Special Issue "Advanced Hydrologic Modeling in Watershed-Scale"

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Hydrology and Hydrogeology".

Deadline for manuscript submissions: closed (31 December 2020).

Special Issue Editor

Prof. Dr. Xuefeng Chu
E-Mail Website
Guest Editor
Department of Civil and Environmental Engineering, North Dakota State University
Interests: watershed modelling; environmental modelling; vadose zone hydrology; hydrotopographic analysis; groundwater modelling
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

Watershed-scale hydrologic modeling is essential to water quantity and quality management. Such large-scale modeling involves a series of complex hydrologic processes and their interactions across surface and subsurface systems under the influence of climate, anthropogenic activities, and other factors. The relevant modeling procedures mainly include acquisition and processing of spatially-distributed GIS data (e.g., digital elevation models (DEMs), land use/land cover (LULC) and soil vector or raster data), watershed delineation, development of mathematical models, as well as model calibration and validation. A variety of watershed-oriented modeling approaches and tools have been developed and applied to various watersheds in different parts of the world. However, there are many challenging issues, such as scale effects, integration of multiple systems (e.g., ecohydroclimatic system), depression-associated threshold behaviors, hydrologic connectivity, and big data-driven real-time prediction.

This special issue aims to stimulate discussions on the advances and recent trends in watershed-scale hydrologic modeling methodologies, development of watershed modeling tools, as well as real-world applications. The topics include, but are not limited to: DEM-based watershed delineation methods and tools, watershed characterization and parameterization, extraction of drainage networks and flow routing, catchment-wide hydrologic connectivity analysis, utilization of high-resolution GIS data for improved watershed modeling, DEM resolution effects and scaling issues, large-scale distributed and lumped hydrologic modeling, integrated modeling of surface and subsurface hydrologic systems, and applications of existing watershed hydrologic modeling systems (e.g., SWAT, HSPF, HEC-HMS, TOPMODEL, and MIKE SHE) at different geographical locations and under varying climate conditions.

Prof. Xuefeng Chu
Guest Editor

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Keywords

  • Watershed
  • DEM
  • Delineation
  • Hydrology
  • Modeling
  • GIS
  • Hydrotopographic analysis

Published Papers (11 papers)

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Research

Article
Multi-Spatial Resolution Rainfall-Runoff Modelling—A Case Study of Sabari River Basin, India
Water 2021, 13(9), 1224; https://doi.org/10.3390/w13091224 - 28 Apr 2021
Viewed by 381
Abstract
One of the challenges in rainfall-runoff modeling is the identification of an appropriate model spatial resolution that allows streamflow estimation at customized locations of the river basin. In lumped modeling, spatial resolution is not an issue as spatial variability is not accounted for, [...] Read more.
One of the challenges in rainfall-runoff modeling is the identification of an appropriate model spatial resolution that allows streamflow estimation at customized locations of the river basin. In lumped modeling, spatial resolution is not an issue as spatial variability is not accounted for, whereas in distributed modeling grid or cell resolution can be related to spatial resolution but its application is limited because of its large data requirements. Streamflow estimation at the data-poor customized locations is not possible in lumped modeling, whereas it is challenging in distributed modeling. In this context, semi-distributed modeling offers a solution including model resolution and estimation of streamflow at customized locations of a river basins with less data requirements. In this study, the Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) model is employed in semi-distribution mode on river basins of six different spatial resolutions. The model was calibrated and validated for fifteen and three selected flood events, respectively, of three types, i.e., single peak (SP), double peak (DP)- and multiple peaks (MP) at six different spatial resolution of the Sabari River Basin (SRB), a sub-basin of the Godavari basin, India. Calibrated parameters were analyzed to understand hydrologic parameter variability in the context of spatial resolution and flood event aspects. Streamflow hydrographs were developed, and various verification metrics and model scores were calculated for reference- and calibration- scenarios. During the calibration phase, the median of correlation coefficient and NSE for all 15 events of all six configurations was 0.90 and 0.69, respectively. The estimated streamflow hydrographs from six configurations suggest the model’s ability to simulate the processes efficiently. Parameters obtained from the calibration phase were used to generate an ensemble of streamflow at multiple locations including basin outlet as part of the validation. The estimated ensemble of streamflows appeared to be realistic, and both single-valued and ensemble verification metrics indicated the model’s good performance. The results suggested better performance of lumped modeling followed by the semi-distributed modeling with a finer spatial resolution. Thus, the study demonstrates a method that can be applied for real-time streamflow forecast at interior locations of a basin, which are not necessarily data rich. Full article
(This article belongs to the Special Issue Advanced Hydrologic Modeling in Watershed-Scale)
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Article
Assessment of Streamflow Simulation for a Tropical Forested Catchment Using Dynamic TOPMODEL—Dynamic fluxEs and ConnectIvity for Predictions of HydRology (DECIPHeR) Framework and Generalized Likelihood Uncertainty Estimation (GLUE)
Water 2021, 13(3), 317; https://doi.org/10.3390/w13030317 - 28 Jan 2021
Cited by 1 | Viewed by 506
Abstract
Rainfall runoff modeling has been a subject of interest for decades due to a need to understand a catchment system for management, for example regarding extreme event occurrences such as flooding. Tropical catchments are particularly prone to the hazards of extreme precipitation and [...] Read more.
Rainfall runoff modeling has been a subject of interest for decades due to a need to understand a catchment system for management, for example regarding extreme event occurrences such as flooding. Tropical catchments are particularly prone to the hazards of extreme precipitation and the internal drivers of change in the system, such as deforestation and land use change. A model framework of dynamic TOPMODEL, DECIPHeR v1—considering the flexibility, modularity, and portability—and Generalized Likelihood Uncertainty Estimation (GLUE) method are both used in this study. They reveal model performance for the streamflow simulation in a tropical catchment, i.e., the Kelantan River in Malaysia, that is prone to flooding and experiences high rates of land use change. Thirty-two years’ continuous simulation at a daily time scale simulation along with uncertainty analysis resulted in a Nash Sutcliffe Efficiency (NSE) score of 0.42 from the highest ranked parameter set, while 25.35% of the measurement falls within the uncertainty boundary based on a behavioral threshold NSE 0.3. The performance and behavior of the model in the continuous simulation suggests a limited ability of the model to represent the system, particularly along the low flow regime. In contrast, the simulation of eight peak flow events achieves moderate to good fit, with the four peak flow events simulation returning an NSE > 0.5. Nonetheless, the parameter scatter plot from both the continuous simulation and analyses of peak flow events indicate unidentifiability of all model parameters. This may be attributable to the catchment modeling scale. The results demand further investigation regarding the heterogeneity of parameters and calibration at multiple scales. Full article
(This article belongs to the Special Issue Advanced Hydrologic Modeling in Watershed-Scale)
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Article
Optimization of Hydrologic Response Units (HRUs) Using Gridded Meteorological Data and Spatially Varying Parameters
Water 2020, 12(12), 3558; https://doi.org/10.3390/w12123558 - 18 Dec 2020
Viewed by 495
Abstract
Although complex hydrological models with detailed physics are becoming more common, lumped and semi-distributed models are still used for many applications and offer some advantages, such as reduced computational cost. Most of these semi-distributed models use the concept of the hydrological response unit [...] Read more.
Although complex hydrological models with detailed physics are becoming more common, lumped and semi-distributed models are still used for many applications and offer some advantages, such as reduced computational cost. Most of these semi-distributed models use the concept of the hydrological response unit or HRU. In the original conception, HRUs are defined as homogeneous structured elements with similar climate, land use, soil and/or pedotransfer properties, and hence a homogeneous hydrological response under equivalent meteorological forcing. This work presents a quantitative methodology, called hereafter the principal component analysis and hierarchical cluster analysis or PCA/HCPC method, to construct HRUs using gridded meteorological data and hydrological parameters. The PCA/HCPC method is tested using the water evaluation and planning system (WEAP) model for the Alicahue River Basin, a small and semi-arid catchment of the Andes, in Central Chile. The results show that with four HRUs, it is possible to reduce the relative within variance of the catchment up to about 10%, an indicator of the homogeneity of the HRUs. The evaluation of the simulations shows a good agreement with streamflow observations in the outlet of the catchment with an Nash–Sutcliffe efficiency (NSE) value of 0.79 and also shows the presence of small hydrological extreme areas that generally are neglected due to their relative size. Full article
(This article belongs to the Special Issue Advanced Hydrologic Modeling in Watershed-Scale)
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Article
Impact of Input Filtering and Architecture Selection Strategies on GRU Runoff Forecasting: A Case Study in the Wei River Basin, Shaanxi, China
Water 2020, 12(12), 3532; https://doi.org/10.3390/w12123532 - 16 Dec 2020
Viewed by 613
Abstract
A gated recurrent unit (GRU) network, which is a kind of artificial neural network (ANN), has been increasingly applied to runoff forecasting. However, knowledge about the impact of different input data filtering strategies and the implications of different architectures on the GRU runoff [...] Read more.
A gated recurrent unit (GRU) network, which is a kind of artificial neural network (ANN), has been increasingly applied to runoff forecasting. However, knowledge about the impact of different input data filtering strategies and the implications of different architectures on the GRU runoff forecasting model’s performance is still insufficient. This study has selected the daily rainfall and runoff data from 2007 to 2014 in the Wei River basin in Shaanxi, China, and assessed six different scenarios to explore the patterns of that impact. In the scenarios, four manually-selected rainfall or runoff data combinations and principal component analysis (PCA) denoised input have been considered along with single directional and bi-directional GRU network architectures. The performance has been evaluated from the aspect of robustness to 48 various hypermeter combinations, also, optimized accuracy in one-day-ahead (T + 1) and two-day-ahead (T + 2) forecasting for the overall forecasting process and the flood peak forecasts. The results suggest that the rainfall data can enhance the robustness of the model, especially in T + 2 forecasting. Additionally, it slightly introduces noise and affects the optimized prediction accuracy in T + 1 forecasting, but significantly improves the accuracy in T + 2 forecasting. Though with relevance (R = 0.409~0.763, Grey correlation grade >0.99), the runoff data at the adjacent tributary has an adverse effect on the robustness, but can enhance the accuracy of the flood peak forecasts with a short lead time. The models with PCA denoised input has an equivalent, even better performance on the robustness and accuracy compared with the models with the well manually filtered data; though slightly reduces the time-step robustness, the bi-directional architecture can enhance the prediction accuracy. All the scenarios provide acceptable forecasting results (NSE of 0.927~0.951 for T + 1 forecasting and 0.745~0.836 for T + 2 forecasting) when the hyperparameters have already been optimized. Based on the results, recommendations have been provided for the construction of the GRU runoff forecasting model. Full article
(This article belongs to the Special Issue Advanced Hydrologic Modeling in Watershed-Scale)
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Article
A New Runoff Routing Scheme for Xin’anjiang Model and Its Routing Parameters Estimation Based on Geographical Information
Water 2020, 12(12), 3429; https://doi.org/10.3390/w12123429 - 06 Dec 2020
Viewed by 529
Abstract
The Xin’anjiang model is a conceptual hydrological model, which has an essential application in humid and semi-humid regions. In the model, the parameters estimation of runoff routing has always been a significant problem in hydrology. The quantitative relationship between parameters of the lag-and-route [...] Read more.
The Xin’anjiang model is a conceptual hydrological model, which has an essential application in humid and semi-humid regions. In the model, the parameters estimation of runoff routing has always been a significant problem in hydrology. The quantitative relationship between parameters of the lag-and-route method and catchment characteristics has not been well studied. In addition, channels in Muskingum method of the Xin’anjiang model are assumed to be virtual channels. Therefore, its parameters need to be estimated by observed flow data. In this paper, a new routing scheme for the Xin’anjiang model is proposed, adopting isochrones method for overland flow and the grid-to-grid Muskingum–Cunge–Todini (MCT) method for channel routing, so that the routing parameters can be estimated according to the geographic information. For the new routing scheme the average overland flow velocity can be determined through the land cover and overland slope, and the channel routing parameters can be determined through channel geometric characteristic, stream order and channel gradient. The improved model was applied at a 90 m grid scale to a nested watershed located in Anhui province, China. The parent Tunxi watershed, with a drainage area of 2692 km2, contains four internal points with available observed streamflow data, allowing us to evaluate the model’s ability to simulate the hydrologic processes within the watershed. Calibration and verification of the improved model were carried out for hourly time scales using hourly streamflow data from 1982 to 2005. Model performance was assessed by comparing simulated and observed flows at the watershed outlet and interior gauging stations. The performance of both original and new runoff routing schemes were tested and compared at hourly scale. Similar and satisfactory performances were achieved at the outlet both in the new runoff routing scheme using the estimated routing parameters and in the original runoff routing scheme using the calibrated routing parameters, with averaged Nash-Sutcliffe efficiency (NSE) of 0.92 and 0.93, respectively. Moreover, the new runoff routing scheme is also able to reproduce promising hydrographs at internal gauges in study catchment with the mean NSE ranging from 0.84 to 0.88. These results indicate that the parameter estimation approach is efficient and the developed model can satisfactorily simulate not only the streamflow at the parent watershed outlet, but also the flood hydrograph at the interior gauging points without model recalibration. This study can provide some guidance for the application of the Xin’anjiang model in ungauged areas. Full article
(This article belongs to the Special Issue Advanced Hydrologic Modeling in Watershed-Scale)
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Article
Influence of Land Use Change on Hydrological Cycle: Application of SWAT to Su-Mi-Huai Area in Beijing, China
Water 2020, 12(11), 3164; https://doi.org/10.3390/w12113164 - 12 Nov 2020
Cited by 1 | Viewed by 562
Abstract
The human activities and urbanization process have changed the underlying surface of urban areas, which would affect the recharge of groundwater through rainfall infiltration and may further influence the groundwater environment. Accordingly, it is imperative to investigate the variation of hydrological cycle under [...] Read more.
The human activities and urbanization process have changed the underlying surface of urban areas, which would affect the recharge of groundwater through rainfall infiltration and may further influence the groundwater environment. Accordingly, it is imperative to investigate the variation of hydrological cycle under the condition of underlying surface change. Based on the high-precision remote sensing data of 2000, 2005, 2010 and 2015, and Soil and Water Assessment Tool (SWAT) model, this work firstly studied the land use change and the corresponding changes in runoff generation mechanism and rainfall infiltration coefficient in Su-Mi-Huai area, Beijing, China. Meanwhile, SWAT-MODFLOW semi-loose coupling model was applied to analyze the water balance in the study area in typical hydrological years. The results showed that the area of the construction land (urban and rural residential land) increased by 1.04 times from 2000 to 2015, which is mainly attributed to the conversion of cultivated land to construction land in the plain area. This change caused the runoff in the area to increase by 7 × 106 m3, the runoff coefficient increased by 17.9%, and the precipitation infiltration coefficient was less than the empirical value determined by lithology. Compared with 2000, the average annual precipitation infiltration coefficient in 2018 decreased by 6.5%. Under the influence of urbanization process, the maximum reduction rate of precipitation infiltration recharge is up to 38%. The study investigated the response of surface runoff and precipitation infiltration recharge to land use change, which can provide helps for water resources managers to coordinate the relationship between land use change and rational water resources planning. Full article
(This article belongs to the Special Issue Advanced Hydrologic Modeling in Watershed-Scale)
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Article
Change in Stream Flow of Gumara Watershed, upper Blue Nile Basin, Ethiopia under Representative Concentration Pathway Climate Change Scenarios
Water 2020, 12(11), 3046; https://doi.org/10.3390/w12113046 - 30 Oct 2020
Cited by 1 | Viewed by 689
Abstract
Climate change plays a pivotal role in the hydrological dynamics of tributaries in the upper Blue Nile basin. The understanding of the change in climate and its impact on water resource is of paramount importance to sustainable water resources management. This study was [...] Read more.
Climate change plays a pivotal role in the hydrological dynamics of tributaries in the upper Blue Nile basin. The understanding of the change in climate and its impact on water resource is of paramount importance to sustainable water resources management. This study was designed to reveal the extent to which the climate is being changed and its impacts on stream flow of the Gumara watershed under the Representative Concentration Pathway (RCP) climate change scenarios. The study considered the RCP 2.6, RCP 4.5, and RCP 8.5 scenarios using the second-generation Canadian Earth System Model (CanESM2). The Statistical Downscaling Model (SDSM) was used for calibration and projection of future climatic data of the study area. Soil and Water Assessment Tool (SWAT) model was used for simulation of the future stream flow of the watershed. Results showed that the average temperature will be increasing by 0.84 °C, 2.6 °C, and 4.1 °C in the end of this century under RCP 2.6, RCP 4.5, and RCP 8.5 scenarios, respectively. The change in monthly rainfall amount showed a fluctuating trend in all scenarios but the overall annual rainfall amount is projected to increase by 8.6%, 5.2%, and 7.3% in RCP 2.6, RCP 4.5, and RCP 8.5, respectively. The change in stream flow of Gumara watershed under RCP 2.6, RCP 4.5, and RCP 8.5 scenarios showed increasing trend in monthly average values in some months and years, but a decreasing trend was also observed in some years of the studied period. Overall, this study revealed that, due to climate change, the stream flow of the watershed is found to be increasing by 4.06%, 3.26%, and 3.67%under RCP 2.6, RCP 4.5, and RCP 8.5 scenarios, respectively. Full article
(This article belongs to the Special Issue Advanced Hydrologic Modeling in Watershed-Scale)
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Article
Urban Runoff Simulation: How Do Land Use/Cover Change Patterning and Geospatial Data Quality Impact Model Outcome?
Water 2020, 12(10), 2715; https://doi.org/10.3390/w12102715 - 28 Sep 2020
Cited by 2 | Viewed by 806
Abstract
With the increase in global urbanization, satellite imagery and other types of geospatial data have been extensively used in urban landscape change research, which includes environmental modeling in order to assess the change impact on urban watersheds. For urban hydrological modeling, as a [...] Read more.
With the increase in global urbanization, satellite imagery and other types of geospatial data have been extensively used in urban landscape change research, which includes environmental modeling in order to assess the change impact on urban watersheds. For urban hydrological modeling, as a focus of this study, several related research questions are raised: (1) How sensitive are runoff simulation to land use and land cover change patterning? (2) How will input data quality impact the simulation outcome? (3) How effective is integrating and synthesizing various forms of geospatial data for runoff modeling? These issues were not fully or adequately addressed in previous related studies. With the aim of answering these questions as research objectives, we conducted a spatial land use and land cover (LULC) change analysis and an urban runoff simulation in the Blue River watershed in the Kansas City metropolitan area between 2003 and 2017. In this study, approaches were developed to incorporate the Hydrologic Engineering Center Hydrologic Modeling System (HEC-HMS) model with remote sensing, geographic information systems (GIS), and radar rainfall data. The impact of data quality on the model simulation outcome was also analyzed. The results indicate that there are no significant differences between simulated runoff responses in the two study years (2003 and 2017) due to spatial and temporal heterogeneity of urbanization processes in the region. While the metropolitan area has been experiencing remarkable urban development in the past few decades, the gain in built-up land in the study watershed during the study period is insignificant. On the other hand, the gain in vegetated land caused by forestation activities is offset by a decrease in farmland and grassland. The results show that increasing spatial data resolution does not necessarily or noticeably improve the HEC-HMS model performance or outcomes. Under these conditions, using Next Generation Weather Radar (NEXRAD) rainfall data in the simulation provides a satisfactory fit in hydrographs’ shapes, peak discharge amounts and time after calibration efforts, while they may overestimate the amount of rainfall as compared with gauge data. This study shows that the developed approach of synthesizing satellite, GIS, and radar rainfall data in hydrological modeling is effective and useful for incorporating urban landscape and precipitation change data in dynamic flood risk assessment at a watershed level. Full article
(This article belongs to the Special Issue Advanced Hydrologic Modeling in Watershed-Scale)
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Article
Estimation of Flood Travel Time in River Network of the Middle Yellow River, China
by
Water 2020, 12(6), 1550; https://doi.org/10.3390/w12061550 - 29 May 2020
Viewed by 614
Abstract
The flood travel time (FTT) along the Longmen-Tongguan Reach, part of the stem channel of the Middle Yellow River, is shorter than 30 h, and estimating the FTT of different discharges propagating from Wubu Hydrology Station to Tongguan Hydrology Station is necessary. However, [...] Read more.
The flood travel time (FTT) along the Longmen-Tongguan Reach, part of the stem channel of the Middle Yellow River, is shorter than 30 h, and estimating the FTT of different discharges propagating from Wubu Hydrology Station to Tongguan Hydrology Station is necessary. However, the propagation of floods in this river network, the main channel of the Wubu-Tongguan Reach and related tributaries, has rarely been analyzed due to the lack of geometry data. Thus, a one-dimensional (1D) dynamic model was selected to simulate the FTT along the WT reach. Firstly, the 1986 flood event was selected to calibrate the physical parameters in the hydraulic model. Secondly, the FTT with different discharges (500–9000 m3/s) were estimated with calibrated parameters. Thirdly, an empirical formula based on simulated results was fitted. This empirical formula could be used to describe the relation between discharges, distances to Tongguan Hydrology Station, and the FTT. Analyses showed that the discharges with minimum FTT were different for different tributaries. For the river reach between Wubu Hydrology Station and the Wuding River, the discharge and corresponding minimum FTT were 6000 m3/s and approximately 30.4–34 h, respectively. For the river reach between the Zhouchuan and Qingjian Rivers, the discharge and FTT were 3000–3500 m3/s and 21–26.8 h, respectively. The formula can be used to estimate the FTT of flood events, which would be cost-saving and time-saving for river management. Sensitivity analyses indicated that the FTT were sensitive to the Tongguan elevation and Manning’s roughness coefficient in the main channel. Full article
(This article belongs to the Special Issue Advanced Hydrologic Modeling in Watershed-Scale)
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Article
Calibration of a Distributed Hydrological Model in a Data-Scarce Basin Based on GLEAM Datasets
Water 2020, 12(3), 897; https://doi.org/10.3390/w12030897 - 22 Mar 2020
Cited by 5 | Viewed by 1154
Abstract
The calibration of hydrological models is often complex in regions with scarce data, and generally only uses site-based streamflow data. However, this approach will yield highly generalised values for all model parameters and hydrological processes. It is therefore necessary to obtain more spatially [...] Read more.
The calibration of hydrological models is often complex in regions with scarce data, and generally only uses site-based streamflow data. However, this approach will yield highly generalised values for all model parameters and hydrological processes. It is therefore necessary to obtain more spatially heterogeneous observation data (e.g., satellite-based evapotranspiration (ET)) to calibrate such hydrological models. Here, soil and water assessment tool (SWAT) models were built to evaluate the advantages of using ET data derived from the Global Land surface Evaporation Amsterdam Methodology (GLEAM) to calibrate the models for the Bayinhe River basin in northwest China, which is a typical data-scarce basin. The result revealed the following: (1) A great effort was required to calibrate the SWAT models for the study area to obtain an improved model performance. (2) The SWAT model performance for simulating the streamflow and water balance was reliable when calibrated with streamflow only, but this method of calibration grouped the hydrological processes together and caused an equifinality issue. (3) The combination of the streamflow and GLEAM-based ET data for calibrating the SWAT model improved the model performance for simulating the streamflow and water balance. However, the equifinality issue remained at the hydrologic response unit (HRU) level. Full article
(This article belongs to the Special Issue Advanced Hydrologic Modeling in Watershed-Scale)
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Article
A New Algorithm for Delineation of Surface Depressions and Channels
Water 2020, 12(1), 7; https://doi.org/10.3390/w12010007 - 18 Dec 2019
Cited by 3 | Viewed by 1021
Abstract
Topographic delineation is critical to watershed hydrologic modeling, which may significantly influence the accuracy of model simulations. In most traditional delineation methods, however, surface depressions are fully filled and hence, watershed-scale hydrologic modeling is based on depression-less topography. In reality, dynamic filling and [...] Read more.
Topographic delineation is critical to watershed hydrologic modeling, which may significantly influence the accuracy of model simulations. In most traditional delineation methods, however, surface depressions are fully filled and hence, watershed-scale hydrologic modeling is based on depression-less topography. In reality, dynamic filling and spilling of depressions affect hydrologic connectivity and surface runoff processes, especially in depression-dominated areas. Thus, accounting for the internal hydrologic connectivity within a watershed is crucial to such hydrologic simulations. The objective of this study was to improve watershed delineation to further reveal such complex hydrologic connectivity. To achieve this objective, a new algorithm, HUD-DC, was developed for delineation of hydrologic units (HUs) associated with depressions and channels. Unlike the traditional delineation methods, HUD-DC considers both filled and unfilled conditions to identify depressions and their overflow thresholds, as well as all channels. Furthermore, HUs, which include puddle-based units and channel-based units, were identified based on depressions and channels and the detailed connectivity between the HUs was determined. A watershed in North Dakota was selected for testing HUD-DC, and Arc Hydro was also utilized to compare with HUD-DC in depression-oriented delineation. The results highlight the significance of depressions and the complexity of hydrologic connectivity. In addition, HUD-DC was utilized to evaluate the variations in topographic characteristics under different filling conditions, which provided helpful guidance for the identification of filling thresholds to effectively remove artifacts in digital elevation models. Full article
(This article belongs to the Special Issue Advanced Hydrologic Modeling in Watershed-Scale)
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