The Effects of Changing Land Cover on Streamflow Simulation in Puerto Rico

This study quantitatively explores whether land cover changes have a substantive impact on simulated streamflow within the tropical island setting of Puerto Rico. The Precipitation Runoff Modeling System (PRMS) was used to compare streamflow simulations based on five static parameterizations of land cover with those based on dynamically varying parameters derived from four land cover scenes for the period 1953‐2012. The PRMS simulations based on static land cover illustrated consistent differences in simulated streamflow across the island. It was determined that the scale of the analysis makes a difference: large regions with localized areas that have undergone dramatic land cover change may show negligible difference in total streamflow, but streamflow simulations using dynamic land cover parameters for a highly altered subwatershed clearly demonstrate the effects of changing land cover on simulated streamflow. Incorporating dynamic parameterization in these highly altered watersheds can reduce the predictive uncertainty in simulations of streamflow using PRMS. Hydrologic models that do not consider the projected changes in land cover may be inadequate for water resource management planning for future conditions.     

Modelling land use change and environmental impact

Land use change models are tools for understanding and explaining the causes and consequences of land use dynamics. Recently, new models, combining knowledge and tools from biophysical and socio-economic sciences, have become available. This has resulted in spatially explicit models focussed on patterns of change as well as agent-based models focused on the underlying decision processes. These developments improve the use of land use change models in environmental impact studies. This special issue documents these developments: (i) analysing the system properties in a biophysical and socio-economic context at multiple scales; (ii) integrating spatially explicit land use change models in integrated assessment models; (iii) visualising and quantifying the potential effects of land use change in trade-off curves, to support land users and policy makers in their decisions; and (iv) modelling of the actual decision making process with agent-based modelling. A new promising future development is the incorporation of dynamic feedbacks between changing land use and changing environmental conditions and vice versa. Unfortunately such dynamic feedbacks between the socio-economic and biophysical model components are still not or only partially operational in current models and are therefore the most important challenge for land use and environmental modellers.     

Assessing hydrological impact of potential land use change through hydrological and land use change modeling for the Kishwaukee River basin (USA)

We connected a cellular, dynamic, spatial urban growth model and a semi-distributed continuous hydrology model to quantitatively predict streamflow in response to possible future urban growth at a basin scale. The main goal was to demonstrate the utility of the approach for informing public planning policy and investment choices. The Hydrological Simulation Program-Fortran (HSPF) was set up and calibrated for the Kishwaukee River basin in the Midwestern USA and was repeatedly run with various land use scenarios generated either by the urban growth model (LEAMluc) or hypothetically. The results indicate that (1) the land use scenarios generated by LEAMluc result in little changes in total runoff but some noticeable changes in surface flow; (2) the argument that low flows tend to decrease with more urbanized areas in a basin was confirmed in this study but the selection of indicators for low flows can result in misleading conclusions; (3) dynamic simulation modeling by connecting a distributed land use change model and a semi-distributed hydrological model can be a good decision support tool demanding reasonable amount of efforts and capable of long-term scenario-based assessments.     

Impact of Climate and Land Use Change on Streamflow and Sediment Yield in a Snow‐Dominated Semiarid Mountainous Watershed

This study investigates the impact of climate and land use change on the magnitude and timing of streamflow and sediment yield in a snow‐dominated mountainous watershed in Salt Lake County, Utah using a scenario approach and the Hydrological Simulation Program — FORTRAN model for the 2040s (year 2035–2044) and 2090s (year 2085–2094). The climate scenarios were statistically and dynamically downscaled from global climate models. Land use and land cover (LULC) changes were estimated in two ways — from a regional planning scenario and from a deterministic model. Results indicate the mean daily streamflow in the Jordan River watershed will increase by an amount ranging from 11.2% to 14.5% in the 2040s and from 6.8% to 15.3% in the 2090s. The respective increases in sediment load in the 2040s and 2090s is projected to be 6.7% and 39.7% in the canyons and about 7.4% to 14.2% in the Jordan valley. The historical 50th percentile timing of streamflow and sediment load is projected to be shifted earlier by three to four weeks by mid‐century and four to eight weeks by late‐century. The projected streamflow and sediment load results establish a nonlinear relationship with each other and are highly sensitive to projected climate change. The predicted changes in streamflow and sediment yield will have implications for water supply, flood control and stormwater management.     

Characterization of Storm Flow Dynamics of Headwater Streams in the South Carolina Lower Coastal Plain1

Epps, Thomas H., Daniel R. Hitchcock, Anand D. Jayakaran, Drake R. Loflin, Thomas M. Williams, and Devendra M. Amatya, 2012. Characterization of Storm Flow Dynamics of Headwater Streams in the South Carolina Lower Coastal Plain. Journal of the American Water Resources Association (JAWRA) 1‐14. DOI: 10.1111/jawr.12000 Abstract: Hydrologic monitoring was conducted in two first‐order lower coastal plain watersheds in South Carolina, United States, a region with increasing growth and land use change. Storm events over a three‐year period were analyzed for direct runoff coefficients (ROC) and the total storm response (TSR) as percent rainfall. ROC calculations utilized an empirical hydrograph separation method that partitioned total streamflow into sustained base flow and direct runoff components. ROC ratios ranged from 0 to 0.32 on the Upper Debidue Creek (UDC) watershed and 0 to 0.57 on Watershed 80 (WS80); TSR results ranged from 0 to 0.93 at UDC and 0.01 to 0.74 at WS80. Variability in event runoff generation was attributed to seasonal trends in water table elevation fluctuation as regulated by evapotranspiration. Groundwater elevation breakpoints for each watershed were identified based on antecedent water table elevation, streamflow, ROCs, and TSRs. These thresholds represent the groundwater elevation above which event runoff generation increased sharply in response to rainfall. For effective coastal land use decision making, baseline watershed hydrology must be understood to serve as a benchmark for management goals, based on both seasonal and event‐based surface and groundwater interactions.     

APPLICATION OF THE SNOWMELT RUNOFF MODEL USING MULTIPLE-PARAMETER LANDSCAPE ZONES ON THE TOWANDA CREEK BASIN,PENNSYLVANIA1

ABSTRACT: The Snowmelt Runoff Model (SRM) is designed to compute daily stream discharge using satellite snow cover data for a basin divided into elevation zones. For the Towanda Creek basin, a Pennsylvania watershed with relatively little relief, analysis of snow cover images revealed that both elevation and land use affected snow accumulation and melt on the landscape. The distribution of slope and aspect on the watershed was also considered; however, these landscape features were not well correlated with the available snow cover data. SRM streamflow predictions for 1990, 1993 and 1994 snowmelt seasons for the Towanda Creek basin using a combination of elevation and land use zones yielded more precise streamflow estimates than the use of standard elevation zones alone. The use of multiple-parameter zones worked best in non-rain-on-snow conditions such as in 1990 and 1994 seasons where melt was primarily driven by differences in solar radiation. For seasons with major rain-on-snow events such as 1993, only modest improvements were shown since melt was dominated by rainfall energy inputs, condensation and sensible heat convection. Availability of GIS coverages containing satellite snow cover data and other landscape attributes should permit similar reformulation of multiple-parameter watershed zones and improved SRM streamflow predictions on other basins.     

Optimal Land Use Management for Soil Erosion Control by Using an Interval-Parameter Fuzzy Two-Stage Stochastic Programming Approach

Soil erosion is one of the most serious environmental and public health problems, and such land degradation can be effectively mitigated through performing land use transitions across a watershed. Optimal land use management can thus provide a way to reduce soil erosion while achieving the maximum net benefit. However, optimized land use allocation schemes are not always successful since uncertainties pertaining to soil erosion control are not well presented. This study applied an interval-parameter fuzzy two-stage stochastic programming approach to generate optimal land use planning strategies for soil erosion control based on an inexact optimization framework, in which various uncertainties were reflected. The modeling approach can incorporate predefined soil erosion control policies, and address inherent system uncertainties expressed as discrete intervals, fuzzy sets, and probability distributions. The developed model was demonstrated through a case study in the Xiangxi River watershed, China’s Three Gorges Reservoir region. Land use transformations were employed as decision variables, and based on these, the land use change dynamics were yielded for a 15-year planning horizon. Finally, the maximum net economic benefit with an interval value of [1.197, 6.311] × 10⁹ $ was obtained as well as corresponding land use allocations in the three planning periods. Also, the resulting soil erosion amount was found to be decreased and controlled at a tolerable level over the watershed. Thus, results confirm that the developed model is a useful tool for implementing land use management as not only does it allow local decision makers to optimize land use allocation, but can also help to answer how to accomplish land use changes.     

HISTORICAL EVOLUTION OF FLOODING DAMAGE ON A USA/QUEBEC RIVER BASIN1

ABSTRACT: There is a general belief in the public eye that extreme events such as floods are becoming more and more common. This paper explores this hypothesis by examining the historical evolution of annual expected flooding damage on the Chateauguay River Basin, located at the border between the United States and the province of Quebec, Canada. A database of basin land use was constructed for the years 1930 and 1995 to assess anthropogenic changes and their impact on the basin's hydrology. The progressive modification of the likelihood of a flooding event over the same period was then investigated using homogeneity and statistical tests on available hydrometric data. The evolution of the annual expected flooding damage was then evaluated using a coupled hydrologic/hydraulic simulator linked to a damage analysis model. The simulator and model were used to estimate flooding damage over a wide range of flooding return periods, for conditions prevailing in 1963 and 1995. Results of the analysis reveal the absence of any increasing or decreasing trend in the historical occurrence of flooding events. However, a general increase in the annual expected flooding damage was observed for all studied river sections. This increase is linked to an historical increase in damages for a given flooding event, and is the result of unbridled construction and development within the flood zone. To assess for future trends, this study also examined the potential impacts linked to the anticipated global warming. Results indicate that a significant increase in seasonal flooding events and annual expected flooding damage is possible over the next century. In fact, what is now considered a 100‐year flooding event for the summer/fall season could become a ten‐year event by the end of this century. This shows that potential future impacts linked to climate change should be considered now by engineers, land planners, and decision makers. This is especially critical if a design return period is part of the decision making process.     

Decoupling Streamflow Responses to Climate Variability and Land Use/Cover Changes in a Watershed in Northern China

Restored annual streamflow (Q_r) and measured daily streamflow of the Chaohe watershed located in northern China and associated long‐term climate and land use/cover data were used to explore the effects of land use/cover change and climate variability on the streamflow during 1961‐2009. There were no significant changes in annual precipitation (P) and potential evapotranspiration, whereas Q_r decreased significantly by 0.81 mm/yr (p < 0.001) over the study period with a change point in 1999. We used 1961‐1998 as the baseline period (BP) and 1999‐2009 the change period (CP). The mean Q_r during the CP decreased by 39.4 mm compared with that in the BP. From 1979 to 2009, the grassland area declined by 69.6%, and the forest and shrublands increased by 105.4 and 73.1%, respectively. The land use/cover change and climate variability contributed for 58.4 and 41.6% reduction in mean annual Q_r, respectively. Compared with the BP, median and high flows in the CP decreased by 38.8 and up to 75.5%, respectively. The study concludes that large‐scale ecological restoration and watershed management in northern China has greatly decreased water yield and reduced high flows due to the improved land cover by afforestation leading to higher water loss through evapotranspiration. At a large watershed scale, land use/cover change could play as much of an important role as climate variability on water resources.     

Streamflow Hydrology Estimate Using Machine Learning (SHEM)

Continuity and accuracy of near real‐time streamflow gauge (streamgage) data are critical for flood forecasting, assessing imminent risk, and implementing flood mitigation activities. Without these data, decision makers and first responders are limited in their ability to effectively allocate resources, implement evacuations to save lives, and reduce property losses. The Streamflow Hydrology Estimate using Machine Learning (SHEM) is a new predictive model for providing accurate and timely proxy streamflow data for inoperative streamgages. SHEM relies on machine learning (“training”) to process and interpret large volumes (“big data”) of historic complex hydrologic information. Continually updated with real‐time streamflow data, the model constructs a virtual dataset index of correlations and groups (clusters) of relationship correlations between selected streamgages in a watershed and under differing flow conditions. Using these datasets, SHEM interpolates estimated discharge and time data for any indexed streamgage that stops transmitting data. These estimates are continuously tested, scored, and revised using multiple regression analysis processes and methodologies. The SHEM model was tested in Idaho and Washington in four diverse watersheds, and the model's estimates were then compared to the actual recorded data for the same time period. Results from all watersheds revealed a high correlation, validating both the degree of accuracy and reliability of the model.     

Impacts of Climate Change on Extreme Precipitation Events Over Flamingo Tropicana Watershed1

Abstract: Climate change, particularly the projected changes to precipitation patterns, is likely to affect runoff both regionally and temporally. Extreme rainfall events are expected to become more intense in the future in arid urban areas and this will likely lead to higher streamflow. Through hydrological modeling, this article simulates an urban basin response to the most intense storm under anthropogenic climate change conditions. This study performs an event‐based simulation for shorter duration storms in the Flamingo Tropicana (FT) watershed in Las Vegas, Nevada. An extreme storm, defined as a 100‐year return period storm, is selected from historical records and perturbed to future climatic conditions with respect to multimodel multiscenario (A1B, A2, B1) bias corrected and spatially disaggregated data from the World Climate Research Programme's (WCRP's) database. The cumulative annual precipitation for each 30‐year period shows a continuous decrease from 2011 to 2099; however, the summer convective storms, which are considered as extreme storms for the study area, are expected to be more intense in future. Extreme storm events show larger changes in streamflow under different climate scenarios and time periods. The simulated peak streamflow and total runoff volume shows an increase from 40% to more than 150% (during 2041‐2099) for different climate scenarios. This type of analysis can help evaluate the vulnerability of existing flood control system and flood control policies.     

Streamflow Responses to Climate Change: Analysis of Hydrologic Indicators in a New York City Water Supply Watershed

Recent works have indicated that climate change in the northeastern United States is already being observed in the form of shorter winters, higher annual average air temperature, and more frequent extreme heat and precipitation events. These changes could have profound effects on aquatic ecosystems, and the implications of such changes are less understood. The objective of this study was to examine how future changes in precipitation and temperature translate into changes in streamflow using a physically based semidistributed model, and subsequently how changes in streamflow could potentially impact stream ecology. Streamflow parameters were examined in a New York City water supply watershed for changes from model‐simulated baseline conditions to future climate scenarios (2081‐2100) for ecologically relevant factors of streamflow using the Indicators of Hydrologic Alterations tool. Results indicate that earlier snowmelt and reduced snowpack advance the timing and increase the magnitude of discharge in the winter and early spring (November‐March) and greatly decrease monthly streamflow later in the spring in April. Both the rise and fall rates of the hydrograph will increase resulting in increased flashiness and flow reversals primarily due to increased pulses during winter seasons. These shifts in timing of peak flows, changes in seasonal flow regimes, and changes in the magnitudes of low flow can all influence aquatic organisms and have the potential to impact stream ecology.     

GIS BASED LONG TERM HYDROLOGIC IMPACT EVALUATION FOR WATERSHED URBANIZATION1

ABSTRACT: To adequately manage impacts of ongoing or future land use changes in a watershed, the magnitude of their hydrologic impacts needs to be assessed. A grid based daily streamflow model was calibrated with two years of observed streamflow data, using time periods when land use data are available and verified by comparison of model predictions with observed streamflow data. Streamflow data were separated into direct runoff and baseflow to estimate the impacts of urbanization on each hydrologic component. Analysis of the ratio between direct runoff and total runoff from 30 years of simulation results and the change in these ratios with urbanization shows that estimated annual direct runoff increased from 49.2 percent (1973) to 63.1 percent (1984) and 65.0 percent (1991), indicating the effects of urbanization are greater on direct runoff than on total runoff. The direct runoff ratio also varies with annual rainfall, with dry year ratios larger than those for wet years. This suggests that the impact of urbanization on areas that are sensitive to runoff ratios, such as stream ecosystems, might be more serious during drier years than in wetter years in terms of water quality and water yield. This indicates that sustainable base‐flow is important to maintaining sound stream ecosystems.     

Land Resources Allocation Strategies in an Urban Area Involving Uncertainty: A Case Study of Suzhou,in the Yangtze River Delta of China

A large number of mathematical models have been developed to support land resource allocation decisions and land management needs; however, few of them can address various uncertainties that exist in relation to many factors presented in such decisions (e.g., land resource availabilities, land demands, land-use patterns, and social demands, as well as ecological requirements). In this study, a multi-objective interval-stochastic land resource allocation model (MOISLAM) was developed for tackling uncertainty that presents as discrete intervals and/or probability distributions. The developed model improves upon the existing multi-objective programming and inexact optimization approaches. The MOISLAM not only considers economic factors, but also involves food security and eco-environmental constraints; it can, therefore, effectively reflect various interrelations among different aspects in a land resource management system. Moreover, the model can also help examine the reliability of satisfying (or the risk of violating) system constraints under uncertainty. In this study, the MOISLAM was applied to a real case of long-term urban land resource allocation planning in Suzhou, in the Yangtze River Delta of China. Interval solutions associated with different risk levels of constraint violation were obtained. The results are considered useful for generating a range of decision alternatives under various system conditions, and thus helping decision makers to identify a desirable land resource allocation strategy under uncertainty.     

Assessment of Economic and Water Quality Impacts of Land Use Change Using a Simple Bioeconomic Model

The objective of this study is to assess the economic and water quality impact of land use change in a small watershed in the Wiregrass region of Alabama. The study compares changes in water quality and revenue from agricultural and timber production due to changes in land use between years 1992 and 2001. The study was completed in two stages. In the first stage, a biophysical model was used to estimate the effect of land use change on nitrogen and phosphorus runoff and sediment deposition in the main channel; in the second stage, farm enterprise budgeting tools were used to estimate the economic returns for the changes in land use condition. Both biophysical and economic results are discussed, and a case for complex optimization to develop a decision support system is presented.     

Trade-off analysis in the Northern Andes to study the dynamics in agricultural land use

In this paper we hypothesize that land use change can be induced by non-linearities and thresholds in production systems that impact farmers' decision making. Tradeoffs between environmental and economic indicators is a useful way to represent dynamic properties of agricultural systems. The Tradeoff Analysis (TOA) System is software designed to implement the integrated analysis of tradeoffs in agricultural systems. The TOA methodology is based on spatially explicit econometric simulation models linked to spatially referenced bio-physical simulation models to simulate land use and input decisions. The methodology has been applied for the potato-pasture production system in the Ecuadorian Andes. The land use change literature often describes non-linearity in land use change as a result of sudden changes in the political (e.g. new agricultural policies) or environmental setting (e.g. earthquakes). However, less attention has been paid to the non-linearities in production systems and their consequences for land use change. In this paper, we use the TOA system to study agricultural land use dynamics and to find the underlying processes for non-linearities. Results show that the sources of non-linearities are in the properties of bio-physical processes and in the decision making-process of farmers.     

An Analysis of the Effects of Land Use and Land Cover on Flood Losses along the Gulf of Mexico Coast from 1999 to 2009

Major coastal flooding events over the last decade have led decision makers in the United States to favor structural engineering solutions as a means to protect vulnerable coastal communities from the adverse impacts of future storms. While a resistance‐based approach to flood mitigation involving large‐scale construction works may be a central component of a regional flood risk reduction strategy, it is equally important to consider the role of land use and land cover (LULC) patterns in protecting communities from floods. To date, little observational research has been conducted to quantify the effects of various LULC configurations on the amount of property damage occurring across coastal regions over time. In response, we statistically examine the impacts of LULC on observed flood damage across 2,692 watersheds bordering the Gulf of Mexico. Specifically, we analyze statistical linear regression models to isolate the influence of multiple LULC categories on over 372,000 insured flood losses claimed under the National Flood Insurance Program per year from 2001 to 2008. Results indicate that percent increase in palustrine wetlands is the equivalent to, on average, a $13,975 reduction in insured flood losses per year, per watershed. These and other results provide important insights to policy makers on how protecting specific types of LULC can help reduce adverse impacts to local communities.     

SIMULATION OF THE EFFECTS OF URBANIZATION ON BASIN STREAMFLOW1

ABSTRACT: The hydrologic modeling of streamflow in the Waterford River Basin has been conducted as part of comprehensive investigations of the effects of urbanization on water resources in the basin. Using a detailed input data base, continuous simulation of streamflow in the study area has been done by means of the HSPF model, which has been calibrated for the existing conditions and then applied to several future land use scenarios. The basin climate and geology contribute to high conversion of precipitation into streamflow under the existing conditions. Consequently, future urban development in the study basin should not increase the annual streamflow, but would contribute to increases in peak flows and the incidence of flooding because of the increased speed of runoff. If the impervious area in the basin is doubled, the peak flows may increase by about 20 percent.     

Climate and Land Use Effects on Hydrologic Processes in a Primarily Rain‐Fed,Agricultural Watershed

Anticipating changes in hydrologic variables is essential for making socioeconomic water resource decisions. This study aims to assess the potential impact of land use and climate change on the hydrologic processes of a primarily rain‐fed, agriculturally based watershed in Missouri. A detailed evaluation was performed using the Soil and Water Assessment Tool for the near future (2020–2039) and mid‐century (2040–2059). Land use scenarios were mapped using the Conversion of Land Use and its Effects model. Ensemble results, based on 19 climate models, indicated a temperature increase of about 1.0°C in near future and 2.0°C in mid‐century. Combined climate and land use change scenarios showed distinct annual and seasonal hydrologic variations. Annual precipitation was projected to increase from 6% to 7%, which resulted in 14% more spring days with soil water content equal to or exceeding field capacity in mid‐century. However, summer precipitation was projected to decrease, a critical factor for crop growth. Higher temperatures led to increased potential evapotranspiration during the growing season. Combined with changes in precipitation patterns, this resulted in an increased need for irrigation by 38 mm representing a 10% increase in total irrigation water use. Analysis from multiple land use scenarios indicated converting agriculture to forest land can potentially mitigate the effects of climate change on streamflow, thus ensuring future water availability.     

Sustainable coasts? Perceptions of change and livelihood vulnerability in Nordland,Norway

ABSTRACT

Northern coastal regions are facing multiple challenges from accelerating global environmental and socioeconomic changes, such as ecosystem degradation, climate change, intensified resource extraction, land use change and declining populations. Based on interviews with 13 farmers, fishers and aquaculture employees from coastal Nordland, northern Norway, this study demonstrates how the local stakeholders’ perceptions of change and experiences of vulnerability are closely linked to their livelihood values and worldviews. What the informants consider a sustainable and meaningful way of coastal living does not coincide with national goals for sustainable, natural resource dependent development of the region. The article demonstrates the importance of attending to local values if policymakers and managers are to ensure successful local mobilisation, reduce vulnerability to ongoing and future processes of change, and ensure legitimacy and consistency in development goals of coastal zone management. Insights from this study are useful for local and regional decision makers with responsibility for natural resource policies and development efforts.