Common Slope Research Articles

Approximate upper- and lower-bound analyses of translational rainfall-induced landslides in curvilinear hillslopes

Increased frequency of rainfall-induced landslides (RILs) with global climate change is expected to be a huge challenge. Previous studies have focused on RILs encompassing the examination of rotational failure mechanisms and straightforward slope geometries, notably those pertaining to planar or cutting slopes. However, instability issues of curvilinear hillslopes have received less attention, although they are of great significance for early warning landslides in more common natural slopes. This study presents a progressive failure mechanism for curvilinear hillslopes in which the local failure initiates at the steepest zone and gradually extends to upslope/downslope flat regions. By means of upper- and lower-bound analyses, approximate criteria for the onset of a translational landslide with respect to the critical wetting front depth and the failure positions are derived. Unlike traditional theories, upper- and lower-bound analyses are unaffected by slope topology, self-weight of soil and cohesion effects. By conducting a case study at the end of the study, the suggested criteria are found to exhibit notable merits in their straightforward implementation for evaluating the stability of curvilinear natural slopes under varying precipitation patterns.

Is the Change in Prevalence of High Myopia Compared to That of Myopia Really Disproportionate?

It has been noted that, at higher prevalences, the rate of change in the prevalence of high myopia seems to be disproportionately greater compared with the rate of change in the prevalence of myopia. A simple, evidence-based explanation for this relationship is offered. Using a convenience sample of 41 datasets with prevalence estimates for at least two refractive error thresholds (e.g., -0.50 and -6.00 D) the common slope of the logit vs. refractive threshold was applied to model expected rates of high myopia across the myopia prevalence range and the corresponding ratio of change in high myopia to myopia prevalence. The logit of high myopia is related linearly to the logit of myopia. The ratio of increase in high myopia prevalence to that for myopia prevalence increases with underlying prevalence. For example, an increase in myopia prevalence from 19% to 20% is modelled to be accompanied by a 0.1% increase in the prevalence of high myopia from 1.55% to 1.65%-a ratio of 0.1. Conversely, an increase in myopia prevalence from 79% to 80% is predicted to result in a 1% increase in the prevalence of high myopia from 20.6% to 21.6%-a ratio of 1.0. The increase in the prevalence of high myopia compared with that of myopia as the latter increases is merely a function of the underlying nature of refractive error probability distributions and requires no further investigation as to its origin. This study shows how the prevalence of myopia and high myopia are inter-related. A widespread effort to slow myopia progression will affect the prevalence of high myopia but not myopia in general. In contrast, efforts to delay myopia onset will affect both.

Young dove trees tend to invest more biomass in vegetative and reproductive organs than old trees at the twig level

Research on the functional traits of twigs is of great significance to clarify the plant life-history strategies, especially for endangered plants. However, little attention has been given to the environmental adaptation strategy of different age twigs. The dove tree (Davidia involucrata Baill.), a relict and critically endangered Chinese species, was employed as a model species. Total lamina mass and area, stem mass and length, total bract mass and area, and total petiole mass were measured for 100 current-year terminal twigs (50 per age group) from old and young dove trees in Pingwu County, Sichuan, southwest China. Then, the scaling relationships within the twig were determined using the standardized major axis (SMA) regression method. Our results showed that the significantly positive correlations among traits of D. involucrata twigs, and scaling relationships between these traits are different between the two age groups. At the twig level, isometric scaling relationships exist between stem mass and lamina size (or bract size) and between total lamina mass and total lamina area (or total petiole mass). In contrast, allometric scaling relationships exist between lamina size (total mass and area) and stem length (with a common slope > 1), and between total lamina mass and total petiole mass (with a common slope < 1). For a given stem mass, stem length and bract area, young trees have larger total lamina mass and total bract mass, larger total lamina mass and area, and larger total bract mass than old trees, respectively. The results suggest that young trees tend to have more vegetative and reproductive organ mass per unit of supporting organ mass than old trees to meet their rapid growth needs.

Upper limit of mineral-associated organic carbon in temperate and sub-tropical soils: How far is it?

Soil organic carbon (SOC) is the main terrestrial C pool and is roughly divided into stable mineral-associated organic carbon (MAOC) and particulate organic matter carbon (POC). However, the sequestration capacity of MAOC remains unquantified. Currently, soils are considered to have a limited capacity to accumulate MAOC, primarily due to the presence of fine fractions, i.e. silt and clay particles. However, it is unlikely that saturation will occur in all soils due to land use. Therefore it is necessary to investigate whether soils from different latitudes and their silt and clay fractions that comprise MAOC are saturated. We selected 71 soil samples that were physically fractionated from a Mexican inventory of vegetation with a wide range of SOC (4–186 g kg−1 soil) and clay (126–777 g kg−1 soil) contents. Soils were grouped into non-volcanic soils and allophanic Andosols. In the first group, we found a positive and highly significant linear relationship between SOC and MAOC contents, but no upper limit was detected. We found a common slope of 0.86 (R2 = 0.97, p < 0.01), i.e. 86% of the SOC was contained in MAOC irrespective of soil types and management, a value very similar to that in other studies. Conversely, for allophanic Andosols, which had SOC content twice that of non-volcanic soils, a second-order polynomial function (R2 = 0.98, p < 0.01) was established, the upper limit of which exceeded 186 g SOC kg−1 for a MAOC of 134 g kg−1. This was also supported by an increasing polynomial function of particulate organic carbon (POC) as the SOC increased. In both types of soils, maximum MAOCs were found between 700 and 800 g kg−1 of silt and clay in medium-textured soils. The amount of silt and clay particles was limited by SOC accumulation in the silt fraction as clay became saturated. These results are influenced by the mass proportion of silt and clay that follows a unique pattern in allophanic Andosols and non-volcanic soils. An investigation of a comprehensive database comprising 21,315 soil profiles sampled 0–30 cm across Mexico showed that most soils are below 186 g SOC kg−1 the bending point above which the upper limit does exist.

Sex-specific scaling of leaf phosphorus vs. nitrogen under unequal reproductive requirements in Eurya japonica, a dioecious plant.

Previous work searching for sexual dimorphism has largely relied on the comparison of trait mean vectors between sexes in dioecious plants. Whether trait scaling (i.e., the ratio of proportional changes in covarying traits) differs between sexes, along with its functional significance, remains unclear. We measured 10 vegetative traits pertaining to carbon, water, and nutrient economics across 337 individuals (157 males and 180 females) of the diocious species Eurya japonica during the fruiting season in eastern China. Piecewise structural equation modeling was employed to reveal the scaling relationships of multiple interacting traits, and multivariate analysis of (co)variance was conducted to test for intersexual differences. There was no sexual dimorphism in terms of trait mean vectors across the 10 vegetative traits in E. japonica. Moreover, most relationships for covarying trait pairs (17 out of 19) exhibited common scaling slopes between sexes. However, the scaling slopes for leaf phosphorus (P) vs. nitrogen (N) differed between sexes, with 5.6- and 3.0-fold increases of P coinciding with a 10-fold increase of N in male and female plants, respectively. The lower ratio of proportional changes in P vs. N for females likely reflects stronger P limitation for their vegetative growth, as they require greater P investments in fruiting. Therefore, P vs. N scaling can be a key avenue allowing for sex-specific strategic optimization under unequal reproductive requirements. This study uncovers a hidden aspect of secondary sex character in dioecious plants, and highlights the use of trait scaling to understand sex-defined economic strategies.

Respiration in light of evergreen and deciduous woody species and its links to the leaf economic spectrum.

Leaf respiration in the light (Rlight) is crucial for understanding the net CO2 exchange of individual plants and entire ecosystems. However, Rlight is poorly quantified and rarely discussed in the context of the leaf economic spectrum (LES), especially among woody species differing in plant functional types (PFTs) (e.g., evergreen vs. deciduous species). To address this gap in our knowledge, Rlight, respiration in the dark (Rdark), light-saturated photosynthetic rates (Asat), leaf dry mass per unit area (LMA), leaf nitrogen (N) and phosphorus (P) concentrations, and maximum carboxylation (Vcmax) and electron transport rates (Jmax) of 54 representative subtropical woody evergreen and deciduous species were measured. With the exception of LMA, the parameters quantified in this study were significantly higher in deciduous species than in evergreen species. The degree of light inhibition did not significantly differ between evergreen (52%) and deciduous (50%) species. Rlight was significantly correlated with LES traits such as Asat, Rdark, LMA, N and P. The Rlight vs. Rdark and N relationships shared common slopes between evergreen and deciduous species, but significantly differed in their y-intercepts, in which the rates of Rlight were slower or faster for any given Rdark or N in deciduous species, respectively. A model for Rlight based on three traits (i.e., Rdark, LMA and P) had an explanatory power of 84.9%. These results show that there is a link between Rlight and the LES, and highlight that PFTs is an important factor in affecting Rlight and the relationships of Rlight with Rdark and N. Thus, this study provides information that can improve the next generation of terrestrial biosphere models (TBMs).

Stability analysis of heterogeneous infinite slopes under rainfall-infiltration by means of an improved Green–Ampt model

Rainfall infiltration analysis has a great significance to the mitigation and risk assessment of rainfall-induced landslides. The original Green–Ampt (GA) model ignored the fact that a transitional layer exists in infiltration regions of soils under the rainfall permeation; moreover, it cannot effectively analyze the rainfall-infiltrated heterogeneous slope considering the spatial variability of saturated hydraulic conductivity ( ks ). In this study, an improved GA model is proposed for the rainfall-infiltration analysis of heterogeneous slopes. Four common slope cases are investigated to validate the effectiveness of the proposed model. An infinite slope model is taken as an illustrative example to investigate the distributions of volumetric water content and slope stability under the rainfall infiltration. The results show that the distributions of volumetric water content and factor of safety ( Fs) obtained from the proposed model are in very good agreement with the numerical results of the Richards' equation. In contrast, the modified GA model obtains biased distributions of volumetric water content and smaller Fs for the same cases. The results show that the proposed GA model can accurately identify the location of critical slip surface of the slope, and as such it provides an efficient method for risk analysis and control of slopes susceptible to landslide.

Statistical considerations on real time and extended controlled temperature conditions (ECTC) stability data analysis of vaccines

BackgroundAlthough maintaining vaccines in a strict cold chain has cost and logistical implications in low- and middle-income countries, only a few vaccines have obtained approval for extended controlled temperature conditions (ECTC) application, which permits the administration of vaccines after storage outside of the cold chain for a defined period. We developed a methodology to evaluate stability data and calculate minimum release potency (MRP) in support of ECTC application. MethodsThe methodology is focused on statistical considerations consisting of stability data collection, statistical analysis plan, statistical modelling, and statistical report. It uses mock stability data from a hypothetical product and may serve as a helpful guide for other products. The statistical data analysis is performed using the R program which is an open-source program and validated using the SAS software. ResultsWe developed a stability data testing scheme that included 24 lots with six-time points for up to 24 months under real-time and real condition (RT) in the cold chain samples stored at 2–8 °C and 12 lots with six timepoints for 14 days under ECTC samples stored at 40 °C. The log-transformed stability data met the linear regression assumptions and were poolable from representative lots with no significant lot variation. The linear regression analysis model with a common slope and intercept confirmed the stable antigen content over time under RT and ECTC by the mean regression line and 95% confidence interval. Based on the fitted models and the estimated coefficients, the antigen content value of 966 was derived as the MRP under RT for 24 months followed by 14 days under ECTC. ConclusionThe presented framework of statistical considerations, with practical methods and R program codes to perform statistical analysis, may serve as a guide for developing the CTC data for a vaccine’s stability evaluation prospectively.

Formula omitted] in speleothem carbonates in Soreq Cave as an archive for hydro-climatic conditions

δ18O in speleothem carbonates is a common archive for paleoclimate on land. Recently, it has been shown that triple oxygen isotopes in CaCO3 (given as Oexcess17=106[ln⁡(10−3δ17O+1)−0.528(ln⁡(10−3δ18O+1)]) record Oexcess17 of its parent water, thus providing additional paleo-hydrology information, primarily about relative humidity. The O17 fractionation between CaCO3 and water has been determined in biogenic and synthetic carbonates. In speleothems, however, this fractionation is expected to be modified by kinetic isotope effects associated with CO2 degassing from cave drip water. Here, we used Soreq Cave as a case study to examine this fractionation and the use of Oexcess17 in speleothems as an archive for paleo rainfall composition. We first characterized Oexcess17 in rainfall collected above the cave. The Oexcess17 value in amount weighted integrated rainfall was 49 per meg, consistent with the low relative humidity at the moisture source of the Eastern Mediterranean Sea. The measured cave water was slightly lower in Oexcess17 and higher in δ18O relative to rainfall, due to modifications of the infiltrating water by epikarst processes such as evaporation and mixing. Oexcess17 in CO2 extracted from CaCO3 of modern speleothems was compared to that in modern cave water, to calculate the carbonate-water fractionation slope (θ=ln17⁡α/ln18⁡α). The resulting θ in Soreq Cave was 0.5230±0.0002, consistent with that observed in other carbonates, indicating the lack of significant dis-equilibrium effects in speleothems Oexcess17. Hence, the common fractionation slope can be used together with a speleothem-specific α18 to reconstruct rainfall Oexcess17 from speleothem carbonates. Whereas speleothems from a variety of caves can be used through this approach to reconstruct Oexcess17 in paleo rainfall, the atmospheric processes that govern rainfall Oexcess17 are expected to be region-specific. Oexcess17 measurements in ancient Soreq speleothems are expected to reveal potential glacial-interglacial changes in moisture source conditions as well as possible changes in epikarst processes over time.

A pre-trained deep-learning surrogate model for slope stability analysis with spatial variability

This paper presents a pre-trained deep-learning surrogate model for the slope stability problem, which can be used to accelerate the stochastic analysis of slope stability with spatial variability. One major innovation is that the model is trained with a big dataset (>12000 data) covering common soil properties, spatial variabilities, and slope shapes such that the trained model is ready to make predictions without additional training or numerical simulations required. Other two minor contributions are: (1) special treatments for the irregular and varying boundaries of slopes and (2) novel techniques that allow the use of non-uniform mesh in data acquisitions. The proposed model is accurate with a mean-absolute-percentage-error of about 6% for the testing dataset. Seven cases of unseen data are also used to verify the model performance, including cases of different soil parameters, slope angles, and even different slope surfaces (e.g., concave and convex slopes, which are not used in training). The results show that the predict slope factor of safety is high consistent with the values from finite element simulations, and so is the obtained probability density functions. But the surrogate model takes much less computational effort (several minutes compared with hours of computing) – proving the effectiveness of our model for efficient stochastic analyses.

Limited evidence for species‐specific sensitivity of temperature‐dependent fractionation of oxygen stable isotope in biominerals: A meta‐analysis

Abstract Water temperature is key to the study of aquatic ectotherm ecology, but precise measurements of individual‐based thermal experience remain difficult to validate. The stable isotope composition of oxygen in biominerals acts as a natural thermometer due to the temperature dependence of isotopic fractionation between water and mineral phases. Coefficients of published temperature‐dependent fractionation equations, however, vary among taxa (the so‐called ‘vital effect’) without apparent consistent predictors, implying that species‐specific experimental validation may be needed before inferring temperature from biomineral oxygen isotope thermometry. Here, we describe a meta‐analysis conducted to assess the influence of biological and experimental sources of variation on the coefficients of published isotope thermometry equations. We observed that the thermal sensitivity (equation slope) was resistant to any biological or experimental factors, while the isotopic spacing between water and biomineral (equation intercept) showed consistent variation. Experimental conditions and phylogeny were the two main sources of variation in equation coefficients, where experiment approaches influenced both equation intercepts and the fit of the linear regression. Our results suggest that the use of common equation slopes and generalized taxa‐specific equation intercepts may be appropriate under some circumstances. We additionally suggest that processes related to oxygen balance and osmoregulation may influence equation intercepts, and suggest further experimental work in this area. Finally, our observations provide ground for improvement for future design and reporting of biomineral thermometry experiments.

Implementation of Surrogate Models for the Analysis of Slope Problems

Numerical modeling is increasingly used to analyze practical rock engineering problems. The geological strength index (GSI) is a critical input for many rock engineering problems. However, no available method allows the quantification of GSI input parameters, and engineers must consider a range of values. As projects progress, these ranges can be narrowed down. Machine learning (ML) algorithms have been coupled with numerical modeling to create surrogate models. The concept of surrogate models aligns well with the deductive nature of data availability in rock engineering projects. In this paper, we demonstrated the use of surrogate models to analyze two common rock slope stability problems: (1) determining the maximum stable depth of a vertical excavation and (2) determining the allowable angle of a slope with a fixed height. Compared with support vector machines and K-nearest algorithms, the random forest model performs best on a data set of 800 numerical models for the problems discussed in the paper. For all these models, regression-type models outperform classification models. Once the surrogate model is confirmed to preform accurately, instantaneous predictions of maximum excavation depth and slope angle can be achieved according to any range of input parameters. This capability is used to investigate the impact of narrowing GSI range estimation.

Identifying latent group structures in spatial dynamic panels

This paper considers the identification of latent group structures in spatial dynamic panels. We follow Lee and Yu (2010) and consider a rich spatial dynamic panel data (SDPD) model with two-way fixed effects. In addition, we also allow for latent panel structures where individuals can be classified into a few groups such that individuals within the same group share the common slope parameters and do not otherwise. Both the number of groups and the individuals’ group membership are unknown. To identify the latent group structures, we first adopt the GMM to obtain the preliminary unconstrained estimates of the slope coefficients. Then we apply the sequential binary segmentation algorithm (SBSA) of Wang and Su (2021) to these estimates and obtain the clusters. A BIC-type information criterion is proposed to choose the number of latent groups consistently. The asymptotic analysis shows that this method can identify the true group structure consistently, and the post-classification estimators enjoy the oracle property. Monte Carlo simulations demonstrate that our method has good finite sample performance. Finally, we apply our approach to the US housing market and identify two latent Metropolitan Statistical Areas groups.

Metabolic rate, sleep duration, and body temperature in evolution of mammals and birds: the influence of geological time of principal groups divergence.

This study contains an analysis of basal metabolic rate (BMR) in 1817 endothermic species. The aim was to establish how metabolic scaling varies between the main groups of endotherms during evolution. The data for all the considered groups were combined and the common exponent in the allometric relationship between the BMR and body weight was established as b = 0.7248. Reduced to the common slope, the relative metabolic rate forms the following series: Neognathae - Passeriformes - 1.00, Neognathae - Non-Passeriformes - 0.75, Palaeognathae - 0.53, Eutheria - 0.57, Marsupialia - 0.44, and Monotremata - 0.26. The main finding is that the metabolic rate in the six main groups of mammals and birds consistently increases as the geological time of the group's divergence approaches the present. In parallel, the average body temperature in the group rises, the duration of sleep decreases and the duration of activity increases. BMR in a taxon correlates with its evolutionary age: the later a clade diverged, the higher is its metabolic rate and the longer is its activity period; group exponents decrease as group divergence nears present times while with increase metabolic rate during activity, they not only do not decrease but can increase. Sleep duration in mammals was on average 40% longer than in birds while BMR, in contrast, was 40% higher in birds. The evolution of metabolic scaling, body temperature, sleep duration, and activity during the development of endothermic life forms is demonstrated, allowing for a better understanding of the underlying principles of endothermy formation.

SNAPenrollment cycles: New insights from heterogeneous panel models withcross‐sectionaldependence

AbstractThe Supplemental Nutrition Assistance Program (SNAP) has grown rapidly over the past 2 decades. A large literature relies on state‐level panel data on SNAP enrollment and implements traditional two‐way fixed effects estimators to identify the impact of economic conditions on SNAP enrollment. This empirical strategy implicitly assumes slope parameter homogeneity and ignores the possibility of cross‐sectional dependence in the regression error terms. The latter could feasibly arise in state‐level panel data if the time‐varying unobserved common shocks, such as national financial crises, have differential effects on SNAP participation across states in the United States. This study empirically evaluates the appropriateness of these two assumptions by adopting a more general common factor model, allowing for slope parameter heterogeneity and error term cross‐sectional dependence both separately and jointly. We find that although assuming a common slope parameter across states does not seem problematic for identification, allowing for the error term cross‐sectional dependence leads to a roughly 40% reduction in the estimated long‐run impact of the unemployment rate on SNAP enrollment. This finding has important implications for policymaking decisions—even small biases could lead to suboptimal policy responses considering the program's size. Our counterfactual simulations support our main results, implying the importance of carefully accounting for time‐varying unobserved heterogeneity when studying the cyclicality of SNAP enrollment using state‐level panel data.

Numerical Simulation of Mechanical Behavior of Gas Pipeline in High and Steep Slope

Long-distance natural gas pipelines can often pass through the common slope safely. However, when pipelines inevitably pass through high and steep slopes(HSS) for some reasons, it is difficult for engineers to predict the stress state of pipelines. Therefore, in order to investigate the safety of natural gas pipelines in HSS areas, the finite element simulation calculation model of the pipeline in HSS was established. The predicted numerical model shows that the maximum Von Mises stress and axial strain of the pipeline in the HSS area appear at the lower elbow of the pipeline, which should be paid more attention to in the risk assessment; The stress and deformation of the pipeline is mainly related with the wall thickness and internal pressure, appropriately increasing the wall thickness and reducing the internal pressure can improve the safety of HSS pipelines.

Гравитационное движение грунтов на склонах и их влияние на состояние водных объектов

The purpose of the research is to study the features of the movement of particles, aggregates and geological bodies (landslides) downhill under the influence of a number of natural and man-made factors, to study the most common natural and man-made objects that reduce the activity of the development of slope processes. Two of the most common slope exogenous geological processes are considered – surface flushing and landslide. These processes contribute to the entry of silt fraction into the sediments of water bodies. The study of pollution of water bodies with heavy metals still remains relevant when assessing the geo ecological state of the environment. On the Volga River basin the principles are proposed and the zoning is presented. According to natural and technogenic objects, four categories of sites were allocated hierarchically for monitoring the pollution of the territory with heavy metals. The zoning of the bed of water bodies for the distribution of silty sediments – sorbents of pollutants was carried out. The elements of the energy approach are presented, giving an understanding of the most likely locations of pollutants – energy traps and potential barriers. Practical examples of the spread of pollutants in the natural and man-made environment and the interaction of natural and man-made processes in the landslide system are given. For the landslide process, the most typical interactions between a geological body and man-made objects are presented. On the example of the most typical landslides for the European part of Russia, the measures aimed at their stabilization, as well as the impacts contributing to their activation, are presented. Natural and man-made potential barriers to the landslide process are considered.

Fixed‐effects binary choice models with three or more periods

We consider fixed‐effects binary choice models with a fixed number of periods T and regressors without a large support. If the time‐varying unobserved terms are i.i.d. with known distribution F, Chamberlain (2010) shows that the common slope parameter is point identified if and only if F is logistic. However, he only considers in his proof T = 2. We show that the result does not generalize to T ≥ 3: the common slope parameter can be identified when F belongs to a family including the logit distribution. Identification is based on a conditional moment restriction. Under restrictions on the covariates, these moment conditions lead to point identification of relative effects. If T = 3 and mild conditions hold, GMM estimators based on these conditional moment restrictions reach the semiparametric efficiency bound. Finally, we illustrate our method by revisiting Brender and Drazen (2008).

Estimation and identification of latent group structures in panel data

This paper provides a framework for joint estimation and identification of latent group structures in panel data models using a pairwise fusion penalized approach. The latent structure of the model allows individuals to be classified into different groups where the number of groups and the group membership are unknown. The individuals within a group have common slope parameters, while parameter heterogeneity is allowed across the groups. A penalized least squares (PLS) approach is introduced for models with exogenous regressors. When the model contains endogenous regressors, a penalized generalized method of moment (PGMM) is introduced. To implement the proposed approach, an alternating direction method of multipliers algorithm has been developed. The proposed method is further illustrated by simulation studies which demonstrate the finite sample performance of the method, and is applied in an empirical analysis.

Mapping Potential Locations of Reservoir Development Planning Based on Biogeophysical Conditions in Bulok Watershed of Lampung Province

Floods and droughts are problems that threaten the success of agricultural crops. The reservoir can be used as a water management system that can anticipate these problems. This study aims to examine the potential location of the reservoir development planning based on biogeophysical conditions in the Bulok Watershed of Lampung Province, which uses the overlay method and weighting and scoring techniques developed by Geographic Information System (GIS). The population covers the entire biogeophysical area of the Bulok watershed, with samples of 4 biogeophysical parameters, namely land cover, slope, soil conditions and geological conditions. The results showed that the distribution of land cover types that dominate in the Bulok watershed is mixed dry land agriculture. The most common slopes are flat to wavy slopes. The soil types that dominates are soils with andesite lithology, basalt, diorite, fine-grained tefra, and coarse-grained tefra. The geological formation that dominates is the Hulu Simpang Formation. Based on the 4 biogeophysical parameters selected in the study, there are 69 locations with great potential for planning the construction of reservoirs in the Bulok watershed. 20 points are spread over the administrative area of Tanggamus Regency, 23 points in Pringsewu Regency, and 26 points in Pesawaran Regency. Of the 87.670 ha of Bulok watershed area, 14.192 ha is very potential location area. Keywords: Biogeophysical Conditions, Potential Locations, Reservoir