Ze Yang, Zhi Dou, Alberto Guadagnini, Xiaoteng Li, Chaoqi Wang, Jinguo Wang
We document results of a set of laboratory experiments aimed at exploring impacts of injection rate and bacterial density on biomineralization across water-saturated porous media. The study relies on a Low-Field Nuclear Magnetic Resonance technology and the ensuing transverse spin-spin relaxation time distributions. The latter is documented to provide a robust quantification of temporal histories of pore size distributions during biomineralization. As such, our work explores and quantifies pore-size dependent biomineralization across the three-dimensional pore space. The study also provides a quantitative analysis of alterations in porosity and permeability induced by biomineralization, together with a quantification of (time-averaged) rates of pore volume change. A plugging ratio efficiency index is introduced to quantify the strength of pore-size-related biomineralization. Our results reveal that biomineralization induces significant alterations in the pore size distribution within a porous medium, these changes being modulated by bacterial density and injection rate. We find that CaCO3 mainly precipitates in macropores, consistent with the presence of favorable local hydrodynamic conditions and large surface areas therein. Precipitated CaCO3 volume is found to increase with bacterial density. High bacterial densities amplify rate of pore volume change within macropores and adequate plugging ratio of biomineralization and contribute to a significant permeability reduction. Otherwise, a diminished strength of biomineralization in mesopores and micropores is documented for the highest injection rates considered.
{"title":"Experimental Analyses of Pore-Size Dependent Biomineralization in Porous Media Under Various Flow Rate and Bacterial Density Scenarios","authors":"Ze Yang, Zhi Dou, Alberto Guadagnini, Xiaoteng Li, Chaoqi Wang, Jinguo Wang","doi":"10.1029/2024wr037674","DOIUrl":"https://doi.org/10.1029/2024wr037674","url":null,"abstract":"We document results of a set of laboratory experiments aimed at exploring impacts of injection rate and bacterial density on biomineralization across water-saturated porous media. The study relies on a Low-Field Nuclear Magnetic Resonance technology and the ensuing transverse spin-spin relaxation time distributions. The latter is documented to provide a robust quantification of temporal histories of pore size distributions during biomineralization. As such, our work explores and quantifies pore-size dependent biomineralization across the three-dimensional pore space. The study also provides a quantitative analysis of alterations in porosity and permeability induced by biomineralization, together with a quantification of (time-averaged) rates of pore volume change. A plugging ratio efficiency index is introduced to quantify the strength of pore-size-related biomineralization. Our results reveal that biomineralization induces significant alterations in the pore size distribution within a porous medium, these changes being modulated by bacterial density and injection rate. We find that CaCO<sub>3</sub> mainly precipitates in macropores, consistent with the presence of favorable local hydrodynamic conditions and large surface areas therein. Precipitated CaCO<sub>3</sub> volume is found to increase with bacterial density. High bacterial densities amplify rate of pore volume change within macropores and adequate plugging ratio of biomineralization and contribute to a significant permeability reduction. Otherwise, a diminished strength of biomineralization in mesopores and micropores is documented for the highest injection rates considered.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"83 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142937720","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}
Huibin Gao, Qin Ju, Dawei Zhang, Zhenlong Wang, Zhenchun Hao, James W. Kirchner
Understanding streamflow generation at the catchment scale requires quantifying how different components of the system are linked, and how they respond to meteorological forcing. Here we present a proof-of-concept study characterizing and quantifying dynamic linkages between precipitation, groundwater recharge, and streamflow using a data-driven nonlinear deconvolution and demixing approach, Ensemble Rainfall-Runoff Analysis (ERRA). Streamflow in our mesoscale, intensively farmed test catchment is flashy, but occurs at time lags that are too long to be plausibly attributed to overland flow. Instead, ERRA's estimates of the impulse responses of groundwater recharge to precipitation, and of streamflow to groundwater recharge, imply that this intermittent streamflow is primarily driven by precipitation infiltrating to recharge groundwater, followed by discharge of groundwater to streamflow. ERRA reveals that streamflow increases nonlinearly with increasing precipitation intensity or groundwater recharge, and exhibits almost no response to precipitation or recharge rates of less than 10 mm d−1. Groundwater recharge is both nonlinear, increasing more-than-proportionally with precipitation intensity, and nonstationary, increasing with antecedent wetness. Simulations with the infiltration model Hydrus-1D can reproduce the observed water table time series reasonably well (NSE = 0.70). However, ERRA shows that the model's impulse response is inconsistent with the real-world impulse response estimated from measured precipitation and groundwater recharge, illustrating that conventional goodness-of-fit statistics can be weak tests of model realism. Thus, our proof-of-concept study demonstrates how impulse responses estimated by ERRA can help clarify linkages between precipitation and streamflow at the catchment scale, quantify nonlinearity and nonstationarity in hydrologic processes, and critically evaluate simulation models.
理解流域尺度上的水流产生需要量化系统的不同组成部分是如何联系在一起的，以及它们如何对气象强迫作出反应。在这里，我们提出了一项概念验证研究，利用数据驱动的非线性反褶积和分解方法，即集合降雨径流分析（ERRA），表征和量化降水、地下水补给和河流流量之间的动态联系。在我们的中尺度、集约化养殖的测试集水区，水流是浮华的，但发生的时间滞后太长，无法合理地归因于陆上水流。相反，对地下水补给对降水的脉冲响应和径流对地下水补给的脉冲响应的估计表明，这种间歇性的径流主要是由降水入渗补给地下水驱动的，然后是地下水向径流的排放。地磁重构显示，径流随降水强度或地下水补给量的增加呈非线性增加，对降水或补给量小于10 mm d−1几乎没有响应。地下水补给是非线性的，随着降水强度的增加而增加，而非平稳性的，随着前期湿度的增加而增加。采用Hydrus-1D入渗模式模拟可以较好地再现观测到的地下水位时间序列（NSE = 0.70）。然而，该模型的脉冲响应与实测降水和地下水补给估计的真实脉冲响应不一致，说明传统的拟合优度统计可能是模型真实性的弱检验。因此，我们的概念验证研究证明了ERRA估计的脉冲响应如何有助于澄清流域尺度上降水和河流流量之间的联系，量化水文过程中的非线性和非平稳性，并批判性地评估模拟模型。
{"title":"Quantifying Dynamic Linkages Between Precipitation, Groundwater Recharge, and Streamflow Using Ensemble Rainfall-Runoff Analysis","authors":"Huibin Gao, Qin Ju, Dawei Zhang, Zhenlong Wang, Zhenchun Hao, James W. Kirchner","doi":"10.1029/2024wr037821","DOIUrl":"https://doi.org/10.1029/2024wr037821","url":null,"abstract":"Understanding streamflow generation at the catchment scale requires quantifying how different components of the system are linked, and how they respond to meteorological forcing. Here we present a proof-of-concept study characterizing and quantifying dynamic linkages between precipitation, groundwater recharge, and streamflow using a data-driven nonlinear deconvolution and demixing approach, Ensemble Rainfall-Runoff Analysis (ERRA). Streamflow in our mesoscale, intensively farmed test catchment is flashy, but occurs at time lags that are too long to be plausibly attributed to overland flow. Instead, ERRA's estimates of the impulse responses of groundwater recharge to precipitation, and of streamflow to groundwater recharge, imply that this intermittent streamflow is primarily driven by precipitation infiltrating to recharge groundwater, followed by discharge of groundwater to streamflow. ERRA reveals that streamflow increases nonlinearly with increasing precipitation intensity or groundwater recharge, and exhibits almost no response to precipitation or recharge rates of less than 10 mm d<sup>−1</sup>. Groundwater recharge is both nonlinear, increasing more-than-proportionally with precipitation intensity, and nonstationary, increasing with antecedent wetness. Simulations with the infiltration model Hydrus-1D can reproduce the observed water table time series reasonably well (NSE = 0.70). However, ERRA shows that the model's impulse response is inconsistent with the real-world impulse response estimated from measured precipitation and groundwater recharge, illustrating that conventional goodness-of-fit statistics can be weak tests of model realism. Thus, our proof-of-concept study demonstrates how impulse responses estimated by ERRA can help clarify linkages between precipitation and streamflow at the catchment scale, quantify nonlinearity and nonstationarity in hydrologic processes, and critically evaluate simulation models.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"27 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142937733","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}
Modeling water stable isotope transport in soil is crucial to sharpen our understanding of water cycles in terrestrial ecosystems. Although several models for soil water isotope transport have been developed, many rely on a semi-coupled numerical approach, solving isotope transport only after obtaining solutions from water and heat transport equations. However, this approach may increase instability and errors of model. Here, we developed an algorithm that solves one-dimensional water, heat, and isotope transport equations with a fully coupled method (MOIST). Our results showed that MOIST is more stable under various spatial and temporal discretization than semi-coupled method and has good agreement with semi-analytical solutions of isotope transport. We also validated MOIST with long-term measurements from a lysimeter study under three scenarios with soil hydraulic parameters calibrated by HYDRUS-1D in the first two scenarios and by MOIST in the last scenario. In scenario 1, MOIST showed an overall NSE, KGE, and MAE of simulated δ18O of 0.47, 0.58, and 0.92‰, respectively, compared to the 0.31, 0.60, and 1.00‰ from HYDRUS-1D; In scenario 2, these indices of MOIST were 0.33, 0.52, and 1.04‰, respectively, compared to the 0.19, 0.58, and 1.15‰ from HYDRUS-1D; In scenario 3, calibrated MOIST exhibited the highest NSE (0.48) and KGE (0.76), the smallest MAE (0.90) among all scenarios. These findings indicate MOIST has better performance in simulating water flow and isotope transport in simplified ecosystems than HYDRUS-1D, suggesting the great potential of MOIST in furthering our understandings of ecohydrological processes in terrestrial ecosystems.
{"title":"A Fully Coupled Numerical Solution of Water, Vapor, Heat, and Water Stable Isotope Transport in Soil","authors":"Han Fu, Eric John Neil, Huijie Li, Bingcheng Si","doi":"10.1029/2024wr037068","DOIUrl":"https://doi.org/10.1029/2024wr037068","url":null,"abstract":"Modeling water stable isotope transport in soil is crucial to sharpen our understanding of water cycles in terrestrial ecosystems. Although several models for soil water isotope transport have been developed, many rely on a semi-coupled numerical approach, solving isotope transport only after obtaining solutions from water and heat transport equations. However, this approach may increase instability and errors of model. Here, we developed an algorithm that solves one-dimensional water, heat, and isotope transport equations with a fully coupled method (MOIST). Our results showed that MOIST is more stable under various spatial and temporal discretization than semi-coupled method and has good agreement with semi-analytical solutions of isotope transport. We also validated MOIST with long-term measurements from a lysimeter study under three scenarios with soil hydraulic parameters calibrated by HYDRUS-1D in the first two scenarios and by MOIST in the last scenario. In scenario 1, MOIST showed an overall <i>NSE</i>, <i>KGE</i>, and <i>MAE</i> of simulated δ<sup>18</sup>O of 0.47, 0.58, and 0.92‰, respectively, compared to the 0.31, 0.60, and 1.00‰ from HYDRUS-1D; In scenario 2, these indices of MOIST were 0.33, 0.52, and 1.04‰, respectively, compared to the 0.19, 0.58, and 1.15‰ from HYDRUS-1D; In scenario 3, calibrated MOIST exhibited the highest <i>NSE</i> (0.48) and <i>KGE</i> (0.76), the smallest <i>MAE</i> (0.90) among all scenarios. These findings indicate MOIST has better performance in simulating water flow and isotope transport in simplified ecosystems than HYDRUS-1D, suggesting the great potential of MOIST in furthering our understandings of ecohydrological processes in terrestrial ecosystems.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"24 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142937763","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}
Heat storage change (HSC) is a crucial component of lake's thermal energy budget. Conventional temperature profile based models of HSC require location specific parameters such as lakebed topography. Based on the half-order time-derivative formula of heat fluxes, an analytical model was formulated for estimating HSC from water surface temperature and solar radiation without using geography dependent parameters. The proposed model was tested against field measurements at Poyang Lake, a shallow inland lake, which has pronounced seasonal variations in water level and lake area. Our analysis indicates that the model accurately simulates diurnal HSC with a coefficient of determination of 0.94 and a root mean squared error (RMSE) of 77.5 ± 21.6 Wm−2 for the study period. Larger nighttime RMSE (75.0 ± 26.8 Wm−2) than the daytime value (55.1 ± 19.7 W m−2) is attributable to larger measurement errors of nighttime turbulent fluxes. The estimation of HSC independent of temperature profile and lake-specific parameters by the proposed model facilitates remote sensing monitoring the HSC of global water bodies.
{"title":"A Half-Order Derivative Based Model of Lake Heat Storage Change","authors":"Yuanbo Liu, Liangjun Tang, Wanqiu Xing, Jingfeng Wang, Ruonan Wang, Yifan Cui, Qi Li","doi":"10.1029/2024wr038269","DOIUrl":"https://doi.org/10.1029/2024wr038269","url":null,"abstract":"Heat storage change (HSC) is a crucial component of lake's thermal energy budget. Conventional temperature profile based models of HSC require location specific parameters such as lakebed topography. Based on the half-order time-derivative formula of heat fluxes, an analytical model was formulated for estimating HSC from water surface temperature and solar radiation without using geography dependent parameters. The proposed model was tested against field measurements at Poyang Lake, a shallow inland lake, which has pronounced seasonal variations in water level and lake area. Our analysis indicates that the model accurately simulates diurnal HSC with a coefficient of determination of 0.94 and a root mean squared error (RMSE) of 77.5 ± 21.6 Wm<sup>−2</sup> for the study period. Larger nighttime RMSE (75.0 ± 26.8 Wm<sup>−2</sup>) than the daytime value (55.1 ± 19.7 W m<sup>−2</sup>) is attributable to larger measurement errors of nighttime turbulent fluxes. The estimation of HSC independent of temperature profile and lake-specific parameters by the proposed model facilitates remote sensing monitoring the HSC of global water bodies.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"7 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142937722","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}
Lena M. Scheiffele, Matthias Munz, Till Francke, Gabriele Baroni, Sascha E. Oswald
Vadose zone models, calibrated with state variables, may offer a robust approach for deriving groundwater recharge. Cosmic-ray neutron sensing (CRNS) provides soil moisture over a large support volume (horizontal extent of hectares) and offers the opportunity to estimate water fluxes at this scale. However, the horizontal and vertical sensitivity of the method results in an inherently weighted water content, which poses a challenge for its application in soil hydrologic modeling. We systematically assess calibrating a soil hydraulic model in HYDRUS 1D at a cropped field site. Calibration was performed using different field-scale soil moisture time series and the ability of the model to represent root zone soil moisture and derive groundwater recharge was assessed. As our benchmark, we used a distributed point sensor network from within the footprint of the CRNS. Models calibrated on CRNS data or combinations of CRNS with deeper point measurements resulted in cumulative groundwater recharge comparable to the benchmark. While models based exclusively on CRNS data do not represent the root zone soil moisture dynamics adequately, combining CRNS with profile soil moisture overcomes this limitation. Models calibrated on CRNS data also perform well in timing the downward flux compared to an independent estimate based on soil water tension measurements. However, the latter provides quantitative groundwater recharge estimates spanning a wide range of values, including unrealistic highs exceeding local annual precipitation. Conversely, modeled groundwater recharge based on the distributed sensor network or on CRNS resulted in estimates ranging between 30% and 40% of annual precipitation.
{"title":"Enhancing Hectare-Scale Groundwater Recharge Estimation by Integrating Data From Cosmic-Ray Neutron Sensing Into Soil Hydrological Modeling","authors":"Lena M. Scheiffele, Matthias Munz, Till Francke, Gabriele Baroni, Sascha E. Oswald","doi":"10.1029/2024wr037641","DOIUrl":"https://doi.org/10.1029/2024wr037641","url":null,"abstract":"Vadose zone models, calibrated with state variables, may offer a robust approach for deriving groundwater recharge. Cosmic-ray neutron sensing (CRNS) provides soil moisture over a large support volume (horizontal extent of hectares) and offers the opportunity to estimate water fluxes at this scale. However, the horizontal and vertical sensitivity of the method results in an inherently weighted water content, which poses a challenge for its application in soil hydrologic modeling. We systematically assess calibrating a soil hydraulic model in HYDRUS 1D at a cropped field site. Calibration was performed using different field-scale soil moisture time series and the ability of the model to represent root zone soil moisture and derive groundwater recharge was assessed. As our benchmark, we used a distributed point sensor network from within the footprint of the CRNS. Models calibrated on CRNS data or combinations of CRNS with deeper point measurements resulted in cumulative groundwater recharge comparable to the benchmark. While models based exclusively on CRNS data do not represent the root zone soil moisture dynamics adequately, combining CRNS with profile soil moisture overcomes this limitation. Models calibrated on CRNS data also perform well in timing the downward flux compared to an independent estimate based on soil water tension measurements. However, the latter provides quantitative groundwater recharge estimates spanning a wide range of values, including unrealistic highs exceeding local annual precipitation. Conversely, modeled groundwater recharge based on the distributed sensor network or on CRNS resulted in estimates ranging between 30% and 40% of annual precipitation.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"107 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142936553","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}
Jiahao Zhang, Mengzhen Xu, Boris Huber, Markus Grünzner, Koen Blanckaert
Mussel biofouling increases energy losses in hydraulic structures. The first contribution of this paper is the quantification of the mussel-induced equivalent sand roughness ks as function of the mussel attachment density N and the shell length L. Laboratory experiments reveal that ks/L ≈ 1.5 for a continuous regular layer of mussels, which is found for N L2 > 1.2. For 0.5 < N L2 < 1.2, the mussels form a continuous irregular roughness layer with increased values of ks/L of up to 2.4. These geometrical irregularities are interpreted as macro-roughness elements, that is, roughness elements with a spatial scale larger than that of an individual mussel. For N L2 < 0.5, the density of the irregularities is too low to act as macro-roughness elements leading to ks/L < 1.5. The second contribution is the establishment of a threshold criterion for the importance of filtering activity on ks based on data from the here reported experiments and data reported in literature in other configurations and/or with other mussel species. It is found that laboratory conditions are often close to the threshold value but that mussel filtering is always negligible in large hydraulic structures. The third contribution is the development of a method based on 3-D numerical simulations for estimating a Darcy-Weisbach friction factor f for walls that are only partially covered with patches of mussels. An application example illustrates how the thus obtained f can be used in a 1-D model for quantifying the additional energy losses in large water transfer projects.
{"title":"Roughness and Energy Losses Induced by Mussel Growth on the Walls of Hydraulic Structures and Application to a Water Transfer Project","authors":"Jiahao Zhang, Mengzhen Xu, Boris Huber, Markus Grünzner, Koen Blanckaert","doi":"10.1029/2023wr036503","DOIUrl":"https://doi.org/10.1029/2023wr036503","url":null,"abstract":"Mussel biofouling increases energy losses in hydraulic structures. The first contribution of this paper is the quantification of the mussel-induced equivalent sand roughness <i>k</i><sub><i>s</i></sub> as function of the mussel attachment density <i>N</i> and the shell length <i>L</i>. Laboratory experiments reveal that <i>k</i><sub><i>s</i></sub><i>/L</i> ≈ 1.5 for a continuous regular layer of mussels, which is found for <i>N L</i><sup>2</sup> > 1.2. For 0.5 < <i>N L</i><sup>2</sup> < 1.2, the mussels form a continuous irregular roughness layer with increased values of <i>k</i><sub><i>s</i></sub><i>/L</i> of up to 2.4. These geometrical irregularities are interpreted as macro-roughness elements, that is, roughness elements with a spatial scale larger than that of an individual mussel. For <i>N L</i><sup>2</sup> < 0.5, the density of the irregularities is too low to act as macro-roughness elements leading to <i>k</i><sub><i>s</i></sub><i>/L</i> < 1.5. The second contribution is the establishment of a threshold criterion for the importance of filtering activity on <i>k</i><sub><i>s</i></sub> based on data from the here reported experiments and data reported in literature in other configurations and/or with other mussel species. It is found that laboratory conditions are often close to the threshold value but that mussel filtering is always negligible in large hydraulic structures. The third contribution is the development of a method based on 3-D numerical simulations for estimating a Darcy-Weisbach friction factor <i>f</i> for walls that are only partially covered with patches of mussels. An application example illustrates how the thus obtained <i>f</i> can be used in a 1-D model for quantifying the additional energy losses in large water transfer projects.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"23 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142936552","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}
Bo Gai, Rohini Kumar, Frank Hüesker, Chenxi Mi, Xiangzhen Kong, Bertram Boehrer, Karsten Rinke, Tom Shatwell
Lentic waters integrate atmosphere and catchment processes, and thus ultimately capture climate signals. However, studies of climate warming effects on lentic waters usually do not sufficiently account for a change in heat flux from the catchment through altered inflow temperature and discharge under climate change. This is particularly relevant for reservoirs, which are highly impacted by catchment hydrology and may be affected by upstream reservoirs or pre-dams. This study explicitly quantified how the catchment and pre-dams modify the thermal response of Rappbode Reservoir, Germany's largest drinking water reservoir system, to climate change. We established a catchment-lake modeling chain in the main reservoir and its two pre-dams utilizing the lake model GOTM, the catchment model mHM, and the stream temperature model Air2stream, forced by an ensemble of climate projections under RCP2.6 and 8.5 warming scenarios. Results exhibited a warming of 0.27/0.15°C decade−1 for the surface/bottom temperatures of the main reservoir, with approximately 8%/24% of this warming attributed to the catchment warming, respectively. The catchment warming amplified the deep water warming more than at the surface, contrary to the atmospheric warming effect, and advanced stratification by about 1 week, while having a minor impact on stratification intensity. On the other hand, pre-dams reduced the inflow temperature into the main reservoir in spring, and consequently lowered the hypolimnetic temperature and postponed stratification onset. This shielded the main reservoir from climate warming, although overall the contribution of pre-dams was minimal. Altogether, our study highlights the importance of catchment alterations and seasonality when projecting reservoir warming, and provides insights into catchment-reservoir coupling under climate change.
{"title":"Catchments Amplify Reservoir Thermal Response to Climate Warming","authors":"Bo Gai, Rohini Kumar, Frank Hüesker, Chenxi Mi, Xiangzhen Kong, Bertram Boehrer, Karsten Rinke, Tom Shatwell","doi":"10.1029/2023wr036808","DOIUrl":"https://doi.org/10.1029/2023wr036808","url":null,"abstract":"Lentic waters integrate atmosphere and catchment processes, and thus ultimately capture climate signals. However, studies of climate warming effects on lentic waters usually do not sufficiently account for a change in heat flux from the catchment through altered inflow temperature and discharge under climate change. This is particularly relevant for reservoirs, which are highly impacted by catchment hydrology and may be affected by upstream reservoirs or pre-dams. This study explicitly quantified how the catchment and pre-dams modify the thermal response of Rappbode Reservoir, Germany's largest drinking water reservoir system, to climate change. We established a catchment-lake modeling chain in the main reservoir and its two pre-dams utilizing the lake model GOTM, the catchment model mHM, and the stream temperature model Air2stream, forced by an ensemble of climate projections under RCP2.6 and 8.5 warming scenarios. Results exhibited a warming of 0.27/0.15°C decade<sup>−1</sup> for the surface/bottom temperatures of the main reservoir, with approximately 8%/24% of this warming attributed to the catchment warming, respectively. The catchment warming amplified the deep water warming more than at the surface, contrary to the atmospheric warming effect, and advanced stratification by about 1 week, while having a minor impact on stratification intensity. On the other hand, pre-dams reduced the inflow temperature into the main reservoir in spring, and consequently lowered the hypolimnetic temperature and postponed stratification onset. This shielded the main reservoir from climate warming, although overall the contribution of pre-dams was minimal. Altogether, our study highlights the importance of catchment alterations and seasonality when projecting reservoir warming, and provides insights into catchment-reservoir coupling under climate change.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"43 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142935164","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}
Aldo Fiori, Felipe P. J. de Barros, Alberto Bellin
Managed Aquifer Recharge (MAR) plays an important role in improving and supplementing groundwater storage. Many natural factors, ranging from climatic conditions to soil characteristics, can impact the efficiency of an infiltration basin. Other factors, such as engineered variables, will also influence the basin performance and the risks associated with groundwater contamination. The latter depends on the interplay between the hydraulic characteristics of the system and the soil and solute properties. The design of infiltration basins has been performed so far with the main objective of mitigating the tendency of the basin to reduce the infiltration rate with time due to clogging of the basin's bottom. Less attention has been paid to the risk of groundwater contamination by the infiltrating water. To understand the complex interplay between natural and engineering parameters on MAR efficiency and the contamination risk, we propose a risk-oriented analytical framework. The framework allows to investigate the interplay between soil parameters, engineering design and climatic factors on the efficiency of an infiltration basin. Our framework relies on novel analytical solutions that relates the geometrical and hydrological features of the infiltration basin to its efficiency and groundwater contamination risk. The solutions incorporates the randomness associated with inflows (precipitation) and soil properties. We explore the trade-off between efficiency and the risk of contamination and delineate a design procedure that balances these two opposing needs. Although the framework relies on simplifying assumptions, it provides a computationally efficient manner to obtain physical insights and relate model input parameters to decision making.
{"title":"An Analytical Framework for Risk Evaluation and Design of Infiltration Basins for Managed Aquifer Recharge","authors":"Aldo Fiori, Felipe P. J. de Barros, Alberto Bellin","doi":"10.1029/2024wr038516","DOIUrl":"https://doi.org/10.1029/2024wr038516","url":null,"abstract":"Managed Aquifer Recharge (MAR) plays an important role in improving and supplementing groundwater storage. Many natural factors, ranging from climatic conditions to soil characteristics, can impact the efficiency of an infiltration basin. Other factors, such as engineered variables, will also influence the basin performance and the risks associated with groundwater contamination. The latter depends on the interplay between the hydraulic characteristics of the system and the soil and solute properties. The design of infiltration basins has been performed so far with the main objective of mitigating the tendency of the basin to reduce the infiltration rate with time due to clogging of the basin's bottom. Less attention has been paid to the risk of groundwater contamination by the infiltrating water. To understand the complex interplay between natural and engineering parameters on MAR efficiency and the contamination risk, we propose a risk-oriented analytical framework. The framework allows to investigate the interplay between soil parameters, engineering design and climatic factors on the efficiency of an infiltration basin. Our framework relies on novel analytical solutions that relates the geometrical and hydrological features of the infiltration basin to its efficiency and groundwater contamination risk. The solutions incorporates the randomness associated with inflows (precipitation) and soil properties. We explore the trade-off between efficiency and the risk of contamination and delineate a design procedure that balances these two opposing needs. Although the framework relies on simplifying assumptions, it provides a computationally efficient manner to obtain physical insights and relate model input parameters to decision making.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"42 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142929494","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}
Minxiang Zhu, Dan Yu, Yiqi Yu, Yi Zheng, Shaobin Li, Ximing Cai, Nengwang Chen
The El Niño-Southern Oscillation (ENSO) significantly disrupts Pacific Ocean watershed hydrology, affecting water supply reliability. However, the specific ways in which ENSO affects seasonal river discharge remain underexplored, presenting a significant gap in our understanding of climate-water interactions. Our study reveals that ENSO exacerbates river discharge variability, evident in the dynamics of maximum rise (Dr) and fall (Df) in standardized discharge, and their duration (M). Notably, ENSO augments Dr but shortens M in major rivers like the Yangtze. Employing a novel metric, the Discharge Instability Index (DII), we find that DII surges by at least 69% in El Niño years, particularly in southwestern North American watersheds. Vegetation and precipitation emerge as pivotal in shaping the discharge response to ENSO. Predictive modeling with DII suggests an escalation in discharge instability under climate warming, with a 0.11%–9.46% increase. This insight calls for water managers to integrate ENSO-induced seasonal variations into strategic planning, blending immediate actions like dam regulation with long-term initiatives such as afforestation, to counteract climate-induced water scarcity.
El Niño-Southern涛动（ENSO）严重破坏了太平洋流域的水文，影响了供水的可靠性。然而，ENSO影响季节性河流流量的具体方式仍未得到充分探索，这表明我们对气候-水相互作用的理解存在重大差距。研究表明，ENSO加剧了河流流量的变化，体现在标准化流量的最大上升（Dr）和最大下降（Df）及其持续时间(M)的动态变化上。值得注意的是，ENSO在长江等主要河流中增加了Dr，缩短了M。采用一种新的度量，即流量不稳定指数（DII），我们发现DII在El Niño年至少激增69%，特别是在北美西南部流域。植被和降水在形成对ENSO的流量响应中起关键作用。基于DII的预测模型表明，气候变暖导致排放不稳定性上升，增幅为0.11% ~ 9.46%。这一见解要求水资源管理者将enso引起的季节变化纳入战略规划，将大坝管理等即时行动与造林等长期举措相结合，以应对气候引起的水资源短缺。
{"title":"ENSO Enhances Seasonal River Discharge Instability and Water Resource Allocation Pressure","authors":"Minxiang Zhu, Dan Yu, Yiqi Yu, Yi Zheng, Shaobin Li, Ximing Cai, Nengwang Chen","doi":"10.1029/2023wr036965","DOIUrl":"https://doi.org/10.1029/2023wr036965","url":null,"abstract":"The El Niño-Southern Oscillation (ENSO) significantly disrupts Pacific Ocean watershed hydrology, affecting water supply reliability. However, the specific ways in which ENSO affects seasonal river discharge remain underexplored, presenting a significant gap in our understanding of climate-water interactions. Our study reveals that ENSO exacerbates river discharge variability, evident in the dynamics of maximum rise (Dr) and fall (Df) in standardized discharge, and their duration (M). Notably, ENSO augments Dr but shortens M in major rivers like the Yangtze. Employing a novel metric, the Discharge Instability Index (DII), we find that DII surges by at least 69% in El Niño years, particularly in southwestern North American watersheds. Vegetation and precipitation emerge as pivotal in shaping the discharge response to ENSO. Predictive modeling with DII suggests an escalation in discharge instability under climate warming, with a 0.11%–9.46% increase. This insight calls for water managers to integrate ENSO-induced seasonal variations into strategic planning, blending immediate actions like dam regulation with long-term initiatives such as afforestation, to counteract climate-induced water scarcity.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"27 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142929600","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}
Mapping ecosystem function indicators helps identify areas susceptible to drought, heat stress, and reduced agricultural production. This information can be used to prioritize areas for targeted interventions to tackle adverse climatic conditions and changes in land use. Root-zone water-storage capacity (SR) is a commonly used variable of agroecosystem functioning, representing the maximum value of water stored within the root zone and accessible to vegetation for its productive growth. Mapping SR over large spatial scales is only feasible through an oversimplification of real-world conditions. Under such circumstances, we propose to resort to soil-hydraulic-energy indices, namely the integral mean water capacity (IMWC) and the integral energy (IE) and an effective root-zone depth (zR). Accordingly, a more efficient and environmentally sensitive, albeit still simplistic, determination of the root-zone water-storage capacity is computed as SR,IMWC = zR × IMWC, and validated against soil moisture measurements carried out along a transect. Subsequently, the SR,IMWC indicator was mapped in Campania, a 13,700 km2 region in southern Italy. This study also addressed the issue of the propagation of epistemic uncertainty in input soil hydraulic parameters to the output response variable IMWC. This was accomplished using a Monte Carlo simulation technique that generated several equiprobable stochastic realizations from the multivariate set of data inputs. Finally, we assessed the potential utility of the integral capacity energy (ICE) composite indicator, computed as the ratio IMWC/IE in %, as a scoring parameter to identify Priority Intervention Areas (PIAs) where resilience to environmental challenges, including water scarcity, drought events, and post-fire conditions, could be enhanced.
{"title":"Root-Zone Water-Storage Capacity and Uncertainty: An Intrinsic Factor Affecting Agroecosystem Resilience to Drought","authors":"Nunzio Romano, Caterina Mazzitelli, Paolo Nasta","doi":"10.1029/2024wr037719","DOIUrl":"https://doi.org/10.1029/2024wr037719","url":null,"abstract":"Mapping ecosystem function indicators helps identify areas susceptible to drought, heat stress, and reduced agricultural production. This information can be used to prioritize areas for targeted interventions to tackle adverse climatic conditions and changes in land use. Root-zone water-storage capacity (<i>S</i><sub><i>R</i></sub>) is a commonly used variable of agroecosystem functioning, representing the maximum value of water stored within the root zone and accessible to vegetation for its productive growth. Mapping <i>S</i><sub><i>R</i></sub> over large spatial scales is only feasible through an oversimplification of real-world conditions. Under such circumstances, we propose to resort to soil-hydraulic-energy indices, namely the integral mean water capacity (IMWC) and the integral energy (IE) and an effective root-zone depth (<i>z</i><sub><i>R</i></sub>). Accordingly, a more efficient and environmentally sensitive, albeit still simplistic, determination of the root-zone water-storage capacity is computed as <i>S</i><sub><i>R</i>,IMWC</sub> = <i>z</i><sub><i>R</i></sub> × IMWC, and validated against soil moisture measurements carried out along a transect. Subsequently, the <i>S</i><sub><i>R</i>,IMWC</sub> indicator was mapped in Campania, a 13,700 km<sup>2</sup> region in southern Italy. This study also addressed the issue of the propagation of epistemic uncertainty in input soil hydraulic parameters to the output response variable IMWC. This was accomplished using a Monte Carlo simulation technique that generated several equiprobable stochastic realizations from the multivariate set of data inputs. Finally, we assessed the potential utility of the integral capacity energy (ICE) composite indicator, computed as the ratio IMWC/IE in %, as a scoring parameter to identify Priority Intervention Areas (PIAs) where resilience to environmental challenges, including water scarcity, drought events, and post-fire conditions, could be enhanced.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"1 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142924749","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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