Hydrion (Netherlands)

Farmers face increasingly more uncertainty with regards to crop production of due to a changing climate. Temperature and precipitation patterns change, with prolonged periods of heats and droughts. This affects the crop growth season in terms of overall duration and increases the uncertainty of the crop growth conditions. Especially crop water availability is of importance to generate a good yield. Various management strategies can help to manage the water availability, such as drainage, irrigation infrastructures or a combination of both. Within the EU FARMWISE project, various water management strategies are evaluated that could help farmers mitigate future extreme weather conditions. The goal is to determine how various irrigation strategies perform under future climatic conditions.The management strategies under investigation are traditional sprinkler irrigation, subirrigation and a combination of controlled subirrigation with tile drainage. Utilising HydroGeoSphere (HGS), a 3D physics-based integrated surface-subsurface model was setup of an experimental field in the Netherlands. At the field site, an irrigation system, comprising of a controlled drainage with subirrigation is being monitored. The HGS model was calibrated using the field data to simulate the natural groundwater fluctuations, as well as the controlled drainage and subirrigation.To determine the effectiveness of the water management scenarios under various climatic scenarios, the water management scenarios were implemented into the calibrated model. The hydraulic head response and soil moisture content were the parameters of interest. To represent the future climate scenarios, precipitation and evapotranspiration from the SSP1-2.6, SSP2-4.5 and SSP5-8.5 scenarios over three time horizons were used. All model results in terms of hydraulic head and soil moisture response are currently being analysed to determine the effectiveness of the various management strategies under different climates.

The accuracy of flood warnings should ideally be evaluated on real impact data, although such data are often difficult to obtain and work with. The Swedish Meteorological and Hydrological Institute (SMHI) has recently acquired records of flood-affected roads and emergencies attended by fire and rescue services in Sweden over the last 25 years. We analysed whether the impacts were covered by flood-related warnings and whether they coincided with hydrometeorological conditions exceeding flood warning thresholds from hindcast data. Here we present our experiences on tackling challenges associated with using the impact dataset, insights into what type of flood events the warning system handles well and how it can be developed further.The existing SMHI warning methodology explained only 26% of the reported flood impacts, although this proportion increased to 43% after filtering out minor and isolated impacts. Incorporating runoff data from a recently developed sub-daily hydrological model further increased the proportion of explained impacts to 54%. Sub-daily runoff was especially effective in explaining summer flood impacts from cloudbursts in small flashy streams, illustrated through a case study of the Västernorrland flood in September 2025. Notably, total runoff generated in subcatchments was a more important predictor of flood impacts than streamflow, while precipitation did not account for almost any impacts alone without coinciding hydrological causes. Nevertheless, impacts from winter processes, such as urban snowmelt and rain-on-snow floods, remain poorly represented in the warning system. Our findings highlight the importance of filtering impact records prior to evaluation and reveal the benefit of utilising high-resolution hydrological models with outputs beyond streamflow in operational flood warning systems.

<strong class="journal-contentHeaderColor">Abstract.</strong> The Geosciences are amongst the least diverse research fields, where women and other underrepresented 19 groups face systemic biases. This paper presents the state of diversity, equity, and inclusion (DEI) in the cloud-physics community, by combining a metadata analysis of 6987 cloud-physics peer-reviewed journal articles published between 1970 and 2020 with responses from a survey of 198 participants from the cloud-physics community. Women first author contributions are evident only after 1997 and presently only &sim;17 % of studies in the cloud physics field are led by women. Authors from the Global North dominate first and corresponding-author positions, with only &sim;5 % of studies led by tropical affiliation authors. The latter&rsquo;s participation was low even for study sites in the tropics, suggesting widespread practice of parachute science. Of the survey respondents, 23 % identified as a minority group and feel that being a minority has had a negative impact on their scientific career, in terms of collaborations, promotions, publishing, funding, salary, and citations. Although the survey data shows the general experiences of cloud physicists globally, the perspectives from this work can aid the cloud-physics community to develop strategies to improve DEI in institutions beyond a business case for a diverse science community. Rather we should consider an equity-centered approach by understanding our ethical responsibilities to benefit research of the climate system.

<strong class="journal-contentHeaderColor">Abstract.</strong> The Geosciences are amongst the least diverse research fields, where women and other underrepresented 19 groups face systemic biases. This paper presents the state of diversity, equity, and inclusion (DEI) in the cloud-physics community, by combining a metadata analysis of 6987 cloud-physics peer-reviewed journal articles published between 1970 and 2020 with responses from a survey of 198 participants from the cloud-physics community. Women first author contributions are evident only after 1997 and presently only &sim;17 % of studies in the cloud physics field are led by women. Authors from the Global North dominate first and corresponding-author positions, with only &sim;5 % of studies led by tropical affiliation authors. The latter&rsquo;s participation was low even for study sites in the tropics, suggesting widespread practice of parachute science. Of the survey respondents, 23 % identified as a minority group and feel that being a minority has had a negative impact on their scientific career, in terms of collaborations, promotions, publishing, funding, salary, and citations. Although the survey data shows the general experiences of cloud physicists globally, the perspectives from this work can aid the cloud-physics community to develop strategies to improve DEI in institutions beyond a business case for a diverse science community. Rather we should consider an equity-centered approach by understanding our ethical responsibilities to benefit research of the climate system.

<strong class="journal-contentHeaderColor">Abstract.</strong> The Geosciences are amongst the least diverse research fields, where women and other underrepresented 19 groups face systemic biases. This paper presents the state of diversity, equity, and inclusion (DEI) in the cloud-physics community, by combining a metadata analysis of 6987 cloud-physics peer-reviewed journal articles published between 1970 and 2020 with responses from a survey of 198 participants from the cloud-physics community. Women first author contributions are evident only after 1997 and presently only &sim;17 % of studies in the cloud physics field are led by women. Authors from the Global North dominate first and corresponding-author positions, with only &sim;5 % of studies led by tropical affiliation authors. The latter&rsquo;s participation was low even for study sites in the tropics, suggesting widespread practice of parachute science. Of the survey respondents, 23 % identified as a minority group and feel that being a minority has had a negative impact on their scientific career, in terms of collaborations, promotions, publishing, funding, salary, and citations. Although the survey data shows the general experiences of cloud physicists globally, the perspectives from this work can aid the cloud-physics community to develop strategies to improve DEI in institutions beyond a business case for a diverse science community. Rather we should consider an equity-centered approach by understanding our ethical responsibilities to benefit research of the climate system.

Irrigation can significantly influence the hydrological system of agriculturally productive catchments thus understanding the dynamics of the water balance is indispensable for sustainable (agricultural) water management. Accurate estimation of catchment water balance, using distributed hydrological modelling and earth observation data, requires thorough consideration of the associated uncertainties from different sources such as uncertainties in the model representation of system processes and the errors and uncertainties embedded in the remotely sensed data.In this study, we estimate the spatial distribution and temporal dynamics of the water balance of the Hindon River Basin, a sub-basin of the Ganga River Basin in India, where intense irrigation has driven overexploitation of water resources, highly influencing the hydrological regime. For this estimation the open-source distributed hydrological model wflow_sbm is used and evaluated with open global datasets, demonstrating the applicability of this method in data scarce regions. We emphasize on representing relevant hydrological features of the Hindon Basin that are often neglected in hydrological model applications: irrigation, domestic and industrial water use, and (infiltrating) river-aquifer interaction. Our analysis includes the quantification and assessment of the uncertainties associated with the global datasets used and model representation of important processes. First, prior uncertainties of the input variables were analyzed by comparing the errors and correlations of the products from different sources. Second, the impact of different schematizations of irrigation application and subsurface flow (including river infiltration to aquifer) on the modelled water balance is assessed. Finally, model output is evaluated by comparing the estimates and uncertainties of modelled water balance components with estimates from various global datasets.Our analysis reveals the impact of different model choices, highlighting the necessity of proper model representation of hydrological processes and uncertainty assessment to achieve a more reliable estimation of catchment water balance.

A major source of uncertainty in flood statistics are the different flood generation processes. These make the assumption of homogeneous samples questionable. To overcome this issue, a framework for assessing the influence of catchment and climate attributes on flood-generating processes and their effect on flood statistics has been developed and applied to 252 catchments in New Zealand. Mean daily discharge data time series with a length ranging from 20 to 81 years were used. Flood events were classified according to their hydrograph shape. Three types were considered based on the different forcing: heavy rainfall of short duration (termed R1), moderate rainfall of medium intensity and duration (R2), and long-duration rainfall sequences of usually larger spatial extent (R3). The dominant flood type in each catchment was then linked to catchment and climate attributes. This allowed to identify the impact of each flood type on flood statistics and how the flood types have changed over time. The main drivers determining the flood type were rainfall variability and antecedent conditions. Small and steep catchments were dominated by heavy-rainfall floods of shorter duration, while flat and wet catchments were dominated by long-duration floods with larger volumes. Such information can support selection of effective flood protection and management measures.