scholarly journals The Development Trend and Research Frontiers of Distributed Hydrological Models—Visual Bibliometric Analysis Based on Citespace

Water ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 174
Author(s):  
Fangling Qin ◽  
Ying Zhu ◽  
Tianqi Ao ◽  
Ting Chen
Keyword(s):  
Water Resources ◽  
Hydrological Model ◽  
Field Research ◽  
Development Trend ◽  
The United States ◽  
Hydrological Process ◽  
Hydrological Models ◽  
Distributed Hydrological Model ◽  
High Resolution Data ◽  
Distributed Hydrological Models

Based on the bibliometric and data visualization analysis software Citespace, this study carried out document statistics and information mining on the Web of Science database and characterized the distributed hydrological model knowledge system from 1986 to 2019. The results show a few things: (1) from 1986 to 2019, the United States and China accounted for 41% of the total amount of publications, and they were the main force in the field of distributed hydrological model research; (2) field research involves multiple disciplines, mainly covering water resources, geology, earth sciences, environmental sciences, ecology and engineering; (3) the frontier of field research has shifted from using distributed hydrological models in order to simulate runoff and nonpoint source environmental responses to the coupling of technologies and products that can obtain high-precision, high-resolution data with distributed hydrological models. (4) Affected by climate warming, the melting of glaciers has accelerated, and the spatial distribution of permafrost and water resources have changed, which has caused a non-negligible impact on the hydrological process. Therefore, the development of distributed hydrological models suitable for alpine regions and the response of hydrological processes to climate change have also become important research directions at present.

scholarly journals Technical note: Representing glacier geometry changes in a semi-distributed hydrological model

2018 ◽  
Vol 22 (4) ◽  
pp. 2211-2224 ◽  
Author(s):  
Jan Seibert ◽  
Marc J. P. Vis ◽  
Irene Kohn ◽  
Markus Weiler ◽  
Kerstin Stahl
Keyword(s):  
Hydrological Model ◽  
Technical Note ◽  
High Mountain ◽  
Hydrological Models ◽  
Distributed Hydrological Model ◽  
Mass Balances ◽  
Hydrological Simulation ◽  
Distributed Hydrological Models ◽  
Feasible Solutions ◽  
Glacier Advance

Abstract. Glaciers play an important role in high-mountain hydrology. While changing glacier areas are considered of highest importance for the understanding of future changes in runoff, glaciers are often only poorly represented in hydrological models. Most importantly, the direct coupling between the simulated glacier mass balances and changing glacier areas needs feasible solutions. The use of a complex glacier model is often not possible due to data and computational limitations. The Δh parameterization is a simple approach to consider the spatial variation of glacier thickness and area changes. Here, we describe a conceptual implementation of the Δh parameterization in the semi-distributed hydrological model HBV-light, which also allows for the representation of glacier advance phases and for comparison between the different versions of the implementation. The coupled glacio-hydrological simulation approach, which could also be implemented in many other semi-distributed hydrological models, is illustrated based on an example application.

scholarly journals Identifying Key Hydrological Processes in Highly Urbanized Watersheds for Flood Forecasting with a Distributed Hydrological Model

Water ◽  
2019 ◽  
Vol 11 (8) ◽  
pp. 1641 ◽  
Author(s):  
Huanyu Wang ◽  
Yangbo Chen
Keyword(s):  
Water Content ◽  
Parameter Uncertainty ◽  
Hydrological Model ◽  
Flood Forecasting ◽  
Hydrological Processes ◽  
Model Parameters ◽  
Hydrological Models ◽  
Distributed Hydrological Model ◽  
Physically Based ◽  
Distributed Hydrological Models

The world has experienced large-scale urbanization in the past century, and this trend is ongoing. Urbanization not only causes land use/cover (LUC) changes but also changes the flood responses of watersheds. Lumped conceptual hydrological models cannot be effectively used for flood forecasting in watersheds that lack long time series of hydrological data to calibrate model parameters. Thus, physically based distributed hydrological models are used instead in these areas, but considerable uncertainty is associated with model parameter derivation. To reduce model parameter uncertainty in physically based distributed hydrological models for flood forecasting in highly urbanized watersheds, a procedure is proposed to control parameter uncertainty. The core concept of this procedure is to identify the key hydrological and flood processes in the highly urbanized watersheds and the sensitive model parameters related to these processes. Then, the sensitive model parameters are adjusted based on local runoff coefficients to reduce the parameter uncertainty. This procedure includes these steps: collecting the latest LUC information or estimating this information using satellite remote sensing images, analyzing LUC spatial patterns and identifying dominant LUC types and their spatial structures, choosing and establishing a distributed hydrological model as the forecasting tool, and determining the initial model parameters and identifying the key hydrological processes and sensitive model parameters based on a parameter sensitivity analysis. A highly urbanized watershed called Shahe Creek in the Pearl River Delta area was selected as a case study. This study finds that the runoff production processes associated with both the ferric luvisol and acric ferralsol soil types and the runoff routing process on urban land are key hydrological processes. Additionally, the soil water content under saturated conditions, the soil water content under field conditions and the roughness of urban land are sensitive parameters.

scholarly journals Model Hidrologi Terdistribusi untuk Analisis Debit Terserap pada Sumur Resapan, Lubang Biopori dan Kolam Retensi

2020 ◽  
Vol 15 (2) ◽  
pp. 20
Author(s):  
Elvi Roza Syofyan ◽  
Bambang Istijono ◽  
Amrizal Saidi ◽  
Revalin Herdianto
Keyword(s):  
Hydrological Model ◽  
Secondary Data ◽  
Primary Data ◽  
Survey Method ◽  
Hydrological Models ◽  
Distributed Hydrological Model ◽  
Watershed Land Use ◽  
Retention Ponds ◽  
Runoff Rate ◽  
Distributed Hydrological Models

Infiltration wells, biopore holes, retention ponds serve to collect surface water from rain and then seep into the ground to become ground water reserves. This study aims to look at the application of a distributed hydrological model for the analysis of absorbed discharges in infiltration wells, biopore holes and retention ponds in the Batang Kuranji watershed. Research methods the study was conducted using a survey method that is secondary data collection and primary data. In this study the techniques of rainfall data analysis, Batang Kuranji watershed land use, Runoff analysis using distributed hydrological models and absorbed discharges in infiltration wells, biopore holes, retention ponds in the Batang Kuranji watershed. By applying model 4 using 1 infiltration wells, 2 biopore holes and 4 retention ponds can reduce the runoff rate in the sub-watershed by 7.514% - 27.545%, for the watershed level can reduce the discharge of 15.297%, the more the number of absorption wells, biopori holes and retention ponds more effective in reducing runoff in the Batang Kuranji watershed.

scholarly journals Improving flood forecasting capability of physically based distributed hydrological models by parameter optimization

2016 ◽  
Vol 20 (1) ◽  
pp. 375-392 ◽  
Author(s):  
Y. Chen ◽  
J. Li ◽  
H. Xu
Keyword(s):  
Parameter Optimization ◽  
Hydrological Model ◽  
Pso Algorithm ◽  
Flood Forecasting ◽  
Model Parameters ◽  
Hydrological Models ◽  
Distributed Hydrological Model ◽  
Inertia Weight ◽  
Physically Based ◽  
Distributed Hydrological Models

Abstract. Physically based distributed hydrological models (hereafter referred to as PBDHMs) divide the terrain of the whole catchment into a number of grid cells at fine resolution and assimilate different terrain data and precipitation to different cells. They are regarded to have the potential to improve the catchment hydrological process simulation and prediction capability. In the early stage, physically based distributed hydrological models are assumed to derive model parameters from the terrain properties directly, so there is no need to calibrate model parameters. However, unfortunately the uncertainties associated with this model derivation are very high, which impacted their application in flood forecasting, so parameter optimization may also be necessary. There are two main purposes for this study: the first is to propose a parameter optimization method for physically based distributed hydrological models in catchment flood forecasting by using particle swarm optimization (PSO) algorithm and to test its competence and to improve its performances; the second is to explore the possibility of improving physically based distributed hydrological model capability in catchment flood forecasting by parameter optimization. In this paper, based on the scalar concept, a general framework for parameter optimization of the PBDHMs for catchment flood forecasting is first proposed that could be used for all PBDHMs. Then, with the Liuxihe model as the study model, which is a physically based distributed hydrological model proposed for catchment flood forecasting, the improved PSO algorithm is developed for the parameter optimization of the Liuxihe model in catchment flood forecasting. The improvements include adoption of the linearly decreasing inertia weight strategy to change the inertia weight and the arccosine function strategy to adjust the acceleration coefficients. This method has been tested in two catchments in southern China with different sizes, and the results show that the improved PSO algorithm could be used for the Liuxihe model parameter optimization effectively and could improve the model capability largely in catchment flood forecasting, thus proving that parameter optimization is necessary to improve the flood forecasting capability of physically based distributed hydrological models. It also has been found that the appropriate particle number and the maximum evolution number of PSO algorithm used for the Liuxihe model catchment flood forecasting are 20 and 30 respectively.

Application of Distributed Deterministic Hydrological Model in Mediterranean Region, Case Study in Var Catchment, France

10.29007/gmfw ◽  
2018 ◽  
Author(s):  
Qiang Ma ◽  
Ngoc Duong Vo ◽  
Philippe Gourbesville
Keyword(s):  
Mediterranean Region ◽  
Hydrological Model ◽  
Water Cycle ◽  
Time Interval ◽  
Hydrological Models ◽  
Distributed Hydrological Model ◽  
Mike She ◽  
Hydrological System ◽  
Distributed Hydrological Models ◽  
Human And Nature

During last decade, due to intensification of urbanization, connections between human and nature become more closed. Through hydro-informatics applications, such as hydrological or hydraulic model simulations, for local water managers, their knowledge and understanding of regional hydrological characteristics can be strongly improved. Among different kinds of hydrological models, the deterministic distributed hydrological model (MIKE SHE), shows obvious advantages in integrate representing multiple hydrological processes in catchment water cycle and producing more accuracy and detail results at any places on the simulation domain. This research is in project of AquaVar, which aims to create one model-based DSS in Var catchment at French Mediterranean Region. The main objective of this study is to build one deterministic distributed hydrological model through one optimized modelling strategy, which is able to overcome to problems caused by missing data, to well represent the complicated hydrological system in Var catchment. Based on a series of hydrological assessments and model testes, under reasonable hypothesized conditions, the model of MIKE SHE was calibrated from 2008 to 2011 and validated from 2011 to 2013 with daily time interval. With high statistical performance and can well presentation of the floods occurred during simulation period, the model results is able to be applied in AquaVar DSS for real time simulation and forecasting further scenarios. Besides, the modelling strategy conceived in this research can be also applied for building deterministic distributed hydrological models in other similar area.

scholarly journals Improving flood forecasting capability of physically based distributed hydrological model by parameter optimization

2015 ◽  
Vol 12 (10) ◽  
pp. 10603-10649 ◽  
Author(s):  
Y. Chen ◽  
J. Li ◽  
H. Xu
Keyword(s):  
Parameter Optimization ◽  
Hydrological Model ◽  
Pso Algorithm ◽  
Flood Forecasting ◽  
Model Parameters ◽  
Hydrological Models ◽  
Distributed Hydrological Model ◽  
Inertia Weight ◽  
Physically Based ◽  
Distributed Hydrological Models

Abstract. Physically based distributed hydrological models discrete the terrain of the whole catchment into a number of grid cells at fine resolution, and assimilate different terrain data and precipitation to different cells, and are regarded to have the potential to improve the catchment hydrological processes simulation and prediction capability. In the early stage, physically based distributed hydrological models are assumed to derive model parameters from the terrain properties directly, so there is no need to calibrate model parameters, but unfortunately, the uncertanties associated with this model parameter deriving is very high, which impacted their application in flood forecasting, so parameter optimization may also be necessary. There are two main purposes for this study, the first is to propose a parameter optimization method for physically based distributed hydrological models in catchment flood forecasting by using PSO algorithm and to test its competence and to improve its performances, the second is to explore the possibility of improving physically based distributed hydrological models capability in cathcment flood forecasting by parameter optimization. In this paper, based on the scalar concept, a general framework for parameter optimization of the PBDHMs for catchment flood forecasting is first proposed that could be used for all PBDHMs. Then, with Liuxihe model as the study model, which is a physically based distributed hydrological model proposed for catchment flood forecasting, the improverd Particle Swarm Optimization (PSO) algorithm is developed for the parameter optimization of Liuxihe model in catchment flood forecasting, the improvements include to adopt the linear decreasing inertia weight strategy to change the inertia weight, and the arccosine function strategy to adjust the acceleration coefficients. This method has been tested in two catchments in southern China with different sizes, and the results show that the improved PSO algorithm could be used for Liuxihe model parameter optimization effectively, and could improve the model capability largely in catchment flood forecasting, thus proven that parameter optimization is necessary to improve the flood forecasting capability of physically based distributed hydrological model. It also has been found that the appropriate particle number and the maximum evolution number of PSO algorithm used for Liuxihe model catchment flood forcasting is 20 and 30, respectively.

scholarly journals Technical Note: Representing glacier dynamics in a semi-distributed hydrological model

2017 ◽  
Author(s):  
Jan Seibert ◽  
Marc J. P. Vis ◽  
Irene Kohn ◽  
Markus Weiler ◽  
Kerstin Stahl
Keyword(s):  
Hydrological Model ◽  
Technical Note ◽  
High Mountain ◽  
Hydrological Models ◽  
Distributed Hydrological Model ◽  
Mass Balances ◽  
Hydrological Simulation ◽  
Distributed Hydrological Models ◽  
Feasible Solutions ◽  
Glacier Advance

Abstract. Glaciers play an important role in high-mountain hydrology. While changing glacier areas are considered of highest importance for the understanding of future changes in runoff, glaciers are often only poorly represented in hydrological models. Most importantly, the direct coupling between the simulated glacier mass balances and changing glacier areas needs feasible solutions. The use of a complex glacier model is often not possible due to data and computational limitations. The Δh-parameterization is a simple approach to consider the spatial variation of glacier thickness and area changes. Here, we describe a conceptual implementation of the Δh-parameterization into the semi-distributed hydrological model HBV-light, which also allows for the representation of glacier advance phases, and comparison between the different versions of the implementation. The coupled glacio-hydrological simulation approach, which could also be implemented in many other semi-distributed hydrological models, is illustrated based on an example application.

scholarly journals Comparative performance evaluation of self-adaptive differential evolution with GA, SCE and DE algorithms for the automatic calibration of a computationally intensive distributed hydrological model

2020 ◽  
Author(s):  
Saswata Nandi ◽  
M. Janga Reddy
Keyword(s):  
Differential Evolution ◽  
Hydrological Model ◽  
Automatic Calibration ◽  
Hydrological Models ◽  
Distributed Hydrological Model ◽  
Infiltration Capacity ◽  
Vic Model ◽  
Adaptive Differential Evolution ◽  
Computationally Intensive ◽  
Self Adaptive

Abstract Recently, physically-based hydrological models have been gaining much popularity in various activities of water resources planning and management, such as assessment of basin water availability, floods, droughts, and reservoir operation. Every hydrological model contains some parameters that must be tuned to the catchment being studied to obtain reliable estimates from the model. This study evaluated the performance of different evolutionary algorithms, namely genetic algorithm (GA), shuffled complex evolution (SCE), differential evolution (DE), and self-adaptive differential evolution (SaDE) algorithm for the parameter calibration of a computationally intensive distributed hydrological model, variable infiltration capacity (VIC) model. The methodology applied and tested for a case study of the upper Tungabhadra River basin in India, and the performance of the algorithms is evaluated in terms of reliability, variability, efficacy measures in a limited number of function evaluations, their ability for achieving global convergence, and also by their capability to produce a skillful simulation of streamflows. The results of the study indicated that SaDE facilitates an effective calibration of the VIC model with higher reliability and faster convergence to optimal solutions as compared to the other methods. Moreover, due to the simplicity of the SaDE, it provides easy implementation and flexibility for the automatic calibration of complex hydrological models.

scholarly journals Evaluation of global fine-resolution precipitation products and their uncertainty quantification in ensemble discharge simulations

2016 ◽  
Vol 20 (2) ◽  
pp. 903-920 ◽  
Author(s):  
W. Qi ◽  
C. Zhang ◽  
G. Fu ◽  
C. Sweetapple ◽  
H. Zhou
Keyword(s):  
Hydrological Model ◽  
Tropical Rainfall Measuring Mission ◽  
Heavy Precipitation ◽  
Hydrological Models ◽  
Distributed Hydrological Model ◽  
Precipitation Product ◽  
Physically Based ◽  
Precipitation Estimation ◽  
Discharge Simulation ◽  
Fine Resolution

Abstract. The applicability of six fine-resolution precipitation products, including precipitation radar, infrared, microwave and gauge-based products, using different precipitation computation recipes, is evaluated using statistical and hydrological methods in northeastern China. In addition, a framework quantifying uncertainty contributions of precipitation products, hydrological models, and their interactions to uncertainties in ensemble discharges is proposed. The investigated precipitation products are Tropical Rainfall Measuring Mission (TRMM) products (TRMM3B42 and TRMM3B42RT), Global Land Data Assimilation System (GLDAS)/Noah, Asian Precipitation – Highly-Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), and a Global Satellite Mapping of Precipitation (GSMAP-MVK+) product. Two hydrological models of different complexities, i.e. a water and energy budget-based distributed hydrological model and a physically based semi-distributed hydrological model, are employed to investigate the influence of hydrological models on simulated discharges. Results show APHRODITE has high accuracy at a monthly scale compared with other products, and GSMAP-MVK+ shows huge advantage and is better than TRMM3B42 in relative bias (RB), Nash–Sutcliffe coefficient of efficiency (NSE), root mean square error (RMSE), correlation coefficient (CC), false alarm ratio, and critical success index. These findings could be very useful for validation, refinement, and future development of satellite-based products (e.g. NASA Global Precipitation Measurement). Although large uncertainty exists in heavy precipitation, hydrological models contribute most of the uncertainty in extreme discharges. Interactions between precipitation products and hydrological models can have the similar magnitude of contribution to discharge uncertainty as the hydrological models. A better precipitation product does not guarantee a better discharge simulation because of interactions. It is also found that a good discharge simulation depends on a good coalition of a hydrological model and a precipitation product, suggesting that, although the satellite-based precipitation products are not as accurate as the gauge-based products, they could have better performance in discharge simulations when appropriately combined with hydrological models. This information is revealed for the first time and very beneficial for precipitation product applications.

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