0000","PeriodicalId":13143,"journal":{"name":"Hydrology and Earth System Sciences","volume":"84 22","pages":""},"PeriodicalIF":6.3,"publicationDate":"2024-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139381428","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}
Magdalena Uber, M. Haller, C. Brendel, G. Hillebrand, T. Hoffmann
Abstract. Heavy rainfall is the main driver of soil erosion by water, which is a threat to soil and water resources across the globe. As a consequence of climate change, precipitation – especially extreme precipitation – is increasing in a warmer world, leading to an increase in rainfall erosivity. However, conventional global climate models struggle to represent extreme rain events and cannot provide precipitation data at the high spatiotemporal resolution that is needed for an accurate estimation of future rainfall erosivity. Convection-permitting simulations (CPSs), on the other hand, provide high-resolution precipitation data and a better representation of extreme rain events, but they are mostly limited to relatively small spatial extents and short time periods. Here, we present, for the first time, rainfall erosivity in a large modeling domain such as central Europe based on high-resolution CPS climate data generated with the regional climate model COSMO-CLM using the Representative Concentration Pathway 8.5 (RCP8.5) emission scenario. We calculated rainfall erosivity for the past (1971–2000), present (2001–2019), near future (2031–2060) and far future (2071–2100). Our results showed that future increases in rainfall erosivity in central Europe can be up to 84 % in the region's river basins. These increases are much higher than previously estimated based on regression with mean annual precipitation. We conclude that despite remaining limitations, CPSs have an enormous and currently unexploited potential for climate impact studies on soil erosion. Thus, the soil erosion modeling community should closely follow the recent and future advances in climate modeling to take advantage of new CPSs for climate impact studies.
{"title":"Past, present and future rainfall erosivity in central Europe based on convection-permitting climate simulations","authors":"Magdalena Uber, M. Haller, C. Brendel, G. Hillebrand, T. Hoffmann","doi":"10.5194/hess-28-87-2024","DOIUrl":"https://doi.org/10.5194/hess-28-87-2024","url":null,"abstract":"Abstract. Heavy rainfall is the main driver of soil erosion by water, which is a threat to soil and water resources across the globe. As a consequence of climate change, precipitation – especially extreme precipitation – is increasing in a warmer world, leading to an increase in rainfall erosivity. However, conventional global climate models struggle to represent extreme rain events and cannot provide precipitation data at the high spatiotemporal resolution that is needed for an accurate estimation of future rainfall erosivity. Convection-permitting simulations (CPSs), on the other hand, provide high-resolution precipitation data and a better representation of extreme rain events, but they are mostly limited to relatively small spatial extents and short time periods. Here, we present, for the first time, rainfall erosivity in a large modeling domain such as central Europe based on high-resolution CPS climate data generated with the regional climate model COSMO-CLM using the Representative Concentration Pathway 8.5 (RCP8.5) emission scenario. We calculated rainfall erosivity for the past (1971–2000), present (2001–2019), near future (2031–2060) and far future (2071–2100). Our results showed that future increases in rainfall erosivity in central Europe can be up to 84 % in the region's river basins. These increases are much higher than previously estimated based on regression with mean annual precipitation. We conclude that despite remaining limitations, CPSs have an enormous and currently unexploited potential for climate impact studies on soil erosion. Thus, the soil erosion modeling community should closely follow the recent and future advances in climate modeling to take advantage of new CPSs for climate impact studies.\u0000","PeriodicalId":13143,"journal":{"name":"Hydrology and Earth System Sciences","volume":"59 6","pages":""},"PeriodicalIF":6.3,"publicationDate":"2024-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139381923","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}
S. Abbas, R. Bailey, J. White, J. Arnold, M. White, Natalja Čerkasova, Jungang Gao
Abstract. Parameter sensitivity analysis plays a critical role in efficiently determining main parameters, enhancing the effectiveness of the estimation of parameters and uncertainty quantification in hydrologic modeling. In this paper, we demonstrate an uncertainty and sensitivity analysis technique for the holistic Soil and Water Assessment Tool (SWAT+) model coupled with new gwflow module, spatially distributed, physically based groundwater flow modeling. The main calculated groundwater inflows and outflows include boundary exchange, pumping, saturation excess flow, groundwater–surface water exchange, recharge, groundwater–lake exchange and tile drainage outflow. We present the method for four watersheds located in different areas of the United States for 16 years (2000–2015), emphasizing regions of extensive tile drainage (Winnebago River, Minnesota, Iowa), intensive surface–groundwater interactions (Nanticoke River, Delaware, Maryland), groundwater pumping for irrigation (Cache River, Missouri, Arkansas) and mountain snowmelt (Arkansas Headwaters, Colorado). The main parameters of the coupled SWAT+gwflow model are estimated utilizing the parameter estimation software PEST. The monthly streamflow of holistic SWAT+gwflow is evaluated based on the Nash–Sutcliffe efficiency index (NSE), percentage bias (PBIAS), determination coefficient (R2) and Kling–Gupta efficiency coefficient (KGE), whereas groundwater head is evaluated using mean absolute error (MAE). The Morris method is employed to identify the key parameters influencing hydrological fluxes. Furthermore, the iterative ensemble smoother (iES) is utilized as a technique for uncertainty quantification (UQ) and parameter estimation (PE) and to decrease the computational cost owing to the large number of parameters. Depending on the watershed, key identified selected parameters include aquifer specific yield, aquifer hydraulic conductivity, recharge delay, streambed thickness, streambed hydraulic conductivity, area of groundwater inflow to tile, depth of tiles below ground surface, hydraulic conductivity of the drain perimeter, river depth (for groundwater flow processes), runoff curve number (for surface runoff processes), plant uptake compensation factor, soil evaporation compensation factor (for potential and actual evapotranspiration processes), soil available water capacity and percolation coefficient (for soil water processes). The presence of gwflow parameters permits the recognition of all key parameters in the surface and/or subsurface flow processes, with results substantially differing if the base SWAT+ models are utilized.
{"title":"A framework for parameter estimation, sensitivity analysis, and uncertainty analysis for holistic hydrologic modeling using SWAT+","authors":"S. Abbas, R. Bailey, J. White, J. Arnold, M. White, Natalja Čerkasova, Jungang Gao","doi":"10.5194/hess-28-21-2024","DOIUrl":"https://doi.org/10.5194/hess-28-21-2024","url":null,"abstract":"Abstract. Parameter sensitivity analysis plays a critical role in efficiently determining main parameters, enhancing the effectiveness of the estimation of parameters and uncertainty quantification in hydrologic modeling. In this paper, we demonstrate an uncertainty and sensitivity analysis technique for the holistic Soil and Water Assessment Tool (SWAT+) model coupled with new gwflow module, spatially distributed, physically based groundwater flow modeling. The main calculated groundwater inflows and outflows include boundary exchange, pumping, saturation excess flow, groundwater–surface water exchange, recharge, groundwater–lake exchange and tile drainage outflow. We present the method for four watersheds located in different areas of the United States for 16 years (2000–2015), emphasizing regions of extensive tile drainage (Winnebago River, Minnesota, Iowa), intensive surface–groundwater interactions (Nanticoke River, Delaware, Maryland), groundwater pumping for irrigation (Cache River, Missouri, Arkansas) and mountain snowmelt (Arkansas Headwaters, Colorado). The main parameters of the coupled SWAT+gwflow model are estimated utilizing the parameter estimation software PEST. The monthly streamflow of holistic SWAT+gwflow is evaluated based on the Nash–Sutcliffe efficiency index (NSE), percentage bias (PBIAS), determination coefficient (R2) and Kling–Gupta efficiency coefficient (KGE), whereas groundwater head is evaluated using mean absolute error (MAE). The Morris method is employed to identify the key parameters influencing hydrological fluxes. Furthermore, the iterative ensemble smoother (iES) is utilized as a technique for uncertainty quantification (UQ) and parameter estimation (PE) and to decrease the computational cost owing to the large number of parameters. Depending on the watershed, key identified selected parameters include aquifer specific yield, aquifer hydraulic conductivity, recharge delay, streambed thickness, streambed hydraulic conductivity, area of groundwater inflow to tile, depth of tiles below ground surface, hydraulic conductivity of the drain perimeter, river depth (for groundwater flow processes), runoff curve number (for surface runoff processes), plant uptake compensation factor, soil evaporation compensation factor (for potential and actual evapotranspiration processes), soil available water capacity and percolation coefficient (for soil water processes). The presence of gwflow parameters permits the recognition of all key parameters in the surface and/or subsurface flow processes, with results substantially differing if the base SWAT+ models are utilized.\u0000","PeriodicalId":13143,"journal":{"name":"Hydrology and Earth System Sciences","volume":"46 7","pages":""},"PeriodicalIF":6.3,"publicationDate":"2024-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139390568","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 : 2023-12-22DOI: 10.5194/hess-27-4609-2023
Fabian Maier, Florian Lustenberger, Ilja van Meerveld
Abstract. Glacial retreat uncovers large bodies of unconsolidated sediment that are prone to erosion. However, our knowledge of overland flow (OF) generation and sediment transport on moraines that have recently become ice-free is still limited. To investigate how the surface characteristics of young moraines affect OF and sediment transport, we installed five bounded runoff plots on two moraines of different ages in a proglacial area of the Swiss Alps. On each plot we conducted three sprinkling experiments to determine OF characteristics (i.e., total OF and peak OF flow rate) and measured sediment transport (turbidity, sediment concentrations, and total sediment yield). To determine and visualize where sediment transport takes place, we used a fluorescent sand tracer with an afterglow as well as ultraviolet (UV) and light-emitting diode (LED) lamps and a high-resolution camera. The results highlight the ability of this field setup to detect sand movement, even for individual fluorescent sand particles (300–500 µm grain size), and to distinguish between the two main mechanisms of sediment transport: OF-driven erosion and splash erosion. The higher rock cover on the younger moraine resulted in longer sediment transport distances and a higher sediment yield. In contrast, the higher vegetation cover on the older moraine promoted infiltration and reduced the length of the sediment transport pathways. Thus, this study demonstrates the potential of the use of fluorescent sand with an afterglow to determine sediment transport pathways as well as the fact that these observations can help to improve our understanding of OF and sediment transport processes on complex natural hillslopes.
{"title":"Assessment of plot-scale sediment transport on young moraines in the Swiss Alps using a fluorescent sand tracer","authors":"Fabian Maier, Florian Lustenberger, Ilja van Meerveld","doi":"10.5194/hess-27-4609-2023","DOIUrl":"https://doi.org/10.5194/hess-27-4609-2023","url":null,"abstract":"Abstract. Glacial retreat uncovers large bodies of unconsolidated sediment that are prone to erosion. However, our knowledge of overland flow (OF) generation and sediment transport on moraines that have recently become ice-free is still limited. To investigate how the surface characteristics of young moraines affect OF and sediment transport, we installed five bounded runoff plots on two moraines of different ages in a proglacial area of the Swiss Alps. On each plot we conducted three sprinkling experiments to determine OF characteristics (i.e., total OF and peak OF flow rate) and measured sediment transport (turbidity, sediment concentrations, and total sediment yield). To determine and visualize where sediment transport takes place, we used a fluorescent sand tracer with an afterglow as well as ultraviolet (UV) and light-emitting diode (LED) lamps and a high-resolution camera. The results highlight the ability of this field setup to detect sand movement, even for individual fluorescent sand particles (300–500 µm grain size), and to distinguish between the two main mechanisms of sediment transport: OF-driven erosion and splash erosion. The higher rock cover on the younger moraine resulted in longer sediment transport distances and a higher sediment yield. In contrast, the higher vegetation cover on the older moraine promoted infiltration and reduced the length of the sediment transport pathways. Thus, this study demonstrates the potential of the use of fluorescent sand with an afterglow to determine sediment transport pathways as well as the fact that these observations can help to improve our understanding of OF and sediment transport processes on complex natural hillslopes.\u0000","PeriodicalId":13143,"journal":{"name":"Hydrology and Earth System Sciences","volume":"3 3","pages":""},"PeriodicalIF":6.3,"publicationDate":"2023-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138947378","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 : 2023-12-22DOI: 10.5194/hess-27-4637-2023
E. Alonso‐González, Kristoffer Aalstad, N. Pirk, Marco Mazzolini, D. Treichler, P. Leclercq, S. Westermann, J. López‐Moreno, S. Gascoin
Abstract. Data assimilation techniques that integrate available observations with snow models have been proposed as a viable option to simultaneously help constrain model uncertainty and add value to observations by improving estimates of the snowpack state. However, the propagation of information from spatially sparse observations in high-resolution simulations remains an under-explored topic. To remedy this, the development of data assimilation techniques that can spread information in space is a crucial step. Herein, we examine the potential of spatio-temporal data assimilation for integrating sparse snow depth observations with hyper-resolution (5 m) snow simulations in the Izas central Pyrenean experimental catchment (Spain). Our experiments were developed using the Multiple Snow Data Assimilation System (MuSA) with new improvements to tackle the spatio-temporal data assimilation. Therein, we used a deterministic ensemble smoother with multiple data assimilation (DES-MDA) with domain localization. Three different experiments were performed to showcase the capabilities of spatio-temporal information transfer in hyper-resolution snow simulations. Experiment I employed the conventional geographical Euclidean distance to map the similarity between cells. Experiment II utilized the Mahalanobis distance in a multi-dimensional topographic space using terrain parameters extracted from a digital elevation model. Experiment III utilized a more direct mapping of snowpack similarity from a single complete snow depth map together with the easting and northing coordinates. Although all experiments showed a noticeable improvement in the snow patterns in the catchment compared with the deterministic open loop in terms of correlation (r=0.13) and root mean square error (RMSE = 1.11 m), the use of topographical dimensions (Experiment II, r=0.63 and RMSE = 0.89 m) and observations (Experiments III, r=0.92 and RMSE = 0.44 m) largely outperform the simulated patterns in Experiment I (r=0.38 and RMSE = 1.16 m). At the same time, Experiments II and III are considerably more challenging to set up. The results of these experiments can help pave the way for the creation of snow reanalysis and forecasting tools that can seamlessly integrate sparse information from national monitoring networks and high-resolution satellite information.
摘要。将现有观测数据与雪模型相结合的数据同化技术被认为是一种可行的选择，既有助于限制模型的不确定性，又能通过改进对积雪状态的估计来增加观测数据的价值。然而，在高分辨率模拟中如何传播来自空间稀疏观测数据的信息，仍然是一个探索不足的课题。为了解决这一问题，开发能够在空间传播信息的数据同化技术是至关重要的一步。在此，我们研究了时空数据同化技术在整合伊萨斯比利牛斯山脉中部实验集水区（西班牙）稀疏雪深观测数据与超分辨率（5 米）积雪模拟数据方面的潜力。我们的实验是利用多重雪数据同化系统（MuSA）开发的，该系统在时空数据同化方面做了新的改进。在此过程中，我们使用了具有域定位功能的多数据同化确定性集合平滑器（DES-MDA）。为了展示超分辨率雪地模拟中时空信息传递的能力，我们进行了三个不同的实验。实验 I 采用传统的地理欧氏距离来映射单元之间的相似性。实验 II 利用从数字高程模型中提取的地形参数，在多维地形空间中使用马哈拉诺比斯距离。实验三则利用一张完整的雪深图和经纬度坐标，更直接地绘制出雪堆相似度地图。虽然所有实验都显示，与确定性开环相比，集水区的积雪模式在相关性（r=0.13）和均方根误差（RMSE = 1.11 米）方面都有明显改善，但使用地形维度（实验二，r=0.63，RMSE = 0.89 米）和观测数据（实验三，r=0.92，RMSE = 0.44 米）在很大程度上优于实验一的模拟模式（r=0.38，RMSE = 1.16 米）。同时，实验二和实验三的设置难度要大得多。这些实验的结果有助于为创建能够无缝整合来自国家监测网络的稀疏信息和高分辨率卫星信息的积雪再分析和预报工具铺平道路。
{"title":"Spatio-temporal information propagation using sparse observations in hyper-resolution ensemble-based snow data assimilation","authors":"E. Alonso‐González, Kristoffer Aalstad, N. Pirk, Marco Mazzolini, D. Treichler, P. Leclercq, S. Westermann, J. López‐Moreno, S. Gascoin","doi":"10.5194/hess-27-4637-2023","DOIUrl":"https://doi.org/10.5194/hess-27-4637-2023","url":null,"abstract":"Abstract. Data assimilation techniques that integrate available observations with snow models have been proposed as a viable option to simultaneously help constrain model uncertainty and add value to observations by improving estimates of the snowpack state. However, the propagation of information from spatially sparse observations in high-resolution simulations remains an under-explored topic. To remedy this, the development of data assimilation techniques that can spread information in space is a crucial step. Herein, we examine the potential of spatio-temporal data assimilation for integrating sparse snow depth observations with hyper-resolution (5 m) snow simulations in the Izas central Pyrenean experimental catchment (Spain). Our experiments were developed using the Multiple Snow Data Assimilation System (MuSA) with new improvements to tackle the spatio-temporal data assimilation. Therein, we used a deterministic ensemble smoother with multiple data assimilation (DES-MDA) with domain localization. Three different experiments were performed to showcase the capabilities of spatio-temporal information transfer in hyper-resolution snow simulations. Experiment I employed the conventional geographical Euclidean distance to map the similarity between cells. Experiment II utilized the Mahalanobis distance in a multi-dimensional topographic space using terrain parameters extracted from a digital elevation model. Experiment III utilized a more direct mapping of snowpack similarity from a single complete snow depth map together with the easting and northing coordinates. Although all experiments showed a noticeable improvement in the snow patterns in the catchment compared with the deterministic open loop in terms of correlation (r=0.13) and root mean square error (RMSE = 1.11 m), the use of topographical dimensions (Experiment II, r=0.63 and RMSE = 0.89 m) and observations (Experiments III, r=0.92 and RMSE = 0.44 m) largely outperform the simulated patterns in Experiment I (r=0.38 and RMSE = 1.16 m). At the same time, Experiments II and III are considerably more challenging to set up. The results of these experiments can help pave the way for the creation of snow reanalysis and forecasting tools that can seamlessly integrate sparse information from national monitoring networks and high-resolution satellite information.\u0000","PeriodicalId":13143,"journal":{"name":"Hydrology and Earth System Sciences","volume":"3 3","pages":""},"PeriodicalIF":6.3,"publicationDate":"2023-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138944368","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 : 2023-12-22DOI: 10.5194/hess-27-4595-2023
Mennatullah T. Elrashidy, A. Ireson, Saman Razavi
Abstract. Wetland systems are among the largest stores of carbon on the planet, the most biologically diverse of all ecosystems, and dominant controls on the hydrologic cycle. However, their representation in land surface models (LSMs), which are the terrestrial lower boundary of Earth system models (ESMs) that inform climate actions, is limited. Here, we explore different possible parameterizations to represent wetland–groundwater–upland interactions with varying levels of system and computational complexity. We perform a series of numerical experiments informed by field observations from a particular type of wetland, called a fen, at the well-instrumented White Gull Creek in Saskatchewan, in the boreal region of North America. In this study, we focus on how modifying the modelling connection between the upland and the wetland affects the system's outcome. We demonstrate that the typical representation of groundwater-dependent wetlands in LSMs, which ignores interactions with groundwater and uplands, can be inadequate. We show that the optimal level of model complexity depends on the land cover, soil type, and the ultimate modelling purpose, being nowcasting and prediction, scenario analysis, or diagnostic learning.
{"title":"On the optimal level of complexity for the representation of groundwater-dependent wetland systems in land surface models","authors":"Mennatullah T. Elrashidy, A. Ireson, Saman Razavi","doi":"10.5194/hess-27-4595-2023","DOIUrl":"https://doi.org/10.5194/hess-27-4595-2023","url":null,"abstract":"Abstract. Wetland systems are among the largest stores of carbon on the planet, the most biologically diverse of all ecosystems, and dominant controls on the hydrologic cycle. However, their representation in land surface models (LSMs), which are the terrestrial lower boundary of Earth system models (ESMs) that inform climate actions, is limited. Here, we explore different possible parameterizations to represent wetland–groundwater–upland interactions with varying levels of system and computational complexity. We perform a series of numerical experiments informed by field observations from a particular type of wetland, called a fen, at the well-instrumented White Gull Creek in Saskatchewan, in the boreal region of North America. In this study, we focus on how modifying the modelling connection between the upland and the wetland affects the system's outcome. We demonstrate that the typical representation of groundwater-dependent wetlands in LSMs, which ignores interactions with groundwater and uplands, can be inadequate. We show that the optimal level of model complexity depends on the land cover, soil type, and the ultimate modelling purpose, being nowcasting and prediction, scenario analysis, or diagnostic learning.\u0000","PeriodicalId":13143,"journal":{"name":"Hydrology and Earth System Sciences","volume":"3 8","pages":""},"PeriodicalIF":6.3,"publicationDate":"2023-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138944879","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 : 2023-12-20DOI: 10.5194/hess-27-4505-2023
Bich Tran, Johannes van der Kwast, S. Seyoum, R. Uijlenhoet, G. Jewitt, M. Mul
Abstract. Satellite remote sensing (RS) data are increasingly being used to estimate total evaporation, often referred to as evapotranspiration (ET), over large regions. Since RS-based ET (RS-ET) estimation inherits uncertainties from several sources, many available studies have assessed these uncertainties using different methods. However, the suitability of methods and reference data subsequently affects the validity of these evaluations. This study summarizes the status of the various methods applied for uncertainty assessment of RS-ET estimates, discusses the advances and caveats of these methods, identifies assessment gaps, and provides recommendations for future studies. We systematically reviewed 676 research papers published from 2011 to 2021 that assessed the uncertainty or accuracy of RS-ET estimates. We categorized and classified them based on (i) the methods used to assess uncertainties, (ii) the context where uncertainties were evaluated, and (iii) the metrics used to report uncertainties. Our quantitative synthesis shows that the uncertainty assessments of RS-ET estimates are not consistent and comparable in terms of methodology, reference data, geographical distribution, and uncertainty presentation. Most studies used validation methods using eddy-covariance (EC)-based ET estimates as a reference. However, in many regions such as Africa and the Middle East, other references are often used due to the lack of EC stations. The accuracy and uncertainty of RS-ET estimates are most often described by root-mean-squared errors (RMSEs). When validating against EC-based estimates, the RMSE of daily RS-ET varies greatly among different locations and levels of temporal support, ranging from 0.01 to 6.65 mm d−1, with a mean of 1.18 mm d−1. We conclude that future studies need to report the context of validation, the uncertainty of the reference datasets, the mismatch in the temporal and spatial scales of reference datasets to those of the RS-ET estimates, and multiple performance metrics with their variation in different conditions and their statistical significance to provide a comprehensive interpretation to assist potential users. We provide specific recommendations in this regard. Furthermore, extending the application of RS-ET to regions that lack validation will require obtaining additional ground-based data and combining different methods for uncertainty assessment.
{"title":"Uncertainty assessment of satellite remote-sensing-based evapotranspiration estimates: a systematic review of methods and gaps","authors":"Bich Tran, Johannes van der Kwast, S. Seyoum, R. Uijlenhoet, G. Jewitt, M. Mul","doi":"10.5194/hess-27-4505-2023","DOIUrl":"https://doi.org/10.5194/hess-27-4505-2023","url":null,"abstract":"Abstract. Satellite remote sensing (RS) data are increasingly being used to estimate total evaporation, often referred to as evapotranspiration (ET), over large regions. Since RS-based ET (RS-ET) estimation inherits uncertainties from several sources, many available studies have assessed these uncertainties using different methods. However, the suitability of methods and reference data subsequently affects the validity of these evaluations. This study summarizes the status of the various methods applied for uncertainty assessment of RS-ET estimates, discusses the advances and caveats of these methods, identifies assessment gaps, and provides recommendations for future studies. We systematically reviewed 676 research papers published from 2011 to 2021 that assessed the uncertainty or accuracy of RS-ET estimates. We categorized and classified them based on (i) the methods used to assess uncertainties, (ii) the context where uncertainties were evaluated, and (iii) the metrics used to report uncertainties. Our quantitative synthesis shows that the uncertainty assessments of RS-ET estimates are not consistent and comparable in terms of methodology, reference data, geographical distribution, and uncertainty presentation. Most studies used validation methods using eddy-covariance (EC)-based ET estimates as a reference. However, in many regions such as Africa and the Middle East, other references are often used due to the lack of EC stations. The accuracy and uncertainty of RS-ET estimates are most often described by root-mean-squared errors (RMSEs). When validating against EC-based estimates, the RMSE of daily RS-ET varies greatly among different locations and levels of temporal support, ranging from 0.01 to 6.65 mm d−1, with a mean of 1.18 mm d−1. We conclude that future studies need to report the context of validation, the uncertainty of the reference datasets, the mismatch in the temporal and spatial scales of reference datasets to those of the RS-ET estimates, and multiple performance metrics with their variation in different conditions and their statistical significance to provide a comprehensive interpretation to assist potential users. We provide specific recommendations in this regard. Furthermore, extending the application of RS-ET to regions that lack validation will require obtaining additional ground-based data and combining different methods for uncertainty assessment.\u0000","PeriodicalId":13143,"journal":{"name":"Hydrology and Earth System Sciences","volume":"4 2","pages":""},"PeriodicalIF":6.3,"publicationDate":"2023-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138956876","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 : 2023-12-20DOI: 10.5194/hess-27-4551-2023
Haiyang Shi, Geping Luo, O. Hellwich, Xiufeng He, A. Kurban, Philippe De Maeyer, T. van de Voorde
Abstract. In the context of global warming, an increase in atmospheric aridity and global dryland expansion under the future climate has been expected in previous studies. However, this conflicts with observed greening over drylands and the insignificant increase in hydrological and ecological aridity from the ecohydrology perspective. Combining climatic, hydrological, and vegetation data, this study evaluated global dryland aridity changes at meteorological stations from 2003 to 2019. A decoupling between atmospheric, hydrological, and vegetation aridity was found. Atmospheric aridity represented by the vapor pressure deficit (VPD) increased, hydrological aridity indicated by machine-learning-based precipitation minus evapotranspiration (P − ET) data did not change significantly, and ecological aridity represented by the leaf area index (LAI) decreased. P − ET showed nonsignificant changes in most of the dominant combinations of the VPD, LAI, and P − ET. This study highlights the added value of using station-scale data to assess dryland change as a complement to results based on coarse-resolution reanalysis data and land surface models.
摘要在全球变暖的背景下，以往的研究预计未来气候下大气干旱度会增加，全球旱地会扩大。然而，这与观测到的旱地绿化以及从生态水文学角度看水文和生态干旱的显著增加相矛盾。本研究结合气候、水文和植被数据，评估了 2003 年至 2019 年气象站的全球旱地干旱度变化。研究发现，大气干旱度、水文干旱度和植被干旱度之间存在脱钩现象。以水汽压差（VPD）表示的大气干旱度增加了，以基于机器学习的降水量减去蒸散量（P - ET）数据表示的水文干旱度没有显著变化，而以叶面积指数（LAI）表示的生态干旱度降低了。在大多数 VPD、LAI 和 P - ET 的主要组合中，P - ET 的变化并不明显。这项研究强调了利用站点尺度数据评估旱地变化的附加价值，是对基于粗分辨率再分析数据和陆地表面模型结果的补充。
{"title":"Global dryland aridity changes indicated by atmospheric, hydrological, and vegetation observations at meteorological stations","authors":"Haiyang Shi, Geping Luo, O. Hellwich, Xiufeng He, A. Kurban, Philippe De Maeyer, T. van de Voorde","doi":"10.5194/hess-27-4551-2023","DOIUrl":"https://doi.org/10.5194/hess-27-4551-2023","url":null,"abstract":"Abstract. In the context of global warming, an increase in atmospheric aridity and global dryland expansion under the future climate has been expected in previous studies. However, this conflicts with observed greening over drylands and the insignificant increase in hydrological and ecological aridity from the ecohydrology perspective. Combining climatic, hydrological, and vegetation data, this study evaluated global dryland aridity changes at meteorological stations from 2003 to 2019. A decoupling between atmospheric, hydrological, and vegetation aridity was found. Atmospheric aridity represented by the vapor pressure deficit (VPD) increased, hydrological aridity indicated by machine-learning-based precipitation minus evapotranspiration (P − ET) data did not change significantly, and ecological aridity represented by the leaf area index (LAI) decreased. P − ET showed nonsignificant changes in most of the dominant combinations of the VPD, LAI, and P − ET. This study highlights the added value of using station-scale data to assess dryland change as a complement to results based on coarse-resolution reanalysis data and land surface models.\u0000","PeriodicalId":13143,"journal":{"name":"Hydrology and Earth System Sciences","volume":"11 2","pages":""},"PeriodicalIF":6.3,"publicationDate":"2023-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138994316","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 : 2023-12-20DOI: 10.5194/hess-27-4453-2023
Tao Zhang, Qinhong Hu, B. Ghanbarian, Derek Elsworth, Zhiming Lu
Abstract. Nanodarcy level permeability measurements of porous media, such as nano-porous mudrocks, are frequently conducted with gas invasion methods into granular-sized samples with short diffusion lengths and thereby reduced experimental duration; however, these methods lack rigorous solutions and standardized experimental procedures. For the first time, we resolve this by providing an integrated technique (termed gas permeability technique, GPT) with coupled theoretical development, experimental procedures, and data interpretation workflow. Three exact mathematical solutions for transient and slightly compressible spherical flow, along with their asymptotic solutions, are developed for early- and late-time responses. Critically, one late-time solution is for an ultra-small gas-invadable volume, important for a wide range of practical usages. Developed to be applicable to different sample characteristics (permeability, porosity, and mass) in relation to the storage capacity of experimental systems, these three solutions are evaluated from essential considerations of error difference between exact and approximate solutions, optimal experimental conditions, and experimental demonstration of mudrocks and molecular-sieve samples. Moreover, a practical workflow of solution selection and data reduction to determine permeability is presented by considering samples with different permeability and porosity under various granular sizes. Overall, this work establishes a rigorous, theory-based, rapid, and versatile gas permeability measurement technique for tight media at sub-nanodarcy levels.
{"title":"A pulse-decay method for low (matrix) permeability analyses of granular rock media","authors":"Tao Zhang, Qinhong Hu, B. Ghanbarian, Derek Elsworth, Zhiming Lu","doi":"10.5194/hess-27-4453-2023","DOIUrl":"https://doi.org/10.5194/hess-27-4453-2023","url":null,"abstract":"Abstract. Nanodarcy level permeability measurements of porous media, such as nano-porous mudrocks, are frequently conducted with gas invasion methods into granular-sized samples with short diffusion lengths and thereby reduced experimental duration; however, these methods lack rigorous solutions and standardized experimental procedures. For the first time, we resolve this by providing an integrated technique (termed gas permeability technique, GPT) with coupled theoretical development, experimental procedures, and data interpretation workflow. Three exact mathematical solutions for transient and slightly compressible spherical flow, along with their asymptotic solutions, are developed for early- and late-time responses. Critically, one late-time solution is for an ultra-small gas-invadable volume, important for a wide range of practical usages. Developed to be applicable to different sample characteristics (permeability, porosity, and mass) in relation to the storage capacity of experimental systems, these three solutions are evaluated from essential considerations of error difference between exact and approximate solutions, optimal experimental conditions, and experimental demonstration of mudrocks and molecular-sieve samples. Moreover, a practical workflow of solution selection and data reduction to determine permeability is presented by considering samples with different permeability and porosity under various granular sizes. Overall, this work establishes a rigorous, theory-based, rapid, and versatile gas permeability measurement technique for tight media at sub-nanodarcy levels.\u0000","PeriodicalId":13143,"journal":{"name":"Hydrology and Earth System Sciences","volume":"3 1","pages":""},"PeriodicalIF":6.3,"publicationDate":"2023-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138956888","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 : 2023-12-20DOI: 10.5194/hess-27-4485-2023
S. Azimi, C. Massari, G. Formetta, S. Barbetta, A. Tazioli, Davide Fronzi, S. Modanesi, A. Tarpanelli, Riccardo Rigon
Abstract. The study aims to demonstrate that an effective solution can be implemented for modeling complex carbonate basins, in the situation of limited data availability. Considering the alternative modeling approaches under circumstances of data shortage is more significant knowing the vulnerability and effectiveness of these kinds of basins to drought and climate change conditions. In this regard, a hybrid approach that combines time series analysis and reservoir modeling is proposed to describe behavior in carbonate basins. Time series analysis estimates the contributing area and response time of the fractured carbonate system beyond the catchment's hydrographic boundaries. The results obtained align with previous literature-based field surveys. This information is then used to develop a conceptual reservoir system using the GEOframe modeling system. The model is validated using in situ discharge observations and Earth observations (EO) data on evapotranspiration and snow. Model reliability is assessed using traditional goodness of fit indicators, hydrological signatures, and a novel statistical method based on empirical conditional probability. This approach enables detailed analysis and investigation of water budget components in Mediterranean carbonate catchments, highlighting their response to significant precipitation deficits. Overall, our results demonstrate that flows from carbonate rock areas outside the hydrographic boundaries significantly impact the water budget of the upper Nera River. The storage capacity of the carbonate basin plays a crucial role in sustaining river discharge during drought years. In a single dry year, meteorological drought is considerably attenuated, while in subsequent dry years, it is slightly intensified. Multi-year droughts result in slower recovery due to the time required for precipitation to replenish the depleted storage that supported river discharge in previous dry years. This unique behavior makes these basins particularly vulnerable to the more severe and frequent drought episodes expected under future climate change.
{"title":"On understanding mountainous carbonate basins of the Mediterranean using parsimonious modeling solutions","authors":"S. Azimi, C. Massari, G. Formetta, S. Barbetta, A. Tazioli, Davide Fronzi, S. Modanesi, A. Tarpanelli, Riccardo Rigon","doi":"10.5194/hess-27-4485-2023","DOIUrl":"https://doi.org/10.5194/hess-27-4485-2023","url":null,"abstract":"Abstract. The study aims to demonstrate that an effective solution can be implemented for modeling complex carbonate basins, in the situation of limited data availability. Considering the alternative modeling approaches under circumstances of data shortage is more significant knowing the vulnerability and effectiveness of these kinds of basins to drought and climate change conditions. In this regard, a hybrid approach that combines time series analysis and reservoir modeling is proposed to describe behavior in carbonate basins. Time series analysis estimates the contributing area and response time of the fractured carbonate system beyond the catchment's hydrographic boundaries. The results obtained align with previous literature-based field surveys. This information is then used to develop a conceptual reservoir system using the GEOframe modeling system. The model is validated using in situ discharge observations and Earth observations (EO) data on evapotranspiration and snow. Model reliability is assessed using traditional goodness of fit indicators, hydrological signatures, and a novel statistical method based on empirical conditional probability. This approach enables detailed analysis and investigation of water budget components in Mediterranean carbonate catchments, highlighting their response to significant precipitation deficits. Overall, our results demonstrate that flows from carbonate rock areas outside the hydrographic boundaries significantly impact the water budget of the upper Nera River. The storage capacity of the carbonate basin plays a crucial role in sustaining river discharge during drought years. In a single dry year, meteorological drought is considerably attenuated, while in subsequent dry years, it is slightly intensified. Multi-year droughts result in slower recovery due to the time required for precipitation to replenish the depleted storage that supported river discharge in previous dry years. This unique behavior makes these basins particularly vulnerable to the more severe and frequent drought episodes expected under future climate change.\u0000","PeriodicalId":13143,"journal":{"name":"Hydrology and Earth System Sciences","volume":"22 18","pages":""},"PeriodicalIF":6.3,"publicationDate":"2023-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138955247","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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