Fuzzy logic algorithm for runoff-induced sediment transport from bare soil surfaces

Utilizing the rainfall intensity, and slope data, a fuzzy logic algorithm was developed to estimate sediment loads from bare soil surfaces. Considering slope and rainfall as input variables, the variables were fuzzified into fuzzy subsets. The fuzzy subsets of the variables were considered to have triangular membership functions. The relations among rainfall intensity, slope, and sediment transport were represented by a set of fuzzy rules. The fuzzy rules relating input variables to the output variable of sediment discharge were laid out in the IF-THEN format. The commonly used weighted average method was employed for the defuzzification procedure.The sediment load predicted by the fuzzy model was in satisfactory agreement with the measured sediment load data. Predicting the mean sediment loads from experimental runs, the performance of the fuzzy model was compared with that of the artificial neural networks (ANNs) and the physics-based models. The results of showed revealed that the fuzzy model performed better under very high rainfall intensities over different slopes and over very steep slopes under different rainfall intensities. This is closely related to the selection of the shape and frequency of the fuzzy membership functions in the fuzzy model.     

Rain rate measurements over global oceans from IRS-P4 MSMR

In this paper rain estimation capability of MSMR is explored. MSMR brightness temperature data of six channels corresponding to three frequencies of 10, 18 and 21 GHz are colocated with the TRMM Microwave Imager (TMI) derived rain rates to find a new empirical algorithm for rain rate by multiple regression. Multiple correlation analysis involving various combinations of channels in linear and non-linear forms and rain rate from TMI is carried out, and thus the best possible algorithm for rain rate measurement was identified which involved V and H polarized brightness temperature measurements at 10 and 18 GHz channels. This algorithm explained about 82 per cent correlation (r) with rain rate, and 1.61 mm h^-1 of error of estimation. Further, this algorithm is used for generating global average rain rate map for two contrasting months of August (2000) and January (2001) of northern and southern hemispheric summers, respectively. MSMR derived monthly averaged rain rates are compared with similar estimates from TRMM Precipitation Radar (PR), and it was found that MSMR derived rain rates match well, quantitatively and qualitatively, with that from PR.     

A geomorphologic kinematic‐wave (GKW) model for estimation of floods from small alpine watersheds

A geomorphologic kinematic‐wave (GKW) model was developed for simulation of extreme floods from small alpine catchments. The GKW model couples the kinematic‐wave theory and the geomorphologic representation of the catchment based on the Horton–Strahler ordering scheme. The model was tested on two small alpine catchments in Switzerland, and the agreement between simulated and observed floods was good. Care must however be taken with the computation of slope and roughness parameters. Copyright © 1999 John Wiley & Sons, Ltd.     

Application of minimum relative entropy theory for streamflow forecasting

This paper develops and applies the minimum relative entropy (MRE) theory with spectral power as a random variable for streamflow forecasting. The MRE theory consists of (1) hypothesizing a prior probability distribution for the random variable, (2) determining the spectral power distribution, (3) extending the autocorrelation function, and (4) doing forecasting. The MRE theory was verified using streamflow data from the Mississippi River watershed. The exponential distribution was chosen as a prior probability in applying the MRE theory by evaluating the historical data of the Mississippi River. If no prior information is given, the MRE theory is equivalent to the Burg entropy (BE) theory. The spectral density obtained by the MRE theory led to higher resolution than did the BE theory. The MRE theory did not miss the largest peak at 1/12th frequency, which is the main periodicity of streamflow of the Mississippi River, but the BE theory sometimes did. The MRE theory was found to be capable of forecasting monthly streamflow with a lead time from 12 to 48 months. The coefficient of determination (r ²) between observed and forecasted stream flows was 0.912 for Upper Mississippi River and was 0.855 for Lower Mississippi River. Both MRE and BE theories were generally more reliable and had longer forecasting lead times than the autoregressive (AR) method. The forecasting lead time for MRE and BE could be as long as 48–60 months, while it was less than 48 months for the AR method. However, BE was comparable to MRE only when observations fitted the AR process well. The MRE theory provided more reliable forecasts than did the BE theory, and the advantage of using MRE is more significant for downstream flows with irregular flow patterns or where the periodicity information is limited. The reliability of monthly streamflow forecasting was the highest for MRE, followed by BE followed by AR.     

Hydrologic model-based Palmer indices for drought characterization in the Yellow River basin,China

The Palmer indices (PIs) that have been most widely used for drought monitoring and assessment are criticized for two main drawbacks: coarse hydrological accounting processes with a simplified two-stage bucket soil water balance model and arbitrary rules for defining drought properties and standardizing index values through limited calibration and comparison. In this study, we introduce a new proposal of the VIC hydrologic model-based Palmer drought scheme, where traditional PIs (e.g. PDSI) can readily be calculated on the basis of distributed finescale hydrologic simulations. Moreover, recent variants of PI (i.e., SPDI and SPDI-JDI) also provide a preferable standardization strategy that allows probabilistic invariability and better spatio-temporal comparability of computed drought indices. Using gridded meteorological forcing, soil and vegetation data to drive the three-layer VIC model, both non-VIC and VIC-based PIs are investigated to examine their performances for drought characterization and detection. Results indicate that VIC hydrologic model would allow for adjustments in statistical properties of computed PDSI and VIC-based SPDI is also preferable to PDSI for better statistical robustness and spatio-temporal consistency/comparability. Moreover, the joint SPDI-JDI has the strength of integrating multi-scale probabilistic properties and drought information released by individual SPDI, providing overall drought conditions that take into account the onset, persistence and termination of droughts. At proposed 0.25° grid scale, the VIC-based SPDI-JDI indicates high frequency and long total time of drought condition in the Yellow River basin (YRB), China. Although no significant temporal trends are found in identified drought duration and severity, both the seasonal and annual drought index values demonstrate a downward trend (higher drought intensity) for considerable proportions of the YRB. These findings imply high drought risk and potential drying stress for this region. The new framework of hydrologic model-based PIs can help to strengthen our knowledge and/or practices in regional drought monitoring and assessment.     

Estimation of extreme wave heights using GEOSAT measurements

Satellite technology has yielded a large database of global ocean wave heights which may be used for engineering applications. However, the sampling protocol used by the satellite leads to some difficulties in making use of these data for practical applications. These difficulties and techniques to estimate extreme wave heights using satellite measurements are discussed. Significant wave heights for a 50-year return period are estimated using GEOSAT measurements for several regions around North America. Techniques described here may be used for estimation of wave heights associated with any specified return interval in regions where buoy data are not readily available.     

Generic precursors to coastal earthquakes: Inferences from Denali fault earthquake

Recent research has shown evidence of strong coupling between the atmosphere and lithosphere in coastal regions, associating abnormal atmospheric phenomena to the occurrence of strong earthquakes. Surface latent heat flux (SLHF), total column water vapor (CWV), relative humidity (RH) and total ozone column (TOC), analyzed over the epicentral region of the Denali fault earthquake of November 3, 2002, exhibit anomalous behavior that could be related to the earthquake preparatory process and its occurrence. The complementary nature of the parameters provides strong support that the anomalous values were driven by lithospheric processes, rather than other atmospheric phenomena. Due to the wide availability of remote sensing observations of atmospheric parameters, the detection of anomalies can be used to mitigate the earthquake risks.     

Diagnosing peak-discharge power laws observed in rainfall–runoff events in Goodwin Creek experimental watershed

Observations from the Goodwin Creek experimental watershed (GCEW), Mississippi show that peak-discharge Q(A) and drainage area A are related, on average, by a power law or scaling relationship, Q(A) = αA^θ, during single rainfall–runoff events. Observations also show that α and θ change between events, and, based on a recent analysis of 148 events, observations indicate that α and θ change because of corresponding changes in the depth, duration, and spatial variability of excess-rainfall. To improve our physical understanding of these observations, a 5-step framework for diagnosing observed power laws, or other space-time patterns in a basin, is articulated and applied to GCEW using a combination of analysis and numerical simulations. Diagnostic results indicate how the power laws are connected to physical conditions and processes. Derived expressions for α and θ show that if excess-rainfall depth is fixed then there is a decreasing concave relationship between α and excess-rainfall duration, and an increasing and slightly convex relationship between θ and excess rainfall duration. These trends are consistent with observations only when hillslope velocity v_h is given a physically realistic value near 0.1 m/s. If v_h ? 0.1 m/s, then the predicted trends deviate from observed trends. Results also suggest that trends in α and θ can be impacted by the dependence of v_h and link velocity v_l on excess-rainfall rate.     

Extragalactic sources with one-sided radio structure

A list has been compiled of 49 extragalactic sources, most of them identified with quasars, that appear to have a one-sided (D₂ type) radio structure characterized by a single outer component displaced from a compact central (nuclear) component coincident with the optical object. The observed properties of a subsample of 28 D₂ quasars that have an overall angular size larger than 5 arcsec are briefly discussed and compared with those of normal (D1 type) double quasars. It is found that the central components in most D₂ sources account for more than half the total flux density at high frequencies in contrast to the D₁ quasars which generally have less than 20 per cent of their total flux density in a central component. This makes it very unlikely that D₂ sources are just those D1s in which there is a large intrinsic difference in the flux densities or separations of the two outer components. The observed properties of D₂ sources are easier to understand in the relativistic beaming interpretation in which their axes are inclined at smaller angles with the line of sight compared to D₁ sources.