Erosion potential assessment of watersheds through GIS<Emphasis Type="Bold">-</Emphasis>based hypsometric analysis: a case study of Kurram Tangi Dam

Sediment discharge due to soil and rock erosion within the watersheds is the major cause of siltation in water reservoirs. Siltation in reservoirs reduces the capacity for power production, irrigation water supply, and other domestic purposes. Hypsometric analysis has widely been used to identifying the geomorphic development stages (stabilized, equilibrium, and un-stable) to assess the erosion proneness of watersheds. In this study, watershed of Kurram Tangi Dam and its four sub-watersheds (SWs) were considered to determine their sediment discharge capacity through hypsometric analysis. The boundaries of watershed and sub-watersheds were delineated from Digital Elevation Model (DEM). The hypsometric parameters i.e., hypsometric integral (HI) and curves were generated using Geographic Information System (GIS) techniques. The HI values of SW-1 (0.41) and SW-2 (0.36) indicated that these two SWs were relatively more prone to erosion and contributed higher sediment discharge in Dam siltation. The results were validated through sampling the main drainage channel (Kurram River) to determine the sediment concentration at 12 sites during summer, winter, and spring seasons. Comparison of HI and sediment concentration of SWs presented high correlation (R²?=?0.87). The results emphasized the effective watershed management, extensive afforestation, and construction of silt-control structures at appropriate locations in sub-watersheds. This will ultimately maintain the water and power generation capacity as well as extending the life span of the Dam.     

Microfacies analysis and diagenetic fabric of the Lockhart Limestone exposed near Taxila,Margalla Hill Range,Punjab, Pakistan

The microfacies analysis and diagenetic fabric of the Lockhart Limestone are studied in an outcrop section exposed in the Margalla Hill ranges. The Lockhart Limestone is predominantly composed of medium to thick bedded, nodular and occasionally brecciated, highly fossiliferous limestone with thin interbeds of marl and shale. On the basis of detailed petrographic investigations, four microfacies have been identified including bioclastic packstone, wackestone (siliciclastic bioclastic rich sub-microfacies), wackestone-packstone, and mud-wackestone. Based on the microfacies analysis, the Lockhart Limestone is interpreted to have been deposited in the fore-shoal mid-ramp, mid-ramp, and outer ramp depositional environments. The Paleocene age has been assigned to the Lockhart Limestone based on age diagnostic foraminifera, i.e., Miscellanea, Lockhartia, and Ranikothalia. The diagenetic fabric of the Lockhart Limestone is characterized by several diagenetic features such as micritization, neomorphism (aragonite to calcite transformation and development of microspar), compaction, pressure dissolution (microstylolites), and cementation (calcite-filled microfractures). Such diagenetic features are developed in marine, meteoric, and burial diagenetic settings. The Paleocene Lockhart Limestone of Pakistan shows analogous features to that of the Paleocene Zongpu Formation (Member-3) of the Gamba-Tingri Basin of southern Tibet based on the outcrop features, microscopic fabric, and depositional environment.     

Spatio-temporal analysis of temperature variability,trend, and magnitude in the Hindu Kush region using Monte Carlo and Sen’s slope approaches

The present study explores the spatial and temporal deviations in temperature using Monte Carlo (MC) and Sen’s slope (SS) approaches in the Hindu Kush (HK) region. Climate change holds sturdy association against the temperature trend that has generated adverse impacts in the form of floods. In this attempt, for trend analysis, temperature has been selected as a meteorological parameter. This study mainly focuses on exploring the tendency in average temperature with respect to time and the consequential flood recurrences in the region. For the current study, data regarding temperature were typically collected from Pakistan Meteorological Department. In the study region, there are a total of seven meteorological station falls namely Dir, Chitral, Drosh, Saidu, Malam Jabba, Kalam, and Timergara. The temperature time series data was calculated and analyzed using MC and SS approaches for trend detection in order to demonstrate the kind of fluctuation in the Hindu Kush region. The resultant analysis further revealed that in the meteorological station of Dir, a more significant positive trend (α?=?0.0001) was found in mean monthly maximum, minimum, and monthly normal temperature. Likewise, at Drosh, a positive trend is detected in mean monthly maximum (α?=?0.04), monthly minimum (α?=?0.003), and monthly average (α?=?0.0005). Moreover, at Saidu met station, there is also a trend detected in temperature sub-variables such as monthly maximum (α?=?0.0001) and monthly minimum (α?=?0.001). In addition to these, at Kalam, there is a temperature trend noted for monthly minimum (α?=?0.01) and monthly average (α?=?0.02). Furthermore, the analysis demonstrates that there is no trend detected in the remaining stations, i.e., Chitral, Malam Jabba, Drosh, and Timergara. The overall analysis discovered that there is a sturdy relationship between climate change phenomenon and temperature variability. After using SS test to the temperature data of mean monthly maximum (TMMMax), the results explored that Kalam station grips the highest magnitude, i.e., Q?=?0.76; however, Timergara shows the lowermost, i.e., Q?=???0.34. For the monthly minimum temperature (TMMMin), at Kalam again, the highest value (Q?=?0.005) was detected; however, other stations revealed a negative trend, except Drosh which express no change in terms of magnitude. Similarly, in terms of monthly normal temperature (TMNor), Timergara station (Q?=???0.4) verified a negative trend magnitude and Malam Jabba station again trendless. Among all, the met station of Malam Jabba which holds an altitude of 2591 m is a hilly station just followed by Kalam having 2103 m height; however, Dir holds 1375 m height and the rest of the met stations show low elevation. The main reason for the temperature difference is the altitude of the study region.     

The probability distributions and fractal dimension of sunspot cycles associated with ENSO phenomena

Various methods have been used to secure the certainty of significant relations among the sunspot cycles and some of the terrestrial climate parameters such as temperature, rainfall, and ENSO. This study investigates the behavior of ENSO cycles and mean monthly sunspot cycles. Sunspot cycles range from 1755 to 2016 whereas, ENSO cycles range from 1866 to 2012. In this regard, the appropriateness of distributions is investigated with the help of Kolmogorov-Smirnov D, Anderson-Darling, and chi-square tests. It is found that most of the sunspot cycle follows generalized Pareto distribution whereas, generalized extreme value distribution was found appropriate for ENSO cycles. Probability distribution is used to analyze the behavior of each sunspot cycle and ENSO cycle separately. Probability distribution indicates the tail behavior of each cycle; tail explored correlation cycles. Furthermore, self-similar and self-affine fractal dimension methods are used to compute Hurst exponents to determine the persistency of the available data. Fractal dimension has an ability to study the complexity involved in sunspot and ENSO cycles. The fractal dimension and Hurst exponent describe persistency (smoothness) and complexity of data. Hurst exponent measures long-term behavior of time series, making it more helpful for forecasting. This is the measure of regularity or irregularity (chaos) of the time function in the form of their persistency or anti-persistency, respectively. Hurst exponents are computed using rescaled range analysis method and box counting methods. Both these methods are suitable for long-term forecasting. The results of this study confirm that during the period 1980–2000, ENSO cycles were very active. Simultaneously, ENSO was active for the periods 1982–1983, 1986–1987, 1991–1993, 1994–1995, and 1997–1998; these periods include two strongest periods of the century viz., 1982–1983 and 1997–1998. Sunspot cycles and ENSO cycles both were found to be persistent. Self-similar fractal dimensions exhibited a better persistency and a better correlation as compared to self-affine fractal dimension. This research is a part of a larger research project investigating the correlation of sunspot cycles and ENSO cycles, and the influence of ENSO cycles on variations of the local climatic parameters which in turn depends on solar activity changes.     

Flood frequency analysis of river swat using Log Pearson type 3, Generalized Extreme Value,Normal, and Gumbel Max distribution methods

In Pakistan, floods are among the most devastating and recurring natural hazards. Flood hazard assessment requires flood event magnitude and probability of occurrence. Flood frequency analysis is the most common technique used for the at-site estimation of flood recurrence magnitude. This paper evaluates four most commonly used distribution methods, i.e., Generalized Extreme Value (GEV), Log Pearson 3 (LP3), Gumbel Max, and Normal for the flood frequency and estimation of flood recurrence. Different hydrological stations data namely Khwazakhela, Chakdarra, Panjkora, and Munda Headwork located at Swat river was taken from Provincial Irrigation Department, Khyber Pakhtunkhwa. The analysis is done for 5-, 10-, 25-, 50-, and 100-year return periods by using annual maximum discharge data from 1980 to 2016 (37 yr). Three goodness-of-fit tests were applied to the fitted distributions, i.e., Kolmogorov–Smirnov, Anderson–Darling, and Chi-squared at 5% significance level. Results indicate that LP3 and GEV were ranked top two distributions at all locations while Gumbel Max and Normal were the least fitted having rank 3 and 4, respectively. Based on the goodness-of-fit ranking, LP3 was selected for the estimation of flood magnitude and return periods at Khwazakhela. Designed hydrographs based on probabilistic approach and flood 2010 hydrograph are presented for flood simulation.     

The Origin and MgCl<Subscript>2</Subscript>–NaCl Variations in an Athalassic Sag Pond: Insights from Chemical and Isotopic Data

The examination of past and new chemical–isotopic data (²H/¹H–¹⁸O/¹⁶O, ¹¹B/¹⁰B and ⁸⁷Sr/⁸⁶Sr ratios) shows the meteoric origin of the Sawa Lake (Muthanna Governorate, Iraq) and its connection with the local aquifers, which feed the lake via the groundwater emerging from its floor through fault systems. The chemical and isotopic evaporation models are traced by geochemical computer codes by using a different composition of some potential inflows to the lake (e.g., the Euphrates River and Dammam aquifer). The main product of the chemical evaporation models is gypsum, as confirmed by the mineralogical examination of the sediment and the surrounding outcrops. A strong ¹⁸O–²H enrichment is a consequence of the evaporation effect in arid regions; δ¹⁸O–Cl models and δ¹¹B?=?+?23.4‰ exclude the contribution of any seawater-derived fluids. This latter value along with ⁸⁷Sr/⁸⁶Sr?=?0.707989 suggests a mixed origin from the Eocene–Miocene aquifers. The isotope and chemical evaporation paths from the meteorically recharged sources match the lake composition. However, compositional switches from NaCl toward MgCl₂ occurred in the last decade and are related to post-drought periods, showing that the interaction of the recharging waters with the local soils (Na–Mg exchange and/or the leaching of the top layer salts) have a role in the chemical composition. This demonstrates that the lake is significantly influenced by climatic variations.     

Elastic wave velocity monitoring as an emerging technique for rainfall-induced landslide prediction

Landslides are recurring phenomena causing damages to private property, public facilities, and human lives. The need for an affordable instrumentation that can be used to provide an early warning of slope instability to enable the evacuation of vulnerable people, and timely repair and maintenance of critical infrastructure is self-evident. A new emerging technique that correlates soil moisture changes and deformations in slope surface by means of elastic wave propagation in soil was developed. This approach quantifies elastic wave propagation as wave velocity. To verify its applicability, a series of fixed and varied slope model tests, as well as a large scale model test, were conducted. Analysis of the results has established that the elastic wave velocity continuously decreases in response of moisture content and deformation, and there was a distinct surge in the decrease rate of wave velocity with failure initiation, soil deformation was thus envisaged to have more significant effect on elastic wave velocity than water content. It is proposed that a warning be issued at switch of wave velocity decrease rate. Based on these observations, expected operation of the elastic wave velocity monitoring system for landslide prediction in the field application is presented. Consequently, we conclude that the elastic wave velocity monitoring technique has the potential to contribute to landslide prediction.     

Investigating the flood damages in Lower Indus Basin since 2000: Spatiotemporal analyses of the major flood events

While historically significant for ancient civilizations, the Indus basin is also known for its floods and complex anthropogenic management history. Resulting from years of modifications by the pre-British era Mughal rulers followed by the post-partition division of river waters among the two neighbors, India and Pakistan, Pakistan faces severe management and financial challenges of water management. This study investigates the intricacies arising from this complicated management doctrine for the lower Indus basin. A detailed remote sensing-based analysis of the significant floods to hit the lower Indus basin since 2000 has been provided. Flood years were identified, and Moderate Resolution Imaging Spectroradiometer (MODIS) data for the years 2003, 2005, 2006, 2010, 2011, 2012, 2015, and 2016 were used to map their spatiotemporal extents. Almost all the flood water accumulated in the north is released in one river channel of the lower Indus basin. Further, the challenges were exacerbated due to the excessive rainfall in 2011 and 2012 in southeastern Sindh. A trend analysis of rainfall data shows an increase in the southern basin in the last 21 years, particularly toward the central plains and Sindh Province. The floodwater accumulated in the lower basin for as many as?~?425 days on average, stretching to?~?800 days of stagnancy in some places. The water stagnation period has been the highest in the river floodplain, highly populated and cultivated. The analyses of the current study suggest that the riverine channel has been better managed after the 2010 floods; however, the monsoon’s shift in 2011 and 2012 led to widespread disaster in low-lying regions of Sindh Province.

     

Prediction of future situation of land use/cover change and modeling sensitivity to pollution in Edku Lake,Egypt based on geospatial analyses

GeoJournal - Assessing land use/cover (LULC) change in coastal lakes is an essential process for sustainable development. Edku Lake is one of the most important lakes in the northern part of Nile...     

Land suitability analysis for maize production in Indonesia using satellite remote sensing and GIS-based multicriteria decision support system

GeoJournal - Maize is one of the potential crops can help in regional food production with self-sufficiency of foods in the drought prone areas of East Java in Indonesia. The purpose of this...