Climate Change Impact on the Water Resources of the Limpopo Basin: Simulations of a Coupled GCM and Hybrid Atmospheric-Terrestrial Water Balance (HATWAB) Model

Climate Change Impact on the Water Resources of the Limpopo Basin: Simulations of a Coupled GCM and Hybrid Atmospheric-Terrestrial Water Balance (HATWAB) Model

Berhanu F. Alemaw (University of Botswana, Botswana) and Thebeyame Ronald Chaoka (University of Botswana, Botswana)
Copyright: © 2018 |Pages: 24
DOI: 10.4018/978-1-5225-3440-2.ch012
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Abstract

This chapter aims to evaluate the impacts of climate change on both hydrologic regimes and water resources of the Limpopo River Basin in southern Africa. Water resources availability in the basin, in terms of, seasonal and annual runoff (R), soil moisture (S) and actual evapotranspiration (Ea) is simulated and evaluated using the hydrological model, HATWAB. These water balances were computed from precipitation (P), potential evapotranspiration (Ep) and other variables that govern the soil-water-vegetation-atmospheric processes at 9.2km latitude/ longitude gird cells covering the basin. The 1961-90 simulated mean annual runoff reveals mixed patterns of high and low runoff across the region. Although relatively small changes in runoff simulations are prevalent among the three climate change scenarios, generally the OSU simulated relatively high runoff compared to the UKTR and HADCM2 GCMs.
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Introduction

The UN expert panel on climate change has concluded that high rates of CO2 emission into the atmosphere will induce global warming. The effects will be felt worldwide, but the regional and local implications are uncertain. Major effects are expected to be increases in temperature and extreme weather events, along with sea-level rise. Appendix presents some of terminology as used in the climate research community. The worst consequences of global climate change are expected in the developing countries which have little resources to mitigate the effects of extreme climatic events such as storms, floods and droughts.

Alternation in the availability of freshwater resources, including changes in stream flows and soil moisture is one of the most important regional consequences of global climatic changes. Since the current generation of climate models are well suited to the evaluation of detailed water resource problems, a variety of other impact assessment techniques and tools must be developed and tested. The hydrologic effect of climatic change is a subject of much interest in recent environmental research. Almost exclusively, conceptual type hydrological models have been used to study the impact of climate change on basin hydrology (Miller and Russell 1992; Schaake and Chunzhen 1989; Middelkoop et al. 2001).

In studying the impact of climate change on water resources at a catchment or regional scales, various hydrological models at varied temporal scale have been commonly applied, such as the monthly time step regional hydrological models (e.g., Guo et al. 2005), hourly and daily time step models (e.g., Middelkoop et al. 2001) and daily time step model, (e.g. Hulme et al. 1996).

In this study, we undertake hydrological and water resources assessment at relatively low resolution to map local level water availability and hydrological impacts as a result of climate change. Therefore, for this study, HATWAB (Alemaw, 2012), which is a modified version of its predecessor, hydrologic model known as a distributed GIS-based hydrological model (DGHM) for southern Africa, is applied (Alemaw and Chaoka 2003, Alemaw, 1999). It is employed in order to partition regional rainfall and climatic forcing of potential evapotranspiration into surface runoff, evapotranspiration, soil moisture, and other components of the hydrologic cycle. The adopted hydrological model, HATWAB, uses monthly accounting of water balances to model surface water balances and monthly soil moisture. For the latter, we employed a soil moisture accounting technique suggested in Vorosmarty et al. (1989), Alemaw and Chaoka (2003).

The basis of various climate change scenarios adopted by many researchers was founded on the global warming guidelines recommended by the International Panel on Climate Change (IPCC) (IPCC 1995a,b, 1996, 1998, 2000, 2001a,b, 2007). Scenarios of changes of up to 4oC in temperature and changes from 0 to ±20% in mean monthly rainfall have been considered for studying possible climate change impacts on hydrology and water resources (Guo et al. 2005; Panagoulia 1991; Nemec and Schaake 1982). On the other hand, several other researchers such as Hulme and Jones (1989), Hulme et al. (1996), IPCC (1995b) identify scenarios based on physical and statistical reasoning, from past instrumental data, from spatial analogues, and from climate models. These approaches and their limitations are described in Hulme and Jones (1989) and Carter et al. (1993). Among these, the most widely accepted approach involves the use of results from GCM climate change experiments (Arnell 2003; Hulme and Jones 1989), and this approach is adopted in this study.

Key Terms in this Chapter

Vulnerability: Vulnerability is the degree to which a system is susceptible to, or unable to cope with, adverse effects of climate change, including climate variability and extremes. Vulnerability is a function of the character, magnitude, and rate of climate change and variation to which a system is exposed, its sensitivity, and its adaptive capacity.

Emission Scenarios: The IPCC has developed a range of scenarios, IS92a-f, of future greenhouse gas and aerosol precursor emissions based on assumptions concerning population and economic growth, land-use, technological changes, energy availability and fuel mix during the period 1990 to 2100. Through understanding of the global carbon cycle and of atmospheric chemistry, these emissions can be used to project atmospheric concentrations of greenhouse gases and aerosols and the perturbation of natural radiative forcing.

Climate Sensitivity: Sensitivity is the degree to which a system is affected, either adversely or beneficially, by climate-related stimuli. Climate-related stimuli encompass all the elements of climate change, including mean climate characteristics, climate variability, and the frequency and magnitude of extremes. The effect may be direct (e.g., a change in crop yield in response to a change in the mean, range, or variability of temperature) or indirect (e.g., damages caused by an increase in the frequency of coastal flooding due to sea-level rise). The term climate sensitivity refers to the steady-state increase in the global annual mean surface air temperature associated with a given global-mean radiative forcing. It is common practise to use CO2 doubling as a benchmark for comparing GCM climate sensitivities. Thus in practise the climate sensitivity may be defined as the change in global-mean temperature that would ultimately be reached following a doubling of CO2 concentration in the atmosphere (e.g. from 275 ppmv to 550 ppmv). The IPCC has always reported the likely range for this quantity to be between 1.5º and 4.5ºC, with a 'mid-range' estimate of 2.5ºC. Each GCM has different climate sensitivity, depending on the representation of various feedback processes in the model, including water vapour. It is generally assumed that the climate sensitivity of a model is approximately constant over the range of forcings expected for the next century. The climate sensitivity of a model is also largely independent (±10%) of the specific combination of different forcing factors (solar, aerosols, CO2, CH4, etc.) that produce a given global-mean forcing. The range of climate sensitivities in the DDC models is from about 2.5ºC to 4.0ºC (IPCC DDC).

Climate Projection: A climate projection refers to a description of the response of the climate system to a scenario of greenhouse gas and aerosol emissions, as simulated by a climate model. According to the IPCC climate projections alone can rarely provide sufficient information to estimate future impacts of climate change. Model outputs commonly have to be manipulated and combined with observed climate data to be usable as inputs to impact models. A range of uncertainties affects projections of climate change. Uncertainty in projected climate change arises from three main sources; uncertainty in forcing scenarios, uncertainty in modelled responses to given forcing scenarios, and uncertainty due to missing or misrepresented physical processes in models.

Adaptive Capacity: Adaptive capacity is the ability of a system to adjust to climate change (including climate variability and extremes) to moderate potential damages, to take advantage of opportunities, or to cope with the consequences.

Baseline Climate: A climate change scenario is defined with respect to a climatological baseline, which determines a reference point for the projected climate changes. Climate scenarios that are developed for impacts applications usually require that some estimate of climate change be combined with baseline observational climate data. Thus, the demand for more complete and sophisticated observational data sets of climate has grown in recent years. The important considerations for the baseline include the time period adopted as well as the spatial and temporal resolution of the baseline data. IPCC have usually taken the year '1990' as the baseline year for the presentation of emissions scenarios and for calculations of future climate and sea-level change. '1990' has also been adopted by the United Nations Framework Convention on Climate Change (UNFCCC) in their definition of emissions reductions targets. Choosing a single year as a baseline is appropriate for some applications, but not for climate change studies. Due to climate variability a single year may be unusually warm, cold, dry or wet and thus will not make a useful reference point for measuring climate change. It is more common to use the average climate over a 30-year period to define the baseline climate. A 30-year climatic average smoothes out many of the year-to-year variations in the climate. In addition, the individual 30 years of such a period captures much of the interannual and short time-scale variability of climate that may be relevant for an impact application. The IPCC Data Distribution Centre (IPCC DDC) suggests the period 1961-90 to be used as the baseline period. This period has generally good observed data and it represents the recent climate to which many present-day human or natural systems are likely to be reasonably well adapted. The period also ends in 1990, the year adopted by many IPCC and UN FCCC applications.

Climate Scenario: A climate scenario refers to a plausible future climate that has been constructed for explicit use in investigating the potential consequences of anthropogenic climate change. Such climate scenarios should represent future conditions that account for both human-induced climate change and natural climate variability ( IPCC 2001a ).

SRES Scenarios: In 1996, the IPCC began the development of a new set of emissions scenarios, effectively to update and replace the IS92 scenarios. The approved new set of scenarios is described in the IPCC Special Report on Emission Scenarios (SRES) ( IPCC 2000 ). Four different narrative storylines (A1, A2, B1, B2) were developed to describe consistently the relationships between emission driving forces and their evolution and to add context for the scenario quantification. Each emission scenario represents a specific quantification of one of the four storylines, and all scenarios based on the same storyline constitute a scenario “family”. The resulting set of forty scenarios (thirty-five of which contain data on the full range of gases required for climate modelling) cover a wide range of the main demographic, economic and technological driving forces of future greenhouse gas and sulphur emissions. None of the emission scenarios explicitly assume implementation of the UN FCCC or the emissions targets of the Kyoto Protocol. However, greenhouse gas emissions are directly affected by implementation of policies designed for a wide range of other purposes. Furthermore, government policies can, to varying degrees, influence the greenhouse gas emission drivers, and this influence is broadly reflected in the storylines and resulting scenarios. Graphical description of SRES Scenarios is depicted in Figure 8 .

Climate Change Scenario: A climate change scenario is different from a climate scenario, even though the term sometimes is used in the scientific literature to denote a plausible future climate. However, this term should strictly refer to a representation of the difference between some plausible future climate and the current or control climate (usually as represented in a climate model) (IPCC 2001 AU27: The citation "IPCC 2001" matches multiple references. Please add letters (e.g. "Smith 2000a"), or additional authors to the citation, to uniquely match references and citations. ). A climate change scenario can be viewed as an interim step toward constructing a climate scenario. Usually a climate scenario requires combining the climate change scenario with a description of the current climate as represented by climate observations.

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