scholarly journals Neural-network-based simulation-optimization model for water allocation planning at basin scale

2008 ◽  
Vol 10 (4) ◽  
pp. 331-343 ◽  
Author(s):  
M. Shourian ◽  
S. Jamshid Mousavi ◽  
M. B. Menhaj ◽  
E. Jabbari
Keyword(s):  
River Basin ◽  
Network Flow ◽  
Model Performance ◽  
Optimization Methods ◽  
Pso Algorithm ◽  
Ann Model ◽  
Modeling Framework ◽  
Operational Variables ◽  
Basin Scale ◽  
Computationally Intensive

Heuristic search techniques are highly flexible, though they represent computationally intensive optimization methods that may require thousands of evaluations of expensive objective functions. This paper integrates MODSIM, a generalized river basin network flow model, a particle swarm optimization (PSO) algorithm and artificial neural networks into a modeling framework for optimum water allocations at basin scale. MODSIM is called in the PSO model to simulate a river basin system operation and to evaluate the fitness of each set of selected design and operational variables with respect to the model's objective function, which is the minimization of the system's design and operational cost. Since the direct incorporation of MODSIM into a PSO algorithm is computationally prohibitive, an ANN model as a meta-model is trained to approximate the MODSIM modeling tool. The resulting model is used in the problem of optimal design and operation of the upstream Sirvan river basin in Iran as a case study. The computational efficiency of the model makes it possible to analyze the model performance through changing its parameters so that better solutions are obtained compared to those of the original PSO–MODSIM model.

scholarly journals Modeling 25 years of spatio-temporal surface water and inundation dynamics on large river basin scale using time series of earth observation data

2015 ◽  
Vol 12 (11) ◽  
pp. 11847-11903 ◽  
Author(s):  
V. Heimhuber ◽  
M. G. Tulbure ◽  
M. Broich
Keyword(s):  
Time Series ◽  
Surface Water ◽  
River Basin ◽  
Earth Observation ◽  
Water Dynamics ◽  
Observation Data ◽  
Grid Cells ◽  
Modeling Framework ◽  
Basin Scale ◽  
Lag Times

Abstract. The usage of time series of earth observation (EO) data for analyzing and modeling surface water dynamics (SWD) across broad geographic regions provides important information for sustainable management and restoration of terrestrial surface water resources, which suffered alarming declines and deterioration globally. The main objective of this research was to model SWD from a unique validated Landsat-based time series (1986–2011) continuously through cycles of flooding and drying across a large and heterogeneous river basin, the Murray–Darling Basin (MDB) in Australia. We used dynamic linear regression to model remotely sensed SWD as a function of river flow and spatially explicit time series of soil moisture (SM), evapotranspiration (ET) and rainfall (P). To enable a consistent modeling approach across space, we modeled SWD separately for hydrologically distinct floodplain, floodplain-lake and non-floodplain areas within eco-hydrological zones and 10 km × 10 km grid cells. We applied this spatial modeling framework (SMF) to three sub-regions of the MDB, for which we quantified independently validated lag times between river gauges and each individual grid cell and identified the local combinations of variables that drive SWD. Based on these automatically quantified flow lag times and variable combinations, SWD on 233 (64 %) out of 363 floodplain grid cells were modeled with r2 ≥ 0.6. The contribution of P, ET and SM to the models' predictive performance differed among the three sub-regions, with the highest contributions in the least regulated and most arid sub-region. The SMF presented here is suitable for modeling SWD on finer spatial entities compared to most existing studies and applicable to other large and heterogeneous river basins across the world.

scholarly journals Socio-hydrologic modeling to understand and mediate the competition for water between agriculture development and environmental health: Murrumbidgee River Basin, Australia

2014 ◽  
Vol 11 (3) ◽  
pp. 3387-3435 ◽  
Author(s):  
T. H. M. van Emmerik ◽  
Z. Li ◽  
M. Sivapalan ◽  
S. Pande ◽  
J. Kandasamy ◽  
...  
Keyword(s):  
System Dynamics ◽  
Environmental Health ◽  
River Basin ◽  
Agricultural Development ◽  
Environmental Awareness ◽  
State Variables ◽  
Modeling Framework ◽  
Pendulum Swing ◽  
Basin Scale ◽  
Holistic Understanding

Abstract. Competition for water between humans and ecosystems is set to become a flash point in the coming decades in many parts of the world. An entirely new and comprehensive quantitative framework is needed to establish a holistic understanding of that competition, thereby enabling the development of effective mediation strategies. This paper presents a modeling study centered on the Murrumbidgee River Basin (MRB). The MRB has witnessed a unique system dynamics over the last 100 years as a result of interactions between patterns of water management and climate driven hydrological variability. Data analysis has revealed a pendulum swing between agricultural development and restoration of environmental health and ecosystem services over different stages of basin scale water resource development. A parsimonious, stylized, quasi-distributed coupled socio-hydrologic system model that simulates the two-way coupling between human and hydrological systems of the MRB is used to mimic dominant features of the pendulum swing. The model consists of coupled nonlinear ordinary differential equations that describe the interaction between five state variables that govern the co-evolution: reservoir storage, irrigated area, human population, ecosystem health, and a measure of environmental awareness. The model simulations track the propagation of the external climatic and socio-economic drivers through this coupled, complex system to the emergence of the pendulum swing. The model results point to a competition between human "productive" and environmental "restorative" forces that underpin the pendulum swing. Both the forces are endogenous, i.e., generated by the system dynamics in response to external drivers and mediated by humans through technology change and environmental awareness, respectively. We propose this as a generalizable modeling framework for coupled human hydrological systems that is potentially transferable to systems in different climatic and socio-economic settings.

scholarly journals MAgPIE 4 – a modular open-source framework for modeling global land systems

2019 ◽  
Vol 12 (4) ◽  
pp. 1299-1317 ◽  
Author(s):  
Jan Philipp Dietrich ◽  
Benjamin Leon Bodirsky ◽  
Florian Humpenöder ◽  
Isabelle Weindl ◽  
Miodrag Stevanović ◽  
...  
Keyword(s):  
Open Source ◽  
Model Evaluation ◽  
Model Performance ◽  
Source Modeling ◽  
Modeling Framework ◽  
Detailed Model ◽  
Specific Analysis ◽  
Land Systems ◽  
Computationally Intensive ◽  
Technical Features

Abstract. The open-source modeling framework MAgPIE (Model of Agricultural Production and its Impact on the Environment) combines economic and biophysical approaches to simulate spatially explicit global scenarios of land use within the 21st century and the respective interactions with the environment. Besides various other projects, it was used to simulate marker scenarios of the Shared Socioeconomic Pathways (SSPs) and contributed substantially to multiple IPCC assessments. However, with growing scope and detail, the non-linear model has become increasingly complex, computationally intensive and non-transparent, requiring structured approaches to improve the development and evaluation of the model.Here, we provide an overview on version 4 of MAgPIE and how it addresses these issues of increasing complexity using new technical features: modular structure with exchangeable module implementations, flexible spatial resolution, in-code documentation, automatized code checking, model/output evaluation and open accessibility. Application examples provide insights into model evaluation, modular flexibility and region-specific analysis approaches. While this paper is focused on the general framework as such, the publication is accompanied by a detailed model documentation describing contents and equations, and by model evaluation documents giving insights into model performance for a broad range of variables.With the open-source release of the MAgPIE 4 framework, we hope to contribute to more transparent, reproducible and collaborative research in the field. Due to its modularity and spatial flexibility, it should provide a basis for a broad range of land-related research with economic or biophysical, global or regional focus.

scholarly journals Modeling 25 years of spatio-temporal surface water and inundation dynamics on large river basin scale using time series of Earth observation data

2016 ◽  
Vol 20 (6) ◽  
pp. 2227-2250 ◽  
Author(s):  
Valentin Heimhuber ◽  
Mirela G. Tulbure ◽  
Mark Broich
Keyword(s):  
Time Series ◽  
Surface Water ◽  
River Basin ◽  
Spatial Modeling ◽  
Earth Observation ◽  
Observation Data ◽  
Grid Cells ◽  
Modeling Framework ◽  
Basin Scale ◽  
Lag Times

Abstract. The usage of time series of Earth observation (EO) data for analyzing and modeling surface water extent (SWE) dynamics across broad geographic regions provides important information for sustainable management and restoration of terrestrial surface water resources, which suffered alarming declines and deterioration globally. The main objective of this research was to model SWE dynamics from a unique, statistically validated Landsat-based time series (1986–2011) continuously through cycles of flooding and drying across a large and heterogeneous river basin, the Murray–Darling Basin (MDB) in Australia. We used dynamic linear regression to model remotely sensed SWE as a function of river flow and spatially explicit time series of soil moisture (SM), evapotranspiration (ET), and rainfall (P). To enable a consistent modeling approach across space, we modeled SWE dynamics separately for hydrologically distinct floodplain, floodplain-lake, and non-floodplain areas within eco-hydrological zones and 10km × 10km grid cells. We applied this spatial modeling framework to three sub-regions of the MDB, for which we quantified independently validated lag times between river gauges and each individual grid cell and identified the local combinations of variables that drive SWE dynamics. Based on these automatically quantified flow lag times and variable combinations, SWE dynamics on 233 (64 %) out of 363 floodplain grid cells were modeled with a coefficient of determination (r2) greater than 0.6. The contribution of P, ET, and SM to the predictive performance of models differed among the three sub-regions, with the highest contributions in the least regulated and most arid sub-region. The spatial modeling framework presented here is suitable for modeling SWE dynamics on finer spatial entities compared to most existing studies and applicable to other large and heterogeneous river basins across the world.

scholarly journals Socio-hydrologic modeling to understand and mediate the competition for water between agriculture development and environmental health: Murrumbidgee River basin, Australia

2014 ◽  
Vol 18 (10) ◽  
pp. 4239-4259 ◽  
Author(s):  
T. H. M. van Emmerik ◽  
Z. Li ◽  
M. Sivapalan ◽  
S. Pande ◽  
J. Kandasamy ◽  
...  
Keyword(s):  
System Dynamics ◽  
Environmental Health ◽  
River Basin ◽  
Hydrologic Modeling ◽  
Environmental Awareness ◽  
Coupled Systems ◽  
Modeling Framework ◽  
Pendulum Swing ◽  
Basin Scale ◽  
Holistic Understanding

Abstract. Competition for water between humans and ecosystems is set to become a flash point in the coming decades in many parts of the world. An entirely new and comprehensive quantitative framework is needed to establish a holistic understanding of that competition, thereby enabling the development of effective mediation strategies. This paper presents a modeling study centered on the Murrumbidgee River basin (MRB). The MRB has witnessed a unique system dynamics over the last 100 years as a result of interactions between patterns of water management and climate driven hydrological variability. Data analysis has revealed a pendulum swing between agricultural development and restoration of environmental health and ecosystem services over different stages of basin-scale water resource development. A parsimonious, stylized, quasi-distributed coupled socio-hydrologic system model that simulates the two-way coupling between human and hydrological systems of the MRB is used to mimic and explain dominant features of the pendulum swing. The model consists of coupled nonlinear ordinary differential equations that describe the interaction between five state variables that govern the co-evolution: reservoir storage, irrigated area, human population, ecosystem health, and environmental awareness. The model simulations track the propagation of the external climatic and socio-economic drivers through this coupled, complex system to the emergence of the pendulum swing. The model results point to a competition between human "productive" and environmental "restorative" forces that underpin the pendulum swing. Both the forces are endogenous, i.e., generated by the system dynamics in response to external drivers and mediated by humans through technology change and environmental awareness, respectively. Sensitivity analysis carried out with the model further reveals that socio-hydrologic modeling can be used as a tool to explain or gain insight into observed co-evolutionary dynamics of diverse human–water coupled systems. This paper therefore contributes to the ultimate development of a generic modeling framework that can be applied to human–water coupled systems in different climatic and socio-economic settings.

Innovative Tools for Water Quality Management and Policy Analysis: Desert and Streamplan

1999 ◽  
Vol 40 (10) ◽  
pp. 103-110
Author(s):  
Carlo De Marchi ◽  
Pavel Ivanov ◽  
Ari Jolma ◽  
Ilia Masliev ◽  
Mark Griffin Smith ◽  
...  
Keyword(s):  
Water Quality ◽  
Quality Management ◽  
Policy Analysis ◽  
River Basin ◽  
Emission Reduction ◽  
Water Quality Management ◽  
Water Quality Modeling ◽  
Detailed Model ◽  
Basin Scale ◽  
Alternative Water

This paper presents the major features of two decision support systems (DSS) for river water quality modeling and policy analysis recently developed at the International Institute of Applied Systems Analysis (IIASA), DESERT and STREAMPLAN. DESERT integrates in a single package data management, model calibration, simulation, optimization and presentation of results. DESERT has the flexibility to allow the specification of both alternative water quality models and flow hydraulics for different branches of the same river basin. Specification of these models can be done interactively through Microsoft® Windows commands and menus and an easy to use interpreted language. Detailed analysis of the effects of parameter uncertainty on water quality results is integrated into DESERT. STREAMPLAN, on the other hand, is an integrated, easy-to-use software system for analyzing alternative water quality management policies on a river basin level. These policies include uniform emission reduction and effluent standard based strategies, ambient water quality and least-cost strategies, total emission reduction under minimized costs, mixed strategies, local and regional policies, and strategies with economic instruments. A distinctive feature of STREAMPLAN is the integration of a detailed model of municipal wastewater generation with a water quality model and policy analysis tools on a river basin scale.

scholarly journals Winter Inputs Buffer Streamflow Sensitivity to Snowpack Losses in the Salt River Watershed in the Lower Colorado River Basin

Water ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 3
Author(s):  
Marcos D. Robles ◽  
John C. Hammond ◽  
Stephanie K. Kampf ◽  
Joel A. Biederman ◽  
Eleonora M. C. Demaria
Keyword(s):  
River Basin ◽  
Colorado River ◽  
Snow Accumulation ◽  
Colorado River Basin ◽  
Scale Model ◽  
Annual Streamflow ◽  
Basin Scale ◽  
Salt River ◽  
Lower Colorado River Basin ◽  
Lower Colorado River

Recent streamflow declines in the Upper Colorado River Basin raise concerns about the sensitivity of water supply for 40 million people to rising temperatures. Yet, other studies in western US river basins present a paradox: streamflow has not consistently declined with warming and snow loss. A potential explanation for this lack of consistency is warming-induced production of winter runoff when potential evaporative losses are low. This mechanism is more likely in basins at lower elevations or latitudes with relatively warm winter temperatures and intermittent snowpacks. We test whether this accounts for streamflow patterns in nine gaged basins of the Salt River and its tributaries, which is a sub-basin in the Lower Colorado River Basin (LCRB). We develop a basin-scale model that separates snow and rainfall inputs and simulates snow accumulation and melt using temperature, precipitation, and relative humidity. Despite significant warming from 1968–2011 and snow loss in many of the basins, annual and seasonal streamflow did not decline. Between 25% and 50% of annual streamflow is generated in winter (NDJF) when runoff ratios are generally higher and potential evapotranspiration losses are one-third of potential losses in spring (MAMJ). Sub-annual streamflow responses to winter inputs were larger and more efficient than spring and summer responses and their frequencies and magnitudes increased in 1968–2011 compared to 1929–1967. In total, 75% of the largest winter events were associated with atmospheric rivers, which can produce large cool-season streamflow peaks. We conclude that temperature-induced snow loss in this LCRB sub-basin was moderated by enhanced winter hydrological inputs and streamflow production.

scholarly journals Using the Global Hydrodynamic Model and GRACE Follow-On Data to Access the 2020 Catastrophic Flood in Yangtze River Basin

2021 ◽  
Vol 13 (15) ◽  
pp. 3023
Author(s):  
Jinghua Xiong ◽  
Shenglian Guo ◽  
Jiabo Yin ◽  
Lei Gu ◽  
Feng Xiong
Keyword(s):  
River Basin ◽  
Hydrodynamic Model ◽  
Yangtze River ◽  
Large Scale ◽  
Yangtze River Basin ◽  
The Yangtze River ◽  
Ecosystem Monitoring ◽  
Catastrophic Flood ◽  
Basin Scale ◽  
The Yangtze River Basin

Flooding is one of the most widespread and frequent weather-related hazards that has devastating impacts on the society and ecosystem. Monitoring flooding is a vital issue for water resources management, socioeconomic sustainable development, and maintaining life safety. By integrating multiple precipitation, evapotranspiration, and GRACE-Follow On (GRAFO) terrestrial water storage anomaly (TWSA) datasets, this study uses the water balance principle coupled with the CaMa-Flood hydrodynamic model to access the spatiotemporal discharge variations in the Yangtze River basin during the 2020 catastrophic flood. The results show that: (1) TWSA bias dominates the overall uncertainty in runoff at the basin scale, which is spatially governed by uncertainty in TWSA and precipitation; (2) spatially, a field significance at the 5% level is discovered for the correlations between GRAFO-based runoff and GLDAS results. The GRAFO-derived discharge series has a high correlation coefficient with either in situ observations and hydrological simulations for the Yangtze River basin, at the 0.01 significance level; (3) the GRAFO-derived discharge observes the flood peaks in July and August and the recession process in October 2020. Our developed approach provides an alternative way of monitoring large-scale extreme hydrological events with the latest GRAFO release and CaMa-Flood model.

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