Analyzing the Benefit-Cost Ratio of Sediment Resources by Remote Sensing Data in the Ping River Basin, Thailand

Rangsiwanichpong, Prem; Melesse, Assefa M.

doi:10.3390/w14132071

Cited by 3 publications

(1 citation statement)

References 53 publications

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“…planting vetiver grass as hedgerows parallel to the slope contour (Fig. 1) [2]. Very effective for reduction of runoff energy and for sediment trap, the vetiver hedgerow has a very dense fine vertical root system which is also beneficial for shallow slope stabilization [3][4].…”

Section: Introductionmentioning

confidence: 99%

Field observations of soil moisture, suction and movement of cornfield in tropical highland with and without vetiver system

et al. 2023

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An increasing large number of cornfield have been cultivated in highland of many Southeast Asian countries. In most cases, this corn plantation is done without proper soil & water conservation such as vetiver system (VS), thus causing land degradation and shallow slide. This study is aimed at investigating the field behaviour of slopes with corn plantation with and without vetiver system in Chiang Mai, Northern Thailand. Tensiometers, soil moisture sensors, in-place inclinometers and tiltmeters were installed at a slope in two locations, with and without vetiver system from surface to 2m depth. The monitoring results show that for the vetiver treatment, the soil moisture tended to be higher and response faster to rainfall than the cornfield without vetiver. However, the pore-water pressure in the root zone (about 0.5m) was higher for the vetiver treatment than the cornfield which only has the root depth of about 0.2m. For cornfield without vetiver, the seasonal variation of the soil moisture and pore-water pressure was also larger. Tiltmeter indicates a larger surface movement in the cornfield without VS. However, the inclinometer readings suggested that for slope with VS there was some cyclic movement toward hillside at the surface. This could be an indication of non-uniform settlement of soil layers or influence of groundwater rising.

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Section: Introductionmentioning

confidence: 99%

Field observations of soil moisture, suction and movement of cornfield in tropical highland with and without vetiver system

et al. 2023

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Profitability of Yam Production Under Farmer Practice, Abamectin Treatment and Banana Paper Techniques in Ghana

Asem,

Nyaku,

Kolog

et al. 2024

Preprint

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Enhancing rainfall–runoff model accuracy with machine learning models by using soil water index to reflect runoff characteristics

Iamampai,

Talaluxmana,

Kanasut

et al. 2024

Water Science &Amp; Technology

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The advancement of data-driven models contributes to the improvement of estimating rainfall–runoff models due to their advantages in terms of data requirements and high performance. However, data-driven models that rely solely on rainfall data have limitations in responding to the impact of soil moisture changes and runoff characteristics. To address these limitations, a method was developed for selecting predictor variables that utilize the accumulation of rainfall at various time intervals to represent soil moisture, the changes in the runoff coefficient, and runoff characteristics. Furthermore, this study investigated the utility of rainfall products [such as climate hazards group infrared precipitation with station data (CHIRPS) and global precipitation measurement (GPM)] for representing rainfall data, while also using the soil water index (SWI) to enhance runoff estimation. To assess these methods, the random forest (RF) and artificial neural network (ANN) models were utilized to simulate daily runoff. Incorporating both the rainfall and SWI data led to improved outcomes. The RF demonstrated superior performance compared with the ANN and the conceptual model, without the need for baseflow separation or antecedent runoff. Furthermore, accumulated rainfall was shown to be a valuable input for the models. These findings should facilitate the estimation of runoff in locations with limited measurement data on rainfall and soil moisture by utilizing remote sensing data.

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Analyzing the Benefit-Cost Ratio of Sediment Resources by Remote Sensing Data in the Ping River Basin, Thailand

Cited by 3 publications

References 53 publications

Field observations of soil moisture, suction and movement of cornfield in tropical highland with and without vetiver system

Field observations of soil moisture, suction and movement of cornfield in tropical highland with and without vetiver system

Profitability of Yam Production Under Farmer Practice, Abamectin Treatment and Banana Paper Techniques in Ghana

Enhancing rainfall–runoff model accuracy with machine learning models by using soil water index to reflect runoff characteristics

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