Under rapid ongoing climate change, accurate quantification of natural greenhouse gas emissions in aquatic environments such as lakes and ponds are needed to understand regulation and feedbacks. Building on the rapid development in wireless communication, sensors and computation technology, we here present a low-cost, open source, automated and remotely accessed and controlled device for carbon dioxide and methane fluxes from open water environments, along with tests showing their potential.

A big dataset of hydrologic events (rainfall and soil moisture) at a hillslope can be characterized by machine learning algorithm. An unsupervised machine learning algorithm was used to cluster the hydrologic events. The hillslope hydrological processes, vertical flow, and lateral flow were responsible for the distinctions between the event clusters. A supervised machine learning algorithm provided a decision tree to identify cluster of events without rainfall and antecedent soil moisture.

This work presents a laboratory facility designed to simulate saltwater intrusion in coastal aquifers, with the goal of providing benchmarks for numerical models. The experiment studies the evolution of the seawater wedge into a homogeneous aquifer also in case of a freshwater pumping. The agreement between the numerical and the experimental (photos and electrical resistivity tomography) results proves that the proposed facility can provide the aforementioned benchmark, even in complex cases.

Rivers show distinct behaviours that can be quantified with so-called hydrological signatures (e.g. the mean discharge). We used five well-understood hydrological signatures to sort 643 rivers from the United States, into ten behavioural groups. Those groups showed a distinction between the western and eastern United States. While the rivers in the western United States are mainly driven by climate, it is the topography in the eastern United States.

Rapid warming in the Arctic is causing increased permafrost temperatures and ground ice degradation. To study the effects of ice degradation on water distribution, tracer was applied to two end members of ice-wedge polygons – a ubiquitous landform in the Arctic. End member type was found to significantly affect water distribution as lower flux was observed with ice-wedge degradation. Results suggest ice degradation can influence partitioning of sequestered carbon as carbon dioxide or methane.

We propose an alternative model to simulate preferential soil water flow and tracer transport in soils with macropores. We advance the model of Zehe and Jackisch (2016) by two extensions: a) a new routine for solute transport within the soil matrix and b) the implementation of a 1-D preferential flow domain. The evaluation of the model with data of tracer field experiments and the sensitivity analyses reveal the feasibility and physical validity of the model structure and the transport approach.

How far can we reach in predicting river flow globally, using integrated catchment modelling and open global data? For the first time, a catchment model was applied world-wide covering the entire globe with relatively high resolution. The results show that stepwise calibration provided better performance than traditional modelling of the globe. The study highlights that open data and models are crucial to advance hydrological sciences by sharing knowledge and enabling transparent evaluation.

This paper attempts to find the relationship and further discusses the difference between two type generalized Nash models – the DLCM and the GNM. It is found that the main difference lies in the way to estimate the initial storage state. The GNM is the unique analytical solution of the Nash cascade model with a non-zero initial condition, and the DLCM is an approximate solution.

In this paper we show that major groundwater resources in the UK, many of which are used for drinking water, exhibit strong multi-year cycles. These cycles can account for up to 40 % of total groundwater level variance. Additionally we show that these cycles align with wide-spread groundwater droughts in recent history. By measuring the timescales of these recurring patterns, we estimate the onset of future groundwater droughts in the UK, allowing for improved water resource management.

An important part of the Arctic water cycle is the snow that falls in winter, which builds up into a snow pack and then melts in spring. To estimate the amount of snowfall, we use the water balance: precipitation is equal to evaporation plus riverflow plus change in soil moisture and lying snow. We use estimates of the latter to infer what the snowfall must have been and use this to correct the amount of snow in four data sets. This improves how a land surface model represents Arctic hydrology.

A database of soil moisture measurements was used to test the potential of a soil moisture database in estimating the SWBCs. Although the planting of the past decade have significantly increased the soils' water-holding ability, the magnitude of increase in most of the parameters was independent of the treatments. Significant variances were observed among the plots in both the cumulative irrigation volumes and deep drainages, and the ET demands for all the plots behaved pretty much the same.

This study assesses the usability of Weather Research and Forecasting (WRF) model simulated soil moisture for landslide monitoring in northern Italy between 2006 and 2015. Particularly three advanced Land Surface Model schemes (Noah, Noah-MP and CLM4) integrated with the WRF are used to provide comprehensive multi-layer soil moisture information. The results have shown Noah-MP at the surface soil layer with 30 % exceedance probability provides the best landslide monitoring performance.

We develop a new indicator of reservoir effects called rainfall-reservoir composite index (RRCI). RRCI, coupled by the effects of static reservoir capacity and scheduling-related multivariate rainfall (SRMR), has better performance than the previous indicator in terms of explaining the variation of the downstream floods affected by reservoir operation. Covariate-based flood frequency analysis using RRCI can provide more reliable downstream flood risk estimation.

China's so-called Three North Forest Shelter project has produced a vast area of forest in the semi-arid regions with the purpose of battling desertification, according to NASA's observations this project contributes a quarter of the global net increase in green vegetation coverage. Vegetation consumes water resources, which profoundly affect the fragile ecological environment. This research focus on observing the water consumption of trees in semi-arid areas using a new instrument.

Evapotranspiration (ET) rates and the properties regulating them are spatially heterogeneous at scales much smaller than typical Earth System Models (ESMs) grid cells. Averaging over this spatial heterogeneity leads to biased estimates of fluxes in ESMs. We quantified the effects of averaging over spatial heterogeneity on grid-cell-averaged ET rates across the globe. We showed as ET is a nonlinear function, averaging over sub-grid heterogeneity of drivers of ET, leads to overestimation of ET.

The environmental effects of the world's largest Three Gorges Dam (TGD) have been received worldwide attentions. It is the first dynamics monitoring of mid-channel bars (MCBs) in the downstream of TGD at large spatiotemporal scale. The study shows most of the MCBs are located in the lower reach. Small MCBs become shorter and wider whereas the others became slimmer in post-TGD period. Impacts from the TGD operation on the MCB dynamics could decrease along with the increasing distance from TGD.

In recent years many methods for statistical downscaling of the climate model outputs have been developed. Each statistical downscaling method (SDM) has strengths and limitations, but those are rarely evaluated. This paper proposes an approach to evaluate the skill of SDMs for the specific purpose of impact analysis in hydrology.

This research was undertaken to critically evaluate I₃₀, a widely-used measure of rainfall intensity. Originally proposed from field area in the USA, I₃₀ is now used internationally, in areas having very different rainfall duration and intensity. Results show that in long rainfall events, I₃₀ reflects only the rainfall of a brief fraction of the rainfall; likewise, it cannot be derived for short rainfall events. A versatile new index is proposed, the rainfall of the wettest 5 % of an event.

We developed and tested a conceptual model to estimate depression storage capacity (DSC) having small roughness values usually encountered in rainwater harvesting microcatchments in arid regions with only one fitting parameter. Results indicated that the developed linear model between DSC and the square root of the ration of random roughness (RR) to slope was significant. The model predicts depression storage of small relief at higher accuracy compared to other models found in the literature.

A new quasi-3D GIS-based model was developed by coupling a soil water balance model with MODFLOW iteratively for regional scale water flow modeling. The model was tested to be effective and efficient with well-maintained mass balance. The modeling framework was developed by Python script to wrap the coupled model with the pre- and post-process modules. The model is then used to evaluate groundwater recharge in a real-world irrigated area, which shows the model practicability in regional scales.

Urban drainage models are usually calibrated using a few events so that they accurately represent a real world site. This paper compares 14 single- and two-stage strategies for selecting these events and found significant variation between them in terms of model performance and the obtained values of model parameters. Calibrating parameters for green and impermeable areas in two separate steps improved model performance in the validation period while making calibration easier and faster.

High latitude, alpine environments are changing rapidly in response to warmer temperatures and associated impacts and feedbacks. We used streamflow and dissolved organic carbon concentrations and quality to better understand how different surface water bodies transport and process this dissolved material over multiple seasons and years. Information on quality provides insight into organic material sources and possible changes in composition related to higher summer rainfall and fall flow.

We focus on the role of precipitation on the high magnitude flood generation to explore in what extent such events could be explained by only atmospheric variables. The role of the precipitation accumulations prior to the flood day progressively decreases when considering floods of weaker magnitude, suggesting a higher diversity of processes involved in the generation of e.g. annual flooding. Our results open new perspectives for flood hazard assessments directly based on climate model outputs.