Abstract. Remote sensing and satellite geodetic observations are capable of hydrologic monitoring of freshwater resources. Although satellite radar altimetry has been used in monitoring water level or discharge, its use is often limited to monitoring large rivers (>1 km) with longer interval periods (>1 week) because of its low temporal and spatial resolutions (i.e., satellite revisit period). Several studies have reported successful retrieval of water levels for small rivers as narrow as 40 m. However, processing current satellite altimetry signals for such small water bodies to retrieve water levels accurately remains challenging. Physically, the radar signal returned by water bodies smaller than the satellite footprint is most likely contaminated by non-water surfaces, which may degrade the measurement quality. In order to address this scientific challenge, we carefully selected the waveform shapes corresponding to the range measurement resulting from standard retrackers for the European Space Agency's (ESA's) Envisat (Environmental Satellite) radar altimetry. We applied this approach to small (40–200 m in width) and medium-sized (200–800 m in width) rivers and small lakes (extent <1000 km2) in the humid tropics of Southeast Asia, specifically in Indonesia. This is the first study that explored the ability of satellite altimetry to monitor small water bodies in Indonesia. The major challenges in this study include the size of the water bodies that are much smaller than the nominal extent of the Envisat satellite footprint (e.g., ~250 m compared to ~1.7 km, respectively) and slightly smaller than the along-track distance (i.e., ~370 m). We addressed this challenge by optimally using geospatial information and optical remote sensing data to define the water bodies accurately, thus minimizing the probability of non-water contamination in the altimetry measurement. Considering that satellite altimetry processing may vary with different geographical regions, meteorological conditions, or hydrologic dynamic, we further evaluated the performance of all four Envisat standard retracking procedures. We found that satellite altimetry provided a good alternative or the only means in some regions of measuring the water level of medium-sized rivers and small lakes with high accuracy (root mean square error (RMSE) of 0.21–0.69 m and a correlation coefficient of 0.94–0.97). In contrast to previous studies, we found that the commonly used Ice-1 retracking algorithm was not necessarily the best retracker among the four standard waveform retracking algorithms for Envisat radar altimetry observing inland water bodies. As a recommendation, we propose to include the identification and selection of standard waveform shapes to complete the use of standard waveform retracking algorithms for Envisat radar altimetry data over small and medium-sized rivers and small lakes.

Indonesian Borneo (Kalimantan) sustains ~37 million hectares of native tropical forest. Numerous large-scale infrastructure projects aimed at promoting land-development activities are planned or ongoing in the region. However, little is known of the potential impacts of this new infrastructure on Bornean forests or biodiversity. We found that planned and ongoing road and rail-line developments will have many detrimental ecological impacts, including fragmenting large expanses of intact forest. Assuming conservatively that new road and rail projects will influence only a 1 km buffer on either side, landscape connectivity across the region will decline sharply (from 89% to 55%) if all imminently planned projects proceed. This will have particularly large impacts on wide-ranging, rare species such as rhinoceros, orangutans, and elephants. Planned developments will impact 42 protected areas, undermining Indonesian efforts to achieve key targets under the Convention on Biological Diversity. New infrastructure will accelerate expansion in intact or frontier regions of legal and illegal logging and land colonization as well as illicit mining and wildlife poaching. The net environmental, social, financial, and economic risks of several imminent projects—such as parallel border roads in West, East, and North Kalimantan, new Trans-Kalimantan road developments in Central Kalimantan and North Kalimantan, and freeways and rail lines in East Kalimantan—could markedly outstrip their overall benefits. Such projects should be reconsidered in light of rigorous cost-benefit frameworks.

Mofizul IK Forhad (5) , Mariam Akhter (4-6) , Zaheer Iqbal (4) , Falgoonee Kumar Mondol (6) Allometric models are commonly used to estimate biomass, nutrients and carbon stocks in trees, and contribute to an understanding of forest status and resource dynamics. The selection of appropriate and robust models, therefore, have considerable influence on the accuracy of estimates obtained. Allometric models can be developed for individual species or to represent a community or bioregion. In Bangladesh, the nation forest inventory classifies tree and forest resources into five zones (Sal, Hill, Coastal, Sundarbans and Village), based on their floristic composition and soil type. This study has developed allometric biomass models for multi-species of the Sal zone. The forest of Sal zone is dominated by Shorea robusta Roth. The study also investigates the concentrations of Nitrogen, Phosphorus, Potassium and Carbon in different tree components. A total of 161 individual trees from 20 different species were harvested across a range of tree size classes. Diameter at breast height (DBH), total height (H) and wood density (WD) were considered as predictor variables, while total above-ground biomass (TAGB), stem, bark, branch and leaf biomass were the output variables of the allometric models. The best fit allometric biomass model for TAGB, stem, bark, branch and leaf were: ln (TAGB) =-2.460 + 2.171 ln (DBH) + 0.367 ln (H) + 0.161 ln (WD); ln (Stem) =-3.373 + 1.934 ln (DBH) + 0.833 ln (H) + 0.452 ln (WD); ln (Bark) =-5.87 + 2.103 ln (DBH) + 0.926 ln (H) + 0.587 ln (WD); ln (Branch) =-3.154 + 2.798 ln (DBH)-0.729 ln (H)-0.355 ln (WD); and ln (Leaf) =-4.713 + 2.066 ln (DBH), respectively. Nutrients and carbon concentration in tree components varied according to tree species and component. A comparison to frequently used regional and pantropical biomass models showed a wide range of model prediction error (35.48 to 85.51%) when the observed TAGB of sampled trees were compared with the estimated TAGB of the models developed in this study. The improved accuracy of the best fit model obtained in this study can therefore be used for more accurate estimation of TAGB and carbon and nutrients in TAGB for the Sal zone of Bangladesh.

As part of operational guidance of mangrove forest rehabilitation in the Mahakam delta, Indonesia, site suitability mapping for 14 species of mangrove was modelled by combining 4 underlying factors-clay, sand, salinity and tidal inundation. Semivariogram analysis and a geographic information system (GIS) were used to apply a site-suitability model, while kriging interpolation generated surface layers, based on sample point data collection. The tidal inundation map was derived from a tide table and a digital elevation model from topographic maps. The final site-suitability maps were produced using spatial analysis technique, by overlaying all surface layers. We used a Gaussian model to adjust a semivariogram graph in order to help to understand the variation of sample data values, and create a natural surface layer of data distribution over the area of study. By examining the statistical value and the visual inspection of surface layers, we saw that the models were consistent with the expected data behavior; therefore, we assumed that interpolation has been carried out appropriately. Our site-suitability map showed that Avicennia species was the most suitable species and matched with 50% of the study area, followed by Nypa fruticans, which occupied about 42%. These results were actually consistent with the mangrove zoning pattern in the region prior to deforestation and conversion.