Improving the calibration strategy of the physically-based model WaSiM-ETH using critical events

Abstract

The use of a physically-based hydrological model for streamflow forecasting is limited by the complexity in the model structure and the data requirements for model calibration. The calibration of such models is a difficult task, and running a complex model for a single simulation can take up to several days, depending on the simulation period and model complexity. The information contained in a time series is not uniformly distributed. Therefore, if we can find the critical events that are important for identification of model parameters, we can facilitate the calibration process. The aim of this study is to test the applicability of the Identification of Critical Events (ICE) algorithm for physically-based models and to test whether ICE algorithm-based calibration depends on any optimization algorithm. The ICE algorithm, which uses the data depth function, was used herein to identify the critical events from a time series. Low depth in multivariate data is an unusual combination and this concept was used to identify the critical events on which the model was then calibrated. The concept is demonstrated by applying the physically-based hydrological model WaSiM-ETH on the Rems catchment, Germany. The model was calibrated on the whole available data, and on critical events selected by the ICE algorithm. In both calibration cases, three different optimization algorithms, shuffled complex evolution (SCE-UA), parameter estimation (PEST) and robust parameter estimation (ROPE), were used. It was found that, for all the optimization algorithms, calibration using only critical events gave very similar performance to that using the whole time series. Hence, the ICE algorithm-based calibration is suitable for physically-based models; it does not depend much on the kind of optimization algorithm. These findings may be useful for calibrating physically-based models on much fewer data.

Editor D. Koutsoyiannis; Associate editor A. Montanari

Citation Singh, S.K., Liang, J.Y., and Bárdossy, A., 2012. Improving calibration strategy of physically-based model WaSiM-ETH using critical events. Hydrological Sciences Journal, 57 (8), 1487–1505.     

Topo-stress based probabilistic model for shallow landslide susceptibility zonation in the Nepal Himalaya

While dealing with slope stability issues, determining the state of stress and the relation between driving force and resisting force are the fundamental deterministic steps. Gravitational stresses affect geologic processes and engineering operations in slopes. Considering this fact, a concept of topo-stress evaluation is developed in this research and used to produce a shallow landslide susceptibility map in a model area. The topo-stress introduced in this research refers to the shear stress induced by the gravitational forces on the planes parallel to the ground surface. Weight of the material on a slope and friction angle of the jointed rock mass are the two fundamental parameters that are considered to govern topo-stress in this study. Considering topo-stress as a main factor for initiating shallow landslides, a GIS-based probabilistic model is developed for shallow landslide susceptibility zonation. An ideal terrain in central Nepal is selected as the study area for this purpose. Two event-based shallow landslide inventories are used to predict accuracy of the model, which is found to be more than 78 % for the first event-landslides and more than 76 % for the second event-landslides. It is evident from these prediction rates that the probabilistic topo-stress model proposed in this work is quite acceptable when regional scale shallow landslide susceptibility mapping is practiced, such as in the Himalayan rocky slopes.     

Geochemical alterations in surface waters of Govind Ballabh Pant Sagar,Northern Coalfield,India

Major ions showed high concentrations, ionic strength and chemical activity in the surface waters of Govind Ballabh Pant Sagar reservoir. Various geochemical ratios showed the dominance of silicate over carbonate weathering and major ions such as Na⁺ + K⁺ account for about 52 % of the cation budget. The high Na⁺ and K⁺ showed sedimentation of rock/coal particles consisting of highly weathered silicate minerals contributed by the discharge of mine water, fly ash mixing during transportation, etc. Further, Ca²⁺ + Mg²⁺/Na⁺ + K⁺ ratio was <1 (0.92) indicating the occurrence of silicate weathering in the reservoir catchment. The comparative assessment showed that the proportion of Ca²⁺ + Mg²⁺/Na⁺ + K⁺ tends to be lower along the coal mining belts compared to non-coal mining regions in the world. The Ca²⁺/SO₄ ^2? ratio <1 revealed not only H₂CO₃ but H₂SO₄ also acting as a source of protons for rock weathering. The cause underlying these differences can be related directly to geological substrate and anthropogenic activities.     

Stable isotopic composition of precipitation in the River Bhagirathi Basin and identification of source vapour

River Ganges one of important rivers in the northern part of India receives water from two of its tributaries, Alaknanda and Bhagirathi. In this present study, we have tried to characterise the precipitation in the Bhagirathi River Basin. The study shows that isotopic composition of precipitation shows depleted nature during monsoon period due to moisture source from the oceanic region and from African region of Indian Ocean and enriched isotopic composition during non-monsoon period due to moisture source from westerlies and local evaporation. The study also shows that temperature and amount show expected positive and negative relationship with individual locations. A positive relationship is exhibited by amount for the entire region due to depleted isotopic composition with increase in altitude. The altitude effect shows that there is a depletion of up to ?0.24 to ?0.29 ‰ of isotopic composition with an increase in 100 m of elevation.     

Factors influencing the high fluoride concentration in groundwater of Vellore District,South India

Most of the arid and semi-arid zones of the Indian subcontinent experience serious health problems due to high concentration of fluoride in drinking water. The Vellore District of Tamil Nadu suffers from high concentration of fluoride in water. However, most of the past studies in this region focused on tannery-related pollution and not on fluoride contamination. The present study attempts to identify the factors influencing the origin and spatial distribution of fluoride in the district. From the observed hydrochemical results of 68 well samples in the context of water level, well depth and hydrochemical parameters, F^? concentration showed increasing trend in the presence of Na⁺ and HCO₃ ^?. This is due to the alkaline nature of groundwater that favors the dissolution of F^?-rich minerals. The occurrence of high fluoride in Na–HCO₃ type of water confirmed this hypothesis. However, Ca²⁺ showed an insignificant correlation with F^?. The high Na/Ca ratio (>1) in 73 % of the samples and the result of Na/Na+Cl plot suggest the occurrence of cation exchange in the study area. The major source of F^? was identified as products of the weathering and the dissolution of fluorites, amphiboles and micas present in the geological formations in the study area. The positive relationship between NO₃ ^? and F^? in few wells located in agricultural fields suggest possible source of F^? from the application of fertilizers. More than 25 % of the samples had higher values of fluoride than the permissible limit of drinking water according to Indian standards. Spatial distribution of fluoride showed a higher concentration in the southwest part of the study area, namely, Thirupathur and Vaniyambadi. This study shows that contamination was high in certain parts of Vellore District and the quality of water must be maintained by resorting to appropriate treatment and management strategies.     

Palaeoenvironmental significance of fluvial facies and archives of Late Quaternary deposits in the floodplain of Damodar River,India

Statigraphic exposures, fluvial archives and borehole data have been allowed to reconstruct the alluvial history of Late Pleistocene to Early Holocene and climate changes in the monsoonal wet–dry region of lower Damodar Basin (West Bengal, India). The facies architectures and climate proxies suggest that five to six climate changes occurred in between ～14 and 6 kiloannum (ka). Supporting evidence from the floodplain of Damodar River demonstrates that the successive phases of aggradation and incision were linked to the south-west monsoonal variability of Late Quaternary period. The onset of semi-arid climate was associated with caliches, pond and backswamp deposits of waning low-energy floods. The relatively warm-humid climate was associated with sandy bedforms, valley fills, slack water deposits and ferruginous nodules. This paper presents a synthesis of the available palaeoclimatic records from the lower Ganga Basin and the rivers of western and central India for the palaeoenvironmental significance of Late Quaternary deposits and discusses the influence of palaeoclimatic controls on the fluvial architectures and archives that developed below the floodplain of Damodar River. We have taken some representative studies from the region to reveal the spatial variability in fluvial successions in response to climate changes during this period.     

Flood susceptibility mapping using integrated bivariate and multivariate statistical models

Flooding can have catastrophic effects on human lives and livelihoods and thus comprehensive flood management is needed. Such management requires information on the hydrologic, geotechnical, environmental, social, and economic aspects of flooding. The number of flood events that took place in Busan, South Korea, in 2009 exceeded the normal situation for that city. Mapping the susceptible areas helps us to understand flood trends and can aid in appropriate planning and flood prevention. In this study, a combination of bivariate probability analysis and multivariate logistic regression was used to produce flood susceptibility maps of Busan City. The main aim of this research was to overcome the weakness of logistic regression regarding bivariate probability capabilities. A flood inventory map with a total of 160 flood locations was extracted from various sources. Then, the flood inventory was randomly split into a testing dataset 70 % for training the models and the remaining 30 %, which was used for validation. Independent variables datasets included the rainfall, digital elevation model, slope, curvature, geology, green farmland, rivers, slope, soil drainage, soil effect, soil texture, stream power index, timber age, timber density, timber diameter, and timber type. The impact of each independent variable on flooding was evaluated by analyzing each independent variable with the dependent flood layer. The validation dataset, which was not used for model generation, was used to evaluate the flood susceptibility map using the prediction rate method. The results of the accuracy assessment showed a success rate of 92.7 % and a prediction rate of 82.3 %.     

Sediment yield assessment at basin scale using geospatial technique

Soil erosion and sediment yield from catchments are key limitations to achieving sustainable land use and maintaining water quality in nature. One of the important aspects in protecting the watershed is evaluation of sediment produced by statistical methods. Controlling sediment loading in protecting the watershed requires knowledge of soil erosion and sedimentation. Sediment yield is usually not available as a direct measurement but is estimated using geospatial models. One of the geospatial models for estimating sediment yield at the basin scale is sediment delivery ratio (SDR). The present study investigates the spatial SDR model in determining the sediment yield rate considering climate and physical factors of basin in geographic information system environment. This new approach was developed and tested on the Amammeh catchments in Iran. The validation of the model was evaluated using the Nash Sutcliffe efficiency coefficient. The developed model is not only conceptually easy and well suited to the local data needs but also requires less parameter, which offers less uncertainty in its application while meeting the intended purpose. The model is developed based on local data. The results predict strong variations in SDR from 0 in to 70 % in the uplands of the Basin.     

Debris flow impact assessment caused by 14 April 2012 rainfall along the Al-Hada Highway,Kingdom of Saudi Arabia using high-resolution satellite imagery

The Al-Hada highway that descends towards the west of the city of At-Taif is a major connecting highway in the western part of the Kingdom of Saudi Arabia. It is one of the series of descending roads connecting the holy city of Makkah and the city of Jeddah with the city of At-Taif and the cities farther south along the escarpment. The length of the Al-Hada highways is about 22 km. The Al-Hada highway has been historically exposed to landslides and other geohazards since the day it was opened to public some 60 years ago. The road has been reconstructed and many slope instabilities have been remediated and the road has been expanded to two lanes in each direction. Heavy rainfalls occurred on the 14th of April 2012 in the province of At-Taif, causing huge debris flows in two places along the Al-Hada highway. As a result of that, these debris flows closed all four lanes of the highway for 2 weeks in order to remove the debris. The current research deals with mapping of all debris flows along Al-Hada highway and determining their volumes and their impact on the road. Finally, suitable solutions have been suggested to address these critical sites to minimize and/or avoid the debris flow hazards in the future.     

Application of frequency ratio,statistical index,and weights-of-evidence models and their comparison in landslide susceptibility mapping in Central Nepal Himalaya

The Mugling–Narayanghat road section falls within the Lesser Himalaya and Siwalik zones of Central Nepal Himalaya and is highly deformed by the presence of numerous faults and folds. Over the years, this road section and its surrounding area have experienced repeated landslide activities. For that reason, landslide susceptibility zonation is essential for roadside slope disaster management and for planning further development activities. The main goal of this study was to investigate the application of the frequency ratio (FR), statistical index (SI), and weights-of-evidence (WoE) approaches for landslide susceptibility mapping of this road section and its surrounding area. For this purpose, the input layers of the landslide conditioning factors were prepared in the first stage. A landslide inventory map was prepared using earlier reports, aerial photographs interpretation, and multiple field surveys. A total of 438 landslide locations were detected. Out these, 295 (67 %) landslides were randomly selected as training data for the modeling using FR, SI, and WoE models and the remaining 143 (33 %) were used for the validation purposes. The landslide conditioning factors considered for the study area are slope gradient, slope aspect, plan curvature, altitude, stream power index, topographic wetness index, lithology, land use, distance from faults, distance from rivers, and distance from highway. The results were validated using area under the curve (AUC) analysis. From the analysis, it is seen that the FR model with a success rate of 76.8 % and predictive accuracy of 75.4 % performs better than WoE (success rate, 75.6 %; predictive accuracy, 74.9 %) and SI (success rate, 75.5 %; predictive accuracy, 74.6 %) models. Overall, all the models showed almost similar results. The resultant susceptibility maps can be useful for general land use planning.