scholarly journals Hydrological Response Unit Analysis Using AVSWAT 2000 for Keuliling Reservoir Watershed, Aceh Province, Indonesia

2015 ◽  
Vol 4 (1) ◽  
Author(s):  
. Azmeri ◽  
Alfian Yulianur ◽  
Maimun Rizalihadi ◽  
Shafur Bachtiar
Keyword(s):  
Land Use ◽  
Soil Type ◽  
Soil Erodibility ◽  
Hydrologic Response ◽  
Response Unit ◽  
Area 5 ◽  
Soil Erodibility Factor ◽  
Hydrologic Response Unit ◽  
Factor C ◽  
Basin Area

<p>Sediments deposition derived from the erosion in upstream areas can lead to river siltation or canals downstream irrigation. According to the complexity of erosion problem at Keuliling reservoir, it is essential that topography, hydrology, soil type and land use to be analyzed comprehensively. Software used to analyze is AVSWAT 2000 (Arc View Soil and Water Assessment Tools-2000), one of the additional tool of ArcView program. The results obtained are the watershed delineation map, soil type map to produce soil erodibility factor (K) which indicates the resistance of soil particles toward exfoliation, land use map to produce crop management factor (C) and soil conservation and its management factors (P). Hydrology analysis includes soil type, land use and utility for the erosion rate analysis through Hydrologic Response Unit (HRU). The biggest HRU value of sub-basin is on area 5 and the lowest one is on area 10. All four HRU in sub-basin area 5 are potentially donating high value for HRU. In short, this area has the longest slope length so that it has a large LS factor. About 50% of the land was covered by bushes which gain higher C factor rather than forest. Moreover, it has contour crop conservation technique with 9-20 % declivity resulting in having dominant factor of P. Soil type is dominated by Meucampli Formation which has soil erodibility factor with high level of vulnerable toward the rainfall kinetic energy. All in all, the vast majority of HRU parameters in this sub-basin area obtain the highest HRU value. Hydrology analysis, soil type, and use-land are useful for land area analysis that is susceptible to erosion which was identified through Hydrologic Response Unit (HRU) using GIS. As the matter of fact, spatially studies constructed with GIS can facilitate the agency to determine critical areas which are needed to be aware or fully rehabilitated.</p>

scholarly journals SPATIAL PATTERN OF HYDROLOGIC RESPONSE UNIT (HRU) EFFECT ON FLOW DISCHARGE OF CI RASEA WATERSHED USING LANDSAT TM IN 1997 TO 2009

2017 ◽  
Vol 13 (1) ◽  
pp. 39
Author(s):  
. Emiyati ◽  
Eko Kusratmoko ◽  
. Sobirin
Keyword(s):  
Land Cover ◽  
Spatial Pattern ◽  
Soil Type ◽  
Surface Runoff ◽  
Clay Soil ◽  
Sandy Loam ◽  
Hydrologic Response ◽  
Response Unit ◽  
Loam Soil ◽  
Hydrologic Response Unit

Hydrologic Response Unit (HRU) is a unit formed of hydrological analysis based on geology and soil type, slope, and land cover. This paper discussed the spatial pattern of Hydrologic Response Unit (HRU) in 1997-2009 and its impact on flow Ci Rasea watershed temporally. In this study, SWAT (Soil and Water Assessment Tool) model, based on land cover changed, was used to get HRU and flow in spatially and temporally. This method used Landsat TM 1997, 2003 and 2009 data for land cover and daily rainfall 1997-2009 for flow modeling. The results showed the spatial pattern of HRU in temporally was affected by landcover based on the changing of HRU. The majority of HRU spatial pattern at Ci Rasea watershed were clustered. During 1997-2009, accumulated surface runoff and the changing of flow discharge were affected by changes of HRU spatial pattern. The biggest accumulated surface runoff in Ci Rasea watershed influenced by HRU of agricultural cropland in area of clay soil type with slope slightly obliquely. While the smallest accumulated surface runoff in Ci Rasea watershed influenced by HRU of paddy field in the area of sandy loam soil type with a gentle slope. The changes of HRU agriculture cropland become HRU mixed cropland in area clay soil type with slope at a slight angle and HRU agriculture cropland become HRU paddy field in area, sandy loam soil type with a gentle slope could be decreasing the accumulation of surface runoff in Ci Rasea watershed.

scholarly journals Characteristics of Soil Erodibility K Value and Its Influencing Factors in the Changyan Watershed, Southwest Hubei, China

Land ◽  
2022 ◽  
Vol 11 (1) ◽  
pp. 134
Author(s):  
Xiaofang Huang ◽  
Lirong Lin ◽  
Shuwen Ding ◽  
Zhengchao Tian ◽  
Xinyuan Zhu ◽  
...  
Keyword(s):  
Land Use ◽  
Soil Erosion ◽  
Spatial Variability ◽  
Influencing Factors ◽  
Soil Type ◽  
Soil Survey ◽  
Purple Soil ◽  
Soil Erodibility ◽  
K Value ◽  
K Factor

Soil erodibility K factor is an important parameter for evaluating soil erosion vulnerability and is required for soil erosion prediction models. It is also necessary for soil and water conservation management. In this study, we investigated the spatial variability characteristics of soil erodibility K factor in a watershed (Changyan watershed with an area of 8.59 km2) of Enshi, southwest of Hubei, China, and evaluated its influencing factors. The soil K values were determined by the EPIC model using the soil survey data across the watershed. Spatial K value prediction was conducted by regression-kriging using geographic data. We also assessed the effects of soil type, land use, and topography on the K value variations. The results showed that soil erodibility K values varied between 0.039–0.052 t·hm2·h/(hm2·MJ·mm) in the watershed with a block-like structure of spatial distribution. The soil erodibility, soil texture, and organic matter content all showed positive spatial autocorrelation. The spatial variability of the K value was related to soil type, land use, and topography. The calcareous soil had the greatest K value on average, followed by the paddy soil, the yellow-brown soil (an alfisol), the purple soil (an inceptisol), and the fluvo-aquic soil (an entisol). The soil K factor showed a negative correlation with the sand content but was positively related to soil silt and clay contents. Forest soils had a greater ability to resist to erosion compared to the cultivated soils. The soil K values increased with increasing slope and showed a decreasing trend with increasing altitude.

Identification of Suitable Hydrologic Response Unit Thresholds for Soil and Water Assessment Tool Streamflow Modelling

2021 ◽  
Vol 31 (4) ◽  
pp. 696-710
Author(s):  
Liupeng Jiang ◽  
Jinghai Zhu ◽  
Wei Chen ◽  
Yuanman Hu ◽  
Jing Yao ◽  
...  
Keyword(s):  
Assessment Tool ◽  
Hydrologic Response ◽  
Response Unit ◽  
Hydrologic Response Unit ◽  
Water Assessment ◽  
Soil And Water

scholarly journals Use of Visible and Near-Infrared Reflectance Spectroscopy Models to Determine Soil Erodibility Factor (K) in an Ecologically Restored Watershed

2020 ◽  
Vol 12 (18) ◽  
pp. 3103
Author(s):  
Qinghu Jiang ◽  
Yiyun Chen ◽  
Jialiang Hu ◽  
Feng Liu
Keyword(s):  
Land Use ◽  
Spectral Data ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Soil Erodibility ◽  
Infrared Reflectance ◽  
Cultivated Land ◽  
Near Infrared Reflectance ◽  
Natural Land ◽  
Soil Erodibility Factor

This study aimed to assess the ability of using visible and near-infrared reflectance (Vis–NIR) spectroscopy to quantify soil erodibility factor (K) rapidly in an ecologically restored watershed. To achieve this goal, we explored the performance and transferability of the developed spectral models in multiple land-use types: woodland, shrubland, terrace, and slope farmland (the first two types are natural land and the latter two are cultivated land). Subsequently, we developed an improved approach by combining spectral data with related topographic variables (i.e., elevation, watershed location, slope height, and normalized height) to estimate K. The results indicate that the calibrated spectral model using total samples could estimate K factor effectively (R2CV = 0.71, RMSECV = 0.0030 Mg h Mj−1 mm−1, and RPDCV = 1.84). When predicting K in the new samples, models performed well in natural land soils (R2P = 0.74, RPDP = 1.93) but failed in cultivated land soils (R2P = 0.24, RPDP = 0.99). Furthermore, the developed models showed low transferability between the natural and cultivated land datasets. The results also indicate that the combination of spectral data with topographic variables could slightly increase the accuracies of K estimation in total and natural land datasets but did not work for cultivated land samples. This study demonstrated that the Vis–NIR spectroscopy could be used as an effective method in predicting K. However, the predictability and transferability of the calibrated models were land-use type dependent. Our study also revealed that the coupling of spectrum and environmental variable is an effective improvement of K estimation in natural landscape region.

scholarly journals Hydrologic Response Unit Routing in SWAT to Simulate Effects of Vegetated Filter Strip for South-Korean Conditions Based on VFSMOD

Water ◽  
2011 ◽  
Vol 3 (3) ◽  
pp. 819-842 ◽  
Author(s):  
Youn Shik Park ◽  
Jeong Hee Park ◽  
Won Seok Jang ◽  
Ji Chul Ryu ◽  
Hyunwoo Kang ◽  
...  
Keyword(s):  
Hydrologic Response ◽  
Filter Strip ◽  
South Korean ◽  
Response Unit ◽  
Hydrologic Response Unit

scholarly journals THE EFFECT OF HYDROLOGIC RESPONSE UNIT ON CI RASEA WATERSHED STREAMFLOW BASED ON LANDSAT TM

2017 ◽  
Vol 12 (2) ◽  
pp. 97
Author(s):  
. Emiyati ◽  
Eko Kusratmoko ◽  
. Sobirin
Keyword(s):  
Land Cover ◽  
Spatial Pattern ◽  
Soil Type ◽  
Surface Runoff ◽  
River Flow ◽  
Clay Soil ◽  
Landsat Tm ◽  
Hydrologic Response ◽  
Flow Discharge ◽  
Hydrologic Response Unit

. This paper discusses spatial pattern of Hydrologic Response Unit (HRU), which is a unit formed of hydrological analysis, including geology and soil type, elevation and slope, and also land cover in 2009. This paper also discusses the impact of HRU on streamflow of Ci Rasea watershed, West Java. Ci Rasea watershed is located at the upstream part of Ci Tarum watersheds in West Java Province, Indonesia. This research used SWAT (Soil and Water Assessment Tool) model to obtain spatial HRU and river flow. The method used Landsat TM data for land cover and daily rainfall for river flow modeling. The results have shown spatial pattern of HRU which was affected by land cover, soil type and slope. In 2009, accumulated surface runoff and streamflow changes were spatially affected by HRU changes. The large amount accumulation of river flow discharge happened in HRU with landcover paddy field, silty clay soil, and flat slope. While the low discharge of river flow happened in HRU with plantation, clay soil, and slightly steep slopes as HRU dominant. It was found that accumulation of surface runoff in Ci Rasea watershed can be reduced by changing the land cover type in some areas with clay and slightly steep slope to become plantation area and the areas with sandy loam soil and flat slope can be used for paddy fields. Beside affected by HRU, the river flow discharge was also affected by the distance of sub watershed to the outlet. By using NS model and statistical t-student for calibration and validation, it was obtained that the accuracy of river flow models with HRU was 70%. It meant that the model could better simulate water flows of the Ci Rasea watershed.

scholarly journals Effects of Content of Soil Rock Fragments on Soil Erodibility in China

2022 ◽  
Vol 19 (2) ◽  
pp. 648
Author(s):  
Miaomiao Yang ◽  
Keli Zhang ◽  
Chenlu Huang ◽  
Qinke Yang
Keyword(s):  
Land Use ◽  
Soil Erosion ◽  
Soil Type ◽  
Soil Profile ◽  
Redundancy Analysis ◽  
Vegetation Index ◽  
Vegetation Coverage ◽  
Soil Erodibility ◽  
Rock Fragments ◽  
Normalised Difference Vegetation Index

Soil erosion is serious in China—the soil in plateau and mountain areas contain a large of rock fragments, and their content and distribution have an important influence on soil erosion. However, there are still no complete results for calculating soil erodibility factor (K) that have corrected rock fragments in China. In this paper, the data available on rock fragments in the soil profile (RFP); rock fragments on the surface of the soil (RFS); and environmental factors such as elevation, terrain relief, slope, vegetation coverage (characterised by normalised difference vegetation index, NDVI), land use, precipitation, temperature, and soil type were used to explore the effects of content of soil rock fragments on calculating of K in China. The correlation analysis, typical sampling area analysis, and redundancy analysis were applied to analyse the effects of content of soil rock fragments on calculating of K and its relationship with environment factors. The results showed that (1) The rock fragments in the soil profile (RFP) increased K. The rock fragments on the surface (RFS) of the soil reduced K. The effect of both RFP and RFS reduced K. (2) The effect of rock fragments on K was most affected by elevation, followed by terrain relief, NDVI, slope, soil type, temperature, and precipitation, but had little correlation with land use. (3) The result of redundancy analysis showed elevation to be the main predominant factor of the effect of rock fragments on K. This study fully considered the effect of rock fragments on calculating of K and carried out a quantitative analysis of the factors affecting the effect of rock fragments on K, so as to provide necessary scientific basis for estimating K and evaluating soil erosion status in China more accurately.

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