This paper reviews the status of hydrological modeling in the mountainous region of central Asia, discussing the limitations of the available models and shedding light on future directions. We conclude that the main sources of uncertainty in hydrological modeling are the input uncertainty and lack of understanding of the hydrological regimes. Future focuses should be on the use of multi-source of input data combined with multi-objective calibration and validation.

Most of the rain falling on land is returned to the atmosphere by plant leaves, which release water vapour (transpire) through tiny pores. To better understand this process, we used artificial leaves in a special wind tunnel and discovered major problems with an established approach (PM equation) widely used to quantify transpiration and its sensitivity to climate change. We present an improved set of equations, consistent with experiments and displaying more realistic climate sensitivity.

We developed a method to characterize the distribution and variance of the hydraulic conductivity k in a multiple-zone alluvial fan by fusing multiple-source data. Consistently with the scales of the sedimentary transport energy, the k variance of the various facies decreases from the upper to the lower portion along the flow direction. The 3-D distribution of k is consistent with that of the facies. The potentialities of the proposed approach are tested on the Chaobai River megafan, China.

The distributed hydrological model has not yet been applied in large watershed flood forecasting due to some limitations. By proposing a method for estimating channel cross section size with remote sensing data, employing the PSO algorithm optimize model parameters and running the model on high-performance supercomputer with parallel computation technique, this article successfully applied the Liuxihe model in a larger watershed flood forecasting in southern China at high resolution.

We use water level observations from the CryoSat-2 satellite in combination with a river model of the Brahmaputra River, extracting satellite data over a dynamic river mask derived from Landsat imagery. The novelty of this work is the use of the CryoSat-2 water level observations, collected using a complex spatio-temporal sampling scheme, to calibrate a hydrodynamic river model. The resulting model accurately reproduces water levels, without precise knowledge of river bathymetry.

Recent developments have made it possible to easily crowdsource meteorological measurements from automatic personal weather stations worldwide. This has offered free access to rainfall ground measurements at spatial and temporal resolutions far exceeding those of national operational sensor networks, especially in cities. This paper is the first step to make optimal use of this promising source of rainfall measurements and identify challenges for future implementation for urban applications.

This research seeks out to answer a fundamental question about the functioning of the water cycle in the atmosphere: how much time does a water particle spend in the atmosphere? Based on state-of-the-art data, we derive a global average residence time of water in the atmosphere of 8–10 days. We further show in this paper how the residence time of water varies in time and space. This serves to illustrate why it is so difficult to make weather predictions on timescales longer than a week.

We assess water scarcity under various socio-economic pathways and its impact on food production in the Yellow River basin. The rapidly increasing industrial water demand will put the middle and lower reaches in a condition of water scarcity. The industrial water demand is the main contributing factor to water scarcity. Water scarcity will lead to at least 9 % reduction in food production in 2084. This suggests that a trade-offs should be considered when developing regional adaptation strategies.

This study analyses the subgrid variability of the snow distribution in a Mediterranean region and formulates a parametric approach that includes these scale effects in the physical modelling of snow by means of accumulation–depletion curves associated with snow evolution patterns, by means of terrestrial photography. The results confirm that the use of these on a cell scale provides a solid foundation for the extension of point snow models to larger areas.

Global numerical models perform differently, as has been found in some model intercomparison studies, which mainly focused on components like evapotranspiration, soil moisture or runoff. We have applied terrestrial water storage that is estimated from a GRACE-based state-of-art post-processing method to validate four global numerical models and try to identify the advantages and deficiencies of a certain model. GRACE-based TWS demonstrates its additional benefits to improve the models in future.

This study assesses the potential use of crowdsourced data in hydrological modeling, which are characterized by irregular availability and variable accuracy. We show that even data with these characteristics can improve flood prediction if properly integrated into hydrological models. This study provides technological support to citizen observatories of water, in which citizens can play an active role in capturing information, leading to improved model forecasts and better flood management.

Seasonal and inter-annual features of E_T were analyzed over four periods. A normalization method was adopted to exclude the effects of potential evapotranspiration and soil water stress on E_T. During the land degradation process, when natural vegetation (including leaves and branches), sand dunes, dry sand layers, and BSCs were all bulldozed, E_T was observed to increase at a mild rate. In a vegetation rehabilitation process with sufficient groundwater, E_T also increased at a faster rate.

This study presents and compares two different approaches to using satellite-derived estimates of actual evapotranspiration (ET) to improve the performance of a conceptual rainfall–runoff model. In the first approach, the ET process within the model is constrained using the satellite ET estimates, while in the second one, the model structure is altered. Results indicate that both the approaches improve streamflow forecasting, while the second one also improves the ET simulations significantly.

During August 2016, heavy precipitation led to devastating floods in south Louisiana, USA. Here, we analyze the climatological statistics of the precipitation event, as defined by its 3-day total over 12–14 August. Using observational data and high-resolution global coupled model experiments, we find for a comparable event on the central US Gulf Coast an average return period of about 30 years and the odds being increased by at least 1.4 since 1900 due to anthropogenic climate change.

Understanding how groundwater and streamflow interact over large areas is a challenge. In this study we use a computer simulation that calculates water movement and storage at the land surface and in the subsurface within California's San Joaquin River basin to analyze different parts of the watershed. Results show that the mountains may be an important source of groundwater to the Central Valley while differences in relative speed of groundwater and river flow affect their connection patterns.

Do you feel angry if the river in your living place is polluted by industries? Do you want to do something to save your environment? Just log in to http://www.thuhjjc.com and use the Tsinghua Environment Monitoring Platform (TEMP) to photograph the water pollution actives and make your report. This study established a social media platform to monitor and report surface water quality. The effectiveness of the platform was demonstrated by the 324 water quality reports across 30 provinces in China.

The study presents validation of precipitation events as simulated by an ensemble of regional climate models for the Czech Republic. While the number of events per season, seasonal total precipitation due to heavy events and the distribution of rainfall depths are simulated relatively well, event maximum precipitation and event intensity are strongly underestimated. This underestimation cannot be explained by scale mismatch between point observations and area average (climate model simulations).

Our long-term results are relevant to land areas that are in pasture and those that have reverted back to forests. We found that within a deciduous forest, species identity matters in terms of how much precipitation leaves the watershed as evapotranspiration versus water yield. We demonstrate that a shift in tree species composition from species with ring-porous xylem to species with diffuse-porous xylem can increase water use, and in turn, produce a long-term reduction in water yield.

We develop a fusion framework to improve precipitation estimation by jointly utilizing the gauge precipitation and vegetation index and then applying them to mountainous areas of the Nu River basin. The results demonstrate the reliability of the framework in reproducing the high-resolution precipitation regime and capturing its high spatial variability in the Nu River basin. The framework can significantly reduce the errors in precipitation estimates as compared with the IDW and TRMM methods.

This work explores the utility of a thermal remote sensing based MODIS/Landsat ET data fusion procedure over a mixed forested/agricultural landscape in North Carolina, USA. The daily ET retrieved at 30 m resolution agreed well with measured fluxes in a clear-cut and a mature pine stand. An accounting of consumptive water use by land cover classes is presented, as well as relative partitioning of ET between evaporation (E) and transpiration (T) components.

Beaver ponds are found in many landscapes and their transient nature makes it difficult to account for the surface water they store using traditional methods. We found that reliable estimates of surface water storage in beaver ponds can be made with simple measurements of pond depth and surface area. This makes it possible for hydrologists and environmental managers to include beaver ponds in models and land use planning decisions without the need for resource intensive topographic surveys.

The human use of water for irrigation is often ignored in models and operational forecasts. We describe four plausible and relatively simple irrigation routines that can be coupled to the next generation of models. The routines are tested against a unique irrigation dataset from western Nebraska. The most aggressive water-saving irrigation routine indicates a potential irrigation savings of 120 mm yr⁻¹ and yield losses of less than 3 % against the crop model benchmark and historical averages.

A complicating factor in describing the flow of two immiscible fluids in a porous medium is ensuring that experiments, theory, and simulation are all formulated at the same length scale. We have quantitatively analyzed the internal structure of a two-fluid system including the distribution of phases and the location of interfaces between phases. The data we have obtained allow for a clearer definition of capillary pressure at the averaged scale as a state function that describes the system.

In this study we develop a method to estimate the spatially averaged rainfall intensity together with associated level of uncertainty using geostatistical upscaling. Rainfall data collected from a cluster of eight paired rain gauges in a small urban catchment are used in this study. Results show that the prediction uncertainty comes mainly from two sources: spatial variability of rainfall and measurement error. Results from this study can be used for uncertainty analyses of hydrologic modelling.

This is the first work on the internal seiches of the South Aral Sea, which is also of general interest as the lake is considered a paradigm for the lakes whose surface levels are decreasing. It is based on field data and numerical simulations. For autumn 2006 and 2013, the fundamental mode is discussed together with other modes which are found to be higher vertical modes. The importance of sea level variation on the development of higher horizontal modes is also discussed.

The natural environment that we live in is the result of evolution. This does not only apply to ecosystems, but also to the physical environment through which the water flows. This has resulted in the formation of flow patterns that obey sometimes surprisingly simple mathematical laws. Hydrological models should represent the physics of these patterns and should account for the fact that the ecosystem adjusts itself continuously to changing circumstances. Physics-based models are alive!

We evaluate the impact of groundwater–surface water exchanges on the fraction of precipitation that leaves a watershed as either surface runoff or evapotranspiration. Results show that groundwater storage can systematically influence watershed behavior at the land surface. This is an important finding because most studies of tradeoffs between runoff and evapotranspiration assume that watersheds are in a steady-state condition where there are no net exchanges between the surface and subsurface.

We present a coupled modeling approach used to objectively identify representative snow-monitoring locations in a forested watershed in the western Oregon Cascades mountain range. The resultant Forest Elevational Snow Transect (ForEST) represents combinations of forested and open land cover types at low, mid-, and high elevations.

New Zealand is a natural laboratory for investigating water quality responses to land use intensity because it has one of the highest rates of agricultural intensification globally over recent decades. We interpreted water quality state and trends (1989–2014) of 77 river sites across NZ. We show that the greatest long-term negative impacts on river water quality have been increased cattle densities and legacy nutrients from intensively managed grasslands and plantation forests.

The subsurface is increasingly perforated for exploitation of water and energy. This has increased the risk of leakage between originally separated aquifers. It is shown how this leakage can have a very negative impact on the recovery of freshwater during aquifer storage and recovery (ASR) in brackish-saline aquifers. Deep interception of intruding brackish-saline water can mitigate the negative effects and buoyancy of freshwater to some extent, but not completely.

We present a dataset of daily meteorological variables at 1 km resolution over Great Britain (1961–2012), calculated by spatially downscaling coarser resolution datasets, adjusting for local topography, along with derived potential evapotranspiration (PET). A positive trend in PET was identified and attributed to trends in the meteorology. The trend in PET is particularly driven by decreasing relative humidity and increasing shortwave radiation in the spring.

In this study we examine whether we can step beyond the qualitative character of perceptual models by using them as a blueprint for setting up representative hillslope models. Thereby we test the hypothesis of whether a single hillslope can represent the functioning of an entire lower mesoscale catchment in a spatially aggregated way.

Estimates of evapotranspiration are vital for validation of models. However, those datasets are often limited to research applications. Here, we explore using vadose zone modeling with widespread and readily available soil water content monitoring networks. While this work focused on one agricultural site, the framework can be used everywhere there is basic data. The resulting evapotranspiration and soil water content measurements are valuable benchmarks for evaluation of land surface models.

Quantitative precipitation forecast produced by the WRF model has a similar pattern to that estimated by rain gauges in a southern China large watershed, hydrological model parameters should be optimized with QPF produced by WRF, and simulating floods by coupling the WRF QPF with a distributed hydrological model provides a good reference for large watershed flood warning and could benefit the flood management communities due to its longer lead time.

This work exhaustively evaluates – for the first time – the suitability of seven state-of-the-art satellite-based rainfall estimates (SREs) over the complex topography and diverse climatic gradients of Chile. Several indices of performance are used for different timescales and elevation zones. Our analysis reveals what SREs are in closer agreement to ground-based observations and what indices allow for understanding mismatches in shape, magnitude, variability and intensity of precipitation.

This study presents a new method for coupling a 3-D geophysical model with a 3-D groundwater model for improved groundwater model construction and prediction accuracy. The hydrological data consist of 35 hydraulic head measurements and one river discharge measurement, while the geophysical data set consists of 6300 measurement positions. The results demonstrate that the geophysical inversion strategy significantly affects the construction and prediction capability of the groundwater model.