Detection and prediction of land use change impact on the streamflow regime in Sahelian river basin, northwestern Nigeria

Umar, Da’u Abba; Ramli, Mohammad Firuz; Tukur, Abubakar Ibrahim; Jamil, Nor Rohaizah; Zaudi, Muhammad Amar

doi:10.2166/h2oj.2021.065

Cited by 6 publications

(5 citation statements)

References 60 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Also, built-up area increased with 187.84 sq.km, mainly due to the population growth around the basin. This is in line with a similar research carried out by [4], which revealed decrease in grassland and water bodies with an increase in built-up and agricultural land use in northwestern Nigeria basins. There has been an increase in demand for new cultivation land and settlement which in turn resulted in shrinking of other types of land use and land cover of the area.…”

Section: B Discussionsupporting

confidence: 92%

Assessment of the Impact of Land Use and Land Cover Change on the Surface Runoff of Hadejia River System, Kano, Nigeria

Joke Oluronke Lawal,

Felix Ndukson Buba,

Helen Awe-Peter

2024

IJLTEMAS

View full text Add to dashboard Cite

Land use and land cover changes, mostly driven by anthropogenic activities, affect the processes of the water cycle. The impacts of land use (LU) and land cover (LC) changes between 1995 and 2015 on the surface runoff of the Hadejia River System (HRS) were investigated. The LULC changes obtained through re-classifications of selected Landsat satellite images and their effects on runoff peak discharges and volumes were assessed using selected hydrologic models for runoff generation and routing available within the HEC-HMS. Physically-based parameters of the models were estimated from the LULC change maps together with a digital elevation model and soil datasets of the basin. The simulated flows from the 90 sub-catchments were routed to the basin outlet afterwards to obtain the accrued effects in the entire river basin. Model results obtained generally revealed significant and varying increases in the runoff peak discharges and volumes within some sub-basins in the whole catchment, though the change was not significant at the basin outlet. In the sub-catchments within Kano and Jigawa states, increase between 15-20% and 10-15% were observed in the peak discharge respectively. These are the areas with the highest increase in agricultural activities and urbanization within the whole catchment. In the entire basin, however, the flood peak discharges and volumes increased by at least 3.57% and 8.18% respectively. From these results, the study concludes that changes were more pronounced in Kano and Jigawa states due to the increase of urbanization and farming activities in those areas, leading to reduction of infiltration and hence, increase in surface runoff. The study successfully outlined the hydrological consequences of land cover changes, emphasizing the importance of sustainable land use and catchment management strategies. Hence, integration of remote sensing, GIS, and the hydrological model (HEC-HMS) can be used to solve hydrological problems in a river basin.

show abstract

Section: B Discussionsupporting

confidence: 92%

Assessment of the Impact of Land Use and Land Cover Change on the Surface Runoff of Hadejia River System, Kano, Nigeria

Joke Oluronke Lawal,

Felix Ndukson Buba,

Helen Awe-Peter

2024

IJLTEMAS

View full text Add to dashboard Cite

show abstract

“…The major causes of transformation is due to conversion of the forest area to newly formed towns and industries in the upper basin. The lacustrine area have augmented from 1.2% to 4% may be due to focused attention of the government for the development of watershed, formation of reservoirs and waterbodies [45].…”

Section: Results Of Land Use Land Cover Classificationmentioning

confidence: 99%

Geomorphologic Change in Nagavali River Basin: Geospatial Approach

Mishra

Patel

Mishra

et al. 2021

IJECC

View full text Add to dashboard Cite

The Nagavali river basin (NRB), along east coast of India investigated for its land use and land cover changes (LULCC) in the golden spike period of Anthropocene Epoch. Attempts made to assess the vicissitudes, causes, and consequences of natural resources, and soil/water resources of the NRB in last three decades as significant changes in hydro-climatic variables occurred. The interstate basin is well developed in lower reaches (north Andhra Pradesh) whereas upper stretches, South Odisha is less organized. GIS and remote sensing are efficient tools for an ideal study of LULCC of the area. Present work evaluates the dynamics of LULCC of NRB. LANDSAT-5, LANDSAT-8, of 1990, 2000, 2010 and 2020, respectively, were digitally classified for land use land cover mapping. The changing aspects of LULCC critically analyzed for three span, 1990–2000, 2000–2010 and 2010–2020. Through Normalized Difference Vegetation Index (NDVI) of the NRB examined carefully to assess the recent LULCC pattern. Major changes are sue to exchanges of areas are in between forest and built-up land followed by water body. The transformations are from forest to human habitation; especially built-up area that constitutes major percentage of the total landscape. The study shows that emphasis is necessary on more water consolidation projects in the upper Nagavali Basin considering the long-term LULC trend analysis.

show abstract

“…This manifests the necessity of future LULC projection for streamflow forecast. It aids in capturing changes in evapotranspiration, land surface features, surface runoff, and land management practices [8,9].…”

Section: Introductionmentioning

confidence: 99%

Basin-Scale Streamflow Projections for Greater Pamba River Basin, India Integrating GCM Ensemble Modelling and Flow Accumulation-Weighted LULC Overlay in Deep Learning Environment

Geetha Raveendran Nair,

Shamsudeen,

Mohan

et al. 2023

Sustainability

View full text Add to dashboard Cite

Accurate prediction of future streamflow in flood-prone regions is crucial for effective flood management and disaster mitigation. This study presents an innovative approach for streamflow projections in deep learning (DL) environment by integrating the quantitative Land-Use Land-Cover (LULC) overlaid with flow accumulation values and the various Global Climate Model (GCM) simulated data. Firstly, the Long Short Term Memory (LSTM) model was developed for the streamflow prediction of Greater Pamba River Basin (GPRB) in Kerala, India for 1985 to 2015 period, considering the climatic inputs. Then, the flow accumulation-weighted LULC integration was considered in modelling, which substantially improves the accuracy of streamflow predictions including the extremes of all the three stations, as the model accounts for the geographical variety of land cover types towards the streamflow at the sub-basin outlets. Subsequently, Reliability Ensemble Averaging (REA) technique was used to create an ensemble of three candidate GCM products to illustrate the spectrum of uncertainty associated with climate projections. Future LULC changes are accounted in regional scale based on the sub-basin approach by means of Cellular-Automata Markov Model and used for integrating with the climatic indices. The basin-scale streamflow projection is done under three climate scenarios of SSP126, SSP245 and SSP585 respectively for lowest, moderate and highest emission conditions. This work is a novel approach of integrating quantified LULC with flow accumulation and other climatic inputs in a DL environment against the conventional techniques of hydrological modelling. The DL model can adapt and account for shifting hydrological responses induced by changes in climatic and LULC inputs. The integration of flow accumulation with changes in LULC was successful in capturing the flow dynamics in long-term. It also identifies regions that are more likely to experience increased flooding in the near future under changing climate scenarios and supports decision-making for sustainable water management of the Greater Pamba Basin which was the worst affected region in Kerala during the mega floods of 2018.

show abstract

Detection and prediction of land use change impact on the streamflow regime in Sahelian river basin, northwestern Nigeria

Cited by 6 publications

References 60 publications

Assessment of the Impact of Land Use and Land Cover Change on the Surface Runoff of Hadejia River System, Kano, Nigeria

Assessment of the Impact of Land Use and Land Cover Change on the Surface Runoff of Hadejia River System, Kano, Nigeria

Geomorphologic Change in Nagavali River Basin: Geospatial Approach

Basin-Scale Streamflow Projections for Greater Pamba River Basin, India Integrating GCM Ensemble Modelling and Flow Accumulation-Weighted LULC Overlay in Deep Learning Environment

Contact Info

Product

Resources

About