Alterations in Hydrological Responses under Changing Climate and Land Use/Land Cover across Contrasting Agroecological Environments: A Case Study on the Chemoga Watershed in the Upper Blue Nile Basin, Ethiopia

Meshesha, Taye Minichil; Tsunekawa, Atsushi; Haregeweyn, Nigussie; Tsubo, Mitsuru; Fenta, Ayele Almaw; Berihun, Mulatu Liyew; Mulu, Arega; Belay, Ashebir Sewale; Sultan, Dagnenet; Ebabu, Kindiye; Setargie, Tadesual Asamin; Kassa, Samuel Berihun; Hailu, Yoseph Buta; Abe, Takeshi

doi:10.3390/w16071037

Cited by 3 publications

(1 citation statement)

References 67 publications

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“…Rainfall is a key component of the hydrologic cycle, and its accurate measurement and monitoring of its spatio-temporal distribution are essential for various applications. This includes monitoring droughts/floods under changing climate [1][2][3][4], water resources management [3,5,6], assessing land degradation by water erosion [7][8][9][10][11], and proposing appropriate land management options [12][13][14]. Reliable rainfall data can be obtained from traditional rain gauges, which offer direct rainfall measurements.…”

Section: Introductionmentioning

confidence: 99%

Unveiling the Accuracy of New-Generation Satellite Rainfall Estimates across Bolivia’s Complex Terrain

Gutierrez,

Fenta,

Meshesha

et al. 2024

Remote Sensing

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This study evaluated the accuracy of two new generation satellite rainfall estimates (SREs): Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) and Integrated Multi-satellite Retrieval for GPM (IMERG) over Bolivia’s complex terrain. These SREs were compared against rainfall data from rain gauge measurements on a point-to-pixel basis for the period 2002–2020. The evaluation was performed across three regions with distinct topographical settings: Altiplano (Highland), Valles (Midland), and Llanos (Lowland). IMERG exhibited better accuracy in rainfall detection than CHIRPS, with the highest rainfall detection skills observed in the Highland region. However, IMERG’s higher rainfall detection skill was countered by its higher false alarm ratio. CHIRPS provided a more accurate estimation of rainfall amounts across the three regions, exhibiting low random errors and relative biases below 10%. IMERG tended to overestimate rainfall amounts, with marked overestimation by up to 75% in the Highland region. Bias decomposition revealed that IMERG’s high false rainfall bias contributed to its marked overestimation of rainfall. We showcase the utility of long-term CHIRPS data to investigate spatio-temporal rainfall patterns and meteorological drought occurrence in Bolivia. The findings of this study offer valuable insights for choosing appropriate SREs for informed decision-making, particularly in regions of complex topography lacking reliable gauge data.

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Section: Introductionmentioning

confidence: 99%

Unveiling the Accuracy of New-Generation Satellite Rainfall Estimates across Bolivia’s Complex Terrain

Gutierrez,

Fenta,

Meshesha

et al. 2024

Remote Sensing

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Landslide Hazard Prediction Based on Small Baseline Subset–Interferometric Synthetic-Aperture Radar Technology Combined with Land-Use Dynamic Change and Hydrological Conditions (Sichuan, China)

Guo,

Martínez-Graña

2024

Remote Sensing

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Le’an Town, located in the southwest of Qingchuan County, Guangyuan City, Sichuan Province, boasts a unique geographical position. The town’s terrain is complex, and its geological environment is fragile. Multiple phases of tectonic movements have resulted in numerous cracks and faults, making the area prone to landslides, debris flows, and other disasters. Additionally, heavy rainfall and fluctuating groundwater levels further exacerbate the instability of the mountains. Human activities, such as overdevelopment and deforestation, have significantly increased the risk of geological disasters. Currently, the methods for landslide prediction in Le’an Town are limited; traditional techniques cannot provide precise forecasts, and the study area is largely covered by tall vegetation. Therefore, this paper proposes a method that combines SBAS-InSAR technology with dynamic changes in land use and hydrological conditions. SBAS-InSAR technology is used to obtain surface deformation information, while land-use changes and hydrological condition data are incorporated to analyze the dynamic characteristics and potential influencing factors of landslide areas. The innovation of this method lies in its high-precision surface deformation monitoring capability and the integration of multi-source data, which can more comprehensively reveal the geological environmental characteristics of the study area, thereby achieving accurate predictions of landslide development. The study results indicate that the annual subsidence rate in most deformation areas of Le’an Town ranges from −10 to 0 mm, indicating slow subsidence. In some areas, the subsidence rate exceeds −50 mm per year, showing significant slope aspect differences, reflecting the combined effects of geological structures, climatic conditions, and human activities. It is evident that land-use changes and hydrological conditions have a significant impact on the occurrence and development of landslides. Therefore, by utilizing SBAS-InSAR technology and cross-verifying it with other techniques, the consistency of identified landslide deformation areas can be enhanced, thereby improving results. This method provides a scientific basis for the monitoring and early warning of landslide disasters and has important practical application value.

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Risk Perception in the Nigua River Basin: Key Determinants and Policy Implications

Maldonado-Santana,

Torres-Valle,

Franco-Billini

et al. 2024

Water

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The Nigua River basin in the Dominican Republic is a critical hydrographic area facing significant environmental challenges, including deforestation, soil erosion and pollution from mining and agricultural activities. This study explores the role of risk perception among local residents in shaping policies for the basin’s sustainable management. The research aims to identify the factors influencing risk perception and propose actionable strategies to improve environmental governance in the region. A “perceived risk profile” methodology was applied, using survey data from 1223 basin residents. The analysis identified key variables that influence risk perception, including demographic factors such as education, gender, and place of residence. The findings reveal that risk underestimation correlates with low awareness of risks, uncertainty about the origins of disasters, fatalism toward natural events, and low trust in institutions. In contrast, risk over-estimation is linked to infrequent risk communication, heightened catastrophism and a strong emphasis on the benefits of environmental protection. The study also highlights significant regional differences in risk perception, with residents of the lower basin exhibiting higher perceptions of risk due to cumulative pollution and frequent disaster impacts. Based on these insights, the study recommends targeted strategies to bridge risk perception gaps, including tailored risk communication, community-based environmental education and stronger institutional trust-building initiatives, all aimed at fostering more effective and inclusive environmental governance in the Nigua basin.

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Alterations in Hydrological Responses under Changing Climate and Land Use/Land Cover across Contrasting Agroecological Environments: A Case Study on the Chemoga Watershed in the Upper Blue Nile Basin, Ethiopia

Cited by 3 publications

References 67 publications

Unveiling the Accuracy of New-Generation Satellite Rainfall Estimates across Bolivia’s Complex Terrain

Unveiling the Accuracy of New-Generation Satellite Rainfall Estimates across Bolivia’s Complex Terrain

Landslide Hazard Prediction Based on Small Baseline Subset–Interferometric Synthetic-Aperture Radar Technology Combined with Land-Use Dynamic Change and Hydrological Conditions (Sichuan, China)

Risk Perception in the Nigua River Basin: Key Determinants and Policy Implications

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