Hidayat Hidayat

Spatial autocorrelation and arbitrary ordering of heterogeneous conditioning factors can distort algorithm comparisons in landslide susceptibility modeling. This study benchmarks four tree ensembles, a tabular multilayer perceptron, a support-vector classifier, penalized logistic regression, a frequency-ratio reference, and three one-dimensional convolutional architectures using 695 landslide locations, 695 pseudo-absence locations, and 13 conditioning factors in Bogor Regency, Indonesia. Models were evaluated by repeated nested five-fold spatial-block cross-validation using 5 km blocks; tuning was confined to inner training blocks, and discrimination, precision–recall performance, Brier score, expected calibration error, and calibration slope were computed from pooled out-of-fold predictions. Tree ensembles achieved ROC-AUC 0.833–0.839 and PR-AUC 0.848–0.852, whereas the convolutional models achieved ROC-AUC 0.794–0.807. CatBoost exceeded ResNet by 0.032 ROC-AUC (95% CI 0.013–0.051), and random forest exceeded the EfficientNet-inspired 1-D MBConv model by 0.036 (95% CI 0.016–0.062); ResNet and the tabular multilayer perceptron were not distinguishable. Across 30 factor orderings, convolutional ROC-AUC varied by approximately 0.05–0.07. Under an equal budget of 24 unique candidates, six search strategies produced best inner-CV AUCs of 0.723–0.729. TreeSHAP analysis of random forest ranked elevation, geology, terrain ruggedness, NDVI, and soil type as the leading contributors. For this small tabular geospatial dataset and evaluation design, model representation and spatial validation were more consequential than added architectural or metaheuristic complexity.

Tropical peatlands are among the most carbon-dense ecosystems on Earth, and their water storage dynamics strongly control these carbon stocks. The hydrological functioning of tropical peatlands differs from that of northern peatlands, which has not yet been accounted for in global land surface models (LSMs). Here, we integrated tropical peat-specific hydrology modules into a global LSM for the first time, by utilizing the peatland-specific model structure adaptation (PEATCLSM) of the NASA Catchment Land Surface Model (CLSM). We developed literature-based parameter sets for natural (PEATCLSM _Trop,Nat ) and drained (PEATCLSM _Trop,Drain ) tropical peatlands. The operational CLSM version (which includes peat as a soil class) and PEATCLSM _Trop,Nat were forced with global meteorological input data and evaluated over the major tropical peatland regions in Central and South America, the Congo Basin, and Southeast Asia. Evaluation against a unique and extensive data set of in situ water level and eddy covariance-derived evapotranspiration showed an overall improvement in bias and correlation over all three study regions. Over Southeast Asia, an additional simulation with PEATCLSM _Trop,Drain was run to address the large fraction of drained tropical peatlands in this region. PEATCLSM _Trop,Drain outperformed both CLSM and PEATCLSM _Trop,Nat over drained sites. Despite the overall improvements of both tropical PEATCLSM modules, there are strong differences in performance between the three study regions. We attribute these performance differences to regional differences in accuracy of meteorological forcing data, and differences in peatland hydrologic response that are not yet captured by our model.

Wetlands are important reservoirs of water, carbon and biodiversity. They are typical landscapes of lowland regions that have high potential for water retention. However, the hydrology of these wetlands in tropical regions is often studied in isolation from the processes taking place at the catchment scale. Our main objective is to study the hydrological dynamics of one of the largest tropical rainforest regions on an island using a combination of satellite remote sensing and novel observations from dedicated field campaigns. This contribution offers a comprehensive analysis of the hydrological dynamics of two neighbouring poorly gauged tropical basins; the Kapuas basin (98 700 km²) in West Kalimantan and the Mahakam basin (77 100 km²) in East Kalimantan, Indonesia. Both basins are characterised by vast areas of inland lowlands. Hereby, we put specific emphasis on key hydrological variables and indicators such as discharge and flood extent. The hydroclimatological data described herein were obtained during fieldwork campaigns carried out in the Kapuas over the period 2013–2015 and in the Mahakam over the period 2008–2010. Additionally, we used the Tropical Rainfall Measuring Mission (TRMM) rainfall estimates over the period 1998–2015 to analyse the distribution of rainfall and the influence of El-Niño – Southern Oscillation. Flood occurrence maps were obtained from the analysis of the Phase Array type L-band Synthetic Aperture Radar (PALSAR) images from 2007 to 2010. Drought events were derived from time series of simulated groundwater recharge using time series of TRMM rainfall estimates, potential evapotranspiration estimates and the threshold level approach. The Kapuas and the Mahakam lake regions are vast reservoirs of water of about 1000 and 1500 km² that can store as much as 3 and 6.5 billion m³ of water, respectively. These storage capacity values can be doubled considering the area of flooding under vegetation cover. Discharge time series show that backwater effects are highly influential in the wetland regions, which can be partly explained by inundation dynamics shown by flood occurrence maps obtained from PALSAR images. In contrast to their nature as wetlands, both lowland areas have frequent periods with low soil moisture conditions and low groundwater recharge. The Mahakam wetland area regularly exhibits low groundwater recharge, which may lead to prolonged drought events that can last up to 13 months. It appears that the Mahakam lowland is more vulnerable to hydrological drought, leading to more frequent fire occurrences than in the Kapuas basin.

Wetlands are important reservoirs of water, carbon and biodiversity. They are typical landscapes of lowland regions that have high potential for water retention. However, the hydrology of these wetlands in tropical regions is often studied in isolation from the processes taking place at the catchment scale. This contribution offers a comprehensive analysis of the hydrological dynamics of two neighbouring poorly gauged tropical basins; the Kapuas basin (98,700 km²) in West Kalimantan and the Mahakam basin (77,100 km²) in East Kalimantan, Indonesia. Both basins are characterized by vast areas of inland lowlands. The hydro-climatological data described herein were obtained during fieldwork campaigns carried out in the Kapuas over the period 2013–2015 and in the Mahakam over the period 2008–2010. Additionally, we used the Tropical Rainfall Measuring Mission (TRMM) rainfall estimates over the period 1998–2015 for analysing the distribution of rainfall and the influence of El-Niño – Southern Oscillation. Flood occurrence maps were obtained from the analysis of the Phase Array L-band Synthetic Aperture Radar (PALSAR) images of 2007 through 2010. Drought events were derived from time-series of simulated groundwater recharge using time series of TRMM rainfall estimates, potential evapotranspiration estimates and the threshold level approach. The Kapuas and the Mahakam lakes region are vast reservoirs of water of about 1000 km² and 1500 km² that can store as much as 3 billion m³ and 6.5 billion m³ of water, respectively. These storage capacity values can be doubled considering the area of flooding under vegetation cover. Discharge time-series show that backwater effects are highly influential in the wetland regions, which can be partly explained by inundation dynamics shown by flood occurrence maps obtained from PALSAR images. In contrast to their nature as a wetland, both lowland areas have frequent periods with low soil moisture conditions and low groundwater recharge. The Mahakam wetland area regularly exhibits low groundwater recharges, which may lead to prolonged drought events that can last up to 13 months. It appears that the Mahakam lowland is more vulnerable to hydrological drought leading to fire occurrence than the Kapuas basin.

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.

Autogenic scouring in sharp river bends has received ample attention in laboratory and modeling studies. These studies have significantly advanced our understanding of how flow processes are influenced by strong curvature and how they affect the bathymetry. Here we present a 300 km reach of the Mahakam River in Indonesia, which features several sharp bends (W/R > 0.5), providing a unique field data set to validate existing knowledge on sharp bends. Scour depths were found to strongly exceed what can be expected based on existing understanding of sharp bends and are highly correlated with curvature. A comprehensive stream reconnaissance was carried out to compare the occurrence of sharp bends and deep scours with lateral bank migration. Histograms of the occurrence of erosive, stable, advancing, and bar‐type banks as a function of curvature quantify the switch from a mildly curved bend regime to a sharp bend regime. In mild bends, outer banks erode and inner banks advance. In sharp bends the erosion pattern inverts. Outer banks stabilize or advance, while inner banks erode. In sharply curved river bends, bars occur near the outer banks that become less erosive for higher curvatures. Inner banks become more erosive for higher curvatures but nevertheless accommodate the larger portion of exposed bars. No relation was found between the land cover adjacent to the river and the occurrence of sharp bends. Soil processes may play a crucial role in the formation of sharp bends, which is inferred from iron and manganese concretions observed in the riverbanks, indicating ferric horizons and early stages of the formation of plinthic horizons. Historical topographic maps show the planform activity of the river is low, which may relate to the scour holes slowing down planimetric development.

Key Points: Bed‐load and suspended‐load division functions at bifurcations are different 3D effects of the suspended sediment transport at bifurcations can be limited Sediment transport rates can be estimated from boat‐mounted ADCPs