Site selection for runoff harvesting at large scales is a very complex task. It requires inclusion and spatial analysis of a multitude of accurately measured parameters in a time-efficient manner. Compared with direct measurements of runoff, which is time consuming and costly, a combination of a Geographic Information System (GIS) and multi-criteria techniques have proven feasible to address this challenge. Although the accuracy of this new approach is lower than the direct method, conducting in-situ measurements over large scales is not feasible due to its financial issues, a lack of sufficient human resources, and time limitations. To achieve this purpose, climatic, topographic, and soil parameters were used to estimate a runoff coefficient and volume for a single event with the 33%-exceedance probability of maximum daily rainfall in the Kavir National Park of Iran. The main challenges ahead of this research have been a) the large area of the park and the inability to directly evaluate site suitability for runoff harvesting, b) the need for a quick and reliable site evaluation to implement water harvesting measures to address water scarcity, and c) the lack of discharge volume data from water streams (as there are no permanent water streams in the site) and the necessity of reliably estimating runoff in different parts of the park to design water harvesting structures which have been addressed by using GIS and a rainfall-runoff model (Soil Conservation Service Curve Number (SCS-CN)). Site suitability was evaluated for the natural territory of two important wildlife species of the park, namely Gazella dorcas and Ovis orientalis, as the main important food sources of an endangered species named Acinonyx jubatus, commonly known as Persian Cheetah. Saving Persian Cheetah from extinction is currently the top priority for the park managers, which is the main factor behind the species chosen for this research. The Analytic Hierarchical Process (AHP) and fuzzy membership functions were employed to assign weights and standardized thematic layers, respectively. The layers were then integrated using the weighted linear combination method (WLC) to obtain the final suitability map. Accordingly, 38% of the area (846 km2) is suitable or highly suitable for runoff harvesting, while 62% (2623 km2) has a very low potential for this purpose. Afterward, 11 suitable locations were identified to collect runoff. The results indicated that suitable catchments are mainly located on the southern slopes of the Mount Siahkouh as the only major elevation in the area. The storage capacity of the earth embankment in each catchment was estimated based on the upstream area of the catchment and runoff volume. Based on the population of the intended wildlife species and their average water requirement, there is a need for 6500 m3 of drinking water annually. In the best-case scenario and under the circumstance of receiving five rainstorm events a year, only 257 m3 is collectible from all runoff harvesting structures, which is only 4% of the total water demand.
Estimating CPT Parameters at Unsampled Locations Based on Kriging Interpolation Method
