Gopal Bhatt

A tightly coupled GIS and distributed hydrologic modeling framework

Distributed, physics-based hydrologic models require spatially explicit specification of parameters related to climate, geology, land-cover, soil, and topography. Extracting these parameters from national geodatabases requires intensive data processing. Furthermore, mapping these parameters to model mesh elements necessitates development of data access tools that can handle both spatial and temporal datasets. This paper presents an open-source, platform independent, tightly coupled GIS and distributed hydrologic modeling framework, PIHMgis (www.pihm.psu.edu), to improve model-data integration. Tight coupling is achieved through the development of an integrated user interface with an underlying shared geodata model, which improves data flow between the PIHMgis data processing components. The capability and effectiveness of the PIHMgis framework in providing functionalities for watershed delineation, domain decomposition, parameter assignment, simulation, visualization and analyses, is demonstrated through prototyping of a model simulation. The framework and the approach are applicable for watersheds of varied sizes, and offer a template for future GIS-Model integration efforts. A coupled GIS and distributed hydrologic modeling framework, PIHMgis was developed.PIHMgis uses national geospatial dataset to setup, execute, and analyze simulations.Procedural framework improves model-data integration using shared geodata model.

An efficient domain decomposition framework for accurate representation of geodata in distributed hydrologic models

Physically‐based, fully‐distributed hydrologic models simulate hydrologic state variables in space and time while using information regarding heterogeneity in climate, land use, topography and hydrogeology. Since fine spatio‐temporal resolution and increased process dimension will have large data requirements, there is a practical need to strike a balance between descriptive detail and computational load for a particular model application. In this paper, we present a flexible domain decomposition strategy for efficient and accurate integration of the physiographic, climatic and hydrographic watershed features. The approach takes advantage of different GIS feature types while generating high‐quality unstructured grids with user‐specified geometrical and physical constraints. The framework is able to anchor the efficient capture of spatially distributed and temporally varying hydrologic interactions and also ingest the physical prototypes effectively and accurately from a geodatabase. The proposed decomposition framework is a critical step in implementing high quality, multiscale, multiresolution, temporally adaptive and nested grids with least computational burden. We also discuss the algorithms for generating the framework using existing GIS feature objects. The framework is successfully being used in a finite volume based integrated hydrologic model. The framework is generic and can be used in other finite element/volume based hydrologic models.

Parameterization for distributed watershed modeling using national data and evolutionary algorithm

Distributed hydrologic models supported by national soil survey, geology, topography and vegetation data products can provide valuable information about the watershed hydrologic cycle. However numerical simulation of the multi-state, multi-process system is structurally complex and computationally intensive. This presents a major difficulty in model calibration using traditional techniques. This paper presents an efficient calibration strategy for the physics-based, fully coupled, distributed hydrologic model Penn State Integrated Hydrologic Model (PIHM) with the support of national data products. PIHM uses a semi-discrete Finite Volume Method (FVM) formulation of the system of coupled ordinary differential equations (e.g. canopy interception, transpiration, soil evaporation) and partial differential equations (e.g. groundwater-surface water, overland flow, infiltration, channel flow, etc.). The matrix of key parameters to be estimated in the optimization process was partitioned into two groups according to the sensitivity to difference in time scales. The first group of parameters generally describes hydrologic processes influenced by hydrologic events (event-scale group: EG), which are sensitive to short time runoff generation, while the second group of parameters is largely influenced by seasonal changes in energy (seasonal time scale group: SG). The Covariance Matrix Adaptation Evolution Strategy (CMA-ES) is used to optimize the EG parameters in Message Passing Interface (MPI) environment, followed by the estimation of parameters in the SG. The calibration strategy was applied at three watersheds in central PA: a small upland catchment (8.4ha), a watershed in the Appalachian Plateau (231km^2) and the Valley and Ridge of central Pennsylvania (843km^2). A partition calibration enabled a fast and efficient estimation of parameters.

The Hydroarchaeological Method: A Case Study at the Maya Site of Palenque

This research consists mainly of introducing the hydroarchaeological method, especially as related to issues of drought. The article outlines how this multidisciplinary method can provide insights into the success and failures of an archaeolog ical site, in this case the Maya site of Palenque. We also detail convincing evidence that shows that the Maya of Palenque did not leave their city because of deficiencies of water, as some paleoclimatologists and archaeologists have asserted. The first logical step toward understanding any settlement’s water system is to use basic hydrologic methods and theory and to understand the local watershed. There is great potential for watershed-climate modeling in developing plausible scenarios of water use and supply and of the effect of extreme conditions (flood and drought), all of which cannot be fully represented by atmosphere-based climate and weather projections. The research demonstrates how the local watershed, land-use, and ecological conditions interact with regional climate changes. The archaeological implications for this noninvasive “vir tual” method are many, including detecting periods of stress within a community, estimating population by developing caps based on the availability of water, and understanding settlement patterns, as well as assisting present local populations in understanding their water cycle. El objetivo principal de esta investigacion es la introduccion del metodo hidroarqueologico, especialmente en lo relacionado a temas como la sequia. El articulo describe como este metodo multidisciplinario ayuda a entender las causas del exito y fracaso de un sitio arqueologico, en este caso, del sitio maya de Palenque. Tambien detallamos evidencia convincente que muestra que— a diferencia de lo que algunos paleoclimatologos y arqueologos han afirmado— los mayas de Palenque no abandonaron su ciudad debido a escasez de agua. El primer paso logico para entender el sistema hidraulico de cualquier asentamiento es usar la teoria y metodos hidrologicos basicos, y conocer la cuenca hidrologica local. Existe un gran poten cial para los modelos climatologicos-hidrologicos para proporcionar posibles escenarios de uso y abasto de agua, y los efec tos de posibles condiciones extremas (inundacion y sequia), todo lo cual no puede ser representado totalmente mediante pronosticos del tiempo y del clima que se basan en la atmosfera unicamente. Esta investigacion demuestra como interactuan las cuencas locales, el uso de la tierra y las condiciones ecologicas, con los cambios climaticos regionales. Las implica ciones arqueologicas de este metodo no-invasivo “virtual” son muchas, incluyendo: la deteccion de periodos de estres en el interior de una comunidad; la estimacion de la poblacion al disenar topes de crecimiento basados en la disponibilidad de agua; la comprension de los patrones de asentamiento; asi como la asistencia a las poblaciones actuales en la localidad para el entendimiento de su ciclo de agua.

An object-oriented shared data model for GIS and distributed hydrologic models

Distributed physical models for the space–time distribution of water, energy, vegetation, and mass flow require new strategies for data representation, model domain decomposition, a priori parameterization, and visualization. The geographic information system (GIS) has been traditionally used to accomplish these data management functionalities in hydrologic applications. However, the interaction between the data management tools and the physical model are often loosely integrated and nondynamic. This is because (a) the data types, semantics, resolutions, and formats for the physical model system and the distributed data or parameters may be different, with significant data preprocessing required before they can be shared; (b) the management tools may not be accessible or shared by the GIS and physical model; and (c) the individual systems may be operating system dependent or are driven by proprietary data structures. The impediment to seamless data flow between the two software components has the effect of increasing the model setup time and analysis time of model output results, and also makes it restrictive to perform sophisticated numerical modeling procedures (real-time forecasting, sensitivity analysis, etc.) that utilize extensive GIS data. These limitations can be offset to a large degree by developing an integrated software component that shares data between the (hydrologic) model and the GIS modules. We contend that the prerequisite for the development of such an integrated software component is a ‘shared data model’, which is designed using an object-oriented strategy. Here we present the design of such a shared data model taking into consideration the data type descriptions, identification of data classes, relationships, and constraints. The developed data model has been used as a method base for developing a coupled GIS interface to Penn State Integrated Hydrologic Model (PIHM), called PIHMgis.

Modelling long-term water yield effects of forest management in a Norway spruce forest

Abstract Intensive forest management is one of the main land cover changes over the last century in Central Europe, resulting in forest monoculture. It has been proposed that these monoculture stands impact hydrological processes, water yield, water quality and ecosystem services. At the Lysina Critical Zone Observatory, a forest catchment in the western Czech Republic, a distributed physics-based hydrologic model, Penn State Integrated Hydrologic Model (PIHM), was used to simulate long-term hydrological change under different forest management practices, and to evaluate the comparative scenarios of the hydrological consequences of changing land cover. Stand-age-adjusted LAI (leaf area index) curves were generated from an empirical relationship to represent changes in seasonal tree growth. By consideration of age-adjusted LAI, the spatially-distributed model was able to successfully simulate the integrated hydrological response from snowmelt, recharge, evapotranspiration, groundwater levels, soil moisture and streamflow, as well as spatial patterns of each state and flux. Simulation scenarios of forest management (historical management, unmanaged, clear cutting to cropland) were compared. One of the critical findings of the study indicates that selective (patch) forest cutting results in a modest increase in runoff (water yield) as compared to the simulated unmanaged (no cutting) scenario over a 29-year period at Lysina, suggesting the model is sensitive to selective cutting practices. A simulation scenario of cropland or complete forest cutting leads to extreme increases in annual water yield and peak flow. The model sensitivity to forest management practices examined here suggests the utility of models and scenario development to future management strategies for assessing sustainable water resources and ecosystem services. Editor D. Koutsoyiannis

Open science in practice: Learning integrated modeling of coupled surface-subsurface flow processes from scratch.

Integrated modeling of coupled surface-subsurface flow and ensuing role in diverse Earth system processes is of current research interest to characterize nonlinear rainfall-runoff response and also to understand land surface energy balances, biogeochemical processes, geomorphological dynamics, etc. A growing number of complex models have been developed for water-related research, and many of these are made available to the Earth science community. However, relatively few resources have been made accessible to the potentially large group of Earth science and engineering users. New users have to invest an extraordinary effort to study the models. To provide a stimulating experience focusing on the learning curve of integrated modeling of coupled surface-subsurface flow, we describe use cases of an open source model, the Penn State Integrated Hydrologic Model, PIHM. New users were guided through data processing and model application by reproducing a numerical benchmark problem and a real-world watershed simulation. Specifically, we document the PIHM application and its computational workflow to enable intuitive understanding of coupled surface-subsurface flow processes. In addition, we describe the user experience as important evidence of the significance of reusability. The interaction shows that documentation of data, software, and computational workflow in research papers is a promising method to foster open scientific collaboration and reuse. This study demonstrates how open science practice in research papers would promote the utility of open source software. Addressing such open science practice in publications would promote the utility of journal papers. Further, popularization of such practice will require coordination among research communities, funding agencies, and journals.

Cyber-Innovated Watershed Research at the Shale Hills Critical Zone Observatory

Cyberinfrastructure is enabling ever more integrative and transformative science. Technological advances in cyberinfrastructure have allowed deeper understanding of watershed hydrology by improved integration of data, information, and models. The synthesis of all sources of hydrologic variables (historical, real time, future scenarios, observed, and modeled) requires advanced data acquisition, data storage, data management, data integration, data mining, and data visualization. In this context, cyber-innovated hydrologic research was implemented to carry out watershed-based historical climate simulations at the Shale Hills Critical Zone Observatory. The simulations were based on the assimilation of data from a hydrologic monitoring network into a multiphysics hydrologic model (the Penn State Integrated Hydrology Model). We documented workflows for the model application and applied the model to short-time hyporheic exchange flow study and long-term climate scenario analysis. The effort reported herein demonstrates that advances in cyberscience allows innovative research that improves our ability to access and share data; to allow collective development of science hypotheses; and to support building models via team participation. We simplified communications between model developers and community scientists, software professionals, students, and decision makers, which in the long term will improve the utilization of hydrologic models for science and societal applications.

Revised Method and Outcomes for Estimating Soil Phosphorus Losses from Agricultural Land in the Chesapeake Bay Watershed Model

Current restoration efforts for the Chesapeake Bay watershed mandate a timeline for reducing the load of nutrients and sediment into receiving waters. The Chesapeake Bay watershed model (WSM) has been used for two decades to simulate hydrology and nutrient and sediment transport; however, spatial limitations of the WSM preclude edge-of-field scale representation of phosphorus (P) losses. Rather, the WSM relies on literature-derived, county-scale rates of P loss (targets) for simulated land uses. An independent field-scale modeling tool, Annual Phosphorus Loss Estimator (APLE), was used as an alternative to the current WSM approach. Identical assumptions of county-level acreage, soil properties, nutrient management practices, and transport factors from the WSM were used as inputs to APLE. Incorporation of APLE P-loss estimates resulted in greater estimated total P loss and a revised spatial pattern of P loss compared with the WSMs original targets. Subsequently, APLEs revised estimates for P loss were substituted into the WSM and resulted in improved WSM calibration performance at up to 79% of tributary monitoring stations. The incorporation of APLE into the WSM will improve its ability to assess P loss and the impact of field management on Chesapeake Bay water quality.

Assessing water quality of the Chesapeake Bay by the impact of sea level rise and warming

The influence of sea level rise and warming on circulation and water quality of the Chesapeake Bay under projected climate conditions in 2050 were estimated by computer simulation. Four estuarine circulation scenarios in the estuary were run using the same watershed load in 1991-2000 period. They are, 1) the Base Scenario, which represents the current climate condition, 2) a Sea Level Rise Scenario, 3) a Warming Scenario, and 4) a combined Sea Level Rise and Warming Scenario. With a 1.6-1.9°C increase in monthly air temperatures in the Warming Scenario, water temperature in the Bay is estimated to increase by 0.8-1°C. Summer average anoxic volume is estimated to increase 1.4 percent compared to the Base Scenario, because of an increase in algal blooms in the spring and summer, promotion of oxygen consumptive processes, and an increase of stratification. However, a 0.5-meter Sea Level Rise Scenario results in a 12 percent reduction of anoxic volume. This is mainly due to increased estuarine circulation that promotes oxygen-rich sea water intrusion in lower layers. The combined Sea Level Rise and Warming Scenario results in a 10.8 percent reduction of anoxic volume. Global warming increases precipitation and consequently increases nutrient loads from the watershed by approximately 5-7 percent. A scenario that used a 10 percent increase in watershed loads and current estuarine circulation patterns yielded a 19 percent increase in summer anoxic volume, while a scenario that used a 10 percent increase in watershed loads and modified estuarine circulation patterns by the aforementioned sea level rise and warming yielded a 6 percent increase in summer anoxic volume. Impacts on phytoplankton, sediments, and water clarity were also analysed.