An Improved Grid-Xinanjiang Model and Its Application in the Jinshajiang Basin, China
Abstract
:1. Introduction
2. Improved GXAJ Model Formulation
2.1. Two-Source Potential Evapotranspiration (TSPE) Model
2.2. Infiltration and Saturation Excess Runoff Model (ISER)
2.3. Nonlinear Muskingum–Cunge Routing Method
2.4. Schematic Diagram of the Integration of the ANNs with Conceptual Models
3. A Brief Description of the Study Area
4. Materials and Methods
4.1. Topographical Land Cover Data
4.2. Modis LAI
4.3. Meteorological Data
4.4. A Prior Parameter Estimation
5. Results and Discussion
5.1. Evaluation of the Simulated Streamflow
5.2. Uncertainty Analysis
5.3. Annual Water Budget Simulated by the Modified Xinanjiang Model
5.4. Seasonal Variation of the Evapotranspiration and the Soil Moisture
5.5. Spatial Patterns of the Annual Precipitation and Evapotranspiration
6. Conclusions
Author Contributions
Funding
Conflicts of Interest
Abbreviations
GXAJ | Grid-Xinanjiang model |
TSPE | two-source potential evapotranspiration model |
CT | canopy transpiration |
IE | interception evaporation |
SE | soil evaporation |
PE | potential evapotranspiration |
DEM | digital elevation model |
MODIS | Moderate Resolution Imaging Spectroradiometer |
LAI | leaf area index |
BNU | Beijing Normal University |
XAJ | Xinanjiang |
IER | infiltration excess runoff |
SER | saturation excess runoff |
AE | actual evapotranspiration |
NMC | nonlinear Muskingum–Cunge |
SR | surface runoff |
TWC | tension water capacity |
SIC | soil infiltration capacity |
ISER | Infiltration and saturation excess runoff model |
FWC | free water capacity |
SRTM | shuttle radar topography mission |
MMAP | measured mean annual precipitation |
GR | groundwater runoff |
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Watershed | Area (km2) | Evaporation (mm) | PE (mm) | Temperature (°C) | Runoff (mm) | Runoff Coeff | Climate Zone |
---|---|---|---|---|---|---|---|
Sub-basin 1 | 214,184 | 461.5 | 1351.54 | 0.44 | 201.90 | 0.44 | Semi-arid, semi-humid |
Sub-basin 2 | 136,000 | 753.16 | 1264.57 | 7.43 | 446.16 | 0.59 | Semi-humid |
Sub-basin 3 | 108,616 | 909.76 | 1267.21 | 13.52 | 479.53 | 0.53 | Humid |
Module | Parameter | Description | Acquisition Method |
---|---|---|---|
Two-source potential evapotranspiration | rmin | minimum stamatal resistance(sm−1) | based on land data assimilation system (LDAS) |
ac | albedo | based on land data assimilation system (LDAS) | |
h | height of vegetation(m) | based on land data assimilation system (LDAS) | |
Wmax | maximum leaf width | based on land data assimilation system (LDAS) | |
d0 | monthly zero-plane displacement | based on land data assimilation system (LDAS) | |
z0 | monthly roughness length | based on land data assimilation system (LDAS) | |
LAI | Leaf area index | from the BNU MODIS LAI dataset | |
Actual evaporation | Wum | tension water capacity (TWC) of upper layer (mm) | Based on WM |
Wlm | TWC of lower layer (mm) | Based on WM | |
C | evapotranspiration coefficient of deeper layer | determined by optimization algorithm | |
Runoff generation | Wm | TWC (mm) | using θfc, θwp, and aeration zone thickness |
θs | saturated moisture content | from literature | |
θfc | field capacity | from literature | |
θwp | wilting point | from literature | |
Sm | free water capacity (FWC; mm) | using θs, θfc, and humus layer thickness | |
Ki | outflow coefficient of FWS to interflow | on the basis of soil properties | |
Kg | outflow coefficient of FWS to groundwater | on the basis of soil properties | |
Ci | recession coefficient of interflow water | determined by optimization algorithm | |
Cg | recession coefficient of groundwater water | outflow of dry season at time t+1, t | |
Nonlinear Muskingum–Cunge routing method | n | Manning roughness coefficient | from literature |
q0 | water discharge of reference(m3s−1) | using outflow and inflow of each grid | |
S0 | river bed slope | derived from the shuttle radar topography mission (SRTM) digital elevation model (DEM) | |
w | width of a river reach (m) | derived from the drainage area | |
Dx′ | length of a river reach(m) | using total river length within each grid | |
Infiltration and saturation excess runoff | b | exponent of TWC capacity distribution curve | determined by optimization algorithm |
B | exponent of soil infiltration capacity distribution curve | determined by optimization algorithm | |
a | average basal area of plant stems | determined by optimization algorithm |
Parameter | Category | Calibration | Validation | ||||
---|---|---|---|---|---|---|---|
Sub-Basin 1 | Sub-Basin 2 | Sub-Basin 3 | Sub-Basin 1 | Sub-Basin 2 | Sub-Basin 3 | ||
Modified GRAJ Model | |||||||
NSE (%) | mean annual flow | 95.39 | 88.97 | 94.80 | 94.81 | 88.35 | 95.63 |
rainy season | 91.26 | 83.54 | 92.19 | 91.58 | 85.03 | 93.86 | |
dry season | 81.68 | 61.06 | 82.82 | 76.94 | 58.49 | 87.70 | |
RE | mean annual flow | −2.60 | −6.51 | 1.41 | 4.26 | −6.88 | 1.20 |
rainy season | −3.65 | −5.97 | 1.11 | 3.46 | −4.53 | 2.97 | |
dry season | 4.95 | −11.10 | 2.43 | 8.27 | −12.77 | −3.97 | |
PEP | rainy season | −3.80 | −9.80 | −4.40 | −4.80 | −8.60 | −3.40 |
PEV | rainy season | −6.50 | −11.50 | 2.60 | 6.13 | −8.65 | 5.35 |
ISER + GRAJ Model | |||||||
NSE | mean annual flow | 94.22 | 86.68 | 93.34 | 93.59 | 85.87 | 94.66 |
rainy season | 89.29 | 81.87 | 90.05 | 90.02 | 83.10 | 93.00 | |
dry season | 80.34 | 62.18 | 80.95 | 74.34 | 56.67 | 85.37 | |
RE | mean annual flow | −3.70 | −6.88 | −2.10 | 4.65 | −6.30 | -2.50 |
rainy season | −4.50 | −6.60 | −1.82 | 4.12 | −5.70 | −2.90 | |
dry season | 6.20 | −12.00 | −4.20 | 8.67 | −11.90 | 3.50 | |
PEP | rainy season | −4.60 | −10.10 | −5.10 | −5.30 | 9.50 | −4.10 |
PEV | rainy season | −7.10 | −13.20 | −4.30 | 7.32 | −12.46 | −5.12 |
TSPE + GRAJ Model | |||||||
NSE | mean annual flow | 92.33 | 81.90 | 91.16 | 92.59 | 76.98 | 90.66 |
rainy season | 87.17 | 80.44 | 89.15 | 87.66 | 80.30 | 92.32 | |
dry season | 75.60 | 60.66 | 76.90 | 69.38 | 56.99 | 82.46 | |
RE | mean annual flow | −8.03 | −7.83 | −2.01 | −5.12 | −8.94 | −3.31 |
rainy season | −7.90 | −7.37 | −2.53 | −4.17 | −7.24 | −2.90 | |
dry season | −8.23 | −12.00 | 5.62 | −9.46 | −15.30 | −7.42 | |
PEP | rainy season | −9.70 | −12.40 | −7.70 | −9.20 | −11.70 | −6.20 |
PEV | rainy season | −14.50 | −16.30 | −7.05 | −8.47 | −14.87 | −5.31 |
Uncertainty Parameter | Catchment | ||
---|---|---|---|
Sub-Basin 1 | Sub-Basin 2 | Sub-Basin 3 | |
average relative length (ARIL) | 0.265 | 0.513 | 0.267 |
average asymmetry degree (AAD) | 0.300 | 0.324 | 0.298 |
average deviation amplitude (ADA) | 285.878 | 406.498 | 108.610 |
Watershed | Year | Precipitation | Storage Change | Modeled Annual Actual Evaporation | Measured Discharge |
---|---|---|---|---|---|
Sub-basin 1 | mean annual (mm) | 461.50 | −1.08 | 258.63 | 201.90 |
σ/Mean | 0.23 | - | 0.09 | 0.38 | |
correlation with Precipitation | 1.00 | 0.85 | 0.41 | 0.81 | |
Sub-basin 2 | mean annual (mm) | 753.16 | −1.40 | 338.12 | 446.16 |
σ/Mean | 0.20 | - | 0.07 | 0.40 | |
correlation with Precipitation | 1.00 | 0.66 | 0.64 | 0.95 | |
Sub-basin 3 | mean annual (mm) | 909.76 | 1.62 | 422.21 | 479.53 |
σ/Mean | 0.27 | - | 0.07 | 0.46 | |
correlation with Precipitation | 1.00 | 0.62 | 0.59 | 0.94 |
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Meng, C.; Zhou, J.; Zhong, D.; Wang, C.; Guo, J. An Improved Grid-Xinanjiang Model and Its Application in the Jinshajiang Basin, China. Water 2018, 10, 1265. https://doi.org/10.3390/w10091265
Meng C, Zhou J, Zhong D, Wang C, Guo J. An Improved Grid-Xinanjiang Model and Its Application in the Jinshajiang Basin, China. Water. 2018; 10(9):1265. https://doi.org/10.3390/w10091265
Chicago/Turabian StyleMeng, Changqing, Jianzhong Zhou, Deyu Zhong, Chao Wang, and Jun Guo. 2018. "An Improved Grid-Xinanjiang Model and Its Application in the Jinshajiang Basin, China" Water 10, no. 9: 1265. https://doi.org/10.3390/w10091265