Showing papers in "Journal of Earth System Science in 2019"

Fractal dimension analysis for seismicity spatial and temporal distribution in the circum-Pacific seismic belt

Abstract: In this study, we present the fractal characteristics of the spatio-temporal sequence for seismic activity in the circum-Pacific seismic belt and vicinity regions, which is one of the most active seismic zones worldwide. We select the seismic dataset with magnitude $$M\ge 4.4$$ in the circum-Pacific seismic belt region and its vicinity from 1900–2015 as the objects. Based on the methods of capacity dimension and information dimension, using $$\hbox {ln}(1/\delta )$$ – $$\hbox {ln }N(\delta )$$ of the relationship to evaluate and explain, the results show that (1) in the circum-Pacific seismic belt and the surrounding areas, for the seismic activity with magnitude $$M\ge 4.4$$ , the time series dimension is 0.63, the spatial distribution dimension is 0.52 and they have fractal structure. (2) For the earthquakes with $$M\ge 7.0$$ , the time series dimension increases greatly, which indicates that the cluster characteristics in time is greatly reduced. And the earthquakes with magnitude $$7.0 \ge M \ge 4.4$$ have significant impact on the characterized by clustering in time in the study region. (3) There is significant fractal structure at spatio-temporal distribution of earthquakes in the circum-Pacific seismic belt. It reveals the tectonic movements keep continuous, obvious anisotropism characteristic of geological structure and the distribution of surface stress field is spatio-temporal heterogeneity in the study area.

Gravity data interpretation using the particle swarm optimisation method with application to mineral exploration

Abstract: This paper describes a new method based on the particle swarm optimisation (PSO) technique for interpreting the second moving average (SMA) residual gravity anomalies. The SMA anomalies are deduced from the measured gravity data to eradicate the regional anomaly by utilising filters of consecutive window lengths (s-value). The buried structural parameters are the amplitude factor (A), depth (z), location (d) and shape (q) that are estimated from the PSO method. The discrepancy between the measured and the predictable gravity anomaly is estimated by the root mean square error. The PSO method is applied to two different theoretical and three real data sets from Cuba, Canada and India. The model parameters inferred from the method developed here are compared with the available geological and geophysical information.

Analysis of deformation characteristics and stability mechanisms of typical landslide mass based on the field monitoring in the Three Gorges Reservoir, China

Abstract: Based on a large number of data including GPS monitoring of surface deformation and inclinometer monitoring of internal deformation over 7 years, we find that the displacement of a typical landslide mass has the stepped evolution characteristics as: the variation of the reservoir water level under the different years and months in the Three Gorges Reservoir and the deformation of landslide mass surges in the flood season. On the contrary, the deformation of landslide mass slows down in the non-flood season. Especially, in 2007, 2009 and 2011, the fluctuation of the surface monitoring displacement is more intense than that in the other years. In addition, the whole landslide mass has a characteristic of the trial-type sliding. The surface displacement is greater than the internal displacement. Based on that, deformation characteristics, stability mechanisms and the influencing factors of landslide mass are studied deeply. The results show that the drawdown of the water level of the Three Gorges Reservoir region is the main controlling factor of the deformation of the landslide mass. The results of the study have a significant value of reference on the stability analysis of landslide mass under the similar engineering geological conditions.

Landslide prediction capability by comparison of frequency ratio, fuzzy gamma and landslide index method

Abstract: This study presented the prediction capability of three methods including the frequency ratio (FR), fuzzy gamma (FG) and landslide index method (LIM) to produce landslide-prone areas in the Sari-Kiasar watershed, Mazandaran Province of Iran. In the first step, 105 landslide locations were selected and were randomly divided into two groups of 75% (78 locations) and 25% (27 locations) as training and testing datasets. Then the 17 landslide conditioning factors including land use/land cover, Differential Vegetation Index (DVI), lithology and distance from faults, elevation, slope aspect, slope angle, tangential curvature, profile curvature and plane curvature, distance from drainage, rainfall, Stream Power Index, Sediment Transport Index and temperature, and distance from road, density of settlement were considered for the proposed modelling approach. Finally, by applying the training dataset, three landslide susceptibility maps were constructed by using the FR, FG and LIM methods. The prediction capability of the performed model was evaluated by the area under the receiver operating curve or AUC for both training (success rate) and testing (prediction rate) datasets. The results showed that the AUC for success rate of FR, FG and LIM models was 82.04%, 81.08% and 73.61% and for prediction rate was 82.72%, 79.09% and 65.45%, respectively. The results showed that the FR model has a higher prediction accuracy than the FG and LIM methods. This study revealed that the most important factors in landslide occurrence are rainfall, slope and vegetation. The result of the present study can be possibly useful for land use planning and watershed management.

A comparative study of conceptual rainfall-runoff models GR4J, AWBM and Sacramento at catchments in the upper Godavari river basin, India

Abstract: Accurate catchment level water resource assessment is the base for integrated river basin management. Due to the complexity in model structure and requirement of a large amount of input data for semi-distributed/distributed models, the conceptual models are gaining much attention in catchment modelling these days. The present study compares the performance of three conceptual models, namely GR4J, Australian Water Balance Model (AWBM) and Sacramento for runoff simulation. Four small catchments and one medium catchment in the upper Godavari river basin are selected for this study. Gap-filled daily rainfall data and potential evapotranspiration (PET) measured from the same catchment or adjacent location are the major inputs to these models. These models are calibrated using daily Nash–Sutcliffe efficiency (NSE) with bias penalty as the objective function. GR4J, AWBM and Sacramento models have four, eight and twenty-two parameters, respectively, to optimise during the calibration. Various statistical measures such as NSE, the coefficient of determination, bias and linear correlation coefficient are computed to evaluate the efficacy of model runoff predictions. From the obtained results, it is found that all the models provide satisfactory results at the selected catchments in this study. However, it is found that the performance of GR4J model is more appropriate in terms of prediction and computational efficiency compared to AWBM and Sacramento models.

Performance of a very high-resolution global forecast system model (GFS T1534) at 12.5 km over the Indian region during the 2016–2017 monsoon seasons

Abstract: A global forecast system model at a horizontal resolution of T1534 ( $${\sim }12.5\, \hbox {km}$$ ) has been evaluated for the monsoon seasons of 2016 and 2017 over the Indian region. It is for the first time that such a high-resolution global model is being run operationally for monsoon weather forecast. A detailed validation of the model therefore is essential. The validation of mean monsoon rainfall for the season and individual months indicates a tendency for wet bias over the land region in all the forecast lead time. The probability distribution of forecast rainfall shows an overestimation (underestimation) of rainfall for the lighter (heavy) categories. However, the probability distribution functions of moderate rainfall categories are found to be reasonable. The model shows fidelity in capturing the extremely heavy rainfall categories with shorter lead times. The model reasonably predicts the large-scale parameters associated with the Indian summer monsoon, particularly, the vertical profile of the moisture. The diurnal rainfall variability forecasts in all lead times show certain biases over different land and oceanic regions and, particularly, over the north–west Indian region. Although the model has a reasonable fidelity in capturing the spatio-temporal variability of the monsoon rain, further development is needed to enhance the skill of forecast of a higher rain rate with a longer lead time.

The first record of active methane (cold) seep ecosystem associated with shallow methane hydrate from the Indian EEZ

Abstract: Here we report the discovery of cold-seep ecosystem and shallow methane hydrates (2–3 mbsf) associated with methane gas flares in the water column from the Indian EEZ for the first time. The seep-sites are located in the Krishna–Godavari (K–G) basin at water depths of 900–1800 m and are characterized by gas flares in the water-column images. The occurrence of methane gas hydrates at very shallow depths (2–3 mbsf) at some of the seep-sites is attributed to high methane flux and conducive P–T conditions, necessary for the stability of methane hydrate. Chemosymbiont bearing Bivalves (Vesicomidae, Mytilidae, Thyasiridae and Solemyidae families); Polychaetes (Siboglinidae family) and Gastropods (Provannidae family) are also identified from seep-sites.

Groundwater potential assessment of the Sero plain using bivariate models of the frequency ratio, Shannon entropy and evidential belief function

Abstract: The goal of the present research is to evaluate three bivariate models of the frequency ratio, Shannon entropy (SE) and evidential belief function in the spatial prediction of groundwater at the Sero plain located in west Azerbaijan, Iran. In the first phase, well locations with groundwater yields $${>}11\hbox { m}^{3}$$ /hr were identified (75 well locations). Ten groundwater conditioning factors affecting the occurrence of groundwater, namely, altitude, slope degree, curvature, slope aspect, rainfall, soil, land-use, geology and distance from the fault and the river, were selected for modelling. Finally, the groundwater potential map results were drawn from three implemented models and they were validated using testing data by area under the receiver operating characteristic curve (AUC). The AUCs of these models were 0.84, 81 and 85%, respectively. The results of the current study demonstrated that these models could be successfully employed for spatial prediction modelling. Moreover, the results of the SE model demonstrated that the most and the least important factors in groundwater occurrences in the area under study were altitude, curvature and rainfall, respectively. The results of this study are helpful for the Regional Water Authority of Urmia and the decision makers to comprehensively assess the groundwater exploration development and environmental management in future planning.

ENSO-induced groundwater changes in India derived from GRACE and GLDAS

Abstract: This study aims to quantify the interannual variations of groundwater storage changes (GWSCs) over India. GWSCs are derived from the gravity recovery and climate experiment (GRACE) and global land data assimilation system (GLDAS)-Noah life safety model (LSM) for the period 2003–2015. Estimated GWSCs are validated with the satellite altimetry over the six lake stations. The variability of GWSC and altimetry water-level heights are assessed with the cross-correlation and plotting analysis. Annual trends of GWSC and GRACE in terrestrial water storage (TWS) were estimated using the non-parametric Mann–Kendall test and Sen’s slope method. Results suggest that GWSC and TWS have declined in northern India at the rate of $$\sim $$ 1.6 cm $$\hbox {yr}^{-1}$$ and in southern and western central India at the rate of $$\sim $$ 0.5 cm $$\hbox {yr}^{-1}$$ . Impacts of short-term climate perturbations such as El Nino and La Nina for the GWSCs are assessed. During the El Nino period, the decline of GWSC over northern India enhanced, whereas during the La Nina period, the recovery of GWSC is evident. These interannual variations of GWSCs over India are attributed by interannual precipitation changes. Under the global warming scenario, the occurrences of El Nino events are likely to enhance in the future, and our findings help the water resource management policy makers for necessary actions during such short-term climate perturbations.

Potential detection of water resources in karst formations using APLIS model and modification with AHP and TOPSIS

Abstract: Population growth and water shortage in Iran have highlighted the importance of studies on karst. However, in developing countries such as Iran, studies on the karst region including the construction of piezometric wells, exploratory boreholes, qualitative sampling and tracing tests are performed infrequently due to the huge costs. Hence, it is necessary to conduct karst studies in regions with a high potential of recharge using the map of groundwater recharge potential. In addition, determining and estimating the potential of these resources for management planning is vital in water shortage conditions. In this study, the potential detection of water resources in karst formations using ranking methods is investigated. First, APLIS weighting model was used in Javanroud, Kermanshah region, as the main method of and the basis of this research. Then, analytic hierarchy process (AHP) and TOPSIS techniques were used to modify the weight of the APLIS model and lastly, the three final maps of APLIS, AHP and TOPSIS were matched and compared with maps of spring and fault. Thus, the TOPSIS method, despite five springs with discharge of $$38 \, {\hbox {m}}^{3}/\hbox {s}$$ and four faults with length of 8869 m in a region with very high recharge, was selected as the best method. The results obtained enable us to select the best region for geophysical operation that requires the least amount of time along with the lowest cost.

Landslide susceptibility mapping of the Tehri reservoir rim area using the weights of evidence method

Abstract: This study was aimed to utilise important landslide causal factors for the delineation of the landslide susceptible area using the weights of evidence (WofE) method in the Tehri reservoir rim region on a macro scale. The Tehri reservoir extends up to 70 km and bounded by moderate to steep slopes. Landslide susceptibility mapping (LSM) is an essential measure for identifying the potentially unstable slopes bounding the reservoir. With the help of ancillary data, remote sensing imagery and a digital elevation model, 10 causative factors along with landslide inventory were extracted. Initially, the WofE model was applied to obtain the association between landslides and causative factors. The process gave the numerical estimate of correlation between landslides and causative factors by means of positive and negative correlation. Important factor attributes, potentially causing landslides, were identified based on high positive correlation values. Later, the posterior probability of landslide occurrence for each mapping unit was also computed using the WofE model. Posterior probability was divided into five relative susceptibility classes. Validation of the posterior probability map was carried out by using the prediction rate curve technique and a reasonable accuracy of 83% was achieved. LSM of the Tehri reservoir rim area implicates unplanned road construction and settlements coupled with the reservoir slope settlement process for the present degradation of the geo-environmental system in that region.

Evolution of extreme rainfall events over Indo-Gangetic plain in changing climate during 1901–2010

Abstract: Due to climate variability and climate change there is an increase in magnitude and frequency of extreme precipitation events. During the last few decades these extreme rainfall events have been increased in global as well as on regional scale. Our climate is very much affected by the changes in frequency of extreme rainfall events. Particularly, variability of extreme rainfall events has been studied over one of the most valuable Indian region i.e. over Indo-Gangetic plain (IGP). Long term trend in extreme events has been analyzed with the help of IMD classification. The classification is considered for moderate rain (2.5–64.4 mm; category I), heavy rain (64.5–124.4 mm; category II) and very heavy rain (124.5 mm or more; category III) and the categorization of rainfall events is based on daily rainfall for the period 1901–2010 during Indian summer monsoon (JJAS). The significant long term trend in frequency of extreme rainfall events is analyzed using the statistical test. Long term trend analysis shows the significant decreasing trend for categories II and III. However, an increasing rainfall frequency is observed for moderate rainfall events (category I) during the considered period. A significant interannual and inter-decadal fluctuation in rainfall frequency and magnitude were observed over IGP. Events of moderate and heavy rainfall increases during the withdrawal period of Indian summer monsoon, which might contribute in several cases of flood in the region of IGP. In term of distribution and contribution of rainfall in agriculture area categories I and II, rainfall events are more important but changes in rainfall pattern may lead to flood and drought risk over IGP. The policy making decision for disaster risk and food security should be based on spatial as well as temporal variability of rainfall pattern over IGP region.

Kharif crop characterization using combination of SAR and MSI Optical Sentinel Satellite datasets

Abstract: In the present study, the differences in the kharif crop reflectance at varied wavelength regions and temporal SAR backscatter (at VV and VH polarizations) during different crop stages were analyzed to classify crop types in parts of Ranchi district, East India using random forest classifier. The spectral signature of crops was generated during various growth stages using temporal Sentinel-2 MSI (optical) satellite images. The temporal backscatter profile that depends on the geometric and di-electric properties of crops were studied using Sentinel-1 SAR data. The spectral profile exhibited distinctive reflectance at the NIR (0.842 µm) and SWIR (1.610 µm) wavelength regions for paddy (Oryza sativa; ~0.25 at NIR, ~0.27 at SWIR), maize (Zea mays; ~0.24 at NIR, ~0.29 at SWIR) and finger millet (Eleusine coracana, ~0.26 NIR, ~0.31 at SWIR) during pre-sowing season (mid-June). Similar variations in crop’s reflectance at their different growth stages (vegetative to harvesting) were observed at various wavelength ranges. Further, the variations in the backscatter coefficient of different crops were observed at various growth stages depending upon the differences in sowing–harvesting periods, field conditions, geometry, and water presence in the crop field, etc. The Sentinel-1 SAR based study indicated difference in the backscatter of crops (i.e., ~−18.5 dB (VH) and ~−10 dB (VV) for paddy, ~−14 dB (VH) and ~−7.5 dB (VV) for maize, ~−14.5 dB and ~−8 dB (VV) for finger millet) during late-July (transplantation for paddy; early vegetative for maize and finger millet). These variations in the reflectance and backscatter values during various stages were used to deduce the best combination of the optical and SAR layers in order to classify each crop precisely. The GLCM texture analysis was performed on SAR for better classification of crop fields with higher accuracies. The SAR-MSI based kharif crop assessment (2017) indicated that the total cropped area under paddy, maize and finger millet was 24,544.55, 1468.28 and 632.48 ha, respectively. The result was validated with ground observations, which indicated an overall accuracy of 83.87% and kappa coefficient of 0.78. The high temporal, spatial spectral agility of Sentinel satellite are highly suitable for kharif crop monitoring. The study signifies the role of combined SAR–MSI technology for accurate mapping and monitoring of kharif crops.

Mapping of groundwater spring potential zone using geospatial techniques in the Central Nepal Himalayas: A case example of Melamchi–Larke area

Abstract: Studies assessing the groundwater spring potential in the Himalayan mountain slopes are very important for sustainable water resources management and build climate resilience in mountains, but such studies are few in the Himalayas. Hence, this paper attempts to identify the groundwater spring potential zone in the Central Himalayas of Nepal. About 412 groundwater springs were surveyed, which were mainly originated from the weathered, jointed or fractured rock aquifers in the high-grade metamorphosed rocks. Eleven influencing factors, viz., altitude, slope gradient, slope shape, relative relief, flow accumulation, drainage density, geology, lineament density, land use and vegetation density were considered in assessing the groundwater spring potential using the weight of evidence method. Weight indicating the probability of groundwater spring occurrence on multiple classes of each factor was calculated and finally summed up to determine the groundwater spring potential. Gentle slope, low relative relief, high flow accumulation, north- and east-facing slopes, denser lineament density, altitude class of 1500–2500 m, high vegetation density, and forest demonstrated a higher likelihood of spring occurrence. Validation of the groundwater spring potential map was successful, which implies the method can be replicated in a similar biophysical environment, where the hydrogeological or geophysical surveyed data is not available.

Long-term (2005–2012) measurements of near-surface air pollutants at an urban location in the Indo-Gangetic Basin

Abstract: Simultaneous long-term measurements of near-surface air pollutants at an urban station, New Delhi, were studied during 2005–2012 to understand their distribution on different temporal scales. The annual mean mass concentrations of nitrogen dioxide ( $$\hbox {NO}_{2})$$ , sulphur dioxide ( $$\hbox {SO}_{2})$$ , particulate matter less than $$10\,\upmu \hbox {m}$$ ( $$\hbox {PM}_{10})$$ and suspended particulate matter (SPM) were found to be $$62.0\,{\pm }\,27.6$$ , $$12.5\,{\pm }\,8.2$$ , $$253.7\,{\pm }\,134$$ and $$529.2\,{\pm }\,213.1\,\upmu \hbox {g}/\hbox {m}^{3}$$ , respectively. The 24-hr mean mass concentrations of $$\hbox {NO}_{2}$$ , $$\hbox {PM}_{10}$$ and SPM were exceeded on $$\sim $$ 27%, 87% and 99% days that of total available measurement days to their respective National Ambient Air Quality Standard (NAAQS) level. However, it never exceeded for $$\hbox {SO}_{2}$$ , which could be attributed to reduction of sulphur in diesel, use of cleaner fuels such as compressed natural gas, LPG, etc. The mean mass concentrations of measured air pollutants were found to be the highest during the winter/post-monsoon seasons, which are of concern for both climate and human health. The annual mean mass concentrations of $$\hbox {NO}_{2}$$ , $$\hbox {PM}_{10}$$ and SPM showed an increasing trend while $$\hbox {SO}_{2}$$ appears to be decreasing since 2008. Air mass cluster analysis showed that north–northwest trajectories accounted for the highest mass concentrations of air pollutants (more prominent in the winter/post-monsoon season); however, the lowest were associated with the southeast trajectory cluster.

Delineating groundwater prospect zones in a region with extreme climatic conditions using GIS and remote sensing techniques: A case study from central India

Abstract: Sustainable groundwater management of an extreme climatic region is very important from both social and economic point of view. This study attempts to delineate the groundwater potential zones of Sonepur district, Odisha, which falls under an extreme climatic region, using remote sensing, geographical information system and Saaty’s analytical hierarchy process (AHP). Different ancillary data, multiple data sets obtained from LANDSAT 8 OLI and ASTER Level-1T were used in conjunction with Cartosat-1 imagery to study the detailed physical attributes of the study area and to prepare the groundwater prospect map using a weighted overlay method in ArcGIS 10.4 software. The AHP technique was used for determining the weights of each layer. From the groundwater prospect map, it was found that 52% of the area belongs to the moderate groundwater prospect zone followed by good to very good, very good to excellent (32%) and poor (16%) groundwater prospect zones. Statistical analysis of the number of existing wells in each of these water potential zones and their water level was used to verify the accuracy of the water potentiality estimated in this study. The groundwater potentiality map prepared as a part of this study would serve as an important tool for identifying suitable zones for rainwater harvesting and also for managing groundwater abstraction for a safe and sustainable water supply.

Groundwater prospecting by the inversion of cumulative data of Wenner–Schlumberger and dipole–dipole arrays: A case study at Turamdih, Jharkhand, India

Abstract: The present study deals with groundwater prospecting in hardrock terrain. Initially, the Wenner–Schlumberger array and the dipole–dipole array data have been acquired using Syscal Junior Switch-48. Furthermore, data acquired using both arrays have been merged using Prosys-II data handling software for the inversion of the cumulative data for possible mapping of water-bearing fracture rock masses with different structural distribution in a complex geological environment. The data have been analysed using RES2DINV software, based on the smoothness constrained least-square technique. Two numbers of 2D electrical resistivity tomography profiles (AA $$'$$ and BB $$'$$ ) have been selected over an official colony of the Turamdih uranium mine for groundwater prospecting, which is located at about 24 km west of Jaduguda, Jharkhand, India. High-resistivity features associated with a dyke-like structure have been delineated in both the profiles. Three low-resistivity features have been delineated as water saturated alluvium/aquifers in profile AA $$'$$ . A low-resistivity feature associated with the water-saturated fracture zone has been identified in profile BB $$'$$ , which is well correlated with the surficial location of an ephemeral channel at the bottom of the hill across the slope. It is observed that geoelectric sections generated by the inversion of cumulative data of both arrays provide superior results compared with the Wenner–Schlumberger and dipole–dipole arrays, separately.

Seasonal variation of evapotranspiration and its effect on the surface energy budget closure at a tropical forest over north-east India

Abstract: This study uses 1 yr of eddy covariance (EC) flux observations to investigate seasonal variations in evapotranspiration (ET) and surface energy budget (SEB) closure at a tropical semi-deciduous forest located in north-east India. The annual cycle is divided into four seasons, namely, pre-monsoon, monsoon, post-monsoon and winter. The highest energy balance closure (76%) is observed during pre-monsoon, whereas the lowest level of closure (62%) is observed during winter. Intermediate closure of 68% and 72% is observed during the monsoon and post-monsoon seasons, respectively. Maximum latent heat flux during winter ( $$\hbox {150 W m}^{-2}$$ ) is half of the maximum latent heat ( $$\hbox {300 W m}^{-2}$$ ) flux during the monsoon. ET is a controlling factor of SEB closure, with the highest rates of closure corresponding to the periods of the highest ET. The Bowen ratio ranges from 0.93 in winter to 0.27 during the monsoon. This is the first time the role of ET in the seasonal variation of SEB closure has been reported for any ecosystem in north-east India using EC measurements.

Review on estimation methods of the Earth’s surface energy balance components from ground and satellite measurements

Abstract: Accurate estimation of the Earth’s surface energy balance (SEB) components is very much important for characterising the environmental, hydrological and bio-geophysical processes to predict the weather and climate or climate change. This narrative review summarises the basic theories of estimation methods of the solar (shortwave) radiation, thermal (longwave) radiation and evapotranspiration (latent heat flux) from both the ground and satellite measurements, which are inherently complex to measure at large scale. This paper discusses the reviews of prior and recent advances in the estimation methods and models by focusing their advantages, disadvantages and recommendations. Uncertainties associated with satellite estimations and some key directions for further studies are also discussed, including the status of ground-based measurements at regional and global scales and the advent of new satellite technologies for quantifying the SEB components more accurately. This study infers that the further advances in the satellite remote sensing and worldwide ground-based measurement networks will enhance the capabilities for the potential estimation of the SEB parameters as well as monitoring the global water and energy cycles to develop significant environmental studies for the betterment of living on the Earth.

Landslide stability assessment along Panchkula–Morni road, Nahan salient, NW Himalaya, India

Abstract: We report the slope stability analysis of three vulnerable sites (S1, S2 and S3) within the lower Siwalik along the Panchkula–Morni road section in the Nahan salient, north-western Himalaya. Kinematic analysis of joint data was conducted to understand the different modes of failure. Rock mass classification techniques like rock mass rating, slope mass rating (SMR) and continuous SMR were used for stability classification and the factor of safety was calculated using stability charts. At site S1, the instability is controlled by the orientation of the discontinuity joint J1 which is parallel to the bedding and at site S2, the slope fails due to the wedge. The Umri landslide site S3 is the product of a damage zone by the normal faults which intersect at joint J3; a wedge is formed which falls in the critical zone. The damage zone in the Umri landslide greatly affects the porosity and permeability of the rockmass and acts as a pathway for the percolation of water during rainfall which reduces effective stress. The slope failures are tectonically controlled results due to the high slope angles, structural discontinuities like joints and faults and structural damage zones associated with the faults.

Groundwater quality in a semi-arid region of India: Suitability for drinking, agriculture and fluoride exposure risk

Abstract: Fluoride exposure through consumption of drinking water was studied in a heavily industrialised area and suitable measures were suggested to control the fluorosis risk to residents. Groundwater quality conforms to World Health Organization (WHO) criterion for drinking except for fluoride and is also suitable for irrigation. Fluoride concentration ranges from 0.1 to 4.4 mg/l and 39% of the total samples measured were found to be contaminated as per WHO limits (1.5 mg/l). The fluoride intake through drinking water was calculated to be 0.10 mg/kg/d for infants, 0.09 mg/kg/d for children and 0.05 mg/kg/d for adults with a corresponding exposure dose exceeding 2.1, 1.9 and 1.1 times for infants, children and adults, respectively, compared to the minimum risk value of 0.05 mg/kg/d. The fluorosis risk map indicates that with a few exceptions of some western and northwestern parts, the entire study area is prone to fluorosis and the highest being in the south central part. The fluoride exposure dose suggests the risk of mottled enamel among residents if untreated groundwater is provided for drinking for a long time. Considering the hydrogeological setup of this region, various amelioration methods to help mitigate the ill effects of high fluoride were evaluated and better nutrition containing calcium and vitamin C was found to be the most effective and viable option.

Flash flood susceptibility modelling using geomorphometric approach in the Ushairy Basin, eastern Hindu Kush

Abstract: This study focuses on flash flood susceptibility modelling using geomorphometric ranking approach in the Ushairy Basin. In the study area, flash floods are highly unpredictable and the worst hydrometeorological disaster. An advanced spaceborne thermal emission and reflection radiometer global digital elevation model was used as input data in a geographic information system environment to delineate the target basin. A total of 17 sub-basins were delimited using a threshold of $$4 \hbox {km}^{2}$$ . The attribute information of each sub-basin was analysed to compute the geomorphometric parameters by applying Hortonian and Strahler geomorphological models. The results were analysed and categorised into five classes using statistical techniques, and the rank score was assigned to each class of all parameters depending on their relation with flash flood risk. In this study, 16 parameters were analysed to quantify the geomorphometric number of each sub-basin depicting the degree of flash flood susceptibility. The geomorphometric number of each sub-basin was linked to the geo-database for spatial visualisation. The analysis reveals that extremely high, very high, high and moderate sub-basins susceptible to flash floods were spread over an area of 55%, 8.5%, 23.7%, and 11.5%, respectively. It was found that out of total settlements, 53% are located in the extremely highly and very highly susceptible sub-basins. In the study area, the upper reaches are characterised by snow-covered peaks, steep slopes and high drainage densities ( $${>}1.7 \hbox { km/km}^{2})$$ . The analysis further indicated that the flash flood susceptibility increases with the increase in area, relief and relief ratio of the sub-basins. Model accuracy was assessed using primary data regarding past flood damages and human fatalities. Similarly, socio-demographic conditions of each sub-basin were also compared and linked to the extent of flash flood susceptibility. This study may assist the district government and district disaster management authority of Dir upper to initiate flood risk reduction strategies in highly susceptible zones of the Ushairy Basin.

Monthly prediction of streamflow using data-driven models

Abstract: The estimation of river run-off is a complex process, but it is of vital importance to the proper operation of reservoirs, the design of hydraulic structures, flood control, drought management and the supply of water and electricity. The high uncertainty in rainfall–run-off modelling and lack of data has made the development of rainfall–run-off models with acceptable levels of accuracy and precision challenging. Furthermore, the rainfall–run-off models commonly do not provide an explicit relationship between run-off and other variables to be used for run-off-related investigations. To overcome the knowledge and information shortage in rainfall–run-off modelling, data-driven models have been used instead of conceptual models for the development of rainfall–run-off models. In this paper, three data-driven models, the genetic algorithm-support vector regression (GA-SVR), genetic algorithm-artificial neural network (GA-ANN) and the group method of data handling (GMDH) have been used to predict the monthly run-off of the Gavehroud basin. Their performances are compared with a conceptual hydrological model (HYMOD) whose parameters are calibrated using the GA. To this end, the monthly data on precipitation, temperature and run-off at the Gavehroud basin over 49 yr (1960–2009) were analysed. Evaluation of the results using performance evaluation indicators showed that the hybrid model of GA-SVR provided better accuracy in predicting the nonlinear behaviour of flow data than the GA-ANN, GMDH and HYMOD.

Projected changes of inundation of cyclonic storms in the Ganges-Brahmaputra-Meghna delta of Bangladesh due to SLR by 2100

Abstract: Almost every year, Bangladesh experiences disasters such as tropical cyclones, storm surges, coastal erosion or floods. Tropical cyclones originate from the North Indian Ocean and often cause devastating flood inundations in Bangladesh. Storm surges of the Bay of Bengal (BOB) are larger compared to other regions of the world for similar cyclones due to amplification by the shallow water depth, huge continental shelf and convergent coastlines. This scenario of inundation for such storm surges in the future when the sea level rise (SLR) occurs due to global warming will be different from the present. The densely populated coastal region of Bangladesh is likely to become more vulnerable in the future due to SLR. Disaster risks can be reduced if storm surges can be predicted well ahead. To assess the possible changes of inundation in the future, a widely used coastal model, Delft3D, has been applied for this BOB region. The model has been validated for the storm surge of three recent devastating cyclones, namely, Sidr, Aila and Roanu in the southern coast of Bangladesh. The validated model has been run to produce inundation maps and statistics for cyclonic storm surges such as Sidr, Aila and Roanu and probable SLR. Three possible SLR boundary conditions are chosen from the business-as-usual climate scenario representative concentration pathway 8.5 with values of 0.5 m (lower limit), 1 m (upper limit) and 1.5 m (extreme case, considering the subsidence and a rapid collapse of the Antarctic ice sheet). It is found that a category 4 cyclone such as cyclone Sidr would inundate 2.6%, 3.67% and 5.84% of the area of the country if the SLR is 0.5, 1 and 1.5 m, which will affect the livelihood of nearly 4.1, 7.0 and 9.1 million people of Bangladesh, respectively. It will also inundate up to 21.0%, 42.1% and 65.1% of the Sundarbans mangrove forest, which will undoubtedly affect the ecology of this unique ecosystem.

Assessment of Met Office Unified Model (UM) quantitative precipitation forecasts during the Indian summer monsoon: Contiguous Rain Area (CRA) approach

Abstract: The operational medium range rainfall forecasts of the Met Office Unified Model (UM) are evaluated over India using the Contiguous Rainfall Area (CRA) verification technique. In the CRA method, forecast and observed weather systems (defined by a user-specified rain threshold) are objectively matched to estimate location, volume, and pattern errors. In this study, UM rainfall forecasts from nine (2007–2015) Indian monsoon seasons are evaluated against $$0.5^{\circ }\times 0.5^{\circ }$$ IMD–NCMRWF gridded observed rainfall over India $$(6.5^{\circ }{-}38.5^{\circ }\hbox {N}, 66.5^{\circ }{-}100.5^{\circ }\hbox {E})$$ . The model forecasts show a wet bias due to excessive number of rainy days particularly of low amounts $$({<}1\,\hbox {mm}\,\hbox {d}^{-1})$$ . Verification scores consistently suggest good skill the forecasts at threshold of $$10\,\hbox {mm}\,\hbox {d}^{-1}$$ , while moderate (poor) skill at thresholds of $${<}20\,\hbox {mm}\,\hbox {d}^{-1}\,({<}40\,\hbox {mm}\,\hbox {d}^{-1})$$ . Spatial verification of rainfall forecasts is carried out for 10, 20, 40 and $$80\,\hbox {mm}\,\hbox {d}^{-1}$$ CRA thresholds for four sub-regions namely (i) northwest (NW), (ii) southwest (SW), (iii) eastern (E), and (iv) northeast (NE) sub-region. Over the SW sub-region, the forecasts tend to underestimate rain intensity. In the SW region, the forecast events tended to be displaced to the west and southwest of the observed position on an average by about $$1^{\circ }$$ distance. Over eastern India (E) forecasts of light (heavy) rainfall events, like $$10\,\hbox {mm}\,\hbox {d}^{-1}$$ (20 and $$40\,\hbox {mm}\,\hbox {d}^{-1}$$ ) tend to be displaced to the south on an average by about $$1^{\circ }$$ (southeast by $$1{-}2^{\circ }$$ ). In all four regions, the relative contribution to total error due to displacement increases with increasing CRA threshold. These findings can be useful for forecasters and for model developers with regard to the model systematic errors associated with the monsoon rainfall over different parts of India.

Identification of inrush water recharge sources using hydrochemistry and stable isotopes: A case study of Mindong No. 1 coal mine in north-east Inner Mongolia, China

Abstract: Rapid identification of inrush water sources is vital for the safe operation of a coal mine. Hydrogeochemical (fuzzy comprehensive evaluation method and cluster analysis method) and isotope analyses are applied to identify the inrush water sources of the Mindong No. 1 mine, which is located in north-east Inner Mongolia, China. The clustering analysis and isotope analysis results show that the inrush water sources are from aquifer 1 (A1), aquifer 2 (A2) and Yimin river. However, fuzzy comprehensive evaluation shows that the inrush water sources are from A2, aquifer 3 (A3) and Yimin river. Considering the hydrogeological conditions of the study area, it is concluded that the inrush water sources are A1, A2 and Yimin river, with mixing ratios of 30.8%, 60.6% and 8.6%, respectively. The application of multiple methods makes the conclusion more reliable. Additionally, this study improves the speed and effectiveness of the identification of inrush water sources in coal mines and provides a practical reference for research related to mine water inrush to ensure the safe operation of coal mines.

Erosion–deposition and land use/land cover of the Brahmaputra river in Assam, India

Abstract: The Brahmaputra is a unique dynamic river in the world with intense braiding and critical bank erosion. Both erosion and deposition are continuous processes in the river in an attempt to reach a new equilibrium in channel geometry and morphology by the ever dynamic nature of flow. Erosion and deposition of the river have link to land use and land cover (LULC) as the land cover is under constant change in a dynamic landscape constantly shaped by continuous erosion and deposition. The objective of the present work is to evaluate the extent of erosion and deposition along the Brahmaputra river and change in the LULC of the Brahmaputra river in Assam, India. Remote sensing and geographic information system (GIS) techniques were utilised to extract information from Landsat images. Total area of erosion and deposition during 1973–2014 was 1557 and 204 km2, respectively. Increase in area (28%) of the Brahmaputra during 1973–2014 is not solely due to bank erosion, but also for the bifurcation of streams without the loss of land. LULC study has revealed that 29% area was occupied by active channels and 71% was occupied by bars in 2014. Maximum reaches experienced reduction of the submerged part in 2014 compared to 1994 in the post-monsoon months with an overall decrease from 37% to 29%. A reduction in natural grassland and forest has been observed with a corresponding increase in agricultural practices in different bars and islands of the Brahmaputra in Assam during 1994–2014.

Uncertainty analysis of rainfall depth duration frequency curves using the bootstrap resampling technique

Abstract: Rainfall depth duration frequency (DDF) curves are used extensively in many engineering designs. However, due to the sampling error and the uncertainty associated with the parameter estimation process, the DDF curves are subjected to parameter uncertainty. In this study, an evaluation of the uncertainty of the DDF curves in the Kelantan river basin was performed using the bootstrap resampling method. Annual maximum rainfall series for durations of 24, 48, 72, 96 and 120 h were derived from the stochastic rainfall model outputs and fitted to the generalised extreme value (GEV) distribution. The bootstrap samples were generated by resampling with replacement from the annual maximum rainfall series. The relationships that describe the GEV parameters as a function of duration were used to establish the DDF curves. The 95% confidence intervals were used as an indicator to quantify the uncertainty in the DDF curves. The bootstrap distribution of the rainfall depth quantiles was represented by a normal probability density function. The results showed that uncertainty increased with the return period and there was significant uncertainty in the DDF curves. The suggested procedure is expected to contribute to endeavours in obtaining reliable DDF curves, where the uncertainty features are assessed.

Groundwater modelling using an analytic element method and finite difference method: An insight into Lower Ganga river basin

Abstract: Groundwater flow modelling provides the water flow dynamics for the estimation and prediction of groundwater movement and its condition in the aquifer. The modelling helps for the management of the groundwater resources under various hydrological and anthropogenic stresses. In this paper, a modelling exercise was performed using the analytic element method (AEM) and finite difference method (FDM) for the part of Ganga river basin which includes the Varanasi district. Further compression was performed to understand the limitations and benefits of both AEM and FDM based on ease of model development, data requirement and their performances. The groundwater model was developed for the transient state condition based on data for the year 2004–2017. The results show that for most of the observed wells, the difference between the observed head and the simulated head is found in the 90% confidence level. It is found that the AEM does not require a fixed boundary condition which makes the development of the conceptual model less complicated. In the FDM, pumping wells are approximately located and averaged over the cell which becomes a cause of the inaccurate location of the wells. It is found that model development in the AEM is less complicated compared to the FDM. It can be concluded that in some cases AEM-based modelling is more accurate as compared to FDM-based flow modelling. This study can be very helpful for groundwater professionals in deciding the best suitable method for their study area and to avoid the complexity of the model.

The geological site characterisation of the Mandla region, Eastern Deccan Volcanic Province, Central India

Abstract: Detailed geological studies were carried out on the basaltic sequences along the Jabalpur–Niwas, Jabalpur–Chutka and Jabalpur–Mandla traverses covering an area of about $$12\hbox { km} \times 15\hbox { km}$$ to characterise various basaltic lava flows and their behaviour on seismotectonics and geodynamic setting of their formation in the Mandla region of the Eastern Deccan Volcanic Province (EDVP). The studies involve an analysis of the satellite images for the identification of lineaments/faults and field geological studies consisting of geological controls such as ground check, thickness of fractures and orientation along the acknowledged lineaments/faults. The results of the present research comprising 65 lineaments/faults mainly belonging to two geometric groups, minor and major dominantly in the NW–SE and the NE–SW and altered strata varying lithology (weathered to compact basalts) are recognised in the study area. Based on their extent, 57 lineaments have been classified as minor ( 300 km) lineaments are noticed in the study region. The field geological investigations have facilitated the recognition of 10 flows with different characteristic features and a variety of volcanic structures such as columnar, vesicular, amygdaloidal, inflated pahoehoe lava flows and red bole interflow horizons have been documented. Basement rocks of these Deccan basalt lavas are represented by Tirodi Biotite gneisses, quartzite, quartz–mica schists and crystalline limestone in the SE part of the study area of the Mandla region. The present study will help evaluate the localised site characterisation for urban planning and setting up major civil structures.