Earth system (climate) model is an important instrument for projecting the global water cycle and climate change, in which tides are commonly excluded due to the much small timescales compared to the climate. However, we found that tides significantly impact the river water transport pathways, transport timescales, and concentrations in shelf seas. Thus, the tidal effect should be carefully considered in earth system models to accurately project the global water and biogeochemical cycle.

Despite its advantages for the simulation of flow in heterogeneous and fractured porous media, the mixed hybrid finite element method has been rarely used for transport as it suffers from strong unphysical oscillations. We develop here a new upwind scheme for the mixed hybrid finite element that can avoid oscillations. Numerical examples confirm the robustness of this new scheme for the simulation of contaminant transport in both saturated and unsaturated conditions.

We present a new approach to estimate extreme rainfall probability and severity using the atmospheric water balance, where precipitation is the sum of water vapor components moving in and out of a storm. We apply our method to the Mississippi Basin and its five major subbasins. Our approach achieves a good fit to reference precipitation, indicating that the rainfall probability estimation can benefit from additional information from physical processes that control rainfall.

An improved GIS-derived distributed unit hydrograph routing method considering time-varying soil moisture was proposed for flow routing. The method considered the changes of time-varying soil moisture and rainfall intensity. The response of underlying surface to the soil moisture content was considered an important factor in this study. The SUH, DUH, TDUH and proposed routing methods (TDUH-MC) were used for flood forecasts, and the simulated results were compared and discussed.

Variable infiltration capacity simulation considering dynamic vegetation types and structural parameters is able to better capture the effect of temporally explicit vegetation change and climate variation in hydrological regimes. Vegetation greening including interannual LAI and intra-annual LAI temporal pattern change induced by large-scale ecological restoration and non-vegetation underlying surface change played dominant roles in the natural streamflow reduction of the Yellow River basin.

In this study, we proposed a new framework that considered the uncertainties of model simulations in quantifying the contribution rate of climate change and human activities to streamflow changes. Then, the Lancang River basin was selected for the case study. The results of quantitative analysis using the new framework showed that the reason for the decrease in the streamflow at Yunjinghong station was mainly human activities.

We adapt the informal Kling–Gupta efficiency (KGE) with a gamma distribution to apply it as an informal likelihood function in the DiffeRential Evolution Adaptive Metropolis DREAM_(ZS) method. Our adapted approach performs as well as the formal likelihood function for exploring posterior distributions of model parameters. The adapted KGE is superior to the formal likelihood function for calibrations combining multiple observations with different lengths, frequencies and units.

Of all the planting options for wood production and carbon storage, Eucalyptus species provoke the greatest concern about their effect on water resources. We compared Eucalyptus and Pinus species (the two most widely planted genera) by fitting a simple model to the published estimates of their annual water use. There was no significant difference between the two genera. This has important implications for the global debate around Eucalyptus and is an option for carbon forests.

A farm-scale hydroclimatic machine learning framework to advise farmers was developed. FarmCan uses remote sensing data and farmers' input to forecast crop water deficits. The 8 d composite variables are better than daily ones for forecasting water deficit. Evapotranspiration (ET) and potential ET are more effective than soil moisture at predicting crop water deficit. FarmCan uses a crop-specific schedule to use surface or root zone soil moisture.

The goal of this work was to make a map of the mean annual runoff for Norway for a 30-year period. We first simulated runoff by using a process-based model that models the relationship between runoff, precipitation, temperature, and land use. Next, we corrected the map based on runoff observations from streams by using a statistical method. We were also able to use data from rivers that only had a few annual observations. We find that the statistical correction improves the runoff estimates.

This study presents the climatology of the observed land–atmosphere interactions on a subdaily timescale during the warm season from flux site observations. Multivariate metrics are employed to examine the land, atmosphere, and combined couplings, and a mixing diagram is adopted to understand the coevolution of the moist and thermal energy budget within the atmospheric mixed layer. The diurnal cycles of both mixing diagrams and hourly land–atmosphere couplings exhibit hysteresis.