Macroscale hydrological modelling approach for study of large scale hydrologic impacts under climate change in Indian river basins

Hydrol. Earth Syst. Sci.

Arheimer

2015

100

101

Abstract. The scientific initiative Prediction in UngaugedBasins (PUB) (2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012) by the IAHS) put considerable effort into improving the reliability of hydrological models to predict flow response in ungauged rivers. PUB's collective experience advanced hydrologic science and defined guidelines to make predictions in catchments without observed runoff data. At present, there is a raised interest in applying catchment models to large domains and large data samples in a multi-basin manner, to explore emerging spatial patterns or learn from comparative hydrology. However, such modelling involves additional sources of uncertainties caused by the inconsistency between input data sets, i.e. particularly regional and global databases. This may lead to inaccurate model parameterisation and erroneous process understanding. In order to bridge the gap between the best practices for flow predictions in single catchments and multi-basins at the large scale, we present a further developed and slightly modified version of the recommended best practices for PUB by Takeuchi et al. (2013). By using examples from a recent HYPE (Hydrological Predictions for the Environment) hydrological model set-up across 6000 subbasins for the Indian subcontinent, named India-HYPE v1.0, we explore the PUB recommendations, identify challenges and recommend ways to overcome them. We describe the work process related to (a) errors and inconsistencies in global databases, unknown human impacts, and poor data quality; (b) robust approaches to identify model parameters using a stepwise calibration approach, remote sensing data, expert knowledge, and catchment similarities; and (c) evaluation based on flow signatures and performance metrics, using both multiple criteria and multiple variables, and independent gauges for "blind tests". The results show that despite the strong physiographical gradient over the subcontinent, a single model can describe the spatial variability in dominant hydrological processes at the catchment scale. In addition, spatial model deficiencies are used to identify potential improvements of the model concept. Eventually, through simultaneous calibration using numerous gauges, the median Kling-Gupta efficiency for river flow increased from 0.14 to 0.64. We finally demonstrate the potential of multi-basin modelling for comparative hydrology using PUB, by grouping the 6000 subbasins based on similarities in flow signatures to gain insights into the spatial patterns of flow generating processes at the large scale.

Section: Performance In India-hype V10 and Future Model Refinementsmentioning

confidence: 86%

Section: Introductionmentioning

confidence: 99%

Large-scale hydrological modelling by using modified PUB recommendations: the India-HYPE case

Hydrol. Earth Syst. Sci.

Arheimer

2015

100

101

“…This conclusion is consistent with our results. Change in runoff in the Krishna river is ambiguous with studies showing both a future increase [32,69], as here, and a decrease [31].…”

Section: Enhancing Understanding Of Future Climate Change Impactsmentioning

confidence: 94%

“…Conventionally, hydrologic impacts are investigated on small (~0.1-10 2 km 2 ) or medium-sized basins (~10 2 -10 3 km 2 ); however, current needs require assessment on larger areas and river basins, which requires the use of large scale hydrological models [31,32]. This type of modelling has the potential to encompass many river basins, cross-regional, and international boundaries and represents a number of different geophysical and climatic zones [33].…”

Section: Introductionmentioning

confidence: 99%

Multi-Basin Modelling of Future Hydrological Fluxes in the Indian Subcontinent

Olsson

Bosshard

et al. 2016

Water

Abstract:The impact of climate change on the hydro-climatology of the Indian subcontinent is investigated by comparing statistics of current and projected future fluxes resulting from three RCP scenarios (RCP2.6, RCP4.5, and RCP8.5). Climate projections from the CORDEX-South Asia framework have been bias-corrected using the Distribution-Based Scaling (DBS) method and used to force the HYPE hydrological model to generate projections of evapotranspiration, runoff, soil moisture deficit, snow depth, and applied irrigation water to soil. We also assess the changes in the annual cycles in three major rivers located in different hydro-climatic regions. Results show that conclusions can be influenced by uncertainty in the RCP scenarios. Future scenarios project a gradual increase in temperature (up to 7˝C on average), whilst changes (both increase and decrease) in the long-term average precipitation and evapotranspiration are more severe at the end of the century. The potential change (increase and decrease) in runoff could reach 100% depending on the region and time horizon. Analysis of annual cycles for three selected regions showed that changes in discharge and evapotranspiration due to climate change vary between seasons, whereas the magnitude of change is dependent on the region's hydro-climatic gradient. Irrigation needs and the snow depth in the Himalayas are also affected.

“…The region already faces water stresses due to increase in population, urbanisation, and increasing demands in the agriculture, industrial and hydropower sectors. Climate change is expected to further aggravate water shortage (Gosain et al, 2011;Raje et al, 2014). The State of Rajasthan, in the western part of the country, is severely deficient in water resources, whereas changes are being already experienced in its climate indicating an increase in annual mean surface temperature of 2-4 °C (GoR, 2011).…”

Section: Introductionmentioning

confidence: 99%

Assessment of the climate change impacts on the water resources of the Luni region, India

Olsson²,

Sharma³

et al. 2015

Global NEST Journal

Climate change is expected to have a strong impact on water resources at the local, regional and global scales. In this study, the impact of climate change on the hydro-climatology of the Luni region, India, is investigated by comparing statistics of current and projected future fluxes resulting from three representative concentration pathways (RCP2.6, RCP4.5, and RCP8.5). The use of different scenarios allows for the estimation of uncertainty of future impacts. The projections are based on the CORDEXSouth Asia framework and are bias-corrected using the DBS method before being entered into the HYPE (HYdrological Predictions for the Environment) hydrological model to generate predictions of runoff, evapotranspiration, soil moisture deficit, and applied irrigation water to soil. Overall, the high uncertainty in the climate projections is propagated in the impact model, and as a result the spatiotemporal distribution of change is subject to the climate change scenario. In general, for all scenarios, results show a -20 to +20% change in the long-term average precipitation and evapotranspiration, whereas more pronounced impacts are expected for runoff (-40 to +40% change). Climate change can also affect other hydro-climatic components, however, at a lower impact. Finally, the flow dynamics in the Luni River are substantially affected in terms of shape and magnitude.