Pub Date : 2023-08-09DOI: 10.5194/hess-27-2935-2023
S. Ulzega, Carlo Albert
Abstract. Stochastic models in hydrology are very useful and widespread tools for making reliable probabilistic predictions. However, such models are only accurate at making predictions if model parameters are first of all calibrated to measured data in a consistent framework such as the Bayesian one, in which knowledge about model parameters is described through probability distributions. Unfortunately, Bayesian parameter calibration, a. k. a. inference, with stochastic models, is often a computationally intractable problem with traditional inference algorithms, such as the Metropolis algorithm, due to the expensive likelihood functions. Therefore, the prohibitive computational cost is often overcome by employing over-simplified error models, which leads to biased parameter estimates and unreliable predictions. However, thanks to recent advancements in algorithms and computing power, fully fledged Bayesian inference with stochastic models is no longer off-limits for hydrological applications. Our goal in this work is to demonstrate that a computationally efficient Hamiltonian Monte Carlo algorithm with a timescale separation makes Bayesian parameter inference with stochastic models feasible. Hydrology can potentially take great advantage of this powerful data-driven inference method as a sound calibration of model parameters is essential for making robust probabilistic predictions, which can certainly be useful in planning and policy-making. We demonstrate the Hamiltonian Monte Carlo approach by detailing a case study from urban hydrology. Discussing specific hydrological models or systems is outside the scope of our present work and will be the focus of further studies.
{"title":"Bayesian parameter inference in hydrological modelling using a Hamiltonian Monte Carlo approach with a stochastic rain model","authors":"S. Ulzega, Carlo Albert","doi":"10.5194/hess-27-2935-2023","DOIUrl":"https://doi.org/10.5194/hess-27-2935-2023","url":null,"abstract":"Abstract. Stochastic models in hydrology are very useful and widespread tools for making reliable probabilistic predictions. However, such models are only accurate at making predictions if model parameters are first of all calibrated to measured data in a consistent framework such as the Bayesian one, in which knowledge about model parameters is described through probability distributions. Unfortunately, Bayesian parameter calibration, a. k. a. inference, with stochastic models, is often a computationally intractable problem with traditional inference algorithms, such as the Metropolis algorithm, due to the expensive likelihood functions. Therefore, the prohibitive computational cost is often overcome by employing over-simplified error models, which leads to biased parameter estimates and unreliable predictions. However, thanks to recent advancements in algorithms and computing power, fully fledged Bayesian inference with stochastic models is no longer off-limits for hydrological applications.\u0000Our goal in this work is to demonstrate that a computationally efficient Hamiltonian Monte Carlo algorithm with a timescale separation makes Bayesian parameter inference with stochastic models feasible. Hydrology can potentially take great advantage of this powerful data-driven inference method as a sound calibration of model parameters is essential for making robust probabilistic predictions, which can certainly be useful in planning and policy-making. We demonstrate the Hamiltonian Monte Carlo approach by detailing a case study from urban hydrology. Discussing specific hydrological models or systems is outside the scope of our present work and will be the focus of further studies.\u0000","PeriodicalId":13143,"journal":{"name":"Hydrology and Earth System Sciences","volume":" ","pages":""},"PeriodicalIF":6.3,"publicationDate":"2023-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48739510","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}
Abstract. Accurate snowpack simulations are critical for regional hydrological predictions, snow avalanche prevention, water resource management, and agricultural production, particularly during the snow ablation period. Data assimilation methodologies are increasingly being applied for operational purposes to reduce the uncertainty in snowpack simulations and to enhance their predictive capabilities. This study aims to investigate the feasibility of using a genetic particle filter (GPF) as a snow data assimilation scheme designed to assimilate ground-based snow depth (SD) measurements across different snow climates. We employed the default parameterization scheme combination within the Noah-MP (with multi-parameterization) model as the model operator in the snow data assimilation system to evolve snow variables and evaluated the assimilation performance of the GPF using observational data from sites with different snow climates. We also explored the impact of measurement frequency and particle number on the filter updating of the snowpack state at different sites and the results of generic resampling methods compared to the genetic algorithm used in the resampling process. Our results demonstrate that a GPF can be used as a snow data assimilation scheme to assimilate ground-based measurements and obtain satisfactory assimilation performance across different snow climates. We found that particle number is not crucial for the filter's performance, and 100 particles are sufficient to represent the high dimensionality of the point-scale system. The frequency of measurements can significantly affect the filter-updating performance, and dense ground-based snow observational data always dominate the accuracy of assimilation results. Compared to generic resampling methods, the genetic algorithm used to resample particles can significantly enhance the diversity of particles and prevent particle degeneration and impoverishment. Finally, we concluded that the GPF is a suitable candidate approach for snow data assimilation and is appropriate for different snow climates.
{"title":"A genetic particle filter scheme for univariate snow cover assimilation into Noah-MP model across snow climates","authors":"Yuanhong You, Chunlin Huang, Zuo Wang, Jinliang Hou, Ying Zhang, Peipei Xu","doi":"10.5194/hess-27-2919-2023","DOIUrl":"https://doi.org/10.5194/hess-27-2919-2023","url":null,"abstract":"Abstract. Accurate snowpack simulations are critical for regional hydrological predictions, snow avalanche prevention, water resource management, and agricultural production, particularly during the snow ablation period. Data assimilation methodologies are increasingly being applied for operational purposes to reduce the uncertainty in snowpack simulations and to enhance their predictive capabilities. This study aims to investigate the feasibility of using a genetic particle filter (GPF) as a snow data assimilation scheme designed to assimilate ground-based snow depth (SD) measurements across different snow climates. We employed the default parameterization scheme combination within the Noah-MP (with multi-parameterization) model as the model operator in the snow data assimilation system to evolve snow variables and evaluated the assimilation performance of the GPF using observational data from sites with different snow climates. We also explored the impact of measurement frequency and particle number on the filter updating of the snowpack state at different sites and the results of generic resampling methods compared to the genetic algorithm used in the resampling process. Our results demonstrate that a GPF can be used as a snow data assimilation scheme to assimilate ground-based measurements and obtain satisfactory assimilation performance across different snow climates. We found that particle number is not crucial for the filter's performance, and 100 particles are sufficient to represent the high dimensionality of the point-scale system. The frequency of measurements can significantly affect the filter-updating performance, and dense ground-based snow observational data always dominate the accuracy of assimilation results. Compared to generic resampling methods, the genetic algorithm used to resample particles can significantly enhance the diversity of particles and prevent particle degeneration and impoverishment. Finally, we concluded that the GPF is a suitable candidate approach for snow data assimilation and is appropriate for different snow climates.","PeriodicalId":13143,"journal":{"name":"Hydrology and Earth System Sciences","volume":" ","pages":""},"PeriodicalIF":6.3,"publicationDate":"2023-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45454341","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-02DOI: 10.5194/hess-27-2883-2023
Emily I. Burt, Daxs Herson Coayla Rimachi, Adan J. Ccahuana Quispe, Abra Atwood, A. West
Abstract. The role of topography in determining water transit times and pathways through catchments is unclear, especially in mountainous environments – yet these environments play central roles in global water, sediment, and biogeochemical fluxes. Since the vast majority of intensively monitored catchments are at northern latitudes, the interplay between water transit, topography, and other landscape and climatic characteristics is particularly underexplored in tropical environments. To address this gap, here we present the results of a multiyear hydrologic sampling campaign (twice-monthly and storm sampling) to quantify water transit in seven small catchments (<1.3 km2 area) across the transition from the Andes mountains to the Amazon floodplain in southern Peru. We use the stable isotope composition of water (δ18O) to calculate the fraction of streamflow comprised of recent precipitation (“young water fraction”) for each of the seven small catchments. Flow-weighted young water fractions (Fyw) are 5 %–26 % in the high-elevation mountains, 22 %–52 % in the mid-elevation mountains, and 7 % in the foreland floodplain. Across these catchments, topography does not exert a clear control on water transit; instead, stream Fyw is apparently controlled by a combination of hydroclimate (precipitation regime) and bedrock permeability. Mid-elevation sites are posited to have the highest Fyw due to more frequent and intense rainfall; less permeable bedrock and poorly developed soils may also facilitate high Fyw at these sites. Lowland soils have low Fyw due to very low flow path gradients despite low permeability. The data presented here highlight the complexity of factors that determine water transit in tropical mountainous catchments, particularly highlighting the role of intense orographic precipitation at mountain fronts in driving rapid conveyance of water through catchments. These results have implications for the response of Earth's montane “water towers” to climate change and for water–rock reactions that control global biogeochemical cycles.
{"title":"Isotope-derived young water fractions in streamflow across the tropical Andes mountains and Amazon floodplain","authors":"Emily I. Burt, Daxs Herson Coayla Rimachi, Adan J. Ccahuana Quispe, Abra Atwood, A. West","doi":"10.5194/hess-27-2883-2023","DOIUrl":"https://doi.org/10.5194/hess-27-2883-2023","url":null,"abstract":"Abstract. The role of topography in determining water transit times and pathways\u0000through catchments is unclear, especially in mountainous environments\u0000– yet these environments play central roles in global water, sediment, and\u0000biogeochemical fluxes. Since the vast majority of intensively monitored\u0000catchments are at northern latitudes, the interplay between water transit,\u0000topography, and other landscape and climatic characteristics is particularly\u0000underexplored in tropical environments. To address this gap, here we present\u0000the results of a multiyear hydrologic sampling campaign (twice-monthly and\u0000storm sampling) to quantify water transit in seven small catchments\u0000(<1.3 km2 area) across the transition from the Andes mountains\u0000to the Amazon floodplain in southern Peru. We use the stable isotope\u0000composition of water (δ18O) to calculate the fraction of\u0000streamflow comprised of recent precipitation (“young water fraction”) for\u0000each of the seven small catchments. Flow-weighted young water fractions\u0000(Fyw) are 5 %–26 % in the high-elevation mountains, 22 %–52 % in the mid-elevation mountains, and 7 % in the foreland floodplain. Across these\u0000catchments, topography does not exert a clear control on water transit;\u0000instead, stream Fyw is apparently controlled by a combination of\u0000hydroclimate (precipitation regime) and bedrock permeability. Mid-elevation\u0000sites are posited to have the highest Fyw due to more frequent and\u0000intense rainfall; less permeable bedrock and poorly developed soils may also\u0000facilitate high Fyw at these sites. Lowland soils have low Fyw due\u0000to very low flow path gradients despite low permeability. The data presented\u0000here highlight the complexity of factors that determine water transit in\u0000tropical mountainous catchments, particularly highlighting the role of\u0000intense orographic precipitation at mountain fronts in driving rapid\u0000conveyance of water through catchments. These results have implications for\u0000the response of Earth's montane “water towers” to climate change and for\u0000water–rock reactions that control global biogeochemical cycles.\u0000","PeriodicalId":13143,"journal":{"name":"Hydrology and Earth System Sciences","volume":" ","pages":""},"PeriodicalIF":6.3,"publicationDate":"2023-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45350534","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-02DOI: 10.5194/hess-27-2899-2023
C. Fischer‐Bedtke, J. C. Metzger, Gokben Demir, T. Wutzler, A. Hildebrandt
Abstract. Throughfall heterogeneity induced by the redistribution of precipitation in vegetation canopies has repeatedly been hypothesized to affect the variation in the soil water content and runoff behavior, especially in forests. However, observational studies relating the spatial variation in the soil water content directly to net precipitation are rare, and few confirm modeling hypotheses. Here, we investigate whether throughfall patterns affect the spatial heterogeneity in the soil water response in the main rooting zone. We assessed rainfall, throughfall and soil water content (at two depths, 7.5 and 27.5 cm) on a 1 ha temperate mixed-beech forest plot in Germany during the 2015 and 2016 growing seasons using independent, high-resolution, stratified, random designs. Because the throughfall and soil water content cannot be measured at the same location, we used kriging to derive the throughfall values at the locations where the soil water content was measured. We first explored the spatial variation and temporal stability of throughfall and soil water patterns and subsequently evaluated the effects of input (throughfall), soil properties (field capacity and macroporosity), and vegetation parameters (canopy cover and distance to the next tree) on the soil water content and dynamics. Throughfall spatial patterns were related to canopy density. Although spatial autocorrelation decreased with increasing event sizes, temporally stable throughfall patterns emerged, leading to reoccurring higher- and lower-input locations across precipitation events. Linear mixed-effects model analysis showed that soil water content patterns were poorly related to spatial patterns of throughfall and that they were more influenced by unidentified, but time constant, factors. Instead of the soil water content itself, the patterns of its increase after rainfall corresponded more closely to throughfall patterns: more water was stored in the soil in areas where throughfall was elevated. Furthermore, soil moisture patterns themselves affected the local soil water response, probably by mediating fast drainage and runoff. Locations with a low topsoil water content tended to store less of the input water, indicating preferential flow. In contrast, locations with a high water content stored less water in the subsoil. Moreover, the distance to the next tree and macroporosity modified how much water was retained in soil storage. Overall, throughfall patterns imprinted less on the soil water content and more on the soil water dynamics shortly after rainfall events; therefore, percolation rather than the soil water content may depend on the small-scale spatial heterogeneity in canopy input patterns.
{"title":"Throughfall spatial patterns translate into spatial patterns of soil moisture dynamics – empirical evidence","authors":"C. Fischer‐Bedtke, J. C. Metzger, Gokben Demir, T. Wutzler, A. Hildebrandt","doi":"10.5194/hess-27-2899-2023","DOIUrl":"https://doi.org/10.5194/hess-27-2899-2023","url":null,"abstract":"Abstract. Throughfall heterogeneity induced by the redistribution\u0000of precipitation in vegetation canopies has repeatedly been hypothesized to\u0000affect the variation in the soil water content and runoff behavior, especially\u0000in forests. However, observational studies relating the spatial variation in the\u0000soil water content directly to net precipitation are rare, and few confirm\u0000modeling hypotheses. Here, we investigate whether throughfall patterns\u0000affect the spatial heterogeneity in the soil water response in the main rooting\u0000zone. We assessed rainfall, throughfall and soil water content (at two depths,\u00007.5 and 27.5 cm) on a 1 ha temperate mixed-beech forest plot in Germany\u0000during the 2015 and 2016 growing seasons using independent, high-resolution,\u0000stratified, random designs. Because the throughfall and soil water content cannot\u0000be measured at the same location, we used kriging to derive the throughfall\u0000values at the locations where the soil water content was measured. We first\u0000explored the spatial variation and temporal stability of throughfall and soil\u0000water patterns and subsequently evaluated the effects of input (throughfall), soil\u0000properties (field capacity and macroporosity), and vegetation parameters\u0000(canopy cover and distance to the next tree) on the soil water content and\u0000dynamics. Throughfall spatial patterns were related to canopy density. Although\u0000spatial autocorrelation decreased with increasing event sizes, temporally\u0000stable throughfall patterns emerged, leading to reoccurring higher- and lower-input locations across precipitation events. Linear mixed-effects model\u0000analysis showed that soil water content patterns were poorly related to\u0000spatial patterns of throughfall and that they were more influenced by unidentified,\u0000but time constant, factors. Instead of the soil water content itself, the patterns of its increase after\u0000rainfall corresponded more closely to throughfall patterns: more\u0000water was stored in the soil in areas where throughfall was elevated. Furthermore, soil moisture patterns themselves affected the local soil water response, probably by mediating fast drainage and runoff. Locations with a low\u0000topsoil water content tended to store less of the input water, indicating\u0000preferential flow. In contrast, locations with a high water content\u0000stored less water in the subsoil. Moreover, the distance to the next tree and macroporosity\u0000modified how much water was retained in soil storage. Overall, throughfall\u0000patterns imprinted less on the soil water content and more on the soil water\u0000dynamics shortly after rainfall events; therefore, percolation rather than the\u0000soil water content may depend on the small-scale spatial heterogeneity in canopy\u0000input patterns.\u0000","PeriodicalId":13143,"journal":{"name":"Hydrology and Earth System Sciences","volume":" ","pages":""},"PeriodicalIF":6.3,"publicationDate":"2023-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45127920","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-01DOI: 10.5194/hess-27-2865-2023
J. Pinos, M. Flury, J. Latron, P. Llorens
Abstract. Stemflow and its belowground funnelling along roots and macropores may play an important role in the soil moisture redistribution in forest environments. In this study, a stemflow experiment on Pinus sylvestris L. (Scots pine) used artificial tracers to view and quantify preferential flow after stemflow infiltration into the soil. A total of 41 L of water labelled with enriched deuterium and brilliant blue FCF were applied at a flow rate of 7 L h−1 to the stem of a pine tree, which corresponds to the stemflow caused by about 50 mm of rainfall. Time domain reflectometry (TDR) probes were installed around the tree trunk to measure the high-resolution volumetric water content. A total of 1 d after the stemflow discharge, soil pits were dug in the different cardinal directions and at varying distances from the tree. Photographs were taken for imaging analysis to quantify preferential flow metrics. Soil samples were taken from the different profiles to analyse the dye concentrations and isotopic compositions. We found that stemflow infiltrated through an annulus-shaped area around the tree base. We observed a heterogenous spatiotemporal soil moisture response to stemflow and the occurrence of shallow perched water tables around the tree trunk. Dye staining demonstrated that stemflow infiltrated primarily along the surface of coarse roots and through macropores. The dye coverage was less extensive close to the soil surface and increased with depth and with proximity to the tree trunk. Lateral flow was also observed, mainly in the shallow soil layers. Our analyses demonstrate the prevalence of preferential flow. Deuterium and brilliant blue FCF concentrations were significantly correlated. The tracer concentrations decreased with increasing distance from the tree trunk, indicating dilution and mixing with residual soil water. Macropores, coarse roots (living or decayed) and perched water tables produced a complex network regulating the preferential flow. Our results suggest that stemflow affects soil moisture distribution, and thus likely also groundwater recharge and surface runoff. Our study provides insights into the soil hydrological processes that are regulated by stemflow belowground funnelling and improves our understanding of forest–water interactions.
摘要在森林环境下，茎流及其沿根和大孔的地下漏斗可能在土壤水分再分配中起重要作用。本研究采用人工示踪剂对松木茎流进行试验，观察和量化其茎流入渗土壤后的优先流量。用浓缩氘和亮蓝色FCF标记的41 L水以7 L h−1的流速作用于松树的茎干，这相当于约50 mm降雨引起的茎流。在树干周围安装时域反射(TDR)探针，测量高分辨率的体积含水量。在茎流排出1 d后，在不同的基本方向和离树的不同距离上挖土坑。拍摄照片进行成像分析，以量化优先流量指标。从不同剖面提取土壤样本，分析染料浓度和同位素组成。我们发现茎流通过树基部周围的环形区域渗透。我们观察到土壤水分对茎流和树干周围浅栖息水位的时空响应具有异质性。染料染色表明茎流主要沿粗根表面和大孔渗透。接近土壤表面的染料覆盖度较低，随着深度和接近树干而增加。还观察到横向流动，主要在浅层土层。我们的分析证明了优惠流动的普遍存在。氘浓度与亮蓝色FCF浓度呈显著相关。示踪剂浓度随离树干距离的增加而降低，表明与土壤残馀水的稀释和混合。大孔、粗根(活着的或腐烂的)和悬空的地下水位形成了一个复杂的网络来调节优先流动。我们的研究结果表明，茎流影响土壤水分分布，因此可能也影响地下水补给和地表径流。我们的研究提供了对土壤水文过程的见解，土壤水文过程是由地下漏斗的茎流调节的，并提高了我们对森林-水相互作用的理解。
{"title":"Routing stemflow water through the soil via preferential flow: a dual-labelling approach with artificial tracers","authors":"J. Pinos, M. Flury, J. Latron, P. Llorens","doi":"10.5194/hess-27-2865-2023","DOIUrl":"https://doi.org/10.5194/hess-27-2865-2023","url":null,"abstract":"Abstract. Stemflow and its belowground funnelling along roots and macropores may play an important role in the soil moisture redistribution in forest environments. In this study, a stemflow experiment on Pinus sylvestris L. (Scots pine) used artificial tracers to view and quantify preferential flow after stemflow infiltration into the soil. A total of 41 L of water labelled with enriched deuterium and brilliant blue FCF were applied at a flow rate of 7 L h−1 to the stem of a pine tree, which corresponds to the stemflow caused by about 50 mm of rainfall. Time domain reflectometry (TDR) probes were installed around the tree trunk to measure the high-resolution volumetric water content. A total of 1 d after the stemflow discharge, soil pits were dug in the different cardinal directions and at varying distances from the tree. Photographs were taken for imaging analysis to quantify preferential flow metrics. Soil samples were taken from the different profiles to analyse the dye concentrations and isotopic compositions. We found that stemflow infiltrated through an annulus-shaped area around the tree base. We observed a heterogenous spatiotemporal soil moisture response to stemflow and the occurrence of shallow perched water tables around the tree trunk. Dye staining demonstrated that stemflow infiltrated primarily along the surface of coarse roots and through macropores. The dye coverage was less extensive close to the soil surface and increased with depth and with proximity to the tree trunk. Lateral flow was also observed, mainly in the shallow soil layers. Our analyses demonstrate the prevalence of preferential flow. Deuterium and brilliant blue FCF concentrations were\u0000significantly correlated. The tracer concentrations decreased with increasing distance from the tree trunk, indicating dilution and mixing with residual soil water. Macropores, coarse roots (living or decayed) and\u0000perched water tables produced a complex network regulating the preferential\u0000flow. Our results suggest that stemflow affects soil moisture distribution,\u0000and thus likely also groundwater recharge and surface runoff. Our study\u0000provides insights into the soil hydrological processes that are regulated by stemflow belowground funnelling and improves our understanding of\u0000forest–water interactions.\u0000","PeriodicalId":13143,"journal":{"name":"Hydrology and Earth System Sciences","volume":" ","pages":""},"PeriodicalIF":6.3,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42684406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-01DOI: 10.5194/hess-27-2847-2023
R. Guo, A. Montanari
Abstract. Simulations of daily rainfall for the region of Bologna produced by 13 climate models for the period 1850–2100 are compared with the historical series of daily rainfall observed in Bologna for the period 1850–2014 and analysed to assess meteorological drought changes up to 2100. In particular, we focus on monthly and annual rainfall data, seasonality, and drought events to derive information on the future development of critical events for water resource availability. The results show that historical data analysis under the assumption of stationarity provides more precautionary predictions for long-term meteorological droughts with respect to climate model simulations, thereby outlining that information integration is key to obtaining technical indications.
{"title":"Historical rainfall data in northern Italy predict larger meteorological drought hazard than climate projections","authors":"R. Guo, A. Montanari","doi":"10.5194/hess-27-2847-2023","DOIUrl":"https://doi.org/10.5194/hess-27-2847-2023","url":null,"abstract":"Abstract. Simulations of daily rainfall for the region of Bologna produced by 13 climate models for the period 1850–2100 are compared with the historical series of daily rainfall observed in Bologna for the period 1850–2014 and analysed to assess meteorological drought changes up to 2100. In particular, we focus on monthly and annual rainfall data, seasonality, and drought events to derive information on the future development of critical events for water resource availability. The results show that historical data analysis under the assumption of stationarity provides more precautionary predictions for long-term meteorological droughts with respect to climate model simulations, thereby outlining that information integration is key to obtaining technical indications.\u0000","PeriodicalId":13143,"journal":{"name":"Hydrology and Earth System Sciences","volume":" ","pages":""},"PeriodicalIF":6.3,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46604202","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 : 2023-07-31DOI: 10.5194/hess-27-2827-2023
Tanja Denager, T. Sonnenborg, M. Looms, H. Bogena, K. Jensen
Abstract. This study evaluates water and energy fluxes and variables in combination with parameter optimization of version 5 of the state-of-the-art Community Land Model (CLM5) land surface model, using 6 years of hourly observations of latent heat flux, sensible heat flux, groundwater recharge, soil moisture and soil temperature from an agricultural observatory in Denmark. The results show that multi-objective calibration in combination with truncated singular value decomposition and Tikhonov regularization is a powerful method to improve the current practice of using lookup tables to define parameter values in land surface models. Using measurements of turbulent fluxes as the target variable, parameter optimization is capable of matching simulations and observations of latent heat, especially during the summer period, whereas simulated sensible heat is clearly biased. Of the 30 parameters considered, the soil texture, monthly leaf area index (LAI) in summer, stomatal conductance and root distribution have the highest influence on the local-scale simulation results. The results from this study contribute to improvements of the model characterization of water and energy fluxes. This work highlights the importance of performing parameter calibration using observations of hydrologic and energy fluxes and variables to obtain the optimal parameter values for a land surface model.
{"title":"Point-scale multi-objective calibration of the Community Land Model (version 5.0) using in situ observations of water and energy fluxes and variables","authors":"Tanja Denager, T. Sonnenborg, M. Looms, H. Bogena, K. Jensen","doi":"10.5194/hess-27-2827-2023","DOIUrl":"https://doi.org/10.5194/hess-27-2827-2023","url":null,"abstract":"Abstract. This study evaluates water and energy fluxes and variables in combination with parameter optimization of version 5 of the state-of-the-art Community Land Model (CLM5) land surface model, using 6 years of hourly\u0000observations of latent heat flux, sensible heat flux, groundwater recharge,\u0000soil moisture and soil temperature from an agricultural observatory in\u0000Denmark. The results show that multi-objective calibration in combination\u0000with truncated singular value decomposition and Tikhonov regularization is a powerful method to improve the current practice of using lookup tables to define parameter values in land surface models. Using measurements of\u0000turbulent fluxes as the target variable, parameter optimization is capable\u0000of matching simulations and observations of latent heat, especially during\u0000the summer period, whereas simulated sensible heat is clearly biased. Of the\u000030 parameters considered, the soil texture, monthly leaf area index (LAI) in summer, stomatal\u0000conductance and root distribution have the highest influence on the\u0000local-scale simulation results. The results from this study contribute to\u0000improvements of the model characterization of water and energy fluxes. This work highlights the importance of performing parameter calibration using\u0000observations of hydrologic and energy fluxes and variables to obtain the optimal parameter values for a land surface model.\u0000","PeriodicalId":13143,"journal":{"name":"Hydrology and Earth System Sciences","volume":" ","pages":""},"PeriodicalIF":6.3,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49056050","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 : 2023-07-28DOI: 10.5194/hess-27-2807-2023
S. Talke, D. Jay, H. Diefenderfer
Abstract. Using archival research methods, we recovered and combined data from multiple sources to produce a unique, 140-year record of daily water temperature (Tw) in the lower Willamette River, Oregon (1881–1890, 1941–present). Additional daily weather and river flow records from the 1850s onwards are used to develop and validate a statistical regression model of Tw for 1850–2020. The model simulates the time-lagged response of Tw to air temperature and river flow and is calibrated for three distinct time periods: the late 19th, mid-20th, and early 21st centuries. Results show that Tw has trended upwards at 1.1 ∘C per century since the mid-19th century, with the largest shift in January and February (1.3 ∘C per century) and the smallest in May and June (∼ 0.8 ∘C per century). The duration that the river exceeds the ecologically important threshold of 20 ∘C has increased by about 20 d since the 1800s, to about 60 d yr−1. Moreover, cold-water days below 2 ∘C have virtually disappeared, and the river no longer freezes. Since 1900, changes are primarily correlated with increases in air temperature (Tw increase of 0.81 ± 0.25 ∘C) but also occur due to alterations in the river system such as depth increases from reservoirs (0.34 ± 0.12 ∘C). Managed release of water affects Tw seasonally, with an average reduction of up to 0.56 ∘C estimated for September. River system changes have decreased variability (σ) in daily minimum Tw by 0.44 ∘C, increased thermal memory, reduced interannual variability, and reduced the response to short-term meteorological forcing (e.g., heat waves). These changes fundamentally alter the response of Tw to climate change, posing additional stressors on fauna.
{"title":"Warming of the Willamette River, 1850–present: the effects of climate change and river system alterations","authors":"S. Talke, D. Jay, H. Diefenderfer","doi":"10.5194/hess-27-2807-2023","DOIUrl":"https://doi.org/10.5194/hess-27-2807-2023","url":null,"abstract":"Abstract. Using archival research methods, we recovered and combined data from multiple sources to produce a unique, 140-year record of daily water\u0000temperature (Tw) in the lower Willamette River, Oregon (1881–1890, 1941–present). Additional daily weather and river flow records from the 1850s onwards are used to develop and validate a statistical regression model of Tw for 1850–2020. The model simulates the time-lagged response of Tw to air temperature and river flow and is calibrated for three distinct time periods: the late 19th, mid-20th, and early 21st centuries. Results show that Tw has trended upwards at 1.1 ∘C per century since the mid-19th century, with the largest shift in January and February (1.3 ∘C per century) and the smallest in May and June (∼ 0.8 ∘C per century). The duration that the river exceeds the ecologically important threshold of 20 ∘C has increased by about 20 d since the 1800s, to about 60 d yr−1. Moreover, cold-water days below 2 ∘C have virtually disappeared, and the river no longer freezes. Since 1900, changes are primarily correlated with increases\u0000in air temperature (Tw increase of 0.81 ± 0.25 ∘C) but also occur due to alterations in the river system such as depth increases from reservoirs (0.34 ± 0.12 ∘C). Managed release of water affects Tw seasonally, with an average reduction of up to 0.56 ∘C estimated for September. River system changes have decreased variability (σ) in daily minimum Tw by 0.44 ∘C, increased thermal memory, reduced interannual variability, and reduced the response to short-term meteorological forcing (e.g., heat waves). These changes fundamentally alter the response of Tw to climate change, posing additional stressors on fauna.\u0000","PeriodicalId":13143,"journal":{"name":"Hydrology and Earth System Sciences","volume":" ","pages":""},"PeriodicalIF":6.3,"publicationDate":"2023-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49004349","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 : 2023-07-26DOI: 10.5194/hess-27-2787-2023
P. Lawston-Parker, Joseph A. Santanello Jr., N. Chaney
Abstract. The transport of water, heat, and momentum from the surface to the atmosphere is dependent, in part, on the characteristics of the land surface. Along with the model physics, parameterization schemes, and parameters employed, land datasets determine the spatial variability in land surface states (i.e., soil moisture and temperature) and fluxes. Despite the importance of these datasets, they are often chosen out of convenience or owing to regional limitations, without due assessment of their impacts on model results. Irrigation is an anthropogenic form of land heterogeneity that has been shown to alter the land surface energy balance, ambient weather, and local circulations. As such, irrigation schemes are becoming more prevalent in weather and climate models, with rapid developments in dataset availability and parameterization scheme complexity. Thus, to address pragmatic issues related to modeling irrigation, this study uses a high-resolution, regional coupled modeling system to investigate the impacts of irrigation dataset selection on land–atmosphere (L–A) coupling using a case study from the Great Plains Irrigation Experiment (GRAINEX) field campaign. The simulations are assessed in the context of irrigated vs. nonirrigated regions, subregions across the irrigation gradient, and sub-grid-scale process representation in coarser-scale models. The results show that L–A coupling is sensitive to the choice of irrigation dataset and resolution and that the irrigation impact on surface fluxes and near-surface meteorology can be dominant, conditioned on the details of the irrigation map (e.g., boundaries and heterogeneity), or minimal. A consistent finding across several analyses was that even a low percentage of irrigation fraction (i.e., 4 %–16 %) can have significant local and downstream atmospheric impacts (e.g., lower planetary boundary layer, PBL, height), suggesting that the representation of boundaries and heterogeneous areas within irrigated regions is particularly important for the modeling of irrigation impacts on the atmosphere in this model. When viewing the simulations presented here as a proxy for “ideal” tiling in an Earth-system-model-scale grid box, the results show that some “tiles” will reach critical nonlinear moisture and PBL thresholds that could be important for clouds and convection, implying that heterogeneity resulting from irrigation should be taken into consideration in new sub-grid L–A exchange parameterizations.
{"title":"Investigating the response of land–atmosphere interactions and feedbacks to spatial representation of irrigation in a coupled modeling framework","authors":"P. Lawston-Parker, Joseph A. Santanello Jr., N. Chaney","doi":"10.5194/hess-27-2787-2023","DOIUrl":"https://doi.org/10.5194/hess-27-2787-2023","url":null,"abstract":"Abstract. The transport of water, heat, and momentum from the surface to the\u0000atmosphere is dependent, in part, on the characteristics of the land surface.\u0000Along with the model physics, parameterization schemes, and parameters\u0000employed, land datasets determine the spatial variability in land surface\u0000states (i.e., soil moisture and temperature) and fluxes. Despite the\u0000importance of these datasets, they are often chosen out of convenience or\u0000owing to regional limitations, without due assessment of their impacts on model\u0000results. Irrigation is an anthropogenic form of land heterogeneity that has\u0000been shown to alter the land surface energy balance, ambient weather, and\u0000local circulations. As such, irrigation schemes are becoming more prevalent\u0000in weather and climate models, with rapid developments in dataset\u0000availability and parameterization scheme complexity. Thus, to address\u0000pragmatic issues related to modeling irrigation, this study uses a\u0000high-resolution, regional coupled modeling system to investigate the impacts\u0000of irrigation dataset selection on land–atmosphere (L–A) coupling using a\u0000case study from the Great Plains Irrigation Experiment (GRAINEX) field\u0000campaign. The simulations are assessed in the context of irrigated vs.\u0000nonirrigated regions, subregions across the irrigation gradient, and\u0000sub-grid-scale process representation in coarser-scale models. The results\u0000show that L–A coupling is sensitive to the choice of irrigation dataset and\u0000resolution and that the irrigation impact on surface fluxes and near-surface\u0000meteorology can be dominant, conditioned on the details of the irrigation\u0000map (e.g., boundaries and heterogeneity), or minimal. A consistent finding\u0000across several analyses was that even a low percentage of irrigation\u0000fraction (i.e., 4 %–16 %) can have significant local and downstream\u0000atmospheric impacts (e.g., lower planetary\u0000boundary layer, PBL, height), suggesting that the representation\u0000of boundaries and heterogeneous areas within irrigated regions is\u0000particularly important for the modeling of irrigation impacts on the\u0000atmosphere in this model. When viewing the simulations presented here as a\u0000proxy for “ideal” tiling in an Earth-system-model-scale grid box, the results\u0000show that some “tiles” will reach critical nonlinear moisture and PBL thresholds that could be important for clouds and\u0000convection, implying that heterogeneity resulting from irrigation should be\u0000taken into consideration in new sub-grid L–A exchange\u0000parameterizations.\u0000","PeriodicalId":13143,"journal":{"name":"Hydrology and Earth System Sciences","volume":" ","pages":""},"PeriodicalIF":6.3,"publicationDate":"2023-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44050052","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 : 2023-07-26DOI: 10.5194/hess-27-2763-2023
Amanda Triplett, L. Condon
Abstract. The Heihe River basin in northwest China depends heavily on both anthropogenic and natural storage (e.g., surface reservoirs, rivers and groundwater) to support economic and environmental functions. The Qilian Mountain cryosphere in the upper basin is integral to recharging these storage supplies. It is well established that climate warming is driving major shifts in high-elevation water storage through loss of glaciers and permafrost. However, the impacts on groundwater–surface-water interactions and water supply in corresponding lower reaches are less clear. We built an integrated hydrologic model of the middle basin, where most water usage occurs, in order to explore the hydrologic response to the changing cryosphere. We simulate the watershed response to loss of glaciers (glacier scenario), advanced permafrost degradation (permafrost scenario), both of these changes simultaneously (combined scenario) and projected temperature increases in the middle basin (warming scenario) by altering streamflow inputs to the model to represent cryosphere-melting processes, as well as by increasing the temperature of the climate forcing data. Net losses to groundwater storage in the glacier scenario and net gains in the permafrost and combined scenarios show the potential of groundwater exchanges to mediate streamflow shifts. The result of the combined scenario also shows that permafrost degradation has more of an impact on the system than glacial loss. Seasonal differences in groundwater–surface-water partitioning are also evident. The glacier scenario has the highest fraction of groundwater in terms of streamflow in early spring. The permafrost and combined scenarios meanwhile have the highest fraction of streamflow infiltration in late spring and summer. The warming scenario raises the temperature of the combined scenario by 2 ∘C. This results in net groundwater storage loss, a reversal from the combined scenario. Large seasonal changes in evapotranspiration and stream network connectivity relative to the combined scenario show the potential for warming to overpower changes resulting from streamflow. Our results demonstrate the importance of understanding the entire system of groundwater–surface-water exchanges to assess water resources under changing climatic conditions. Ultimately, this analysis can be used to examine the cascading impact of climate change in the cryosphere on the resilience of water resources in arid basins downstream of mountain ranges globally.
{"title":"Climate-warming-driven changes in the cryosphere and their impact on groundwater–surface-water interactions in the Heihe River basin","authors":"Amanda Triplett, L. Condon","doi":"10.5194/hess-27-2763-2023","DOIUrl":"https://doi.org/10.5194/hess-27-2763-2023","url":null,"abstract":"Abstract. The Heihe River basin in northwest China depends heavily\u0000on both anthropogenic and natural storage (e.g., surface reservoirs, rivers and\u0000groundwater) to support economic and environmental functions. The Qilian\u0000Mountain cryosphere in the upper basin is integral to recharging these\u0000storage supplies. It is well established that climate warming is driving\u0000major shifts in high-elevation water storage through loss of glaciers and\u0000permafrost. However, the impacts on groundwater–surface-water interactions\u0000and water supply in corresponding lower reaches are less clear. We built an\u0000integrated hydrologic model of the middle basin, where most water usage\u0000occurs, in order to explore the hydrologic response to the changing\u0000cryosphere. We simulate the watershed response to loss of glaciers (glacier scenario),\u0000advanced permafrost degradation (permafrost scenario), both of these changes simultaneously (combined scenario) and\u0000projected temperature increases in the middle basin (warming scenario) by altering\u0000streamflow inputs to the model to represent cryosphere-melting processes, as\u0000well as by increasing the temperature of the climate forcing data. Net\u0000losses to groundwater storage in the glacier scenario and net gains in the permafrost and combined scenarios show\u0000the potential of groundwater exchanges to mediate streamflow shifts. The\u0000result of the combined scenario also shows that permafrost degradation has more of an\u0000impact on the system than glacial loss. Seasonal differences in\u0000groundwater–surface-water partitioning are also evident. The glacier scenario has\u0000the highest fraction of groundwater in terms of streamflow in early spring. The\u0000permafrost and combined scenarios meanwhile have the highest fraction of streamflow\u0000infiltration in late spring and summer. The warming scenario raises the temperature\u0000of the combined scenario by 2 ∘C. This results in net groundwater storage\u0000loss, a reversal from the combined scenario. Large seasonal changes in\u0000evapotranspiration and stream network connectivity relative to the combined scenario show the\u0000potential for warming to overpower changes resulting from streamflow. Our\u0000results demonstrate the importance of understanding the entire system of\u0000groundwater–surface-water exchanges to assess water resources under\u0000changing climatic conditions. Ultimately, this analysis can be used to\u0000examine the cascading impact of climate change in the cryosphere on the\u0000resilience of water resources in arid basins downstream of mountain ranges\u0000globally.\u0000","PeriodicalId":13143,"journal":{"name":"Hydrology and Earth System Sciences","volume":" ","pages":""},"PeriodicalIF":6.3,"publicationDate":"2023-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46138319","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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