Forecast Models for Urban Dynamics (Kathmandu Valley)

Authors

  • Laxman Basnet Department of Mathematics, Kirtipur, Nepal

DOI:

https://doi.org/10.3126/jacem.v6i0.38318

Keywords:

global techniques, log-linear transformation, urban complex

Abstract

The climatic signature of global warming is both local and global. The forcing by increasing greenhouse gases is global, so there is clearly a global component to the climatic signature. Moreover, the damaging impacts of global warming are manifesting themselves around the world in the form of extreme weather events like storms, tornadoes, floods and droughts, all of which have been escalating in frequency and intensity. Furthermore, it is a well-known fact that there is high degree of uncertainty surrounding projections of basic climate variables, such as temperature and precipitation. However, numerous authors have explored many of these effects individually and have begun exploring the interactions between climate change-induced impacts in different sectors of urban activities. Therefore, it is safe to say that an attempt to conduct a definitive, comprehensive analysis of all the potential impacts of climate change on the urban structure is premature at present. This communication attempts to examine the trends in maximum monthly urban temperature fluctuations. Analysis reveals increasing trends in urban temperature fluctuations showing effect of Kathmandu industrializations. Forecast models also suggest future scenario with respect to occurrence of extreme temperature. The analysis carried out in this work would be useful for urban planners for sustainable future development, economists and environmentalists etc.

Let C be an urban complex (such as a city with its entire infrastructure) and UC the urban system associated with C. We shall consider UC = UC (PC, SC, EC) where, PC is the set of physical indicators like population, land, population density and infrastructure like developed and undeveloped areas etc. SC is the set of socio-economic factors and EC is the set of environmental indicators like pollution and climatic variability (land and sea surface temperature, frequency of hazards like cyclones etc.). All these sets are finite.  The urban development can refer to both growth and decline. If we represent the growth of an urban complex by GC, then it will be the rate of increase of UC with respect to time so that GC = .  G is thus a system resulting from the complex dynamical interactions of P, S, and E in a certain time interval. Furthermore, P, S, and E which are called generator functions or the complexity of the system U involve finite variables depending on time. On occasions these may be random making the situation complex. The urban growth G can be considered a system itself depending on P, S, and E. Thus, we can consider G = G (P, S, E). In the following we shall study the urban growth G in the perspective of the variability in P and E only so that G = G (P, E). We shall also study the interactions of P and E. The generator function P and E are themselves subsystems of the system G.  

We begin by reviewing the global and local trends of urban growth and then separately study the components P and E of urban growth G. The component P of G corresponds to the physical growth of the urban complex C under consideration i.e. the growth of urban population and area. As a consequence of urban growth, a settlement comprising of small population limited to a small area can be gradually transformed into a town, city and megacity.  The process usually gets impetus from the massive population movements from rural to urban areas. The urban growth phenomenon associated with a particular urban complex at first seems to be very local but in the perspective of international migrations, globalization of socio-economic activities and environmental issues like global warming, it simultaneously translates into global one. The component E of G corresponds to the environmental issues associated with an urban complex C. There are a number of issues requiring attention and those which are particularly related to climatic variability. Climatic variability may be natural or arising from natural causes or may be anthropogenic arising due to non-friendly attitude of humans towards environment. There are various strands of the study of the links between urban growth and climatic variability. But we  restrict ourselves to the study of the temperature variations associated with urban mega-complexes. It is interesting to study the impact of these temperature variations on the urban population. In this regard we have given stress to the possibility of increase in the number of tropical cyclones which can create hazards in the coastal populations.  This is why we have selected the mega-city of Kathmandu to study as a test case.

 The following points are sufficient to gauge the importance of our selection. 

  1. As regards population and population density Kathmandu is among one of the top of the world
  2. It has a very high population growth rate
  3. Though it is considered to be a planned city but problems related to its unplanned part which consists of slums seems to overwhelm those of the planned part.
  4. It is considered a city having a moderate climate as compared to the other parts of the country. But now spells of intense heat can be easily observed in the records of past few decades.  
  5. It is the economic hub of Nepal as it is Kingdom of Nepal.

The situation arising from the very high population growth rate and the increasing number of Kathmandu is clearly hazardous and it will be no exaggeration if we consider high level of population concentration pollution itself. We are of the opinion that the enhanced level of anthropogenic activities is increasing the environmental burden. So we shall stress upon (d) as well and will see that how the extreme temperatures are behaving and whether these extremes are under the influence of human activities or not.  

In the perspective of Kathmandu the urban growth G will be a system G = G (P, S, E) with P, S and E as its subsystems where P = P (p (t), A (t)) and E = E (T1 (t), Tss (t)), p, A, Tl, Tss and t  represent the population, area, land temperature, sea surface temperature and time  respectively. The subsystem P can further be considered asP = Ps(p (t), A (t)) + Pus (p (t), A (t)) where Ps and Pus are the settled and unsettled parts respectively of an urban complex. P and E and in turn G can be considered as physical processes. The subsystem S because of its prime importance has worth for a separate study and will be considered somewhere else.    

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Published

2021-07-08

How to Cite

Basnet, L. (2021). Forecast Models for Urban Dynamics (Kathmandu Valley). Journal of Advanced College of Engineering and Management, 6, 57–60. https://doi.org/10.3126/jacem.v6i0.38318

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