The Saint-Venant equations are numerically solved to simulate free surface flows in one dimension. A Riemann solver is needed to compute the numerical flux for capturing shocks and flow discontinuities occurring in flow situations such as hydraulic jump, dam-break wave propagation, or bore wave propagation. A Riemann solver that captures shocks and flow discontinuities is not yet reported to be implemented within the framework of a meshless method for solving the Saint-Venant equations. Therefore, a wide range of free surface flow problems cannot be simulated by the available meshless methods. In this study, a shock-capturing meshless method is proposed for simulating one-dimensional (1D) flows on a highly variable topography. The Harten–Lax–van Leer Riemann solver is used for computing the convective flux in the proposed meshless method. Spatial derivatives in the Saint-Venant equations and the reconstruction of conservative variables for flux terms are computed using a weighted least square approximation. The proposed method is tested for various numerically challenging problems and laboratory experiments on different flow regimes. The proposed highly accurate shock-capturing meshless method has the potential to be extended to solve the two-dimensional (2D) shallow water equations without any mesh requirements.
{"title":"A shock-capturing meshless method for solving the one-dimensional Saint-Venant equations on a highly variable topography","authors":"D. Satyaprasad, S. N. Kuiry, S. Sundar","doi":"10.2166/hydro.2023.164","DOIUrl":"https://doi.org/10.2166/hydro.2023.164","url":null,"abstract":"\u0000 The Saint-Venant equations are numerically solved to simulate free surface flows in one dimension. A Riemann solver is needed to compute the numerical flux for capturing shocks and flow discontinuities occurring in flow situations such as hydraulic jump, dam-break wave propagation, or bore wave propagation. A Riemann solver that captures shocks and flow discontinuities is not yet reported to be implemented within the framework of a meshless method for solving the Saint-Venant equations. Therefore, a wide range of free surface flow problems cannot be simulated by the available meshless methods. In this study, a shock-capturing meshless method is proposed for simulating one-dimensional (1D) flows on a highly variable topography. The Harten–Lax–van Leer Riemann solver is used for computing the convective flux in the proposed meshless method. Spatial derivatives in the Saint-Venant equations and the reconstruction of conservative variables for flux terms are computed using a weighted least square approximation. The proposed method is tested for various numerically challenging problems and laboratory experiments on different flow regimes. The proposed highly accurate shock-capturing meshless method has the potential to be extended to solve the two-dimensional (2D) shallow water equations without any mesh requirements.","PeriodicalId":54801,"journal":{"name":"Journal of Hydroinformatics","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2023-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43717233","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Alovya Ahmed Chowdhury, G. Kesserwani, C. Rougé, P. Richmond
Wavelet-based grid resolution adaptation driven by the ‘multiresolution analysis’ (MRA) of the Haar wavelet (HW) allows to devise an adaptive first-order finite volume (FV1) model (HWFV1) that can readily preserve the modelling fidelity of its reference uniform-grid FV1 counterpart. However, the MRA entails an enormous computational effort as it involves ‘encoding’ (coarsening), ‘decoding’ (refining), analysing and traversing modelled data across a deep hierarchy of nested, uniform grids. GPU-parallelisation of the MRA is needed to handle its computational effort, but its algorithmic structure (1) hinders coalesced memory access on the GPU and (2) involves an inherently sequential tree traversal problem. This work redesigns the algorithmic structure of the MRA in order to parallelise it on the GPU, addressing (1) by applying Z-order space-filling curves and (2) by adopting a parallel tree traversal algorithm. This results in a GPU-parallelised HWFV1 model (GPU-HWFV1). GPU-HWFV1 is verified against its CPU predecessor (CPU-HWFV1) and its GPU-parallelised reference uniform-grid counterpart (GPU-FV1) over five shallow water flow test cases. GPU-HWFV1 preserves the modelling fidelity of GPU-FV1 while being up to 30 times faster. Compared to CPU-HWFV1, it is up to 200 times faster, suggesting that the GPU-parallelised MRA could be used to speed up other FV1 models.
{"title":"GPU-parallelisation of Haar wavelet-based grid resolution adaptation for fast finite volume modelling: application to shallow water flows","authors":"Alovya Ahmed Chowdhury, G. Kesserwani, C. Rougé, P. Richmond","doi":"10.2166/hydro.2023.154","DOIUrl":"https://doi.org/10.2166/hydro.2023.154","url":null,"abstract":"\u0000 Wavelet-based grid resolution adaptation driven by the ‘multiresolution analysis’ (MRA) of the Haar wavelet (HW) allows to devise an adaptive first-order finite volume (FV1) model (HWFV1) that can readily preserve the modelling fidelity of its reference uniform-grid FV1 counterpart. However, the MRA entails an enormous computational effort as it involves ‘encoding’ (coarsening), ‘decoding’ (refining), analysing and traversing modelled data across a deep hierarchy of nested, uniform grids. GPU-parallelisation of the MRA is needed to handle its computational effort, but its algorithmic structure (1) hinders coalesced memory access on the GPU and (2) involves an inherently sequential tree traversal problem. This work redesigns the algorithmic structure of the MRA in order to parallelise it on the GPU, addressing (1) by applying Z-order space-filling curves and (2) by adopting a parallel tree traversal algorithm. This results in a GPU-parallelised HWFV1 model (GPU-HWFV1). GPU-HWFV1 is verified against its CPU predecessor (CPU-HWFV1) and its GPU-parallelised reference uniform-grid counterpart (GPU-FV1) over five shallow water flow test cases. GPU-HWFV1 preserves the modelling fidelity of GPU-FV1 while being up to 30 times faster. Compared to CPU-HWFV1, it is up to 200 times faster, suggesting that the GPU-parallelised MRA could be used to speed up other FV1 models.","PeriodicalId":54801,"journal":{"name":"Journal of Hydroinformatics","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2023-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46855391","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nowadays, the conflict between the supply and demand of water resources in many regions is becoming increasingly prominent. Scientific allocation of regional water resources has become the key to solving the contradiction. In this study, a regional multi-objective water resources optimization allocation model considering social, economic, and ecological objectives is established, and four improvement spots are introduced to the sparrow search algorithm (SSA) to form an improved sparrow search algorithm (ISSA). By testing nine benchmark functions including monotonic and multi-peaked, the search efficiency and average convergence results of ISSA are significantly enhanced compared with other intelligent algorithms. Meanwhile, this research uses Luanchuan County, Henan Province, China, as an example to solve the water resource allocation scheme for 2025 and 2030 in the region using ISSA. The results show that the overall water shortage rate decreases to 3.49 and 2.79%, respectively, under the 75% guarantee rate, resulting in an effective reduction in future water shortages. Simultaneously, the scheme proposed has sound comprehensive benefits and can provide important technical support for the refined management of water resources, which is a reference and guidance for solving the contradiction between water supply and demand at the current stage.
{"title":"Research on multi-objective optimal allocation of regional water resources based on improved sparrow search algorithm","authors":"Zhiyuan Yao, Zhaocai Wang, Xuefei Cui, Haifeng Zhao","doi":"10.2166/hydro.2023.037","DOIUrl":"https://doi.org/10.2166/hydro.2023.037","url":null,"abstract":"\u0000 \u0000 Nowadays, the conflict between the supply and demand of water resources in many regions is becoming increasingly prominent. Scientific allocation of regional water resources has become the key to solving the contradiction. In this study, a regional multi-objective water resources optimization allocation model considering social, economic, and ecological objectives is established, and four improvement spots are introduced to the sparrow search algorithm (SSA) to form an improved sparrow search algorithm (ISSA). By testing nine benchmark functions including monotonic and multi-peaked, the search efficiency and average convergence results of ISSA are significantly enhanced compared with other intelligent algorithms. Meanwhile, this research uses Luanchuan County, Henan Province, China, as an example to solve the water resource allocation scheme for 2025 and 2030 in the region using ISSA. The results show that the overall water shortage rate decreases to 3.49 and 2.79%, respectively, under the 75% guarantee rate, resulting in an effective reduction in future water shortages. Simultaneously, the scheme proposed has sound comprehensive benefits and can provide important technical support for the refined management of water resources, which is a reference and guidance for solving the contradiction between water supply and demand at the current stage.","PeriodicalId":54801,"journal":{"name":"Journal of Hydroinformatics","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2023-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41696408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The growing use of global-scale environmental products in hydro-climatic modeling has increased the variety of their applications and the complications of their uncertainties and evaluations. Researchers have recently turned to statistical blending of these products to achieve optimal modeling. The proposed statistical blending in this study includes five large-scale and satellite precipitation (CHIRPS, ERA5-Land of ECMWF, GPM (IMERG), TRMM, and Terra) and evapotranspiration (GLEAM, SSEBop, MODIS, Terra, and ERA) products committed in three modeling scenarios. The blending procedures are organized using a conceptual water balance model to achieve the best precipitation and evapotranspiration results for the conceptual production of streamflow using hydrological inverse modeling. Based on the results, the proposed blending procedures of precipitation and evapotranspiration improved the performance of the model using different statistical metrics. In addition, the results show the conformity of the pattern and behavior of the blended precipitation calculated using the moving least square method in the study area. This happened by changing the estimation based on in situ values, particularly in cold months considering the orographic/snow effects. The combining method provides a good fusion procedure to improve the realistic estimation of precipitation and evapotranspiration in ungagged watersheds as well.
{"title":"Statistical blending of global-gridded climatological products: an approach to inverse hydrological model","authors":"Rahimeh Mousavi, M. Nasseri, S. Abbasi","doi":"10.2166/hydro.2023.141","DOIUrl":"https://doi.org/10.2166/hydro.2023.141","url":null,"abstract":"\u0000 The growing use of global-scale environmental products in hydro-climatic modeling has increased the variety of their applications and the complications of their uncertainties and evaluations. Researchers have recently turned to statistical blending of these products to achieve optimal modeling. The proposed statistical blending in this study includes five large-scale and satellite precipitation (CHIRPS, ERA5-Land of ECMWF, GPM (IMERG), TRMM, and Terra) and evapotranspiration (GLEAM, SSEBop, MODIS, Terra, and ERA) products committed in three modeling scenarios. The blending procedures are organized using a conceptual water balance model to achieve the best precipitation and evapotranspiration results for the conceptual production of streamflow using hydrological inverse modeling. Based on the results, the proposed blending procedures of precipitation and evapotranspiration improved the performance of the model using different statistical metrics. In addition, the results show the conformity of the pattern and behavior of the blended precipitation calculated using the moving least square method in the study area. This happened by changing the estimation based on in situ values, particularly in cold months considering the orographic/snow effects. The combining method provides a good fusion procedure to improve the realistic estimation of precipitation and evapotranspiration in ungagged watersheds as well.","PeriodicalId":54801,"journal":{"name":"Journal of Hydroinformatics","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2023-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46660639","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
There is a lag between the latest development of the heuristic algorithm and its application in environmental model calibration. Besides, heuristic algorithms are usually thought to be deterministic and can hardly account for the equifinality of different parameters. To fix these limitations, we proposed a novel elite opposition-modified moth-flame optimizer (EOMFO) and presented a scheme combining it with the frequency statistical method for auto-calibration and prediction uncertainty estimation. A case study of a hydraulic-water quality coupling model was provided, in which the urban non-point source ammonia nitrogen (NH3-N) and total phosphorus (TP) were simulated. Compared with the benchmark particle swarm optimizer (PSO) and MFO, EOMFO has better global optimization ability and can obtain behavioral samples with higher quality for sensitive parameters. Regarding the calibration performance, EOMFO performed well in both the NH3-N and TP simulations (Nash–Sutcliffe efficiency around or greater than 0.5 and R greater than 0.7) and outperformed benchmark algorithms for both the deterministic prediction and uncertainty band prediction. The generated uncertainty band bracketed the majority of TP observation points, although it is not in good agreement with NH3-N observations due to several potential reasons. With this scheme, a more efficient and robust calibration process is expected.
{"title":"Calibration and prediction uncertainty analysis of a hydraulic-water quality coupling model using a modified moth-flame optimizer","authors":"Qianyang Wang, Jingshan Yu, Xueyu Zhang","doi":"10.2166/hydro.2023.039","DOIUrl":"https://doi.org/10.2166/hydro.2023.039","url":null,"abstract":"\u0000 \u0000 There is a lag between the latest development of the heuristic algorithm and its application in environmental model calibration. Besides, heuristic algorithms are usually thought to be deterministic and can hardly account for the equifinality of different parameters. To fix these limitations, we proposed a novel elite opposition-modified moth-flame optimizer (EOMFO) and presented a scheme combining it with the frequency statistical method for auto-calibration and prediction uncertainty estimation. A case study of a hydraulic-water quality coupling model was provided, in which the urban non-point source ammonia nitrogen (NH3-N) and total phosphorus (TP) were simulated. Compared with the benchmark particle swarm optimizer (PSO) and MFO, EOMFO has better global optimization ability and can obtain behavioral samples with higher quality for sensitive parameters. Regarding the calibration performance, EOMFO performed well in both the NH3-N and TP simulations (Nash–Sutcliffe efficiency around or greater than 0.5 and R greater than 0.7) and outperformed benchmark algorithms for both the deterministic prediction and uncertainty band prediction. The generated uncertainty band bracketed the majority of TP observation points, although it is not in good agreement with NH3-N observations due to several potential reasons. With this scheme, a more efficient and robust calibration process is expected.","PeriodicalId":54801,"journal":{"name":"Journal of Hydroinformatics","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2023-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44600415","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper proposes a formulation of modularity tailored to the dual water distribution network (WDN) topology based on segments and valves, to be conveniently adopted for the partitioning into district-metered areas (DMAs). Notably, it allows considering both properties to be made uniform across DMAs, such as water demand or total pipe length, and properties to be made uniform inside each DMA, such as nodal ground elevations or pipe age for the sake of pressure regulation or maintenance easiness, respectively. This paper also proposes a new algorithm for the identification of the optimal clustering of WDN segments into any desired number of DMAs. Taking as a starting point any WDN clustering solution, i.e., the solution obtained with Newman's fast algorithm for community detection, the novel algorithm operates by exploring changes in the community of belonging to segments lying in the boundary between adjacent communities, by applying an optimization inspired by the simulated annealing technique. The applications of the novel modularity formulation and optimization algorithm to two case studies yield well-performing clustering solutions in terms of engineering judgment criteria, such as the low number of inter-DMA boundary pipes, uniformity of DMAs and hydraulic performance.
{"title":"Improved community detection for WDN partitioning in the dual topology based on segments and valves","authors":"E. Creaco, C. Giudicianni, Amirabbas Mottahedin","doi":"10.2166/hydro.2023.209","DOIUrl":"https://doi.org/10.2166/hydro.2023.209","url":null,"abstract":"\u0000 \u0000 This paper proposes a formulation of modularity tailored to the dual water distribution network (WDN) topology based on segments and valves, to be conveniently adopted for the partitioning into district-metered areas (DMAs). Notably, it allows considering both properties to be made uniform across DMAs, such as water demand or total pipe length, and properties to be made uniform inside each DMA, such as nodal ground elevations or pipe age for the sake of pressure regulation or maintenance easiness, respectively. This paper also proposes a new algorithm for the identification of the optimal clustering of WDN segments into any desired number of DMAs. Taking as a starting point any WDN clustering solution, i.e., the solution obtained with Newman's fast algorithm for community detection, the novel algorithm operates by exploring changes in the community of belonging to segments lying in the boundary between adjacent communities, by applying an optimization inspired by the simulated annealing technique. The applications of the novel modularity formulation and optimization algorithm to two case studies yield well-performing clustering solutions in terms of engineering judgment criteria, such as the low number of inter-DMA boundary pipes, uniformity of DMAs and hydraulic performance.","PeriodicalId":54801,"journal":{"name":"Journal of Hydroinformatics","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2023-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48679709","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In contrast to the traditional black box machine learning model, the white box model can achieve higher prediction accuracy and accurately evaluate and explain the prediction results. Cavity water depth and cavity length of aeration facilities are predicted in this research based on Extreme Gradient Boosting (XGBoost) and a Bayesian optimization technique. The Shapley Additive Explanation (SHAP) method is then utilized to explain the prediction results. This study demonstrates how SHAP may order all features and feature interaction terms in accordance with the significance of the input features. The XGBoost–SHAP white box model can reasonably explain the prediction results of XGBoost both globally and locally and can achieve prediction accuracy comparable to the black box model. The cavity water depth and cavity length white box model developed in this study have a promising future application in the shape optimization of aeration facilities and the improvement of model experiments.
{"title":"An interpretable machine learning model for predicting cavity water depth and cavity length based on XGBoost–SHAP","authors":"Tiexiang Mo, Shanshan Li, Guodong Li","doi":"10.2166/hydro.2023.050","DOIUrl":"https://doi.org/10.2166/hydro.2023.050","url":null,"abstract":"\u0000 In contrast to the traditional black box machine learning model, the white box model can achieve higher prediction accuracy and accurately evaluate and explain the prediction results. Cavity water depth and cavity length of aeration facilities are predicted in this research based on Extreme Gradient Boosting (XGBoost) and a Bayesian optimization technique. The Shapley Additive Explanation (SHAP) method is then utilized to explain the prediction results. This study demonstrates how SHAP may order all features and feature interaction terms in accordance with the significance of the input features. The XGBoost–SHAP white box model can reasonably explain the prediction results of XGBoost both globally and locally and can achieve prediction accuracy comparable to the black box model. The cavity water depth and cavity length white box model developed in this study have a promising future application in the shape optimization of aeration facilities and the improvement of model experiments.","PeriodicalId":54801,"journal":{"name":"Journal of Hydroinformatics","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2023-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41585702","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
When a reservoir is damaged, it will bring destruction to people's lives and the regional economy. Flood simulation and risk assessment are two effective ways to mitigate flood risk. Flood risk is assessed by using flood hazard and vulnerability indices. However, one of the key concerns is how to quantify hazards and vulnerabilities more rationally. To this end, this study introduces a new quantitative method for flood risk assessment. Three schemes – full dam breach (S1), 1/2 dam breach (S2), and 1/3 dam breach (S3) – were proposed for flood simulation. HEC-RAS 2D was used to simulate the evolution process of dam-break floods. This study used a new quantification approach to calculate flood risk based on simulation results. The results show the following: (1) The inundation process is similar under the three schemes, but the degree differs. The greater the degree of dam break, the greater the inundation depth, maximum flow velocity, and inundation duration. (2) High-risk areas decrease with decreased dam break degree. Under the three schemes, the flood risk areas of Longjing Street account for 65.37, 71.41, and 66.22% of the total risk areas, respectively, which are the areas most affected by dam-break floods.
{"title":"Simulation of dam-break flood and risk assessment: a case study of Chengbi River Dam in Baise, China","authors":"Chong-xun Mo, Weiyan Cen, Xin Lei, Huazhen Ban, Yuli Ruan, Shufeng Lai, Yue Shen, Zhenxiang Xing","doi":"10.2166/hydro.2023.193","DOIUrl":"https://doi.org/10.2166/hydro.2023.193","url":null,"abstract":"\u0000 When a reservoir is damaged, it will bring destruction to people's lives and the regional economy. Flood simulation and risk assessment are two effective ways to mitigate flood risk. Flood risk is assessed by using flood hazard and vulnerability indices. However, one of the key concerns is how to quantify hazards and vulnerabilities more rationally. To this end, this study introduces a new quantitative method for flood risk assessment. Three schemes – full dam breach (S1), 1/2 dam breach (S2), and 1/3 dam breach (S3) – were proposed for flood simulation. HEC-RAS 2D was used to simulate the evolution process of dam-break floods. This study used a new quantification approach to calculate flood risk based on simulation results. The results show the following: (1) The inundation process is similar under the three schemes, but the degree differs. The greater the degree of dam break, the greater the inundation depth, maximum flow velocity, and inundation duration. (2) High-risk areas decrease with decreased dam break degree. Under the three schemes, the flood risk areas of Longjing Street account for 65.37, 71.41, and 66.22% of the total risk areas, respectively, which are the areas most affected by dam-break floods.","PeriodicalId":54801,"journal":{"name":"Journal of Hydroinformatics","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2023-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42296679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, a deterioration model is created and used to simulate the life cycle of a water distribution network (WDN). Then, two strategies – leakage fixing and pipe cleaning – are evaluated to rehabilitate its capacity to attend the demand. In order to implement the deterioration model, the following parameters were considered: growth of the consumer population, increase in leakage rate, functional pipe deterioration and reduction of the hydraulic capacity of the pumps. For the leakage fixing, a fixed reduction rate in water losses was considered throughout the entire WDN until a minimum reference value was reached. For pipe rehabilitation, leaning was considered at a rate of 1% of the total length of the network per year. In each of the rehabilitation strategies, a cost–benefit analysis was carried out using the net present value. The results showed that both alternatives can restore the capacity of the WDN, with the pipe cleaning presenting a better economic impact.
{"title":"Rehabilitation of water distribution networks: when and how to rehabilitate","authors":"Leandro Alves Evangelista, B. Brentan, G. Lima","doi":"10.2166/hydro.2023.206","DOIUrl":"https://doi.org/10.2166/hydro.2023.206","url":null,"abstract":"\u0000 \u0000 In this paper, a deterioration model is created and used to simulate the life cycle of a water distribution network (WDN). Then, two strategies – leakage fixing and pipe cleaning – are evaluated to rehabilitate its capacity to attend the demand. In order to implement the deterioration model, the following parameters were considered: growth of the consumer population, increase in leakage rate, functional pipe deterioration and reduction of the hydraulic capacity of the pumps. For the leakage fixing, a fixed reduction rate in water losses was considered throughout the entire WDN until a minimum reference value was reached. For pipe rehabilitation, leaning was considered at a rate of 1% of the total length of the network per year. In each of the rehabilitation strategies, a cost–benefit analysis was carried out using the net present value. The results showed that both alternatives can restore the capacity of the WDN, with the pipe cleaning presenting a better economic impact.","PeriodicalId":54801,"journal":{"name":"Journal of Hydroinformatics","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2023-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45706927","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Drought disasters have caused serious impacts on the social economy and ecological environment, which are continuously and increasingly exacerbated by climate warming and other factors. Drought disaster management usually involves processing a mass of isolated data from many fields expressed in different terminologies and formats. These heterogeneous data or so-called data silos have greatly hindered drought disaster management in an information-rich manner. Establishing a drought disaster knowledge graph can facilitate the reuse of these heterogeneous data and provide references for drought disaster management, and ontology design and named entity recognition are the two major challenges. Therefore, in this study, we first designed a drought disaster ontology by recognizing the major concepts in the drought disaster field and their relationships, which was implemented with an ontology modeling language. We next constructed a drought disaster corpus and an integrated entity recognition model that was built by integrating multiple deep learning methods. Finally, we applied the integrated entity recognition model to extract information from the CNKI literature database. The integrated model shows satisfactory results in drought disaster named entity recognition. We thus conclude that combining ontology and deep learning technology toward establishing a knowledge graph for drought disasters is promising.
{"title":"Toward establishing a knowledge graph for drought disaster based on ontology design and named entity recognition","authors":"Yihui Fang, Dejian Zhang, Guoxiang Wu","doi":"10.2166/hydro.2023.046","DOIUrl":"https://doi.org/10.2166/hydro.2023.046","url":null,"abstract":"\u0000 \u0000 Drought disasters have caused serious impacts on the social economy and ecological environment, which are continuously and increasingly exacerbated by climate warming and other factors. Drought disaster management usually involves processing a mass of isolated data from many fields expressed in different terminologies and formats. These heterogeneous data or so-called data silos have greatly hindered drought disaster management in an information-rich manner. Establishing a drought disaster knowledge graph can facilitate the reuse of these heterogeneous data and provide references for drought disaster management, and ontology design and named entity recognition are the two major challenges. Therefore, in this study, we first designed a drought disaster ontology by recognizing the major concepts in the drought disaster field and their relationships, which was implemented with an ontology modeling language. We next constructed a drought disaster corpus and an integrated entity recognition model that was built by integrating multiple deep learning methods. Finally, we applied the integrated entity recognition model to extract information from the CNKI literature database. The integrated model shows satisfactory results in drought disaster named entity recognition. We thus conclude that combining ontology and deep learning technology toward establishing a knowledge graph for drought disasters is promising.","PeriodicalId":54801,"journal":{"name":"Journal of Hydroinformatics","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2023-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47906968","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：