GPS-derived deformation rates in northwestern Himalaya and Ladakh

Deformation rates derived from GPS measurements made at two continuously operating stations at Leh (34.1°N, 77.6°E) and Hanle (32.7°N, 78.9°E), and eight campaign sites in the trans-Himalayan Ladakh spanning 11 years (1997–2008), provide a clear picture of the kinematics of this region as well as the convergence rate across northwestern Himalaya. All the Ladakh sites move 32–34 mm/year NE in the ITRF2005 reference frame, and their relative velocities are 13–16 mm/year SW in the Indian reference frame and ~19 mm/year W with reference to the Lhasa IGS station in southeastern Tibet. The results indicate that there is no statistically significant deformation in the 200-km stretch between the continuous sites Leh and Hanle as well as between Leh and Nubra valley sites along the Karakoram fault, whereas the sites in and around the splayed Karakoram fault region indicate surface deformation of 2.5 mm/year. Campaign sites along the Karakoram fault zone indicate a fault parallel surface motion of 1.4–2.5 mm/year in the Tangste and western Panamik segment of the Karakoram fault, which quantifies the best possible GPS-derived dextral slip rate of 3 mm/year along this fault during this 11-year period. Baselines of Ladakh sites show convergence rates of 15–18 mm/year with respect to south India and 12–15 mm/year with respect to Delhi in north India and Almora in the Himalaya ~400 km north-northeast of Delhi. These constitute an arc normal convergence of 12–15 mm/year across the western Himalaya, which is consistent with arc normal convergence all along the Himalayan arc from west to east. Baseline extension rates of 14–16 mm/year between Lhasa and Ladakh sites are consistent with the east–west extension rate of Tibetan Plateau.     

A land surface data assimilation framework using the land information system: Description and applications

The Land Information System (LIS) is an established land surface modeling framework that integrates various community land surface models, ground measurements, satellite-based observations, high performance computing and data management tools. The use of advanced software engineering principles in LIS allows interoperability of individual system components and thus enables assessment and prediction of hydrologic conditions at various spatial and temporal scales. In this work, we describe a sequential data assimilation extension of LIS that incorporates multiple observational sources, land surface models and assimilation algorithms. These capabilities are demonstrated here in a suite of experiments that use the ensemble Kalman filter (EnKF) and assimilation through direct insertion. In a soil moisture experiment, we discuss the impact of differences in modeling approaches on assimilation performance. Provided careful choice of model error parameters, we find that two entirely different hydrological modeling approaches offer comparable assimilation results. In a snow assimilation experiment, we investigate the relative merits of assimilating different types of observations (snow cover area and snow water equivalent). The experiments show that data assimilation enhancements in LIS are uniquely suited to compare the assimilation of various data types into different land surface models within a single framework. The high performance infrastructure provides adequate support for efficient data assimilation integrations of high computational granularity.     

Nitrogen uptake and denitrification in restored and unrestored streams in urban Maryland, USA

There is growing interest in rates of nitrate uptake and denitrification in restored streams to better understand the effects of restoration on nitrogen processing. This study quantified nitrate uptake in two restored and two unrestored streams in Baltimore, Maryland, USA using nitrate additions, denitrification enzyme assays, and a ¹⁵N isotope tracer addition in one of the urban restored streams, Minebank Run. Restoration included either incorporation of stormwater ponds below a storm drain and catch basins to attenuate flow or hydrologic “reconnection” of a stream channel to its floodplain. Stream restoration was conducted for restoring aging sanitary and bridge infrastructure and introducing some stormwater management in watersheds developed prior to current regulations. Denitrification potential in sediments was variable across streams, whereas nitrate uptake length appeared to be significantly correlated to surface water velocity, which was low in the restored streams during summer baseflow conditions. Uptake length of NO₃ ⁻–N in Minebank Run estimated by ¹⁵N tracer addition was 556 m. Whole stream denitrification rates in Minebank Run were 153 mg NO₃ ⁻–N m⁻² day⁻¹, and approximately 40% of the daily load of nitrate was estimated to be removed via denitrification over a distance of 220.5 m in a stream reach designed to be hydrologically “connected” to its floodplain. Increased hydrologic residence time in Minebank Run during baseflow likely influenced rates of whole stream denitrification, suggesting that hydrologic residence time may be a key factor influencing N uptake and denitrification. Restoration approaches that increase hydrologic “connectivity” with hyporheic sediments and increase hydrologic residence time may be useful for stimulating denitrification. More work is necessary, however, to examine changes in denitrification rates in restored streams across different seasons, variable N loads, and in response to the “flashy” hydrologic flow conditions during storms common in urban streams.     

Mesoscale model forecast verification during monsoon 2008

There have been very few mesoscale modelling studies of the Indian monsoon, with focus on the verification and intercomparison of the operational real time forecasts. With the exception of Das et al (2008), most of the studies in the literature are either the case studies of tropical cyclones and thunderstorms or the sensitivity studies involving physical parameterization or climate simulation studies. Almost all the studies are based on either National Center for Environmental Prediction (NCEP), USA, final analysis fields (NCEP FNL) or the reanalysis data used as initial and lateral boundary conditions for driving the mesoscale model.     

Accuracy assessment in cotton acreage estimation using Indian remote sensing satellite data

The accuracy of cotton crop classification using satellite data has been assessed with respect to a detailed land cover map prepared by field survey. The effect of spatial resolution on classification accuracy was studied using LISS-I (spatial resolution 72.6 m) and LISS-II data (spatial resolution 36.25 m) of the Indian remote sensing satellite IRS-1B. The performances of the maximum likelihood and the minimum distance to mean as classifiers have also been assessed. LISS-II data have been found to give a higher classification accuracy. The estimate of cotton acreage using LISS-II data was closer to that obtained from the base map. The maximum likelihood classifier (MXL) and the minimum distance to mean (MDM) classifier performed equally well.     

Potassium and Residue Management Options to Enhance Productivity and Soil Quality in Zero Till Maize–Wheat Rotation

Crop residue burning and imbalanced use of chemical fertilizers in intensive cereal–cereal rotations are present ecological threats in any agro‐ecosystem of the world. Therefore, identification of best suitable agricultural practices can be a feasible option. The present experiment was initiated in 2013 and consisted of four residue levels (0, 2, 4, and 6 Mg ha^?1) and five potassium (K) levels (0, 50, 100, 150% recommended dose of K and 50%RDK+K solubilizing bacteria, KSB). Crop residue (CR) and K management significantly improve crop and soil quality associated parameters. Among the treatments, maximum increase in crop growth, physiological parameters, grain yield, quality aspects, and water productivity are recorded with the application of 4–6 Mg ha^?1 CR. Application of 50%RDK+KSB also significantly increases crop and soil related parameters. Soil quality indicators (bulk density, pH, electrical conductivity, and available micronutrients) do not vary significantly with CR and K management. Change in soil organic carbon status, soil enzymes, and potassium‐solubilizing bacterial count are significantly increased with 4–6 Mg ha^?1 CR and application of 50%RDK+KSB, and this is in accordance with correlation study carried out. Therefore, it is concluded that CR retention (4–6 Mg ha^?1) and reduction of inorganic K fertilizer by 50% and inoculation of KSB enhance the soil quality indicators and thereby improve crop growth, physiological parameters, grain yield, and quality aspects along with water productivity under zero till maize–wheat rotation.     

Modeling the depletion of dissolved oxygen in a lake due to algal bloom: Effect of time delay

We propose and analyze a non-linear mathematical model for algal bloom in a lake to account for the delay in conversion of detritus into nutrients. It is assumed that there is a continuous inflow of nutrients in the lake due to agricultural run off. The model involves four variables, namely nutrient concentration, algal population density, detritus density and dissolved oxygen concentration. The dynamics of the model is studied in terms of local stability analysis and Hopf-bifurcation analysis. It is found that the positive equilibrium of the model may switch from stability to instability to stability, and eventually instability sets in under certain conditions. The numerical simulation is performed to support the analytical results.     

The MJO’s impact on rainfall trends over the Congo rainforest

Climate Dynamics - A significant declining trend in rainfall over the Congo basin has been observed over the past three decades. Since the Madden–Julian oscillation (MJO) is a major forcing...