# Effects of Microtopography on Runoff Generation in Plain Farmland: New Insights from an Event-Based Rainfall–Runoff Model

^{1}

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## Abstract

**:**

## 1. Introduction

## 2. Materials and Methods

#### 2.1. Site, Instrument, and Soil Sampling

^{2}, in which 4186 scattered elevation sample points were collected. The average sampling density was about 4 points/m

^{2}and the corresponding sampling interval was 0.5 m. We adopted the Regularized Spline interpolation method to obtain 0.1 m-resolution DEM of the field (Figure 2a). The elevations varied from 2.45 m to 3.74 m with a mean of 3.14 m. Distinct layered characteristics can be seen from the excavated soil profile in the field, i.e., 0–13 cm is plough layer(A), 13–22 cm is plow pan (A

_{p}), 22–47 cm is percogenic horizon(P), and below 47 cm is waterloggogenic horizon(W). A meteorological station, a soil moisture profile (10 cm, 20 cm, 40 cm, 60 cm, 80 cm, 100 cm), and a groundwater observation well has been set up in the field since 2011.

^{2}with an average length of 87 m and average width of 10.5m. Meanwhile, Ditch 1 and Ditch 2 are the two main artificial drainage pathways surrounding the main field. Ditch 1 collects the outflow from the main field and Ditch 2 collects the lateral leakage flow from rice fields outside. A 90° V-notch weir was set up to measure outflow discharge at the outlet of Ditch 1.

#### 2.2. Model Structure

_{g}recharging to groundwater.

^{2}and the area ratio was 60%, the rill was 136.8 m

^{2}and the area ratio was 15%, and the ditch was 228 m

^{2}and the area ratio was 25%. The relative average elevation of the main field was set as 0 cm. Based on the geometry of Ditch 1 and field investigation, the relative elevations of the rill and ditch were −10 cm and −30 cm, respectively.

#### 2.3. Model Performance

#### 2.4. Modeling Cases

## 3. Results

#### 3.1. Homogeneous Soil during Unsteady Rainfall

_{c}was 0, effective saturated hydraulic conductivity K

_{s}was 1.42 cm/h, and the product of the effective suction (S) of the wetting front and the initial soil water deficit (M) was 3.6 cm. When the rainfall intensity was larger than the infiltration capacity, the infiltration-excess runoff occurred. The shift time was called the ponding moment. Only one ponding moment occurred in the first case and three ponding moments occurred in the second case. The infiltration-excess runoff ceased as rainfall intensity was smaller than the infiltration capacity. The rainfall intensity and decreasing infiltration capacity jointly controlled surface runoff generation. The calculated ponding time, infiltration volume, and infiltration rate of this proposed model were all consistent with Chu’s results (Figure 5).

#### 3.2. Ponding Infiltration Experiment on the Field

_{s}was set as the average value of K

_{s}(0.07 cm/min) in 0–10 cm. However, the simulated ponding depths were clearly overestimated. Then we increased the value of K

_{s}by 15 percent of the last trial value. The final effective saturated hydraulic conductivity K

_{s}was 0.018 cm/min. (Table 2).

_{s}from top to bottom and the initial trial value of each layer was set as 0.018 cm/min. The final calibrated parameters are shown in Table 2. The simulated ponding water depths in the multilayered case were better than that of the homogeneous case. The RMSE and NSE of the multilayered case was 0.035 cm and 0.999, respectively. By increasing the effective saturated hydraulic conductivity of the topsoil, the simulated infiltration rate after the first injection in the multilayered case became larger than that of the homogeneous case. Furthermore, when the wetting front advanced to deeper soil, the multilayered settings of initial soil water deficit and effective saturated hydraulic conductivity reduced the infiltration rate, which was more reasonable. The homogeneous case would underestimate the final wetting front depth in this experiment.

#### 3.3. Rainfall–Runoff Events Simulation

#### 3.3.1. Typical Short-Duration Rainstorm Event

_{c}was 5 mm, Q

_{g}was 0.01 mm/min. Average concentration time T was set as four levels, i.e., 0(direct outflow), 10, 13, and 15 min. The time step was set as one minute.

#### 3.3.2. Typical Long-Duration Light Rainfall Event

_{c}was 5 mm and Q

_{g}was 0.01 mm/min. The concentration time was set as 20, 30, and 40 min. Time step was set as one minute.

## 4. Discussion

## 5. Conclusions

## Author Contributions

## Funding

## Institutional Review Board Statement

## Informed Consent Statement

## Data Availability Statement

## Acknowledgments

## Conflicts of Interest

## References

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**Figure 1.**Information of the experimental field: (

**a**) location of Hongqi polder; (

**b**) land use of Hongqi polder; (

**c**) location of the experimental field.

**Figure 2.**(

**a**) Topography (0.1 m−resolution DEM) and layout of the experimental field; (

**b**) three−dimensional view of the isolated catchment; (

**c**) section shape of western ditch; (

**d**) section shape of eastern ditch.

**Figure 3.**Schematic representation of the Green–Ampt model for layered soils under nonsteady rainfall infiltration.

**Figure 4.**Schematic of rainfall–runoff model considering effects of microtopography: (

**a**) a rainfall–runoff event at the field; (

**b**) model structure.

**Figure 6.**Ponding infiltration experiment on the field: (

**a**)schematic diagram; (

**b**) modeling results of homogeneous and multilayered cases.

**Figure 7.**Simulated hydrographs of different concentration time in unified topography case in 20160808 rainfall event.

**Figure 8.**The 20160808 runoff case considering the effect of microtopography: (

**a**) classified topography setting; (

**b**) observed and simulated results.

**Figure 9.**Observed and simulated hydrographs of unified topography cases of different concentration times in 20160406 rainfall event.

**Figure 10.**The 20160406 runoff case considering the effect of microtopography: (

**a**) classified topography setting; (

**b**) simulation results.

**Table 1.**Average values of grain composition, physical properties, and saturated hydraulic conductivities of five depths in the experimental field. Range is in parentheses (minimum/maximum values).

Depth (cm) | Clay (-) | Silt (-) | ${\mathit{\rho}}_{\mathit{b}}$ (g/cm ^{3})
| $\mathit{n}$ (-) | K_{s}(cm/min) |
---|---|---|---|---|---|

0–10 10–20 20–40 40–60 60–80 | 0.31 (0.27–0.34) 0.29 (0.26–0.34) 0.29 (0.26–0.32) 0.33 (0.30–0.35) 0.41 (0.38–0.43) | 0.57 (0.53–0.62) 0.61 (0.58–0.64) 0.63 (0.61–0.67) 0.61 (0.58–0.64) 0.54 (0.53–0.58) | 1.20 (1.10–1.28) 1.23 (1.05–1.50) 1.47 (1.41–1.50) 1.46 (1.35–1.53) 1.46 (1.41–1.50) | 0.55(0.52–0.58) 0.50(0.43–0.60) 0.45(0.43–0.47) 0.45(0.42–0.49) 0.45(0.42–0.47) | 0.07(0.02–0.25) 0.08(0.01–0.22) 0.07(0.02–0.13) 0.11(0.04–0.18) 0.03(0.01–0.05) |

Homogeneous Case | Multilayered Case | ||||||
---|---|---|---|---|---|---|---|

Depth (cm) | $\mathit{M}$ (-) | S (cm) | K_{s} (cm/min) | Depth (cm) | $\mathit{M}$ (-) | S (cm) | K_{s} (cm/min) |

0–60 | 0.17 | 20 | 0.018 | 0–13 | 0.17 | 20 | 0.022 |

13–47 | 0.14 | 20 | 0.015 | ||||

47–60 | 0.12 | 20 | 0.012 |

Layer Number | Depth (cm) | M (-) | S (cm) | K_{s} (cm/min) |
---|---|---|---|---|

I | 0–5 | 0.130 | 20 | 0.018 |

II | 5–19 | 0.062 | 20 | 0.015 |

III | 19–39 | 0.028 | 20 | 0.015 |

IV | 39–51 | 0.006 | 20 | 0.008 |

Parameters | Main Field | Rill | Ditch |
---|---|---|---|

$\alpha $ (/) | 0.6 | 0.15 | 0.25 |

$\overline{H}$ (cm) | 0 | −10 | −30 |

${S}_{c}$ (mm) | 5 | 4 | 3.5 |

T(min) | 14 | 10 | 7 |

Layer(cm) | I (0–10) | I (0–5) | I (0–5) |

II (10–24) | II (5–14) | II (5–14) | |

III (24–44) | III (14–34) | III (14–21) | |

IV (44–51) | IV (34–41) | - |

Parameter | Main Field | Rill | Ditch |
---|---|---|---|

WFD/UZT (cm) | 23/51 | 36/41 | 21/21 |

Subunit infiltration (mm) | 21.1 | 18.1 | 13.8 |

Subunit runoff (mm) | 2.6 | 5.6 | 9.9 |

Area ratio (-) | 0.60 | 0.15 | 0.25 |

Converted total runoff(mm) | 1.54 | 0.84 | 2.48 |

Runoff ratio (-) | 0.32 | 0.17 | 0.51 |

Runoff ratio/Area ratio (-) | 0.5 | 1.1 | 2.0 |

Layer Number | Depth (cm) | M (-) | S (cm) | K_{s} (cm/min) |
---|---|---|---|---|

I | 0–5 | 0.094 | 20 | 0.018 |

II | 5–19 | 0.029 | 20 | 0.015 |

III | 19–34 | 0.035 | 20 | 0.015 |

IV | 34–60 | 0.024 | 20 | 0.008 |

V | 60–95 | 0.013 | 20 | 0.005 |

Parameter | Main Field | Rill | Ditch |
---|---|---|---|

T(min) | 40 | 35 | 25 |

Layers(cm) | I (0–5) | I (0–5) | I (0–5) |

II (5–19) | II (5–9) | II (5–10) | |

III (19–34) | III (9–24) | III (10–20) | |

IV (34–60) | IV (24–50) | IV (20–30) | |

V (60–95) | V (50–85) | V (30–65) |

Parameter | Main Field | Rill | Ditch |
---|---|---|---|

WFD/UZT (cm) | 95/95 | 85/85 | 65/65 |

Subunit infiltration (mm) | 40.0 | 36.8 | 35.1 |

Subunit Runoff (mm) | 7.9 | 11.1 | 12.8 |

Area ratio (-) | 0.6 | 0.15 | 0.25 |

Converted total runoff (mm) | 4.7 | 1.7 | 3.2 |

Runoff ratio (-) | 0.49 | 0.18 | 0.33 |

Runoff ratio/Area ratio (-) | 0.8 | 1.2 | 1.3 |

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**MDPI and ACS Style**

Yang, H.; Jiang, Y.; Zhou, Q.; Yang, H.; Ma, Q.; Zhang, C.; Wang, C. Effects of Microtopography on Runoff Generation in Plain Farmland: New Insights from an Event-Based Rainfall–Runoff Model. *Water* **2022**, *14*, 2686.
https://doi.org/10.3390/w14172686

**AMA Style**

Yang H, Jiang Y, Zhou Q, Yang H, Ma Q, Zhang C, Wang C. Effects of Microtopography on Runoff Generation in Plain Farmland: New Insights from an Event-Based Rainfall–Runoff Model. *Water*. 2022; 14(17):2686.
https://doi.org/10.3390/w14172686

**Chicago/Turabian Style**

Yang, Hai, Yuehua Jiang, Quanping Zhou, Hui Yang, Qingshan Ma, Chengcheng Zhang, and Chuanhai Wang. 2022. "Effects of Microtopography on Runoff Generation in Plain Farmland: New Insights from an Event-Based Rainfall–Runoff Model" *Water* 14, no. 17: 2686.
https://doi.org/10.3390/w14172686