Synergistic Impacts of Rainfall Variability and Land Use Heterogeneity on Nitrate Retention in River Networks: Exacerbation or Compensation?

2020 ◽  
Vol 56 (8) ◽  
Author(s):  
Sheng Ye ◽  
Murugesu Sivapalan ◽  
Qihua Ran
Keyword(s):  
Land Use ◽  
Rainfall Variability ◽  
River Networks ◽  
Nitrate Retention

scholarly journals Land Use/Cover Response to Rainfall Variability: A Comparing Analysis between NDVI and EVI in the Southwest of Burkina Faso

Climate ◽  
2014 ◽  
Vol 3 (1) ◽  
pp. 63-77 ◽  
Author(s):  
Benewinde Zoungrana ◽  
Christopher Conrad ◽  
Leonard Amekudzi ◽  
Michael Thiel ◽  
Evariste Da
Keyword(s):  
Land Use ◽  
Burkina Faso ◽  
Rainfall Variability

scholarly journals Bivariate Based Susceptibility Mapping for Gully Erosion in Wanjoga River Catchment Upper Tana Basin, Kenya

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Cecilia Wawira Ireri ◽  
George Krhoda ◽  
Mukhovi Stellah
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Arid Regions ◽  
Rainfall Variability ◽  
Gully Erosion ◽  
Geographical Information ◽  
Susceptibility Map ◽  
Error Matrix ◽  
Conditioning Factors ◽  
Semi Arid

Gullies occur in semi-arid regions characterized by rainfall variability and seasonality, increased overland flow, affecting ecological fragility of an area. In most gully prone areas, extent of land affected by gullies is increasing. Thus, predicting susceptibility to gully erosion in semi-arid environment is an important step towards effectively rehabilitating and prevention against gully erosion. Proneness to gully occurrence was assessed against; Land cover/land use, slope, soil characteristics, rainfall variability and elevation, and modelled using geographical information system (GIS)-based bivariate statistical approach. Objectives of the study were; a) to assess influence of geomorphological factors on gully erosion, b) analyze and develop gully erosion susceptibility map, c) verify gully susceptibility images using error matrix of class labels in classified map against ground truth reference data. Total of 66 gullied areas (width and depth ≥ ranging 0.5), were mapped using 15m resolution Landsat images for 2018 and field surveys to estimate susceptibility to gully erosion by Global Mapper software in GIS. The images were verified using 120 pixels of known 15 gully presence or absence to produce an error matrix based on comparison of actual outcomes to predicted outcomes. Influence of conditioning factors to gully erosion showed a significant positive relationship between gully susceptibility and gully conditioning factors with consistency value; CR =0.097; value< 0.1, indicating, individual conditioning factors had an importance in influencing gully erosion. Slope (43%) and soil lithotype (25%), most influenced gully susceptibility, while land cover/land use (12%) and rainfall (12%) had least impact. Verification results showed satisfactory agreement between susceptibility map and field data on gullied areas at approximately 76.2%, an error of positive value of 4% and a negative value of 7%. Thus, production of susceptibility map by bivariate statistical method represents a useful tool for ending long and short-term gully emergencies by planning conservation of semi-arid regions.

Inventory and preliminary assessment of natural hazards in Kigezi highlands, South Western Uganda

2021 ◽  
Author(s):  
Violet Kanyiginya ◽  
Ronald Twongyirwe ◽  
Grace Kagoro ◽  
David Mubiru ◽  
Matthieu Kervyn ◽  
...  
Keyword(s):  
Land Use ◽  
Natural Hazards ◽  
Natural Hazard ◽  
Rainfall Variability ◽  
Land Use Changes ◽  
Satellite Image ◽  
Google Earth ◽  
Landscape Characteristics ◽  
Western Uganda ◽  
The Impact

&lt;p&gt;Uganda is regularly affected by multiple natural hazards, including floods, droughts, earthquakes, landslides and windstorms. This is due to a combination of natural biophysical factors such as steep topography, intense rainfall, variability of dry and rain seasons and high weathering rates. In addition, high population density, deforestation and other human-induced land use changes, and high poverty levels are believed to have an influence on the patterns of natural hazards and their impacts in the region. Despite this, there are limited studies that assess where and when natural hazards occur in Uganda, and a dearth of information on the processes involved. In addition, drivers and earth/landscape characteristics controlling the occurrence of natural hazards in the country remain poorly understood despite the high need for effective disaster risk reduction. Here, we present the ongoing methodological research framework and the first results of a study whose main objective is to understand the spatial and temporal occurrence of natural hazards that affect the Kigezi Highlands of south western Uganda and their interactions. To this end, the study is undertaking a comprehensive regional hazard inventory consisting of satellite image analysis, field surveys and exploration of literature and archives. Historical aerial photos and interviews with the elderly are important tools to analyze the impact of multi-decadal human-induced land use changes on natural hazard occurrences. Meanwhile, a network of 15 geo-observers, i.e. citizens of local communities distributed across representative landscapes of the study area, was established in December 2019. Trained at using smartphone technology, they collect information (processes and impacts) on seven different natural hazards (droughts, earthquakes, floods, hailstorms, landslides, lightning, and windstorms) whenever they occur. &amp;#160;During the first 12 months, 204 natural hazard events with accurate timing information have been reported by the geo-observers. Combined to field survey, these recent events have been associated mainly with the occurrence of &gt; 3000 shallow landslides and 30 floods, frequently in co-occurrence and triggered by heavy rainfall. Additional inventory from Google Earth and Planet imagery covering a region much larger than that of the geo-observer network and a time window of more than 10 years shows an extra 230 landslide and flood occurrences, while archives and literature indicate 226 natural hazard events over the last 30 years. The preliminary results already demonstrate the value of citizen-science in producing highly detailed natural hazard inventory. A combination of different inventory methods improves the level of accuracy in understanding the spatial-temporal distribution of natural hazards.&lt;/p&gt;

scholarly journals Model-based study of the role of rainfall and land use–land cover in the changes in the occurrence and intensity of Niger red floods in Niamey between 1953 and 2012

2016 ◽  
Vol 20 (7) ◽  
pp. 2841-2859 ◽  
Author(s):  
Claire Casse ◽  
Marielle Gosset ◽  
Théo Vischel ◽  
Guillaume Quantin ◽  
Bachir Alkali Tanimoun
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Rainfall Variability ◽  
Drainage Area ◽  
Annual Rainfall ◽  
Data Sets ◽  
Relative Role ◽  
Land Use Land Cover ◽  
Rainfall Deficit

Abstract. Since 1950, the Niger River basin has gone through three main climatic periods: a wet period (1950–1960), an extended drought (1970–1980) and since 1990 a recent partial recovery of annual rainfall. Hydrological changes co-occur with these rainfall fluctuations. In most of the basin, the rainfall deficit caused an enhanced discharge deficit, but in the Sahelian region the runoff increased despite the rainfall deficit. Since 2000 the Sahelian part of the Niger has been hit by an increase of flood hazards during the so-called red flood period. In Niamey city, the highest river levels and the longest flooded period ever recorded occurred in 2003, 2010, 2012 and 2013, with heavy casualties and property damage. The reasons for these changes, and the relative role of climate versus land use–land cover (LULC) changes are still debated and are investigated in this paper. The evolution of the Niger red flood in Niamey from 1950 to 2012 is analysed based on long-term records of rainfall (three data sets based on in situ and/or satellite data) and discharge, and a hydrological model. The model is first run with the present LULC conditions in order to analyse solely the effect of rainfall variability. The impact of LULC and drainage area modification is investigated in a second step. The simulations based on the current surface conditions are able to reproduce the observed trend in the red flood occurrence and intensity since the 1980s. This has been verified with three independent rainfall data sets and implies that rainfall variability is the main driver for the red flood intensification observed over the last 30 years. The simulation results since 1953 have revealed that LULC and drainage area changes need to be invoked to explain the changes over a 60-year period.

scholarly journals Sensitivity of the agroecosystem in the Ganges basin to inter-annual rainfall variability and associated changes in land use

2013 ◽  
Vol 34 (10) ◽  
pp. 3066-3077 ◽  
Author(s):  
C. Siderius ◽  
P. J. G. J. Hellegers ◽  
A. Mishra ◽  
E. C. van Ierland ◽  
P. Kabat
Keyword(s):  
Land Use ◽  
Rainfall Variability ◽  
Annual Rainfall ◽  
Ganges Basin ◽  
The Ganges

scholarly journals The Relationship between Climate Change, Variability, and Food Security: Understanding the Impacts and Building Resilient Food Systems in West Pokot County, Kenya

2022 ◽  
Vol 14 (2) ◽  
pp. 765
Author(s):  
Everlyne B. Obwocha ◽  
Joshua J. Ramisch ◽  
Lalisa Duguma ◽  
Levi Orero
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Food Security ◽  
Land Cover ◽  
Rainfall Variability ◽  
Early Warning Systems ◽  
Annual Rainfall ◽  
Climate Change And Variability ◽  
West Pokot ◽  
The Mean

This study integrated local and scientific knowledge to assess the impacts of climate change and variability on food security in West Pokot County, Kenya from 1980–2012. It characterized rainfall and temperature from 1980–2011 and the phenology of agricultural vegetation, assessed land use and land cover (LULC) changes, and surveyed local knowledge and perceptions of the relationships between climate change and variability, land use decisions, and food (in)security. The 124 respondents were aware of long-term changes in their environment, with 68% strongly believing that climate has become more variable. The majority of the respondents (88%) reported declining rainfall and rising temperatures, with respondents in the lowland areas reporting shortened growing seasons that affected food production. Meteorological data for 1980–2011 confirmed high inter-annual rainfall variability around the mean value of 973.4 mm/yr but with no notable trend. Temperature data showed an increasing trend between 1980 and 2012 with lowlands and highlands showing changes of +1.25 °C and +1.29 °C, respectively. Land use and land cover changes between 1984 and 2010 showed cropland area increased by +4176% (+33,138 ha), while grassland and forest areas declined by –49% (–96,988 ha) and –38% (–65,010 ha), respectively. These area changes illustrate human-mediated responses to the rainfall variability, such as increased stocking after good rainfall years and crop area expansion. The mean Normalized Difference Vegetation Index (NDVI) values ranged from 0.36–0.54 within a year, peaking in May and September. For weather-related planning, respondents relied on radio (64%) and traditional forecasters (26%) as predominant information sources. Supporting continuous climate change monitoring, intensified early warning systems, and disseminating relevant information to farmers could help farmers adopt appropriate adaptation strategies.

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