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As the adverse impacts of hydrological extremes increase in many regions of the world, a better understanding of the drivers of changes in risk and impacts is essential for effective flood and drought risk management and climate adaptation. However, there is currently a lack of comprehensive, empirical data about the processes, interactions and feedbacks in complex human-water systems leading to flood and drought impacts. Here we present a benchmark dataset containing socio-hydrological data of paired events, i.e., two floods or two droughts that occurred in the same area. The 45 paired events occurred in 42 different study areas and cover a wide range of socio-economic and hydro-climatic conditions. The dataset is unique in covering both floods and droughts, in the number of cases assessed, and in the quantity of socio-hydrological data. The benchmark dataset comprises: 1) detailed review style reports about the events and key processes between the two events of a pair; 2) the key data table containing variables that assess the indicators which characterise management shortcomings, hazard, exposure, vulnerability and impacts of all events; 3) a table of the indicators-of-change that indicate the differences between the first and second event of a pair. The advantages of the dataset are that it enables comparative analyses across all the paired events based on the indicators-of-change and allows for detailed context- and location-specific assessments based on the extensive data and reports of the individual study areas. The dataset can be used by the scientific community for exploratory data analyses e.g. focused on causal links between risk management, changes in hazard, exposure and vulnerability and flood or drought impacts. The data can also be used for the development, calibration and validation of socio-hydrological models. The dataset is available to the public through the GFZ Data Services (Kreibich et al. 2023, link for review: https://dataservices.gfz-potsdam.de/panmetaworks/review/923c14519deb04f83815ce108b48dd2581d57b90ce069bec9c948361028b8c85/).

There is an expected increase in the occurrence and severity of hydrometeorological extremes in many regions worldwide. Current research indicates that despite a positive trend in reducing drought impacts, most regions still need to adapt their monitoring practices to cope with projected drought events effectively. On the other hand, we still need a clear understanding of how a changing climate can modify the hydrological regime of catchments in the future. Therefore, it is essential to understand which drought indicators are relevant to monitoring catchments with different hydrological regimes.Therefore, this study aims to elucidate which drought indices are required to effectively monitor hydrological drought depending on the catchment’s hydrological regime, using 100 near-natural Chilean catchments with contrasting climatic conditions and hydrological regimes as a case study. For this purpose, different drought indices were computed at different temporal scales: SPI and SPEI at 3, 6, 9, 12, and 24 months; the Empirical Standardised Soil Moisture Index (ESSMI) at 3, 6, and 12 months; and a standardised snow water equivalent index (SSWEI) at 3 and 6 months. State-of-the-art gridded datasets used for computing the drought indices were: CR2MET v2.5 (a Chilean dataset based on ERA5) for precipitation and potential evapotranspiration; ERA5, ERA5-Land, and SMAP (L3 and L4) for soil moisture; and ERA5 and ERA5-Land for snow water equivalent. These indices were evaluated against the Standardised Streamflow Index (SSI) to select indices that are able to effectively monitor hydrological droughts, considering different hydrological regimes. A cross-correlation analysis and an event coincidence were used to assess which index had the highest correlation with SSI. Results showed that the indices and temporal scales used to effectively monitor hydrological droughts changed according to the catchment's hydrological regime. The results of the present work are pivotal for water managers as they provide insights on how the hydrological regime of the catchments should be considered in drought monitoring.

For more than two decades, multi-objective optimisation (MOO) has imposed a new paradigm in the calibration of hydrological models, and over the years different algorithms and calibration approaches have been developed that aim to obtain consistent parameters for some specific hydrological model. However, the development of flexible multi-objective calibration tools has been scarce, making it difficult to spread these approaches to a wide range of researchers. The objective of this work is to show the application of a new multi-objective and multi-platform R package (hydroMOPSO) for the calibration of SWAT+, a widely used semi-distributed hydrological model. In particular, in this work hydroMOPSO is used beyond the traditional adoption of multiple objective functions. Instead, a multi-period (dry and wet years), and multi-variable (point streamflows and gridded soil moisture and evapotranspiration) are used as objectives, to illustrate the flexibility of hydroMOPSO to be linked with different model input and outputs, both with different file formats and temporal frequencies. Similar approaches could be applied with other hydrological models available in R (e.g., TUWmodel, airGR, topmodel) or any other model that can be run from the system console (e.g., Raven, MODFLOW, WEAP).

Drought is one of the main hydroclimatic hazards worldwide, affecting water availability, ecosystems and socioeconomic activities. Since 2010, Central Chile (30–38°S) has been experiencing a drought with unprecedented duration and severity (also known as the Central Chile megadrought), producing drastic reductions in river flows, snow cover and reservoir levels. Nevertheless, there is limited understanding of how hydrological processes have been altered and whether such variations will persist during the 21st century. In this study, we characterize the magnitude, frequency, and duration of drought events under historical conditions and future climate scenarios across different hydrological regimes in Central Chile. To this end, we generate daily time series of streamflow, evapotranspiration, soil moisture and other hydrological variables in six case study basins with little human intervention for the period 1981-2100, using the Structure for Unifying Multiple Modeling Alternatives (SUMMA) framework and the mizuRoute model. Simulations are conducted at a 0.05º x 0.05º horizontal resolution, using a combination of the CR2MET gridded product and ERA5 outputs to obtain historical meteorological forcings, and statistically downscaled global climate model (GCM) outputs from the Coupled Model Intercomparison Project Phase 6 (CMIP6) to obtain future climate time series. Finally, we characterize drought events with the Standardized Precipitation Index (SPI), Standardized Streamflow Index (SSI), and Soil Moisture Index (SMI). The calibrated hydrologic model parameters yield daily streamflow simulations with a Kling-Gupta Efficiency (KGE) greater than 0.78 and 0.61 in all basins for the calibration and evaluation periods, respectively. The drought indices estimated for the historical period enable identifying the severe events of 1998-1999 and 2010-2020 (with standardized values smaller than -1.28); however, the magnitude and duration varies depending on the event and hydrological variable analyzed. Ongoing work seeks to examine inter-basin differences in terms of drought characteristics, along with projected changes in the frequency and intensity of this type of event.

Several long-term gridded datasets have become available in the last decades on a global scale, at increasing spatial and temporal resolution, with low latency times. These datasetshave opened new opportunities to advance Earth Sciences modelling studies at different spatial and temporal scales, especially in poorly gauged areas. However, working with (hundreds of) thousands of raster time series (e.g., for (sub)daily precipitation), usually in different vectorial and raster formats, impose high computational challenges to efficiently analyse all the gridded datasets.In this work we introduce a new R package for easy processing and analysis of raster time series, to bring the use of gridded data closer to the Earth Sciences community. This package expands the large number of spatial functions provided by the terra package by taking advantage of the time attribute of raster objects. A particular emphasis of the package is exploring and comparing gridded datasets of hydrological variables with different time frequencies (e.g., sub-hourly, hourly, daily, monthly, seasonal, annual).General purpose functions include temporal subsetting, resampling, cropping, extracting time series for points or polygons, comparing two datasets using summary statistics, and exporting a raster time series as a collection of daily/monthly/annual files, each one of them with several layers of a higher temporal frequency. Also, temporal aggregation is possible from sub-hourly to hourly/daily/weekly/monthly/annual, among others. Most functions can take advantage of multi-core computers and network clusters, to reduce the computational burden.To illustrate the use of this new package, we compared different state-of-the-art gridded precipitation products (CHIRPSv2, CMORPH v1.0, IMERGv06B, MSWXv1.0, ERA5, ERA5-Land, CR2METv2.5), all of them with different data formats and spatial resolutions, using continental Chile as a case study. However, based on the package's flexibility and ease of use, we hope the broader community of hydro-scientists and water-engineers will use it to visualise the spatio-temporal variation of key hydrological/environmental variables,to carry out time series analysis, to combinedifferent types of models and data sources, and to improve our integrated knowledge of the water cycle.

The Coastal Range in the Mediterranean segment of the Chilean active margin is a soil mantled landscape able to store fresh water and potentially support a biodiverse native forest. In this landscape, human intervention has been increasing soil erosion for ~200 yr, with the last ~45 yr experiencing intensive management of exotic tree plantations. At the same time, this landscape has been affected by a prolonged megadrought, and how the anthropogenic disturbances and hydrometeorologic trends affect sediment transport is not yet well understood. In this study we calculate a decadal-scale catchment erosion rate from suspended sediment loads and compare it with a 10-year-scale catchment denudation rate estimated from detritic 10Be. We then contrast these rates against the effects of discrete disturbances and hydroclimatic trends. Erosion/denudation rates are similar on both time scales, i.e. 0.018 ± 0.005 mm/yr and 0.024 ± 0.004 mm/yr, respectively. Recent human-made disturbances include logging operations during each season and a dense network of forestry roads, which increase structural sediment connectivity. Other disturbances include the 2010 M 8.8 Maule earthquake, and two widespread wildfires in 2015 and 2017. A decrease in suspended sediment load is observed during the wet seasons for the period 1986-2018 coinciding with a decline in several hydroclimatic parameters. The low 10-year denudation rate agrees with a landscape dominated by slow soil creep. The low 10-year-scale erosion rate and the decrease in suspended sediments, however, conflicts with both the observed disturbances and increased structural (sediment) connectivity. These observations suggest that, either suspended sediment loads and, thus, catchment erosion, are underestimated, and/or that decennial sediment detachment and transport were smeared by decreasing rainfall and streamflow. Our findings indicate that human-made disturbances and hydrometeorologic trends may result in opposite, partially offsetting effects on recent sediment transport, but both contribute to the degradation of the landscape.

The landscape of south-central Chile, originally a mosaic of pristine native forests and crops, has been converted into tree plantations and agroindustry. Farmlands and native forests have undergone a rapid conversion to fast-growing non-native pine and eucalyptus plantations, as well as irrigated fruits production for international exports. These two drivers have severely transformed the socio-ecological system, resulting in less biodiversity, more erosion, emigration and work depence, less drinking water, and a fire-prone landscape. A participatory approach helps not only to visualise tensions in the territory, but it is also useful for stakeholders to explore the possible environmental futures. However, frequently the development of land-use scenarios is mostly based on the views of experts and policymakers, missing out a wealth of local knowledge about the environment which experts seek to comprehend. This work aims at quantifying the impacts of the aforementioned land cover changes in water provision for the population and ecosystems, by incorporating the views of the people that still live in a drought-prone rural area in the construction of different narratives representing future land management scenarios. The study area is the Cauquenes River Basin, a mediterranean catchment located in central Chile, historically known for wine production and rainfed agriculture. To develop the narratives, we conducted semi-structured interviews to collect and analyse qualitative information using a coding system systematised in the Atlas.ti software. Using 2050 as the simulation target year, narratives gave us the guidelines to develop the spatial scenarios. Then, using an open-source land use change model- called CLUE-s we constructed scenarios of future land use change. The CLUE-s algorithm allocates land uses based on the suitability of each land use as well as spatial regulations. To assess the impact on water provision of each scenario, they were evaluated using a hydrological model (SWAT+).Our results identified two different narratives: i) rural development: where water availability could increase, if a protection strip is established near water courses, that is, scrublands and native forest are assigned in these areas and, rainfed agriculture is strengthened and reach the extension it had in 1990 and ii) agro-industrial development, in which the central government promotes irrigated agriculture for international export markets, at the same time, passive preservation plans for protect native forest are applied according to the current forestry regulation. We expect that this participatory approach will enrich and strengthen adaptive management capacity at the local level, to be able to face the challenges ahead presented by a drier future.

In this work we introduce hydroMOPSO, a novel multi-objective R package that combines two search mechanisms to maintain diversity of the population and accelerate its convergence towards the Pareto-optimal set: Particle Swarm Optimisation (PSO) and genetic operations. hydroMOPSO is model-independent, which allows to interface any model code with the calibration engine, including models available in R (e.g., TUWmodel, airGR, topmodel), but also any other complex models that can be run from the system console (e.g. SWAT+, Raven, WEAP). In addition, hydroMOPSO is platform-independent, which allows it to run on GNU/Linux, Mac OSX and Windows systems, among others.Considering the long execution time of some real-world models, we used three benchmark functions to search for a configuration that allows to reach the Pareto-optimal front with a low number of model evaluations, analysing different combinations of: i) the swarm size in PSO, ii) the maximum number of particles in the external archive, and iii) the maximum number of genetic operations in the external archive. In addition, the previous configuration was then evaluated against other state-of-the-art multi-objective optimisation algorithms (MMOPSO, NSGA-II, NSGA-III). Finally, hydroMOPSO was used to calibrate a GR4J-CemaNeige hydrological model implemented in the Raven modelling framework (http://raven.uwaterloo.ca), using two goodness-of-fit functions: i) the modified Kling-Gupta efficiency (KGE') and ii) the Nash-Sutcliffe efficiency with inverted flows (iNSE).Our results showed that the configuration selected for hydroMOPSO makes it very competitive or even superior against MMOPSO, NSGA-II and NSGA- III in terms of the number of function evaluations required to achieve stabilisation in the Pareto front, and also showed some advantages of using a compromise solution instead of a single-objective one for the estimation of hydrological model parameters.

The Coastal Range in the Mediterranean segment of the Chilean active margin is a soil mantled landscape of gentle hillslopes, able to store fresh water and potentially to support biodiverse native forests. In this landscape, anthropogenic intervention has been increasing soil erosion for ∼200 yr, with the last ∼45 yr experiencing intensive management on exotic tree plantations. Such intense forest management practices come along with rotational cycles as short as 9-25 yrs, depending on the tree species, dense forest road networks, and promoting wildfire susceptibility. Here we compare decadal-scale catchment erosion rates from suspended sediment loads with 104-years-scale catchment erosion rate estimated from detritic 10Be in a ∼400 km2 catchment. We relate these rates to land cover dynamics, sediment connectivity modified by forestry roads, and hydro-meteorologic trends, because the catchment has been widely disturbed by forest management practices, wildfires, and earthquakes, while an unprecedented drought started on 2010. Both, short- and long-term erosion show comparably low rates (0.018 ± 0.005 mm/yr and 0.024 ± 0.004 mm/yr). Recent human-made disturbances include logging operations every season and the building, the maintaining and the heavy machinery traffic on forestry road. Forestry roads often intersect streams, thus forming bypasses to route sediments between hillslopes and valleys. That is, increasing structural sediment connectivity. In addition, one Mw 8.8 earthquake and two widespread wildfires disturbed this catchment in 2010, 2015 and 2017, respectively. Mann-Kendall tests applied to decadal records of rainfall and streamflow resulted in decreasing trends. The suspended sediments fluxes of July also decreases in the same period, yet other subsets of that specific series were ruled out by autocorrelation or by completeness tests. The low 104-years erosion rate agrees with a landscape dominated by slow soil creep. The low 10-years-scale erosion rate, however, conflicts with the observed disturbances and the increase in structural sediment connectivity.The latter results suggest that, either the suspended sediment fluxes are underestimated, or the decennial sediment detachment and transport may be affected by the negative trends on rainfall and streamflows. Sediment mobilization depends mostly on specific thresholds of rainfall intensity on hillslopes and on water discharge in the streams, while the unprecedented drought starting in 2010 together with high water demands of fast-growing tree plantations mean a reduction in water availability. Ultimately, our findings indicate that human-made disturbances and hydrometeorologic trends may result in contrasting effects for the recent mobilization of sediments. However, both are negative for the resilience of ecosystems and then, for humans.

Risk management has reduced vulnerability to floods and droughts globally1,2, yet their impacts are still increasing3. An improved understanding of the causes of changing impacts is therefore needed, but has been hampered by a lack of empirical data4,5. On the basis of a global dataset of 45 pairs of events that occurred within the same area, we show that risk management generally reduces the impacts of floods and droughts but faces difficulties in reducing the impacts of unprecedented events of a magnitude not previously experienced. If the second event was much more hazardous than the first, its impact was almost always higher. This is because management was not designed to deal with such extreme events: for example, they exceeded the design levels of levees and reservoirs. In two success stories, the impact of the second, more hazardous, event was lower, as a result of improved risk management governance and high investment in integrated management. The observed difficulty of managing unprecedented events is alarming, given that more extreme hydrological events are projected owing to climate change3.