The Regional Hydro-Ecological Simulation System for 30 Years: A Systematic Review
Abstract
:1. Introduction
2. The Basic Structure and Development History of RHESSys
3. Research Trends and Characteristics
4. Main Application Progress of RHESSys
4.1. Climate Change
4.2. Disturbance
4.3. Urbanization
4.4. Water Quality
4.5. Land Management
4.6. Biogeochemical Cycle
5. Calibration, Validation, and Uncertainty Analysis of RHESSys
5.1. Calibration
5.2. Verification and Uncertainty Analysis
6. Future Perspectives of RHESSys
6.1. Key Challenges
6.2. Future Directions
7. Conclusions
Supplementary Materials
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Model | Structure | Key Processes Representing Eco-Hydrological Interactions | Applications | References |
---|---|---|---|---|
RHESSys | Basin-Zone-Hillslope-Patch-Canopy strata | Carbon and nitrogen cycling of soil and vegetation, Plant physiological process, Evapotranspiration, Lateral flow, Slope confluence | Urbanization, Water quality, Climate change, Disturbance, Water resource management, Land management, Biogeochemical cycle | [2] |
TOPOG_IRM | Basin-subbasin | Carbon cycling of vegetation, Plant physiological process, Evapotranspiration, Lateral flow, Slope confluence | Climate change, Disturbance, Water resource management, Land management, Biogeochemical cycle | [19] |
SWAT (Soil and Water Assessment Tool) | Basin-subbasin-Hydrological response units | Evapotranspiration, Lateral flow | Urbanization, Water quality, Climate change, Water resource management, Land management | [20] |
BEPS-TerrainLab (Boreal Ecosystem Productivity Simulator-TerrainLab) | Basin-grid | Carbon and nitrogen cycling of soil and vegetation, Plant physiological process, Evapotranspiration, Lateral flow, Slope confluence | Water resource management, Biogeochemical cycle | [21] |
tRIBS-VEGGIE (TIN-based Real-time Integrated Basin Simulator-Vegetation Generator for Interactive Evolution) | Basin-tin | Carbon cycling of soil and vegetation, Plant physiological process, Evapotranspiration, Lateral flow Slope confluence | Disturbance, Water resource management, Biogeochemical cycle | [22] |
Category | Parameters | Description | Observed Data | Criteria * | Methods | References |
---|---|---|---|---|---|---|
Soil | m | The decay rate of saturated hydraulic conductivity with soil depth | Streamflow | NSe, LogNSe, RMSE, PBIAS, RSR | Monte Carlo, GLUE | [9,33,37,55,59] |
Ksat0 | The saturated hydraulic conductivity at the soil surface (both dimension) | |||||
gw1 | Groundwater bypass flow, dimensionless | |||||
gw2 | Groundwater drainage rate, dimensionless | |||||
psi | Soil pore-size index, dimensionless | |||||
psi_air_entry | Soil air-entry pressure, dimensionless | |||||
soil depth | Maximum soil dept, dimensionless | |||||
Snow | Lapse_rate | The lapse rates for the daily maximum and minimum air temperature | Snow depth, SWE, Streamflow | R2 | Manually adjusted | [31,37,55] |
max_snow_tem | Temperature threshold values for the partition of snow and rain in the total precipitation | |||||
temcf | An empirical temperature melt coefficient (accounting for snowmelt due to latent and sensible heat) | |||||
Vegetation | phenology date | Number of days for leaf out period and number of days for litterfall period | LAI | RMSE, Literature-based value | Manually adjusted | [18,38,54] |
Q10 | Maintenance respiration (The proportional change in respiration per 10C rise in temperature) | |||||
epc.flnr | Ration Leaf nitrogen in Rubisco to leaf nitrogen | |||||
epc.proj_sla | Specific leaf area | |||||
Water quality | kg | Base growth rate of chl-a in algae | DON, DOC fluxes | Kolmogorov-Smirnov D test | Monte Carlo, GLUE, Latin hypercube sampling (LHS) | [44,56] |
kd | Base death rate of chl-a in algae | |||||
kr | Base respiration rate of chl-a in algae | |||||
vs | Settling rate of algae as chl-a | |||||
ksn | Half saturation concentration of nitrogen | |||||
ksp | Half saturation concentration of Phosphorous | |||||
P | Phosphorous concentration in the SCM | |||||
kpn | Constant of preferential NH4 uptake, over NO3 | |||||
qg | Constant for kg dependency on temperature | |||||
qd | Constant for kd dependency on temperature | |||||
qr | Constant for kr dependency on temperature | |||||
Is | Optimum radiation level for algae growth |
Category | Observed Data | Source | Time Resolution | Criteria * | Methods ** | References |
---|---|---|---|---|---|---|
Streamflow | Streamflow | Gauge measurement | Daily, Monthly, Annual | NSe, LogNSe, PBIAS, R2 | Statistical analysis | [61] |
Gauge measurement | Daily | Peak flow error, NSe, Flow variability, R2 | Statistical analysis | [63] | ||
Gauge measurement | Daily, Monthly, Annual | NSe, PBIAS | MLE | [64] | ||
Soil | Soil moisture | Field measurement | Daily | R | Correlation analysis | [65] |
Snow | Snowmelt | Field measurement | Daily | R2 | Correlation analysis | [37] |
Snow depth | Field measurement | Daily | R2 | Correlation analysis | [54] | |
Vegetation | ET | Flux tower measurement | Daily | R2 | Correlation analysis | [59] |
Flux tower measurement | Daily | RMSE, PBIAS, R2 | Correlation analysis | [5] | ||
GPP | Remote sensing | Monthly | R2 | Correlation analysis | [59] | |
Flux tower measurement | Daily | RMSE, PBIAS, R2 | Correlation analysis | [5] | ||
NPP | Field measurement | Daily | N/A | Qualitative | [64] | |
Field measurement | Annual | N/A | Qualitative | [67] | ||
Remote sensing | Annual | Mean error | Statistical analysis | [9] | ||
PSNet | Remote sensing | Daily | R2 | Correlation analysis | [59] | |
Transpiration | Field measurement | Daily | R | Correlation analysis | [64] | |
LAI | Field measurement | Daily | N/A | Qualitative | [68] | |
Remote sensing | Daily | N/A | Qualitative | [9] | ||
Water quality | DOC | Gauge measurement | Daily, Monthly, Annual | NSe, LogNSe | WRTD | [48] |
NO3 | Monthly | NSe, R | Statistical analysis | [44] |
Source | Specific Sources | Solutions | References |
---|---|---|---|
Input Data | Coarse-resolution of DEM | Fine-resolution DEM data | [55] |
Lack of detailed precipitation, gauge, soil, and other basic data | Multi-source data acquisition | [6,34,37,71] | |
Lack of carbon fluxes and pool data | Spin-up strategy, and integrate remote sensing data | [34] | |
Model structure and algorithms | Interpolation strategy of air temperature and precipitation | Explicitly incorporate spatial characteristics of surface metrological variables | [7,37,54,71,72,73] |
Without the plant migration and structure change | Couple vegetation dynamic models | [66] | |
Without the in-stream process | SCM sub-model | [2,56] | |
Scale problem | In-stream routing, and adapted landscape partitioning strategy | [9] | |
Parameters | Simplification of vegetation variability | Multi-source data assimilation | [66,74] |
Empirical parameters | Detailed filed studies, Calibration | [54,66,71,75] |
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Chen, B.; Liu, Z.; He, C.; Peng, H.; Xia, P.; Nie, Y. The Regional Hydro-Ecological Simulation System for 30 Years: A Systematic Review. Water 2020, 12, 2878. https://doi.org/10.3390/w12102878
Chen B, Liu Z, He C, Peng H, Xia P, Nie Y. The Regional Hydro-Ecological Simulation System for 30 Years: A Systematic Review. Water. 2020; 12(10):2878. https://doi.org/10.3390/w12102878
Chicago/Turabian StyleChen, Benxin, Zhifeng Liu, Chunyang He, Hui Peng, Pei Xia, and Yu Nie. 2020. "The Regional Hydro-Ecological Simulation System for 30 Years: A Systematic Review" Water 12, no. 10: 2878. https://doi.org/10.3390/w12102878
APA StyleChen, B., Liu, Z., He, C., Peng, H., Xia, P., & Nie, Y. (2020). The Regional Hydro-Ecological Simulation System for 30 Years: A Systematic Review. Water, 12(10), 2878. https://doi.org/10.3390/w12102878