Designing a watershed scorecard as a performance evaluation tool for Ur River watershed, Tikamgarh District, Madhya Pradesh

Gupta, Meeta; Goyal, Vikas; Tarannum, Fawzia; Patil, Jyoti P.

doi:10.1016/j.iswcr.2017.10.001

Cited by 5 publications

(5 citation statements)

References 2 publications

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“…The low infiltration rate in the Capivari basin is related to the characteristics of the basin, which has less permeable soils (naturally or as a result of improper handling), in addition to the undulating relief that favors the runoff process. In addition to these factors, the tree vegetation would have a fundamental role in this process (SALOMÃO, 2012;FERNANDES et al, 2014;FELIPPE et al, 2016;VIEIRA et al, 2016;GUPTA et al, 2017) is degraded in most of the basin.…”

Section: Resultsmentioning

confidence: 99%

“…The proposed model indicates the spring zone as the lowest flow propensity for 2017. This is primarily due to the flat terrain and lower precipitation, but the lack of adequate riparian vegetation (VIEIRA et al, 2016;GUPTA et al, 2017), the use of the soil with agricultural activities without proper management (BENDA et al, 2007) and the semi-arid climate, influence the state of intermittent course of river in this area. The most vulnerable area of the basin, as proposed, is the area near the mouth, and this result reflects the features of this area.…”

Section: Resultsmentioning

confidence: 99%

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Runoff, Identification of Sensitive Zones in the Capivari Watershed – BA

Santana

Silva

Santos

et al. 2022

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The watershed is an active environment, defined as an area of land surface drained by a primary river and its tributaries, which are bounded by water dividers. Among the processes that affect water movement in a watershed, the surface runoff stands out, responsible for the transport of soil particles (nutrients and pollutants) to the lower parts of the landscape. The objective of this study was to demonstrate the influence of land use and cover on surface runoff dynamics in the Capivari Basin in Bahia, Brazil. To reach that objective, the Curve Number method (SCS-CN) was employed, with the ALOS/PALSAR RTC Digital Elevation Model; IBGE soil data; data from government weather stations and local agribusiness; land use and land cover from the LC08_L1TP_216069_20170619 landsat8 OLI sensor, through the classifier Bhattacharya. The processing was carried out on a GIS platform, using SPRING and QGIS software. Highest levels of precipitation, the soil features and the higher slope affected the greatest vulnerability to runoff at the mouth, based on the proposed model, however, the most conserved Permanent Preservation Area (PPA) have been effective in maintaining the Capivari River in these areas. The areas considered most critical in terms of the risk of water erosion for the year 2017 were those in the middle of Capivari, because they presented high precipitation in some months, but do not present PPA in riparian forest areas or in hill tops, this increases the vulnerability of these regions to erosion. The proposed model was successful in identifying areas most vulnerable to runoff in the Capivari Basin.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Runoff, Identification of Sensitive Zones in the Capivari Watershed – BA

Santana

Silva

Santos

et al. 2022

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“…The watershed priority scale determination becomes important in terms of watershed management [9] and it is used as management program plan, necessary in developing management identification, developing maintenance plan, and can help taking prevention acts needed in an a priori condition [10], including problems of limited funding [11]. Given the fact that in Watershed management, big investation fund is needed [12], thus a scientific analysis is needed [3].…”

Section: Introductionmentioning

confidence: 99%

“…Gangsa watershed support capability condition has the value of 106, consists of Land Condition criteria: Critical Land Percentage (10), Vegetation Coverage Percentage (12.5), Erosion Index of 10, in total 32.5. Meanwhile the water system condition consists of the Flow Regime Coefficient 7.5, Annual Flow Coefficient (C) 7.5, Sedimentary Content (SC) 6, Flood in score 3, while Water Use Index (WUI) is 5, in total 29.…”

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confidence: 99%

Developed watershed classification index determining management priority level based on watershed carrying capacity

Sriyana

2019

MATEC Web Conf.

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Watershed classification index is important in terms of determining watershed management priority level based on its carrying capacity score whereby currently watershed is classified into two indexes which are “to be maintained” if the carrying capacity score is below 100 and “to be restored” if it is above 100. This index fails to capture existing condition where there are watersheds with carrying capacity score in between 90 and 110. The purpose of this paper is to propose developed watershed classification index to determine management priority level based on watershed carrying capacity score. The method used to develop the watershed classification index is Classification Interval approach. The analysis is resulting in rigorous management priority level based on developed watershed classification index which is 50 < carrying capacity ≤ 90 as Priority 3 (watershed indexed as “to be maintained”), 90 < carrying capacity ≤ 110 as Priority 2 (watershed indexed as “to be improved”) and 110 < carrying capacity ≤ 150 as Priority 1 (watershed indexed as “to be restored”). Therefore, the correct management priority level for Gangsa Watershed that has carrying capacity of 106 is Priority 2.

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“…Very sharp fluctuations indicate that the watershed function is unstable. 3,4 Watershed as an ecological controller has a strategic function. 5 Therefore, the damage to the watershed has implications for many things, including the possibility of degradation of the physical environment and destruction of the agricultural land.…”

Section: Introductionmentioning

confidence: 99%

Threats of sedimentation to agricultural land due to land use and degradation of watershed physical environmental

et al. 2018

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Background: The Lake Lindu sub-watershed has experienced environmental damage, mainly as a result of various activities of the surrounding community who are less aware of the principles of environmental sustainability. This study aims to determine the effect of land use area and environmental physical conditions on sedimentation and water debit in the Lake Lindu sub-watershed.Methods: This research was carried out by implementing survey and non-experimental method at 3 rivers: Langko (P1), Wongkodono (P2), and Kati (P3). The dependent variable in this study is the area of land use (area of farm, shrub, paddy field, forest, and settlement) and the physical condition of the environment (the width of the catchment area and annual average rainfall). Then, the independent variables are sedimentation and water debit. Statistical analysis used is a multiple regression model. Results: The results of this study are that the wider shrub (X2) reduces the sedimentation (Y1) and increases the water debit (Y2). Each addition of one shrub unit will reduce the sediment by 0.208 mg/L and affect the water debit of 0.258 m3/ s-1. The regression equation is Y1=185.903 - 0.208X2-587.269X8 and Y2=6.854+0.258 X2 - 71.708 X8. As for the coefficient of the shape of the river (X8). The bigger the shape of the river, the smaller the average of the water debit. Thus, each reduction of one coefficient unit of the river shape will affect the water debit of 71,708 m3 /s-1.Conclusions: The significant predictor factors for sedimentation and river water debit are the shrubs and the coefficient of the river shape.

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Designing a watershed scorecard as a performance evaluation tool for Ur River watershed, Tikamgarh District, Madhya Pradesh

Cited by 5 publications

References 2 publications

Runoff, Identification of Sensitive Zones in the Capivari Watershed – BA

Runoff, Identification of Sensitive Zones in the Capivari Watershed – BA

Developed watershed classification index determining management priority level based on watershed carrying capacity

Threats of sedimentation to agricultural land due to land use and degradation of watershed physical environmental

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