Evaluation of Satellite-Based Rainfall Estimates in the Lower Mekong River Basin (Southeast Asia)

Satellite-based precipitation is an essential tool for regional water resource applications that requires frequent observations of meteorological forcing, particularly in areas that have sparse rain gauge networks. To fully realize the utility of remotely sensed precipitation products in watershed modeling and decision-making, a thorough evaluation of the accuracy of satellite-based rainfall and regional gauge network estimates is needed. In this study, Tropical Rainfall Measuring Mission (TRMM) Multi-Satellite Precipitation Analysis (TMPA) 3B42 v.7 and Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) daily rainfall estimates were compared with daily rain gauge observations from 2000 to 2014 in the Lower Mekong River Basin (LMRB) in Southeast Asia. Monthly, seasonal, and annual comparisons were performed, which included the calculations of correlation coefficient, coefficient of determination, bias, root mean square error (RMSE), and mean absolute error (MAE). Our validation test showed TMPA to correctly detect precipitation or no-precipitation 64.9% of all days and CHIRPS 66.8% of all days, compared to daily in-situ rainfall measurements. The accuracy of the satellite-based products varied greatly between the wet and dry seasons. Both TMPA and CHIRPS showed higher correlation with in-situ data during the wet season (JuneSeptember) as compared to the dry season (NovemberJanuary). Additionally, both performed better on a monthly than an annual time-scale when compared to in-situ data. The satellite-based products showed wet biases during months that received higher cumulative precipitation. Based on a spatial correlation analysis, the average r-value of CHIRPS was much higher than TMPA across the basin. CHIRPS correlated better than TMPA at lower elevations and for monthly rainfall accumulation less than 500 mm. While both satellite-based products performed well, as compared to rain gauge measurements, the present research shows that CHIRPS might be better at representing precipitation over the LMRB than TMPA

Utilizing Satellite Based Observations and Physical Hydrological Modeling for Freshwater Ecosystem Health in the Lower Mekong River Basin

Freshwater availability is necessary to promote economic growth through agriculture, fisheries, transport, environmental health, and social equity.The National Aeronautics and Space Administration (NASA) and the Conservation International (CI) are partnering to use remote sensing Earth observations to improve regional efforts that assess natural resources for conservation and sustainable management. (Vollmer et al.,2018) have presented the social-ecological framework named the Freshwater Health Index (FHI), which takes account of the interplay between governance, stakeholders, freshwater ecosystems and the ecosystem services they provide.In this work, we develop decision support and making tools for natural resources conservation in the Lower Mekong by leveraging the FHI framework, multiple data products, and hydrological modeling capabilities (Mohammed et al., 2018). Modeling capabilities enable the integration of satellite-based daily gridded precipitation, air temperature, digital elevation model, soil characteristics, and land cover and land use information to simulate water flux framework

Landscape level characterization of seasonal floodplains under community based aquaculture: illustrating a case of the Ganges and the Mekong Delta

The project 'Community-based Fish Culture in Seasonal Floodplains' (henceforward the community-based fish culture project), CGIAR Challenge Program on Water and Food, aims to enhance fish production in seasonal floodplains to improve and sustain rural livelihoods in Bangladesh, Cambodia, China, Mali and Vietnam. Based on the premise that production from these water bodies could be enhanced by stocking locally important fish species, the community-based fish culture project seeks to develop technologies and institutional arrangements to support collective fish culture in the flood season. The current report provides a landscape level characterization of seasonal floodplains in two of these areas. We compare the Ganges seasonal floodplain agro-ecology in Bangladesh to that in the Mekong Delta of Cambodia and Vietnam. In both areas the project has been under implementation since the outset, but has met with contrasting resultsFlood plains, Aquaculture, Remote sensing

A MODIS-Based Automated Flood Monitoring System for Southeast Asia

Flood disasters in Southeast Asia result in significant loss of life and economic damage. Remote sensing information systems designed to spatially and temporally monitor floods can help governments and international agencies formulate effective disaster response strategies during a flood and ultimately alleviate impacts to population, infrastructure, and agriculture. Recent destructive flood events in the Lower Mekong River Basin occurred in 2000, 2011, 16 2013, and 2016 (http://ffw.mrcmekong.org/historical_rec.htm, April 24, 2017). The large spatial distribution of flooded areas and lack of proper gauge data in the region makes accurate monitoring and assessment of impacts of floods difficult. Here, we discuss the utility of applying satellite-based Earth observations for improving flood inundation monitoring over the flood-prone Lower Mekong River Basin. We present a methodology for determining near real-time surface water extent associated with current and historic flood events by training surface water classifiers from 8-day, 250-meter Moderate-resolution Imaging Spectroradiometer (MODIS) data spanning the length of the MODIS satellite record. The Normalized Difference Vegetation Index (NDVI) signature of permanent water bodies (MOD44W; Carroll et al., 2009) is used to train surface water classifiers which are applied to a time period of interest. From this, an operational nowcast flood detection component is produced using twice daily imagery acquired at 3-hour latency which performs image compositing routines to minimize cloud cover. Case studies and accuracy assessments against radar-based observations for historic flood events are presented. The customizable system has been transferred to regional organizations and near real-time derived surface water products are made available through a web interface platform. Results highlight the potential of near real-time observation and impact assessment systems to serve as effective decision support tools for governments, international agencies, and disaster responders

Applications of TRMM-based Multi-Satellite Precipitation Estimation for Global Runoff Simulation: Prototyping a Global Flood Monitoring System

Advances in flood monitoring/forecasting have been constrained by the difficulty in estimating rainfall continuously over space (catchment-, national-, continental-, or even global-scale areas) and flood-relevant time scale. With the recent availability of satellite rainfall estimates at fine time and space resolution, this paper describes a prototype research framework for global flood monitoring by combining real-time satellite observations with a database of global terrestrial characteristics through a hydrologically relevant modeling scheme. Four major components included in the framework are (1) real-time precipitation input from NASA TRMM-based Multi-satellite Precipitation Analysis (TMPA); (2) a central geospatial database to preprocess the land surface characteristics: water divides, slopes, soils, land use, flow directions, flow accumulation, drainage network etc.; (3) a modified distributed hydrological model to convert rainfall to runoff and route the flow through the stream network in order to predict the timing and severity of the flood wave, and (4) an open-access web interface to quickly disseminate flood alerts for potential decision-making. Retrospective simulations for 1998-2006 demonstrate that the Global Flood Monitor (GFM) system performs consistently at both station and catchment levels. The GFM website (experimental version) has been running at near real-time in an effort to offer a cost-effective solution to the ultimate challenge of building natural disaster early warning systems for the data-sparse regions of the world. The interactive GFM website shows close-up maps of the flood risks overlaid on topography/population or integrated with the Google-Earth visualization tool. One additional capability, which extends forecast lead-time by assimilating QPF into the GFM, also will be implemented in the future

Managing Water Resources in Large River Basins

Management of water resources in large rivers basins typically differs in important ways from management in smaller basins. While in smaller basins the focus of water resources management may be on project implementation, irrigation and drainage management, water use efficiency and flood operations; in larger basins, because of the greater complexity and competing interests, there is often a greater need for long-term strategic river basin planning across sectors and jurisdictions, and considering social, environmental, and economic outcomes. This puts a focus on sustainable development, including consumptive water use and non-consumptive water uses, such as inland navigation and hydropower. It also requires the consideration of hard or technical issues—data, modeling, infrastructure—as well as soft issues of governance, including legal frameworks, policies, institutions, and political economy. Rapidly evolving technologies could play a significant role in managing large basins. This Special Issue of Water traverses these hard and soft aspects of managing water resources in large river basins through a series of diverse case studies from across the globe that demonstrate recent advances in both technical and governance innovations in river basin management

Improving the recovery of monthly regional water storage using one year simulated observations of two pairs of GRACE-type satellite gravimetry constellation

Increasing the spatial sampling isotropy is a major issue in designing future missions dedicated to continue the task of the Gravity Recovery And Climate Experiment (GRACE) mission. From various possible future satellite gravimetry scenarios, the two-pair multi-orbit satellite configuration (Bender-type in the sequence), consisting of a coupled semi-polar pair (the same as GRACE) and an inclined pair of satellites seems to be an optimal mission choice. This contribution examines the performance of a Bender-type scenario at altitudes of 335 km and 352 km and inclinations of 89° and 63°, respectively, for improving the regional recovery of hydrological signals. To this end, we created one full year of simulated observations of the GRACE and Bender-type configurations. Our investigations include: 1) evaluating the feasible spatial resolution for the recovery of terrestrial water storage (TWS) changes in the presence of realistic instrumental noise and errors in the background models; 2) assessing the influence of aliasing errors in the TWS recovery and its separation from instrumental noise and introduced hydrological signals; and 3) analyzing the regional quality of the gravity-derived TWS results by assessing water storage changes over the 33 world major river basins. From our simulations, the Bender-derived spectral error curves indicate that, in spite of the instrumental noise, aliasing errors still contaminate the gravity fields above geopotential spherical harmonic coefficient (SHC) degree and order (d/o) 80 till 100. Regarding to the TWS recovery, we found notable improvements for the Bender-type configuration results in medium and small-scale basins, such as the Brahmaputra, Euphrates, Ganges, Indus, Mekong basins in Asia and the Yellow and Orange basins in South Africa. These results were achieved without applying post-processing, which was unachievable using simulations of one pair of GRACE-like configuration. Comparing the magnitudes of errors in the Bender-derived solutions with those of GRACE indicate that the accuracy derived from the Bender-type fields is about two times better than that of GRACE, specifically at medium spatial resolutions of 250 km (SHC d/o 80). We truncated the TWS recovery up to SHC d/o 80 in the spectral domain, whereas all comparisons are demonstrated in the spatial domain after a truncation of the solutions and WGHM field at d/o 60, since beyond this range; a relatively strong instrumental and aliasing errors contaminate the solutions. Our numerical results indicate that the spatial resolution of the Bender-type TWS recovery can be even higher for the basins with strong temporal water storage variations such as the Amazon basin. Short wavelength mass variations in basins with relatively weaker temporal TWS magnitude, such as the Murray basin, might still need the application of a filter with small averaging kernel

Evaluating the impacts of rice-based protection dykes on floodwater dynamics in the vietnamese mekong delta using geographical impact factor (Gif)

This study aims at evaluating the geographical influences of rice-based protection dykes on floodwater regimes along the main rivers, namely the Mekong and the Bassac, in the Vietnamese Mekong Delta (VMD). Specifically, numerous low dykes and high dykes have been constructed particularly in the upper delta’s floodplains to protect the double and triple rice cropping against the annual flooding. For the whole deltaic domain, a 1D-quasi-2D hydrodynamic model setup was used to simulate seventy-two (72) scenarios of dyke construction development in the context of low, medium, and high floods that occurred in the VMD to examine the effects of different flood magnitudes on a certain dyke construction area. Based on the model simulation results, we established an evaluation indicator, the so-called Geographical Impact Factor (GIF), to evaluate the impacts of zone-based dyke compartments on the floodwater regimes along the main rivers for different kinds of floods. Our findings revealed different rates of influences on the floodwater levels along the Mekong and Bassac Rivers under different scenarios of zone-based high-dyke developments. GIF is a useful index for scientists and decision-makers in land use planning, especially in rice intensification, in conjunction with flood management for the VMD and for similar deltas worldwide

Snow Cover and Precipitation Impacts on Dry Season Streamflow in the Lower Mekong Basin

Climate change impacts on dry season streamflow in the Mekong River are relatively understudied, despite the fact that water availability during this time is critically important for agricultural and ecological systems. Analyses of two gauging stations (Vientiane and Kratie) in the Lower Mekong Basin (LMB) show significant positive correlations between dry season (March through May, MAM) discharge and upper basin snow cover and local precipitation. Using snow cover, precipitation, and upstream discharge as predictors, we develop skillful regression models for MAM streamflow at Vientiane and Kratie, and force these models with output from a suite of general circulation model (GCM) experiments for the twentieth and twenty-first centuries. The GCM simulations predict divergent trends in snow cover (decreasing) and precipitation (increasing) over the twenty-first century, driving overall negligible long-term trends in dry season streamflow. Our study demonstrates how future changes in dry season streamflow in the LMB will depend on changes in snow cover and precipitation, factors that will need to be considered when assessing the full basin response to other climatic and non-climatic drivers