Catchment Risk Assessments using Multi-Scale Data (CARISMA)

CARISMA项目（利用多尺度数据进行汇水风险评估）旨在通过整合来自社区主导的监测（水文“公民科学”）和遥感最新发展的独立信息源，解决汇水平衡评估中数据匮乏的问题。这个项目的重点是撒哈拉以南非洲的埃塞俄比亚和坦桑尼亚的两个研究领域，在那里这些问题特别严重，但是它的目的是发展一种更普遍适用的方法。由于过度抽取、土地利用的变化或气候的变率和变化，许多集水区或河流流域都面临水压力。水压力可能被视为整个集水区的长期趋势，但更多的是被视为偶发事件，如季节性或多年干旱，并且可能在空间上位于某些河流支流或子集水区。因此，如果在正确的地点和正确的时间没有足够的数据，就很难确定水压力的根本原因，以及特定的用水者群体如何为潜在的解决方案作出贡献。我们最近的研究已经证明了社区主导的监测的可行性，以提供可靠的关键水文信息，以提高对地表水和地下水资源的理解，多层次的治理方法是解决水管理政策的可行方法。我们的工作表明，数据共享平台（如“环境虚拟观测站”或“决策剧院”）有潜力帮助整合和呈现支持各级决策的信息，但它们的设计需要以用户为导向，以促进其采用。这些新出现的范例为更好地进行环境管理开辟了新的机会，但需要参与性地开发公开和透明的系统，以便整合多种信息来源，以提供成功的结果。本项目旨在以我们之前的研究为基础，与埃塞俄比亚（阿贝河流域管理局）和坦桑尼亚（鲁菲济河流域管理局）两个流域的合作伙伴和利益相关者共同开发一个原型数据集成和演示平台，该平台将在空间尺度上量化流域水平衡的关键水文指标，以便在水资源紧张的流域制定可持续的水管理政策和实践。将采用参与式方法确定与代表社区、生态系统、商业和治理利益的利益相关者群体相关的指标。拟议的平台利用可公开获得的遥感数据对关键水文成分进行空间评估，特别是降雨和蒸散，并利用社区主导的对地面变量（包括降雨、河流水位和流量以及地下水位）的低成本监测，以补充现有的正式监测网络。将使用标准化的水会计建模框架评估每个组成部分的不确定性如何有助于对水平衡的总体理解。然后，这可以支持更好地量化流域水资源短缺的贡献者，为多方利益相关者的决策提供信息。从不同的数据来源了解减少不确定性将为适当设计监测网络提供指导基础，并为支持基于风险的水管理方法提供证据。原型数据平台的项目输出将为我们的合作伙伴WWF-UK的战略提供关键的一步，该战略致力于开发和共享更好的水文数据的通用能力，以支持他们的全球活动，特别是通过他们的水管理计划。坦桑尼亚世界自然基金会密切参与这一项目将为实现这一目标迈出切实的第一步。

The CARISMA project (Catchment Risk Assessments using Multi-Scale Data) aims to address issues of data scarcity in catchment water balance assessments through integrating independent sources of information from community-led monitoring (hydrological 'citizen science') and recent developments in remote sensing. The project focusses on two study areas in sub-Saharan Africa, in Ethiopia and Tanzania, where such problems are particularly acute, but aims to develop a more generally applicable methodology.Many catchments or river basins undergo water stress due to a combination of over-abstraction, changes in land-use, or climatic variability and changes. Water stresses may be felt as long-term trends over whole catchment areas, but more often are seen as episodic events such as seasonal or multi-annual drought, and may be spatially located in certain river tributaries or sub-catchments. It is then difficult to identify the underlying causes of water stress, and how particular groups of water users could contribute to potential solutions, if insufficient data are available in the right place and at the right time. Our recent research has demonstrated the viability of community-led monitoring to provide credible key hydrological information to improve understanding of surface and groundwater resources, and that multi-level governance approaches are a feasible way of addressing water management policy. Our work has shown that data-sharing platforms (such as 'Environmental Virtual Observatories' or 'Decision Theatres') have potential to help integrate and present information is ways that support decision making at all levels, but their design needs to be user-driven to facilitate their adoption. These emerging paradigms open up new opportunities for better environmental management, but require participatory development of open and transparent systems for integration of multiple sources of information to provide successful outcomes. This project aims to build on our previous research by co-developing with partners and stakeholders in two catchment in Ethiopia (Abay River Basin Authority) and Tanzania (Rufiji River Basin Authority) a prototype data integration and presentation platform that will quantify key hydrological indicators of catchment water balances at spatial scales appropriate to developing sustainable water management policies and practices in water-stressed catchments. Indicators relevant to stakeholder groups representing community, ecosystem, business, and governance interests will be identified using a participatory approach. The proposed platform uses publicly available remote sensing data for spatial assessments of key hydrological components, particularly rainfall and evapotranspiration, and community-led low-cost monitoring of ground-based variables (including rainfall, river levels and flows, and groundwater levels) to complement available formal monitoring networks. Evaluation of how uncertainty in each component can contribute to overall understanding of water balances will be assessed using a standardised water accounting modelling framework. This can then support better quantification of contributors to catchment water scarcity, to inform multi-stakeholder decision making. Understanding of uncertainty reduction from the different data sources will provide the basis for guidance on appropriate design of monitoring networks, and evidence to support a risk-based approach to water management.The project output of a prototype data platform will provide a key step towards our partner WWF-UK's strategy of working towards a generic capability for developing and sharing better hydrological data to underpin their global activities, particularly through their Water Stewardship Programme. Close involvement of WWF-Tanzania in this project will provide a tangible first step towards this goal.