Recharge, defining the renewal rate of groundwater resources, is difficult to estimate at basin scale. Here, recharge variations are inferred from water table variations recorded in boreholes. First, results show that aquifer-scale properties controlling these variations can be inferred from boreholes. Second, groundwater is recharged by both intense and seasonal rainfall. Third, the short-term contribution appears overestimated in recharge models and depends on the unsaturated zone thickness.

While land surface models are a common approach for estimating macroscale snow water equivalent (SWE), the SWE accuracy is often limited by uncertainties in model physics and forcing inputs. In this study, we found large underestimations of modeled SWE compared to observations. Precipitation forcings and melting physics limitations dominantly contribute to the SWE underestimations. Results provide insights into prioritizing strategies to improve the SWE simulations for hydrologic applications.

Extreme rainfall events are major concerns in Bangladesh. Heavy downpours can cause flash floods and damage nearly harvestable crops in pre-monsoon season. While in monsoon season, the impacts can range from widespread agricultural loss, huge property damage, to loss of lives and livelihoods. This paper assesses the role of anthropogenic climate change drivers in changing risks of extreme rainfall events during pre-monsoon and monsoon seasons at local sub-regional-scale within Bangladesh.

This study assesses the detailed water budget of the Saq–Ram Aquifer System using satellite gravity data. Spatial heterogeneities regarding the groundwater recharge were identified: (i) irrigation excess is great enough to artificially recharge the aquifer; and (ii) volcanic lava deposits, which cover 8% of the domain, contribute to more than 50% of the total natural recharge. This indicates a major control of geological context on arid aquifer recharge, which has been poorly discussed hitherto.

The productivity of semiarid grazed grasslands is linked to the variation in rainfall and transpiration. By combining carbon dioxide and water flux measurements, we show that the annual transpiration is nearly constant during wet years while grasses react quickly to dry spells and drought, which reduce transpiration. The planning of annual grazing strategies could consider the early-season rainfall frequency that was linked to the portion of annual transpiration.

Hydrologists have long dreamed of a tool that could adequately predict runoff in catchments. Data-driven long short-term memory (LSTM) models appear very promising to the hydrology community in this respect. Here, we have sought to benefit from traditional practices in hydrology to improve the effectiveness of LSTM models. We discovered that one LSTM parameter has a hydrologic interpretation and that there is a need to increase the data and to tune two parameters, thereby improving predictions.

In this study, we set up a water quality model using a 5-year paired high-frequency water quality dataset from a large agricultural stream. The simulations were compared with the 15 min interval measurements and showed very good fits. Based on these, we quantified the N uptake pathway rates and efficiencies at daily, seasonal, and yearly scales. This study offers an overarching understanding of N processing in large agricultural streams across different temporal scales.

We systematically investigate the uncertainties in previously observed isotopic offsets between plant source water and water extracted by cryogenic vacuum distillation. Our results show that hydrogen isotope exchange between organic material and water is a real phenomenon. However, the isotopic offsets are rather influenced by the actual amount of extracted water, sublimation, and evaporation. Our findings will help improve interpretations of ecohydrological processes in isotope-based studies.

The way soils capture infiltrating water affects crops and natural vegetation as well as groundwater recharge. This retention of soil water is captured by a mathematical function that covers all water contents from very dry to water-saturated. Unfortunately, data in the dry range are often absent or unreliable. I modified an earlier function to be more robust in the absence of dry-range data, and present a computer program to estimate the parameters of the new function.

Hydrological models at high spatial resolution are computationally expensive. However, outputs from such models, such as the depth of the groundwater table, are often desired in high resolution. We developed a downscaling algorithm based on machine learning that allows us to increase spatial resolution of hydrological model outputs, alleviating computational burden. We successfully applied the downscaling algorithm to the climate-change-induced impacts on the groundwater table across Denmark.

A framework for assessing the reliability of urban drainage models is developed in this paper. The method applies observation data from water level sensors and model results for up to 10 years of data for 23 sites in two case areas in Odense, Denmark. With the use of signatures as a method to extract information from the time series, it is possible to differentiate the performance for different model objectives.

Achieving water security in poorly gauged regions is hindered by a lack of in situ hydrometeorological data. In this study, we validated nine existing gridded water resource reanalyses and eight evapotranspiration products in eight representative gauged basins in Central–West Africa. Our results show the strengths and and weaknesses of the existing products and that these products can be used to assess water security in ungauged basins. However, it is imperative to validate these products.

This study addresses the issue of increasing interest in the hydrological impacts of converting cropland to perennial forage cover in the Canadian Prairies. By developing customized models using the Cold Regions Hydrological Modelling (CRHM) platform, this long-term (1992–2013) modelling study is expected to provide stakeholders with science-based information regarding the hydrological impacts of land use conversion from annual crop to perennial forage cover in the Canadian Prairies.

Monitoring extreme flood events has long been a hot topic for hydrologists and decision makers around the world. In this study, we propose a new index incorporating satellite observations combined with meteorological data to monitor extreme flood events at sub-monthly timescales for the Yangtze River basin (YRB), China. The conclusions drawn from this study provide important implications for flood hazard prevention and water resource management over this region.