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This study explores whether incorporating a more sophisticated representation of groundwater, and human-groundwater interactions, improves predictive capability in a large-scale water resource model. The Global Water Availability Assessment model (GWAVA) is developed to include a simple layered aquifer and associated fluxes (GWAVA-GW), and applied to the Cauvery river basin in India, a large, human-impacted basin with a high dependence on groundwater. GWAVA-GW shows good predictive skill for streamflow upstream of the Mettur dam: Kling-Gupta Efficiency ≥ 0.3 for 91% of subcatchments, and improved model skill for streamflow prediction compared to GWAVA over the majority of the basin. GWAVA-GW shows some level of predictive skill for groundwater levels over seasonal and long-term time scales, with a tendency to overestimate depth to groundwater in areas with high levels of groundwater pumping. Overall, GWAVA-GW is a useful tool when assessing water resources at a basin scale, especially in areas that rely on groundwater.

This report has been produced to summarise the results of the floods and droughts research infrastructure scoping study for the interested community.

The Cauvery basin in southern India is experiencing transboundary issues due to increasing water demand. This study analysed water balance components and the impact of agricultural water management (AWM) interventions in the upper Cauvery catchment of the Cauvery basin. Results showed that the study catchment receives an average of 1280 mm of annual rainfall. Of this, 29% (370 mm) flows downstream, 54% (700 mm) contributes to evapotranspiration (ET) and 17% (215 mm) contributes to groundwater recharge and surface storage. Rainfall varies from 700 to 5400 mm and the Western Ghats (mountain pass) are the main source of freshwater generation. The estimated ET in different catchments ranged from 500 to 900 mm per annum. An increase in the allocation of fresh water supplied by all three reservoirs (Hemavathi, Harangi and KRS) was observed in the canal command areas, from 1450 million cubic metres (MCM) yr‾¹ in 1971–1980 to 3800 MCM yr‾¹ in 2001–2010. AWM interventions harvested 140–160 MCM (13–20 mm) of surface runoff upstream of the upper Cauvery and reduced inflow into the Krishnaraja Sagar reservoir by 2–6%. The study findings are useful for designing and planning suitable water management interventions at basin scale.

Droughts are known to be one of the most damaging and costly natural hazards as a result of their large spatial scale, creeping nature and long duration. They have widespread primary and secondary impacts, and as such, proactive drought management is crucial to mitigate those impacts. In order to do so, it is crucial to understand the drought risk – i.e. the characteristics of the drought hazard, who or what is exposed to the drought hazard, and who (or what) is vulnerable to the effects of drought. Drought mitigation is one of five strategic objectives under the United Nations Convention to Combat Desertification (UNCCD) 2018-2030 Strategic Framework, under which a monitoring framework and a range of indicators was agreed by country Parties to the UNCCD. Here we present new guidance created to help Parties to the UNCCD report on their progress towards Strategic Objective 3 ‘To mitigate, adapt to, and manage the effects of drought in order to enhance resilience of vulnerable populations and ecosystems’. Progress is monitored using three indicators, capturing the three fundamental components of risk: drought hazard, exposure to drought and vulnerability to drought. The three indicators, as agreed by Parties to the UNCCD, are: - Trends in the proportion of land under drought over the total land area, - Trends in the proportion of the total population exposed to drought, and - Trends in the degree of drought vulnerability. Acknowledging the need for global applicability, the methods recommended to calculate these three indicators balance state-of-the-art science with relative simplicity, whilst also meeting the requirements set out in official UNCCD Decisions, guidelines of the World Meteorological Organization, and where possible utilising datasets used for other reporting activities (e.g. the Sustainable Development Goals). The methods for each indicator are illustrated using contrasting case studies, highlighting the flexibility of the approaches recommended, as wel

Droughts are known to be one of the most damaging and costly natural hazards as a result of their large spatial scale, creeping nature and long duration. They have widespread primary and secondary impacts, and as such, proactive drought management is crucial to mitigate those impacts. In order to do so, it is crucial to understand the drought risk in terms of the characteristics of the drought hazard, who or what is exposed to the drought hazard, and who (or what) is vulnerable to the effects of drought. Drought mitigation, adaptation and management was adopted as one of five strategic objectives under the United Nations Convention to Combat Desertification (UNNCD) 2018-2030 Strategic Framework. Country Parties to the UNCCD agreed a monitoring framework and a range of indicators in order to track progress towards this objective. Here we present new guidance created to help Parties to the UNCCD report on their progress towards Strategic Objective 3 ‘To mitigate, adapt to, and manage the effects of drought in order to enhance resilience of vulnerable populations and ecosystems’. Progress is monitored using three indicators, characterising the three fundamental components of risk: drought hazard, exposure to drought and vulnerability to drought. The three indicators, as agreed by Parties to the UNCCD, are: - Trends in the proportion of land under drought over the total land area, - Trends in the proportion of the total population exposed to drought, and - Trends in the degree of drought vulnerability. Acknowledging the need for global applicability, the methods recommended to calculate these three indicators balance state-of-the-art science with relative simplicity, whilst also meeting the requirements set out in official UNCCD Decisions, guidelines of the World Meteorological Organization, and where possible utilising datasets used for other reporting activities (e.g. the Sustainable Development Goals). The recommended methods for each indicator are illustrated using