Hydrometeorological feedbacks and changes in water storage and fluxes in northern India

印度北部水文气象反馈以及水储存和通量的变化

• 批准号: NE/I022558/1
• 负责人: Wouter Buytaert
• 金额: $ 50.33万
• 依托单位: Imperial College London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2012
• 资助国家: 英国
• 起止时间: 2012 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FI022558%2F1
• 关键词: Hydrometeorological; feedbacks; changes; water; storage

The Gangetic Plain is a large fertile area at the foot of the Himalayas, covering most of northern India. Home to around 400 million inhabitants, it is one of the most densely inhabited regions in South-East Asia. With its fertile soils, monsoon precipitation and vast groundwater aquifers, the plains have been at the heart of the Indian agricultural revolution. Over the last 4 decades, the introduction of new fertilisers and crops, and the construction of large-scale irrigation systems have been major drivers of socio-economic development in the region. These practices have, however, also led to severe groundwater decline and strains on other water resources. Changing feedbacks of water and energy between the land-surface and atmosphere may have even altered the local climate system. A strong economic development is expected to continue these trends in the near future and future climate change is also expected to increase the pressure on local water resources systems.Identifying the major causes of observed historical changes in water availability and predicting the future impact of local water management strategies under climate change are particularly challenging, yet indispensable for the sustainable management of water resources. For example: assessing the sustainability of groundwater aquifers requires knowledge of global climate influences, but also of the influence of land-use, abstractions and soil moisture dynamics; furthermore, the unprecedented scale of land-use changes and increased irrigation are expected to have influenced local climate through feedbacks of water and energy. In order to unravel and quantify the impact of different drivers of change, a fully integrated analysis of the major water fluxes in the Gangetic Plain is needed.This study would be the first to analyse changes in the main water fluxes and feedbacks of the Gangetic Plain in a fully integrated modelling set-up. The approach will enable the separation of the impact of local and regional land use change from that of global climate drivers. We will develop a custom-built coupled hydrological model for the region using available groundwater and surface water modelling toolboxes. This model will be calibrated and tested using a variety of different sources of information, from local measurements, satellite observations and global climate (reanalysis) datasets. Subsequently, we will run the model with different land-use and water extraction scenarios. This will allow us to quantify the impact of land-use change and extraction on the main hydrological fluxes and water resources.At the same time, the hydrological model will generate high-resolution data about soil moisture changes resulting from historical land-use, as well as different hypothetical scenarios. By feeding these scenarios into a global climate model, we will study the potential feedbacks of large-scale changes in soil moisture on the Indian monsoon system. A pair of state-of-the-art global climate models will be used: the UK MetOffice Unified Model (MetUM) and the NCAR Community Atmosphere Model (CAM4). In a final step, the superimposed impact of climate change will be assessed and future predictions of water availability will be generated. For this purpose, we will use the new CMIP5 ensemble of climate models. Using a statistical approach, these models will be downscaled to a level useful for application over the Gangetic Plains. The integrated hydrological model can then be run with these future climate projections to assess the impact of future climate change on regional and local water availability. Two local case studies will address the usefulness of such projections and their uncertainties in a local ecosystem-oriented management setting.

恒河平原是喜马拉雅山脚下的一个大的肥沃地区，覆盖了印度北方的大部分地区。它拥有约4亿居民，是东南亚人口最稠密的地区之一。凭借其肥沃的土壤，季风降水和巨大的地下蓄水层，平原一直是印度农业革命的核心。在过去的40年里，新肥料和作物的引进以及大规模灌溉系统的建设一直是该地区社会经济发展的主要推动力。然而，这些做法也导致地下水严重下降，对其他水资源造成压力。陆地表面和大气之间不断变化的水和能量反馈甚至可能改变了当地的气候系统。预计强劲的经济发展将在不久的将来继续这些趋势，未来的气候变化预计也将增加对当地水资源系统的压力，确定观测到的水供应历史变化的主要原因，并预测气候变化对当地水资源管理战略的未来影响，这是特别具有挑战性的，但对于水资源的可持续管理是必不可少的。举例来说：评估地下水蓄水层的可持续性需要了解全球气候影响，但也需要了解土地使用、抽取和土壤水分动态的影响;此外，土地使用变化的空前规模和灌溉的增加预计会通过水和能源的反馈影响当地气候。为了揭示和量化不同变化驱动因素的影响，需要对恒河平原的主要水通量进行全面综合分析，这项研究将是第一个在全面综合建模设置中分析恒河平原主要水通量变化和反馈的研究。这一办法将有助于将地方和区域土地利用变化的影响与全球气候驱动因素的影响分开。我们将利用现有的地下水和地表水建模工具箱为该地区开发一个定制的耦合水文模型。将利用各种不同的信息来源，包括当地测量、卫星观测和全球气候（再分析）数据集，对这一模型进行校准和测试。随后，我们将使用不同的土地使用和水提取方案运行模型。这将使我们能够量化土地利用变化和开采对主要水文通量和水资源的影响，同时，水文模型将生成关于历史土地利用以及不同假设情景导致的土壤湿度变化的高分辨率数据。通过将这些情景输入全球气候模式，我们将研究印度季风系统土壤湿度大规模变化的潜在反馈。将使用一对最先进的全球气候模型：英国MetOffice统一模型（MetUM）和NCAR社区大气模型（CAM 4）。最后一步，将评估气候变化的叠加影响，并对未来的水供应情况作出预测。为此，我们将使用新的CMIP 5气候模式集合。使用统计方法，这些模型将被缩小到一个有用的水平，在恒河平原上的应用。然后，综合水文模型可以与这些未来气候预测一起运行，以评估未来气候变化对区域和当地水资源供应的影响。两项地方案例研究将探讨这种预测的效用及其在地方生态系统管理环境中的不确定性。

项目成果

A Comparative Analysis of TRMM-Rain Gauge Data Merging Techniques at the Daily Time Scale for Distributed Rainfall-Runoff Modeling Applications

• DOI: 10.1175/jhm-d-14-0197.1
• 发表时间: 2015-10
• 期刊: Journal of Hydrometeorology
• 影响因子: 3.8
• 作者: D. Nerini;Z. Zulkafli;Li-Pen Wang;C. Onof;W. Buytaert;Waldo Lavado-Casimiro;J. Guyot

Combining information from multiple flood projections in a hierarchical Bayesian framework

在分层贝叶斯框架中组合来自多个洪水预测的信息

• DOI: 10.1002/2015wr018143
• 发表时间: 2016
• 期刊: Water Resources Research
• 影响因子: 5.4
• 作者: Le Vine N

An open and extensible framework for spatially explicit land use change modelling: the lulcc R package

• DOI: 10.5194/gmd-8-3215-2015
• 发表时间: 2015-01-01
• 期刊: GEOSCIENTIFIC MODEL DEVELOPMENT
• 影响因子: 5.1
• 作者: Moulds, S.;Buytaert, W.;Mijic, A.
• 通讯作者: Mijic, A.

Accounting for dependencies in regionalized signatures for predictions in ungauged catchments

考虑区域化签名中的依赖性以进行未计量流域的预测

• DOI: 10.5194/hess-20-887-2016
• 发表时间: 2016
• 期刊: Hydrology and Earth System Sciences
• 影响因子: 6.3
• 作者: Almeida S

Open and scalable analytics of large Earth observation datasets: From scenes to multidimensional arrays using SciDB and GDAL

• DOI: 10.1016/j.isprsjprs.2018.01.014
• 发表时间: 2018-04-01
• 期刊: ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
• 影响因子: 12.7
• 作者: Appel, Marius;Lahn, Florian;Pebesma, Edzer
• 通讯作者: Pebesma, Edzer