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1

Usefulness of the Modified NRCS-CN Method for the Assessment of Direct Runoff in a Mountain Catchment

Wałęga A., Rutkowska A.

Acta Geophysica

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2015

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Vol. 63, no. 5

1423--1446

EN

The aim of this study was to evaluate the usefulness of modified methods, developed on the basis of NRCS-CN method, in determining the size of an effective rainfall (direct runoff). The analyses were performed for the mountain catchment of the Kamienica river, right-hand tributary of the Dunajec. The amount of direct runoff was calculated using the following methods: (1) Original NRCS-CN model, (2) Mishra- Singh model (MS model), (3) Sahu-Mishra-Eldho model (SME model), (4) Sahu 1-p model, (5) Sahu 3-p model, and (6) Q_base model. The study results indicated that the amount of direct runoff, determined on the basis of the original NRCS-CN method, may differ significantly from the actually observed values. The best results were achieved when the direct runoff was determined using the SME and Sahu 3-p model.

2

On regularized time varying gravity field models based on GRACE data and their comparison with hydrological models

Eshagh M., Lemoine J.-M., Gegout P., Biancale R.

Acta Geophysica

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2013

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Vol. 61, no. 1

1--17

EN

Determination of spherical harmonic coefficients of the Earth’s gravity field is often an ill-posed problem and leads to solving an ill-conditioned system of equations. Inversion of such a system is critical, as small errors of data will yield large variations in the result. Regularization is a method to solve such an unstable system of equations. In this study, direct methods of Tikhonov, truncated and damped singular value decomposition and iterative methods of v, algebraic reconstruction technique, range restricted generalized minimum residual and conjugate gradient are used to solve the normal equations constructed based on range rate data of the gravity field and climate experiment (GRACE) for specific periods. Numerical studies show that the Tikhonov regularization and damped singular value decomposition methods for which the regularization parameter is estimated using quasioptimal criterion deliver the smoothest solutions. Each regularized solution is compared to the global land data assimilation system (GLDAS) hydrological model. The Tikhonov regularization with L-curve delivers a solution with high correlation with this model and a relatively small standard deviation over oceans. Among iterative methods, conjugate gradient is the most suited one for the same reasons and it has the shortest computation time.

3

Modelling flow changes in potential climate change conditions - an example of the Kaczawa basin

Kuchar L., Iwański S., Jelonek L., Szalińska W.

Studia Geotechnica et Mechanica

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2012

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Vol. 34, nr 2

51-62

EN

Climate change, regardless of the causes shaping its rate and direction, can have far-reaching environmental, economic and social impact. A major aspect that might be transformed as a result of climate change are water resources of a catchment. The article presents a possible method of predicting water resource changes by using a meteorological data generator and classical hydrological models. The assessment of water resources in a catchment for a time horizon of 30-50 years is based on an analysis of changes in annual runoff that might occur in changing meteorological conditions. The model used for runoff analysis was the hydrological rainfall-runoff NAM model. Daily meteorological data essential for running the hydrological model were generated by means of SWGEN model. Meteorological data generated for selected climate change scenarios (GISS, CCCM and GFDL) for the years 2030 and 2050 enabled analysing different variants of climate change and their potential effects. The presented results refer to potential changes in water resources of the Kaczawa catchment. It should be emphasized that the obtained results do not say which of the climate change scenarios is more likely, but they present the consequences of climate change described by these scenarios.

4

A neural network relation of GPS results with continental hydrology

Ogaja C.

Artificial Satellites : Journal of Planetary Geodesy

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2006

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Vol. 41, No. 1

23--32

EN

This paper presents the application of a neural network methodology to historical time series of GPS data from the IGS (International GPS Service) network, based on terrestrial water storage information. Hydrology signals at the GPS sites are important for including water loading corrections in GPS data processing. However, it is quite common that a correct global water storage model may not be available for this purpose, due to lack of science data. It is therefore mostly assumed that water mass redistribution is one of the potential contributors to the seasonal variations in GPS station position results, particularly, in the vertical direction. Presently, the IERS Special Bureau for Hydrology (SBH) has archived continental water storage data from some of the latest model developments. Examples include the monthly (GRACE, NOAA CPC, NCEP/NCAR CDAS-1) and daily (NCEP/NCAR and ECMWF reanalyses) solutions. It is valuable to study the relationship between these solutions and long-term geodetic results, especially as the water storage models continue to be refined. Using neural networks offers an effective approach to correlate the non-linear input of hydrology signals and output of geodetic results by recognizing the historic patterns between them. In this study, a neural network model is developed to enable the prediction of GPS height residuals based on the input of NOAA CPC hydrology data. The model is applied to eight GPS sites with satisfactory results.

5

Hysteresis in hydrology

O'Kane J. P.

Acta Geophysica Polonica

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2005

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Vol. 53, nr 4

373-383

EN

Rate-independent hysteresis arising from the multi-valued soil-moisture char-acteristic has been ignored in almost all hydrological models. This paper introduces the concept of rate-independence in a hydrological context and shows how to insert rate-independent hysteresis in conceptual hydrological models using the single lin-ear reservoir as an example.