SENSITIVITY OF A PRAIRIE WETLAND TO INCREASED TEMPERATURE AND SEASONAL PRECIPITATION CHANGES1

ABSTRACT: We assessed the potential effects of increased temperature and changes in amount and seasonal timing of precipitation on the hydrology and vegetation of a semi-permanent prairie wetland in North Dakota using a spatially-defined, rule-based simulation model. Simulations were run with increased temperatures of 2°C combined with a 10 percent increase or decrease in total growing season precipitation. Changes in precipitation were applied either evenly across all months or to individual seasons (spring, summer, or fall). The response of semi-permanent wetland P1 was relatively similar under most of the seasonal scenarios. A 10 percent increase in total growing season precipitation applied to summer months only, to fall months only, and over all months produced lower water levels compared to those resulting from the current climate due to increased evapotranspiration. Wetland hydrology was most affected by changes in spring precipitation and runoff. Vegetation response was relatively consistent across scenarios. Seven of the eight seasonal scenarios produced drier conditions with no open water and greater vegetation cover compared to those resulting from the current climate. Only when spring precipitation increased did the wetland maintain an extensive open water area (49 percent). Potential changes in climate that affect spring runoff, such as changes to spring precipitation and snow melt, may have the greatest impact on prairie wetland hydrology and vegetation. In addition, relatively small changes in water level during dry years may affect the period of time the wetland contains open water. Emergent vegetation, once it is established, can survive under drier conditions due to its ability to persist in shallow water with fluctuating levels. The model's sensitivity to changes in temperature and seasonal precipitation patterns accentuates the need for accurate regional climate change projections from general circulation models.     

A VOLUME BALANCE SOLUTION FOR WATER FLOW OVER FLAT SOIL SURFACES1

ABSTRACT: This paper presents the development of a mathematical model to compute the advance of water flowing over flat soil surfaces. The solution is of interest to the design and management of irrigation systems, and the model can also be applied to overland flow problems. The hydraulics of water flow during the advance phase is simulated by the Lewis-Milne integral equation. The general solution to this equation is obtained by using the Laplace transform theory. A particular solution was developed, based on series expansions, that uses the modified Kostiakov equation to predict infiltration. The solution is given by a double infinite series that has terms of alternate sign. Results from this model show satisfactory agreement when compared with field data collected by the author.     

APPLICATION OF A LOW-FLOW ASSESSMENT MODEL FOR THE MONONGAHELA RIVER BASIN1

ABSTRACT: The application of a low-flow assessment model is illustrated for the Monogahela River Basin. The model simulates the impact of reservoir operating rules and consumptive use limitation policies on low-flow frequency at downstream locations in the basin. Policies are evaluated using an observed flow sequence and synthetic flow inputs. The paper reviews the historical development of flow management on the Monogahela to provide background for the current study.     

ASSESSMENT OF REMOTE SENSING INPUT TO HYDROLOGIC MODELS1

Remotely sensed variables such as land cover type and snow-cover extent can currently be used directly and effectively in a few specific hydrologic models. Regression models can also be developed using physiographic and snow-cover data to permit estimation of discharge characteristics over extended periods such as a season or year. Most models, however, are not of an appropriate design to readily accept as input the various types of remote sensing parameters that can be obtained now or in the future. Because this new technology has the potential for producing hydrologic data that has significant information content on an areal basis, both inexpensively and repetitively, effort should be devoted now to either modifying existing models or developing new models that can use these data. Minor modifications would at least allow the remote sensing data to be used in an ancillary way to update the model state variables, whereas major structural modifications or new models would permit direct input of the data through remote sensing compatible algorithms. Although current remote sensing inputs to hydrologic models employ only visible and near infrared data, model modification or development should accommodate microwave and thermal infrared data that will be more widely available in the future.     

UPLAND SOIL EROSION SIMULATION FOR AGRICULTURAL WATERSHEDS1

ABSTRACT: A soil erosion simulation model that considered the physical conditions of agricultural watersheds and that interfaced with the modified USDAHL-74 watershed hydrology model was developed. The erosion model simulates the detachment and transport of soil particles caused by raindrop impact and overland flow from rill and interrill areas. The model considers temporal and spatial variation of plant residue, crop canopy cover, snow cover, and the moisture content of surface soil as modifying factors of the erosive forces of raindrop impact and overland flow. The hydrology model simulates overland flow and some of the physical parameters that are used in the erosion model. The simulation is executed in the time interval determined by the rainfall rate or snowmelt rate. The erosion model compares the transport capacity of the overland flow and the sediment loaded in the overland flow to determine the fate account for the free soil particles that have already been detached and are readily available to be transported by the overland flow. The model was tested with data from two small agricultural watersheds in the Palouse region of the Pacific Northwest dryland. The model was calibrated by trial-and-error to determine the coefficients of the model.     

OPTIMAL GROUND WATER MANAGEMENT IN TWO-AQUIFER SYSTEMS1

ABSTRACT; This paper presents a numerical model for the prediction of optimal ground water withdrawal from a two-aquifer system by observing a set of constraints determined by the ecological conditions of the ground water basin. The aquifer system consists of an upper unconfined and a lower confined aquifer with a leaky stratum between them. It is assumed that water is withdrawn from the confined aquifer only, but the unconfined aquifer will also be affected due to the leakiness of the layer separating the upper and lower aquifers. Simulation and linear programming are employed for developing a computer model for the optimal management of such systems, with the objectives of determining withdrawal rates for predetermined ground water levels.     

A MULTIOBJECTIVE,DISCRETE SYSTEM REPRESENTATION OF RANGELAND WATERSHEDS1

ABSTRACT: Resource utilization as practiced by humans is identified as the main cause of the degradation of rangeland watersheds, a process referred to as desertification. This paper introduces a multi-objective decision making methodology for the selection of a plan which if implemented should limit the desertification process. The evaluation objectives are measured by quantitative and qualitative criteria. The quantitative criteria provide the performance level for production and sediment yield, while the qualitative criteria give such information as public acceptance of a particular alternative or worth of an appropriate wildlife habitat. A system model is applied to describe the dynamics of a range site in response to climatic and human inputs. As such it provides the information required by the quantitative criteria as well as a range condition index that identifies the productivity of a given range site. A multiobjective selection procedure is presented that will lead to the appropriate technique from an available set, in this case ESAP, Environmental Sensitivity Analysis Package. Four individuals with diverse backgrounds in natural resource management participated as decision makers and decided on their preferred alternatives. Finally, ranked alternatives in agreement with all of the decision makers were obtained.     

FORECAST UNCERTAINTY IN WATER SUPPLY RESERVOIR OPERATION1

ABSTRACT: This research investigates the benefits of forecasting in water supply systems. Questions relating operational losses to forecast period and accuracy are addressed. Some simple available forecasting techniques are assessed for their accuracy and applicability. These issues are addressed through the use of a simulation model of the Cedar and South Fork Tolt Rivers, where the system is modeled as a single purpose reservoir supplying municipal and industrial water to the Seattle metropolitan area. The following conclusions were made for this system: (1) reservoir operation deteriorates markedly with the loss of forecast accuracy; (2) the optimal length of forecasting period is five months; (3) reservoir operation may be improved by as much as 88 percent if perfect predictive abilities are available; (4) the mean of the historic data is not recommended to predict future flows because Markov methods are always superior; and (5) lag-one autoregressive Markov schemes exhibit about a 9 percent improvement in operation over no forecasting.     

SENSITIVITY ANALYSIS OF A DRAINAGE SIMULATION MODEL1

A sensitivity analysis of a computer model, simulating major water and nitrogen processes of a soil-water-plant-climatic system on an annual basis, was conducted to determine how the model reacts to the variations in selected hydrologic and nitrogen parameters. Two major output variables (namely, total subsurface drain volume and cumulative nitrate loss with subsurface drain water) were selected for the sensitivity analysis. Model sensitivity analysis shows that the model is most sensitive to hydrologic parameters. The model is very sensitive to variations in the initial water content in the soil profile.     

Patchy distribution fields: sampling distance unit of a zigzag survey and reconstruction adequacy

A mathematical model was used to examine the effects of choosingvarious units of sampling distance of a zigzag survey on the adequacy of reconstructing patchy distribution fields. The modelsimulates fish or plankton patches (or gaps) of different shapesand spatial orientations, and an acoustic survey by zigzag or parallel transects along which a unit of sampling distance is set. Adequacy of the reconstructed fields to those originally generated is evaluated by calculating their correlations (r). A priori information on the autocorrelation radii for the field in the directions of the survey (R_s) and perpendiculardirection (R_p) allows optimisation of the survey design andthe algorithm of data analysis. A field can be reconstructed properly (r² > 0.70) if the distance between transects D < (1.0–1.5)R_s and the unit of sampling distance d < (1.0–1.5)R_p. A posteriori determination of patchorientation allows reconstruction of the best field attainable onthe basis of the survey data. In cases of field movement, if thedimension of patches in the direction of movement exceeds that ofa surveyed area, a survey in the opposite direction gives bestresults; in contrast, if the dimension of moving patches is smaller than that of a surveyed area, it is reasonable to carryout a survey in the same direction. The criterion remains validwhen a survey is carried out by zigzag transects and a unit ofsampling distance is set along them. The results obtained indicate that, for a fixed transect spacing and a given number of sampling points on each full transect, zigzag pattern allowsless adequate reconstruction of an original distribution field (in cases of both immovable and movable fields) than corresponding parallel pattern.