Hydrology and Earth System Sciences Discussions 

About: Hydrology and Earth System Sciences Discussions is an academic journal. The journal publishes majorly in the area(s): Surface runoff & Streamflow. It has an ISSN identifier of 1812-2108. Over the lifetime, 1733 publications have been published receiving 9701 citations.

SWRC fit - a nonlinear fitting program with a water retention curve for soils having unimodal and bimodal pore structure

Abstract: . The soil hydraulic parameters for analyzing soil water movement can be determined by fitting a soil water retention curve to a certain function, i.e., a soil hydraulic model. For this purpose, the program "SWRC Fit," which performs nonlinear fitting of soil water retention curves to 5 models by Levenberg-Marquardt method, was developed. The five models are the Brooks and Corey model, the van Genuchten model, Kosugi's log-normal pore-size distribution model, Durner's bimodal pore-size distribution model, and a bimodal log-normal pore-size distribution model propose in this study. This program automatically determines all the necessary conditions for the nonlinear fitting, such as the initial estimate of the parameters, and, therefore, users can simply input the soil water retention data to obtain the necessary parameters. The program can be executed directly from a web page at http://purl.org/net/swrc/ ; a client version of the software written in numeric calculation language GNU Octave is included in the electronic supplement of this paper. The program was used for determining the soil hydraulic parameters of 420 soils in UNSODA database. After comparing the root mean square error of the unimodal models, the van Genuchten and Kosugi's models were better than the Brooks and Corey model. The bimodal log-normal pore-size distribution model had similar fitting performance to Durner's bimodal pore-size distribution model.

Variability of rainfall in Peninsular Malaysia

Abstract: . This study analyzed and quantified the spatial patterns and time-variability of rainfall in Peninsular Malaysia on monthly, yearly and monsoon temporal scales. We first obtained an overview of rainfall patterns through the analysis of 16 point data sources. The results led to choosing three distinct regions, i.e.~the east coast, inland and west coast regions. For detailed analysis, Shepard's interpolation scheme was applied to the station data to produce daily rainfall fields on a 0.05 degree resolution grids for the period 1971–2006. The rainfall characteristics in time and space derived from a frequency analysis were found to be distinctly different in these three regions. In the east coast region, monthly rainfall shows a significant periodicity dominated by an annual cycle, followed by a half-year cycle. The inland and west coast regions show that the dominant periodic fluctuations in the monthly rainfall are dominated by a half-year cycle, followed by an annual cycle. The long-term rainfall variability analysis shows that the dry and wet conditions in Peninsular Malaysia are not primarily governed by the ENSO events. The results from the individual regions suggest that although the relative variability is influenced by ENSO, local and regional conditions have an effect on the interannual rainfall variability, which is superimposed on the large-scale weather conditions. A significant increasing trends in annual rainfall (9.3 mm/year) and northeast monsoon rainfall (6.2 mm/monsoon) were only detected in the west coast region. No trend was found in the monthly rainfall, except for November in the west coast region. The spatial variation analysis shows that the east coast region, which received substantially higher amounts of rainfall during the northeast monsoon, has lower spatial rainfall variability and a more uniform rainfall distribution than other regions. A larger range for the monthly spatial variation was observed in the west coast region.

Mekong River flow and hydrological extremes under climate change

Abstract: . Climate change poses critical threats to water-related safety and sustainability in the Mekong River basin. Hydrological impact signals from earlier Coupled Model Intercomparison Project phase 3 (CMIP3)-based assessments, however, are highly uncertain and largely ignore hydrological extremes. This paper provides one of the first hydrological impact assessments using the CMIP5 climate projections. Furthermore, we model and analyse changes in river flow regimes and hydrological extremes (i.e. high-flow and low-flow conditions). In general, the Mekong's hydrological cycle intensifies under future climate change. The scenario's ensemble mean shows increases in both seasonal and annual river discharges (annual change between +5 and +16 %, depending on location). Despite the overall increasing trend, the individual scenarios show differences in the magnitude of discharge changes and, to a lesser extent, contrasting directional changes. The scenario's ensemble, however, shows reduced uncertainties in climate projection and hydrological impacts compared to earlier CMIP3-based assessments. We further found that extremely high-flow events increase in both magnitude and frequency. Extremely low flows, on the other hand, are projected to occur less often under climate change. Higher low flows can help reducing dry season water shortage and controlling salinization in the downstream Mekong Delta. However, higher and more frequent peak discharges will exacerbate flood risks in the basin. Climate-change-induced hydrological changes will have important implications for safety, economic development, and ecosystem dynamics and thus require special attention in climate change adaptation and water management.

Klinkenberg effect for gas permeability and its comparison to water permeability for porous sedimentary rocks

Abstract: . The difference between gas and water permeabilities is significant not only for solving gas-water two-phase flow problems, but also for quick measurements of permeability using gas as pore fluid. We have measured intrinsic permeability of sedimentary rocks from the Western Foothills of Taiwan, using nitrogen gas and distilled water as pore fluids, during several effective-pressure cycling tests at room temperature. The observed difference in gas and water permeabilities has been analyzed in view of the Klinkenberg effect. This effect is due to slip flow of gas at pore walls which enhances gas flow when pore sizes are very small. Experimental results show (1) that gas permeability is larger than water permeability by several times to one order of magnitude, (2) that gas permeability increases with increasing pore pressure, and (3) that water permeability slightly increases with increasing pore-pressure gradient across the specimen. The results (1) and (2) can be explained by Klinkenberg effect quantitatively with an empirical power law for Klinkenberg constant. Thus water permeability can be estimated from gas permeability. The Klinkenberg effect is important when permeability is lower than 10−18 m2 and at low differential pore pressures, and its correction is essential for estimating water permeability from the measurement of gas permeability. A simple Bingham-flow model of pore water can explain the overall trend of the result (3) above. More sophisticated models with a pore-size distribution and with realistic rheology of water film is needed to account for the observed deviation from Darcy's law.

A statistical post-processor for accounting of hydrologic uncertainty in short-range ensemble streamflow prediction

Abstract: . In addition to the uncertainty in future boundary conditions of precipitation and temperature (i.e. the meteorological uncertainty), parametric and structural uncertainties in the hydrologic models and uncertainty in the model initial conditions (i.e. the hydrologic uncertainties) constitute a major source of error in hydrologic prediction. As such, accurate accounting of both meteorological and hydrologic uncertainties is critical to producing reliable probabilistic hydrologic prediction. In this paper, we describe and evaluate a statistical procedure that accounts for hydrologic uncertainty in short-range (1 to 5 days ahead) ensemble streamflow prediction (ESP). Referred to as the ESP post-processor, the procedure operates on ensemble traces of model-predicted streamflow that reflect only the meteorological uncertainty and produces post-processed ensemble traces that reflect both the meteorological and hydrologic uncertainties. A combination of probability matching and regression, the procedure is simple, parsimonious and robust. For a critical evaluation of the procedure, independent validation is carried out for five basins of the Juniata River in Pennsylvania, USA, under a very stringent setting. The results indicate that the post-processor is fully capable of producing ensemble traces that are unbiased in the mean and in the probabilistic sense. Due primarily to the uncertainties in the cumulative probability distributions (CDF) of observed and simulated flows, however, the unbiasedness may be compromised to a varying degree in real world situations. It is also shown, however, that the uncertainties in the CDF's do not significantly diminish the value of post-processed ensemble traces for decision making, and that probabilistic prediction based on post-processed ensemble traces significantly improves the value of single-value prediction at all ranges of flow.