Mapping runoff generating areas using AGNPS-VSA model

Panjabi, Kishor; Rudra, R. P.; Goel, Pradeep K.; Daggupati, Prasad; Shrestha, Narayan Kumar; Shukla, Rituraj; Zhang, Binbin; Allataifeh, Nabil

doi:10.1080/02626667.2020.1798007

Cited by 3 publications

(2 citation statements)

References 47 publications

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“…The wetness index provides the spatial distribution and zones of saturation (flooded areas) or runoff generation areas (Wu et al, 2016). The wetness index has been widely used to understand spatial scale effects on hydrological processes and to predict observed patterns of saturated areas (Panjabi et al, 2020).…”

Section: Wetness Indexmentioning

confidence: 99%

Modelling flood hazard in dry climates of southern Africa: a case of Beitbridge, Limpopo Basin, Zimbabwe

Chikwiramakomo

Gumindoga

Shekede

et al. 2021

WSA

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Floods are among the natural hazards that have adverse effects on human lives, livelihoods, economies and infrastructure. Dry climates of southern Africa have, over the years, experienced an increase in the frequency of tropical cyclone induced floods. However, understanding the key factors that influence susceptibility to floods has remained largely unexplored in these dry climates. Therefore, this study sought to model flood hazards and determine key factors that significantly explain the probability of flood occurrence in the southern parts of Beitbridge District, Zimbabwe. To achieve these objectives, logistic regression was used to predict spatial variations in flood hazards following cyclone Dineo in 2017. Before spatial prediction of flood hazard, environmental variables were tested for multicollinearity using the Pearson correlation coefficient. Only two environmental variables, i.e., elevation and rainfall, were not significantly correlated and were thus used in the subsequent flood hazard modelling. Results demonstrate that two variables significantly (p < 0.05) predicted spatial variations in flood hazard in the southern parts of the Beitbridge District with relatively high accuracy defined by the area under the curve (AUC = 0.98). In addition, results indicate that ~56 % of the study area is regarded as highly susceptible to floods. Given the projected increase in extreme events such as intense rainfall as a result of climate change, floods will be expected to correspondingly increase in these semi-arid regions. Results presented in this study underscore the importance of geospatial techniques in flood-hazard modelling, which is the key input in sustainable land-use planning. It can thus be concluded that spatial analytical techniques play a key role in flood early warning systems aimed at supporting and building resilient communities in the face of climate change–induced floods.

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Section: Wetness Indexmentioning

confidence: 99%

Modelling flood hazard in dry climates of southern Africa: a case of Beitbridge, Limpopo Basin, Zimbabwe

Chikwiramakomo

Gumindoga

Shekede

et al. 2021

WSA

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“…This model predicts the surface runoff, sediment and nutrient transport in agricultural watersheds [20]. Many hydrologists and environmentalists have employed the AGNPS model to quantify the runoff, erosion and nutrient movement in the watershed [21,22]. The impact of land-use changes [23,24] and input usages, such as fertilizers and pesticides, can also be assessed in agriculture dominated watersheds.…”

Section: Introductionmentioning

confidence: 99%

Deriving Land Management Practices for Reduced Nutrient Movement from an Agricultural Watershed Using the AGNPS Model

2023

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The effect of nutrient management practices and the land-use system on nutrient enrichment in water resources of a hilly watershed was assessed with an event-based agricultural non-point source (AGNPS) model. The model intended to assess the runoff, sediment and nutrient loads in a typical hilly agricultural watershed. The model was calibrated, evaluated and applied in integration with GIS to predict the soil and nutrient loss. Two nutrient management scenarios were simulated with 25 and 50% reductions in the nutrient application from the present nutrient application. The third scenario was simulated by converting 25% of the agricultural land-use to tea plantations. A total of 15 simulations were run for the different rainfall intensities of the year 2017. The existing land-use scenario simulated the maximum soil loss and Nitrogen and phosphorus load of 8.23 t ha−1, 22.8 and 5.0 kg ha−1. The 50% nutrient reduction scenario reduced 48 and 36% of the Nitrogen and phosphorus load compared to the existing farmers' practice. The same nutrient dose was compared with the STCR equation, developed for major crops such as potato and carrot in Nilgiris soil, and confirmed the sufficient nutrient supply to produce a sustainable yield. The conversion of 25% of the agricultural land-use to tea plantations reduced the soil loss by 10% from the current land-use. The Nitrogen and phosphorus load was reduced to 56 and 48%, respectively. Hence, the farmers may convert 25% of the land area to tea plantations and reduce 50% of the present fertilizer dose for the major vegetable crops with INM to reduce the nutrient enrichment in the surface water bodies. This study demonstrated the applicability of the AGNPS model in similar watersheds for deriving possible management strategies to reduce soil loss and nutrient movement. Further, the hydrological models can provide valuable insights for promptly prioritizing and making policy decisions in ungauged/data-scarce watersheds.

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Post-fire recovery of nematode communities along a slope gradient in a pine forest

Papapostolou,

Kekelis,

Zafeiriou

et al. 2024

Environ Monit Assess

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Mapping runoff generating areas using AGNPS-VSA model

Cited by 3 publications

References 47 publications

Modelling flood hazard in dry climates of southern Africa: a case of Beitbridge, Limpopo Basin, Zimbabwe

Modelling flood hazard in dry climates of southern Africa: a case of Beitbridge, Limpopo Basin, Zimbabwe

Deriving Land Management Practices for Reduced Nutrient Movement from an Agricultural Watershed Using the AGNPS Model

Post-fire recovery of nematode communities along a slope gradient in a pine forest

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