Comparison of seven simple loss models for runoff prediction at the plot, hillslope and catchment scale in the semiarid southwestern U.S.

Schoener, Gerhard; Stone, Mark C.; Thomas, Charles C.

doi:10.1016/j.jhydrol.2021.126490

Cited by 17 publications

(15 citation statements)

References 65 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…At the same time, a more considerable value with a flatter surface texture as expected, such as soil without plants" [13]. "The approach of the original Horton equation is partial to ponding conditions, and modified Horton methods are used only for specific modelling or intermittent rainfall events" [13]. "𝑓 0 and 𝑓𝑐 are functions of soil type and cover; for example, sandy or gravel soil without plants has high 𝑓 0 and 𝑓𝑐 values, and loamy soil without plants have low 𝑓 0 and 𝑓𝑐 values, but both values increase for both soil types.…”

Section: Horton Modelmentioning

confidence: 73%

“…"The significant amount of water infiltrated at a period depends on the infiltration rate and time function" [13]. "If the infiltration rate at some point is 𝑓(𝑡), then the cumulative infiltration or the amount of water infiltrated is 𝐹(𝑡)" [13]. "Referring to "Eq.…”

Section: Horton Modelmentioning

confidence: 99%

“…"Referring to "Eq. ( 1)", the amount of water infiltrated 𝐹(𝑡) is integral to the infiltration rate" [13]. "The infiltration rate is a derivative of the cumulative infiltration of 𝐹(𝑡)" [13].…”

Section: Horton Modelmentioning

confidence: 99%

“…( 1)", the amount of water infiltrated 𝐹(𝑡) is integral to the infiltration rate" [13]. "The infiltration rate is a derivative of the cumulative infiltration of 𝐹(𝑡)" [13]. The following calculation of the infiltration rate using Horton Model:…”

Section: Horton Modelmentioning

confidence: 99%

See 3 more Smart Citations

Modified Horton Method Based on Field Work During Intermittent Rainfall

Kencanawati,

Maulana

2024

Preprint

View full text Add to dashboard Cite

Infiltration can be identified as the critical processes in the hydrological process. Infiltration affects the vertical distribution of rainwater on surface water and significantly distresses between groundwater and surface water. Infiltration is one of an important parameters that could affect and increase the runoff. In advance, the Horton Method is the most widely used in hydrology infiltration models for fields research than the others. The objective of this study was to determine a relationship between infiltration capacity and runoff flow to improve the Horton infiltration equation during intermittent rainfall by field work. Research area was located Lanang sub-catchment, Kediri, East Java. Double ring infiltrometer was used to determine field infiltration rate. Land use and soil type maps were used to categorize sampling area and type of soil. Intermittent rainfall data was measured from rain gauge in the study area. According to the analysis, the capacity of infiltration decreases equal to a constant value and the results of infiltration rate from a double ring infiltrometer value obtained was 90 mm/hour at the upstream area. In the other hands, the downstream area resulted 26,4 mm/hour of infiltration rate or 30% out of upstream area value

show abstract

Section: Horton Modelmentioning

confidence: 73%

Section: Horton Modelmentioning

confidence: 99%

Section: Horton Modelmentioning

confidence: 99%

Section: Horton Modelmentioning

confidence: 99%

See 2 more Smart Citations

Modified Horton Method Based on Field Work During Intermittent Rainfall

Kencanawati,

Maulana

2024

Preprint

View full text Add to dashboard Cite

show abstract

“…In the past few decades, numerical models of physical mechanism [5][6][7] and data-driven methods [8][9][10] have been widely used in runoff prediction and simulation [11]. The numerical model of physical mechanism started early and has been widely used in runoff prediction [12][13][14].…”

Section: Introductionmentioning

confidence: 99%

Improved runoff forecasting based on time-varying model averaging method and deep learning

et al. 2022

View full text Add to dashboard Cite

In order to improve the accuracy and stability of runoff prediction. This study proposed a dynamic model averaging method with Time-varying weight (TV-DMA). Using this method, an integrated prediction model framework for runoff prediction was constructed. The framework determines the main variables suitable for runoff prediction through correlation analysis, and uses TV-DMA and deep learning algorithm to construct an integrated prediction model for runoff. The results demonstrate that the current monthly runoff, the runoff of the previous month, the current monthly temperature, the temperature of the previous month and the current monthly rainfall were the variables suitable for runoff prediction. The results of runoff prediction show that the TV-DMA model has the highest prediction accuracy (with 0.97 Nash-efficiency coefficient (NSE)) and low uncertainty. The interval band of uncertainty was 33.3%-65.5% lower than single model. And the prediction performance of the single model and TV-DMA model in flood season is obviously lower than that in non-flood season. In addition, this study indicate that the current monthly runoff, rainfall and temperature are the important factor affecting the runoff prediction, which should be paid special attention in the runoff prediction.

show abstract