Forest status is crucial for catchment hydrology and water quality but is increasingly disturbed by human activities and climatic factors. Therefore, it is urgently necessary to develop water quality models that can adapt to these changes. This study used a new dynamic Hydrological Predictions for the Environment (HYPE) model to assess the effect of rapid and continuous forest changes on catchment hydrology and nitrogen export. The modified HYPE model was implemented for the 25 years period in the Große Ohe catchment in Germany, which has experienced severe forest dieback and recovery. Due to the stochastic nature of infestation events, data covering the entire process of forest change are rare. The modified HYPE model performed well at different scales for discharge and dissolved inorganic nitrogen (DIN) export. It was able to (a) capture the timing of peak flows and the seasonal DIN concentration dynamics and (b) reflect the initial increase and subsequent decrease trend in discharge and DIN export in accordance with forest dieback and regeneration. The increase in nitrogen export after forest dieback primarily resulted from reduced forest uptake and increased soil nitrogen availability from tree residues. The difference in runoff and nitrogen export increment with or without regeneration highlights the importance of forest regeneration in restoring catchment hydrology and water quality. Additionally, a decrease in DIN export after residue removal implies the impact of sound post-disturbance management strategies. The dynamic modeling under changing catchment forests can enhance the analysis of catchment water quality and effectively support forest management.
森林状况对集水区的水文和水质至关重要，但人类活动和气候因素对森林状况的干扰日益严重。因此，迫切需要开发能够适应这些变化的水质模型。本研究使用了一种新的动态环境水文预测模型（HYPE），以评估快速、持续的森林变化对集水区水文和氮输出的影响。修改后的 HYPE 模型在德国 Große Ohe 流域实施了 25 年，该流域经历了严重的森林衰退和恢复。由于虫害事件的随机性，涵盖森林变化全过程的数据非常罕见。改进后的 HYPE 模型在不同尺度的排水和溶解无机氮 (DIN) 输出方面表现良好。它能够：（a）捕捉到峰值流量的时间和季节性 DIN 浓度动态；（b）反映出排水量和 DIN 排放量随森林枯死和再生而出现的最初增加和随后减少的趋势。森林衰退后氮输出量增加的主要原因是森林吸收量减少以及树木残留物增加了土壤中的氮供应量。再生与否导致的径流和氮输出增量差异突出表明了森林再生在恢复集水区水文和水质方面的重要性。此外，清除残留物后 DIN 排放量的减少意味着合理的扰动后管理策略的影响。集水区森林变化下的动态建模可加强对集水区水质的分析，并有效支持森林管理。
{"title":"Impact of Forest Dieback on Hydrology and Nitrogen Export Using a New Dynamic Water Quality Model","authors":"Mufeng Chen, Seifeddine Jomaa, Angela Lausch, Burkhard Beudert, Salman Ghaffar, Wenhao Jia, Michael Rode","doi":"10.1029/2024wr037341","DOIUrl":"https://doi.org/10.1029/2024wr037341","url":null,"abstract":"Forest status is crucial for catchment hydrology and water quality but is increasingly disturbed by human activities and climatic factors. Therefore, it is urgently necessary to develop water quality models that can adapt to these changes. This study used a new dynamic Hydrological Predictions for the Environment (HYPE) model to assess the effect of rapid and continuous forest changes on catchment hydrology and nitrogen export. The modified HYPE model was implemented for the 25 years period in the Große Ohe catchment in Germany, which has experienced severe forest dieback and recovery. Due to the stochastic nature of infestation events, data covering the entire process of forest change are rare. The modified HYPE model performed well at different scales for discharge and dissolved inorganic nitrogen (DIN) export. It was able to (a) capture the timing of peak flows and the seasonal DIN concentration dynamics and (b) reflect the initial increase and subsequent decrease trend in discharge and DIN export in accordance with forest dieback and regeneration. The increase in nitrogen export after forest dieback primarily resulted from reduced forest uptake and increased soil nitrogen availability from tree residues. The difference in runoff and nitrogen export increment with or without regeneration highlights the importance of forest regeneration in restoring catchment hydrology and water quality. Additionally, a decrease in DIN export after residue removal implies the impact of sound post-disturbance management strategies. The dynamic modeling under changing catchment forests can enhance the analysis of catchment water quality and effectively support forest management.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"15 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142694247","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}
J. Kucharski, S. Steinschneider, J. Herman, J. Olszewski, W. Arnold, S. Rahat, R. Maendly, P. Ray
The threat that climate change poses to water resource systems has led to a substantial and growing number of impact studies. These studies follow two approaches: (a) top-down studies are driven by projections of future climate change provided by downscaled general circulation models (GCMs); and (b) bottom-up studies are driven by the systematic evaluation of exploratory scenarios. Top-down approaches produce realistic scenarios rooted in the simulation of thermodynamic and dynamic processes represented in GCMs, but the internal resolution of these processes make it difficult to link vulnerabilities to discrete components of change. Bottom-up approaches link vulnerabilities to discrete components of change through the structured evaluation of exploratory scenarios, but the lack of insight rooted in climate change processes can lead to the development of implausible scenarios. This paper evaluates exploratory scenarios developed through thermodynamic and dynamical guided perturbations motivated by GCM-bound insights. The result is a hybrid approach that bridges a gap between top-down and bottom-up approaches. This yields several advantages. First, emerging vulnerabilities are linked to distinct thermodynamic and dynamic processes that are modeled in GCMs with differential likelihoods and plausible ranges of change. Second, the structured evaluation of process-informed exploratory scenarios link system vulnerabilities to distinct components of climate change. An illustrative case study demonstrates perturbations linked to thermodynamic and dynamical processes have a large impact on stakeholder-defined flood and drought performance, and the structured evaluation of process-informed exploratory scenarios find nuanced infrastructure-specific vulnerabilities that would be difficult to identify using an alternative approach.
{"title":"Bridging the Gap Between Top-Down and Bottom-Up Climate Vulnerability Assessments: Process Informed Exploratory Scenarios Identify System-Based Water Resource Vulnerabilities","authors":"J. Kucharski, S. Steinschneider, J. Herman, J. Olszewski, W. Arnold, S. Rahat, R. Maendly, P. Ray","doi":"10.1029/2023wr036649","DOIUrl":"https://doi.org/10.1029/2023wr036649","url":null,"abstract":"The threat that climate change poses to water resource systems has led to a substantial and growing number of impact studies. These studies follow two approaches: (a) top-down studies are driven by projections of future climate change provided by downscaled general circulation models (GCMs); and (b) bottom-up studies are driven by the systematic evaluation of exploratory scenarios. Top-down approaches produce realistic scenarios rooted in the simulation of thermodynamic and dynamic processes represented in GCMs, but the internal resolution of these processes make it difficult to link vulnerabilities to discrete components of change. Bottom-up approaches link vulnerabilities to discrete components of change through the structured evaluation of exploratory scenarios, but the lack of insight rooted in climate change processes can lead to the development of implausible scenarios. This paper evaluates exploratory scenarios developed through thermodynamic and dynamical guided perturbations motivated by GCM-bound insights. The result is a hybrid approach that bridges a gap between top-down and bottom-up approaches. This yields several advantages. First, emerging vulnerabilities are linked to distinct thermodynamic and dynamic processes that are modeled in GCMs with differential likelihoods and plausible ranges of change. Second, the structured evaluation of process-informed exploratory scenarios link system vulnerabilities to distinct components of climate change. An illustrative case study demonstrates perturbations linked to thermodynamic and dynamical processes have a large impact on stakeholder-defined flood and drought performance, and the structured evaluation of process-informed exploratory scenarios find nuanced infrastructure-specific vulnerabilities that would be difficult to identify using an alternative approach.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"76 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142690869","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}
Muhammed Shikhani, Johannes Feldbauer, Robert Ladwig, Daniel Mercado-Bettín, Tadhg N. Moore, Artur Gevorgyan, Amalya Misakyan, Chenxi Mi, Martin Schultze, Bertram Boehrer, Tom Shatwell, Klemens Barfus, Karsten Rinke
Global warming is shifting the thermal dynamics of lakes, with resulting climatic variability heavily affecting their mixing dynamics. We present a dual ensemble workflow coupling climate models with lake models. We used a large set of simulations across multiple domains, multi-scenario, and multi GCM- RCM combinations from CORDEX data. We forced a set of multiple hydrodynamic lake models by these multiple climate simulations to explore climate change impacts on lakes. We also quantified the contributions from the different models to the overall uncertainty. We employed this workflow to investigate the effects of climate change on Lake Sevan (Armenia). We predicted for the end of the 21st century, under RCP 8.5, a sharp increase in surface temperature <span data-altimg="/cms/asset/a0dee58f-5cfc-4223-852a-a9175483d560/wrcr27552-math-0001.png"></span><mjx-container ctxtmenu_counter="179" ctxtmenu_oldtabindex="1" jax="CHTML" role="application" sre-explorer- style="font-size: 103%; position: relative;" tabindex="0"><mjx-math aria-hidden="true" location="graphic/wrcr27552-math-0001.png"><mjx-semantics><mjx-mrow data-semantic-children="8" data-semantic-content="0,9" data-semantic- data-semantic-role="leftright" data-semantic-speech="left parenthesis 4.3 plus or minus 0.7 normal upper K right parenthesis" data-semantic-type="fenced"><mjx-mo data-semantic- data-semantic-operator="fenced" data-semantic-parent="10" data-semantic-role="open" data-semantic-type="fence" style="margin-left: 0.056em; margin-right: 0.056em;"><mjx-c></mjx-c></mjx-mo><mjx-mrow data-semantic-children="1,7" data-semantic-content="2" data-semantic- data-semantic-parent="10" data-semantic-role="addition" data-semantic-type="infixop"><mjx-mn data-semantic-annotation="clearspeak:simple" data-semantic-font="normal" data-semantic- data-semantic-parent="8" data-semantic-role="float" data-semantic-type="number"><mjx-c></mjx-c><mjx-c></mjx-c><mjx-c></mjx-c></mjx-mn><mjx-mo data-semantic- data-semantic-operator="infixop,±" data-semantic-parent="8" data-semantic-role="addition" data-semantic-type="operator" rspace="4" space="4"><mjx-c></mjx-c></mjx-mo><mjx-mrow data-semantic-annotation="clearspeak:simple;clearspeak:unit" data-semantic-children="3,5" data-semantic-content="6" data-semantic- data-semantic-parent="8" data-semantic-role="implicit" data-semantic-type="infixop"><mjx-mn data-semantic-annotation="clearspeak:simple" data-semantic-font="normal" data-semantic- data-semantic-parent="7" data-semantic-role="float" data-semantic-type="number"><mjx-c></mjx-c><mjx-c></mjx-c><mjx-c></mjx-c></mjx-mn><mjx-mspace data-semantic- data-semantic-operator="infixop," data-semantic-parent="7" data-semantic-role="space" data-semantic-type="operator" style="width: 0.28em;"></mjx-mspace><mjx-mi data-semantic-annotation="clearspeak:simple" data-semantic-font="normal" data-semantic- data-semantic-parent="7" data-semantic-role="latinletter" data-semantic-type="identifier"><mjx-c></mjx-c></mjx-mi></mjx-mrow></
{"title":"Combining a Multi-Lake Model Ensemble and a Multi-Domain CORDEX Climate Data Ensemble for Assessing Climate Change Impacts on Lake Sevan","authors":"Muhammed Shikhani, Johannes Feldbauer, Robert Ladwig, Daniel Mercado-Bettín, Tadhg N. Moore, Artur Gevorgyan, Amalya Misakyan, Chenxi Mi, Martin Schultze, Bertram Boehrer, Tom Shatwell, Klemens Barfus, Karsten Rinke","doi":"10.1029/2023wr036511","DOIUrl":"https://doi.org/10.1029/2023wr036511","url":null,"abstract":"Global warming is shifting the thermal dynamics of lakes, with resulting climatic variability heavily affecting their mixing dynamics. We present a dual ensemble workflow coupling climate models with lake models. We used a large set of simulations across multiple domains, multi-scenario, and multi GCM- RCM combinations from CORDEX data. We forced a set of multiple hydrodynamic lake models by these multiple climate simulations to explore climate change impacts on lakes. We also quantified the contributions from the different models to the overall uncertainty. We employed this workflow to investigate the effects of climate change on Lake Sevan (Armenia). We predicted for the end of the 21st century, under RCP 8.5, a sharp increase in surface temperature <span data-altimg=\"/cms/asset/a0dee58f-5cfc-4223-852a-a9175483d560/wrcr27552-math-0001.png\"></span><mjx-container ctxtmenu_counter=\"179\" ctxtmenu_oldtabindex=\"1\" jax=\"CHTML\" role=\"application\" sre-explorer- style=\"font-size: 103%; position: relative;\" tabindex=\"0\"><mjx-math aria-hidden=\"true\" location=\"graphic/wrcr27552-math-0001.png\"><mjx-semantics><mjx-mrow data-semantic-children=\"8\" data-semantic-content=\"0,9\" data-semantic- data-semantic-role=\"leftright\" data-semantic-speech=\"left parenthesis 4.3 plus or minus 0.7 normal upper K right parenthesis\" data-semantic-type=\"fenced\"><mjx-mo data-semantic- data-semantic-operator=\"fenced\" data-semantic-parent=\"10\" data-semantic-role=\"open\" data-semantic-type=\"fence\" style=\"margin-left: 0.056em; margin-right: 0.056em;\"><mjx-c></mjx-c></mjx-mo><mjx-mrow data-semantic-children=\"1,7\" data-semantic-content=\"2\" data-semantic- data-semantic-parent=\"10\" data-semantic-role=\"addition\" data-semantic-type=\"infixop\"><mjx-mn data-semantic-annotation=\"clearspeak:simple\" data-semantic-font=\"normal\" data-semantic- data-semantic-parent=\"8\" data-semantic-role=\"float\" data-semantic-type=\"number\"><mjx-c></mjx-c><mjx-c></mjx-c><mjx-c></mjx-c></mjx-mn><mjx-mo data-semantic- data-semantic-operator=\"infixop,±\" data-semantic-parent=\"8\" data-semantic-role=\"addition\" data-semantic-type=\"operator\" rspace=\"4\" space=\"4\"><mjx-c></mjx-c></mjx-mo><mjx-mrow data-semantic-annotation=\"clearspeak:simple;clearspeak:unit\" data-semantic-children=\"3,5\" data-semantic-content=\"6\" data-semantic- data-semantic-parent=\"8\" data-semantic-role=\"implicit\" data-semantic-type=\"infixop\"><mjx-mn data-semantic-annotation=\"clearspeak:simple\" data-semantic-font=\"normal\" data-semantic- data-semantic-parent=\"7\" data-semantic-role=\"float\" data-semantic-type=\"number\"><mjx-c></mjx-c><mjx-c></mjx-c><mjx-c></mjx-c></mjx-mn><mjx-mspace data-semantic- data-semantic-operator=\"infixop,\" data-semantic-parent=\"7\" data-semantic-role=\"space\" data-semantic-type=\"operator\" style=\"width: 0.28em;\"></mjx-mspace><mjx-mi data-semantic-annotation=\"clearspeak:simple\" data-semantic-font=\"normal\" data-semantic- data-semantic-parent=\"7\" data-semantic-role=\"latinletter\" data-semantic-type=\"identifier\"><mjx-c></mjx-c></mjx-mi></mjx-mrow></","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"4 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142690870","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}
Kofi Ohemeng Kyei Prempeh, Parker William George, Pavel Bedrikovetsky
Upscaling of 1D two-phase flows in heterogeneous porous media is important in interpretation of laboratory coreflood data, streamline quasi 3D modeling, and numerical reservoir simulation. In 1D heterogeneous media with properties varying along the flow direction, phase permeabilities are coordinate-dependent. This yields the Buckley-Leverett equation with coordinate-dependent fractional flow f = f(s, x), which reflects the heterogeneity. So, an x-dependency is considered to reflect microscale heterogeneity and averaging over x—upscaling. This work aims to average or upscale the heterogeneous system to obtain the homogenized media with such fractional flow function F(S) that provides the same water-cut history at the reservoir outlet, x = 1. Thus, F(S) is an equivalent property of the medium. So far, the exact upscaling for 1D micro heterogeneous systems has not been derived. With the x-dependency of fractional flow, the Riemann invariant is flux f, which yields exact integration of 1D flow problems. The novel exact solutions are derived for flows with continuous saturation profile, transition of shock into continuous wave, transition of continuous wave into shock, and transport in heterogeneous piecewise-uniform rocks. The exact procedure of upscaling from f = f(s, x) to F(S) is as follows: the inverse function to the upscaled F(S) is equal to the averaged saturation over x of the inverse microscale function s = f−1(f, x). It was found that the Welge's method as applied to heterogeneous cores provides the upscaled F(S). For characteristic finite-difference scheme, the fluxes for microscale and upscaled-numerical-cell systems, coincide in all grid nodes.
将异质多孔介质中的一维两相流放大，对于解释实验室岩心注水数据、简化准三维建模和油藏数值模拟非常重要。在性质沿流动方向变化的一维异质介质中，相渗透率与坐标有关。这就产生了 Buckley-Leverett 方程，其中的分数流量 f = f(s, x)与坐标相关，反映了异质性。因此，我们认为 x 依赖性反映了微尺度异质性和 x 放大平均。这项工作的目的是对异质系统进行平均或放大，以获得具有这种分数流量函数 F(S) 的均质介质，从而在水库出口（x = 1）处提供相同的断水历史。因此，F(S) 是介质的等效属性。到目前为止，还没有推导出一维微观异质系统的精确放大模型。由于分数流的 x 依赖性，黎曼不变式是通量 f，这就产生了一维流动问题的精确积分。对于具有连续饱和剖面的流动、冲击波向连续波的过渡、连续波向冲击波的过渡以及异质片状均匀岩石中的输运，推导出了新的精确解。从 f = f(s, x) 放大到 F(S) 的精确过程如下：放大后的 F(S) 的反函数等于反微尺度函数 s = f -1(f, x) 在 x 上的平均饱和度。研究发现，应用于异质磁芯的 Welge 方法可提供放大的 F(S)。对于特征有限差分方案，微尺度和放大数值单元系统的通量在所有网格节点上都是一致的。
{"title":"Exact Solutions and Upscaling for 1D Two-Phase Flow in Heterogeneous Porous Media","authors":"Kofi Ohemeng Kyei Prempeh, Parker William George, Pavel Bedrikovetsky","doi":"10.1029/2024wr037917","DOIUrl":"https://doi.org/10.1029/2024wr037917","url":null,"abstract":"Upscaling of 1D two-phase flows in heterogeneous porous media is important in interpretation of laboratory coreflood data, streamline quasi 3D modeling, and numerical reservoir simulation. In 1D heterogeneous media with properties varying along the flow direction, phase permeabilities are coordinate-dependent. This yields the Buckley-Leverett equation with coordinate-dependent fractional flow <i>f = f</i>(<i>s, x</i>), which reflects the heterogeneity. So, an <i>x</i>-dependency is considered to reflect microscale heterogeneity and averaging over <i>x</i>—upscaling. This work aims to average or upscale the heterogeneous system to obtain the homogenized media with such fractional flow function <i>F</i>(<i>S</i>) that provides the same water-cut history at the reservoir outlet, <i>x</i> = 1. Thus, <i>F</i>(<i>S</i>) is an equivalent property of the medium. So far, the exact upscaling for 1D micro heterogeneous systems has not been derived. With the <i>x</i>-dependency of fractional flow, the Riemann invariant is flux <i>f</i>, which yields exact integration of 1D flow problems. The novel exact solutions are derived for flows with continuous saturation profile, transition of shock into continuous wave, transition of continuous wave into shock, and transport in heterogeneous piecewise-uniform rocks. The exact procedure of upscaling from <i>f = f</i>(<i>s, x</i>) to <i>F</i>(<i>S</i>) is as follows: the inverse function to the upscaled <i>F</i>(<i>S</i>) is equal to the averaged saturation over <i>x</i> of the inverse microscale function <i>s = f</i> <sup>−1</sup>(<i>f, x</i>). It was found that the Welge's method as applied to heterogeneous cores provides the upscaled <i>F</i>(<i>S</i>). For characteristic finite-difference scheme, the fluxes for microscale and upscaled-numerical-cell systems, coincide in all grid nodes.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"15 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142690889","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}
Chi Zhang, Zhe Zhu, Yu Li, Erhu Du, Yan Sun, Zhihong Liu
Data uncertainty affects the accuracy of pollution source detection (PSD), particularly in the background of low-cost water quality sensing and low-accuracy data challenge. This study aims to develop a novel PSD method to use low-accuracy sensor data, namely, the method of coupled forward data Assimilation and inverse Optimization in PSD (A&O-PSD). This approach primarily employs filtering strategies to handle observation errors and extract hidden trend information during forward water quality data assimilation, and then optimal estimation of pollution source information through inverse optimization with enhanced trend information matching, avoiding the non-Gaussian distribution challenge of pollution source information. Both real-world pollution events and semi-synthetic cases were used to evaluate the methodology and compare its performance with the traditional optimization approach (T-PSD). The results indicated that T-PSD is significantly affected by observational and parameter noise, engendering noticeable biases in PSD under the low-accuracy sensor conditions. In contrast, the A&O-PSD could accomplish the estimation task of PSD in real-world pollution events, with improved robustness against noise interference. Furthermore, A&O-PSD achieved an accuracy improvement of over 10% compared to T-PSD in estimating pollution source locations within the typical noise distribution range of most low-accuracy sensors currently available, making it possible to use low-accuracy data that would otherwise be unusable in T-PSD. Overall, the A&O-PSD method, combined with low-cost low-accuracy water quality sensing, offers an effective solution for watershed environmental management.
{"title":"Pollution Source Detection With Low-Cost Low-Accuracy Sensors Through Coupling Forward Data Assimilation and Inverse Optimization","authors":"Chi Zhang, Zhe Zhu, Yu Li, Erhu Du, Yan Sun, Zhihong Liu","doi":"10.1029/2023wr036834","DOIUrl":"https://doi.org/10.1029/2023wr036834","url":null,"abstract":"Data uncertainty affects the accuracy of pollution source detection (PSD), particularly in the background of low-cost water quality sensing and low-accuracy data challenge. This study aims to develop a novel PSD method to use low-accuracy sensor data, namely, the method of coupled forward data Assimilation and inverse Optimization in PSD (A&O-PSD). This approach primarily employs filtering strategies to handle observation errors and extract hidden trend information during forward water quality data assimilation, and then optimal estimation of pollution source information through inverse optimization with enhanced trend information matching, avoiding the non-Gaussian distribution challenge of pollution source information. Both real-world pollution events and semi-synthetic cases were used to evaluate the methodology and compare its performance with the traditional optimization approach (T-PSD). The results indicated that T-PSD is significantly affected by observational and parameter noise, engendering noticeable biases in PSD under the low-accuracy sensor conditions. In contrast, the A&O-PSD could accomplish the estimation task of PSD in real-world pollution events, with improved robustness against noise interference. Furthermore, A&O-PSD achieved an accuracy improvement of over 10% compared to T-PSD in estimating pollution source locations within the typical noise distribution range of most low-accuracy sensors currently available, making it possible to use low-accuracy data that would otherwise be unusable in T-PSD. Overall, the A&O-PSD method, combined with low-cost low-accuracy water quality sensing, offers an effective solution for watershed environmental management.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"15 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142690825","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}
Yunxiang Chen, Jie Bao, Rongyao Chen, Bing Li, Yuan Yang, Lupita Renteria, Dillman Delgado, Brieanne Forbes, Amy E. Goldman, Manasi Simhan, Morgan E. Barnes, Maggi Laan, Sophia McKever, Z. Jason Hou, Xingyuan Chen, Timothy Scheibe, James Stegen
Streambed grain sizes control river hydro-biogeochemical (HBGC) processes and functions. However, measuring their quantities, distributions, and uncertainties is challenging due to the diversity and heterogeneity of natural streams. This work presents a photo-driven, artificial intelligence (AI)-enabled, and theory-based workflow for extracting the quantities, distributions, and uncertainties of streambed grain sizes from photos. Specifically, we first trained You Only Look Once, an object detection AI, using 11,977 grain labels from 36 photos collected from nine different stream environments. We demonstrated its accuracy with a coefficient of determination of 0.98, a Nash–Sutcliffe efficiency of 0.98, and a mean absolute relative error of 6.65% in predicting the median grain size of 20 ground-truth photos representing nine typical stream environments. The AI is then used to extract the grain size distributions and determine their characteristic grain sizes, including the 10th, 50th, 60th, and 84th percentiles, for 1,999 photos taken at 66 sites within a watershed in the Northwest US. The results indicate that the 10th, median, 60th, and 84th percentiles of the grain sizes follow log-normal distributions, with most likely values of 2.49, 6.62, 7.68, and 10.78 cm, respectively. The average uncertainties associated with these values are 9.70%, 7.33%, 9.27%, and 11.11%, respectively. These data allow for the computation of the quantities, distributions, and uncertainties of streambed HBGC parameters, including Manning's coefficient, Darcy-Weisbach friction factor, top layer interstitial velocity magnitude, and nitrate uptake velocity. Additionally, major sources of uncertainty in grain sizes and their impact on HBGC parameters are examined.
{"title":"Quantifying Streambed Grain Size, Uncertainty, and Hydrobiogeochemical Parameters Using Machine Learning Model YOLO","authors":"Yunxiang Chen, Jie Bao, Rongyao Chen, Bing Li, Yuan Yang, Lupita Renteria, Dillman Delgado, Brieanne Forbes, Amy E. Goldman, Manasi Simhan, Morgan E. Barnes, Maggi Laan, Sophia McKever, Z. Jason Hou, Xingyuan Chen, Timothy Scheibe, James Stegen","doi":"10.1029/2023wr036456","DOIUrl":"https://doi.org/10.1029/2023wr036456","url":null,"abstract":"Streambed grain sizes control river hydro-biogeochemical (HBGC) processes and functions. However, measuring their quantities, distributions, and uncertainties is challenging due to the diversity and heterogeneity of natural streams. This work presents a photo-driven, artificial intelligence (AI)-enabled, and theory-based workflow for extracting the quantities, distributions, and uncertainties of streambed grain sizes from photos. Specifically, we first trained You Only Look Once, an object detection AI, using 11,977 grain labels from 36 photos collected from nine different stream environments. We demonstrated its accuracy with a coefficient of determination of 0.98, a Nash–Sutcliffe efficiency of 0.98, and a mean absolute relative error of 6.65% in predicting the median grain size of 20 ground-truth photos representing nine typical stream environments. The AI is then used to extract the grain size distributions and determine their characteristic grain sizes, including the 10th, 50th, 60th, and 84th percentiles, for 1,999 photos taken at 66 sites within a watershed in the Northwest US. The results indicate that the 10th, median, 60th, and 84th percentiles of the grain sizes follow log-normal distributions, with most likely values of 2.49, 6.62, 7.68, and 10.78 cm, respectively. The average uncertainties associated with these values are 9.70%, 7.33%, 9.27%, and 11.11%, respectively. These data allow for the computation of the quantities, distributions, and uncertainties of streambed HBGC parameters, including Manning's coefficient, Darcy-Weisbach friction factor, top layer interstitial velocity magnitude, and nitrate uptake velocity. Additionally, major sources of uncertainty in grain sizes and their impact on HBGC parameters are examined.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"99 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142673042","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}
A. Bertagnoli, C. Luce, R. van Kampen, U. Schneidewind, M. van Berkel, A. W. Tranmer, G. Vandersteen, S. Krause, D. Tonina
iFLOW is a free, open-source, and python-based framework and graphical user interface to visualize and analyze temperature time series, and extract one dimensional thermal velocity, vT, and bulk effective thermal diffusivity, ke. Information of thermal properties of the sediment-water mixture (bulk) and water allows quantifying the one-dimensional Darcian flux, q, and seepage velocity, v, from vT. Available software packages were developed to quantify q and ke only based on a specific mathematical model or focused on specific data processing or parameter estimation techniques, and all these steps were lumped together preventing users to identify potential source of errors. iFLOW proposes a novel organizational philosophy with a modular framework that parses the analysis process into three fundamental steps: (a) the mathematical model, (b) signal processing, and (c) parameter estimation. iFLOW houses a suite of models and analysis techniques. This suite can be readily added to and expanded through its modular framework. iFLOW contains a wizard to guide users through the selection process with respect to the three fundamental steps. Users can analyze and visualize intermediate results to identify problematic issues in the time series data and improve data interpretation. Here, we present iFLOW and summarize its performance using a set of one-dimensional synthetic heat transport simulations.
{"title":"iFLOW: A Framework and GUI to Quantify Effective Thermal Diffusivity and Advection in Permeable Materials From Temperature Time Series","authors":"A. Bertagnoli, C. Luce, R. van Kampen, U. Schneidewind, M. van Berkel, A. W. Tranmer, G. Vandersteen, S. Krause, D. Tonina","doi":"10.1029/2024wr037370","DOIUrl":"https://doi.org/10.1029/2024wr037370","url":null,"abstract":"iFLOW is a free, open-source, and python-based framework and graphical user interface to visualize and analyze temperature time series, and extract one dimensional thermal velocity, <i>v</i><sub><i>T</i></sub>, and bulk effective thermal diffusivity, <i>k</i><sub>e</sub>. Information of thermal properties of the sediment-water mixture (bulk) and water allows quantifying the one-dimensional Darcian flux, <i>q</i>, and seepage velocity, <i>v</i>, from <i>v</i><sub><i>T</i></sub>. Available software packages were developed to quantify <i>q</i> and <i>k</i><sub><i>e</i></sub> only based on a specific mathematical model or focused on specific data processing or parameter estimation techniques, and all these steps were lumped together preventing users to identify potential source of errors. iFLOW proposes a novel organizational philosophy with a modular framework that parses the analysis process into three fundamental steps: (a) the mathematical model, (b) signal processing, and (c) parameter estimation. iFLOW houses a suite of models and analysis techniques. This suite can be readily added to and expanded through its modular framework. iFLOW contains a wizard to guide users through the selection process with respect to the three fundamental steps. Users can analyze and visualize intermediate results to identify problematic issues in the time series data and improve data interpretation. Here, we present iFLOW and summarize its performance using a set of one-dimensional synthetic heat transport simulations.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"69 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142673068","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}
Many major cities worldwide have inevitably experienced excessive groundwater pumping due to growing demands for freshwater in urban development. To mitigate land subsidence problems during urbanization, various regulations have been adopted to control groundwater usage. This study examines the transition in the post-subsidence stage, especially in metropolitan areas, to adaptively adjust subsidence prevention strategies for effective groundwater management. Taking the Taipei Basin as an example, historical data reveals significant subsidence of more than 2 m during early urban development, with subsidence hazards largely mitigated over decades. However, the rising groundwater level poses a risk to the stability of engineering excavations. In this study, 29 X-band Cosmo-Skymed constellation (CSK) images were utilized with the Persistent Scatterer InSAR (PSInSAR/PSI) technique to monitor surface displacements during the construction of the Mass Rapid Transit system. Correlating groundwater levels helps identify the heterogeneous hydrogeological environment, and the potential groundwater capacity is assessed. PSI time-series reveal that approximately 2 cm of recoverable land displacements correspond to groundwater fluctuations in the confined aquifer, indicative of the typically elastic behavior of the resilient aquifer system. The estimated groundwater storage variation is about 1.6 million cubic meters, suggesting this potential groundwater capacity could provide available water resources with proper management. Additionally, engineering excavation safety can be ensured with lowered groundwater levels. This study emphasizes the need to balance groundwater resource use with urban development by adjusting subsidence prevention and control strategies to achieve sustainable water management in the post-subsidence stage.
{"title":"Assessing Potential Groundwater Storage Capacity for Sustainable Groundwater Management in the Transitioning Post-Subsidence Metropolitan Area","authors":"Shao-Hung Lin, Jyr-Ching Hu, Shih-Jung Wang","doi":"10.1029/2023wr036951","DOIUrl":"https://doi.org/10.1029/2023wr036951","url":null,"abstract":"Many major cities worldwide have inevitably experienced excessive groundwater pumping due to growing demands for freshwater in urban development. To mitigate land subsidence problems during urbanization, various regulations have been adopted to control groundwater usage. This study examines the transition in the post-subsidence stage, especially in metropolitan areas, to adaptively adjust subsidence prevention strategies for effective groundwater management. Taking the Taipei Basin as an example, historical data reveals significant subsidence of more than 2 m during early urban development, with subsidence hazards largely mitigated over decades. However, the rising groundwater level poses a risk to the stability of engineering excavations. In this study, 29 X-band Cosmo-Skymed constellation (CSK) images were utilized with the Persistent Scatterer InSAR (PSInSAR/PSI) technique to monitor surface displacements during the construction of the Mass Rapid Transit system. Correlating groundwater levels helps identify the heterogeneous hydrogeological environment, and the potential groundwater capacity is assessed. PSI time-series reveal that approximately 2 cm of recoverable land displacements correspond to groundwater fluctuations in the confined aquifer, indicative of the typically elastic behavior of the resilient aquifer system. The estimated groundwater storage variation is about 1.6 million cubic meters, suggesting this potential groundwater capacity could provide available water resources with proper management. Additionally, engineering excavation safety can be ensured with lowered groundwater levels. This study emphasizes the need to balance groundwater resource use with urban development by adjusting subsidence prevention and control strategies to achieve sustainable water management in the post-subsidence stage.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"56 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142670376","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}
Jan Vinogradov, Miftah Hidayat, Mohammad Sarmadivaleh, David Vega-Maza, Stefan Iglauer, Lijuan Zhang, Dajiang Mei, Jos Derksen
Although CO2 geological storage (CGS) is thought to be one of the most promising technologies to sequester the anthropogenic CO2 to mitigate the climate change, implementation of the method is still challenging due to lack of fundamental understanding of controls of wettability, which is responsible for residual trapping of the gas and its flow dynamics. One of the key parameters that controls the wetting state is the zeta potential, ζ, at rock-water and CO2-water interfaces. ζ in systems comprising rocks, carbonated aqueous solutions and immiscible supercritical CO2 have not been measured prior to this study, where we detail the experimental protocol that enables measuring ζ in such systems, and report novel experimental data on the multi-phase ζ. We also demonstrate for the first time that ζ of supercritical CO2-water interface is negative with a magnitude greater that 14 mV. Moreover, our experimental results suggest that presence of multi-valent cations in tested solutions causes a shift of wettability toward intermediate-wet state. We introduce a new parameter that combines multi-phase ζ and relative permeability endpoints to characterize the wetting state and residual supercritical CO2 saturation. Based on these results, we demonstrate that ζ measurements could serve as a powerful experimental method for predicting CGS efficiency and/or for designing injection of aqueous solutions with bespoke composition prior to implementing CGS to improve the residual CO2 trapping in sandstone formations.
{"title":"Zeta Potential of Supercritical CO2-Water-Sandstone Systems and Its Correlation With Wettability and Residual Subsurface Trapping of CO2","authors":"Jan Vinogradov, Miftah Hidayat, Mohammad Sarmadivaleh, David Vega-Maza, Stefan Iglauer, Lijuan Zhang, Dajiang Mei, Jos Derksen","doi":"10.1029/2023wr036698","DOIUrl":"https://doi.org/10.1029/2023wr036698","url":null,"abstract":"Although CO<sub>2</sub> geological storage (CGS) is thought to be one of the most promising technologies to sequester the anthropogenic CO<sub>2</sub> to mitigate the climate change, implementation of the method is still challenging due to lack of fundamental understanding of controls of wettability, which is responsible for residual trapping of the gas and its flow dynamics. One of the key parameters that controls the wetting state is the zeta potential, <i>ζ</i>, at rock-water and CO<sub>2</sub>-water interfaces. <i>ζ</i> in systems comprising rocks, carbonated aqueous solutions and immiscible supercritical CO<sub>2</sub> have not been measured prior to this study, where we detail the experimental protocol that enables measuring <i>ζ</i> in such systems, and report novel experimental data on the multi-phase <i>ζ</i>. We also demonstrate for the first time that <i>ζ</i> of supercritical CO<sub>2</sub>-water interface is negative with a magnitude greater that 14 mV. Moreover, our experimental results suggest that presence of multi-valent cations in tested solutions causes a shift of wettability toward intermediate-wet state. We introduce a new parameter that combines multi-phase <i>ζ</i> and relative permeability endpoints to characterize the wetting state and residual supercritical CO<sub>2</sub> saturation. Based on these results, we demonstrate that <i>ζ</i> measurements could serve as a powerful experimental method for predicting CGS efficiency and/or for designing injection of aqueous solutions with bespoke composition prior to implementing CGS to improve the residual CO<sub>2</sub> trapping in sandstone formations.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"6 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2024-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142665233","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}
Zhen Zhou, Laura Riis-Klinkvort, Emilie Ahrnkiel Jørgensen, Christine Lindenhoff, Monica Coppo Frías, Alexander Rietz Vesterhauge, Daniel Haugård Olesen, Makar Lavish, Alexey Dobrovolskiy, Alexey Kadek, Niksa Orlic, Tomislav Grubesa, Luka Drmić, Henrik Grosen, Sune Nielsen, Daniel Wennerberg, Viktor Fagerström, Jenny Axén, David Gustafsson, Peter Bauer-Gottwein
Using Unoccupied Aerial Systems (UAS) equipped with optical RGB cameras and Doppler radar, surface velocity can be efficiently measured at high spatial resolution. UAS-borne Doppler radar is particularly attractive because it is suitable for real-time velocity determination, because the measurement is contactless, and because it has fewer limitations than image velocimetry techniques. In this paper, five cross-sections (XSs) were surveyed within a 10 km stretch of Rönne River in Sweden. Ground-truth surface velocity observations were retrieved with an electromagnetic velocity sensor (OTT MF Pro) along the XS at one m spacing. Videos from a UAS RGB camera were analyzed using both Particle Image Velocimetry (PIV) and Space-Time Image Velocimetry (STIV) techniques. Furthermore, we recorded full waveform signal data using a Doppler radar at multiple waypoints across the river. An algorithm fits two alternative models to the average amplitude curve to derive the correct river surface velocity based on Gaussian models with: (a) one peak, and (b) two peaks. Results indicate that river flow velocity and propwash velocity caused by the drone can be found in XS where the flow velocity is low, while the drone-induced propwash velocity can be neglected in fast and highly turbulent flows. To verify the river flow velocity derived from Doppler radar, a mean PIV value within the footprint of the Doppler radar at each waypoint was calculated. Finally, quantitative comparisons of OTT MF Pro data with STIV, mean PIV and Doppler radar revealed that UAS-borne Doppler radar could reliably measure the river surface velocity.
{"title":"Measuring River Surface Velocity Using UAS-Borne Doppler Radar","authors":"Zhen Zhou, Laura Riis-Klinkvort, Emilie Ahrnkiel Jørgensen, Christine Lindenhoff, Monica Coppo Frías, Alexander Rietz Vesterhauge, Daniel Haugård Olesen, Makar Lavish, Alexey Dobrovolskiy, Alexey Kadek, Niksa Orlic, Tomislav Grubesa, Luka Drmić, Henrik Grosen, Sune Nielsen, Daniel Wennerberg, Viktor Fagerström, Jenny Axén, David Gustafsson, Peter Bauer-Gottwein","doi":"10.1029/2024wr037375","DOIUrl":"https://doi.org/10.1029/2024wr037375","url":null,"abstract":"Using Unoccupied Aerial Systems (UAS) equipped with optical RGB cameras and Doppler radar, surface velocity can be efficiently measured at high spatial resolution. UAS-borne Doppler radar is particularly attractive because it is suitable for real-time velocity determination, because the measurement is contactless, and because it has fewer limitations than image velocimetry techniques. In this paper, five cross-sections (XSs) were surveyed within a 10 km stretch of Rönne River in Sweden. Ground-truth surface velocity observations were retrieved with an electromagnetic velocity sensor (OTT MF Pro) along the XS at one m spacing. Videos from a UAS RGB camera were analyzed using both Particle Image Velocimetry (PIV) and Space-Time Image Velocimetry (STIV) techniques. Furthermore, we recorded full waveform signal data using a Doppler radar at multiple waypoints across the river. An algorithm fits two alternative models to the average amplitude curve to derive the correct river surface velocity based on Gaussian models with: (a) one peak, and (b) two peaks. Results indicate that river flow velocity and propwash velocity caused by the drone can be found in XS where the flow velocity is low, while the drone-induced propwash velocity can be neglected in fast and highly turbulent flows. To verify the river flow velocity derived from Doppler radar, a mean PIV value within the footprint of the Doppler radar at each waypoint was calculated. Finally, quantitative comparisons of OTT MF Pro data with STIV, mean PIV and Doppler radar revealed that UAS-borne Doppler radar could reliably measure the river surface velocity.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"6 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142645886","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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