Showing papers by "Faisal Hossain published in 2007"

A first approach to global runoff simulation using satellite rainfall estimation

Abstract: Many hydrological models have been introduced in the hydrological literature to predict runoff but few of these have become common planning or decision-making tools, either because the data requirements are substantial or because the modeling processes are too complicated for operational application. On the other hand, progress in regional or global rainfall-runoff simulation has been constrained by the difficulty of measuring spatiotemporal variability of the primary causative factor, i.e. rainfall fluxes, continuously over space and time. Building on progress in remote sensing technology, researchers have improved the accuracy, coverage, and resolution of rainfall estimates by combining imagery from infrared, passive microwave, and space-borne radar sensors. Motivated by the recent increasing availability of global remote sensing data for estimating precipitation and describing land surface characteristics, this note reports a ballpark assessment of quasi-global runoff computed by incorporating satellite rainfall data and other remote sensing products in a relatively simple rainfall-runoff simulation approach: the Natural Resources Conservation Service (NRCS) runoff Curve Number (CN) method. Using an Antecedent Precipitation Index (API) as a proxy of antecedent moisture conditions, this note estimates time-varying NRCS-CN values determined by the 5-day normalized API. Driven by multi-year (1998-2006) Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis, quasi-global runoff was retrospectively simulated with the NRCS-CN method and compared to Global Runoff Data Centre data at global and catchment scales. Results demonstrated the potential for using this simple method when diagnosing runoff values from satellite rainfall for the globe and for medium to large river basins. This work was done with the simple NRCS-CN method as a first-cut approach to understanding the challenges that lie ahead in advancing the satellite-based inference of global runoff. We expect that the successes and limitations revealed in this study will lay the basis for applying more advanced methods to capture the dynamic variability of the global hydrologic process for global runoff monlto~ngin real time. The essential ingredient in this work is the use of global satellite-based rainfall estimation.

Satellite-based Flood Modeling Using TRMM-based Rainfall Products.

Abstract: Increasingly available and a virtually uninterrupted supply of satellite-estimatedrainfall data is gradually becoming a cost-effective source of input for flood predictionunder a variety of circumstances. However, most real-time and quasi-global satelliterainfall products are currently available at spatial scales ranging from 0.25o to 0.50o andhence, are considered somewhat coarse for dynamic hydrologic modeling of basin-scaleflood events. This study assesses the question: what are the hydrologic implications ofuncertainty of satellite rainfall data at the coarse scale? We investigated this question onthe 970 km² Upper Cumberland river basin of Kentucky. The satellite rainfall productassessed was NASA's Tropical Rainfall Measuring Mission (TRMM) Multi-satellitePrecipitation Analysis (TMPA) product called 3B41RT that is available in pseudo real timewith a latency of 6-10 hours. We observed that bias adjustment of satellite rainfall data canimprove application in flood prediction to some extent with the trade-off of more falsealarms in peak flow. However, a more rational and regime-based adjustment procedureneeds to be identified before the use of satellite data can be institutionalized among floodmodelers.

The emerging role of satellite rainfall data in improving the hydro-political situation of flood monitoring in the under-developed regions of the world

Abstract: The systematic decline of in situ networks for hydrologic measurements has been recognized as a crucial limitation to advancing hydrologic monitoring in medium to large basins, especially those that are already sparsely instrumented. As a collective response, sections of the hydrologic community have recently forged partnerships for the development of space-borne missions for cost-effective, yet global, hydrologic measurements by building upon the technological advancements since the last two decades. In this article, we review the state-of-the-art on flood monitoring in medium and large ungauged basins where satellite remote sensing can facilitate development of a cost-effective mechanism. We present our review in the context of the current hydro-political situation of flood monitoring in flood-prone developing nations situated in international river basins (IRBs). Given the large number of such basins and the difficulty in acquisition of multi-faceted geophysical data, we argue that the conventional data-intensive implementation of physically based hydrologic models that are complex and distributed is time-consuming for global assessment of the utility of proposed global satellite hydrologic missions. A more parsimonious approach is justified at the tolerable expense of accuracy before such missions begin operation. Such a parsimonious approach can subsequently motivate the identified international basins to invest greater effort in conventional and detailed hydrologic studies to design a prototype flood forecasting system in an effort to overcome the hydro-political hurdles to flood monitoring. Through a modeling exercise involving an open-book watershed concept, we demonstrate the value of a parsimonious approach in understanding the utility of NASA-derived satellite rainfall products. It is critical now that real-world operational flood forecasting agencies in the under-developed world come forward to collaborate with the research community in order to leverage satellite rainfall data for greater societal benefit for inhabitants in IRBs.

Geostatistically based management of arsenic contaminated ground water in shallow wells of Bangladesh

Abstract: This paper investigates the effectiveness of geostatistical approaches, specifically ordinary kriging, for regional management of arsenic contaminated shallow ground water in Bangladesh. The arsenic database for reference comprised the nation-wide survey (of 3534 drinking wells) completed in 1999 by the British Geological Survey (BGS) in collaboration with the Department of Public Health Engineering (DPHE) of Bangladesh. A Monte Carlo (MC) framework was devised for selection of randomly-sampled networks of wells from this reference database. Each randomly sampled network was assumed an equi-probable exploratory field campaign designed commensurably with the requirements of rapidity and cost-effectiveness in a rural setting. In general, the kriging method was found to underestimate the arsenic concentration at non-sampled locations. This underestimation exceeded the safe limits at the Holocene region of Southcentral Bangladesh. The probability of successful prediction of safe wells for this region was found to be 72% (WHO safe limit – 10 ppb) and 78% (Bangladesh safe limit – 50 ppb). For the Pleistocene Northwestern region of Bangladesh, the safe well prediction probability was in the ranges of 90%–97%. The relatively more contaminated Holocene region in Southcentral Bangladesh, on other hand, was found more amenable to accurate geostatistical prediction of unsafe wells. Findings from this study exemplify that, while mainstream geostatistical approaches (e.g., ordinary kriging) may not provide the most accurate prediction of mean arsenic concentration at non-sampled locations, they can delineate an approximate strategy for management of arsenic contaminated shallow ground water if applied carefully. The kriging methodology is applied to a test case in Bangladesh; the approach, however, is general and is expected to have application in rural settings for other developing countries where arsenic contamination of ground water is also widespread (e.g., parts of India, Vietnam, Taiwan and Mexico).

An open-book watershed model for prototyping space-borne flood monitoring systems in International River Basins

Abstract: A new era involving both simple and complex hydrologic modeling of un-gauged river basins may now emerge with the anticipated global availability of high resolution satellite rainfall data from the proposed Global Precipitation Measurement (GPM) mission. This era of application pertains to rapid prototyping of GPM-based flood monitoring systems for downstream nations in International River Basins (IRBs) where basin-wide in-situ rainfall data is unavailable due to lack of either an infrastructure or a treaty for real-time data sharing with upstream riparian nations. In this paper, we develop, verify and apply an open-book watershed model for demonstrating the value of a parsimonious modeling scheme in quick prototyping of satellite rainfall-based flood monitoring systems for lowermost nations in flood-prone IRBs. The open-book watershed modeling concept was first formulated by Yen and Chow [1969. A laboratory study of surface runoff due to moving rainstorms. Water Resources Research 5(5), 989-1006] more than 30years ago as a convenient and pragmatic framework to understand the underlying physics behind surface hydrologic phenomena. Our developed model is based on first principles of conservation of mass and momentum that parsimoniously represents the static geophysical features of a basin with minimum calibration. Such a generic and parsimonious representation has the added potential to supplement complex hydrologic models for stakeholder involvement and conflict management in transboundary river basins, among many additional applications. We first demonstrate the physical consistency of our model through sensitivity analysis of some geophysical basin parameters pertinent to the rainfall-runoff transformation. Next, we simulate the stream-flow hydrograph for a 4-month long period using basin-wide radar (WSR-88D) rainfall data over Oklahoma assuming an open-book river basin configuration. Finally, using the radar-simulated hydrograph as the benchmark, and assuming a two-nation hypothetical IRB over Oklahoma, we explored the impact of assimilating NASA's real-time satellite rainfall data (IR-3B41RT) over the upstream nation on the flow monitoring accuracy for the downstream nation. We developed a relationship defining the improvement in flow monitoring that can be expected from assimilating IR-3B41RT over transboundary regions as a function of the relative area occupied by the downstream nation for a semi-arid region. The relative improvement in flow monitoring accuracy for the downstream nation was found to be clearly high (over 35% reduction in root mean squared error) when more than 90% of the basin is transboundary. However, flow monitoring accuracy reduces considerably and even becomes negative when 60% or less of the basin area is transboundary to the downstream nation. Our findings, although hypothetical and very regime-specific, illustrate very clearly the feasibility of utilizing anticipated GPM data to alleviate the current flood monitoring limitations experienced by many nations in IRBs through the application of a generic and parsimonious model.

Watershed modeling of dissolved oxygen and biochemical oxygen demand using a hydrological simulation Fortran program

Abstract: Several inland water bodies in the St. Louis Bay watershed have been identified as being potentially impaired due to low level of dissolved oxygen (DO). In order to calculate the total maximum daily loads (TMDL), a standard watershed model supported by U.S. Environmental Protection Agency, Hydrological Simulation Program Fortran (HSPF), was used to simulate water temperature, DO, and bio-chemical oxygen demand (BOD). Both point and non-point sources of BOD were included in watershed modeling. The developed model was calibrated at two time periods: 1978 to 1986 and 2000 to 2001 with simulated DO closely matched the observed data and captured the seasonal variations. The model represented the general trend and average condition of observed BOD. Water temperature and BOD decay are the major factors that affect DO simulation, whereas nutrient processes, including nitrification, denitrification, and phytoplankton cycle, have slight impacts. The calibrated water quality model provides a representative linkage between the sources of BOD and in-stream DO\BOD concentrations. The developed input parameters in this research could be extended to similar coastal watersheds for TMDL determination and Best Management Practice (BMP) evaluation.

Satellites as the Panacea to Transboundary Limitations for Longer Term Flood Forecasting

Abstract: This article presents a brief overview of the challenges associated with long-term flood forecasting, as experienced by many flood-prone developing nations, due to transboundary limitations. The potential of satellite rainfall data to overcome such limitations is highlighted. The article also discusses the limitations of rainfall estimates from space-borne platforms due to their high degree of uncertainty in measurement. This is contrasted by the vantage of space that makes them immune to transboundary limitations of real-time sharing of rainfall data across boundaries. Since the availability of satellite rainfall is expected to magnify with the proposed Global Precipitation Measurement (GPM) mission in 2013, it is important for flood forecasting agencies in developing countries to initiate a range of error propagation studies in order to assess the true worth of globally available satellite rainfall data.

Correction to "A two-dimensional satellite rainfall error model"

Abstract: Two corrections to the above-named article [ibid., vol. 44, no. 6, pp. 1511? 1522, Jun. 2006] are indicated here. They are, respectively, to the biography for author F. Hossain and to reference [17].

Developing a Graphical User Interface to Improve Learning of Stochastic Theory in Hydrosciences in the Classroom

Abstract: The objective of this paper is two fold: i) to gauge the current state of instruction of stochastic theory for water resources in US universities and thereby identify the potential for curriculum improvement and ii) to demonstrate a proof of concept of a computer-assisted Graphical User Interface (GUI) to improve the current state of learning in the classroom of stochastic theory for hydrosciences. Our study indicates that 84% of the total 241 relevant courses surveyed are available only at the graduate level, while 4.5% and 11.5% were either dual-listed or undergraduate-level courses, respectively. It is worthwhile for the CE educators to consider creating more undergraduate variants of such courses and offer them to students early in their education experience. To further popularize stochastic theory education in context of water resources, more computer-assisted graphics-based schemes should also be used in the undergraduate classroom. The illustration provided herein is a GUI that connects a comprehensive space-time stochastic model for generating rainfall fields that exhibit complex natural variability. Our main finding, based on on-going educational software development, is that effective instructional software building requires evolution from the simplest configuration if its continual upgrade is to continue in liaison with student software developers that are usually available from a computer science department of the university.