Land-Use Change Impacts on the Hydrology of the Upper Grande River Basin, Brazil

Oliveira, Vinícius Augusto de; Mello, Carlos Rogério de; Viola, Marcelo Ribeiro; Srinivasan, Raghavan

doi:10.1590/01047760201824042573

Cited by 26 publications

(16 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Many scholars have simulated future runoff variation in different rivers, such as the Yellow River [2][3][4], Hoeya River [5], Altmühl River [6], Beijiang River [7], and the upper reaches of the Grande River [8]. For example, Li et al [9] simulated the future runoff variation in the upper reaches of the Yellow River under two climate scenarios (A2 and B2) using seven CMIP3 models.…”

Section: Introductionmentioning

confidence: 99%

Future Runoff Variation and Flood Disaster Prediction of the Yellow River Basin Based on CA-Markov and SWAT

Lai

Xia

et al. 2021

Land

View full text Add to dashboard Cite

The purpose of this paper is to simulate the future runoff change of the Yellow River Basin under the combined effect of land use and climate change based on Cellular automata (CA)-Markov and Soil & Water Assessment Tool (SWAT). The changes in the average runoff, high extreme runoff and intra-annual runoff distribution in the middle of the 21st century are analyzed. The following conclusions are obtained: (1) Compared with the base period (1970–1990), the average runoff of Tangnaihai, Toudaoguai, Sanmenxia and Lijin hydrological stations in the future period (2040–2060) all shows an increasing trend, and the probability of flood disaster also tends to increase; (2) Land use/cover change (LUCC) under the status quo continuation scenario will increase the possibility of future flood disasters; (3) The spring runoff proportion of the four hydrological stations in the future period shows a decreasing trend, which increases the risk of drought in spring. The winter runoff proportion tends to increase; (4) The monthly runoff proportion of the four hydrological stations in the future period tends to decrease in April, May, June, July and October. The monthly runoff proportion tends to increase in January, February, August, September and December.

show abstract

Section: Introductionmentioning

confidence: 99%

Future Runoff Variation and Flood Disaster Prediction of the Yellow River Basin Based on CA-Markov and SWAT

Lai

Xia

et al. 2021

Land

View full text Add to dashboard Cite

show abstract

“…However, as there are notable achievements in the construction of water storages and diversion structures in the basin (Alemngus & Semere Amlesom, 2017), the impacts could be minimized. This may further contribute to the socioeconomic development with the possibility of agricultural production and hydropower generation which could have regional impact in the hydrological cycle (De Oliveira et al, 2018).…”

Section: Resultsmentioning

confidence: 99%

Land Use/Land Cover Changes and Associated Impacts on Water Yield Availability and Variations in the Mereb‐Gash River Basin in the Horn of Africa

et al. 2020

View full text Add to dashboard Cite

Climate variability and drought are increasing in the Horn of Africa. Evaluating land use/land cover (LULC) changes and their impacts on water availability and variation are vital for regional land use planning and water resources management. LULC changes during 2000–2015 were estimated using high‐resolution Landsat images and the Google Earth Engine cloud platform, and land use dynamic index (K). The impact of LULC change on water yield was evaluated using the Integrated Valuation of Ecosystem Services and Tradeoff (InVEST) model. The results at a regional scale show that there were rapid decreases in the area of forests and barren lands (‐K) while there was a drastic increase in the built‐up area (+K values). The transition was found to occur from forested land to low and very low biomass areas with 51.13% and 16.7%, respectively. There were similar LULC changes in the Mereb‐Gash River Basin. The mean annual water yield increased for all the catchments during 2000–2015 and with the peak in 2005. The highest annual sum water yield decreased in the forested lands from 43.18 million m3 in 2000 to 4.1 million m3 in 2015. There was a strong positive correlation between areal changes (%) and the annual water yield variations (%) for all the LULC types except for water body, and the correlation was significantly positive for forest (p < 0.01). The study demonstrates that the decrease in forested areas and expansion in the built‐up areas had large impacts on water yield. The impacts may increase pressure on ecosystem services, exacerbate water scarcity, and food insecurity.

show abstract

“…A topografia da bacia é classificada como ondulada, com 57,2% da área apresentando declives superiores a 15% (OLIVEIRA et al, 2019). Figura 1.…”

Section: áRea De Estudounclassified

Avaliação Da Riqueza De Espécies Arbóreas Através Dos Métodos Bootstrap E Regressao Quadrática De Platô

Santos

França

Monti

et al. 2019

BIOFIX

View full text Add to dashboard Cite

As florestas tropicais no Brasil apresentam elevada diversidade de espécies arbóreas e, vêm sofrendo grande pressão devido a expansão agrícola, pecuária e outras atividades econômicas antrópicas. Diante desses fatores torna-se cada vez mais importante estudos fitossociológicos que envolvam riqueza de espécies, com intuito de conhecer o potencial biológico existente, bem como justificar a conservação dos remanescentes florestais nativos. Sendo assim, o objetivo deste trabalho foi verificar a suficiência amostral necessária para a quantificação da riqueza arbórea da Bacia Hidrográfica do Rio Grande (BHRG), no sul de Minas Gerais, avaliando em nível de fragmentos (parcelas por fragmento) e para toda a área da bacia (fragmentos na área total), essa análise foi estendida para a análise pontual da fitofisionomia Floresta Estacional Semidecidual, que é a principal fisionomia de ocorrência na bacia hidrográfica, verificando também a utilização da modelagem para a estimativa total de espécies arbóreas. O método utilizado foi a regressão de platô, para isso utilizou-se a reamostragem bootstrap sem reposição para a retirada da subjetividade na entrada dos dados no ajuste do modelo. A regressão de platô indicou o ponto onde seria encontrada a suficiência amostral. Concluiu-se, pelo modelo quadrático de resposta em platô, que a amostragem realizada para a bacia como um todo atingiu a suficiência amostral com 26 fragmentos. Já a nível de fragmentos, a suficiência amostral foi atingida em 55% dos fragmentos amostrados. Os resultados aqui apresentados podem ser utilizados para fins de indicação de espécies destinadas à recuperação de ecossistemas degradados, dentre outras aplicações de conservação florestal.

show abstract

Land-Use Change Impacts on the Hydrology of the Upper Grande River Basin, Brazil

Abstract: HIGHLIGHTS SWAT model effectively estimates the streamfl ow in the Upper Grande River Basin. Deforestation of native vegetation may lead to an increase in runoff and peak fl ow. Reforestation of native vegetation may lead to an increase in infi ltration and soil-water holding capacity.

Cited by 26 publications

References 35 publications

Future Runoff Variation and Flood Disaster Prediction of the Yellow River Basin Based on CA-Markov and SWAT

Future Runoff Variation and Flood Disaster Prediction of the Yellow River Basin Based on CA-Markov and SWAT

Land Use/Land Cover Changes and Associated Impacts on Water Yield Availability and Variations in the Mereb‐Gash River Basin in the Horn of Africa

Avaliação Da Riqueza De Espécies Arbóreas Através Dos Métodos Bootstrap E Regressao Quadrática De Platô

Contact Info

Product

Resources

About