Classifying Annual Daily Hydrographs in Western North America using t-Distributed Stochastic Neighbor Embedding (t-SNE)

Flow regimes are critical for determining physical and biological processes in rivers, and their classification and regionalization traditionally seeks to link patterns of flow to physiographic, climate and other information. There are many approaches to, and rationales for, catchment classification, with those focused on streamflow often seeking to relate a particular response characteristic to a physical property or climatic driver. Rationales include such topics as Prediction in Ungauged Basins (PUB), helping with experimental approaches, and providing guidance for model selection in poorly understood hydrological systems. While scale and time are important considerations for classification, the Annual Daily Hydrograph (ADH) is a first-order easily visualized integrated expression of catchment function, and over many years is a distinct hydrological signature. In this study, we use t-SNE, a state-of-the-art technique of dimensionality reduction, to classify 17110 ADHs for 304 reference catchments in mountainous Western North America. t-SNE is chosen over other conventional methods of dimensionality reduction (e.g. PCA) as it presents greater separability of ADHs, which are projected on a 2D map where the similarities are evaluated according to their map distance. We then utilize a Deep Learning encoder to upgrade the non-parametric t-SNE to a parametric approach, enhancing its capability to address ‘unseen’ samples. Results showed that t-SNE was an effective classifier as it successfully clustered ADHs of similar flow regimes on the 2D map. In addition, many compact clusters on the 2D map in the coastal Pacific Northwest suggest information redundancy in the local hydrometric network. The t-SNE map provides an intuitive way to visualize the similarity of high-dimensional data of ADHs, groups catchments with like characteristics, and avoids the reliance on subjective hydrometric indicators.

Hydrologic assessment of a small maritime hydrometric monitoring network using a combined inductive-deductive process-informed catchment classification system

<p>The National Hydrometric Program, operated by the Water Survey of Canada, is the primary source of surface water quantity data in Canada. The network is cost-shared between the federal and provincial governments, and decisions relating to station placement are made according to both federal and provincial interests. Nova Scotia is a small maritime province in Atlantic Canada that is roughly one third the size of England and Wales and has a diverse climate and geology. The Nova Scotia hydrometric monitoring network currently consists of just 31 stations. The overall objective of this study was to determine how well the current network captures the level of hydrologic variability expected in the province using a regional catchment classification scheme. To accomplish this, we developed a combined inductive-deductive catchment classification system and applied it to the province’s active monitoring network and ungauged major watersheds. Initially, hydrologic signatures were used to quantify the catchment function of 47 long-term gauged catchments and to cluster similarly behaving catchments. We identified five generalized flow classes and then attempted to replicate this classification using a deductive-based decision tree framework with physiographic and meteorological explanatory variables. The validated decision tree was used to classify the active hydrometric network and 250+ major watersheds in the province. The network was assessed to determine how well it covered the expected hydrologic variability in the major watersheds across the province. The decision tree proved to be a useful tool for understanding the current network’s coverage and could also be easily applied by practitioners to identify appropriate donor catchments for ungauged watersheds.</p>

Australian Alps

Australian Alps is a fascinating guide to Kosciuszko, Alpine and Namadgi National Parks. It introduces the reader to some of Australia’s highest mountains, their climate, geology and soils, plants and animals and their human history. It traces the long-running conflicts between successive users of the mountains and explores the difficulties in managing the land for nature conservation. The book gives credit to little-known or understood stories of the people who have worked to establish better understanding of the Alps, especially their vital role as the major water catchments for south-eastern Australia. This new edition updates many themes, including the involvement of Aboriginal people in the region, catchment function and condition, pest plants and animals, fire and the issue of climate change. Written by a specialist with over 25 years’ experience in community education in and about the Australian Alps National Parks, this new edition features many excellent natural history and historical photographs. Ideal as support information for field trips, it will make a wonderful memento of an alpine visit. This book acts as a detailed companion to park interpretive material and to topic-specific field guides: it caters for readers who want a broad overview of areas of interest they will come across in a visit to the mountains.

DAMPAK ERUPSI GUNUNG MERAPI TERHADAP LAHAN DAN UPAYA-UPAYA PEMULIHANNYA

<p>The eruption of Merapi mountain has primary and secondary hazard and may damage to the land. In detail, the hazards are land degradation is a loss of some or many of germplasm and changes in plant biodiversity. The others hazard including loss of water catchment areas, the destruction of forests, and even the closing of the water source, as well as the loss of water channels. The burried of soil and soil formation inhibition were caused by the repeated eruptions of Merapi, beside the loss of roads access to agricultural land and loss of land ownerships boundaries by the eruption and cool lava. Materials of eruption are sand and pyroclastic materials, as well as the nature of cementation require special techniques and technology to use the land as new farmland. Land restoration efforts can be done with the land management by reforestation on government-owned land for water catchment function, agroforestry forage grass based, grazing field on land owned by the village and residents, with the use of organic materials in the eruption sandy soil ameliorant.</p>

Thermodynamic constraints on effective energy and mass transfer and catchment function

Understanding how water, energy and carbon are partitioned to primary production and effective precipitation is central to quantifying the limits on critical zone evolution. Recent work suggests quantifying energetic transfers to the critical zone in the form of effective precipitation and primary production provides a first order approximation of critical zone process and structural organization. However, explicit linkage of this effective energy and mass transfer (EEMT; W m−2) to critical zone state variables and well defined physical limits remains to be developed. The objective of this work was to place EEMT in the context of thermodynamic state variables of temperature and vapor pressure deficit, with explicit definition of EEMT physical limits using a global climate dataset. The relation of EEMT to empirical measures of catchment function was also examined using a subset of the Model Parameter Estimation Experiment (MOPEX) catchments. The data demonstrated three physical limits for EEMT: (i) an absolute vapor pressure deficit threshold of 1200 Pa above which EEMT is zero; (ii) a temperature dependent vapor pressure deficit limit following the saturated vapor pressure function up to a temperature of 292 K; and (iii) a minimum precipitation threshold required from EEMT production at temperatures greater than 292 K. Within these limits, EEMT scales directly with precipitation, with increasing conversion of the precipitation to EEMT with increasing temperature. The state-space framework derived here presents a simplified framework with well-defined physical limits that has the potential for directly integrating regional to pedon scale heterogeneity in effective energy and mass transfer relative to critical zone structure and function within a common thermodynamic framework.

Catchment classification: empirical analysis of hydrologic similarity based on catchment function in the eastern USA

Hydrologic similarity between catchments, derived from similarity in how catchments respond to precipitation input, is the basis for catchment classification, for transferability of information, for generalization of our hydrologic understanding and also for understanding the potential impacts of environmental change. An important question in this context is, how far can widely available hydrologic information (precipitation-temperature-streamflow data and generally available physical descriptors) be used to create a first order grouping of hydrologically similar catchments? We utilize a heterogeneous dataset of 280 catchments located in the Eastern US to understand hydrologic similarity in a 6-dimensional signature space across a region with strong environmental gradients. Signatures are defined as hydrologic response characteristics that provide insight into the hydrologic function of catchments. A Bayesian clustering scheme is used to separate the catchments into 9 homogeneous classes, which enable us to interpret hydrologic similarity with respect to similarity in climatic and landscape attributes across this region. We finally derive several hypotheses regarding controls on individual signatures from the analysis performed here.

Thermodynamic constraints on effective energy and mass transfer and catchment function

Understanding how water, energy and carbon are partitioned to primary production and effective precipitation is central to quantifying the limits on critical zone evolution. Recent work suggests quantifying energetic transfers to the critical zone in the form of effective precipitation and primary production provides a first order approximation of critical zone process and structural organization. However, explicit linkage of this effective energy and mass transfer (EEMT; W m−2) to critical zone state variables and well defined physical limits remains to be developed. The objective of this work was to place EEMT in the context of thermodynamic state variables of temperature and vapor pressure deficit, with explicit definition of EEMT physical limits using a global climate dataset. The relation of EEMT to empirical measures of catchment function was also examined using a subset of the Model Parameter Estimation Experiment (MOPEX) catchments. The data demonstrated three physical limits for EEMT: (i) an absolute vapor pressure deficit threshold of 1200 Pa above which EEMT is zero; (ii) a temperature dependent vapor pressure deficit limit following the saturated vapor pressure function up to a temperature of 292 K; and (iii) a minimum precipitation threshold required from EEMT production at temperatures greater than 292 K. Within these limits, EEMT scales directly with precipitation, with increasing conversion of the precipitation to EEMT with increasing temperature. The state-space framework derived here presents a simplified framework with well-defined physical limits that has the potential for directly integrating regional to pedon scale heterogeneity in effective energy and mass transfer relative to critical zone structure and function within a common thermodynamic framework.

Catchment classification: empirical analysis of hydrologic similarity based on catchment function in the eastern USA

Hydrologic similarity between catchments, derived from their similarity in how they respond to precipitation input, is the basis for classification, for transferability, for generalization and also for understanding the potential impacts of environmental change. An important question in this context is, in how far can widely available hydrologic information (precipitation-temperature-streamflow) be used to create a first order grouping of hydrologically similar catchments? We utilize a heterogeneous dataset of 280 catchments located in the Eastern US to understand hydrologic similarity in a 6-dimensional signature space across a region with strong environmental gradients. Signatures are defined as hydrologic response characteristics that provide some insight into the hydrologic function of catchments. A Bayesian clustering scheme is used to separate the catchments into 9 classes, which are subsequently analyzed with respect to their hydrologic, as well as climatic and landscape attributes. Based on the empirical results we hypothesize the following: (1) Streamflow elasticity with respect to precipitation is modified by the soil characteristics of a catchment. (2) Spatial proximity is a good first indicator of hydrologic similarity because of the strong control climate exerts on catchment function, and because it varies slowly in space.