A remote sensing algorithm named temperature sharpening and flux aggregation (TSFA) was applied to HJ-1B satellite data to estimate evapotranspiration over heterogeneous surface considering landscape and statistical effects on mixed pixels. Footprint validation results showed TSFA was more accurate and less uncertain than other two upscaling methods. Additional analysis and comparison showed TSFA can capture land surface heterogeneities and integrate the effect of landscapes within mixed pixels.

This is the first observation of tree water use in cave drip water. Our novel time series analysis using the synchrosqueeze transform identified daily and sub-daily oscillations in drip rate. The only hypothesis consistent with hydrologic theory and the data was that the oscillations were caused by solar driven pumping by trees above the cave. We propose a new protocol for inferring karst architecture and our findings support research on the impact trees on speleothem paleoclimate proxies.

The ridge–slough landscape is a major part of the Everglades, a critically imperiled wetland in south Florida (USA). The landscape consists of two wetland types, shallow water ridges and deep water sloughs, interspersed in a complex pattern. Human changes to hydrology have changed this pattern, impacting water flow, fish movement, and bird habitat. Restoring pattern requires understanding its origins. We describe the pattern in detail, gaining insights relevant for management on its origins.

The paper finds that combined inflow from both current and previous years' discharge determines water availability in downstream regions. Temperature determines broad vegetation distribution while hydrological variables show significant effects only in near-river-channel regions. Agricultural development curtailed further vegetation recovery in the studied area. Enhancing current water allocation schemes and regulating regional agricultural activities are required for future restoration.

We present a new method that incorporates flood-envelope-curve methods, radar-derived precipitation data, and flow-routing algorithms to calculate frequency-magnitude-area curves (FMAC). Our results show that flood discharges increase as a power-law function for small contributing areas, but start to increase more slowly at higher contributing areas. We find that our FMACs have similar and/or higher flood discharges than published flood-envelope curves for the same areas.

We present a new method to derive the empirical (i.e., data-based) elasticity of streamflow to precipitation and potential evaporation. This method, which uses long-term hydrometeorological records, is tested on a set of 519 French catchments. We compare our method with the classical approach found in the literature and demonstrate its robustness and efficiency. Empirical elasticity is a powerful tool to test the extrapolation capacity of hydrological models.

A variety of threshold mechanisms influence the transfer of rainfall to runoff from catchments. Some of these mechanisms depend on the occurrence of intense rainfall and others depend on the catchment being wet. This article first provides a framework for considering which mechanisms are important in different situations and then uses that framework to examine the behaviour of a catchment in Australia that exhibits a mix of both rainfall intensity and catchment wetness dependent thresholds.

Benchmarks for the water footprint (WF) of crop production can serve as a reference and be helpful in setting WF reduction targets. The study explores which environmental factors should be distinguished when determining benchmarks for the consumptive (green and blue) WF of crops. Through a case study for winter wheat in China over 1961–2008, we find that when determining benchmark levels for the consumptive WF of a crop, it is most useful to distinguish between different climate zones.

The paper addresses the issue of sampling errors when using the ensemble Kalman filter, in particular its hybrid and second-order formulations. The presented work is aimed at estimating concentration and biodegradation rates of subsurface contaminants at the port of Rotterdam in the Netherlands. Overall, we found that accounting for both forecast and observation sampling errors in the joint data assimilation system helps recover more accurate state and parameter estimates.

This paper focuses on performance evaluation of simplified, physically based landslide susceptibility models. It presents a new methodology to systemically and objectively calibrate, verify, and compare different models and models performances indicators in order to individuate and select the models whose behavior is more reliable for a certain case study. The procedure was implemented in a package for landslide susceptibility analysis and integrated the open-source hydrological model NewAge.

Most statistically based seasonal precipitation forecast models utilize a small set of well-known climate indices as potential predictor variables. However, for many target regions, these indices do not lead to sufficient results and customized predictors are required for an accurate prediction. This study presents a statistically based routine, which automatically identifies suitable predictors from globally gridded SST and climate variables by means of an extensive data mining procedure.

We investigated the potential use of trace element and stable oxygen-isotope variations in cave drip water as palaeorainfall proxies in an Australian alpine karst site. Using 7 years of cave monitoring data, we constrained the hydrological processes impacting the drip-water composition and identified a robust ENSO–drip water hydrochemical relationship. These findings are fundamental for reconstructing past ENSO variability from speleothems (cave deposits) regionally and globally.

Ten algorithms for estimating DL and one for UL are integrated in a new model (LWRB) and connected to hydrological model JGrass-NewAge. The algorithms are tested against energy flux measurements available for 24 sites in North America to assess their reliability. We evaluated the performances of simplified models (SMs) of DL, as presented in literature formulations, and determined by automatic calibration the site-specific parameter sets for SMs of DL to improve model predictions.

Results of this study indicate that it is possible to identify the influence of different hydrologic processes when simulating with a distributed-parameter hydrology model on the basis of parameter sensitivity analysis. Identification of these processes allows the modeler to focus on the more important aspects of the model input and output, which can simplify all facets of the hydrologic modeling application.

Drought propagation from rainfall deficits to reservoir depletion was studied based on remote sensing, monitoring and modelling data. Regional droughts were shown by widespread depletion in total water storage that reduced soil moisture storage and runoff, greatly reducing reservoir storage. The multidisciplinary approach to drought assessment shows the linkages between meteorological and hydrological droughts that are essential for managing water resources subjected to climate extremes.

We demonstrate that the classical approach to solve the surface energy balance equation in land surface models has its issues, and we propose an improved method.