Measuring and modeling water and nutrient flux between a mid-Missouri stream and forested riparian zone in the central U.S.

Title from PDF of title page (University of Missouri--Columbia, viewed on February 21, 2013).The entire thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file; a non-technical public abstract appears in the public.pdf file.Dissertation advisor: Dr. Jason A. HubbartIncludes bibliographical references.Vita.Ph.D. University of Missouri--Columbia 2012."December 2012"To improve process based understanding of stream water-groundwater interactions, high-frequency water quantity data were collected from four stilling wells and two transects of piezometers (n = 6 each) during the 2011 water year along Brushy Creek, located in central Missouri. Weekly water quality data were also collected. Results indicate that Brushy Creek alternates between being a losing and gaining reach, along the study reach (length = 830 m), but is on average a losing stream (-3 x 10-5 m3 s-1 m-1). Annual average stream water NO3- was 0.53 mg L-1, while P, K and NH4+ concentrations were 0.13, 3.29 and 0.06 mg L-1, respectively. Annual average groundwater NO3- was 0.01 mg L-1, while total P, K and NH4+ concentrations were 0.03, 1.7 and 0.04 mg L-1, respectively. Results of a hyperbolic model indicated that NO3- and K exhibited dilution behavior while NH4+ had a concentration effect and P was hydrologically constant. Groundwater modeling with MODFLOW and HYDRUS - 1D indicates that karst geology promotes rapid water movement that can increase dominance of geochemical nutrient cycling pathways relative to biochemical nutrient cycling pathways. Baseline data and results of analysis presented in this dissertation will aid in identification, improvement and validation of management tools that will contribute to advancements in stream - riparian zone best management practices, in particular in karst hydrogeological environments.Includes bibliographical reference

Village level identification of sugarcane in Sangali, Maharashtra using open source data

Agriculture and crop monitoring are very important for an agrarian country like India. This study is done in June Khed village in the Sangli district of Maharashtra, India to assessing the efficiency of an open source cloud-based remote sensing platform Google Earth Engine (GEE), in the village-scale identification of sugarcane. The ground-truth data was collected and the efficiency of Landsat-8 and Sentinel-2 satellite data was assessed in driving GEE’s inbuilt Machine Learning classifiers: Classification and Regression Tree (CART), Support Vector Machine (SVM) and Random Forest (RF). Results were validated with the ground truth data and the official data. Of the methods used, SVM outperformed RF and CART with the lowest relative deviation (+9.2%), highest F1-score (0.8) and overall accuracy (78%), using the Sentinel-2 data. Results also indicated the in-situ use of observation data with high spatio-temporal resolution data. The validated model was then up-scaled for the Walwa Taluka level, to map sugarcane area that can be used for further agriculture tasks such as crop monitoring and yield prediction, leading to better management of crop and better formulating of sugarcane farmer policy

Water Management in the Noyyal River Basin A Situation Analysis

The Noyyal sub-basin, which is 3510 sq km in area, is part of the Cauvery basin that lies in the state of Tamil Nadu. It is a rapidly urbanizing sub-basin that includes the Class I cities of Coimbatore and Tiruppur as well as 84 smaller urban settlements. Water issues in this basin have been the focus of much public debate and action over the last two decades. Most of the debate, triggered by farmer agitations and court cases, has focused on the question of water pollution; water scarcity and sustainability issues have received relatively little attention. Recent bans on industrial effluent discharge into the Noyyal, as well as changes in water supply infrastructure, watershed development activities, urban demand and agricultural water use have dramatically altered the future of the Noyyal River and merit follow-up studies. The purpose of this situation analysis is to summarize the current state of knowledge regarding water resources management in the Noyyal sub-basin and identify critical knowledge gaps to inform water-related research in the basin. It is hoped that such an analysis will help those studying or working on water issues in the Noyyal, and also provide useful insights for other urbanizing basins

Depleting groundwater – an opportunity for flood storage?: a case study from part of the Ganges River Basin, India

Storing excess rainwater underground can become key in mitigating the frequency and magnitude of flood events. In this context, assessment of depleted groundwater storage that can be refilled in water surplus periods is imperative. The study uses Gravity Recovery and Climate Experiment (GRACE) data to identify variations in groundwater storage in the monsoonal Ramganga River basin (tributary of the Ganges, with an area of 32,753 km2) in India, over the nine-year period of 2002–2010. Results indicate that basin groundwater storage is depleting at the rate of 1.6 bill. m3 yr 1 . This depleted aquifer volume can be used to store floodwater effectively – up to 76% of the rainfall on average across the Ramganga with a maximum of 94% in parts of the basin. However, the major management challenge is to find and introduce technical and policy interventions to augment recharge rates to capture excess water, at required scales

Stream and shallow groundwater nutrient concentrations in an Ozark forested riparian zone of the central USA

Characterizing spatiotemporal variations in surface water (SW)–shallow groundwater (GW) nutrient concentrations is important to predict stream ecosystem responses to disturbance. Unfortunately, there is a lack of such information from mixed-deciduous semi-karst hydro-geological regions. Nitrate (NO3 -), total phosphorous (P), potassium (K) and ammonium (NH4 +) concentrations were monitored in a case study between an Ozark stream and riparian hardwood forest GW over the 2011 water year in the central USA. Average SW NO3 -, P, K and NH4 + concentrations were 0.53, 0.13, 3.29 and 0.06 mg L-1, respectively. Nine meters from the streambank, average GW NO3 -concentration was 0.01 mg L-1, while P, K and NH4 + concentrations were 0.03, 1.7 and 0.04 mg L-1, respectively. Hyperbolic dilution model results indicated that NO3 - and K exhibited dilution behavior, while NH4 + had a concentration effect and P was hydrologically constant. Observed seasonal NO3 - concentration patterns of winter maxima and summer minima in SW (1.164 and 0.133 mg L-1) and GW (0.019 and 0.011 mg L-1) were supported by previous studies yet exhibited distinct semi-karst characteristics. Results indicate that in addition to relatively low residence time, lower nutrient concentrations in GW (relative to SW) may suggest that shallow GW flow processes are important for vegetation removal and retention of nutrients from streams in semi-karst shallow groundwater systems of the central USA

Improving spatiotemporal groundwater estimates after natural disasters using remotely sensed data: a case study of the Indian Ocean Tsunami

The Indian Ocean Tsunami of December 26, 2004 devastated coastal ecosystems across South Asia. Along the coastal regions of South India, increased groundwater levels (GWL), largely caused by saltwater intrusion, infiltration from inundated land, and disturbance of freshwater lenses, were reported. Many agencies allocated funding for restoration and rehabilitation projects. However, to streamline funding allocation efforts, district-level groundwater inundation/recession data would have been a useful tool for planners. Thus, to ensure better preparedness for future disaster relief operations, it is crucial to quantify pre- and post-tsunami groundwater levels across coastal districts in India. Since regional scale GWL field observations are not often available, this study instead used space gravimetry data from NASA’s Gravity Recovery and Climate Experiment (GRACE), along with soil moisture data from the Global Land Data Assimilation Systems (GLDAS), to quantify GWL fluctuations caused by the tsunami. A time-series analysis of equivalent groundwater thickness was developed for February 2004–December 2005 and the results indicated a net increase of 274 % in GWLs along coastal regions in Tamil Nadu following the tsunami. The net recharge volume of groundwater due to the tsunami was 16.8 km3, just 15 % lower than the total annual groundwater recharge (19.8 km3) for the state of Tamil Nadu. Additionally, GWLs returned to average within 3 months following the tsunami. The analysis demonstrated the utility of remotely sensed data in predicting and assessing the impacts of natural disasters

Potential of MODFLOW to model hydrological interactions in a Semikarst floodplain of the Ozark Border Forest in the Central United States

Riparian shallow groundwater and nutrient movement is important for aquatic and forest ecosystem health. Understanding stream water (SW)–shallow groundwater (GW) interactions is necessary for proper management of floodplain biodiversity, but it is particularly confounding in underrepresented semikarst hydrogeological systems. The Modular Three-Dimensional Finite-Difference Ground-Water Flow Model (MODFLOW) was used to simulate shallow groundwater flow and nutrient transport processes in a second-growth Ozark border forest for the 2011 water year. MODFLOW provided approximations of hydrologic head that were statistically comparable to observed data (Nash–Sutcliffe = 0.47, r2 = 0.77, root-mean-square error = 0.61 cm, and mean difference = 0.46 cm). Average annual flow estimates indicated that 82% of the reach length was a losing stream, while the remaining 18% was gaining. The reach lost more water to the GW during summer (2405 m3 day-1) relative to fall (2184 m3 day-1), spring (2102 m3 day-1), and winter (1549 m3 day-1) seasons. Model results showed that the shallow aquifer had the highest nitrate loading during the winter season (707 kg day-1). A Particle-Tracking Model for MODFLOW (MODPATH) revealed significant spatial variations between piezometer sites (p = 0.089) in subsurface flow path and travel time, ranging from 213 m and 3.6 yr to 197 m and 11.6 yr. The current study approach is novel with regard to the use of transient flow conditions (as opposed to steady state conditions) in underrepresented semikarst geological systems of the U.S. Midwest. This study emphasizes the significance of semikarst geology in regulating SW–GW hydrologic and nutrient interactions and provides baseline information and modeling predictions that will facilitate future studies and management plans

Estimation of sediment load for Himalayan rivers: case study of Kaligandaki in Nepal

Himalayan regions have increasing sediment yield due to undulating topography, slope and improper watershed management. However, due to limited observation data, and site accessibility issues, less studies have quantiBed sedimentation loads in the Himalayas, especially Nepal. This has hindered the investments on run-of-river hydropower projects as high and unpredicted sedimentation has increased losses in hydropower production. Therefore, there is a need to understand key physical processes driving sedimentation in these regions, with the available data. This study used the Soil and Water Assessment Tool (SWAT) to estimate the sedimentation yields in the Kaligandaki basin of Nepal, which is an important tributary that drains into the Ganges. Multi-source data from Beld observations, remote sensing platforms, surveys and government records were used to set up and run the SWAT model for the Kaligandaki basin from 2000 to 2009. Results for the 10-year model run indicate that 73% of the total sediment load is estimated to come from the upstream regions (also known as High Himalayan region), while only 27% is contributed from the Middle and High Mountain regions (where land managementbased interventions were deemed most feasible for future scenarios). The average sediment concentration was 1986 mg/kg (ppm), with values of 8432 and 12 mg/kg (ppm) for maximum and minimum, respectively. Such high sedimentation rates can impact river ecosystems (due to siltation), ecosystem services and hydropower generation. In addition, model results indicate the need for better high frequency observation data. Results from this study can aid in better watershed management, which is aimed at reducing sedimentation load and protecting Himalayan rivers