The groundwater systems of northwest India and central Pakistan are amongst the most heavily exploited in the world. Groundwater has been monitored in the region for more than a century resulting in a unique long-term record of groundwater level change. Here we present an analysis of post-monsoon groundwater levels from 1900 to 2010. We show that for the majority of the last century groundwater levels were rising and calculate net groundwater accumulation of c.350 km 3 (estimated range: 150-450 km 3 ). Large scale irrigation development via canal construction played a defining role in groundwater accumulation during the early twentieth century. More recent, and well documented, groundwater depletion c.75 km 3 (estimate range: 25-100 km 3 ) occurred during the first decade of the 21 st century and was driven by the superimposed effects of low rainfall and large-scale tubewell development. However, between 1970-2000, when large increases in tubewell irrigation began, groundwater levels stabilised as a result of higher than average rainfall. Human activity in the early 20 th century increased the total volume of groundwater available prior to large-scale exploitation in the late 20 th century. MainThe transboundary aquifer of central Pakistan and northwest India sits below one of the most intensively irrigated areas in the world. In the first two decades of the 21 st century several studies, largely using the Gravity Recovery and Climate Experiment (GRACE) satellites, identified groundwater depletion in the region 1-6 . Declining groundwater levels were attributed to increased groundwater abstraction which began in the late 20 th century to supplement surface water irrigation. More recently a number of studies have demonstrated the value of using in-situ measurements of groundwater level to understand the nuance of groundwater level change in the region 4,7,8 . These studies highlight the impact of changes in monsoon precipitation 7 and recharge from the vast canal network 9 as playing an important role in controlling groundwater storage in the region.

Abstract. In Europe, it is estimated that around 65 % of drinking water is extracted from groundwater. Worryingly, groundwater drought events (defined as below normal groundwater levels) pose a threat to water security. Groundwater droughts are caused by seasonal to multi-seasonal or even multi-annual episodes of meteorological drought during which the drought propagates through the river catchment into the groundwater system by mechanisms of pooling, lagging, and lengthening of the drought signals. Recent European drought events in 2010–2012, 2015 and 2017–2018 exhibited spatial coherence across large areas, thus demonstrating the need for transboundary monitoring and analysis of groundwater level fluctuations. However, such monitoring and analysis of groundwater drought at a pan-European scale is currently lacking, and so represents a gap in drought research as well as in water management capability. To address this gap, the European Groundwater Drought Initiative (GDI), a pan-European collaboration, is undertaking a large-scale data synthesis of European groundwater level data. This is being facilitated by the establishment of a new network to co-ordinate groundwater drought research across Europe. This research will deliver the first assessment of spatio-temporal changes in groundwater drought status from ∼1960 to present, and a series of case studies on groundwater drought impacts in selected temperate and semi-arid environments across Europe. Here, we describe the methods used to undertake the continental-scale status assessment, which are more widely applicable to transboundary or large-scale groundwater level analyses also in regions beyond Europe, thereby enhancing groundwater management decisions and securing water supply.

Purpose – The need in disaster response to assess how reliably and equitably funding was accounted for and distributed is addressed by a standardized report and index applicable to any disaster type. The paper aims to discuss this issue. Design/methodology/approach – Data from the Nepal earthquake (2015), Typhoon Haiyan (2013), the Haiti earthquake (2010), Sri Lankan flood (2011), and Hurricane Sandy (2012) illustrate uses of a public equitable allocation of resources log (PEARL). Drawing from activity-based costing and the Gini index, a PEARL spreadsheet computes absolute inequity sector by sector as well as a cumulative index. Response variations guide index value interpretation. Findings – Index values indicates major inequity in Nepal hygiene kit distribution and Haiti earthquake (both PEARL indices near 0.5), moderate inequity for the Sri Lankan flood (index roughly 0.75) and equitable distributions for Typhoon Haiyan and Hurricane Sandy (both indices approximately 0.95). Indices are useful to approximate proportions of inequity in the total response and investigate allocation under uncertainty in sector need specification. Originality/value – This original tool is implementable using a website containing a practice PEARL, completed examples and downloadable spreadsheet. Used across multiple sectors or for a single sector, PEARL may signal need for additional resources, correct inequitable distribution decisions, simplify administrative monitoring/assessment, and foster greater accounting transparency in summary reports. PEARL also assists historical analysis of all disaster types to determine completeness of public accounting records and equity in fund distribution.

Large-scale studies of the spatial and temporal variation of groundwater drought status require complete inventories of groundwater levels on regular time steps from many sites so that a standardised drought index can be calculated for each site. However, groundwater levels are often measured sporadically, and inventories include missing or erroneous data. A flexible and efficient modelling framework is developed to fill gaps and regularise data in such inventories. It uses linear mixed models to account for seasonal variation, long-term trends and responses to precipitation and temperature over different temporal scales. The only data required to estimate the models are the groundwater level measurements and freely available gridded weather products. The contribution of each of the four types of trends at a site can be determined and thus the causes of temporal variation of groundwater levels can be interpreted. Validation reveals that the models explain a substantial proportion of groundwater level variation and that the uncertainty of the predictions is accurately quantified. The computation for each site takes less than 130 s and requires little supervision. Hence, the approach is suitable to be upscaled to represent the variation of groundwater levels in large datasets consisting of thousands of boreholes.