Structural evolution of the Feda Graben area – A new model

The pre-Cretaceous basin evolution of the Feda Graben area in the vicinity of the Norwegian-Danish basin has been reconstructed utilizing geological and structural interpretation. The analysis reveals that the basin was faulted at its borders prior to the salt deposition in the Late Permian. Salt movement was initiated in Late Triassic and thick Triassic and Lower Jurassic pods were deposited in the graben area due to this movement. Salt pillows were developing along the Feda Graben bordering faults until Middle Jurassic when the pillows were collapsed. Salt diapirs within the study area preferentially occupy the crest of the Feda Graben and their occurrence is controlled by the underlying faulted topography. The diapirs were fed by salt from the central and southern parts of the basin and were developed by different processes i.e. upbuilding, downbuilding. Various raft structures were developed in the graben area hanging wall while some uplift occurred in the footwall during Mesozoic rifting. The Feda Graben area experienced rifting from Late Jurassic to Early Cretaceous. The most pronounced subsidence episode related with this rifting in the Feda Graben area took place along the eastern bounding Gert Fault. The Mesozoic rifting event is marked by a major unconformity on the seismic sections throughout the study area. Furthermore, the region experienced basin inversion in Late Cretaceous. The effects of inversion are more pronounced in the western part and along the Gert Fault. The inversion phenomenon can be properly understood only when considered together with the geometry of the Late Jurassic half-graben. Due to some inconsistencies in the previously proposed models for the development of the Feda Graben, a new conceptual model has been constructed.     

Distinguishing Mountain Front and Mountain Block Recharge in an Intermontane Basin of the Himalayan Region

Intermontane basin aquifers worldwide, particularly in the Himalayan region, are recharged largely by the adjoining mountains. Recharge in these basins can occur either by water infiltrating from streams near mountain fronts (MFs) as mountain front recharge (MFR) or by sub-surface mountain block infiltration as mountain block recharge (MBR). MFR and MBR recharge are challenging to distinguish and are least quantified, considering the lack of extensive understanding of the hydrological processes in the mountains. This study used oxygen and hydrogen isotopes (δ¹⁸O and δ²H), electrical conductivity (EC) data, hydraulic head, and groundwater level data to differentiate MFR and MBR. Groundwater level data provide information about the groundwater-surface water interactions and groundwater flow directions, whereas isotopes and EC data are used to distinguish and quantify different recharge sources. The present methodology is tested in an intermontane basin of the Himalayan region. The results suggest that karst springs (KS) and deep groundwater (DGW) recharge are dominated by snowmelt (47% ± 10% and 46% ± 9%) as MBR from adjacent mountains, insignificantly affected by evaporation. The hydraulic head data and isotopes indicate Quaternary shallow groundwater (SGW) aquifer system recharge as MFR of local meteoric water with significant evaporation. The results indicate several flow paths in the aquifer system, a local flow for KS, intermediate flow for SGW, and regional flow for DGW. The findings will significantly impact water resource management in the area and provide vital baseline knowledge for sustainable groundwater management in other Himalayan intermontane basins.     

Smallholders adaptation to climate change in Mali

This study was undertaken to assess the potential impacts of climate change on agriculture in the Sikasso region of southern Mali, as part of an effort by the U.S. Agency for International Development (USAID) to integrate climate change adaptation considerations into their development projects. The region is considered to be the breadbasket of Mali, providing a substantial amount of the country’s food supplies as well as cotton for exchange earnings. The project had two components: modeling how climate change could affect production of cereal and cash crops in southern Mali; and conducting a stakeholder-driven vulnerability and adaptation assessment to identify potential options for addressing current and projected risks to agriculture from climate change. Projected changes in crop yields were based on a previous analysis that was extended for the purposes of this study. The projections suggested that the sensitivity of maize to changing weather conditions is relatively small (generally less than 10% change) under both dry and wet scenarios in 2030 and 2060. White (Irish) potatoes, the primary cash crop, are the most sensitive to changing weather conditions, with yields decreasing under both dry and wet conditions; yields could decrease by about 25% by 2060. Stakeholder workshops, field interviews, and an expert analysis were used to assess current and future climate-related vulnerability and to identify potential adaptation options. The main focus of the assessment was farmers in a village of about 3,000 people in the Sikasso region that practiced a rice-potato rotation system typical to the region. The farmers emphasized adaptation measures that require outside financial and technical assistance, for example installation of a water gate that would retain more water in the inland valley and increase the water table to flood rice fields during the rainy season and for furrow irrigation of potatoes during the dry season. Adaptations emphasized by both the farmers and representatives of regional technical services were crop diversification and germplasm improvement; soil and water management; access to equipment (plows, carts, oxen, and improved stoves); credit stockage villageois (CSV); and fertilizer.     

Comparative study of probable maximum precipitation and isohyetal maps for mountainous regions, Pakistan

Probable maximum precipitation (PMP) is widely used by hydrologists for appraisal of probable maximum flood (PMF) used for soil and water conservation structures, and design of dam spillways. A number of methods such as empirical, statistical and dynamic are used to estimate PMP, the most favored being statistical and hydro-meteorological. In this paper, PMP estimation in mountainous regions of Pakistan is studied using statistical as well as physically based hydro-meteorological approaches. Daily precipitation, dew point, wind speed and temperature data is processed to estimate PMP for a one-day duration. Maximum precipitation for different return periods is estimated by using statistical approaches such as Gumble and Log-Pearson type-III (LP-III) distribution. Goodness of fit (GOF) test, chi-square test, correlation coefficient and coefficient of determination were applied to Gumble and LP-III distributions. Results reveal that among statistical approaches, Gumble distribution performed the best result compared to LP-III distribution. Isohyetal maps of the study area at different return periods are produced by using the GIS tool, and PMP in mountainous regions varies from 150 to 320 mm at an average value of 230.83 mm. The ratio of PMP for one-day duration to highest observed rainfall (HOR) varied from 1.08 to 1.29 with an average value of 1.18. An appropriate frequency factor (K_m) is very important which is a function of mean for observed precipitation and PMP for 1-day duration, and K_m values varies from 2.54 to 4.68. The coefficient of variability (C_v) varies from minimum value of 28% to maximum value of 43.35%. It was concluded that the statistical approach gives higher results compared to moisture maximization (MM) approach. In the hydro-meteorological approach, moisture maximization (MM) and wind moisture maximization (WMM) techniques were applied and it was concluded that wind moisture maximization approach gives higher results of PMP as compared to moisture maximization approach as well as for Hershfield technique. Therefore, it is suggested that MM approach is the most favored in the study area for PMP estimation, which leads to acceptable results, compared to WMM and statistical approaches.     

Uncertainty analysis of runoff and sedimentation in a forested watershed using sequential uncertainty fitting method

The Soil and Water Assessment Tool(SWAT) was implemented in a small forested watershed of the Soan River Basin in northern Pakistan through application of the sequential uncertainty fitting(SUFI-2) method to investigate the associated uncertainty in runoff and sediment load estimation. The model was calibrated for a 10-year period(1991–2000) with an initial 4-year warm-up period(1987–1990), and was validated for the subsequent 10-year period(2001–2010). The model evaluation indices R~2(the coefficient of determination), NS(the Nash-Sutcliffe efficiency), and PBIAS(percent bias) for stream flows simulation indicated that there was a good agreement between the measured and simulated flows. To assess the uncertainty in the model outputs, p-factor(a 95% prediction uncertainty, 95PPU) and r-factors(average wideness width of the 95 PPU band divided by the standard deviation of the observed values) were taken into account. The 95 PPU band bracketed 72% of the observed data during the calibration and 67% during the validation. The r-factor was 0.81 during the calibration and 0.68 during the validation. For monthly sediment yield, the model evaluation coefficients(R~2 and NS) for the calibration were computed as 0.81 and 0.79, respectively; for validation, they were 0.78 and 0.74, respectively. Meanwhile, the 95 PPU covered more than 60% of the observed sediment data during calibration and validation. Moreover, improved model prediction and parameter estimation were observed with the increased number of iterations. However, the model performance became worse after the fourth iterations due to an unreasonable parameter estimation. Overall results indicated the applicability of the SWAT model with moderate levels of uncertainty during the calibration and high levels during the validation. Thus, this calibrated SWAT model can be used for assessment of water balance components, climate change studies, and land use management practices.