Water Cycle Changes

This chapter assesses multiple lines of evidence to evaluate past, present and future changes in the global water cycle. It complements material in Chapters 2, 3 and 4 on observed and projected changes in the water cycle, and Chapters 10 and 11 on regional climate change and extreme events. The assessment includes the physical basis for water cycle changes, observed changes in the water cycle and attribution of their causes, future projections and related key uncertainties, and the potential for abrupt change. Paleoclimate evidence, observations, reanalyses and global and regional model simulations are considered. The assessment shows widespread, nonuniform human-caused alterations of the water cycle, which have been obscured by a competition between different drivers across the 20th century and that will be increasingly dominated by greenhouse gas forcing at the global scale

Quantifying Uncertainties of Multi-Model Climate Change Scenarios on the Water Crisis in Malaysia

Malaysia has a relatively limited capacity to deal with the effects of climate change while being one of the most vulnerable nations to its effects. As a developing country, the lack of a consistent temporal and spatial data source has always been an issue, and the region is also considered data-scarce. This study’s primary goal is to evaluate the effects of climate change on Malaysia’s water resources, particularly the Selangor River Basin (SRB). Instead of using a single source input dataset, cross-combined datasets from multiple sources were used in order to optimise the hydrological model. Five input variables, including precipitation, temperature, solar radiation, relative humidity, and wind speed, were used to define seven scenarios using single and cross- combined method. To improve the hydrological model multi-site calibration method is employed. Finally, climate change prediction data from several Global Climate Models (GCMs) is utilised to assess the effects of climate change on SRB water supplies. The CFSR and CMADS global reanalysis datasets show a highly significant relationship on precipitation, with an r-value of 0.81 for both datasets. However, for temperature data, CMADS surpasses CFSR on maximum and minimum temperatures, with 0.6 and 0.7, respectively. In the SWAT model, most of the scenarios achieved a ‘good’ performance range on the calibration and validation processes. However, SWAT model with CFSR as input data achieved an ‘unsatisfactory’ range with R2 of 0.35, NSE of 0.16, Pbias of 0.00, KGE of 0.50, and RSR of 0.92. For a cross-combined approach, the result shows the combination of the observed and CMADS datasets performed better than the combination of the observed and CFSR datasets. The sequential technique outperformed the simultaneous and basin-by-basin techniques by achieving ‘satisfactory’ range at all outlets. The SRB’s assessment of climate change predicted an increase in precipitation and temperature from 2030 to 2050. Climate data from ‘ensemble average’ realisation predicted SRB would receive a huge amount of precipitation in November and April every year, and high temperatures from February to June. Additionally, a few sub-basins are expected to have water availability greater than 5 m3/s for three consecutive years

Water resources availability in the Caledon River basin : past, present and future

The Caledon River Basin is located on one of the most water-scarce region on the African continent. The water resources of the Caledon River Basin play a pivotal role in socio-economic activities in both Lesotho and South Africa but the basin experiences recurrent severe droughts and frequent water shortages. The Caledon River is mostly used for commercial and subsistence agriculture, industrial and domestic supply. The resources are also important beyond the basin’s boundaries as the water is transferred to the nearby Modder River. The Caledon River is also a significant tributary to the Orange-Senqu Basin, which is shared by five southern African countries. However, the water resources in the basin are under continuous threat as a result of rapidly growing population, economic growth as well as changing climate, amongst others. It is therefore important that the hydrological regime and water resources of the basin are thoroughly evaluated and assessed so that they can be sustainably managed and utilised for maximum economic benefits. Climate change has been identified by the international community as one of the most prominent threats to peace, food security and livelihood and southern Africa as among the most vulnerable regions of the world. Water resources are perceived as a natural resource which will be affected the most by the changing climate conditions. Global warming is expected to bring more severe, prolonged droughts and exacerbate water shortages in this region. The current study is mainly focused on investigating the impacts of climate change on the water resources of the Caledon River Basin. The main objectives of the current study included assessing the past and current hydrological characteristics of the Caledon River Basin under current state of the physical environment, observed climate conditions and estimated water use; detecting any changes in the future rainfall and evaporative demands relative to present conditions and evaluating the impacts of climate on the basin’s hydrological regime and water resources availability for the future climate scenario, 2046-2065. To achieve these objectives the study used observed hydrological, meteorological data sets and the basin’s physical characteristics to establish parameters of the Pitman and WEAP hydrological models. Hydrological modelling is an integral part of hydrological investigations and evaluations. The various sources of uncertainties in the outputs of the climate and hydrological models were identified and quantified, as an integral part of the whole exercise. The 2-step approach of the uncertainty version of the model was used to estimate a range of parameters yielding behavioural natural flow ensembles. This approach uses the regional and local hydrological signals to constrain the model parameter ranges. The estimated parameters were also employed to guide the calibration process of the Water Evaluation And Planning (WEAP) model. The two models incorporated the estimated water uses within the basin to establish the present day flow simulations and they were found to sufficiently simulate the present day flows, as compared to the observed flows. There is an indication therefore, that WEAP can be successfully applied in other regions for hydrological investigations. Possible changes in future climate regime of the basin were evaluated by analysing downscaled temperature and rainfall outputs from a set of 9 climate models. The predictions are based on the A2 greenhouse gases emission scenario which assumes a continuous increase in emission rates. While the climate models agree that temperature, and hence, evapotranspiration will increase in the future, they demonstrate significant disagreement on whether rainfall will decrease or increase and by how much. The disagreement of the GCMs on projected future rainfall constitutes a major uncertainty in the prediction of water resources availability of the basin. This is to the extent that according to 7 out of 9 climate models used, the stream flow in four sub-basins (D21E, D22B, D23D and D23F) in the Caledon River Basin is projected to decrease below the present day flows, while two models (IPSL and MIUB) consistently project enhanced water resource availability in the basin in the future. The differences in the GCM projections highlight the margin of uncertainty involved predicting the future status of water resources in the basin. Such uncertainty should not be ignored and these results can be useful in aiding decision-makers to develop policies that are robust and that encompass all possibilities. In an attempt to reduce the known uncertainties, the study recommends upgrading of the hydrological monitoring network within the Caledon River Basin to facilitate improved hydrological evaluation and management. It also suggests the use of updated climate change data from the newest generation climate models, as well as integrating the findings of the current research into water resources decision making process

Investigating uncertainty in global hydrology modelling

As projections of future climate raise concerns over water availability and extreme hydrological events, global hydrology models are increasingly being employed to better understand our global water resources and how they may be affected by climate change. Being a relatively recent development in hydrological science, global hydrology modelling has not yet undergone the same level of assessment and evaluation as catchment scale hydrology modelling. Until now, global hydrology models have presented just one deterministic model output for use in scientific research. Recently, multi-model ensembles have compared these outputs for different global models, but this has been done prematurely as the uncertainties within individual models have yet to be understood. This study demonstrates a rigorous uncertainty investigation of the 123 parameters within the Mac-PDM global hydrology model over 21 global river catchments. Mac-PDM was selected for its relative simplicity amongst global hydrology models, and its suitability for application using high performance computer clusters. A new version of the model, Mac-PDM.14 is provided, with updated soil and vegetation classifications. This model is then subjected to a 100,000 parameter realisation Generalised Likelihood Uncertainty Estimation (GLUE) experiment, requiring 40 days of high performance computing time, and outputting over 2Tb of data. The top performing model parameterisation from this experiment provides an annual average error of 47% when compared to observed records, a 45% improvement over the previous version of the model, Mac-PDM.09. Given the computational expense of such an experiment, smaller sample sizes of parameter realisations are explored. Whilst the top performing parameterisation in a sample size as small as 1,000 can perform almost as well as that from 100,000 parameterisations, the number of good parameterisations is fewer, and the range of model uncertainty may therefore be significantly underestimated. Mac-PDM.14 is shown to have a lower mean absolute relative error than all models involved in both the Water and Global Change (WATCH) project and the Inter-Sectoral Impacts Model Intercomparison Project (ISI-MIP). Parameter uncertainty is compared to model uncertainty, and the uncertainty range between the models within the WATCH and ISI-MIP projects is comparable to the parameter uncertainty within Mac-PDM.14. Catchment specific calibrations of the global hydrology model are explored, and it is demonstrated that the model performance is improved by 22 to 92%, for the Niger and the Yangtze respectively, with catchment specific parameter values over a global calibration. Approximate Bayesian Rejection is applied to explore the catchment specific parameter values that result in good parameter performance. Few trends can be identified from this analysis, which suggests that Mac-PDM may be over-parameterised. Catchment specific calibrations in both high latitude and arid to semi-arid regions show significant improvement over global calibration, which indicate a deficiency in model structure; the addition of a glacier component to Mac-PDM is recommended. Model calibrations are validated using the ISI-MIP forcing dataset, and the best model performance gives an error of 44%. This is a betterment on the performance with the WATCH forcing data used in calibration, and so implies that models not need to be recalibrated every time new forcing datasets are employed. This research highlights that the performance of global hydrology models can be significantly improved by running a parameter uncertainty assessment, and that in catchment scale studies, catchment specific calibration should be carefully considered. Furthermore, the uncertainty within individual global hydrology models is an important consideration that should not be overlooked as these models are increasingly included in ensembles and interdisciplinary studies

Investigating uncertainty in global hydrology modelling

As projections of future climate raise concerns over water availability and extreme hydrological events, global hydrology models are increasingly being employed to better understand our global water resources and how they may be affected by climate change. Being a relatively recent development in hydrological science, global hydrology modelling has not yet undergone the same level of assessment and evaluation as catchment scale hydrology modelling. Until now, global hydrology models have presented just one deterministic model output for use in scientific research. Recently, multi-model ensembles have compared these outputs for different global models, but this has been done prematurely as the uncertainties within individual models have yet to be understood. This study demonstrates a rigorous uncertainty investigation of the 123 parameters within the Mac-PDM global hydrology model over 21 global river catchments. Mac-PDM was selected for its relative simplicity amongst global hydrology models, and its suitability for application using high performance computer clusters. A new version of the model, Mac-PDM.14 is provided, with updated soil and vegetation classifications. This model is then subjected to a 100,000 parameter realisation Generalised Likelihood Uncertainty Estimation (GLUE) experiment, requiring 40 days of high performance computing time, and outputting over 2Tb of data. The top performing model parameterisation from this experiment provides an annual average error of 47% when compared to observed records, a 45% improvement over the previous version of the model, Mac-PDM.09. Given the computational expense of such an experiment, smaller sample sizes of parameter realisations are explored. Whilst the top performing parameterisation in a sample size as small as 1,000 can perform almost as well as that from 100,000 parameterisations, the number of good parameterisations is fewer, and the range of model uncertainty may therefore be significantly underestimated. Mac-PDM.14 is shown to have a lower mean absolute relative error than all models involved in both the Water and Global Change (WATCH) project and the Inter-Sectoral Impacts Model Intercomparison Project (ISI-MIP). Parameter uncertainty is compared to model uncertainty, and the uncertainty range between the models within the WATCH and ISI-MIP projects is comparable to the parameter uncertainty within Mac-PDM.14. Catchment specific calibrations of the global hydrology model are explored, and it is demonstrated that the model performance is improved by 22 to 92%, for the Niger and the Yangtze respectively, with catchment specific parameter values over a global calibration. Approximate Bayesian Rejection is applied to explore the catchment specific parameter values that result in good parameter performance. Few trends can be identified from this analysis, which suggests that Mac-PDM may be over-parameterised. Catchment specific calibrations in both high latitude and arid to semi-arid regions show significant improvement over global calibration, which indicate a deficiency in model structure; the addition of a glacier component to Mac-PDM is recommended. Model calibrations are validated using the ISI-MIP forcing dataset, and the best model performance gives an error of 44%. This is a betterment on the performance with the WATCH forcing data used in calibration, and so implies that models not need to be recalibrated every time new forcing datasets are employed. This research highlights that the performance of global hydrology models can be significantly improved by running a parameter uncertainty assessment, and that in catchment scale studies, catchment specific calibration should be carefully considered. Furthermore, the uncertainty within individual global hydrology models is an important consideration that should not be overlooked as these models are increasingly included in ensembles and interdisciplinary studies

The First Global Integrated Marine Assessment: World Ocean Assessment I

We used satellite-derived sea-surface-temperature (SST) data along with in-situ data collected along a meridional transect between 18.85 and 20.25°N along 69.2°E to describe the evolution of an SST filament and front during 25 November to 1 December in the northeastern Arabian Sea (NEAS). Both features were ∼ 100 km long, lasted about a week and were associated with weak temperature gradients (∼ 0.07°C km⁻¹). The in-situ data were collected first using a suite of surface sensors during a north–south mapping of this transect and showed the existence of a chlorophyll maximum within the filament. This surface data acquisition was followed by a high-resolution south–north CTD (conductivity–temperature–depth) sampling along the transect. In the two days that elapsed between the two in-situ measurements, the filament had shrunk in size and moved northward. In general, the current direction was northwestward and advected these mesoscale features. The CTD data also showed an SST front towards the northern end of the transect. In both these features, the chlorophyll concentration was higher than in the surrounding waters. The temperature and salinity data from the CTD suggest upward mixing or pumping of water from the base of the mixed layer, where a chlorophyll maximum was present, into the mixed layer that was about 60 m thick. A striking diurnal cycle was evident in the chlorophyll concentration, with higher values tending to occur closer to the surface during the night. The in-situ data from both surface sensors and CTD, and so also satellite-derived chlorophyll data, showed higher chlorophyll concentration, particularly at sub-surface levels, between the filament and the front, but there was no corresponding signature in the temperature and salinity data. Analysis of the SST fronts in the satellite data shows that fronts weaker than those associated with the filament and the front had crossed the transect in this region a day or two preceding the sampling of the front