The role of remote sensing in hydrological modelling of the Okavango Delta, Botswana

A coupled surface water-groundwater model of the Okavango Delta has been built based on the United States Geological Survey software MODFLOW 2000 including the SFR2 package for stream-flow routing. It will provide a new tool for evaluating water management and climate change scenarios. The delta's size and limited accessibility make direct, on the ground data acquisition difficult. Remote sensing methods are the most promising source of acquiring spatially distributed data for both model input parameters and calibration. Topography, aquifer thickness, channel positions, evapotranspiration and precipitation data are all based on remote sensing. Simulated flooding patterns are compared to patterns derived from visible to thermal NOAA-AVHRR data and microwave radar ENVISAT-ASAR data.     

Arctic Lake Physical Processes and Regimes with Implications for Winter Water Availability and Management in the National Petroleum Reserve Alaska

Lakes are dominant landforms in the National Petroleum Reserve Alaska (NPRA) as well as important social and ecological resources. Of recent importance is the management of these freshwater ecosystems because lakes deeper than maximum ice thickness provide an important and often sole source of liquid water for aquatic biota, villages, and industry during winter. To better understand seasonal and annual hydrodynamics in the context of lake morphometry, we analyzed lakes in two adjacent areas where winter water use is expected to increase in the near future because of industrial expansion. Landsat Thematic Mapper and Enhanced Thematic Mapper Plus imagery acquired between 1985 and 2007 were analyzed and compared with climate data to understand interannual variability. Measured changes in lake area extent varied by 0.6% and were significantly correlated to total precipitation in the preceding 12 months (p < 0.05). Using this relation, the modeled lake area extent from 1985 to 2007 showed no long-term trends. In addition, high-resolution aerial photography, bathymetric surveys, water-level monitoring, and lake-ice thickness measurements and growth models were used to better understand seasonal hydrodynamics, surface area-to-volume relations, winter water availability, and more permanent changes related to geomorphic change. Together, these results describe how lakes vary seasonally and annually in two critical areas of the NPRA and provide simple models to help better predict variation in lake-water supply. Our findings suggest that both overestimation and underestimation of actual available winter water volume may occur regularly, and this understanding may help better inform management strategies as future resource use expands in the NPRA.     

Comparison of Function of Created Wetlands of Two Age Classes in Central Pennsylvania

Hydrogeomorphic (HGM) functional assessment models were used to assess whether function in created wetlands of two ages (1 year old and >12 years old) was equivalent to that of natural (reference) mainstem floodplain wetlands. Reference wetlands scored higher than both created age classes for providing energy dissipation and short-term surface water storage. Reference wetlands scored higher in maintaining native plant community and structure than 1-year-old sites, and 12-year-old wetlands scored higher than reference sites for providing vertebrate habitat structure. Analysis of individual model variables showed that reference wetlands had greater vegetative biomass and higher soil organic matter content than both created wetland age classes. Created wetlands were farther from natural wetlands and had smaller mean forest patch sizes within a 1-km-radius circle around the site than did the reference sites, indicating less hydrologic connectivity. Created wetlands also had less microtopographic variation than reference wetlands. The 1-year-old created sites were placed in landscape settings with greater land use diversity and road density than reference sites. The 12-year-old sites had a higher gradient and a higher percentage of their surrounding area in urban land use. These results show that the created wetlands were significantly structurally different (if not functionally so) from reference wetlands even after 12 years. The most profound differences were in hydrology and the characteristics of the surrounding landscape. More attention needs to be focused on placing created wetlands in appropriate settings to encourage proper hydrodynamics, eliminate habitat fragmentation, and minimize the effects of stressors to the site.     

MODIS Biophysical States and NEXRAD Precipitation in a Statistical Evaluation of Antecedent Moisture Condition and Streamflow1

Abstract: The potential of remotely sensed time series of biophysical states of landscape to characterize soil moisture condition antecedent to radar estimates of precipitation is assessed in a statistical prediction model of streamflow in a 1,420 km² watershed in south‐central Texas, Moderate Resolution Imaging Spectroradiometer (MODIS) time series biophysical products offer significant opportunities to characterize and quantify hydrologic state variables such as land surface temperature (LST) and vegetation state and status. Together with Next Generation Weather Radar (NEXRAD) precipitation estimates for the period 2002 through 2005, 16 raw and deseasoned time series of LST (day and night), vegetation indices, infrared reflectances, and water stress indices were linearly regressed against observed watershed streamflow on an eight‐day aggregated time period. Time offsets of 0 (synchronous with streamflow event), 8, and 16 days (leading streamflow event) were assessed for each of the 16 parameters to evaluate antecedent effects. The model results indicated a reasonable correlation (r² = 0.67) when precipitation, daytime LST advanced 16 days, and a deseasoned moisture stress index were regressed against log‐transformed streamflow. The estimation model was applied to a validation period from January 2006 through March 2007, a period of 12 months of regional drought and base‐flow conditions followed by three months of above normal rainfall and a flood event. The model resulted in a Nash‐Sutcliffe estimation efficiency (E) of 0.45 for flow series (in log‐space) for the full 15‐month period, ?0.03 for the 2006 drought condition period, and 0.87 for the 2007 wet condition period. The overall model had a relative volume error of ?32%. The contribution of parameter uncertainties to model discrepancy was evaluated.     

Sensitivity and Uncertainty of Ground‐Water Discharge Estimates for Semiarid Shrublands1

Abstract: We proposed a step‐by‐step approach to quantify the sensitivity of ground‐water discharge by evapotranspiration (ET) to three categories of independent input variables. To illustrate the approach, we adopt a basic ground‐water discharge estimation model, in which the volume of ground water lost to ET was computed as the product of the ground‐water discharge rate and the associated area. The ground‐water discharge rate was assumed to equal the ET rate minus local precipitation. The objective of this study is to outline a step‐by‐step procedure to quantify the contributions from individual independent variable uncertainties to the uncertainty of total ground‐water discharge estimates; the independent variables include ET rates of individual ET units, areas associated with the ET units, and precipitation in each subbasin. The specific goal is to guide future characterization efforts by better targeting data collection for those variables most responsible for uncertainty in ground‐water discharge estimates. The influential independent variables to be included in the sensitivity analysis are first selected based on the physical characteristics and model structure. Both regression coefficients and standardized regression coefficients for the selected independent variables are calculated using the results from sampling‐based Monte Carlo simulations. Results illustrate that, while as many as 630 independent variables potentially contribute to the calculation of the total annual ground‐water discharge for the case study area, a selection of seven independent variables could be used to develop an accurate regression model, accounting for more than 96% of the total variance in ground‐water discharge. Results indicate that the variability of ET rate for moderately dense desert shrubland contributes to about 75% of the variance in the total ground‐water discharge estimates. These results point to a need to better quantify ET rates for moderately dense shrubland to reduce overall uncertainty in estimates of ground‐water discharge. While the approach proposed here uses a basic ground‐water discharge model taken from an earlier study, the procedure of quantifying uncertainty and sensitivity can be generalized to handle other types of environmental models involving large numbers of independent variables.     

Long-Term Relationship between Phosphorus Inputs and Wetland Phosphorus Concentrations in a Northern Everglades Marsh

Assessments of long-term relationships between changes innutrient inputs and wetland nutrient concentrations can becomplicated by fluctuations in other environmental factors aswell as by problems typical of long-term monitoring data.Consequently, statistical analysisof these types of data sets requirescareful consideration of environmental covariates, potentialbiases in the monitoring design, and irregularities caused bychanges in field sampling protocols. We evaluated therelationship between anthropogenic phosphorus (P) inputs andwater-column total P (TP) concentrations in a northernEverglades marsh by statistically analyzing available datacollected from several sampling programs over the past 20 years(1978–1997). Canal inputs of agricultural runoff contributemost of the P to the marsh and have produced a zone ofenrichment within the marsh during the past few decades.Regression analyses showed that both canal and marsh TPconcentrations increased during the 1980s and then decreased inthe 1990s. However, the statistical relationship between canal Pinputs and marsh TP, while significant, generally was weakexcept for marsh locations adjacent to the canal. Strongerrelationships existed between marsh TP and hydrologic parameterssuch as marsh water depth, which is controlled by changes inweather patterns and marsh management. In particular, dryconditions during the 1980s may have contributed to observedincreases in marsh P concentrations and the movement of a P`front' further into the marsh. Higher rainfall and water depthsand agricultural best management programs initiated during the1990s have been associated with reduced P concentrations incanal waters entering the marsh. While it is anticipated thatthis reduction eventually will result in lower marsh TPconcentrations, this effect is not yet evident, possibly due tointernal loading of P from enriched marsh soils. Our findingsillustrate some of the environmental factors that can complicateattempts to develop empirical relationships between P inputs andwetland P concentrations and to use such relationships to forecast changesin marsh concentrations based on past monitoring data alone.     

Implications of Conceptual Channel Representation on SWAT Streamflow and Sediment Modeling

Hydrologic modeling outputs are influenced by how a watershed system is represented. Channel routing is a typical example of the mathematical conceptualization of watershed landscape and processes in hydrologic modeling. We investigated the sensitivity of accuracy, equifinality, and uncertainty of Soil and Water Assessment Tool (SWAT) modeling to channel dimensions to demonstrate how a conceptual representation of a watershed system affects streamflow and sediment modeling. Results showed the amount of uncertainty and equifinality strongly responded to channel dimensions. On the other hand, the model performance did not significantly vary with the changes in the channel representation due to the degree of freedom allowed by the conceptual nature of hydrologic modeling in the parameter calibration. Such findings demonstrated good modeling performance statistics do not necessarily mean small output uncertainty, and partial improvements in the watershed representation may neither increase modeling accuracy nor reduce uncertainty. We also showed the equifinality and uncertainty of hydrologic modeling are case‐dependent rather than specific to models or regions, suggesting great caution should be used when attempting to transfer uncertainty analysis results to other modeling studies, especially for ungauged watersheds. Editor's note: This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

Defining the Diurnal Pattern of Snowmelt Using a Beta Distribution Function

Snow is an important component of the hydrologic cycle for many regions worldwide. In addition to vital water resources, snowmelt can be important for forest ecosystem dynamics and flood risk. However, standard design events in the United States lack a design snowmelt event, including only precipitation events, though snowmelt has been shown to be larger than rainfall. In this article, we present a method using hourly snow water equivalent data to develop and test a function for representing the diurnal pattern of snowmelt. A two‐parameter beta distribution function is modified for the purposes of this study and found to fit the pattern of snowmelt well with a root mean squared error of 0.008. Soil moisture sensors were additionally utilized to assess the timing of the snowmelt water outflow from the base of the snowpack that supports the shape of the function, but suggests that the timing of losses recorded on snow pillows lag as much as 3 h. Further testing of the function showed the shape of the function to be accurate. The methods developed and tested in this paper can be applied for design purposes comparing snowmelt and rainfall events or to improve hydrological models investigating processes such as streamflow or groundwater recharge.     

Does Including Soil Moisture Observations Improve Operational Streamflow Forecasts in Snow‐Dominated Watersheds?

Changing climate and growing water demand are increasing the need for robust streamflow forecasts. Historically, operational streamflow forecasts made by the Natural Resources Conservation Service have relied on precipitation and snow water equivalent observations from Snow Telemetry (SNOTEL) sites. We investigate whether also including SNOTEL soil moisture observations improve April‐July streamflow volume forecast accuracy at 0, 1, 2, and 3‐month lead times at 12 watersheds in Utah and California. We found statistically significant improvement in 0 and 3‐month lead time accuracy in 8 of 12 watersheds and 10 of 12 watersheds for 1 and 2‐month lead times. Surprisingly, these improvements were insensitive to soil moisture metrics derived from soil physical properties. Forecasts were made with volumetric water content (VWC) averaged from October 1 to the forecast date. By including VWC at the 0‐month lead time the forecasts explained 7.3% more variability and increased the streamflow volume accuracy by 8.4% on average compared to standard forecasts that already explained an average 77% of the variability. At 1 to 3‐month lead times, the inclusion of soil moisture explained 12.3‐26.3% more variability than the standard forecast on average. Our findings indicate including soil moisture observations increased statistical streamflow forecast accuracy and thus, could potentially improve water supply reliability in regions affected by changing snowpacks.     

湿地生态系统基质重金属积累与酶活性的研究现状

湿地生态系统具有净化污水的功能,因其具有高效低耗等优点,在污水处理方面极具开发应用前景,而基质作为湿地生态系统重要组成部分,已成为众多学者的研究热点。本文综合分析了湿地生态系统基质中重金属积累和酶活性的时空分布及影响因素的研究现状,并对相关研究提出了新的认识与展望,以期为湿地生态系统基质去除废水中重金属的深入研究和应用提供综合分析资料。