RESPONSE OF RIPARIAN VEGETATION IN AUSTRALIA"S LARGEST RIVER BASIN TO INTER AND INTRA-ANNUAL CLIMATE VARIABILITY AND FLOODING AS QUANTIFIED WITH LANDSAT AND MODIS

Australia is a continent subject to high rainfall variability, which has major influences on runoff and vegetation dynamics. However, the resulting spatial-temporal pattern of flooding and its influence on riparian vegetation has not been quantified in a spatially explicit way. Here we focused on the floodplains of the entire Murray-Darling Basin (MDB), an area that covers over 1M km2, as a case study. The MDB is the country’s primary agricultural area with scarce water resources subject to competing demands and impacted by climate change and more recently by the Millennium Drought (1999–2009). Riparian vegetation in the MDB floodplain suffered extensive decline providing a dramatic degradation of riparian vegetation. We quantified the spatial-temporal impact of rainfall, temperature and flooding patters on vegetation dynamics at the subcontinental to local scales and across inter to intra-annual time scales based on three decades of Landsat (25k images), Bureau of Meteorology data and one decade of MODIS data. Vegetation response varied in space and time and with vegetation types, densities and location relative to areas frequently flooded. Vegetation degradation trends were observed over riparian forests and woodlands in areas where flooding regimes have changed to less frequent and smaller inundation extents. Conversely, herbaceous vegetation phenology followed primarily a ‘boom’ and ‘bust’ cycle, related to inter-annual rainfall variability. Spatial patters of vegetation degradation changed along the N-S rainfall gradient but flooding regimes and vegetation degradation patterns also varied at finer scale, highlighting the importance of a spatially explicit, internally consistent analysis and setting the stage for investigating further cross-scale relationships. Results are of interest for land and water management decisions. The approach developed here can be applied to other areas globally such as the Nile river basin and Okavango River delta in Africa or the Mekong River Basin in Southeast Asia.

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RESPONSE OF RIPARIAN VEGETATION IN AUSTRALIA"S LARGEST RIVER BASIN TO INTER AND INTRA-ANNUAL CLIMATE VARIABILITY AND FLOODING AS QUANTIFIED WITH LANDSAT AND MODIS

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xli-b8-577-2016 ◽

2016 ◽

Vol XLI-B8 ◽

pp. 577-578

Author(s):

M. Broich ◽

M. G. Tulbure

Keyword(s):

River Basin ◽

Vegetation Dynamics ◽

Riparian Vegetation ◽

Rainfall Variability ◽

Annual Rainfall ◽

Spatially Explicit ◽

Rainfall Gradient ◽

Vegetation Degradation ◽

Millennium Drought ◽

Okavango River

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Seasonal and Annual Rainfall Variability and Their Impact on Rural Water Supply Services in the Wami River Basin, Tanzania

Water ◽

10.3390/w11102055 ◽

2019 ◽

Vol 11 (10) ◽

pp. 2055 ◽

Cited By ~ 2

Author(s):

Sekela Twisa ◽

Manfred F. Buchroithner

Keyword(s):

Water Supply ◽

River Basin ◽

Rural Areas ◽

Rainfall Variability ◽

Seasonal Rainfall ◽

Annual Rainfall ◽

Water Supply Systems ◽

Rural Water Supply ◽

Rural Water ◽

Water Supply Services

In some parts of Africa, rainfall variability has resulted in widespread droughts and floods, thus posing a substantial challenge to water availability in rural areas, especially drinking water. Therefore, due to increasing water demands, increases in the population, and economic development, water supply systems are under constant stress. One of the critical uncertainties surrounding the effects of rainfall variability in Africa is the significant impact that it imposes on rural water supply services. The present study analyzes the trends in annual and seasonal rainfall time series in the Wami River Basin to see if there have been any significant changes in the patterns during the period 1983–2017 and how they affect the access to water supply services in rural areas. The study analyzes the trends of rainfall series of three stations using simple regression, Mann–Kendal Test and Sen’s Slope Estimator. The water point mapping datasets were analyzed considering seasonal variation. The analysis showed a statistically significant positive trend in annual rainfall at Kongwa and March–April–May (MAM) seasonal rainfall at Dakawa. The maximum increase in annual rainfall occurred at Kongwa (5.3 mm year−1) and for MAM seasonal data at Dakawa (4.1 mm year−1). Water points were found to be significantly affected by seasonal changes, both in terms of availability and quality of water. There also exists a strong relationship between rural water services and seasons.

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Effects of Climate Variability on Normalized Difference Vegetation Index (NDVI) in the Gojeb River Catchment, Omo-Gibe Basin, Ethiopia

Advances in Meteorology ◽

10.1155/2020/8263246 ◽

2020 ◽

Vol 2020 ◽

pp. 1-16

Author(s):

Melku Dagnachew ◽

Asfaw Kebede ◽

Awdenegest Moges ◽

Adane Abebe

Keyword(s):

Climate Variability ◽

Trend Analysis ◽

Vegetation Dynamics ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Rainfall Variability ◽

Time Lag ◽

Rainfall Time Series ◽

River Catchment ◽

Vegetation Degradation

Vegetation dynamics have been visibly influenced by climate variability. The Normalized Difference Vegetation Index (NDVI) has been the most commonly used index in vegetation dynamics. The study was conducted to examine the effects of climatic variability (rainfall) on NDVI for the periods 1982–2015 in the Gojeb River Catchment (GRC), Omo-Gibe Basin, Ethiopia. The spatiotemporal trend in NDVI and rainfall time series was assessed using a Theil–Sen (Sen) slope and Mann–Kendall (MK) statistical significance test at a 95% confidence interval. Moreover, the residual trend analysis (RESTREND) method was used to investigate the effect of rainfall and human induction on vegetation degradation. The Sen’s slope trend analysis and MK significant test indicated that the magnitude of annual NDVI and rainfall showed significant decrement and/or increment in various portions of the GRC. The concurrent decrement and/or increment of annual NDVI and rainfall distributions both spatially and temporarily could be attributed to the significant positive correlation of the monthly (RNDVI-RF = 0.189, P≤0.001) and annual (RNDVI-RF = 0.637, P≤0.001) NDVI with rainfall in almost all portions of the catchment. In the GRC, a strongly negative decrement and strong positive increment of NDVI could be derived by human-induced and rainfall variability, respectively. Accordingly, the significant NDVI decrement in the downstream portion and significant increment in the northern portion of the catchment could be attributed to human-induced vegetation degradation and the variability of rainfall, respectively. The dominance of a decreasing trend in the residuals at the pixel level for the NDVI from 1982, 1984, 2000, 2008 to 2012 indicates vegetation degradation. The strong upward trend in the residuals evident from 1983, 1991, 1998 to 2007 was indicative of vegetation improvements. In the GRC, the residuals may be derived from climatic variations (mainly rainfall) and human activities. The time lag between NDVI and climate factors (rainfall) varied mainly from two to three months. In the study catchment, since vegetation degradations are mainly caused by human induction and rainfall variability, integrated and sustainable landscape management and climate-smart agricultural practices could have paramount importance in reversing the degradation processes.

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Relative Contribution of Anthropogenic Forcing and Natural Processes to Rainfall Variability over Victoria, Australia

10.5194/egusphere-egu2020-21262 ◽

2020 ◽

Author(s):

Surendra Rauniyar ◽

Scott Power

Keyword(s):

Climate Models ◽

Global Climate ◽

Rainfall Variability ◽

Global Climate Models ◽

Interquartile Range ◽

Annual Rainfall ◽

External Forcing ◽

Cool Season ◽

Millennium Drought ◽

Forced Drying

Victoria is the second-most populated and most densely populated state in Australia with a population of over 6.5 million. Over two thirds of the population live in greater Melbourne. It is also a major area for agriculture and tourism and is the second largest economy in Australia, accounting for a quarter of Australia's Gross Domestic Product. Any changes in Victoria's climate has huge impacts in these sectors. Rainfall over Victoria during the cool season (e.g. April to October) has been unusually low since the beginning of the Millennium Drought in 1997 (~12% below the 20th century average). Cool season rainfall contributes two-third to annual rainfall and is very important for many crops and for replenishing reservoirs across the state. Here we examine the extent to which this reduction in cool season rainfall is driven by external forcing, and the prospects for future multi-decadal rainfall, taking both external forcing and internal natural climate variability into account.We analyse simulations from 40 global climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) under preindustrial and historical forcing, as well as three scenarios for the 21st century: Representative Concentration Pathway (RCP)2.6, RCP4.5 and RCP8.5, which vary markedly in the amount of greenhouse gas emitted over the coming century. While the 1997-2018 average rainfall for cool season is below the preindustrial average in more than two-thirds of models under the three scenarios, the magnitude of the externally-forced drying is very small (median decline is around -2.5% in all three scenarios with an interquartile range around -5% to +1%). The model ensemble results suggest that external forcing contributed only 20% (interquartile range -41% to 4%) to the drying observed in 1997-2018, relative to 1900-1959. These results suggest that the observed drying was dominated by natural, internal rainfall variability. While the multi-model median is below average from 1997-2018 onwards, the externally-forced drying only becomes clear from 2010-2029, when the proportion of models exhibiting drying increases to over 90% under all three scenarios. This agreement reflects the increase in the magnitude of the externally-forced drying. We estimate that there is a 12% chance that internal rainfall variability will completely offset the externally-forced drying averaged over 2018-2037, regardless of scenario. By the late 21st century the externally forced change under RCP8.5 is so large that drying &#8211; even after taking internally variability into account - appears inevitable.&#160;Confidence in the modelled projections is lowered because models have difficulty in simulating the magnitude of the observed decline in rainfall. Some of this difficulty appears to arise because most models seem to underestimate multidecadal rainfall variability. Other candidates are: the observed drying may have been primarily due to the occurrence of an extreme, internally-driven event; the models underestimate the magnitude of the externally-forced drying in recent decades; or some combination of the two. If externally-forced drying is underestimated because the response to greenhouse gases is underestimated then the magnitude of projected changes might also be underestimated.

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Spatiotemporal Rainfall Distribution of Soan River Basin, Pothwar Region, Pakistan

Advances in Meteorology ◽

10.1155/2021/6656732 ◽

2021 ◽

Vol 2021 ◽

pp. 1-24

Author(s):

Fiaz Hussain ◽

Ghulam Nabi ◽

Ray-Shyan Wu

Keyword(s):

River Basin ◽

Water Resource Management ◽

Monsoon Season ◽

Rainfall Variability ◽

Annual Rainfall ◽

Mountainous Areas ◽

Distribution Maps ◽

Annual Basis ◽

Rational Management ◽

Rainfall Patterns

This study evaluates the spatiotemporal rainfall variability over the semimountainous Soan River Basin (SRB) of sub-Himalayan Pothwar region, Pakistan. The temporal rainfall trend analysis of sixteen rain gauges was performed on annual basis with long-term (1981–2016) data. The results depicted that there is substantial year-to-year and season-to-season variability in rainfall patterns, and rainfall patterns are generally erratic in nature. The results highlight that most of the highland rainfall stations showed decreasing trends on annual basis. The central and lowland stations of the study area recorded an increasing trend of rainfall except for Talagang station. The average annual rainfall of the study area ranges between 492 mm and 1710 mm in lowland and high-altitude areas, respectively. Of the whole year’s rainfall, about 70 to 75% fall during the monsoon season. The rainfall spatial distribution maps obtained using the inverse distance weighting (IDW) method, through the GIS software, revealed the major rainfall range within the study area. There is a lack of water during postmonsoon months (November–February) and great differences in rainfall amounts between the mountainous areas and the lowlands. There is a need for the rational management of mountainous areas using mini and check dams to increase water production and stream regulation for lowland areas water availability. The spatiotemporal rainfall variability is crucial for better water resource management schemes in the study area of Pothwar region, Pakistan.

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Analysis of Rainfall Variability and Trends Over Nzoia River Basin, Kenya

Journal of Engineering Research and Reports ◽

10.9734/jerr/2021/v21i417457 ◽

2021 ◽

pp. 26-52

Author(s):

Ernest Othieno Odwori ◽

Jacob Wanambacha Wakhungu

Keyword(s):

Economic Development ◽

Regression Analysis ◽

Water Resources ◽

Linear Regression ◽

River Basin ◽

Water Resources Management ◽

Rainfall Variability ◽

Linear Regression Analysis ◽

Annual Rainfall ◽

Resources Management

Nzoia river is mainly rain fed and the basin is one of the regions that is highly vulnerable to climate change in Kenya. Understanding rainfall variability and trends is important for better water resources management and economic development in the basin. The aim of this study is to assess variability and trends in rainfall at 13 sites within Nzoia River Basin over the period, 1970 to 2001, using the parametric test of Linear regression analysis and the non-parametric Mann–Kendall statistical test. Data for this study was obtained from the Kenya Meteorological Department (KMD). The basin experiences four rainfall seasons in a year as a result of the Inter-Tropical Convergence Zone (ITCZ). There are two rainy seasons and two dry seasons. Annual rainfall through Linear regression analysis shows 6 stations, Kaimosi Tea Estate Ltd, Kakamega Meteorological Station, Bungoma Water Supply, Nzoia Forest Station, Malava Forest Station and Webuye Agricultural Office with declining rainfalls. The remaining 7 stations, Leissa Farm Kitale, Turbo Forest Nursery, Chorlim ADC Farm, Kaptagat Forest Station, Kimilili Agricultural Department, Bunyala Irrigation Scheme and Kadenge Yala Swamp showed increasing rainfalls. The majority of stations with increasing annual rainfall are in the upper catchment whereas those with decreasing rainfall are in the middle and lower catchment. Only 3 out of the 13 stations showed statistically significant trends in rainfall with two in the upper catchment and one in the middle; the remaining 10 stations had statistically insignificant trends. These observed changes in rainfall, although most time series are not convincing as they show predominantly no significance, along with the reported climatic warming in most parts of the basin may have future implications on human health, water resources management, various plant and animal species bio-diversity and the overall economic development of the basin.

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Multi-century cool and warm season rainfall reconstructions for Australia's major climatic regions

10.5194/cp-2017-28 ◽

2017 ◽

Cited By ~ 1

Author(s):

Mandy Freund ◽

Benjamin J. Henley ◽

David J. Karoly ◽

Kathryn J. Allen ◽

Patrick J. Baker

Keyword(s):

Large Scale ◽

Rainfall Variability ◽

Warm Season ◽

Seasonal Rainfall ◽

Spatial Extent ◽

Annual Rainfall ◽

The Past ◽

Millennium Drought ◽

Australian Continent ◽

Regional Rainfall

Abstract. Australian seasonal rainfall is strongly influenced by large-scale ocean-atmosphere climate influences. In this study, we exploit the links between these large-scale precipitation influences, regional rainfall variations, and palaeoclimate proxies in the region to reconstruct Australian regional rainfall between four and eight centuries into the past. We use an extensive network of palaeoclimate records from the Southern Hemisphere to reconstruct cool (Apr–Sep) and warm (Oct–Mar) season rainfall in eight natural resource management (NRM) regions spanning the Australian continent. Our sub-annual rainfall reconstruction aligns well with independent early documentary sources and existing reconstructions. Critically, this reconstruction allows us, for the first time, to place recent observations at a sub-annual temporal resolution into a pre-instrumental context, across the entire continent of Australia. We find that recent 30-year and 50-year trends towards wetter conditions in tropical northern Australia are highly unusual in the multi-century context of our reconstruction. Recent cool season drying trends in parts of southern Australia are also very unusual, although not unprecedented, across the multi-century context. We also use our reconstruction to investigate the spatial and temporal extent of historical drought events. Our reconstruction reveals that the spatial extent and duration of the Millennium drought (1997–2009) appears either very much below average or unprecedented in southern Australia over at least the last 400 years. Our reconstruction identifies a number of severe droughts over the past several centuries that vary widely in their spatial footprint, highlighting the high degree of diversity in historical droughts across the Australian continent. We document distinct characteristics of major droughts in terms of their spatial extent, duration, intensity, and seasonality. Compared to the three largest droughts in the instrumental period (Federation drought [1895–1903], World War II drought [1939–1945], and the Millennium drought [1997–2005]), we find that the historically documented Settlement drought [1790–1793], Sturt drought [1809–1830] and the Goyder Line drought [1861–1866] actually had more regionalised patterns and reduced spatial extents. This seasonal rainfall reconstruction provides a new opportunity to understand Australian rainfall variability, by contextualising severe droughts and recent trends in Australia.

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Rainfall Variability and Trends over the African Continent Using TAMSAT Data (1983–2020): Towards Climate Change Resilience and Adaptation

Remote Sensing ◽

10.3390/rs14010096 ◽

2021 ◽

Vol 14 (1) ◽

pp. 96

Author(s):

Niranga Alahacoon ◽

Mahesh Edirisinghe ◽

Matamyo Simwanda ◽

ENC Perera ◽

Vincent R. Nyirenda ◽

...

Keyword(s):

Climate Change ◽

River Basin ◽

Water Resource Management ◽

Rainfall Variability ◽

Decision Makers ◽

Annual Rainfall ◽

African Continent ◽

Climate Zones ◽

Mk Test ◽

Rainfall Trends

This study reveals rainfall variability and trends in the African continent using TAMSAT data from 1983 to 2020. In the study, a Mann–Kendall (MK) test and Sen’s slope estimator were used to analyze rainfall trends and their magnitude, respectively, under monthly, seasonal, and annual timeframes as an indication of climate change using different natural and geographical contexts (i.e., sub-regions, climate zones, major river basins, and countries). The study finds that the highest annual rainfall trends were recorded in Rwanda (11.97 mm/year), the Gulf of Guinea (river basin 8.71 mm/year), the tropical rainforest climate zone (8.21 mm/year), and the Central African region (6.84 mm/year), while Mozambique (−0.437 mm/year), the subtropical northern desert (0.80 mm/year), the west coast river basin of South Africa (−0.360 mm/year), and the Northern Africa region (1.07 mm/year) show the lowest annual rainfall trends. There is a statistically significant increase in the rainfall in the countries of Africa’s northern and central regions, while there is no statistically significant change in the countries of the southern and eastern regions. In terms of climate zones, in the tropical northern desert climates, tropical northern peninsulas, and tropical grasslands, there is a significant increase in rainfall over the entire timeframe of the month, season, and year. This implies that increased rainfall will have a positive effect on the food security of the countries in those climatic zones. Since a large percentage of Africa’s agriculture is based only on rainfall (i.e., rain-fed agriculture), increasing trends in rainfall can assist climate resilience and adaptation, while declining rainfall trends can badly affect it. This information can be crucial for decision-makers concerned with effective crop planning and water resource management. The rainfall variability and trend analysis of this study provide important information to decision-makers that need to effectively mitigate drought and flood risk.

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