Mapping 100 years of Thornthwaite moisture index: Impact of climate change in Victoria, Australia

Geographer C. W. Thornthwaite proposed in 1948 a moisture index called Thornthwaite Moisture Index (TMI) as part of a water balance model for a new classification system for climate. The importance of TMI climatic classification has been recognised in many areas of knowledge and practice worldwide over the last 60 years. However, although past climate research was focused on developing adequate methods for climate classification, current research is more concerned with understanding the patterns of climate change. The use of TMI as an indicator for climate change is still an incipient area of research. The contributions of this paper are twofold. First, it is to fully document a methodology based on geostatistics adopted to produce a time series of TMI maps that are accurate and have high spatial resolution. The state of Victoria, in Australia, over the last century, is used as the case study. Second, by analysing these maps, the paper presents a general evaluation of the spatial patterns found in Victoria related to moisture variability across space and over time. Some potential implications of the verified moisture changes are discussed, and a number of ideas for further development are suggested. © 2014 Institute of Australian Geographers.

The influence of climate change on Thorthwaite moisture index on the design of light structures

Significant long term changes in the earth’s climate have occurred in the past but recently there has been more severe climate fluctuation than have occurred in the past few centuries. The effect of this climate change on the foundation conditions of roads and low-rise buildings is costing several hundred billion dollars world-wide. A method which tracks this climate change will be of great value for companies and governments. C.W. Thornthwaite (1948) defined the Thornthwaite Moisture Index (TMI) as the first base for his climate classification system and mapping in the United States. There are 3 important factors to predict ground movement: (a) the degree of moisture index change (b) the depth at which this change occurs and (c) the foundation soil type. The water budget model was used by Thornthwaite (1948) to calculate the moisture index. This paper also discusses two typical examples of the use of this model. Originally TMI’s were mainly used to map soil moisture conditions for agriculture but soon became a method to predict environmental and pavement foundation changes.

TMI for urban resilience : measuring and mapping long-term climate change effects on soil moisture

The effect of climate change on the shallow expansive foundation conditions of resident dwellings is costing several hundred billion dollars worldwide. The design and costs of constructing or repairing residential footings is greatly influenced by the degree of ground movement, which is driven by the magnitude of change in soil moisture. The impacts of climate change on urban infrastructure are expected to include accelerated degradation of materials and foundations of buildings and facilities, increased ground movement, changes in ground water affecting the chemical structure of foundations, and fatigue of structures from extreme storm events. Previous research found that residential houses that were built less than five years ago have suffered major cracks and other damage caused by slab movement after record rainfall. The Thornthwaite Moisture Index (TMI) categorises climate on the basis of rainfall, temperature, potential evapotranspiration and the water holding capacity of the soil. Originally TMI was mainly used to map soil moisture conditions for agriculture but soon became a method to predict pavement and foundation changes. Few researchers have developed TMI maps for Australia, but generally, their accuracy is low or unknown, and their use is limited. The aims of this paper are: (1) To produce accurate maps of TMI for the state of Victoria for 100 years (1913 to 2012) in 20 year periods using long-term historical climatic data and advanced spatial statistics methods in GIS, and (2) Analyse the spatial and temporal changes of TMI in Victoria. Preliminary results suggest that a better understanding of climate change through long-term TMI mapping can assist urban planning and guide construction regulations towards the development of cities which are more resilient.

The ranking of factors influencing the behaviour of light structures on expansive soils in Victoria, Australia

In this paper a Neural Network Model was used to develop a ranking of the potential damage influences for light structures on expansive soils in Victoria. These influences include geology, Thornthwaite moisture index, vegetation covers, construction foundation type, construction wall type, geographical region and age of building when first inspected. Approximately 400 cases of damage to light structures in Victoria, Australia were considered in this study. Feedforward Backpropagation was adopted to train the data. The ranking of importance was estimated using connection weight approach and then compared to results calculated from sensitivity analysis. From the analysis, the ranking of importance for potential damage factor was noted.

Impacts of Climate variability on Agriculture in Kerala

The study revealed that southwest monsoon rainfall in Kerala has been declining while increasing in post monsoon season. The annual rainfall exhibits a cyclic trend of 40-60 years, with a significant decline in recent decades. The intensity of climatological droughts was increasing across the State of Kerala through it falls under heavy rainfall zone due to unimodal rainfall pattern. The moisture index across the State of Kerala was moving from B4 to B3 humid, indicating that the State was moving from wetness to dryness within the humid climate.The study confirms that a warming Kerala is real as maximum, minimum and mean temperatures and temperature ranges are increasing. The rate of increase in maximum temperature was high (1.46°C) across the high ranges, followed by the coastal belt (1.09°C) of Kerala while the rate of increase was relatively marginal (0.25°C) across the midlands. The rate of increase in temperature across the high ranges is probably high because of deforestation. It indicates that the highranges and coastal belts in Kerala are vulnerable to global warming and climate change when compared to midlands.Interestingly, the trend in annual rainfall is increasing at Pampadumpara (Idukki), while declining at Ambalavayal across the highranges. In the case of maximum temperature, it was showing increasing trend at Pampadumpara while declining trend at Ambalavayal. In the case of minimum temperature it is declining at Pampadumpara while increasing in Ambalavalal.The paddy productivity in Kerala during kharif / virippu is unlikely to decline due to increasing temperature on the basis of long term climate change, but likely to decline to a considerable extent due to prolonged monsoon season, followed by unusual summer rains as noticed in 2007-08 and 2010-11.All the plantation crops under study are vulnerable to climate variability such as floods and droughts rather than long term changes in temperature and rainfall.

Coconut Phenology and Yield Response to Climate Variability and Change

The present investigation on “Coconut Phenology and Yield Response to Climate Variability and Change” was undertaken at the experimental site, at the Regional Station, Coconut Development Board, KAU Campus, Vellanikkara. Ten palms each of eight-year-old coconut cultivars viz., Tiptur Tall, Kuttiadi (WCT), Kasaragod (WCT) and Komadan (WCT) were randomly selected.The study therefore, reinforces our traditional knowledge that the coconut palm is sensitive to changing weather conditions during the period from primordium initiation to harvest of nuts (about 44 months). Absence of rainfall from December to May due to early withdrawal of northeast monsoon, lack of pre monsoon showers and late onset of southwest monsoon adversely affect the coconut productivity to a considerable extent in the following year under rainfed conditions. The productivity can be increased by irrigating the coconut palm during the dry periods.Increase in temperature, aridity index, number of severe summer droughts and decline in rainfall and moisture index were the major factors for a marginal decline or stagnation in coconut productivity over a period of time, though various developmental schemes were in operation for sustenance of coconut production in the State of Kerala. It can be attributed to global warming and climate change. Therefore, there is a threat to coconut productivity in the ensuing decades due to climate variability and change. In view of the above, there is an urgent need for proactive measures as a part of climate change adaptation to sustain coconut productivity in the State of Kerala.The coconut productivity is more vulnerable to climate variability such as summer droughts rather than climate change in terms of increase in temperature and decline in rainfall, though there was a marginal decrease (1.6%) in the decade of 1981-2009 when compared to that of 1951-80. This aspect needs to be examined in detail by coconut development agencies such as Coconut Development Board and State Agriculture Department for remedial measures. Otherwise, the premier position of Kerala in terms of coconut production is likely to be lost in the ensuing years under the projected climate change scenario. Among the four cultivars studied, Tiptur Tall appears to be superior in terms of reproduction phase and nut yield. This needs to be examined by the coconut breeders in their crop improvement programme as a part of stress tolerant under rainfed conditions. Crop mix and integrated farming are supposed to be the best combination to sustain development in the long run under the projected climate change scenarios. Increase in coconut area under irrigation during summer with better crop management and protection measures also are necessary measures to increase coconut productivity since the frequency of intensity of summer droughts is likely to increase under projected global warming scenario.

Evidence of a universal scaling relationship for leaf CO2 drawdown along an aridity gradient

The leaf carbon isotope ratio (δ13C) of C3 plants is inversely related to the drawdown of CO2 concentration during photosynthesis, which increases towards drier environments. We aimed to discriminate between the hypothesis of universal scaling, which predicts between-species responses of δ13C to aridity similar to within-species responses, and biotic homoeostasis, which predicts offsets in the δ13C of species occupying adjacent ranges. The Northeast China Transect spans 130–900 mm annual precipitation within a narrow latitude and temperature range. Leaves of 171 species were sampled at 33 sites along the transect (18 at ≥ 5 sites) for dry matter, carbon (C) and nitrogen (N) content, specific leaf area (SLA) and δ13C. The δ13C of species generally followed a common relationship with the climatic moisture index (MI). Offsets between adjacent species were not observed. Trees and forbs diverged slightly at high MI. In C3 plants, δ13C predicted N per unit leaf area (Narea) better than MI. The δ13C of C4 plants was invariant with MI. SLA declined and Narea increased towards low MI in both C3 and C4 plants. The data are consistent with optimal stomatal regulation with respect to atmospheric dryness. They provide evidence for universal scaling of CO2 drawdown with aridity in C3 plants.

Climate-driven expansion of blanket bogs in Britain during the Holocene

Blanket bog occupies approximately 6 % of the area of the UK today. The Holocene expansion of this hyperoceanic biome has previously been explained as a consequence of Neolithic forest clearance. However, the present distribution of blanket bog in Great Britain can be predicted accurately with a simple model (PeatStash) based on summer temperature and moisture index thresholds, and the same model correctly predicts the highly disjunct distribution of blanket bog worldwide. This finding suggests that climate, rather than land-use history, controls blanket-bog distribution in the UK and everywhere else. We set out to test this hypothesis for blanket bogs in the UK using bioclimate envelope modelling compared with a database of peat initiation age estimates. We used both pollen-based reconstructions and climate model simulations of climate changes between the mid-Holocene (6000 yr BP, 6 ka) and modern climate to drive PeatStash and predict areas of blanket bog. We compiled data on the timing of blanket-bog initiation, based on 228 age determinations at sites where peat directly overlies mineral soil. The model predicts large areas of northern Britain would have had blanket bog by 6000 yr BP, and the area suitable for peat growth extended to the south after this time. A similar pattern is shown by the basal peat ages and new blanket bog appeared over a larger area during the late Holocene, the greatest expansion being in Ireland, Wales and southwest England, as the model predicts. The expansion was driven by a summer cooling of about 2 °C, shown by both pollen-based reconstructions and climate models. The data show early Holocene (pre-Neolithic) blanket-bog initiation at over half of the sites in the core areas of Scotland, and northern England. The temporal patterns and concurrence of the bioclimate model predictions and initiation data suggest that climate change provides a parsimonious explanation for the early Holocene distribution and later expansion of blanket bogs in the UK, and it is not necessary to invoke anthropogenic activity as a driver of this major landscape change.

Climate-driven expansion of blanket bogs in Britain during the Holocene

Blanket bog occupies approximately 6% of the area of the UK today. The Holocene expansion of this hyperoceanic biome has previously been explained as a consequence of Neolithic forest clearance. However, the present distribution of blanket bog in Great Britain can be predicted accurately with a simple model (PeatStash) based on summer temperature and moisture index thresholds, and the same model correctly predicts the highly disjunct distribution of blanket bog worldwide. This finding suggests that climate, rather than land-use history, controls blanket-bog distribution in the UK and everywhere else. We set out to test this hypothesis for blanket bogs in the UK using bioclimate envelope modelling compared with a database of peat initiation age estimates. We used both pollen-based reconstructions and climate model simulations of climate changes between the mid-Holocene (6000 yr BP, 6 ka) and modern climate to drive PeatStash and predict areas of blanket bog. We compiled data on the timing of blanketbog initiation, based on 228 age determinations at sites where peat directly overlies mineral soil. The model predicts that large areas of northern Britain would have had blanket bog by 6000 yr BP, and the area suitable for peat growth extended to the south after this time. A similar pattern is shown by the basal peat ages and new blanket bog appeared over a larger area during the late Holocene, the greatest expansion being in Ireland,Wales, and southwest England, as the model predicts. The expansion was driven by a summer cooling of about 2 °C, shown by both pollen-based reconstructions and climate models. The data show early Holocene (pre- Neolithic) blanket-bog initiation at over half of the sites in the core areas of Scotland and northern England. The temporal patterns and concurrence of the bioclimate model predictions and initiation data suggest that climate change provides a parsimonious explanation for the early Holocene distribution and later expansion of blanket bogs in the UK, and it is not necessary to invoke anthropogenic activity as a driver of this major landscape change.

Zoneamento agroclimático da cultura da mangueira no Estado do Piauí

O presente trabalho teve como objetivo realizar o zoneamento agroclimático da cultura da mangueira no Estado do Piauí. Foram utilizados dados médios anuais de precipitação e temperatura do ar, de 15 municípios do Piauí, representativos das principais regiões do Estado para a elaboração do balanço hídrico e a obtenção do Índice de Umidade (Im). Foram adotadas as seguintes faixas de Índice de Umidade (Im): - Aptidão plena A, Im < -40; - Aptidão plena B, -40 < Im <-20. O critério utilizado na divisão do Estado, em zonas térmicas, baseou-se nas normais de temperaturas médias do mês mais quente (Tq) para cada local. Assim sendo, as faixas A e B, com aptidão plena, do ponto de vista hídrico, foram subdivididas em duas subzonas: Aptidão plena A1: (Tq < 29 ºC), Aptidão plena A2: (29 ºC < Tq <31 ºC) e Aptidão plena B1: (Tq < 29 ºC), Aptidão plena B2: (29 ºC < Tq <31 ºC), para atender ao critério térmico. Com base nas cartas de Tq e Im, foram definidos os limites para as diferentes zonas de aptidão climáticas para o cultivo de manga. À luz dos critérios utilizados e com base na literatura consultada, o Estado do Piauí não apresenta nenhuma restrição climática para o cultivo comercial da mangueira.