Analyzing climate change impacts on water resources under uncertainty using an integrated simulation-optimization approach

Zhuang, Xiaowen; Li, Y. P.; Nie, S.; Fan, Yurui; Huang, Guohe

doi:10.1016/j.jhydrol.2017.11.016

Cited by 53 publications

(20 citation statements)

References 37 publications

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“…Improvement of conceptual rainfall‐runoff models so that they can defensibly be applied in climate change impact studies is one of the most pressing issues in hydrology today. Climate change impact studies inform policy in areas as diverse as water supply (Flörke et al, ; Zhuang et al, ), flood impacts (Iqbal et al, ; Zhou et al, ), ecosystem services (Mahmoud & Gan, ), environmental flow requirements (Cui et al, ), food production (Balkovič et al, ), hydroelectricity (de Jong et al, ), and sociological and indigenous impacts (Emanuel, ; Xue et al, ). In many such studies, rainfall‐runoff models form a vital link, translating projected climatic and weather conditions into river flow and available water.…”

Section: Introductionmentioning

confidence: 99%

Many Commonly Used Rainfall‐Runoff Models Lack Long, Slow Dynamics: Implications for Runoff Projections

Fowler

Knoben

Peel

et al. 2020

Water Resources Research

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Evidence suggests that catchment state variables such as groundwater can exhibit multiyear trends. This means that their state may reflect not only recent climatic conditions but also climatic conditions in past years or even decades. Here we demonstrate that five commonly used conceptual "bucket" rainfall-runoff models are unable to replicate multiyear trends exhibited by natural systems during the "Millennium Drought" in south-east Australia. This causes an inability to extrapolate to different climatic conditions, leading to poor performance in split sample tests. Simulations are examined from five models applied in 38 catchments, then compared with groundwater data from 19 bores and Gravity Recovery and Climate Experiment data for two geographic regions. Whereas the groundwater and Gravity Recovery and Climate Experiment data decrease from high to low values gradually over the duration of the 13-year drought, the model storages go from high to low values in a typical seasonal cycle. This is particularly the case in the drier, flatter catchments. Once the drought begins, there is little room for decline in the simulated storage, because the model "buckets" are already "emptying" on a seasonal basis. Since the effects of sustained dry conditions cannot accumulate within these models, we argue that they should not be used for runoff projections in a drying climate. Further research is required to (a) improve conceptual rainfall-runoff models, (b) better understand circumstances in which multiyear trends in state variables occur, and (c) investigate links between these multiyear trends and changes in rainfall-runoff relationships in the context of a changing climate.Plain Language Summary It is common in science to use a mental picture or metaphor that simplifies a complex phenomenon. A common metaphor used for a water supply catchment is that of a leaky bucket. When it rains, the bucket fills up; when it does not rain for a while, the bucket empties due to evaporation and water used by trees; and leaking water is like river flow. Computer models based on variants of this metaphor are common and can provide predictions of how much streamflow might occur under future scenarios. This paper explores limitations of the bucket metaphor and associated models. Recently, during a 13-year drought in Australia, river catchments gradually started to dry up. With each passing year, the depth to groundwater increased gradually as the water used by trees was not replenished by rainfall. We compare this long, slow behavior to that of five commonly used "bucket" models. The models do not show the long, slow drying up-they only show the seasonal ups and downs, and their predictions of streamflow over the drought are poor. This is surprising, and it means we should choose our models carefully and seek out models that can simulate this behavior and its impact on streamflow.

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Section: Introductionmentioning

confidence: 99%

Many Commonly Used Rainfall‐Runoff Models Lack Long, Slow Dynamics: Implications for Runoff Projections

Fowler

Knoben

Peel

et al. 2020

Water Resources Research

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“…The water resources availability has been affected by climate variability in the past decades, which has caused sustainability concerns in many parts of the world [1,2]. Previous studies have reported that climate variability can alter precipitation, evapotranspiration, soil water, and runoff [3][4][5] resulting in freshwater resources redistributing in spatial and temporal dimensions [6,7].…”

Section: Introductionmentioning

confidence: 99%

Impact of Climate Variability on Blue and Green Water Flows in the Erhai Lake Basin of Southwest China

Yuan

Meng

et al. 2019

Water

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The Erhai Lake Basin is a crucial water resource of the Dali prefecture. This research used the soil and water assessment tool (SWAT) and the China Meteorological Assimilation Driving Datasets for the SWAT model (CMADS) to estimate blue and green water flows. Then the spatial and temporal change of blue and green water flows was investigated. With the hypothetical climate change scenarios, the sensitivity of blue and green water flows to precipitation and temperature has also been analyzed. The results showed that: (1) The CMADS reanalysis dataset can capture the observed probability density functions for daily precipitation and temperature. Furthermore, the CMADS performed well in monthly variables simulation with relative bias and absolute bias less than 7% and 0.5 °C for precipitation and temperature, respectively; (2) blue water flow has increased while green water flow has decreased during 2009 to 2016. The spatial distribution of blue water flow was uneven in the Erhai Lake Basin with the blue water flow increased from low altitudes to mountain areas. While the spatial distribution of green water flow was more homogeneous; (3) a 10% increase in precipitation can bring a 20.8% increase in blue water flow with only a 2.5% increase in green water flow at basin scale. When temperature increases by a 1.0 °C, the blue water flow and green water flow changes by −3% and 1.7%, respectively. Blue and green water flows were more sensitive to precipitation in low altitude regions. In contrast, the water flows were more sensitive to temperature in the mountainous area.

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“…Addressing these issues and developing mitigation or adaptation strategies remains a global challenge for climatologists, hydrologists, climate policy and other decision‐makers. Global climate models (GCM) have allowed several aspects of future climate change to be investigated, including glacial recession (Chaturvedi et al ., ), sea level rise and extreme events (Mahmood and Babel, ; Soraisam et al ., ), drought intensification (Ahmadalipour et al ., ), deforestation causing drought and heatwaves (Deo et al ., ; McAlpine et al ., ; Deo et al ., ; McAlpine et al ., ; IPCC, ), water resources (Shen et al ., ; Zhuang et al ., ) and agricultural adaptations (Nguyen‐Huy et al ., ; ; ). Collectively, these studies have adopted physically based approaches to develop a reliable understanding of extreme climate coping strategies to serve in mitigating damage arising from a shifting climate.…”

Section: Introductionmentioning

confidence: 99%

Projected spatial patterns in precipitation and air temperature for China's northwest region derived from high‐resolution regional climate models

Yin

Feng

Deo

et al. 2019

Intl Journal of Climatology

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Derived from realistic global warming scenarios, long‐term projections of spatial patterns in precipitation and temperature in hydrology and climatology can serve to evaluate climate risk, explore sources of renewable energies and allow local‐scale data to inform decisions regarding agricultural, ecosystem, social, recreational and economic activities. Under the CORDEX‐EA project, the precipitation and temperature projections (2020–2045) for the economically and socially important region of Northwestern China were derived from high‐resolution regional climate model (RCM) simulations for RCP 4.5 and 8.5 scenarios, and compared against a historical period or baseline of 1980–2005. Drawing data from four key RCMs [Weather Research and Forecasting (WRF); Regional Spectral Model (RSM); Regional Climate Model version 4.0 (RegCM4); Mesoscale Model version 5 (MM5)], reliable local‐scale projections were generated by applying suitable bias correction that accords with the multivariate bias correction (MBC) approach. To validate this approach and then evaluate climate change impacts, the adjusted precipitation and temperature estimated from bias‐corrected models for the historical period were compared to the observed data. The results showed that the simulated spatiotemporal distribution of multiyear average precipitation and temperature appear to fit relatively well with the observations, however, the wet‐cold and dry‐warm climate‐related biases were still evident for the high altitude regions. Bias‐corrected future projections of RCMs indicated spatially averaged annual precipitation is expected to rise by about 23.6 and 35.3 mm under the RCP 4.5 and 8.5 scenarios, respectively, while spatially averaged annual temperature is expected to rise by about 1.95 and 1.10°C. Precipitation is projected to increase in all seasons, albeit, more so in the cold season (i.e., boreal winter and spring) than the warm season (i.e., boreal summer and autumn). The annual increase is expected to be about 56.7% under the RCP 4.5 scenario, compared to 67.6% under the RCP 8.5 scenario. The changes of mean temperature in winter are expected to be significant, −37.8% under both RCP scenarios. For spring, the mean temperature will rise by 23.1% (28.9%) under the RCP 4.5 (8.5) scenario. A MBC approach was found to be effective in yielding reliable projected changes in precipitation and temperature variables. The proposed approach has important implications for climatological studies and evaluation of climate change impacts on localized regions, not only in China, but also in other similar areas of the world, where decisions for managing climate risk must be implemented by policy makers, government, industry and stakeholders.

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Analyzing climate change impacts on water resources under uncertainty using an integrated simulation-optimization approach

Cited by 53 publications

References 37 publications

Many Commonly Used Rainfall‐Runoff Models Lack Long, Slow Dynamics: Implications for Runoff Projections

Many Commonly Used Rainfall‐Runoff Models Lack Long, Slow Dynamics: Implications for Runoff Projections

Impact of Climate Variability on Blue and Green Water Flows in the Erhai Lake Basin of Southwest China

Projected spatial patterns in precipitation and air temperature for China's northwest region derived from high‐resolution regional climate models

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